From 974339bf61f0e2d3ca1a13c12d6053067464cb54 Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Mon, 4 May 2026 10:21:23 -0600 Subject: [PATCH 01/20] Passing R CMD CHECK and BiocCheck --- vignettes/get_started.Rmd | 6 ------ 1 file changed, 6 deletions(-) diff --git a/vignettes/get_started.Rmd b/vignettes/get_started.Rmd index dc39141..44efa59 100644 --- a/vignettes/get_started.Rmd +++ b/vignettes/get_started.Rmd @@ -324,8 +324,6 @@ wb_fullRes <- CLAMPfull( wb_summary_df <- as.data.frame(wb_fullRes$summary) %>% dplyr::filter(FDR < 0.05 & AUC > 0.7) %>% dplyr::arrange(FDR) %>% - dplyr::rename(LV = "LV_index") %>% - dplyr::mutate(LV = paste0("LV", LV)) %>% dplyr::select(LV, pathway, FDR, AUC) datatable( @@ -456,8 +454,6 @@ alz_fullRes <- CLAMPfull( alz_summary_df <- as.data.frame(alz_fullRes$summary) %>% filter(FDR < 0.05 & AUC > 0.7) %>% dplyr::arrange(FDR) %>% - dplyr::rename(LV = "LV_index") %>% - dplyr::mutate(LV = paste0("LV", LV)) %>% dplyr::select(LV, pathway, FDR, AUC) datatable( @@ -581,8 +577,6 @@ islet_fullRes <- CLAMPfull( islet_summary_df <- as.data.frame(islet_fullRes$summary) %>% filter(FDR < 0.05 & AUC > 0.7) %>% dplyr::arrange(FDR) %>% - dplyr::rename(LV = "LV_index") %>% - dplyr::mutate(LV = paste0("LV", LV)) %>% dplyr::select(LV, pathway, FDR, AUC) datatable( From 418f37905bd0ab7484553fe02397ac2ba5087278 Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Mon, 4 May 2026 11:03:33 -0600 Subject: [PATCH 02/20] Adding CI workflow for R CMD and BiocCheck --- .github/workflows/BiocCheck.yaml | 38 +++++++++++++++++++++ .github/workflows/R-CMD-check.yaml | 54 ++++++++++++++++++++++++++++++ DESCRIPTION | 6 ++-- README.md | 3 +- 4 files changed, 97 insertions(+), 4 deletions(-) create mode 100644 .github/workflows/BiocCheck.yaml create mode 100644 .github/workflows/R-CMD-check.yaml diff --git a/.github/workflows/BiocCheck.yaml b/.github/workflows/BiocCheck.yaml new file mode 100644 index 0000000..970f42f --- /dev/null +++ b/.github/workflows/BiocCheck.yaml @@ -0,0 +1,38 @@ +on: + push: + branches: [main, devel] + pull_request: + +name: BiocCheck.yaml + +permissions: read-all + +jobs: + BiocCheck: + runs-on: ubuntu-latest + name: BiocCheck + + steps: + - name: Checkout Repo + uses: actions/checkout@v3 + + - name: Setup Pandoc + uses: r-lib/actions/setup-pandoc@v2 + + - name: Setup R + uses: r-lib/actions/setup-r@v2 + with: + r-version: release + http-user-agent: release + use-public-rspm: true + + - name: Install Deps + uses: r-lib/actions/setup-r-dependencies@v2 + with: + cache: true + # Remove pivlab/CLAMPData once CLAMPData is on Bioconductor; + # it will then be picked up automatically from DESCRIPTION. + extra-packages: pivlab/CLAMPData + + - name: Run BiocCheck + uses: insightsengineering/bioc-check-action@v1 diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml new file mode 100644 index 0000000..50051ef --- /dev/null +++ b/.github/workflows/R-CMD-check.yaml @@ -0,0 +1,54 @@ +# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples +# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help +on: + push: + branches: [main, devel] + pull_request: + +name: R-CMD-check.yaml + +permissions: read-all + +jobs: + R-CMD-check: + runs-on: ${{ matrix.config.os }} + + name: ${{ matrix.config.os }} (${{ matrix.config.r }}) + + strategy: + fail-fast: false + matrix: + config: + - {os: macos-latest, r: 'release'} + - {os: windows-latest, r: 'release'} + - {os: ubuntu-latest, r: 'devel', http-user-agent: 'release'} + - {os: ubuntu-latest, r: 'release'} + - {os: ubuntu-latest, r: 'oldrel-1'} + + env: + GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} + R_KEEP_PKG_SOURCE: yes + + steps: + - uses: actions/checkout@v6 + + - uses: r-lib/actions/setup-pandoc@v2 + + - uses: r-lib/actions/setup-r@v2 + with: + r-version: ${{ matrix.config.r }} + http-user-agent: ${{ matrix.config.http-user-agent }} + + - uses: r-lib/actions/setup-r-dependencies@v2 + with: + extra-packages: | + any::rcmdcheck + pivlab/CLAMPData + # Remove pivlab/CLAMPData once CLAMPData is on Bioconductor; + # it will then be picked up automatically from DESCRIPTION. + needs: check + + - uses: r-lib/actions/check-r-package@v2 + with: + upload-snapshots: true + build_args: 'c("--no-manual","--compact-vignettes=gs+qpdf")' diff --git a/DESCRIPTION b/DESCRIPTION index d76fcb1..ee5628a 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -20,10 +20,10 @@ Description: CLAMP performs prior-informed latent variable decomposition of to uncover biologically meaningful patterns that connect genes, pathways, and complex traits in transcriptomics studies. License: GPL-3 -URL: https://mchikina.github.io/CLAMP/, https://github.com/mchikina/CLAMP -BugReports: https://github.com/mchikina/CLAMP/issues +URL: https://chikinalab.github.io/CLAMP/, https://github.com/chikinalab/CLAMP +BugReports: https://github.com/chikinalab/CLAMP/issues/ Depends: - R (>= 4.4.0), + R (>= 4.6.0), Imports: bigstatsr, circlize, diff --git a/README.md b/README.md index 382b184..9550d9b 100644 --- a/README.md +++ b/README.md @@ -3,7 +3,8 @@ [![GitHub issues](https://img.shields.io/github/issues/mchikina/CLAMP)](https://github.com/mchikina/mchikina/CLAMP) [![Lifecycle: stable](https://img.shields.io/badge/lifecycle-stable-green.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable) -[![R-CMD-check-bioc](https://github.com/mchikina/CLAMP/workflows/R-CMD-check-bioc/badge.svg)](https://github.com/mchikina/CLAMP/actions) +[![BiocCheck](https://github.com/mchikina/CLAMP/actions/workflows/BiocCheck.yaml/badge.svg)](https://github.com/chikinalab/CLAMP/actions/workflows/BiocCheck.yaml) +[![R-CMD-check](https://github.com/chikinalab/CLAMP/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/chikinalab/CLAMP/actions/workflows/R-CMD-check.yaml) ## Bioconductor release status From 045deab37aeb9687afc5ef867361be9d35d7f0c5 Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Mon, 4 May 2026 11:21:06 -0600 Subject: [PATCH 03/20] Mac xquartz for workflow --- .github/workflows/R-CMD-check.yaml | 5 ++++- DESCRIPTION | 1 + 2 files changed, 5 insertions(+), 1 deletion(-) diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml index 50051ef..944e874 100644 --- a/.github/workflows/R-CMD-check.yaml +++ b/.github/workflows/R-CMD-check.yaml @@ -23,7 +23,6 @@ jobs: - {os: windows-latest, r: 'release'} - {os: ubuntu-latest, r: 'devel', http-user-agent: 'release'} - {os: ubuntu-latest, r: 'release'} - - {os: ubuntu-latest, r: 'oldrel-1'} env: GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} @@ -32,6 +31,10 @@ jobs: steps: - uses: actions/checkout@v6 + - name: Install XQuartz (macOS) + if: runner.os == 'macOS' + run: brew install --cask xquartz + - uses: r-lib/actions/setup-pandoc@v2 - uses: r-lib/actions/setup-r@v2 diff --git a/DESCRIPTION b/DESCRIPTION index ee5628a..b3e0a2c 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -46,6 +46,7 @@ Imports: Suggests: AnnotationDbi, BiocStyle, + Cairo, CLAMPData, data.table, DiagrammeR, From 57406430ac16a845f49922a52c5f0171cda57f2a Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Mon, 4 May 2026 11:43:40 -0600 Subject: [PATCH 04/20] Makevars files --- src/Makevars | 1 + src/Makevars.win | 1 + 2 files changed, 2 insertions(+) create mode 100644 src/Makevars create mode 100644 src/Makevars.win diff --git a/src/Makevars b/src/Makevars new file mode 100644 index 0000000..22ebc63 --- /dev/null +++ b/src/Makevars @@ -0,0 +1 @@ +PKG_LIBS = $(LAPACK_LIBS) $(BLAS_LIBS) $(FLIBS) diff --git a/src/Makevars.win b/src/Makevars.win new file mode 100644 index 0000000..22ebc63 --- /dev/null +++ b/src/Makevars.win @@ -0,0 +1 @@ +PKG_LIBS = $(LAPACK_LIBS) $(BLAS_LIBS) $(FLIBS) From 75999b5ab1cb12a9af556bf2fd3301a5c1f1fc9b Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Mon, 4 May 2026 13:08:24 -0600 Subject: [PATCH 05/20] Removing external network calls --- .github/workflows/BiocCheck.yaml | 2 +- .github/workflows/R-CMD-check.yaml | 1 + DESCRIPTION | 1 - R/utils.R | 4 +- inst/extdata/CellMarker_2024.rds | Bin 0 -> 190502 bytes .../Diabetes_Perturbations_GEO_2022.rds | Bin 0 -> 395987 bytes inst/extdata/GO_Biological_Process_2025.rds | Bin 0 -> 600815 bytes inst/extdata/GTEx_Tissues_V8_2023.rds | Bin 0 -> 171429 bytes inst/extdata/KEGG_2021_Human.rds | Bin 0 -> 81578 bytes inst/extdata/MSigDB_Hallmark_2020.rds | Bin 0 -> 26869 bytes vignettes/comparing_clampbase_clampfull.Rmd | 14 ++++++- vignettes/get_started.Rmd | 36 ++++++++++++++++-- 12 files changed, 48 insertions(+), 10 deletions(-) create mode 100644 inst/extdata/CellMarker_2024.rds create mode 100644 inst/extdata/Diabetes_Perturbations_GEO_2022.rds create mode 100644 inst/extdata/GO_Biological_Process_2025.rds create mode 100644 inst/extdata/GTEx_Tissues_V8_2023.rds create mode 100644 inst/extdata/KEGG_2021_Human.rds create mode 100644 inst/extdata/MSigDB_Hallmark_2020.rds diff --git a/.github/workflows/BiocCheck.yaml b/.github/workflows/BiocCheck.yaml index 970f42f..80bca37 100644 --- a/.github/workflows/BiocCheck.yaml +++ b/.github/workflows/BiocCheck.yaml @@ -29,7 +29,7 @@ jobs: - name: Install Deps uses: r-lib/actions/setup-r-dependencies@v2 with: - cache: true + cache: always # Remove pivlab/CLAMPData once CLAMPData is on Bioconductor; # it will then be picked up automatically from DESCRIPTION. extra-packages: pivlab/CLAMPData diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml index 944e874..c612919 100644 --- a/.github/workflows/R-CMD-check.yaml +++ b/.github/workflows/R-CMD-check.yaml @@ -44,6 +44,7 @@ jobs: - uses: r-lib/actions/setup-r-dependencies@v2 with: + cache: always extra-packages: | any::rcmdcheck pivlab/CLAMPData diff --git a/DESCRIPTION b/DESCRIPTION index b3e0a2c..ee5628a 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -46,7 +46,6 @@ Imports: Suggests: AnnotationDbi, BiocStyle, - Cairo, CLAMPData, data.table, DiagrammeR, diff --git a/R/utils.R b/R/utils.R index 0b668f7..64a6f4a 100644 --- a/R/utils.R +++ b/R/utils.R @@ -229,8 +229,8 @@ read_gmt <- function(filename) { } gmt <- list() - lines <- readLines(filename, encoding = "UTF-8") - lines <- iconv(lines, from = "UTF-8", to = "UTF-8", sub = "") + lines <- readLines(filename, warn = FALSE) + lines <- iconv(lines, to = "UTF-8", sub = "") for (line in lines) { # Bioc style: avoid complex nested regex if possible for clarity diff --git a/inst/extdata/CellMarker_2024.rds b/inst/extdata/CellMarker_2024.rds new file mode 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zulN`KF+9Cue&pX&^|#l5^Um!4Cd9=zPmcdt+L~|rk3W9+^waqyiuJe6H}?CF-~Ia^ zzkK@q%Xt+yKYsb~moId(?U!G^`~JxX{+H(WpML!EhmW5>;-&vO`}voj!r%Ni{ruyX z&p&_sCj0Qy55GPh{;!@MuKf>vJo?Yg=ilq2=TmQfoqf+gcRzjk6Xnti(gQD_~Rd+yx=d*kDtE#@WVIn{{HiK^ud4e_~+s8 zfBL%*-<@ClFUpU<|HH@czx?6p<+fk`_~Q>B|M*d^>tF9b|J|1#e*f|J-<(f=_Rass zRh!-4_$B9W{^-s0Z=QVQKMQ}ht0#Z|^K6}eGk*B#4h95tE_vz!$-?$IIeE+|E zI8V1f|M6-w`_o_S?=biFKR)-@^s`Lx&wuzdn|Ocuy}zYTf5V^KFCYH!_v)^B+F_>=%v4KmC>Y;fF7O`02yn{o>E^-+kn1`Ir8e z{}k@X?D^RBW}wwde(C&x{Mf&8A3pm>>BG<8B-8ry@rNJ6I{5$mzi Date: Mon, 4 May 2026 14:52:03 -0600 Subject: [PATCH 06/20] Bioccheck on tarball --- .github/workflows/BiocCheck.yaml | 12 ++++++++++-- 1 file changed, 10 insertions(+), 2 deletions(-) diff --git a/.github/workflows/BiocCheck.yaml b/.github/workflows/BiocCheck.yaml index 80bca37..f37b239 100644 --- a/.github/workflows/BiocCheck.yaml +++ b/.github/workflows/BiocCheck.yaml @@ -32,7 +32,15 @@ jobs: cache: always # Remove pivlab/CLAMPData once CLAMPData is on Bioconductor; # it will then be picked up automatically from DESCRIPTION. - extra-packages: pivlab/CLAMPData + extra-packages: | + bioc::BiocCheck + pivlab/CLAMPData + + - name: Build tarball + run: R CMD build --no-manual . - name: Run BiocCheck - uses: insightsengineering/bioc-check-action@v1 + run: | + tarball <- list.files(pattern = "^CLAMP_.*\\.tar\\.gz$")[1] + BiocCheck::BiocCheck(tarball, `quit-with-status` = TRUE) + shell: Rscript {0} From a89bc2b5dc3022604d6b4915cd36177555ddec21 Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Tue, 5 May 2026 13:19:53 -0600 Subject: [PATCH 07/20] applying 4 space indent and start of 80 char limit --- R/celltypeTargets.R | 5 +- R/majorCellTypes.R | 3 +- R/panDB.R | 14 +- R/plots.R | 1263 +++++----- R/solvers.R | 2508 ++++++++++--------- R/utils.R | 794 +++--- R/zzz.R | 2 +- tests/testthat/test-CLAMPbase.R | 46 +- tests/testthat/test-CLAMPfull.R | 140 +- tests/testthat/test-compute_svd.R | 58 +- tests/testthat/test-getGMT.R | 5 +- tests/testthat/test-gmtListToSparseMat.R | 2 +- tests/testthat/test-plots.R | 88 +- tests/testthat/test-preprocessCLAMP.R | 5 +- tests/testthat/test-select_clamp_k.R | 175 +- tests/testthat/test-select_svd_k.R | 4 +- vignettes/comparing_clampbase_clampfull.Rmd | 114 +- vignettes/get_started.Rmd | 155 +- 18 files changed, 2786 insertions(+), 2595 deletions(-) diff --git a/R/celltypeTargets.R b/R/celltypeTargets.R index f9b1dfa..b9210cc 100644 --- a/R/celltypeTargets.R +++ b/R/celltypeTargets.R @@ -1,8 +1,9 @@ #' Cell-type deconvolution matrix #' #' A numeric matrix of estimated cell-type proportions for whole-blood samples. -#' Rows correspond to sample IDs and columns to major immune cell types. This dataset -#' can be used for validation or illustrative purposes in CLAMP analyses. +#' Rows correspond to sample IDs and columns to major immune cell types. +#' This dataset can be used for validation or illustrative purposes in +#' CLAMP analyses. #' #' @format A numeric matrix with samples as rows and cell types as columns. #' Row names are sample identifiers. diff --git a/R/majorCellTypes.R b/R/majorCellTypes.R index a531401..74a1ed8 100644 --- a/R/majorCellTypes.R +++ b/R/majorCellTypes.R @@ -5,7 +5,8 @@ #' in the reference expression matrix. #' #' @format A factor (or character) vector of length N, -#' where each element corresponds to a sample and indicates its major cell type. +#' where each element corresponds to a sample and indicates its major +#' cell type. #' #' @usage data(majorCellTypes) #' diff --git a/R/panDB.R b/R/panDB.R index 6c26faa..b722f6a 100644 --- a/R/panDB.R +++ b/R/panDB.R @@ -1,12 +1,13 @@ #' panDB gene-set database #' -#' A list of curated pathway and biological process gene sets used as prior knowledge -#' for CLAMP and other latent-variable models. +#' A list of curated pathway and biological process gene sets used as prior +#' knowledge for CLAMP and other latent-variable models. #' -#' Each element corresponds to a functional collection (e.g., KEGG, Reactome, GO), -#' where each entry contains a character vector of gene symbols. +#' Each element corresponds to a functional collection (e.g., KEGG, Reactome, +#' GO), where each entry contains a character vector of gene symbols. #' -#' @format A named list of length M, where each element is a gene-set collection. +#' @format A named list of length M, where each element is a gene-set +#' collection. #' @usage data(panDB) #' @keywords datasets #' @docType data @@ -14,5 +15,6 @@ #' @aliases panDB #' @examples #' data(panDB) -#' @return A list of gene-set collections used as priors for pathway-informed modeling. +#' @return A list of gene-set collections used as priors for pathway-informed +#' modeling. "panDB" diff --git a/R/plots.R b/R/plots.R index 62d810e..34fc658 100644 --- a/R/plots.R +++ b/R/plots.R @@ -5,149 +5,164 @@ #' Produces a paired comparison plot and summary statistics. #' #' @param res1, res2 Result objects or matrices containing factor loadings. -#' If a list, must contain element `B`; if of class `"rsvd"`, `t(res$v)` is used. +#' If a list, must contain element `B`; if of class `"rsvd"`, +#' `t(res$v)` is used. #' @param target Numeric matrix of target variables (samples × targets). #' @param method Character, one of `"p"`, `"s"`, `"a"`, or `"t"`, indicating #' Pearson, Spearman, AUC, or t-statistic comparison. #' @param xlab, ylab Labels for x and y axes in the plot. -#' @param stat.method Statistical test to compare correlations (`"t"` or `"wilcox"`). +#' @param stat.method Statistical test to compare correlations +#' (`"t"` or `"wilcox"`). #' @param oneToOne Logical, whether to apply one-to-one masking of associations. #' @param res2 Second result object or matrix to compare against. #' @param ylab Label for y-axis (used in plot). #' @return A list with: #' \describe{ #' \item{plot}{A ggplot object comparing maximal correlations across targets.} -#' \item{df}{A data.frame with per-target metrics and (if available) top genes.} +#' \item{df}{A data.frame with per-target metrics and (if available) +#' top genes.} #' } #' #' @importFrom matrixStats colRanks -#' @importFrom ggplot2 ggplot aes geom_point geom_abline labs annotate theme_minimal +#' @importFrom ggplot2 ggplot aes geom_point geom_abline labs annotate +#' @importFrom ggplot2 theme_minimal #' @export #' @examples #' set.seed(123) #' # Simulated example with 50 genes × 20 samples #' Y <- matrix(rnorm(50 * 20), nrow = 50, ncol = 20) -#' +#' #' # Run two CLAMP-like decompositions (here using simple SVD) #' svd1 <- rsvd::rsvd(Y, k = 5) #' svd2 <- rsvd::rsvd(Y + matrix(rnorm(50 * 20, 0, 0.1), 50, 20), k = 5) -#' +#' #' # Define a target variable (e.g., binary or continuous trait) #' target <- matrix(rnorm(20 * 3), ncol = 3) #' colnames(target) <- c("Trait1", "Trait2", "Trait3") #' #' # Compare the two sets of embeddings -#' res <- compareBs(svd1, svd2, target, method = "p", xlab = "SVD1", ylab = "SVD2") +#' res <- compareBs(svd1, svd2, target, +#' method = "p", xlab = "SVD1", ylab = "SVD2" +#' ) compareBs <- function(res1, res2, target, method = "p", xlab = "1", ylab = "2", stat.method = "t", oneToOne = TRUE) { + extract_B <- function(res) { + if (is.list(res) & !is.null(res$B)) { + return(as.matrix(res$B)) + } else if (inherits(res, "rsvd")) { + return(t(res$v)) + } else { + return(as.matrix(res)) + } + } + + B1 <- extract_B(res1) + B2 <- extract_B(res2) + show(dim(B1)) + show(dim(B2)) + target <- as.matrix(target) + noNA <- !apply(target, 1, function(x) any(is.na(x))) + B1 <- B1[, noNA, drop = FALSE] + B2 <- B2[, noNA, drop = FALSE] + target <- target[noNA, , drop = FALSE] + + # Only correlation-based comparison supported + if (method %in% c("s", "p")) { + mat1 <- cor(t(B1), target, method = method) + mat2 <- cor(t(B2), target, method = method) + } + + # if (method %in% c("s", "p")) { + # mat1 <- cor(t(B1), target, method = method) + # mat2 <- cor(t(B2), target, method = method) + # } else if (method == "a") { + # mat1 <- allAgainstAllAUCs(t(B1), target) + # mat2 <- allAgainstAllAUCs(t(B2), target) + # } else if (method == "t") { + # mat1 <- allAgainstAllTstats(t(B1), target) + # mat2 <- allAgainstAllTstats(t(B2), target) + # } + + if (inherits(res1, "rsvd")) { + mat1 <- abs(mat1) + } + if (inherits(res2, "rsvd")) { + mat1 <- abs(mat1) + } + mat1[is.na(mat1)] <- 0 + mat2[is.na(mat2)] <- 0 + if (oneToOne) { + mat1 <- oneToOneMask(mat1) + mat2 <- oneToOneMask(mat2) + } - extract_B <- function(res) { - if (is.list(res) & !is.null(res$B)) { - return(as.matrix(res$B)) - } else if (inherits(res, "rsvd")) { + cor1 <- apply(mat1, 2, max) + cor2 <- apply(mat2, 2, max) + cor1[cor1 < 0.01] <- NA + cor2[cor2 < 0.01] <- NA + idx1 <- apply(mat1, 2, which.max) + idx2 <- apply(mat2, 2, which.max) + Labels <- colnames(target) + + df <- data.frame( + Cor1 = cor1, Cor2 = cor2, + BestIdxRes1 = idx1, BestIdxRes2 = idx2, + Label = Labels + ) + df$corMean <- (df$Cor1 + df$Cor2) / 2 - return(t(res$v)) + pval <- if (stat.method == "t") { + t.test(df$Cor2, df$Cor1, paired = TRUE, alternative = "greater")$p.value } else { - return(as.matrix(res)) - } - } - - B1 <- extract_B(res1) - B2 <- extract_B(res2) - show(dim(B1)) - show(dim(B2)) - target <- as.matrix(target) - noNA <- !apply(target, 1, function(x) any(is.na(x))) - B1 <- B1[, noNA, drop = FALSE] - B2 <- B2[, noNA, drop = FALSE] - target <- target[noNA, , drop = FALSE] - - # Only correlation-based comparison supported - if (method %in% c("s", "p")) { - mat1 <- cor(t(B1), target, method = method) - mat2 <- cor(t(B2), target, method = method) - } - - # if (method %in% c("s", "p")) { - # mat1 <- cor(t(B1), target, method = method) - # mat2 <- cor(t(B2), target, method = method) - # } else if (method == "a") { - # mat1 <- allAgainstAllAUCs(t(B1), target) - # mat2 <- allAgainstAllAUCs(t(B2), target) - # } else if (method == "t") { - # mat1 <- allAgainstAllTstats(t(B1), target) - # mat2 <- allAgainstAllTstats(t(B2), target) - # } - - if (inherits(res1, "rsvd")) - mat1 <- abs(mat1) - if (inherits(res2, "rsvd")) - mat1 <- abs(mat1) - mat1[is.na(mat1)] <- 0 - mat2[is.na(mat2)] <- 0 - if (oneToOne) { - mat1 <- oneToOneMask(mat1) - mat2 <- oneToOneMask(mat2) - } - - cor1 <- apply(mat1, 2, max) - cor2 <- apply(mat2, 2, max) - cor1[cor1 < 0.01] <- NA - cor2[cor2 < 0.01] <- NA - idx1 <- apply(mat1, 2, which.max) - idx2 <- apply(mat2, 2, which.max) - Labels <- colnames(target) - - df <- data.frame( - Cor1 = cor1, Cor2 = cor2, - BestIdxRes1 = idx1, BestIdxRes2 = idx2, - Label = Labels - ) - df$corMean <- (df$Cor1 + df$Cor2) / 2 - - pval <- if (stat.method == "t") { - t.test(df$Cor2, df$Cor1, paired = TRUE, alternative = "greater")$p.value - } else { - wilcox.test(df$Cor2, df$Cor1, paired = TRUE, alternative = "greater")$p.value - } - - method_label <- switch(method, - p = "Pearson correlation", - s = "Spearman correlation", - a = "AUC", - t = "T-statistic" - ) - - pl <- ggplot2::ggplot(df, ggplot2::aes(x = Cor1, y = Cor2, label = Label)) + - ggplot2::geom_point() + - ggplot2::geom_abline( - slope = 1, intercept = 0, - linetype = "dashed", color = "red", linewidth = 1 - ) + - ggrepel::geom_text_repel() + - ggplot2::labs( - x = sprintf("Max %s %s", method_label, xlab), - y = sprintf("Max %s %s", method_label, ylab) - ) + - ggplot2::annotate( - "text", x = -Inf, y = Inf, hjust = -0.1, vjust = 1.1, - label = sprintf("p = %.3g", pval) - ) + - ggplot2::theme_minimal() - - if (is.list(res1) && !is.null(res1$Z)) { - get_top_genes <- function(Z, k) { - apply(Z, 2, function(col) { - names(sort(col, decreasing = TRUE))[seq_len(min(k, length(col)))] - }) - } - topk1 <- get_top_genes(res1$Z, 7) - topk2 <- get_top_genes(res2$Z, 7) - df$TopGenesRes1 <- vapply(idx1, function(i) paste(topk1[, i], collapse = ","), "") - df$TopGenesRes2 <- vapply(idx2, function(i) paste(topk2[, i], collapse = ","), "") - } - - return(list(plot = pl, df = df)) + wilcox.test( + df$Cor2, df$Cor1, + paired = TRUE, alternative = "greater" + )$p.value + } + + method_label <- switch(method, + p = "Pearson correlation", + s = "Spearman correlation", + a = "AUC", + t = "T-statistic" + ) + + pl <- ggplot2::ggplot(df, ggplot2::aes(x = Cor1, y = Cor2, label = Label)) + + ggplot2::geom_point() + + ggplot2::geom_abline( + slope = 1, intercept = 0, + linetype = "dashed", color = "red", linewidth = 1 + ) + + ggrepel::geom_text_repel() + + ggplot2::labs( + x = sprintf("Max %s %s", method_label, xlab), + y = sprintf("Max %s %s", method_label, ylab) + ) + + ggplot2::annotate( + "text", + x = -Inf, y = Inf, hjust = -0.1, vjust = 1.1, + label = sprintf("p = %.3g", pval) + ) + + ggplot2::theme_minimal() + + if (is.list(res1) && !is.null(res1$Z)) { + get_top_genes <- function(Z, k) { + apply(Z, 2, function(col) { + top_n <- seq_len(min(k, length(col))) + names(sort(col, decreasing = TRUE))[top_n] + }) + } + topk1 <- get_top_genes(res1$Z, 7) + topk2 <- get_top_genes(res2$Z, 7) + df$TopGenesRes1 <- vapply( + idx1, function(i) paste(topk1[, i], collapse = ","), "" + ) + df$TopGenesRes2 <- vapply( + idx2, function(i) paste(topk2[, i], collapse = ","), "" + ) + } + + return(list(plot = pl, df = df)) } #' ComplexHeatmap visualization of top genes by latent variable @@ -155,14 +170,16 @@ compareBs <- function(res1, res2, target, method = "p", xlab = "1", ylab = "2", #' Produces a combined heatmap showing expression, pathway membership, #' and optionally Z-loadings for top genes per LV using ComplexHeatmap. #' -#' @param clampRes A CLAMP result list containing matrices \code{Z}, \code{U}, etc. +#' @param clampRes A CLAMP result list containing matrices \code{Z}, +#' \code{U}, etc. #' @param data Expression matrix with genes as rows. #' @param priorMat Binary gene × pathway matrix. #' @param top Integer, number of top genes per LV. #' @param top.pathway Integer, number of top pathways per LV to annotate. #' @param index Optional vector of LVs to include. #' @param allLVs Logical; include all LVs. -#' @param Zheat Logical; whether to include the Z matrix as an additional heatmap. +#' @param Zheat Logical; whether to include the Z matrix as an additional +#' heatmap. #' @param LV.names Optional character vector for LV names. #' @param max.genes Maximum number of genes allowed in the plot. #' @param max.col Maximum number of columns (samples). @@ -186,121 +203,147 @@ compareBs <- function(res1, res2, target, method = "p", xlab = "1", ylab = "2", #' #' # Simulated Z (gene loadings) and U (pathway loadings) #' Z <- matrix(rnorm(100 * 3), nrow = 100, dimnames = list(genes, lvs)) -#' U <- matrix(abs(rnorm(50 * 3)), nrow = 50, -#' dimnames = list(paste0("Path", 1:50), lvs)) +#' U <- matrix(abs(rnorm(50 * 3)), +#' nrow = 50, +#' dimnames = list(paste0("Path", 1:50), lvs) +#' ) #' #' # Expression data -#' expr_data <- matrix(rnorm(100 * 20), nrow = 100, -#' dimnames = list(genes, samples)) +#' expr_data <- matrix(rnorm(100 * 20), +#' nrow = 100, +#' dimnames = list(genes, samples) +#' ) #' #' # Binary gene × pathway matrix #' priorMat <- matrix(sample(0:1, 100 * 50, replace = TRUE, prob = c(0.9, 0.1)), -#' nrow = 100, ncol = 50, -#' dimnames = list(genes, paste0("Path", 1:50))) +#' nrow = 100, ncol = 50, +#' dimnames = list(genes, paste0("Path", 1:50)) +#' ) #' #' # Create a CLAMP-like result list #' clampRes <- list(Z = Z, U = U) #' #' # Plot top genes and pathway memberships #' plotTopZ_Complex(clampRes, expr_data, priorMat, -#' top = 5, top.pathway = 3, index = 1:2, Zheat = TRUE) -plotTopZ_Complex <- function(clampRes, data, priorMat, top = 10, top.pathway = 5, +#' top = 5, top.pathway = 3, index = 1:2, Zheat = TRUE +#' ) +plotTopZ_Complex <- function(clampRes, data, priorMat, + top = 10, top.pathway = 5, index = NULL, allLVs = FALSE, Zheat = FALSE, - LV.names = NULL, max.genes = 100, max.col = 50, seed = 1234) { - - data <- data[rownames(clampRes$Z), , drop = FALSE] - if (top * length(index) > max.genes) - stop("Too many genes. Reduce number of LVs or 'top', or increase 'max.genes'.") - - if (ncol(data) > max.col) { - data <- data[, sample(ncol(data), max.col)] - } - - priorMat <- priorMat[rownames(clampRes$Z), , drop = FALSE] - ii <- which(colSums(clampRes$U) > 0) - if (!allLVs) { - if (!is.null(index)) ii <- intersect(ii, index) - } else { - ii <- index - } - - tmp <- apply(-clampRes$Z[, ii, drop = FALSE], 2, rank) - nn <- unique(unlist(apply(tmp, 2, function(x) names(which(x <= top))))) - nn <- sort(unique(nn)) - data_sub <- t(scale(t(data[nn, , drop = FALSE]))) - - nnpath <- vapply( - seq_along(ii), - function(i) { - gene_idx <- match(nn, rownames(priorMat)) - col_idx <- which(clampRes$U[, ii[i]] > 0) - Matrix::rowSums(priorMat[gene_idx, col_idx, drop = FALSE]) > 0 - }, - logical(length(nn)) # expected output type - ) - - nnpath <- rowSums(nnpath) > 0 - - gene_annot <- ComplexHeatmap::rowAnnotation( - present = nnpath, - col = list(present = c("TRUE" = "black", "FALSE" = "beige")) - ) - - top_pathways <- unique(unlist(lapply(ii, function(i) - names(sort(clampRes$U[, i], decreasing = TRUE))[seq_len(top.pathway)]))) - gene_idx <- match(nn, rownames(priorMat)) - path_idx <- match(top_pathways, colnames(priorMat)) - pathway_mat <- priorMat[gene_idx, path_idx, drop = FALSE] - pathway_mat <- pathway_mat[, colSums(pathway_mat) > 0, drop = FALSE] - - ht1 <- ComplexHeatmap::Heatmap( - data_sub, name = "expression", - show_row_names = TRUE, show_column_names = FALSE, - cluster_rows = TRUE, cluster_columns = TRUE, - width = grid::unit(7, "cm"), - row_dend_width = grid::unit(0, "mm"), - use_raster = FALSE - ) - - col_fun <- circlize::colorRamp2(c(0, 1), c("white", "black")) - ht2 <- ComplexHeatmap::Heatmap( - as.matrix(pathway_mat > 0), - name = "in pathway", col = col_fun, - show_row_names = TRUE, show_column_names = TRUE, - cluster_rows = FALSE, cluster_columns = FALSE, - column_names_rot = 45, - row_names_gp = grid::gpar(fontsize = 8), - column_names_gp = grid::gpar(fontsize = 8), - width = grid::unit(6, "cm"), - use_raster = FALSE - ) - - if (Zheat) { - gene_idx <- match(nn, rownames(clampRes$Z)) - z_sub <- scale(clampRes$Z[gene_idx, index, drop = FALSE], center = FALSE) - if (!is.null(LV.names)) colnames(z_sub) <- LV.names[index] - z_col_fun <- circlize::colorRamp2(c(0, max(z_sub, na.rm = TRUE)), - c("#e5f5e0", "#31a354")) - ht_z <- ComplexHeatmap::Heatmap( - z_sub, name = "Z", col = z_col_fun, - cluster_rows = TRUE, cluster_columns = TRUE, - show_row_names = TRUE, show_column_names = TRUE, - column_names_rot = 90, - width = grid::unit(1, "cm"), - use_raster = FALSE + LV.names = NULL, max.genes = 100, max.col = 50, + seed = 1234) { + data <- data[rownames(clampRes$Z), , drop = FALSE] + if (top * length(index) > max.genes) { + stop( + "Too many genes. Reduce number of LVs or 'top', ", + "or increase 'max.genes'." + ) + } + + if (ncol(data) > max.col) { + data <- data[, sample(ncol(data), max.col)] + } + + priorMat <- priorMat[rownames(clampRes$Z), , drop = FALSE] + ii <- which(colSums(clampRes$U) > 0) + if (!allLVs) { + if (!is.null(index)) ii <- intersect(ii, index) + } else { + ii <- index + } + + tmp <- apply(-clampRes$Z[, ii, drop = FALSE], 2, rank) + nn <- unique(unlist(apply(tmp, 2, function(x) names(which(x <= top))))) + nn <- sort(unique(nn)) + data_sub <- t(scale(t(data[nn, , drop = FALSE]))) + + nnpath <- vapply( + seq_along(ii), + function(i) { + gene_idx <- match(nn, rownames(priorMat)) + col_idx <- which(clampRes$U[, ii[i]] > 0) + Matrix::rowSums(priorMat[gene_idx, col_idx, drop = FALSE]) > 0 + }, + logical(length(nn)) # expected output type ) - } - - lv_labels <- colnames(clampRes$Z)[max.col(scale(clampRes$Z, center = FALSE), ties.method = "first")] - names(lv_labels) <- rownames(clampRes$Z) - gene_lv <- lv_labels[rownames(data_sub)] - row_annot <- ComplexHeatmap::rowAnnotation(LV = gene_lv, show_annotation_name = FALSE) - - if (!Zheat) { - ComplexHeatmap::draw(row_annot + ht1 + ht2, row_dend_side = "left") - } else { - ComplexHeatmap::draw(row_annot + ht_z + ht1 + ht2, row_dend_side = "left") - } + + nnpath <- rowSums(nnpath) > 0 + + gene_annot <- ComplexHeatmap::rowAnnotation( + present = nnpath, + col = list(present = c("TRUE" = "black", "FALSE" = "beige")) + ) + + top_pathways <- unique(unlist(lapply(ii, function(i) { + names(sort(clampRes$U[, i], decreasing = TRUE))[seq_len(top.pathway)] + }))) + gene_idx <- match(nn, rownames(priorMat)) + path_idx <- match(top_pathways, colnames(priorMat)) + pathway_mat <- priorMat[gene_idx, path_idx, drop = FALSE] + pathway_mat <- pathway_mat[, colSums(pathway_mat) > 0, drop = FALSE] + + ht1 <- ComplexHeatmap::Heatmap( + data_sub, + name = "expression", + show_row_names = TRUE, show_column_names = FALSE, + cluster_rows = TRUE, cluster_columns = TRUE, + width = grid::unit(7, "cm"), + row_dend_width = grid::unit(0, "mm"), + use_raster = FALSE + ) + + col_fun <- circlize::colorRamp2(c(0, 1), c("white", "black")) + ht2 <- ComplexHeatmap::Heatmap( + as.matrix(pathway_mat > 0), + name = "in pathway", col = col_fun, + show_row_names = TRUE, show_column_names = TRUE, + cluster_rows = FALSE, cluster_columns = FALSE, + column_names_rot = 45, + row_names_gp = grid::gpar(fontsize = 8), + column_names_gp = grid::gpar(fontsize = 8), + width = grid::unit(6, "cm"), + use_raster = FALSE + ) + + if (Zheat) { + gene_idx <- match(nn, rownames(clampRes$Z)) + z_sub <- scale( + clampRes$Z[gene_idx, index, drop = FALSE], + center = FALSE + ) + if (!is.null(LV.names)) colnames(z_sub) <- LV.names[index] + z_col_fun <- circlize::colorRamp2( + c(0, max(z_sub, na.rm = TRUE)), + c("#e5f5e0", "#31a354") + ) + ht_z <- ComplexHeatmap::Heatmap( + z_sub, + name = "Z", col = z_col_fun, + cluster_rows = TRUE, cluster_columns = TRUE, + show_row_names = TRUE, show_column_names = TRUE, + column_names_rot = 90, + width = grid::unit(1, "cm"), + use_raster = FALSE + ) + } + + lv_labels <- colnames(clampRes$Z)[ + max.col(scale(clampRes$Z, center = FALSE), ties.method = "first") + ] + names(lv_labels) <- rownames(clampRes$Z) + gene_lv <- lv_labels[rownames(data_sub)] + row_annot <- ComplexHeatmap::rowAnnotation( + LV = gene_lv, show_annotation_name = FALSE + ) + + if (!Zheat) { + ComplexHeatmap::draw(row_annot + ht1 + ht2, row_dend_side = "left") + } else { + ComplexHeatmap::draw( + row_annot + ht_z + ht1 + ht2, + row_dend_side = "left" + ) + } } # Plotting functions (adapted from PLIER, Mao et al.) @@ -335,24 +378,30 @@ plotTopZ_Complex <- function(clampRes, data, priorMat, top = 10, top.pathway = 5 #' @examples #' set.seed(42) #' pathways <- paste0("Path", 1:30) -#' lvs <- paste0("LV", 1:5) +#' lvs <- paste0("LV", 1:5) #' -#' U <- matrix(abs(rnorm(30 * 5)), nrow = 30, -#' dimnames = list(pathways, lvs)) -#' Uauc <- matrix(runif(30 * 5, 0.5, 1.0), nrow = 30, -#' dimnames = list(pathways, lvs)) -#' Up <- matrix(runif(30 * 5, 0, 3), nrow = 30, -#' dimnames = list(pathways, lvs)) +#' U <- matrix(abs(rnorm(30 * 5)), +#' nrow = 30, +#' dimnames = list(pathways, lvs) +#' ) +#' Uauc <- matrix(runif(30 * 5, 0.5, 1.0), +#' nrow = 30, +#' dimnames = list(pathways, lvs) +#' ) +#' Up <- matrix(runif(30 * 5, 0, 3), +#' nrow = 30, +#' dimnames = list(pathways, lvs) +#' ) #' #' # Build a minimal summary table #' nr <- 30 * 5 #' summ <- data.frame( -#' pathway = rep(pathways, 5), -#' LV = rep(lvs, each = 30), -#' AUC = as.vector(Uauc), -#' p_value = runif(nr, 0, 0.1), -#' FDR = runif(nr, 0, 0.1), -#' stringsAsFactors = FALSE +#' pathway = rep(pathways, 5), +#' LV = rep(lvs, each = 30), +#' AUC = as.vector(Uauc), +#' p_value = runif(nr, 0, 0.1), +#' FDR = runif(nr, 0, 0.1), +#' stringsAsFactors = FALSE #' ) #' #' clampRes <- list(U = U, Uauc = Uauc, Up = Up, summary = summ) @@ -360,78 +409,79 @@ plotTopZ_Complex <- function(clampRes, data, priorMat, top = 10, top.pathway = 5 CLAMPplotU <- function(clampRes, auc.cutoff = 0.6, fdr.cutoff = 0.05, indexCol = NULL, indexRow = NULL, top = 3, sort.row = FALSE, cluster.rows = TRUE) { + indexCol <- if (is.null(indexCol)) seq_len(ncol(clampRes$U)) else indexCol + indexRow <- if (is.null(indexRow)) seq_len(nrow(clampRes$U)) else indexRow + + U <- as.matrix(clampRes$U) + + pval.cutoff <- if (!is.null(clampRes$summary) && + any(clampRes$summary[, 5] < fdr.cutoff)) { + max(clampRes$summary[clampRes$summary[, 5] < fdr.cutoff, 4]) + } else { + Inf + } + + U[as.matrix(clampRes$Uauc) < auc.cutoff] <- 0 + U[as.matrix(clampRes$Up) > pval.cutoff] <- 0 + + U <- U[indexRow, indexCol, drop = FALSE] + + for (i in seq_len(ncol(U))) { + ct <- sort(U[, i], decreasing = TRUE)[top] + if (!is.na(ct)) U[U[, i] < ct, i] <- 0 + } + + rownames(U) <- make.unique(strtrim(rownames(U), 30)) + colnames(U) <- make.unique(strtrim(colnames(U), 30)) + + keep_row <- rowSums(abs(U)) > 0 + keep_col <- colSums(abs(U)) > 0 + U <- U[keep_row, keep_col, drop = FALSE] + + if (nrow(U) == 0 || ncol(U) == 0) { + message("No entries pass the AUC/FDR thresholds.") + return(invisible(NULL)) + } + + if (sort.row) { + Utmp <- sweep(sign(U), 2, seq_len(ncol(U)) * 100, "*") + Um <- apply(Utmp, 1, max) + U <- U[order(-Um), , drop = FALSE] + } else if (cluster.rows && nrow(U) > 1) { + U <- U[hclust(dist(U))$order, , drop = FALSE] + } - indexCol <- if (is.null(indexCol)) seq_len(ncol(clampRes$U)) else indexCol - indexRow <- if (is.null(indexRow)) seq_len(nrow(clampRes$U)) else indexRow - - U <- as.matrix(clampRes$U) - - pval.cutoff <- if (!is.null(clampRes$summary) && - any(clampRes$summary[, 5] < fdr.cutoff)) { - max(clampRes$summary[clampRes$summary[, 5] < fdr.cutoff, 4]) - } else { - Inf - } - - U[as.matrix(clampRes$Uauc) < auc.cutoff] <- 0 - U[as.matrix(clampRes$Up) > pval.cutoff] <- 0 - - U <- U[indexRow, indexCol, drop = FALSE] - - for (i in seq_len(ncol(U))) { - ct <- sort(U[, i], decreasing = TRUE)[top] - if (!is.na(ct)) U[U[, i] < ct, i] <- 0 - } - - rownames(U) <- make.unique(strtrim(rownames(U), 30)) - colnames(U) <- make.unique(strtrim(colnames(U), 30)) - - keep_row <- rowSums(abs(U)) > 0 - keep_col <- colSums(abs(U)) > 0 - U <- U[keep_row, keep_col, drop = FALSE] - - if (nrow(U) == 0 || ncol(U) == 0) { - message("No entries pass the AUC/FDR thresholds.") - return(invisible(NULL)) - } - - if (sort.row) { - Utmp <- sweep(sign(U), 2, seq_len(ncol(U)) * 100, "*") - Um <- apply(Utmp, 1, max) - U <- U[order(-Um), , drop = FALSE] - } else if (cluster.rows && nrow(U) > 1) { - U <- U[hclust(dist(U))$order, , drop = FALSE] - } - - df <- data.frame( - pathway = factor(rep(rownames(U), ncol(U)), levels = rev(rownames(U))), - LV = factor(rep(colnames(U), each = nrow(U)), levels = colnames(U)), - value = as.vector(U), - stringsAsFactors = FALSE - ) - - p <- ggplot2::ggplot(df, ggplot2::aes( - x = .data$LV, - y = .data$pathway, - fill = .data$value - )) + - ggplot2::geom_tile(colour = "white", linewidth = 0.4) + - ggplot2::scale_fill_gradient( - name = "U", - low = "#F7FBFF", - high = "#08519C", - limits = c(0, NA) - ) + - ggplot2::theme_minimal(base_size = 10) + - ggplot2::theme( - axis.text.x = ggplot2::element_text(angle = 45, hjust = 1, size = 9), - axis.text.y = ggplot2::element_text(size = 7), - panel.grid = ggplot2::element_blank(), - legend.key.width = ggplot2::unit(0.4, "cm") - ) + - ggplot2::labs(x = "Latent Variable", y = NULL) - - p + df <- data.frame( + pathway = factor(rep(rownames(U), ncol(U)), levels = rev(rownames(U))), + LV = factor(rep(colnames(U), each = nrow(U)), levels = colnames(U)), + value = as.vector(U), + stringsAsFactors = FALSE + ) + + p <- ggplot2::ggplot(df, ggplot2::aes( + x = .data$LV, + y = .data$pathway, + fill = .data$value + )) + + ggplot2::geom_tile(colour = "white", linewidth = 0.4) + + ggplot2::scale_fill_gradient( + name = "U", + low = "#F7FBFF", + high = "#08519C", + limits = c(0, NA) + ) + + ggplot2::theme_minimal(base_size = 10) + + ggplot2::theme( + axis.text.x = ggplot2::element_text( + angle = 45, hjust = 1, size = 9 + ), + axis.text.y = ggplot2::element_text(size = 7), + panel.grid = ggplot2::element_blank(), + legend.key.width = ggplot2::unit(0.4, "cm") + ) + + ggplot2::labs(x = "Latent Variable", y = NULL) + + p } #' Plot top genes per LV by Z loading @@ -461,128 +511,148 @@ CLAMPplotU <- function(clampRes, auc.cutoff = 0.6, fdr.cutoff = 0.05, #' @examples #' set.seed(1) #' genes <- paste0("Gene", 1:80) -#' lvs <- paste0("LV", 1:4) +#' lvs <- paste0("LV", 1:4) #' paths <- paste0("Path", 1:10) -#' Z <- matrix(abs(rnorm(80 * 4)), nrow = 80, -#' dimnames = list(genes, lvs)) -#' U <- matrix(abs(rnorm(10 * 4)), nrow = 10, -#' dimnames = list(paths, lvs)) +#' Z <- matrix(abs(rnorm(80 * 4)), +#' nrow = 80, +#' dimnames = list(genes, lvs) +#' ) +#' U <- matrix(abs(rnorm(10 * 4)), +#' nrow = 10, +#' dimnames = list(paths, lvs) +#' ) #' clampRes <- list(Z = Z, U = U) #' CLAMPplotTopZ(clampRes, top = 20, index = 1:2) CLAMPplotTopZ <- function(clampRes, data = NULL, priorMat = NULL, top = 50, index = NULL, allLVs = FALSE, label.top = min(10, top), max.name.len = 50) { + if (is.null(clampRes$Z)) { + stop("'clampRes' must contain a 'Z' matrix.") + } - if (is.null(clampRes$Z)) { - stop("'clampRes' must contain a 'Z' matrix.") - } + Z <- as.matrix(clampRes$Z) + if (is.null(rownames(Z))) rownames(Z) <- paste0("Gene", seq_len(nrow(Z))) + if (is.null(colnames(Z))) colnames(Z) <- paste0("LV", seq_len(ncol(Z))) + + if (is.null(index)) { + if (!allLVs && !is.null(clampRes$U)) { + ii <- which(colSums(as.matrix(clampRes$U), na.rm = TRUE) > 0) + if (length(ii) == 0) ii <- seq_len(ncol(Z)) + } else { + ii <- seq_len(ncol(Z)) + } + } else if (is.character(index)) { + ii <- match(index, colnames(Z)) + if (anyNA(ii)) { + stop( + "Unknown latent variable(s): ", + paste(index[is.na(ii)], collapse = ", ") + ) + } + } else { + ii <- as.integer(index) + } - Z <- as.matrix(clampRes$Z) - if (is.null(rownames(Z))) rownames(Z) <- paste0("Gene", seq_len(nrow(Z))) - if (is.null(colnames(Z))) colnames(Z) <- paste0("LV", seq_len(ncol(Z))) + ii <- unique(ii[!is.na(ii) & ii >= 1 & ii <= ncol(Z)]) + if (length(ii) == 0) stop("No latent variables selected.") - if (is.null(index)) { - if (!allLVs && !is.null(clampRes$U)) { - ii <- which(colSums(as.matrix(clampRes$U), na.rm = TRUE) > 0) - if (length(ii) == 0) ii <- seq_len(ncol(Z)) - } else { - ii <- seq_len(ncol(Z)) - } - } else if (is.character(index)) { - ii <- match(index, colnames(Z)) - if (anyNA(ii)) { - stop("Unknown latent variable(s): ", - paste(index[is.na(ii)], collapse = ", ")) - } - } else { - ii <- as.integer(index) - } - - ii <- unique(ii[!is.na(ii) & ii >= 1 & ii <= ncol(Z)]) - if (length(ii) == 0) stop("No latent variables selected.") - - top <- as.integer(top)[1] - if (!is.finite(top) || top < 1) stop("'top' must be a positive integer.") - - label.top <- as.integer(label.top)[1] - if (!is.finite(label.top) || label.top < 0) { - stop("'label.top' must be a non-negative integer.") - } - label.top <- min(label.top, top) - - make_lv_df <- function(i) { - loadings <- Z[, i] - keep <- which(!is.na(loadings)) - if (length(keep) == 0) { - return(data.frame()) - } - - loadings <- loadings[keep] - genes <- rownames(Z)[keep] - ord <- order(loadings, decreasing = TRUE) - n_top <- min(top, length(ord)) - ord <- ord[seq_len(n_top)] - - data.frame( - LV = colnames(Z)[i], - rank = seq_len(n_top), - gene = genes[ord], - loading = loadings[ord], - label = ifelse(seq_len(n_top) <= label.top, - strtrim(genes[ord], max.name.len), - NA_character_), - stringsAsFactors = FALSE - ) - } - - plot_df <- do.call(rbind, lapply(ii, make_lv_df)) - if (nrow(plot_df) == 0) stop("Selected latent variables have no finite Z loadings.") - - plot_df$LV <- factor(plot_df$LV, levels = colnames(Z)[ii]) - - make_plot <- function(lv_name) { - df <- plot_df[plot_df$LV == lv_name, , drop = FALSE] - label_df <- df[!is.na(df$label), , drop = FALSE] - - ggplot2::ggplot(df, ggplot2::aes(x = .data$rank, y = .data$loading)) + - ggplot2::geom_point(size = 1.2, colour = "grey75") + - ggplot2::geom_point(data = label_df, colour = "#C23B22", size = 1.6) + - ggrepel::geom_text_repel( - data = label_df, - ggplot2::aes(label = .data$label), - size = 3, - fontface = "italic", - direction = "y", - hjust = 0, - seed = 42, - max.overlaps = Inf, - min.segment.length = 0, - box.padding = 0.3, - point.padding = 0.2, - nudge_x = max(1, top * 0.04), - segment.color = "grey60", - segment.size = 0.25 - ) + - ggplot2::coord_cartesian(clip = "off") + - ggplot2::scale_x_continuous( - expand = ggplot2::expansion(mult = c(0.02, 0.18)) - ) + - ggplot2::labs(title = as.character(lv_name), x = NULL, y = "Loadings") + - ggplot2::theme_classic(base_size = 11) + - ggplot2::theme( - axis.line = ggplot2::element_line(colour = "black", linewidth = 0.4), - axis.ticks = ggplot2::element_line(colour = "black", linewidth = 0.35), - axis.text.x = ggplot2::element_blank(), - axis.ticks.x = ggplot2::element_blank(), - plot.title = ggplot2::element_text(face = "bold", hjust = 0.5, size = 12), - plot.margin = ggplot2::margin(5.5, 28, 5.5, 5.5) - ) - } - - plots <- lapply(levels(plot_df$LV), make_plot) - if (length(plots) == 1) return(plots[[1]]) - - patchwork::wrap_plots(plots, ncol = min(2, length(plots))) + top <- as.integer(top)[1] + if (!is.finite(top) || top < 1) stop("'top' must be a positive integer.") + + label.top <- as.integer(label.top)[1] + if (!is.finite(label.top) || label.top < 0) { + stop("'label.top' must be a non-negative integer.") + } + label.top <- min(label.top, top) + + make_lv_df <- function(i) { + loadings <- Z[, i] + keep <- which(!is.na(loadings)) + if (length(keep) == 0) { + return(data.frame()) + } + + loadings <- loadings[keep] + genes <- rownames(Z)[keep] + ord <- order(loadings, decreasing = TRUE) + n_top <- min(top, length(ord)) + ord <- ord[seq_len(n_top)] + + data.frame( + LV = colnames(Z)[i], + rank = seq_len(n_top), + gene = genes[ord], + loading = loadings[ord], + label = ifelse(seq_len(n_top) <= label.top, + strtrim(genes[ord], max.name.len), + NA_character_ + ), + stringsAsFactors = FALSE + ) + } + + plot_df <- do.call(rbind, lapply(ii, make_lv_df)) + if (nrow(plot_df) == 0) { + stop("Selected latent variables have no finite Z loadings.") + } + + plot_df$LV <- factor(plot_df$LV, levels = colnames(Z)[ii]) + + make_plot <- function(lv_name) { + df <- plot_df[plot_df$LV == lv_name, , drop = FALSE] + label_df <- df[!is.na(df$label), , drop = FALSE] + + ggplot2::ggplot(df, ggplot2::aes(x = .data$rank, y = .data$loading)) + + ggplot2::geom_point(size = 1.2, colour = "grey75") + + ggplot2::geom_point( + data = label_df, colour = "#C23B22", size = 1.6 + ) + + ggrepel::geom_text_repel( + data = label_df, + ggplot2::aes(label = .data$label), + size = 3, + fontface = "italic", + direction = "y", + hjust = 0, + seed = 42, + max.overlaps = Inf, + min.segment.length = 0, + box.padding = 0.3, + point.padding = 0.2, + nudge_x = max(1, top * 0.04), + segment.color = "grey60", + segment.size = 0.25 + ) + + ggplot2::coord_cartesian(clip = "off") + + ggplot2::scale_x_continuous( + expand = ggplot2::expansion(mult = c(0.02, 0.18)) + ) + + ggplot2::labs( + title = as.character(lv_name), x = NULL, y = "Loadings" + ) + + ggplot2::theme_classic(base_size = 11) + + ggplot2::theme( + axis.line = ggplot2::element_line( + colour = "black", linewidth = 0.4 + ), + axis.ticks = ggplot2::element_line( + colour = "black", linewidth = 0.35 + ), + axis.text.x = ggplot2::element_blank(), + axis.ticks.x = ggplot2::element_blank(), + plot.title = ggplot2::element_text( + face = "bold", hjust = 0.5, size = 12 + ), + plot.margin = ggplot2::margin(5.5, 28, 5.5, 5.5) + ) + } + + plots <- lapply(levels(plot_df$LV), make_plot) + if (length(plots) == 1) { + return(plots[[1]]) + } + + patchwork::wrap_plots(plots, ncol = min(2, length(plots))) } #' Dot plot of top pathways for a single latent variable @@ -616,123 +686,128 @@ CLAMPplotTopZ <- function(clampRes, data = NULL, priorMat = NULL, top = 50, #' @examples #' set.seed(9) #' pathways <- paste0("Pathway_", 1:20) -#' lvs <- paste0("LV", 1:5) -#' nr <- length(pathways) * length(lvs) +#' lvs <- paste0("LV", 1:5) +#' nr <- length(pathways) * length(lvs) #' #' summ <- data.frame( -#' pathway = rep(pathways, length(lvs)), -#' LV = rep(lvs, each = length(pathways)), -#' AUC = runif(nr, 0.5, 1.0), -#' FDR = runif(nr, 0, 0.05), -#' stringsAsFactors = FALSE +#' pathway = rep(pathways, length(lvs)), +#' LV = rep(lvs, each = length(pathways)), +#' AUC = runif(nr, 0.5, 1.0), +#' FDR = runif(nr, 0, 0.05), +#' stringsAsFactors = FALSE #' ) #' #' CLAMPdotplot(list(summary = summ), lv = 1, top = 10) -#' CLAMPdotplot(list(summary = summ), lv = "LV2", x.axis = "-log10(FDR)", -#' order.by = "-log10(FDR)") +#' CLAMPdotplot(list(summary = summ), +#' lv = "LV2", x.axis = "-log10(FDR)", +#' order.by = "-log10(FDR)" +#' ) CLAMPdotplot <- function(clampRes, lv = 1, top = 20, auc.cutoff = 0.6, fdr.cutoff = 0.05, max.name.len = 50, x.axis = c("AUC", "-log10(FDR)", "log10FDR"), order.by = x.axis) { + summ <- if (is.data.frame(clampRes)) clampRes else clampRes$summary + if (is.null(summ)) { + stop("'clampRes' must contain a 'summary' data frame or be one itself.") + } + + if ("LV_index" %in% colnames(summ) && !"LV" %in% colnames(summ)) { + summ$LV <- paste0("LV", summ$LV_index) + } + + required <- c("pathway", "LV", "AUC", "FDR") + missing <- setdiff(required, colnames(summ)) + if (length(missing) > 0) { + stop("summary is missing columns: ", paste(missing, collapse = ", ")) + } - summ <- if (is.data.frame(clampRes)) clampRes else clampRes$summary - if (is.null(summ)) - stop("'clampRes' must contain a 'summary' data frame or be one itself.") - - if ("LV_index" %in% colnames(summ) && !"LV" %in% colnames(summ)) - summ$LV <- paste0("LV", summ$LV_index) - - required <- c("pathway", "LV", "AUC", "FDR") - missing <- setdiff(required, colnames(summ)) - if (length(missing) > 0) - stop("summary is missing columns: ", paste(missing, collapse = ", ")) - - normalize_dotplot_metric <- function(x) { - x <- match.arg(x, c("AUC", "-log10(FDR)", "log10FDR")) - if (x == "log10FDR") "-log10(FDR)" else x - } - - x.axis <- normalize_dotplot_metric(x.axis) - order.by <- normalize_dotplot_metric(order.by) - - lv_name <- if (is.numeric(lv)) paste0("LV", lv) else as.character(lv) - df <- summ[summ$LV == lv_name & - summ$AUC >= auc.cutoff & - summ$FDR <= fdr.cutoff, , drop = FALSE] - - if (nrow(df) == 0) { - message("No associations pass the thresholds for ", lv_name, ".") - return(invisible(NULL)) - } - - df$log10_fdr <- -log10(pmax(df$FDR, .Machine$double.eps)) - x_col <- if (x.axis == "AUC") "AUC" else "log10_fdr" - order_col <- if (order.by == "AUC") "AUC" else "log10_fdr" - - df <- df[order(-df[[order_col]], -df$AUC), , drop = FALSE] - df <- df[seq_len(min(top, nrow(df))), , drop = FALSE] - df$x_value <- df[[x_col]] - df$pathway_label <- make.unique(strtrim(df$pathway, max.name.len)) - df$pathway <- factor( - df$pathway_label, - levels = df$pathway_label[order(df[[order_col]], df$AUC)] - ) - - log10_fdr_min <- -log10(max(fdr.cutoff, .Machine$double.eps)) - log10_fdr_max <- max(df$log10_fdr, na.rm = TRUE) - if (log10_fdr_max <= log10_fdr_min) - log10_fdr_max <- log10_fdr_min + 1e-6 - - x_baseline <- if (x.axis == "AUC") auc.cutoff else log10_fdr_min - if (x.axis == "AUC") { - x_limits <- c(max(0, auc.cutoff - 0.02), 1) - x_label <- "AUC" - } else { - x_range <- range(c(x_baseline, df$x_value), na.rm = TRUE) - x_pad <- diff(x_range) * 0.05 - if (!is.finite(x_pad) || x_pad == 0) x_pad <- 0.1 - x_limits <- c(max(0, x_range[1] - x_pad), x_range[2] + x_pad) - x_label <- "-log10(FDR)" - } - - p <- ggplot2::ggplot(df, ggplot2::aes( - x = .data$x_value, - y = .data$pathway, - colour = .data$log10_fdr - )) + - ggplot2::geom_segment( - ggplot2::aes(xend = .data$x_value, yend = .data$pathway), - x = x_baseline, - colour = "#A1D99B", - linewidth = 1 - ) + - ggplot2::geom_point(ggplot2::aes(size = .data$AUC), alpha = 0.9) + - ggplot2::scale_size_continuous( - name = "AUC", - range = c(3, 8), - limits = c(auc.cutoff, 1) - ) + - ggplot2::scale_colour_gradient( - name = "-log10(FDR)", - low = "#DCEFD8", - high = "#1B7837", - limits = c(log10_fdr_min, log10_fdr_max) - ) + - ggplot2::scale_x_continuous( - limits = x_limits, - expand = c(0, 0.01) - ) + - ggplot2::theme_minimal(base_size = 11) + - ggplot2::theme( - plot.title = ggplot2::element_text(hjust = 0.5), - axis.text.y = ggplot2::element_text(size = 9), - panel.grid.major.y = ggplot2::element_line(colour = "grey92"), - panel.grid.major.x = ggplot2::element_line(colour = "grey92"), - panel.grid.minor = ggplot2::element_blank() - ) + - ggplot2::labs(title = lv_name, x = x_label, y = NULL) - - p + normalize_dotplot_metric <- function(x) { + x <- match.arg(x, c("AUC", "-log10(FDR)", "log10FDR")) + if (x == "log10FDR") "-log10(FDR)" else x + } + + x.axis <- normalize_dotplot_metric(x.axis) + order.by <- normalize_dotplot_metric(order.by) + + lv_name <- if (is.numeric(lv)) paste0("LV", lv) else as.character(lv) + df <- summ[summ$LV == lv_name & + summ$AUC >= auc.cutoff & + summ$FDR <= fdr.cutoff, , drop = FALSE] + + if (nrow(df) == 0) { + message("No associations pass the thresholds for ", lv_name, ".") + return(invisible(NULL)) + } + + df$log10_fdr <- -log10(pmax(df$FDR, .Machine$double.eps)) + x_col <- if (x.axis == "AUC") "AUC" else "log10_fdr" + order_col <- if (order.by == "AUC") "AUC" else "log10_fdr" + + df <- df[order(-df[[order_col]], -df$AUC), , drop = FALSE] + df <- df[seq_len(min(top, nrow(df))), , drop = FALSE] + df$x_value <- df[[x_col]] + df$pathway_label <- make.unique(strtrim(df$pathway, max.name.len)) + df$pathway <- factor( + df$pathway_label, + levels = df$pathway_label[order(df[[order_col]], df$AUC)] + ) + + log10_fdr_min <- -log10(max(fdr.cutoff, .Machine$double.eps)) + log10_fdr_max <- max(df$log10_fdr, na.rm = TRUE) + if (log10_fdr_max <= log10_fdr_min) { + log10_fdr_max <- log10_fdr_min + 1e-6 + } + + x_baseline <- if (x.axis == "AUC") auc.cutoff else log10_fdr_min + if (x.axis == "AUC") { + x_limits <- c(max(0, auc.cutoff - 0.02), 1) + x_label <- "AUC" + } else { + x_range <- range(c(x_baseline, df$x_value), na.rm = TRUE) + x_pad <- diff(x_range) * 0.05 + if (!is.finite(x_pad) || x_pad == 0) x_pad <- 0.1 + x_limits <- c(max(0, x_range[1] - x_pad), x_range[2] + x_pad) + x_label <- "-log10(FDR)" + } + + p <- ggplot2::ggplot(df, ggplot2::aes( + x = .data$x_value, + y = .data$pathway, + colour = .data$log10_fdr + )) + + ggplot2::geom_segment( + ggplot2::aes(xend = .data$x_value, yend = .data$pathway), + x = x_baseline, + colour = "#A1D99B", + linewidth = 1 + ) + + ggplot2::geom_point(ggplot2::aes(size = .data$AUC), alpha = 0.9) + + ggplot2::scale_size_continuous( + name = "AUC", + range = c(3, 8), + limits = c(auc.cutoff, 1) + ) + + ggplot2::scale_colour_gradient( + name = "-log10(FDR)", + low = "#DCEFD8", + high = "#1B7837", + limits = c(log10_fdr_min, log10_fdr_max) + ) + + ggplot2::scale_x_continuous( + limits = x_limits, + expand = c(0, 0.01) + ) + + ggplot2::theme_minimal(base_size = 11) + + ggplot2::theme( + plot.title = ggplot2::element_text(hjust = 0.5), + axis.text.y = ggplot2::element_text(size = 9), + panel.grid.major.y = ggplot2::element_line(colour = "grey92"), + panel.grid.major.x = ggplot2::element_line(colour = "grey92"), + panel.grid.minor = ggplot2::element_blank() + ) + + ggplot2::labs(title = lv_name, x = x_label, y = NULL) + + p } #' Dot plot of pathway-LV associations across all latent variables @@ -760,83 +835,89 @@ CLAMPdotplot <- function(clampRes, lv = 1, top = 20, auc.cutoff = 0.6, #' @examples #' set.seed(9) #' pathways <- paste0("Pathway_", 1:20) -#' lvs <- paste0("LV", 1:5) -#' nr <- length(pathways) * length(lvs) +#' lvs <- paste0("LV", 1:5) +#' nr <- length(pathways) * length(lvs) #' #' summ <- data.frame( -#' pathway = rep(pathways, length(lvs)), -#' LV = rep(lvs, each = length(pathways)), -#' AUC = runif(nr, 0.5, 1.0), -#' FDR = runif(nr, 0, 0.2), -#' stringsAsFactors = FALSE +#' pathway = rep(pathways, length(lvs)), +#' LV = rep(lvs, each = length(pathways)), +#' AUC = runif(nr, 0.5, 1.0), +#' FDR = runif(nr, 0, 0.2), +#' stringsAsFactors = FALSE #' ) #' #' CLAMPdotplotAll(list(summary = summ), auc.cutoff = 0.6, fdr.cutoff = 0.15) CLAMPdotplotAll <- function(clampRes, auc.cutoff = 0.6, fdr.cutoff = 0.05, top.per.lv = NULL, max.name.len = 40) { + summ <- if (is.data.frame(clampRes)) clampRes else clampRes$summary + + if (is.null(summ)) { + stop("'clampRes' must contain a 'summary' data frame or be one itself.") + } + + if ("LV_index" %in% colnames(summ) && !"LV" %in% colnames(summ)) { + summ$LV <- paste0("LV", summ$LV_index) + } + + required <- c("pathway", "LV", "AUC", "FDR") + missing <- setdiff(required, colnames(summ)) + if (length(missing) > 0) { + stop("summary is missing columns: ", paste(missing, collapse = ", ")) + } + + df <- summ[summ$AUC >= auc.cutoff & summ$FDR <= fdr.cutoff, , drop = FALSE] + + if (nrow(df) == 0) { + message("No associations pass the AUC/FDR thresholds.") + return(invisible(NULL)) + } + + if (!is.null(top.per.lv)) { + df <- dplyr::group_by(df, .data$LV) + df <- dplyr::slice_max(df, + order_by = .data$AUC, n = top.per.lv, + with_ties = FALSE + ) + df <- dplyr::ungroup(df) + } + + df$pathway <- strtrim(df$pathway, max.name.len) + df$pathway <- factor(df$pathway, + levels = rev(unique(df$pathway[order(df$AUC)])) + ) + df$log10_fdr <- -log10(pmax(df$FDR, .Machine$double.eps)) + + log10_fdr_min <- -log10(max(fdr.cutoff, .Machine$double.eps)) + log10_fdr_max <- max(df$log10_fdr, na.rm = TRUE) + if (log10_fdr_max <= log10_fdr_min) { + log10_fdr_max <- log10_fdr_min + 1e-6 + } - summ <- if (is.data.frame(clampRes)) clampRes else clampRes$summary - - if (is.null(summ)) - stop("'clampRes' must contain a 'summary' data frame or be one itself.") - - if ("LV_index" %in% colnames(summ) && !"LV" %in% colnames(summ)) - summ$LV <- paste0("LV", summ$LV_index) - - required <- c("pathway", "LV", "AUC", "FDR") - missing <- setdiff(required, colnames(summ)) - if (length(missing) > 0) - stop("summary is missing columns: ", paste(missing, collapse = ", ")) - - df <- summ[summ$AUC >= auc.cutoff & summ$FDR <= fdr.cutoff, , drop = FALSE] - - if (nrow(df) == 0) { - message("No associations pass the AUC/FDR thresholds.") - return(invisible(NULL)) - } - - if (!is.null(top.per.lv)) { - df <- dplyr::group_by(df, .data$LV) - df <- dplyr::slice_max(df, order_by = .data$AUC, n = top.per.lv, - with_ties = FALSE) - df <- dplyr::ungroup(df) - } - - df$pathway <- strtrim(df$pathway, max.name.len) - df$pathway <- factor(df$pathway, - levels = rev(unique(df$pathway[order(df$AUC)]))) - df$log10_fdr <- -log10(pmax(df$FDR, .Machine$double.eps)) - - log10_fdr_min <- -log10(max(fdr.cutoff, .Machine$double.eps)) - log10_fdr_max <- max(df$log10_fdr, na.rm = TRUE) - if (log10_fdr_max <= log10_fdr_min) - log10_fdr_max <- log10_fdr_min + 1e-6 - - p <- ggplot2::ggplot(df, ggplot2::aes( - x = .data$LV, - y = .data$pathway, - size = .data$AUC, - colour = .data$log10_fdr - )) + - ggplot2::geom_point(alpha = 0.85) + - ggplot2::scale_size_continuous( - name = "AUC", - range = c(2, 8), - limits = c(auc.cutoff, 1) - ) + - ggplot2::scale_colour_gradient( - name = "-log10(FDR)", - low = "#DCEFD8", - high = "#1B7837", - limits = c(log10_fdr_min, log10_fdr_max) - ) + - ggplot2::theme_minimal(base_size = 11) + - ggplot2::theme( - axis.text.x = ggplot2::element_text(angle = 45, hjust = 1), - axis.text.y = ggplot2::element_text(size = 8), - panel.grid.major = ggplot2::element_line(colour = "grey92") - ) + - ggplot2::labs(x = "Latent Variable", y = "Pathway") - - p + p <- ggplot2::ggplot(df, ggplot2::aes( + x = .data$LV, + y = .data$pathway, + size = .data$AUC, + colour = .data$log10_fdr + )) + + ggplot2::geom_point(alpha = 0.85) + + ggplot2::scale_size_continuous( + name = "AUC", + range = c(2, 8), + limits = c(auc.cutoff, 1) + ) + + ggplot2::scale_colour_gradient( + name = "-log10(FDR)", + low = "#DCEFD8", + high = "#1B7837", + limits = c(log10_fdr_min, log10_fdr_max) + ) + + ggplot2::theme_minimal(base_size = 11) + + ggplot2::theme( + axis.text.x = ggplot2::element_text(angle = 45, hjust = 1), + axis.text.y = ggplot2::element_text(size = 8), + panel.grid.major = ggplot2::element_line(colour = "grey92") + ) + + ggplot2::labs(x = "Latent Variable", y = "Pathway") + + p } diff --git a/R/solvers.R b/R/solvers.R index ef4f10b..ddbac17 100644 --- a/R/solvers.R +++ b/R/solvers.R @@ -10,7 +10,7 @@ NULL #' @param p Numeric vector of p-values. #' @return Adjusted p-values. BH <- function(p) { - p.adjust(p, method = "BH") + p.adjust(p, method = "BH") } #' Row-wise correlation between two matrices @@ -22,16 +22,16 @@ BH <- function(p) { #' @param B A numeric matrix of the same dimensions as \code{A}. #' @return A numeric vector of correlations, one per row. row_cor <- function(A, B) { - A_mat <- as.matrix(A) - B_mat <- as.matrix(B) - if (!all(dim(A_mat) == dim(B_mat))) { - stop("row_cor(): dimensions of A and B must match") - } - A_centered <- A_mat - rowMeans(A_mat) - B_centered <- B_mat - rowMeans(B_mat) - num <- rowSums(A_centered * B_centered) - den <- sqrt(rowSums(A_centered^2) * rowSums(B_centered^2)) - num / den + A_mat <- as.matrix(A) + B_mat <- as.matrix(B) + if (!all(dim(A_mat) == dim(B_mat))) { + stop("row_cor(): dimensions of A and B must match") + } + A_centered <- A_mat - rowMeans(A_mat) + B_centered <- B_mat - rowMeans(B_mat) + num <- rowSums(A_centered * B_centered) + den <- sqrt(rowSums(A_centered^2) * rowSums(B_centered^2)) + num / den } #' Matrix multiplication with support for FBM objects @@ -52,13 +52,13 @@ row_cor <- function(A, B) { #' res1 <- mat_mult(mat1, mat2) #' res1 mat_mult <- function(mat1, mat2, ncores = 1) { - is_fbm <- inherits(mat1, "FBM") - if (is_fbm) { - # For FBM objects, use the specific multiplication method - return(bigstatsr::big_prodMat(mat1, as.matrix(mat2), ncores = ncores)) - } else { - return(mat1 %*% mat2) - } + is_fbm <- inherits(mat1, "FBM") + if (is_fbm) { + # For FBM objects, use the specific multiplication method + return(bigstatsr::big_prodMat(mat1, as.matrix(mat2), ncores = ncores)) + } else { + return(mat1 %*% mat2) + } } #' Ridge-regularized pseudoinverse via SVD @@ -74,16 +74,16 @@ mat_mult <- function(mat1, mat2, ncores = 1) { #' @return A numeric matrix representing the ridge-regularized #' pseudoinverse of \code{m}. pinv.ridge <- function(m, alpha = 0) { - msvd <- svd(m) - d <- msvd$d + msvd <- svd(m) + d <- msvd$d - if (length(d) == 0 || all(d == 0)) { - return(matrix(0, nrow = ncol(m), ncol = nrow(m))) - } + if (length(d) == 0 || all(d == 0)) { + return(matrix(0, nrow = ncol(m), ncol = nrow(m))) + } - d_inv <- if (alpha > 0) d / (d^2 + alpha^2) else 1 / d + d_inv <- if (alpha > 0) d / (d^2 + alpha^2) else 1 / d - msvd$v %*% (d_inv * t(msvd$u)) + msvd$v %*% (d_inv * t(msvd$u)) } #' Rotate SVD components to make dominant directions positive @@ -95,23 +95,22 @@ pinv.ridge <- function(m, alpha = 0) { #' @return A modified \code{svd}‐result list where each column of \code{$u} has been sign‐flipped #' so that its entries sum to a nonnegative value; \code{$v} is flipped correspondingly. rotateSVD <- function(svdres) { - - upos <- svdres$u - uneg <- svdres$u - upos[upos < 0] <- 0 - uneg[uneg >= 0] <- 0 - uneg <- -uneg - sumposu <- colSums(upos) - sumnegu <- colSums(uneg) - - - for (i in seq_len(ncol(svdres$u))) { - if (sumnegu[i] > sumposu[i]) { - svdres$u[, i] <- -svdres$u[, i] - svdres$v[, i] <- -svdres$v[, i] + upos <- svdres$u + uneg <- svdres$u + upos[upos < 0] <- 0 + uneg[uneg >= 0] <- 0 + uneg <- -uneg + sumposu <- colSums(upos) + sumnegu <- colSums(uneg) + + + for (i in seq_len(ncol(svdres$u))) { + if (sumnegu[i] > sumposu[i]) { + svdres$u[, i] <- -svdres$u[, i] + svdres$v[, i] <- -svdres$v[, i] + } } - } - svdres + svdres } #' Binarize matrix by top-k values per column @@ -123,15 +122,15 @@ rotateSVD <- function(svdres) { #' @param keepVals If \code{TRUE}, retains original values above the cutoff; otherwise, sets them to 1. #' @return A modified matrix with only top entries retained per column. binarizeTop <- function(Z, top, keepVals = TRUE) { - for (i in seq_len(ncol(Z))) { - cutoff <- sort(Z[, i], decreasing = TRUE)[top + 1] - if (cutoff == 0) { - cutoff <- min(Z[Z[, i] > 0, i]) - } - Z[Z[, i] < cutoff, i] <- 0 - if (!keepVals) Z[Z[, i] > 0, i] <- 1 - } - Z + for (i in seq_len(ncol(Z))) { + cutoff <- sort(Z[, i], decreasing = TRUE)[top + 1] + if (cutoff == 0) { + cutoff <- min(Z[Z[, i] > 0, i]) + } + Z[Z[, i] < cutoff, i] <- 0 + if (!keepVals) Z[Z[, i] > 0, i] <- 1 + } + Z } #' Fit the loading matrix Z using sparse regression of prior information U @@ -171,167 +170,166 @@ binarizeTop <- function(Z, top, keepVals = TRUE) { #' @examples #' set.seed(123) #' genes <- paste0("G", 1:200) -#' lvs <- paste0("LV", 1:4) +#' lvs <- paste0("LV", 1:4) #' paths <- paste0("Path", 1:60) #' #' Z <- matrix(rnorm(200 * 4), nrow = 200, dimnames = list(genes, lvs)) #' #' priorMat <- matrix(rbinom(200 * 60, 1, 0.07), -#' nrow = 200, dimnames = list(genes, paths)) +#' nrow = 200, dimnames = list(genes, paths) +#' ) #' #' fit1 <- solveU( -#' Z = Z, -#' priorMat = priorMat, -#' pathwaySelection = "fast", -#' alpha = 0.9, -#' maxPath = 10, -#' nfolds = 5, -#' binary = FALSE, -#' refit = TRUE +#' Z = Z, +#' priorMat = priorMat, +#' pathwaySelection = "fast", +#' alpha = 0.9, +#' maxPath = 10, +#' nfolds = 5, +#' binary = FALSE, +#' refit = TRUE #' ) solveU <- function( - Z, Chat = NULL, priorMat, penalty.factor, pathwaySelection = "fast", - alpha = 0.9, maxPath = 10, nfolds = 5, useSE = FALSE, top = NULL, - binary = FALSE, nlambda = 20, scale = TRUE, refit = TRUE, Uprev = NULL, useAUC=TRUE, intercept=TRUE,...) { - if (nrow(Z) != nrow(priorMat)) { - cm <- commonRows(Z, priorMat) - Z <- Z[cm, ] - iim <- match(cm, rownames(priorMat)) - priorMat <- priorMat[iim, ] - - message("matching rows") - } - if (scale) { - col_means <- Matrix::colMeans(priorMat) - col_sds <- sqrt(Matrix::colMeans(priorMat^2) - col_means^2) - col_sds[col_sds == 0] <- 1 # avoid divide-by-zero - priorMat <- Matrix::t((Matrix::t(priorMat) - col_means) / col_sds) - } - if (is.null(Chat) & !useAUC) { - Chat <- pinv.ridge(crossprod(priorMat), 5) %*% (t(priorMat)) - } - - if(!useAUC){ - Ur <- Chat %*% Z # get U by OLS - } - else{ - Ur <- t(allAgainstAllAUCs(Z, priorMat)) - } - Ur <- apply(-Ur, 2, rank) # rank - Urm <- apply(Ur, 1, min) - - # Zhat <- matrix(0, nrow = nrow(Z), ncol = ncol(Z)) - if (is.null(Uprev)) { - U <- Matrix::Matrix(0, nrow = ncol(priorMat), ncol = ncol(Z), sparse = TRUE) - # U=matrix(0,nrow=ncol(priorMat), ncol=ncol(Z)) - } else { - U <- Uprev - } - pathwaySelection <- match.arg(pathwaySelection, c("fast", "complete")) - - if (!is.null(top)) { - Znew <- binarizeTop(Z, top, keepVals = TRUE) - - Z <- Znew - } - if (pathwaySelection == "complete") { - iip <- which(Urm <= maxPath * 5) - message("Picked ", length(iip), " pathways") - } - - for (i in seq_len(ncol(Z))) { - if (all(U[, i] == 0)) { - if (var(Z[, i]) < 1e-9) { - # message("skipping") - next - } - if (pathwaySelection == "fast") { - iip <- which(Ur[, i] <= maxPath) - } - - if (!binary) { # not doing a binary prediction - gres <- cv.glmnet( - y = Z[, i], x = priorMat[, iip], alpha = alpha, lower.limits = 0, - foldid = ((seq_len(nrow(Z))) %% nfolds) + 1, keep = TRUE, nfolds = nfolds, - standardize = scale, dfmax = maxPath, nlambda = nlambda, intercept = intercept,... - ) + Z, Chat = NULL, priorMat, penalty.factor, pathwaySelection = "fast", + alpha = 0.9, maxPath = 10, nfolds = 5, useSE = FALSE, top = NULL, + binary = FALSE, nlambda = 20, scale = TRUE, refit = TRUE, Uprev = NULL, useAUC = TRUE, intercept = TRUE, ... +) { + if (nrow(Z) != nrow(priorMat)) { + cm <- commonRows(Z, priorMat) + Z <- Z[cm, ] + iim <- match(cm, rownames(priorMat)) + priorMat <- priorMat[iim, ] + + message("matching rows") + } + if (scale) { + col_means <- Matrix::colMeans(priorMat) + col_sds <- sqrt(Matrix::colMeans(priorMat^2) - col_means^2) + col_sds[col_sds == 0] <- 1 # avoid divide-by-zero + priorMat <- Matrix::t((Matrix::t(priorMat) - col_means) / col_sds) + } + if (is.null(Chat) & !useAUC) { + Chat <- pinv.ridge(crossprod(priorMat), 5) %*% (t(priorMat)) + } - # plot(gres) - } else { - gres <- cv.glmnet( - y = (Z[, i] > 0) + 1 - 1, x = priorMat[, iip], - family = "binomial", alpha = alpha, lower.limits = 0, - foldid = ((seq_len(nrow(Z))) %% nfolds) + 1, keep = FALSE, - nfolds = nfolds, type.measure = "auc", dfmax = maxPath, nlambda = nlambda, - standardize = scale, nlambda = nlambda, intercept = intercept, ... - ) - } - } # end if all U[,i]==0 - if (refit) { - if (any(U[, i] != 0)) { - selected_features <- which(U[, i] != 0) - } else { - s_best <- if (useSE) gres$lambda.1se else gres$lambda.min - active_coef <- coef(gres, s = s_best) - active_ix <- which(active_coef[-1] != 0) - selected_features <- iip[active_ix] - } - - if (length(selected_features) == 0) { - next - } - X_sel <- priorMat[, selected_features, drop = FALSE] - - # Add dummy column if only one predictor - add_dummy <- ncol(X_sel) == 1 - if (add_dummy) { - X_sel <- cbind(X_sel, dummy = 0) - } - - # Fit relaxed model - if (!binary) { - fit_relaxed <- glmnet(X_sel, Z[, i], - alpha = 0, lambda = 0, - lower.limits = 0, standardize = scale - ) - coefs <- as.vector(coef(fit_relaxed))[-1] - if (add_dummy) coefs <- coefs[-length(coefs)] - U[selected_features, i] <- coefs - # Zhat[, i] <- predict(fit_relaxed, newx = X_sel, s = 0)[,1] - } else { - fit_relaxed <- glmnet(X_sel, (Z[, i] > 0) + 0, - family = "binomial", alpha = 0, lambda = 0, - lower.limits = 0, standardize = scale - ) - coefs <- as.vector(coef(fit_relaxed))[-1] - if (add_dummy) coefs <- coefs[-length(coefs)] - U[selected_features, i] <- coefs - # Zhat[, i] <- predict(fit_relaxed, newx = X_sel, s = 0, type = "response")[,1] - } + if (!useAUC) { + Ur <- Chat %*% Z # get U by OLS } else { + Ur <- t(allAgainstAllAUCs(Z, priorMat)) + } + Ur <- apply(-Ur, 2, rank) # rank + Urm <- apply(Ur, 1, min) + + # Zhat <- matrix(0, nrow = nrow(Z), ncol = ncol(Z)) + if (is.null(Uprev)) { + U <- Matrix::Matrix(0, nrow = ncol(priorMat), ncol = ncol(Z), sparse = TRUE) + # U=matrix(0,nrow=ncol(priorMat), ncol=ncol(Z)) + } else { + U <- Uprev + } + pathwaySelection <- match.arg(pathwaySelection, c("fast", "complete")) + if (!is.null(top)) { + Znew <- binarizeTop(Z, top, keepVals = TRUE) - s_best <- if (useSE) gres$lambda.1se else gres$lambda.min - coef_vec <- as.vector(coef(gres, s = s_best))[-1] # drop intercept - betaI <- which(coef_vec != 0) - U[iip[betaI], i] <- coef_vec[betaI] + Z <- Znew + } + if (pathwaySelection == "complete") { + iip <- which(Urm <= maxPath * 5) + message("Picked ", length(iip), " pathways") + } + + for (i in seq_len(ncol(Z))) { + if (all(U[, i] == 0)) { + if (var(Z[, i]) < 1e-9) { + # message("skipping") + next + } + if (pathwaySelection == "fast") { + iip <- which(Ur[, i] <= maxPath) + } + + if (!binary) { # not doing a binary prediction + gres <- cv.glmnet( + y = Z[, i], x = priorMat[, iip], alpha = alpha, lower.limits = 0, + foldid = ((seq_len(nrow(Z))) %% nfolds) + 1, keep = TRUE, nfolds = nfolds, + standardize = scale, dfmax = maxPath, nlambda = nlambda, intercept = intercept, ... + ) + + # plot(gres) + } else { + gres <- cv.glmnet( + y = (Z[, i] > 0) + 1 - 1, x = priorMat[, iip], + family = "binomial", alpha = alpha, lower.limits = 0, + foldid = ((seq_len(nrow(Z))) %% nfolds) + 1, keep = FALSE, + nfolds = nfolds, type.measure = "auc", dfmax = maxPath, nlambda = nlambda, + standardize = scale, nlambda = nlambda, intercept = intercept, ... + ) + } + } # end if all U[,i]==0 + if (refit) { + if (any(U[, i] != 0)) { + selected_features <- which(U[, i] != 0) + } else { + s_best <- if (useSE) gres$lambda.1se else gres$lambda.min + active_coef <- coef(gres, s = s_best) + active_ix <- which(active_coef[-1] != 0) + selected_features <- iip[active_ix] + } + + if (length(selected_features) == 0) { + next + } + X_sel <- priorMat[, selected_features, drop = FALSE] + + # Add dummy column if only one predictor + add_dummy <- ncol(X_sel) == 1 + if (add_dummy) { + X_sel <- cbind(X_sel, dummy = 0) + } + + # Fit relaxed model + if (!binary) { + fit_relaxed <- glmnet(X_sel, Z[, i], + alpha = 0, lambda = 0, + lower.limits = 0, standardize = scale + ) + coefs <- as.vector(coef(fit_relaxed))[-1] + if (add_dummy) coefs <- coefs[-length(coefs)] + U[selected_features, i] <- coefs + # Zhat[, i] <- predict(fit_relaxed, newx = X_sel, s = 0)[,1] + } else { + fit_relaxed <- glmnet(X_sel, (Z[, i] > 0) + 0, + family = "binomial", alpha = 0, lambda = 0, + lower.limits = 0, standardize = scale + ) + coefs <- as.vector(coef(fit_relaxed))[-1] + if (add_dummy) coefs <- coefs[-length(coefs)] + U[selected_features, i] <- coefs + # Zhat[, i] <- predict(fit_relaxed, newx = X_sel, s = 0, type = "response")[,1] + } + } else { + s_best <- if (useSE) gres$lambda.1se else gres$lambda.min + coef_vec <- as.vector(coef(gres, s = s_best))[-1] # drop intercept + betaI <- which(coef_vec != 0) + U[iip[betaI], i] <- coef_vec[betaI] + } + # end for i in Z } - # end for i in Z - } - # message(sprintf(", Number of annotated columns is %d", sum(Matrix::colSums(U) > 0))) - # rownames(U)=substr(colnames(priorMat),1,30) - rownames(U) <- colnames(priorMat) - colnames(U) <- colnames(Z) - #flag this for dicussion - U <- as.matrix(U) + # message(sprintf(", Number of annotated columns is %d", sum(Matrix::colSums(U) > 0))) + # rownames(U)=substr(colnames(priorMat),1,30) + rownames(U) <- colnames(priorMat) + colnames(U) <- colnames(Z) + # flag this for dicussion + U <- as.matrix(U) - return(list(U = U)) + return(list(U = U)) - message("Number of annotated columns is ", sum(Matrix::colSums(U) > 0)) + message("Number of annotated columns is ", sum(Matrix::colSums(U) > 0)) - rownames(U) <- colnames(priorMat) - colnames(U) <- paste0("LV", seq_len(ncol(U))) - return(U) + rownames(U) <- colnames(priorMat) + colnames(U) <- paste0("LV", seq_len(ncol(U))) + return(U) } #' Compute Chat matrix from prior annotation @@ -362,18 +360,18 @@ solveU <- function( #' Chat <- getChat(priorMat) #' @export getChat <- function(priorMat, scale = TRUE) { - if (scale) { - col_means <- Matrix::colMeans(priorMat) - col_sds <- sqrt(Matrix::colMeans(priorMat^2) - col_means^2) - col_sds[col_sds == 0] <- 1 - priorMat <- Matrix::t((Matrix::t(priorMat) - col_means) / col_sds) - } - - message("Inverting...") - Chat <- pinv.ridge(crossprod(priorMat), 5) %*% t(priorMat) - - message("done") - Chat + if (scale) { + col_means <- Matrix::colMeans(priorMat) + col_sds <- sqrt(Matrix::colMeans(priorMat^2) - col_means^2) + col_sds[col_sds == 0] <- 1 + priorMat <- Matrix::t((Matrix::t(priorMat) - col_means) / col_sds) + } + + message("Inverting...") + Chat <- pinv.ridge(crossprod(priorMat), 5) %*% t(priorMat) + + message("done") + Chat } #' Subset and filter pathway matrix to match target genes #' @@ -403,23 +401,23 @@ getChat <- function(priorMat, scale = TRUE) { #' filtered <- getMatchedPathwayMat(pathMat, new.genes, min.genes = 2) #' @export getMatchedPathwayMat <- function(pathMat, new.genes, min.genes = 10) { - cm <- intersect(rownames(pathMat), new.genes) - mymessage("There are ", length(cm), " genes in the intersection between data and prior") - - matchPathMat <- Matrix::sparseMatrix( - i = match(cm, new.genes), - j = rep(1, length(cm)), # temporary, will be overwritten below - dims = c(length(new.genes), ncol(pathMat)), - x = 0, # fill with zeros for now - dimnames = list(new.genes, colnames(pathMat)) - ) - matchPathMat[cm, ] <- pathMat[cm, ] - - genesInPath <- Matrix::colSums(matchPathMat) - ii <- which(genesInPath >= min.genes) - message(sprintf("Removing %d pathways", ncol(matchPathMat) - length(ii))) - - matchPathMat[, ii] + cm <- intersect(rownames(pathMat), new.genes) + mymessage("There are ", length(cm), " genes in the intersection between data and prior") + + matchPathMat <- Matrix::sparseMatrix( + i = match(cm, new.genes), + j = rep(1, length(cm)), # temporary, will be overwritten below + dims = c(length(new.genes), ncol(pathMat)), + x = 0, # fill with zeros for now + dimnames = list(new.genes, colnames(pathMat)) + ) + matchPathMat[cm, ] <- pathMat[cm, ] + + genesInPath <- Matrix::colSums(matchPathMat) + ii <- which(genesInPath >= min.genes) + message(sprintf("Removing %d pathways", ncol(matchPathMat) - length(ii))) + + matchPathMat[, ii] } #' Subset and filter multiple pathway matrices to match target genes @@ -434,34 +432,34 @@ getMatchedPathwayMat <- function(pathMat, new.genes, min.genes = 10) { #' #' @return A sparse matrix with rows = \code{new.genes} and columns = filtered pathways from all inputs. getMatchedPathwayMat2 <- function(..., new.genes, min.genes = 10) { - pathMats <- list(...) - - filtered <- lapply(pathMats, function(pathMat) { - cm <- intersect(rownames(pathMat), new.genes) - message("There are ", length(cm), " genes in the intersection between data and prior") - - matchPathMat <- Matrix::sparseMatrix( - i = match(cm, new.genes), - j = rep(1, length(cm)), # temporary - dims = c(length(new.genes), ncol(pathMat)), - x = 0, - dimnames = list(new.genes, colnames(pathMat)) - ) - matchPathMat[cm, ] <- pathMat[cm, ] + pathMats <- list(...) + + filtered <- lapply(pathMats, function(pathMat) { + cm <- intersect(rownames(pathMat), new.genes) + message("There are ", length(cm), " genes in the intersection between data and prior") + + matchPathMat <- Matrix::sparseMatrix( + i = match(cm, new.genes), + j = rep(1, length(cm)), # temporary + dims = c(length(new.genes), ncol(pathMat)), + x = 0, + dimnames = list(new.genes, colnames(pathMat)) + ) + matchPathMat[cm, ] <- pathMat[cm, ] - genesInPath <- Matrix::colSums(matchPathMat) + genesInPath <- Matrix::colSums(matchPathMat) - ii <- which(genesInPath >= min.genes) + ii <- which(genesInPath >= min.genes) - message(sprintf("Removing %d pathways", ncol(matchPathMat) - length(ii))) + message(sprintf("Removing %d pathways", ncol(matchPathMat) - length(ii))) - matchPathMat[, ii, drop = FALSE] - }) + matchPathMat[, ii, drop = FALSE] + }) - if (length(filtered) == 1) { - return(filtered[[1]]) - } - do.call(Matrix::cBind, filtered) + if (length(filtered) == 1) { + return(filtered[[1]]) + } + do.call(Matrix::cBind, filtered) } #' Subset and filter pathway matrix to match target genes @@ -477,23 +475,23 @@ getMatchedPathwayMat2 <- function(..., new.genes, min.genes = 10) { #' #' @return A sparse matrix of dimensions \code{length(new.genes)} x filtered pathways. getMatchedPathwayMatOld <- function(pathMat, new.genes, min.genes = 10) { - cm <- intersect(rownames(pathMat), new.genes) - mymessage("There are ", length(cm), " genes in the intersection between data and prior") - - matchPathMat <- Matrix::sparseMatrix( - i = match(cm, new.genes), - j = rep(1, length(cm)), # temporary, will be overwritten below - dims = c(length(new.genes), ncol(pathMat)), - x = 0, # fill with zeros for now - dimnames = list(new.genes, colnames(pathMat)) - ) - matchPathMat[cm, ] <- pathMat[cm, ] - - genesInPath <- Matrix::colSums(matchPathMat) - ii <- which(genesInPath >= min.genes) - message(sprintf("Removing %d pathways", ncol(matchPathMat) - length(ii))) - - matchPathMat[, ii] + cm <- intersect(rownames(pathMat), new.genes) + mymessage("There are ", length(cm), " genes in the intersection between data and prior") + + matchPathMat <- Matrix::sparseMatrix( + i = match(cm, new.genes), + j = rep(1, length(cm)), # temporary, will be overwritten below + dims = c(length(new.genes), ncol(pathMat)), + x = 0, # fill with zeros for now + dimnames = list(new.genes, colnames(pathMat)) + ) + matchPathMat[cm, ] <- pathMat[cm, ] + + genesInPath <- Matrix::colSums(matchPathMat) + ii <- which(genesInPath >= min.genes) + message(sprintf("Removing %d pathways", ncol(matchPathMat) - length(ii))) + + matchPathMat[, ii] } #' Compute AUC using Wilcoxon rank-sum test @@ -511,10 +509,10 @@ getMatchedPathwayMatOld <- function(pathMat, new.genes, min.genes = 10) { #' \item{\code{pval}}{Wilcoxon test p-value, or \code{NA} if one class is missing} #' } AUC <- function(labels, values) { - pos <- labels > 0 - neg <- !pos - posn <- sum(pos) - negn <- sum(neg) + pos <- labels > 0 + neg <- !pos + posn <- sum(pos) + negn <- sum(neg) if (posn > 0 && negn > 0) { res <- stats::wilcox.test(values[pos], values[neg], @@ -526,7 +524,7 @@ AUC <- function(labels, values) { auc <- 0.5 pval <- NA } - list(auc = auc, pval = pval, npos=posn, nneg=negn) + list(auc = auc, pval = pval, npos = posn, nneg = negn) } #' Cross-validation AUC for CLAMP latent variables and pathways @@ -546,44 +544,44 @@ AUC <- function(labels, values) { #' \item{\code{summary}}{Data frame with pathway, LV index, AUC, p-value, and FDR} #' } crossVal <- function(clampRes, priorMat, priorMatcv) { - ii <- which(Matrix::colSums(clampRes$U) > 0) + ii <- which(Matrix::colSums(clampRes$U) > 0) - Uauc <- Matrix::Matrix(0, nrow = nrow(clampRes$U), ncol = ncol(clampRes$U), sparse = TRUE) - Up <- Matrix::Matrix(0, nrow = nrow(clampRes$U), ncol = ncol(clampRes$U), sparse = TRUE) + Uauc <- Matrix::Matrix(0, nrow = nrow(clampRes$U), ncol = ncol(clampRes$U), sparse = TRUE) + Up <- Matrix::Matrix(0, nrow = nrow(clampRes$U), ncol = ncol(clampRes$U), sparse = TRUE) - results <- list() + results <- list() - for (i in ii) { - iipath <- which(clampRes$U[, i] > 0) + for (i in ii) { + iipath <- which(clampRes$U[, i] > 0) - for (j in iipath) { - iiheldout <- which((rowSums(priorMat[, iipath, drop = FALSE]) == 0) | - (priorMat[, j] > 0 & priorMatcv[, j] == 0)) + for (j in iipath) { + iiheldout <- which((rowSums(priorMat[, iipath, drop = FALSE]) == 0) | + (priorMat[, j] > 0 & priorMatcv[, j] == 0)) - aucres <- AUC(priorMat[iiheldout, j], clampRes$Z[iiheldout, i]) + aucres <- AUC(priorMat[iiheldout, j], clampRes$Z[iiheldout, i]) - results[[length(results) + 1]] <- data.frame( - pathway = colnames(priorMat)[j], - LV = paste0("LV", i), - AUC = as.numeric(aucres$auc), - p_value = as.numeric(aucres$pval), - FDR = NA_real_, - npos = aucres$npos, - nneg = aucres$nneg, - stringsAsFactors = FALSE - ) + results[[length(results) + 1]] <- data.frame( + pathway = colnames(priorMat)[j], + LV = paste0("LV", i), + AUC = as.numeric(aucres$auc), + p_value = as.numeric(aucres$pval), + FDR = NA_real_, + npos = aucres$npos, + nneg = aucres$nneg, + stringsAsFactors = FALSE + ) - Uauc[j, i] <- aucres$auc - Up[j, i] <- -log10(aucres$pval) + Uauc[j, i] <- aucres$auc + Up[j, i] <- -log10(aucres$pval) + } } - } - out <- do.call(rbind, results) - out$FDR <- as.numeric(BH(out$p_value)) - out$AUC <- as.numeric(out$AUC) + out <- do.call(rbind, results) + out$FDR <- as.numeric(BH(out$p_value)) + out$AUC <- as.numeric(out$AUC) - return(list(Uauc = Uauc, Upval = Up, summary = out)) + return(list(Uauc = Uauc, Upval = Up, summary = out)) } #' CLAMP base matrix factorization @@ -646,163 +644,165 @@ crossVal <- function(clampRes, priorMat, priorMatcv) { #' #' @export CLAMPbase <- function( - Y, clamp_k = NULL, svd_k = NULL, svdres = NULL, L1 = NULL, L2 = NULL, - Zpos = TRUE, max.iter = 200, tol = 5e-4, trace = FALSE, - rseed = NULL, B = NULL, scale = 1, pos.adj = 3, adaptive.p = 0.05, adaptive.iter = 20, - cutoff = 0, ncores = 1, clamp_k_method = "elbow") { - if (ncores > 1) { - # if we are parallelizing, then disable BLAS parallelization - options(bigstatsr.check.parallel.blas = FALSE) - blas_nproc <- getOption("default.nproc.blas") - options(default.nproc.blas = NULL) - } - - # message("Checking type") - # Detect matrix type - is_fbm <- inherits(Y, "FBM") - is_sparse <- inherits(Y, "dgCMatrix") - - ng <- nrow(Y) - ns <- ncol(Y) - - Bdiff <- Inf - BdiffTrace <- double() - BdiffCount <- 0 - message("****") - - if (is.null(svd_k)) { - svd_k <- select_svd_k(Y) - if (!is.null(clamp_k)) svd_k <- max(svd_k, clamp_k) - } - - if (is.null(svdres) && is.null(B)) { - message("Computing SVD") - svdres <- compute_svd(Y, k = svd_k) - } - - svdres <- rotateSVD(svdres) - - if(is.null(clamp_k)){ - auto <- select_clamp_k(svdres, n_samples = ncol(Y), svd_k = svd_k, - method = clamp_k_method, data = Y) - clamp_k <- auto$clamp_k - d <- auto$scale - } else { - d <- svdres$d[clamp_k] - } - - message("CLAMP k is set to ", clamp_k) - - if (is.null(L1)) { - # L1 <- svdres$d[k] * scale - L1 <- d * scale - if (!is.null(pos.adj)) { - L1 <- L1 / pos.adj - } - } - - if (is.null(L2)) { - # L2 <- svdres$d[k] * scale - L2 <- d * scale - } - - L2k <- L2 * diag(clamp_k) - # L1 <- svdres$d[k]/2*scale - message("L1 is set to ", L1) - message("L2 is set to ", L2) - - if (is.null(B)) { - # initialize B with svd - - B <- t(svdres$v[, seq_len(clamp_k)] %*% diag(sqrt(svdres$d[seq_len(clamp_k)]))) - - # alternative initializations - # seem to be not as good - # B <- t(svdres$v[seq_len(ncol(Y)), seq_len(k)] %*% diag(svdres$d[seq_len(k)])) - # B <- t(svdres$v[seq_len(ncol(Y)), seq_len(k)]) - } else { - message("B given") - } - - if (!is.null(rseed)) { - message("Using random start") - B <- t(apply(B, 1, sample)) - } - - round2 <- function(x) { - signif(x, 4) - } - - getT <- function(x) { - -quantile(x[x < 0], adaptive.p) - } - - for (i in seq_len(max.iter)) { - # main loop - Zraw <- Z <- mat_mult(Y, t(B), ncores = ncores) %*% solve(tcrossprod(B) + L1 * diag(clamp_k)) - - if (i >= adaptive.iter && adaptive.p > 0) { - cutoffs <- apply(Zraw, 2, getT) - - for (j in seq_len(ncol(Z))) { - Z[Z[, j] < cutoffs[j], j] <- 0 - } - } else if (Zpos) { - Z[Z < cutoff] <- 0 + Y, clamp_k = NULL, svd_k = NULL, svdres = NULL, L1 = NULL, L2 = NULL, + Zpos = TRUE, max.iter = 200, tol = 5e-4, trace = FALSE, + rseed = NULL, B = NULL, scale = 1, pos.adj = 3, adaptive.p = 0.05, adaptive.iter = 20, + cutoff = 0, ncores = 1, clamp_k_method = "elbow" +) { + if (ncores > 1) { + # if we are parallelizing, then disable BLAS parallelization + options(bigstatsr.check.parallel.blas = FALSE) + blas_nproc <- getOption("default.nproc.blas") + options(default.nproc.blas = NULL) } - oldB <- B + # message("Checking type") + # Detect matrix type + is_fbm <- inherits(Y, "FBM") + is_sparse <- inherits(Y, "dgCMatrix") - if (is_fbm) { - ZYt <- big_cprodMat(Y, as.matrix(Z), ncores = ncores) - ZY <- Matrix::t(ZYt) - B <- solve(Matrix::t(Z) %*% Z + L2k) %*% ZY + ng <- nrow(Y) + ns <- ncol(Y) + + Bdiff <- Inf + BdiffTrace <- double() + BdiffCount <- 0 + message("****") + + if (is.null(svd_k)) { + svd_k <- select_svd_k(Y) + if (!is.null(clamp_k)) svd_k <- max(svd_k, clamp_k) + } + + if (is.null(svdres) && is.null(B)) { + message("Computing SVD") + svdres <- compute_svd(Y, k = svd_k) + } + + svdres <- rotateSVD(svdres) + + if (is.null(clamp_k)) { + auto <- select_clamp_k(svdres, + n_samples = ncol(Y), svd_k = svd_k, + method = clamp_k_method, data = Y + ) + clamp_k <- auto$clamp_k + d <- auto$scale } else { - B <- solve(Matrix::t(Z) %*% Z + L2k) %*% mat_mult(Matrix::t(Z), Y, ncores = ncores) + d <- svdres$d[clamp_k] } - # update error - Bdiff <- sum((B - oldB)^2) / sum(B^2) + message("CLAMP k is set to ", clamp_k) - # keeping track of this in case this can be useful for convergence - minCor <- min(row_cor(B, oldB)) + if (is.null(L1)) { + # L1 <- svdres$d[k] * scale + L1 <- d * scale + if (!is.null(pos.adj)) { + L1 <- L1 / pos.adj + } + } - BdiffTrace <- c(BdiffTrace, Bdiff) + if (is.null(L2)) { + # L2 <- svdres$d[k] * scale + L2 <- d * scale + } - if (trace) { - message(sprintf("\rProgress %d / %d | Bdiff=%.6f, minCor=%.6f", i, max.iter, Bdiff, minCor)) - flush.console() + L2k <- L2 * diag(clamp_k) + # L1 <- svdres$d[k]/2*scale + message("L1 is set to ", L1) + message("L2 is set to ", L2) + + if (is.null(B)) { + # initialize B with svd + + B <- t(svdres$v[, seq_len(clamp_k)] %*% diag(sqrt(svdres$d[seq_len(clamp_k)]))) + + # alternative initializations + # seem to be not as good + # B <- t(svdres$v[seq_len(ncol(Y)), seq_len(k)] %*% diag(svdres$d[seq_len(k)])) + # B <- t(svdres$v[seq_len(ncol(Y)), seq_len(k)]) + } else { + message("B given") } - # check for convergence - if (i > 52 && Bdiff > BdiffTrace[i - 50]) { - BdiffCount <- BdiffCount + 1 - } else if (BdiffCount > 1) { - BdiffCount <- BdiffCount - 1 + if (!is.null(rseed)) { + message("Using random start") + B <- t(apply(B, 1, sample)) } - if (Bdiff < tol && i > adaptive.iter + 10) { - message(sprintf("Converged at iteration= %d | Bdiff=%.6f, tol=%.6f ", i, Bdiff, tol)) - break + round2 <- function(x) { + signif(x, 4) } - if (BdiffCount > 5 && i > adaptive.iter + 10) { - message("stopped at iteration ", i, " Bdiff is not decreasing") - break + + getT <- function(x) { + -quantile(x[x < 0], adaptive.p) } - } - rownames(B) <- colnames(Z) <- paste0("LV", seq_len(clamp_k)) - if (!is.null(rownames(Y))) rownames(Z) <- rownames(Y) - if (!is.null(colnames(Y))) colnames(B) <- colnames(Y) + for (i in seq_len(max.iter)) { + # main loop + Zraw <- Z <- mat_mult(Y, t(B), ncores = ncores) %*% solve(tcrossprod(B) + L1 * diag(clamp_k)) + + if (i >= adaptive.iter && adaptive.p > 0) { + cutoffs <- apply(Zraw, 2, getT) + + for (j in seq_len(ncol(Z))) { + Z[Z[, j] < cutoffs[j], j] <- 0 + } + } else if (Zpos) { + Z[Z < cutoff] <- 0 + } + + oldB <- B + + if (is_fbm) { + ZYt <- big_cprodMat(Y, as.matrix(Z), ncores = ncores) + ZY <- Matrix::t(ZYt) + B <- solve(Matrix::t(Z) %*% Z + L2k) %*% ZY + } else { + B <- solve(Matrix::t(Z) %*% Z + L2k) %*% mat_mult(Matrix::t(Z), Y, ncores = ncores) + } + + # update error + Bdiff <- sum((B - oldB)^2) / sum(B^2) - if (ncores > 1) { - # restore previous state - options(bigstatsr.check.parallel.blas = TRUE) - options(default.nproc.blas = blas_nproc) - } + # keeping track of this in case this can be useful for convergence + minCor <- min(row_cor(B, oldB)) - return(list(B = as.matrix(B), Z = as.matrix(Z), Zraw = Zraw, L1 = L1, L2 = L2)) + BdiffTrace <- c(BdiffTrace, Bdiff) + if (trace) { + message(sprintf("\rProgress %d / %d | Bdiff=%.6f, minCor=%.6f", i, max.iter, Bdiff, minCor)) + flush.console() + } + + # check for convergence + if (i > 52 && Bdiff > BdiffTrace[i - 50]) { + BdiffCount <- BdiffCount + 1 + } else if (BdiffCount > 1) { + BdiffCount <- BdiffCount - 1 + } + + if (Bdiff < tol && i > adaptive.iter + 10) { + message(sprintf("Converged at iteration= %d | Bdiff=%.6f, tol=%.6f ", i, Bdiff, tol)) + break + } + if (BdiffCount > 5 && i > adaptive.iter + 10) { + message("stopped at iteration ", i, " Bdiff is not decreasing") + break + } + } + + rownames(B) <- colnames(Z) <- paste0("LV", seq_len(clamp_k)) + if (!is.null(rownames(Y))) rownames(Z) <- rownames(Y) + if (!is.null(colnames(Y))) colnames(B) <- colnames(Y) + + if (ncores > 1) { + # restore previous state + options(bigstatsr.check.parallel.blas = TRUE) + options(default.nproc.blas = blas_nproc) + } + + return(list(B = as.matrix(B), Z = as.matrix(Z), Zraw = Zraw, L1 = L1, L2 = L2)) } #' Full CLAMP model with prior information and cross-validation @@ -884,329 +884,331 @@ CLAMPbase <- function( #' ) #' @export CLAMPfullnVP <- function( - Y, priorMat, svdres = NULL, clamp.base.result = NULL, clamp_k = NULL, - svd_k = NULL, L1 = NULL, L2 = NULL, top = NULL, cvn = 5, max.iter = 350, trace = FALSE, Chat = NULL, maxPath = 10, doCrossval = TRUE, - penalty.factor = rep(1, ncol(priorMat)), glm_alpha = 0.9, - minGenes = 10, tol = 5e-4, seed = 123456, allGenes = FALSE, rseed = NULL, - max.U.updates = 5, pathwaySelection = c("fast"), multiplier = 1, - adaptive.p = 0.05, useNNLS = TRUE, useRaw = TRUE, refitAll = FALSE, useSE = FALSE, ncores = 1, - clamp_k_method = "elbow") { - - if (ncores > 1) { - # if we are parallelizing, then disable BLAS parallelization - options(bigstatsr.check.parallel.blas = FALSE) - blas_nproc <- getOption("default.nproc.blas") - options(default.nproc.blas = NULL) - } - - getT <- function(x) { - -quantile(x[x < 0], adaptive.p) - } - - pathwaySelection <- match.arg(pathwaySelection, c("complete", "fast")) - - priorMat <- as.matrix(priorMat) - - message("**CLAMPfullnVP v2 **") - - # Detect matrix type - is_fbm <- inherits(Y, "FBM") - is_sparse <- inherits(Y, "dgCMatrix") - - if (nrow(priorMat) != nrow(Y) || !all(rownames(priorMat) == rownames(Y))) { - if (!allGenes) { - cm <- commonRows(Y, priorMat) - message("Selecting common genes: ", length(cm)) - priorMat <- priorMat[cm, ] - Y <- Y[cm, ] - } else { - extra.genes <- setdiff(rownames(Y), rownames(priorMat)) - eMat <- matrix(0, nrow = length(extra.genes), ncol = ncol(priorMat)) - rownames(eMat) <- extra.genes - priorMat <- rbind(priorMat, eMat) - priorMat <- priorMat[rownames(Y), ] - } - } - - numGenes <- Matrix::colSums(priorMat) - - heldOutGenes <- list() - iibad <- which(numGenes < minGenes) - if (length(iibad) > 0) { - priorMat <- priorMat[, -iibad] - message("Removed ", length(iibad), " pathways with too few genes") - } - if (doCrossval) { - priorMatCV <- as.matrix(priorMat) - if (!is.null(seed)) { - warning("`seed` is deprecated and ignored. Use set.seed(seed) before calling this function.", - call. = FALSE - ) - } - for (j in seq_len(ncol(priorMatCV))) { - iipos <- which(priorMatCV[, j] > 0) - iiposs <- sample(iipos, length(iipos) / 5) - priorMatCV[iiposs, j] <- 0 - heldOutGenes[[colnames(priorMat)[j]]] <- rownames(priorMat)[iiposs] - } - C <- priorMatCV - } else { - C <- priorMat - } - - nc <- ncol(priorMat) - ng <- nrow(Y) - ns <- ncol(Y) - - Bdiff <- -1 - BdiffTrace <- double() - BdiffCount <- 0 - - # YsqSum=sum(Y^2) - # compute svd and use that as the starting point - - if (!is.null(svdres) && nrow(svdres$v) != ncol(Y)) { - message("SVD V has the wrong number of columns") - svdres <- NULL - } - - if (is.null(svd_k) && is.null(clamp.base.result)) { - svd_k <- select_svd_k(Y) - if (!is.null(clamp_k)) svd_k <- max(svd_k, clamp_k) - } - - if (is.null(svdres) && is.null(clamp.base.result)) { - message("Computing SVD") - svdres <- compute_svd(Y, k = svd_k) - } - - if (is.null(svdres) && is.null(clamp.base.result)) { - svdres <- rotateSVD(svdres) - } - - if(is.null(clamp.base.result)){ - auto <- select_clamp_k(svdres, n_samples = ncol(Y), svd_k = svd_k, - method = clamp_k_method, data = Y) - clamp_k <- auto$clamp_k - d <- auto$scale - } else { - d <- svdres$d[clamp_k] - } - - if (is.null(clamp.base.result)) { - message("Running CLAMPbase") - clamp.base.result <- CLAMPbase(Y, clamp_k = clamp_k, svdres = svdres) - } else { - message("using provided CLAMPbase result") - if (nrow(Y) != nrow(clamp.base.result$Z)) { - if (is.null(rownames(Y)) | is.null(rownames(clamp.base.result$Z))) { - stop("Y and clamp.base.result$Z must have equal row numbers or row names") - } - clamp.base.result$Z <- clamp.base.result$Z[rownames(Y), ] - } - clamp_k <- ncol(clamp.base.result$Z) - } - - message("CLAMP k is set to ", clamp_k) - - Z <- clamp.base.result$Z - - if (is.null(L1)) { - L1 <- clamp.base.result$L1 - } - if (is.null(L2)) { - L2 <- clamp.base.result$L2 - } - L1 <- L1 * multiplier - L2 <- L2 / multiplier - message("L1=", L1, "; L2=", L2) - - if (ncol(clamp.base.result$B) == ncol(Y)) { - B <- clamp.base.result$B - } - - oldB <- B - - if (!is.null(rseed)) { - message("Using random start") - # reproducibility is controlled by user calling set.seed before this function - B <- t(apply(B, 1, sample)) - Z <- apply(Z, 2, sample) - } - - U <- matrix(0, nrow = ncol(C), ncol = clamp_k) - - round2 <- function(x) { - signif(x, 4) - } - - u.iter <- 2 - curfrac <- 0 - nposlast <- Inf - npos <- -Inf - num.U.updates <- 0 - L1k <- L1 * diag(clamp_k) - L2k <- L2 * diag(clamp_k) - - if (is_fbm) { - ZYt <- big_cprodMat(Y, as.matrix(Z), ncores = ncores) - ZY <- Matrix::t(ZYt) - B <- solve(Matrix::t(Z) %*% Z + L2k) %*% ZY - } else { - B <- solve(Matrix::t(Z) %*% Z + L2k) %*% mat_mult(Matrix::t(Z), Y, ncores = ncores) - } - - Zraw <- Z - Z2 <- matrix(0, nrow = nrow(Z), ncol = ncol(Z)) - - B <- as.matrix(B) - - for (iter in seq_len(max.iter)) { - if (iter >= u.iter) { #actually do a U iteration - if (num.U.updates < max.U.updates & iter %% 2 == 1) { - # Updating U - if (any(Zraw < 0)) { - stop() - } - if (refitAll || num.U.updates %% 5 == 0) { - Uprev <- NULL - # mRefitting all U coefficinets + Y, priorMat, svdres = NULL, clamp.base.result = NULL, clamp_k = NULL, + svd_k = NULL, L1 = NULL, L2 = NULL, top = NULL, cvn = 5, max.iter = 350, trace = FALSE, Chat = NULL, maxPath = 10, doCrossval = TRUE, + penalty.factor = rep(1, ncol(priorMat)), glm_alpha = 0.9, + minGenes = 10, tol = 5e-4, seed = 123456, allGenes = FALSE, rseed = NULL, + max.U.updates = 5, pathwaySelection = c("fast"), multiplier = 1, + adaptive.p = 0.05, useNNLS = TRUE, useRaw = TRUE, refitAll = FALSE, useSE = FALSE, ncores = 1, + clamp_k_method = "elbow" +) { + if (ncores > 1) { + # if we are parallelizing, then disable BLAS parallelization + options(bigstatsr.check.parallel.blas = FALSE) + blas_nproc <- getOption("default.nproc.blas") + options(default.nproc.blas = NULL) + } + + getT <- function(x) { + -quantile(x[x < 0], adaptive.p) + } + + pathwaySelection <- match.arg(pathwaySelection, c("complete", "fast")) + + priorMat <- as.matrix(priorMat) + + message("**CLAMPfullnVP v2 **") + + # Detect matrix type + is_fbm <- inherits(Y, "FBM") + is_sparse <- inherits(Y, "dgCMatrix") + + if (nrow(priorMat) != nrow(Y) || !all(rownames(priorMat) == rownames(Y))) { + if (!allGenes) { + cm <- commonRows(Y, priorMat) + message("Selecting common genes: ", length(cm)) + priorMat <- priorMat[cm, ] + Y <- Y[cm, ] } else { - Uprev <- U + extra.genes <- setdiff(rownames(Y), rownames(priorMat)) + eMat <- matrix(0, nrow = length(extra.genes), ncol = ncol(priorMat)) + rownames(eMat) <- extra.genes + priorMat <- rbind(priorMat, eMat) + priorMat <- priorMat[rownames(Y), ] + } + } + + numGenes <- Matrix::colSums(priorMat) + + heldOutGenes <- list() + iibad <- which(numGenes < minGenes) + if (length(iibad) > 0) { + priorMat <- priorMat[, -iibad] + message("Removed ", length(iibad), " pathways with too few genes") + } + if (doCrossval) { + priorMatCV <- as.matrix(priorMat) + if (!is.null(seed)) { + warning("`seed` is deprecated and ignored. Use set.seed(seed) before calling this function.", + call. = FALSE + ) + } + for (j in seq_len(ncol(priorMatCV))) { + iipos <- which(priorMatCV[, j] > 0) + iiposs <- sample(iipos, length(iipos) / 5) + priorMatCV[iiposs, j] <- 0 + heldOutGenes[[colnames(priorMat)[j]]] <- rownames(priorMat)[iiposs] + } + C <- priorMatCV + } else { + C <- priorMat + } + + nc <- ncol(priorMat) + ng <- nrow(Y) + ns <- ncol(Y) + + Bdiff <- -1 + BdiffTrace <- double() + BdiffCount <- 0 + + # YsqSum=sum(Y^2) + # compute svd and use that as the starting point + + if (!is.null(svdres) && nrow(svdres$v) != ncol(Y)) { + message("SVD V has the wrong number of columns") + svdres <- NULL + } + + if (is.null(svd_k) && is.null(clamp.base.result)) { + svd_k <- select_svd_k(Y) + if (!is.null(clamp_k)) svd_k <- max(svd_k, clamp_k) + } + + if (is.null(svdres) && is.null(clamp.base.result)) { + message("Computing SVD") + svdres <- compute_svd(Y, k = svd_k) + } + + if (is.null(svdres) && is.null(clamp.base.result)) { + svdres <- rotateSVD(svdres) + } + + if (is.null(clamp.base.result)) { + auto <- select_clamp_k(svdres, + n_samples = ncol(Y), svd_k = svd_k, + method = clamp_k_method, data = Y + ) + clamp_k <- auto$clamp_k + d <- auto$scale + } else { + d <- svdres$d[clamp_k] + } + + if (is.null(clamp.base.result)) { + message("Running CLAMPbase") + clamp.base.result <- CLAMPbase(Y, clamp_k = clamp_k, svdres = svdres) + } else { + message("using provided CLAMPbase result") + if (nrow(Y) != nrow(clamp.base.result$Z)) { + if (is.null(rownames(Y)) | is.null(rownames(clamp.base.result$Z))) { + stop("Y and clamp.base.result$Z must have equal row numbers or row names") + } + clamp.base.result$Z <- clamp.base.result$Z[rownames(Y), ] } + clamp_k <- ncol(clamp.base.result$Z) + } + + message("CLAMP k is set to ", clamp_k) + + Z <- clamp.base.result$Z + + if (is.null(L1)) { + L1 <- clamp.base.result$L1 + } + if (is.null(L2)) { + L2 <- clamp.base.result$L2 + } + L1 <- L1 * multiplier + L2 <- L2 / multiplier + message("L1=", L1, "; L2=", L2) + + if (ncol(clamp.base.result$B) == ncol(Y)) { + B <- clamp.base.result$B + } + + oldB <- B + + if (!is.null(rseed)) { + message("Using random start") + # reproducibility is controlled by user calling set.seed before this function + B <- t(apply(B, 1, sample)) + Z <- apply(Z, 2, sample) + } + + U <- matrix(0, nrow = ncol(C), ncol = clamp_k) + + round2 <- function(x) { + signif(x, 4) + } + + u.iter <- 2 + curfrac <- 0 + nposlast <- Inf + npos <- -Inf + num.U.updates <- 0 + L1k <- L1 * diag(clamp_k) + L2k <- L2 * diag(clamp_k) - if (useRaw) { - res <- solveU(Zraw, Chat, C, penalty.factor, pathwaySelection, + if (is_fbm) { + ZYt <- big_cprodMat(Y, as.matrix(Z), ncores = ncores) + ZY <- Matrix::t(ZYt) + B <- solve(Matrix::t(Z) %*% Z + L2k) %*% ZY + } else { + B <- solve(Matrix::t(Z) %*% Z + L2k) %*% mat_mult(Matrix::t(Z), Y, ncores = ncores) + } + + Zraw <- Z + Z2 <- matrix(0, nrow = nrow(Z), ncol = ncol(Z)) + + B <- as.matrix(B) + + for (iter in seq_len(max.iter)) { + if (iter >= u.iter) { # actually do a U iteration + if (num.U.updates < max.U.updates & iter %% 2 == 1) { + # Updating U + if (any(Zraw < 0)) { + stop() + } + if (refitAll || num.U.updates %% 5 == 0) { + Uprev <- NULL + # mRefitting all U coefficinets + } else { + Uprev <- U + } + + if (useRaw) { + res <- solveU(Zraw, Chat, C, penalty.factor, pathwaySelection, glm_alpha, maxPath, binary = FALSE, nfolds = cvn, top = top, useNNLS = useNNLS, Uprev = Uprev, useSE = useSE - ) - } else { - res <- solveU(Z, Chat, C, penalty.factor, pathwaySelection, + ) + } else { + res <- solveU(Z, Chat, C, penalty.factor, pathwaySelection, glm_alpha, maxPath, binary = FALSE, nfolds = cvn, top = top, useNNLS = useNNLS, Uprev = Uprev, useSE = useSE - ) + ) + } + U <- res$U + + num.U.updates <- num.U.updates + 1 + + iter.full <- iter.full + iter.full.start + + + Z2 <- L1 * C %*% U + } + + curfrac <- (npos <- sum(apply(U, 2, max) > 0)) / clamp_k + # Z1=Y%*%t(B) + Z1 <- mat_mult(Y, t(B), ncores = ncores) + + # ii=which(Z2>0) + # ratio=median(Z2[ii]/abs(Z1[ii])) + + Z <- (Z1 + Z2) %*% solve(tcrossprod(B) + L1k) + } else { + Z <- mat_mult(Y, t(B), ncores = ncores) %*% solve(tcrossprod(B) + L1k) + } + + if (adaptive.p > 0) { + Zraw <- Z + Zraw[Zraw < 0] <- 0 + cutoffs <- apply(Z, 2, getT) + + for (j in seq_len(ncol(Z))) { + Z[Z[, j] < cutoffs[j], j] <- 0 + } + } else { + Z[Z < 0] <- 0 + Zraw <- Z } - U <- res$U - num.U.updates <- num.U.updates + 1 + oldB <- B - iter.full <- iter.full + iter.full.start + if (is_fbm) { + ZYt <- big_cprodMat(Y, as.matrix(Z), ncores = ncores) + ZY <- Matrix::t(ZYt) + B <- solve(Matrix::t(Z) %*% Z + L2k) %*% ZY + } else { + Z_mat <- if (inherits(Z, "matrix")) Z else as.matrix(Z) + B <- solve(Matrix::t(Z_mat) %*% Z + L2k) %*% mat_mult(Matrix::t(Z), Y, ncores = ncores) + } + Bdiff <- sum((B - oldB)^2) / sum(B^2) + minCor <- min(row_cor(B, oldB)) - Z2 <- L1 * C %*% U - } + BdiffTrace <- c(BdiffTrace, Bdiff) - curfrac <- (npos <- sum(apply(U, 2, max) > 0)) / clamp_k - # Z1=Y%*%t(B) - Z1 <- mat_mult(Y, t(B), ncores = ncores) + if (trace) { + message(sprintf("\rProgress %d / %d | Bdiff=%.6f", iter, max.iter, Bdiff)) + flush.console() + } - # ii=which(Z2>0) - # ratio=median(Z2[ii]/abs(Z1[ii])) + if (iter > 52 && Bdiff > BdiffTrace[iter - 50]) { + BdiffCount <- BdiffCount + 1 + # message("Bdiff is not decreasing") + } else if (BdiffCount > 1) { + BdiffCount <- BdiffCount - 1 + } - Z <- (Z1 + Z2) %*% solve(tcrossprod(B) + L1k) - } else { - Z <- mat_mult(Y, t(B), ncores = ncores) %*% solve(tcrossprod(B) + L1k) + if (Bdiff < tol & iter > u.iter + num.U.updates * 2 + 5) { + message(sprintf( + "\rConverged at %d / %d | Bdiff=%.6f, minCor=%.6f\n", iter, max.iter, + Bdiff, minCor + )) + break + } + if (BdiffCount > 5) { + message("converged at iteration", iter, "Bdiff is not decreasing") + break + } } - if (adaptive.p > 0) { - Zraw <- Z - Zraw[Zraw < 0] <- 0 - cutoffs <- apply(Z, 2, getT) + rownames(U) <- colnames(priorMat) + colnames(U) <- rownames(B) <- colnames(Z) <- paste0("LV", seq_len(clamp_k)) + if (!is.null(rownames(Y))) rownames(Z) <- rownames(Y) + if (!is.null(colnames(Y))) colnames(B) <- colnames(Y) + + out <- list(B = B, Z = Z, U = U, C = C, L1 = L1, L2 = L2, heldOutGenes = heldOutGenes) - for (j in seq_len(ncol(Z))) { - Z[Z[, j] < cutoffs[j], j] <- 0 - } + if (doCrossval) { + if (adaptive.p != 0) { + message("Updating Z for CV") + out$Z <- Zraw + out$Z[out$Z < 0] <- 0 + } + message("crossValidation") + priorMat_m <- as.matrix(priorMat) + priorMatCV_m <- as.matrix(priorMatCV) + outAUC <- crossVal(out, priorMat, priorMatCV) + out$Z <- Z + out$Uauc <- outAUC$Uauc + out$Up <- outAUC$Upval + out$summary <- outAUC$summary + out$priorMatCV <- priorMatCV + out$priorMat <- priorMat + out$withPrior <- which(colSums(out$U) > 0) + + tt <- apply(out$Uauc, 2, max) + message("There are ", sum(tt > 0.70), " LVs with AUC>0.70") + message("There are ", sum(tt > 0.90), " LVs with AUC>0.90") } else { - Z[Z < 0] <- 0 - Zraw <- Z + message("Not using cross-validation. No AUCs or p-values") } - oldB <- B + out$call <- call <- match.call() + out$Z <- as.matrix(out$Z) + out$B <- as.matrix(out$B) - if (is_fbm) { - ZYt <- big_cprodMat(Y, as.matrix(Z), ncores = ncores) - ZY <- Matrix::t(ZYt) - B <- solve(Matrix::t(Z) %*% Z + L2k) %*% ZY - } else { - Z_mat <- if (inherits(Z, "matrix")) Z else as.matrix(Z) - B <- solve(Matrix::t(Z_mat) %*% Z + L2k) %*% mat_mult(Matrix::t(Z), Y, ncores = ncores) - } - - Bdiff <- sum((B - oldB)^2) / sum(B^2) - minCor <- min(row_cor(B, oldB)) - - BdiffTrace <- c(BdiffTrace, Bdiff) - - if (trace) { - message(sprintf("\rProgress %d / %d | Bdiff=%.6f", iter, max.iter, Bdiff)) - flush.console() - } - - if (iter > 52 && Bdiff > BdiffTrace[iter - 50]) { - BdiffCount <- BdiffCount + 1 - # message("Bdiff is not decreasing") - } else if (BdiffCount > 1) { - BdiffCount <- BdiffCount - 1 - } - - if (Bdiff < tol & iter > u.iter + num.U.updates * 2 + 5) { - message(sprintf( - "\rConverged at %d / %d | Bdiff=%.6f, minCor=%.6f\n", iter, max.iter, - Bdiff, minCor - )) - break - } - if (BdiffCount > 5) { - message("converged at iteration", iter, "Bdiff is not decreasing") - break - } - } - - rownames(U) <- colnames(priorMat) - colnames(U) <- rownames(B) <- colnames(Z) <- paste0("LV", seq_len(clamp_k)) - if (!is.null(rownames(Y))) rownames(Z) <- rownames(Y) - if (!is.null(colnames(Y))) colnames(B) <- colnames(Y) - - out <- list(B = B, Z = Z, U = U, C = C, L1 = L1, L2 = L2, heldOutGenes = heldOutGenes) - - if (doCrossval) { - if (adaptive.p != 0) { - message("Updating Z for CV") - out$Z <- Zraw - out$Z[out$Z < 0] <- 0 - } - message("crossValidation") - priorMat_m <- as.matrix(priorMat) - priorMatCV_m <- as.matrix(priorMatCV) - outAUC <- crossVal(out, priorMat, priorMatCV) - out$Z <- Z - out$Uauc <- outAUC$Uauc - out$Up <- outAUC$Upval - out$summary <- outAUC$summary - out$priorMatCV <- priorMatCV - out$priorMat <- priorMat - out$withPrior <- which(colSums(out$U) > 0) - - tt <- apply(out$Uauc, 2, max) - message("There are ", sum(tt > 0.70), " LVs with AUC>0.70") - message("There are ", sum(tt > 0.90), " LVs with AUC>0.90") - } else { - message("Not using cross-validation. No AUCs or p-values") - } - - out$call <- call <- match.call() - out$Z <- as.matrix(out$Z) - out$B <- as.matrix(out$B) - - if (ncores > 1) { - # restore previous state - options(bigstatsr.check.parallel.blas = TRUE) - options(default.nproc.blas = blas_nproc) - } - - return(out) + if (ncores > 1) { + # restore previous state + options(bigstatsr.check.parallel.blas = TRUE) + options(default.nproc.blas = blas_nproc) + } + + return(out) } #' Project new data into CLAMP latent space @@ -1240,12 +1242,16 @@ CLAMPfullnVP <- function( #' #' @examples #' # fit a tiny CLAMP model for projection -#' Y0 <- matrix(rnorm(5 * 3), nrow = 5, -#' dimnames = list(paste0("Gene", 1:5), paste0("S", 1:3))) +#' Y0 <- matrix(rnorm(5 * 3), +#' nrow = 5, +#' dimnames = list(paste0("Gene", 1:5), paste0("S", 1:3)) +#' ) #' base <- CLAMPbase(Y0, clamp_k = 2, max.iter = 1, trace = FALSE) #' # new data can be provided in a different row order -#' newY <- matrix(rnorm(5 * 2), nrow = 5, -#' dimnames = list(rev(rownames(Y0)), paste0("N", 1:2))) +#' newY <- matrix(rnorm(5 * 2), +#' nrow = 5, +#' dimnames = list(rev(rownames(Y0)), paste0("N", 1:2)) +#' ) #' projB <- projectCLAMP(base, newdata = newY) #' # check dimensions: 2 latent vars x 2 samples #' dim(projB) @@ -1253,87 +1259,89 @@ CLAMPfullnVP <- function( #' @export projectCLAMP <- function(CLAMPres, newdata, scale = 1, ncores = 1, align = TRUE, verbose = TRUE) { - if (is.null(CLAMPres$Z)) stop("'CLAMPres' must contain a 'Z' matrix.") - if (is.null(CLAMPres$L2)) stop("'CLAMPres' must contain an 'L2' value.") + if (is.null(CLAMPres$Z)) stop("'CLAMPres' must contain a 'Z' matrix.") + if (is.null(CLAMPres$L2)) stop("'CLAMPres' must contain an 'L2' value.") - Z_matrix <- if (inherits(CLAMPres$Z, "Matrix")) { - as.matrix(CLAMPres$Z) - } else { - CLAMPres$Z - } + Z_matrix <- if (inherits(CLAMPres$Z, "Matrix")) { + as.matrix(CLAMPres$Z) + } else { + CLAMPres$Z + } - z_genes <- rownames(Z_matrix) - new_genes <- rownames(newdata) + z_genes <- rownames(Z_matrix) + new_genes <- rownames(newdata) - if (align && !is.null(z_genes) && !is.null(new_genes)) { - if (anyDuplicated(z_genes) > 0 || anyDuplicated(new_genes) > 0) { - stop("Projection row-name alignment requires unique gene names.") - } + if (align && !is.null(z_genes) && !is.null(new_genes)) { + if (anyDuplicated(z_genes) > 0 || anyDuplicated(new_genes) > 0) { + stop("Projection row-name alignment requires unique gene names.") + } - cm <- commonRows(Z_matrix, newdata) - if (length(cm) == 0) { - stop("No common row names found between CLAMPres$Z and newdata.") - } - if (verbose) message(length(cm), " common rows found") + cm <- commonRows(Z_matrix, newdata) + if (length(cm) == 0) { + stop("No common row names found between CLAMPres$Z and newdata.") + } + if (verbose) message(length(cm), " common rows found") - Z_matrix <- Z_matrix[cm, , drop = FALSE] - newdata <- newdata[cm, , drop = FALSE] - } else { - if (nrow(Z_matrix) != nrow(newdata)) { - stop( - "CLAMPres$Z and newdata have different numbers of rows and cannot ", - "be aligned because row names are missing." - ) - } + Z_matrix <- Z_matrix[cm, , drop = FALSE] + newdata <- newdata[cm, , drop = FALSE] + } else { + if (nrow(Z_matrix) != nrow(newdata)) { + stop( + "CLAMPres$Z and newdata have different numbers of rows and cannot ", + "be aligned because row names are missing." + ) + } - if (!is.null(z_genes) && !is.null(new_genes) && !identical(z_genes, new_genes)) { - stop( - "CLAMPres$Z and newdata row names are not in the same order. ", - "Use align = TRUE to align common genes automatically." - ) - } + if (!is.null(z_genes) && !is.null(new_genes) && !identical(z_genes, new_genes)) { + stop( + "CLAMPres$Z and newdata row names are not in the same order. ", + "Use align = TRUE to align common genes automatically." + ) + } - if (verbose && (is.null(z_genes) || is.null(new_genes))) { - message("Row names unavailable; assuming CLAMPres$Z and newdata are already aligned.") + if (verbose && (is.null(z_genes) || is.null(new_genes))) { + message("Row names unavailable; assuming CLAMPres$Z and newdata are already aligned.") + } } - } - - if (ncores > 1) { - # if we are parallelizing, then disable BLAS parallelization - options(bigstatsr.check.parallel.blas = FALSE) - blas_nproc <- getOption("default.nproc.blas") - options(default.nproc.blas = NULL) - on.exit({ - options(bigstatsr.check.parallel.blas = TRUE) - options(default.nproc.blas = blas_nproc) - }, add = TRUE) - } - # Check if newdata is a FBM/big.matrix object - is_fbm <- inherits(newdata, c("big.matrix", "FBM")) + if (ncores > 1) { + # if we are parallelizing, then disable BLAS parallelization + options(bigstatsr.check.parallel.blas = FALSE) + blas_nproc <- getOption("default.nproc.blas") + options(default.nproc.blas = NULL) + on.exit( + { + options(bigstatsr.check.parallel.blas = TRUE) + options(default.nproc.blas = blas_nproc) + }, + add = TRUE + ) + } - if (is_fbm) { - # FBM implementation - use big_cprodMat for efficient computation - # But ensure Z is a standard matrix, not a Matrix package object - ZYt <- big_cprodMat(newdata, Z_matrix, ncores = ncores) - ZY <- t(ZYt) - } else { - # Standard matrix implementation - use regular matrix multiplication - ZY <- t(Z_matrix) %*% newdata - } + # Check if newdata is a FBM/big.matrix object + is_fbm <- inherits(newdata, c("big.matrix", "FBM")) - # Calculate the regularization matrix using standard matrix operations - ZtZ <- t(Z_matrix) %*% Z_matrix - L2k <- CLAMPres$L2 * diag(ncol(Z_matrix)) * scale + if (is_fbm) { + # FBM implementation - use big_cprodMat for efficient computation + # But ensure Z is a standard matrix, not a Matrix package object + ZYt <- big_cprodMat(newdata, Z_matrix, ncores = ncores) + ZY <- t(ZYt) + } else { + # Standard matrix implementation - use regular matrix multiplication + ZY <- t(Z_matrix) %*% newdata + } - # Solve the regularized system - B <- solve(ZtZ + L2k) %*% ZY + # Calculate the regularization matrix using standard matrix operations + ZtZ <- t(Z_matrix) %*% Z_matrix + L2k <- CLAMPres$L2 * diag(ncol(Z_matrix)) * scale - rownames(B) <- colnames(Z_matrix) - colnames(B) <- colnames(newdata) + # Solve the regularized system + B <- solve(ZtZ + L2k) %*% ZY - return(B) + rownames(B) <- colnames(Z_matrix) + colnames(B) <- colnames(newdata) + return(B) } ## Refactored PC estimation functions @@ -1343,14 +1351,14 @@ projectCLAMP <- function(CLAMPres, newdata, scale = 1, ncores = 1, #' @param d Vector of singular values #' @return Estimated number of PCs via elbow run_elbow <- function(d) { - # compute second differences - x_raw <- abs(diff(diff(d))) - # smoothing helper - twiceit <- function(x, twiceit = TRUE) smooth(x, twiceit = TRUE) - x_smooth <- twiceit(x_raw) - cutoff <- quantile(x_smooth, 0.5) - # first index below cutoff plus one for PC count - which(x_smooth <= cutoff)[1] + 1 + # compute second differences + x_raw <- abs(diff(diff(d))) + # smoothing helper + twiceit <- function(x, twiceit = TRUE) smooth(x, twiceit = TRUE) + x_smooth <- twiceit(x_raw) + cutoff <- quantile(x_smooth, 0.5) + # first index below cutoff plus one for PC count + which(x_smooth <= cutoff)[1] + 1 } #' Run permutation method to estimate number of PCs @@ -1360,23 +1368,23 @@ run_elbow <- function(d) { #' @param B Number of permutations #' @return Estimated number of PCs via permutation test run_permutation <- function(data, d, B = 20) { - k <- length(d) - # observed proportions - obs_prop <- d^2 / sum(d^2) - # permuted proportions matrix - perm_mat <- matrix(0, nrow = B, ncol = k) - for (i in seq_len(B)) { - dat0 <- t(apply(data, 1, sample)) - if (ncol(dat0) == k) { - uu0 <- svd(dat0) - } else { - uu0 <- rsvd(dat0, k = k, q = 3) + k <- length(d) + # observed proportions + obs_prop <- d^2 / sum(d^2) + # permuted proportions matrix + perm_mat <- matrix(0, nrow = B, ncol = k) + for (i in seq_len(B)) { + dat0 <- t(apply(data, 1, sample)) + if (ncol(dat0) == k) { + uu0 <- svd(dat0) + } else { + uu0 <- rsvd(dat0, k = k, q = 3) + } + perm_mat[i, ] <- uu0$d[seq_len(k)]^2 / sum(uu0$d[seq_len(k)]^2) } - perm_mat[i, ] <- uu0$d[seq_len(k)]^2 / sum(uu0$d[seq_len(k)]^2) - } - p_vals <- apply(perm_mat >= obs_prop, 2, mean) - p_vals <- cummax(p_vals) - sum(p_vals <= 0.1) + p_vals <- apply(perm_mat >= obs_prop, 2, mean) + p_vals <- cummax(p_vals) + sum(p_vals <= 0.1) } #' Estimate number of principal components via elbow or permutation method @@ -1395,43 +1403,43 @@ run_permutation <- function(data, d, B = 20) { #' num.pc(mat, method = "permutation", B = 5) #' @export num.pc <- function(data, method = c("elbow", "permutation"), B = 20, seed = NULL) { - method <- match.arg(method) - if (!is.null(seed)) { - warning( - "`seed` is deprecated and ignored. ", - "For reproducibility, call set.seed(seed) *before* this function.", - call. = FALSE - ) - } - # Prepare SVD result - if (!inherits(data, "list") || is.null(data$d)) { - message("Computing SVD") - # row-normalize - row_sds <- apply(data, 1, sd) - row_sds[row_sds == 0] <- 1 - data_norm <- sweep(data, 1, row_sds, "/") - n <- ncol(data_norm) - k <- if (n < 500) n else max(200, floor(n / 4)) - if (k == n) { - uu <- svd(data_norm) + method <- match.arg(method) + if (!is.null(seed)) { + warning( + "`seed` is deprecated and ignored. ", + "For reproducibility, call set.seed(seed) *before* this function.", + call. = FALSE + ) + } + # Prepare SVD result + if (!inherits(data, "list") || is.null(data$d)) { + message("Computing SVD") + # row-normalize + row_sds <- apply(data, 1, sd) + row_sds[row_sds == 0] <- 1 + data_norm <- sweep(data, 1, row_sds, "/") + n <- ncol(data_norm) + k <- if (n < 500) n else max(200, floor(n / 4)) + if (k == n) { + uu <- svd(data_norm) + } else { + uu <- rsvd(data_norm, k = k, q = 3) + } } else { - uu <- rsvd(data_norm, k = k, q = 3) + uu <- data + data_norm <- NULL # not needed for elbow + if (method == "permutation") { + message("Raw data required for permutation; switching to elbow") + method <- "elbow" + } } - } else { - uu <- data - data_norm <- NULL # not needed for elbow + + # Dispatch to specific method if (method == "permutation") { - message("Raw data required for permutation; switching to elbow") - method <- "elbow" + run_permutation(data_norm, uu$d, B) + } else { + run_elbow(uu$d) } - } - - # Dispatch to specific method - if (method == "permutation") { - run_permutation(data_norm, uu$d, B) - } else { - run_elbow(uu$d) - } } #' Winsorize matrix columns by capping the top-k values @@ -1445,8 +1453,10 @@ num.pc <- function(data, method = c("elbow", "permutation"), B = 20, seed = NULL #' @export #' @examples #' set.seed(123) -#' M <- matrix(rnorm(20 * 5, mean = 0, sd = 2), nrow = 20, -#' dimnames = list(paste0("Gene", 1:20), paste0("S", 1:5))) +#' M <- matrix(rnorm(20 * 5, mean = 0, sd = 2), +#' nrow = 20, +#' dimnames = list(paste0("Gene", 1:20), paste0("S", 1:5)) +#' ) #' #' # Display column maxima before winsorization #' apply(M, 2, max) @@ -1454,13 +1464,15 @@ num.pc <- function(data, method = c("elbow", "permutation"), B = 20, seed = NULL #' # Winsorize each column by capping top 3 values #' M_winsor <- winsor_topk(M, k = 3) winsor_topk <- function(M, k) { - if (nrow(M) < 10 * k) return(M) - stopifnot(is.matrix(M), is.numeric(M), k >= 1L, k <= nrow(M)) - n <- nrow(M) - thr <- apply(M, 2L, function(x) { - sort.int(x, partial = n - k + 1L)[n - k + 1L] - }) - sweep(M, 2L, thr, pmin) + if (nrow(M) < 10 * k) { + return(M) + } + stopifnot(is.matrix(M), is.numeric(M), k >= 1L, k <= nrow(M)) + n <- nrow(M) + thr <- apply(M, 2L, function(x) { + sort.int(x, partial = n - k + 1L)[n - k + 1L] + }) + sweep(M, 2L, thr, pmin) } #' Cross-product Z^T Y with FBM or dense matrices @@ -1485,13 +1497,13 @@ winsor_topk <- function(M, k) { #' #' # Compute Z^T Y #' res1 <- cross_ZY(Y, Z) -#' dim(res1) # k × samples +#' dim(res1) # k × samples cross_ZY <- function(Y, Z) { - if (inherits(Y, "FBM")) { - Matrix::t(bigstatsr::big_cprodMat(Y, as.matrix(Z))) - } else { - base::crossprod(as.matrix(Z), as.matrix(Y)) - } + if (inherits(Y, "FBM")) { + Matrix::t(bigstatsr::big_cprodMat(Y, as.matrix(Z))) + } else { + base::crossprod(as.matrix(Z), as.matrix(Y)) + } } #' Ridge regression update for B @@ -1512,7 +1524,7 @@ cross_ZY <- function(Y, Z) { #' k <- 5 #' #' Y <- matrix(rnorm(50 * 20), nrow = 50, dimnames = list(genes, samples)) -#' Z <- matrix(rnorm(50 * k), nrow = 50, dimnames = list(genes, paste0("LV", 1:k))) +#' Z <- matrix(rnorm(50 * k), nrow = 50, dimnames = list(genes, paste0("LV", 1:k))) #' #' lambda <- 0.1 #' L2k <- diag(lambda, k) @@ -1520,11 +1532,11 @@ cross_ZY <- function(Y, Z) { #' # Solve for B = (Z'Z + L2)^(-1) Z'Y #' B <- ridge_B(Y, Z, L2k) ridge_B <- function(Y, Z, L2k) { - Zm <- as.matrix(Z) - ZtZ <- Matrix::crossprod(Zm) # Z^T Z - ZY <- cross_ZY(Y, Zm) # Z^T Y - out <- base::solve(ZtZ + L2k, ZY) - as.matrix(out) + Zm <- as.matrix(Z) + ZtZ <- Matrix::crossprod(Zm) # Z^T Z + ZY <- cross_ZY(Y, Zm) # Z^T Y + out <- base::solve(ZtZ + L2k, ZY) + as.matrix(out) } @@ -1605,364 +1617,361 @@ ridge_B <- function(Y, Z, L2k) { #' mat <- matrix(rnorm(100), nrow = 10, ncol = 10) #' base <- CLAMPbase(mat, clamp_k = 5, trace = FALSE, max.iter = 5) #' prior <- matrix(sample(0:1, 10 * 6, TRUE, prob = c(0.9, 0.1)), -#' nrow = 10, ncol = 6) +#' nrow = 10, ncol = 6 +#' ) #' fit <- CLAMPfull( -#' Y = mat, -#' priorMat = prior, -#' clamp.base.result = base, -#' doCrossval = FALSE, -#' adaptive.p = 0, -#' max.U.updates = 0, -#' max.iter = 1, -#' trace = FALSE +#' Y = mat, +#' priorMat = prior, +#' clamp.base.result = base, +#' doCrossval = FALSE, +#' adaptive.p = 0, +#' max.U.updates = 0, +#' max.iter = 1, +#' trace = FALSE #' ) #' @export CLAMPfull <- function( - Y, priorMat, Chat=NULL, svdres = NULL, clamp.base.result = NULL, clamp_k = NULL, - svd_k = NULL, L1 = NULL, L2 = NULL, cvn = 5, max.iter = 30, trace = TRUE, maxPath = 10, doCrossval = TRUE, - penalty.factor = rep(1, ncol(priorMat)), glm_alpha = 0.9, - minGenes = 0, tol = 5e-4, seed = 123456, allGenes = FALSE, rseed = NULL, - max.U.updates = Inf, pathwaySelection = c("fast", "complete"), multiplier = 5, - adaptive.p = 0.05, useNNLS = TRUE, useRaw = TRUE, refitEvery = 3, - useSE = FALSE, var.prior = TRUE, Uscale = FALSE, robust.vp = TRUE, use_cpp=FALSE, - clamp_k_method = "elbow") { - - if (is.infinite(max.U.updates)) max.U.updates <- max.iter - - getT <- function(x) -stats::quantile(x[x < 0], adaptive.p) - - pathwaySelection <- match.arg(pathwaySelection, c("fast", "complete")) - - priorMat <- as.matrix(priorMat) - - message("** CLAMPfull **") - - ## Detect matrix type (FBM block preserved for compatibility) - is_fbm <- inherits(Y, "FBM") - is_sparse <- inherits(Y, "dgCMatrix") - - getVarMultiplier <- function(Zinput, Z2) { - Zmultiplier <- matrix(0, nrow = nrow(Zinput), ncol = ncol(Zinput)) - for (zi in seq_len(ncol(Zinput))) { - if (all(Z2[, zi] == 0)) next - iiback <- Z2[, zi] == 0 & Zinput[, zi] > 0 - iiiforward <- Z2[, zi] > 0 & Zinput[, zi] > 0 - #define proxives for variance - #background in Z - mvarBack <- mean(Zinput[iiback, zi]^2) - #foreground in Z - mvarForward <- mean(Zinput[iiiforward, zi]^2) - #foreground predicted in Z2 - mvarPredicted <- mean(Z2[iiiforward, zi]^2) - #this offset will use the implied foreground variance scale from actual Z - #as opposed to the predcicted on in Z2 - offset <- mvarForward / mvarPredicted - #compute the predicted variance - Z2var <- Z2[, zi]^2 * offset - #compute a fold change - 1 and clip at 0 - #1 will be added later ensuring that the background variance scale is always L1 - Zmultiplier[, zi] <- pmax((Z2var / mvarBack) - 1, 0) - } - Zmultiplier - } - - ## Align genes - if (nrow(priorMat) != nrow(Y) || !all(rownames(priorMat) == rownames(Y))) { - if (!allGenes) { - cm <- commonRows(Y, priorMat) - message("Selecting common genes: ", length(cm)) - priorMat <- priorMat[cm, ] - Y <- Y[cm, ] - } else { - extra.genes <- setdiff(rownames(Y), rownames(priorMat)) - eMat <- matrix(0, nrow = length(extra.genes), ncol = ncol(priorMat)) - rownames(eMat) <- extra.genes - priorMat <- rbind(priorMat, eMat) - priorMat <- priorMat[rownames(Y), ] - } - } - - ## Filter small pathways - numGenes <- Matrix::colSums(priorMat) - heldOutGenes <- list() - iibad <- which(numGenes < minGenes) - if (length(iibad) > 0) { - priorMat <- priorMat[, -iibad, drop = FALSE] - message("Removed ", length(iibad), " pathways with too few genes") - } - ## Cross-validation masking - if (doCrossval) { - priorMatCV <- as.matrix(priorMat) - - for (j in seq_len(ncol(priorMatCV))) { - iipos <- which(priorMatCV[, j] > 0) - iiposs <- sample(iipos, length(iipos) / 5) - priorMatCV[iiposs, j] <- 0 - heldOutGenes[[colnames(priorMat)[j]]] <- rownames(priorMat)[iiposs] - } - C <- priorMatCV - } else { - C <- priorMat - } - - ## Initialize Chat - if (is.null(Chat)) { - #Chat <- pinv.ridge(crossprod(C), 5) %*% t(C) - } - - ## SVD / base init - ns <- ncol(Y) - - if (!is.null(svdres) && nrow(svdres$v) != ncol(Y)) { - message("SVD V has the wrong number of columns") - svdres <- NULL - } - - if (is.null(svd_k) && is.null(clamp.base.result)) { - svd_k <- select_svd_k(Y) - if (!is.null(clamp_k)) svd_k <- max(svd_k, clamp_k) - } - - if (is.null(svdres) && is.null(clamp.base.result)) { - message("Computing SVD") - svdres <- compute_svd(Y, k = svd_k) - } - - if (is.null(svdres) && is.null(clamp.base.result)) { - svdres <- rotateSVD(svdres) - } - - if(is.null(clamp.base.result)){ - auto <- select_clamp_k(svdres, n_samples = ncol(Y), svd_k = svd_k, - method = clamp_k_method, data = Y) - clamp_k <- auto$clamp_k - d <- auto$scale - } else { - d <- svdres$d[clamp_k] - } - - if (is.null(clamp.base.result)) { - message("Running CLAMPbase") - clamp.base.result <- CLAMPbase(Y, clamp_k = clamp_k, svdres = svdres) - } else { - message("using provided CLAMPbase result") - if (nrow(Y) != nrow(clamp.base.result$Z)) { - if (is.null(rownames(Y)) | is.null(rownames(clamp.base.result$Z))) { - stop("Y and clamp.base.result$Z must have equal row numbers or row names") - } - clamp.base.result$Z <- clamp.base.result$Z[rownames(Y), ] - } - clamp_k <- ncol(clamp.base.result$Z) - } - - message("CLAMP k is set to ", clamp_k) - - u.iter <- 2 - - Z <- clamp.base.result$Z - if (is.null(L1)) L1 <- clamp.base.result$L1 - if (is.null(L2)) L2 <- clamp.base.result$L2 - message("L1=", L1, "; L2=", L2) - - if (ncol(clamp.base.result$B) == ncol(Y)) { - B <- clamp.base.result$B - L1scalevec <- rowSums(B^2) - } else { - stop("clamp.base.result$B does not match number of samples in Y") - } - - if (!is.null(rseed)) { - message("Using random start") - B <- t(apply(B, 1, sample)) - Z <- apply(Z, 2, sample) - } - - U <- matrix(0, nrow = ncol(C), ncol = clamp_k) - L1k <- L1 * diag(clamp_k) - L2k <- L2 * diag(clamp_k) - - ## Optional FBM path (kept in comments for compatibility) - # if (is_fbm) { - # ZYt <- bigstatsr::big_cprodMat(Y, as.matrix(Z)) - # ZY <- Matrix::t(ZYt) - # B <- solve(Matrix::t(Z) %*% Z + L2k) %*% ZY - # } else { - # B <- solve(Matrix::t(Z) %*% Z + L2k) %*% mat_mult(Matrix::t(Z), Y) - # } - - Z_mat <- if (inherits(Z, "matrix")) Z else as.matrix(Z) - B <- ridge_B(Y, Z_mat, L2k) - - Zraw <- Z - Z2 <- matrix(0, nrow = nrow(Z), ncol = ncol(Z)) - - B <- as.matrix(B) - n <- nrow(Z) - - - BdiffTrace <- numeric(0) - BdiffCount <- 0 - oldB <- B - - num.U.updates <- 0 - start_time <- Sys.time() - for (iter in seq_len(max.iter)) { - if (iter == 4) { - iter_time <- as.numeric(difftime(Sys.time(), start_time, units="secs")) - est_total <- iter_time * max.iter/4 - message(sprintf("Estimated total runtime: ~%.1f min", est_total / 60)) - } - if (iter >= u.iter) { #do U - if (num.U.updates < max.U.updates) { #actually update U - if (any(Zraw < 0)) stop("Zraw has negative entries before U update") - Uprev <- if (num.U.updates %% refitEvery == 0 || iter==u.iter) NULL else U - if(!is.null(Uprev)){ - # print("Reusing previous") + Y, priorMat, Chat = NULL, svdres = NULL, clamp.base.result = NULL, clamp_k = NULL, + svd_k = NULL, L1 = NULL, L2 = NULL, cvn = 5, max.iter = 30, trace = TRUE, maxPath = 10, doCrossval = TRUE, + penalty.factor = rep(1, ncol(priorMat)), glm_alpha = 0.9, + minGenes = 0, tol = 5e-4, seed = 123456, allGenes = FALSE, rseed = NULL, + max.U.updates = Inf, pathwaySelection = c("fast", "complete"), multiplier = 5, + adaptive.p = 0.05, useNNLS = TRUE, useRaw = TRUE, refitEvery = 3, + useSE = FALSE, var.prior = TRUE, Uscale = FALSE, robust.vp = TRUE, use_cpp = FALSE, + clamp_k_method = "elbow" +) { + if (is.infinite(max.U.updates)) max.U.updates <- max.iter + + getT <- function(x) -stats::quantile(x[x < 0], adaptive.p) + + pathwaySelection <- match.arg(pathwaySelection, c("fast", "complete")) + + priorMat <- as.matrix(priorMat) + + message("** CLAMPfull **") + + ## Detect matrix type (FBM block preserved for compatibility) + is_fbm <- inherits(Y, "FBM") + is_sparse <- inherits(Y, "dgCMatrix") + + getVarMultiplier <- function(Zinput, Z2) { + Zmultiplier <- matrix(0, nrow = nrow(Zinput), ncol = ncol(Zinput)) + for (zi in seq_len(ncol(Zinput))) { + if (all(Z2[, zi] == 0)) next + iiback <- Z2[, zi] == 0 & Zinput[, zi] > 0 + iiiforward <- Z2[, zi] > 0 & Zinput[, zi] > 0 + # define proxives for variance + # background in Z + mvarBack <- mean(Zinput[iiback, zi]^2) + # foreground in Z + mvarForward <- mean(Zinput[iiiforward, zi]^2) + # foreground predicted in Z2 + mvarPredicted <- mean(Z2[iiiforward, zi]^2) + # this offset will use the implied foreground variance scale from actual Z + # as opposed to the predcicted on in Z2 + offset <- mvarForward / mvarPredicted + # compute the predicted variance + Z2var <- Z2[, zi]^2 * offset + # compute a fold change - 1 and clip at 0 + # 1 will be added later ensuring that the background variance scale is always L1 + Zmultiplier[, zi] <- pmax((Z2var / mvarBack) - 1, 0) + } + Zmultiplier + } + + ## Align genes + if (nrow(priorMat) != nrow(Y) || !all(rownames(priorMat) == rownames(Y))) { + if (!allGenes) { + cm <- commonRows(Y, priorMat) + message("Selecting common genes: ", length(cm)) + priorMat <- priorMat[cm, ] + Y <- Y[cm, ] } else { - # print("Fitting new") + extra.genes <- setdiff(rownames(Y), rownames(priorMat)) + eMat <- matrix(0, nrow = length(extra.genes), ncol = ncol(priorMat)) + rownames(eMat) <- extra.genes + priorMat <- rbind(priorMat, eMat) + priorMat <- priorMat[rownames(Y), ] } + } - Zinput <- if (useRaw) Zraw else Z - res <- solveU(Zinput, NULL, C, penalty.factor, pathwaySelection, - glm_alpha, maxPath, binary = FALSE, nfolds = cvn, - useNNLS = useNNLS, Uprev = Uprev, useSE = useSE, scale = Uscale, useAUC = TRUE) - - U <- res$U - num.U.updates <- num.U.updates + 1 - - } #end - - Z1 <- mat_mult(Y, t(B)) - - if (!var.prior) { - Z2 <- C %*% U - Z <- (Z1 + L1* Z2) %*% solve(Matrix::tcrossprod(B) + L1k) - } else { - Z2 <- as.matrix(C %*% U) - if (robust.vp) Z2 <- winsor_topk(Z2, 20) - Zmultiplier <- getVarMultiplier(Zinput, Z2) - - B2 <- B %*% t(B) # k×k - bk2_all <- diag(B2) # length k - YBt <- Y %*% t(B) # n×k - Q <- Z %*% B2 # n×k cache (ZB projected via B) - - if (use_cpp) { - if(!is_fbm) - updateZcpp(Z, Y, B, B2, bk2_all, YBt, Q, Zmultiplier, L1, multiplier, 3, iter) - else - updateZcpp(Z, Y$address, B, B2, bk2_all, YBt, Q, Zmultiplier, - L1, multiplier, 3, iter, - Y_is_fbm = TRUE, n = nrow(Y), p = ncol(Y)) + ## Filter small pathways + numGenes <- Matrix::colSums(priorMat) + heldOutGenes <- list() + iibad <- which(numGenes < minGenes) + if (length(iibad) > 0) { + priorMat <- priorMat[, -iibad, drop = FALSE] + message("Removed ", length(iibad), " pathways with too few genes") + } + ## Cross-validation masking + if (doCrossval) { + priorMatCV <- as.matrix(priorMat) + + for (j in seq_len(ncol(priorMatCV))) { + iipos <- which(priorMatCV[, j] > 0) + iiposs <- sample(iipos, length(iipos) / 5) + priorMatCV[iiposs, j] <- 0 + heldOutGenes[[colnames(priorMat)[j]]] <- rownames(priorMat)[iiposs] } + C <- priorMatCV + } else { + C <- priorMat + } - else { - for (inner.iter in seq_len(3)) { - for (k_index in sample.int(clamp_k)) { + ## Initialize Chat + if (is.null(Chat)) { + # Chat <- pinv.ridge(crossprod(C), 5) %*% t(C) + } + ## SVD / base init + ns <- ncol(Y) - gene_var <-L1 * (1 / (multiplier * Zmultiplier[, k_index] + 1)) + if (!is.null(svdres) && nrow(svdres$v) != ncol(Y)) { + message("SVD V has the wrong number of columns") + svdres <- NULL + } - bk2 <- bk2_all[k_index] - denom <- bk2 + gene_var - num <- YBt[, k_index] - Q[, k_index] + Z[, k_index] * bk2 + if (is.null(svd_k) && is.null(clamp.base.result)) { + svd_k <- select_svd_k(Y) + if (!is.null(clamp_k)) svd_k <- max(svd_k, clamp_k) + } - newZk <- num / denom - delta <- newZk - Z[, k_index] - Z[, k_index] <- newZk + if (is.null(svdres) && is.null(clamp.base.result)) { + message("Computing SVD") + svdres <- compute_svd(Y, k = svd_k) + } - Q <- Q + tcrossprod(delta, B2[k_index, ]) # rank-1 n×1 * 1×k + if (is.null(svdres) && is.null(clamp.base.result)) { + svdres <- rotateSVD(svdres) + } - #if (anyNA(Z)) stop() - } #end for k - } #end inner iter - }#end no CPP + if (is.null(clamp.base.result)) { + auto <- select_clamp_k(svdres, + n_samples = ncol(Y), svd_k = svd_k, + method = clamp_k_method, data = Y + ) + clamp_k <- auto$clamp_k + d <- auto$scale + } else { + d <- svdres$d[clamp_k] + } + if (is.null(clamp.base.result)) { + message("Running CLAMPbase") + clamp.base.result <- CLAMPbase(Y, clamp_k = clamp_k, svdres = svdres) + } else { + message("using provided CLAMPbase result") + if (nrow(Y) != nrow(clamp.base.result$Z)) { + if (is.null(rownames(Y)) | is.null(rownames(clamp.base.result$Z))) { + stop("Y and clamp.base.result$Z must have equal row numbers or row names") + } + clamp.base.result$Z <- clamp.base.result$Z[rownames(Y), ] + } + clamp_k <- ncol(clamp.base.result$Z) + } + message("CLAMP k is set to ", clamp_k) - }#end var prior + u.iter <- 2 + Z <- clamp.base.result$Z + if (is.null(L1)) L1 <- clamp.base.result$L1 + if (is.null(L2)) L2 <- clamp.base.result$L2 + message("L1=", L1, "; L2=", L2) - } # end if full update - else { - Z <- mat_mult(Y, t(B)) %*% solve(Matrix::tcrossprod(B) + L1k) + if (ncol(clamp.base.result$B) == ncol(Y)) { + B <- clamp.base.result$B + L1scalevec <- rowSums(B^2) + } else { + stop("clamp.base.result$B does not match number of samples in Y") } - ## Adaptive thresholding - if (adaptive.p > 0) { - Zraw <- Z - Zraw[Zraw < 0] <- 0 - cutoffs <- apply(Z, 2, getT) - for (j in seq_len(ncol(Z))) Z[Z[, j] < cutoffs[j], j] <- 0 - } else { - Z[Z < 0] <- 0 - Zraw <- Z + if (!is.null(rseed)) { + message("Using random start") + B <- t(apply(B, 1, sample)) + Z <- apply(Z, 2, sample) } - ## Update B - oldB <- B + U <- matrix(0, nrow = ncol(C), ncol = clamp_k) + L1k <- L1 * diag(clamp_k) + L2k <- L2 * diag(clamp_k) + + ## Optional FBM path (kept in comments for compatibility) + # if (is_fbm) { + # ZYt <- bigstatsr::big_cprodMat(Y, as.matrix(Z)) + # ZY <- Matrix::t(ZYt) + # B <- solve(Matrix::t(Z) %*% Z + L2k) %*% ZY + # } else { + # B <- solve(Matrix::t(Z) %*% Z + L2k) %*% mat_mult(Matrix::t(Z), Y) + # } Z_mat <- if (inherits(Z, "matrix")) Z else as.matrix(Z) B <- ridge_B(Y, Z_mat, L2k) - ## Convergence diagnostics - Bdiff <- sum((B - oldB)^2) / sum(B^2) - BdiffTrace <- c(BdiffTrace, Bdiff) - if (trace) { - message(sprintf("\rProgress %d / %d | Bdiff=%.6f", iter, max.iter, Bdiff)) - utils::flush.console() - } - if (iter > 52 && Bdiff > BdiffTrace[iter - 50]) { - BdiffCount <- BdiffCount + 1 - message("Bdiff is not decreasing") - } else if (BdiffCount > 1) { - BdiffCount <- BdiffCount - 1 - } - if (Bdiff < tol && iter > u.iter + num.U.updates * 2 + 5) { - message(sprintf("\rConverged at %d / %d | Bdiff=%.6f", iter, max.iter, Bdiff)) - break - } - if (BdiffCount > 5) { - message("Converged early: Bdiff not decreasing") - break - } - } - - rownames(U) <- colnames(priorMat) - colnames(U) <- rownames(B) <- colnames(Z) <- paste0("LV", seq_len(clamp_k)) - rownames(Z) <- rownames(Y) - if (!is.null(colnames(Y))) colnames(B) <- colnames(Y) - - out <- list(B = B, Z = Z, U = U, C = C, L1 = L1, L2 = L2, Z2=Z2,heldOutGenes = heldOutGenes) - - if (doCrossval) { - if (adaptive.p != 0) { - message("Updating Z for CV") - out$Z <- Zraw - out$Z[out$Z < 0] <- 0 - } - message("crossValidation") - priorMat_m <- as.matrix(priorMat) - priorMatCV_m <- if (exists("priorMatCV")) as.matrix(priorMatCV) else as.matrix(priorMat) - outAUC <- crossVal(out, priorMat, if (exists("priorMatCV")) priorMatCV else priorMat) - out$Z <- Z - out$Uauc <- outAUC$Uauc - out$Up <- outAUC$Upval - out$summary <- outAUC$summary - if (exists("priorMatCV")) out$priorMatCV <- priorMatCV - out$priorMat <- priorMat - out$withPrior <- which(colSums(out$U) > 0) - tt <- apply(out$Uauc, 2, max) - message("There are ", sum(tt > 0.70), " LVs with AUC>0.70") - message("There are ", sum(tt > 0.90), " LVs with AUC>0.90") - } else { - message("Not using cross-validation. No AUCs or p-values") - } - - out$call <- match.call() - out$Z <- as.matrix(out$Z) - out$B <- as.matrix(out$B) - out + Zraw <- Z + Z2 <- matrix(0, nrow = nrow(Z), ncol = ncol(Z)) + + B <- as.matrix(B) + n <- nrow(Z) + + + BdiffTrace <- numeric(0) + BdiffCount <- 0 + oldB <- B + + num.U.updates <- 0 + start_time <- Sys.time() + for (iter in seq_len(max.iter)) { + if (iter == 4) { + iter_time <- as.numeric(difftime(Sys.time(), start_time, units = "secs")) + est_total <- iter_time * max.iter / 4 + message(sprintf("Estimated total runtime: ~%.1f min", est_total / 60)) + } + if (iter >= u.iter) { # do U + if (num.U.updates < max.U.updates) { # actually update U + if (any(Zraw < 0)) stop("Zraw has negative entries before U update") + Uprev <- if (num.U.updates %% refitEvery == 0 || iter == u.iter) NULL else U + if (!is.null(Uprev)) { + # print("Reusing previous") + } else { + # print("Fitting new") + } + + Zinput <- if (useRaw) Zraw else Z + res <- solveU(Zinput, NULL, C, penalty.factor, pathwaySelection, + glm_alpha, maxPath, + binary = FALSE, nfolds = cvn, + useNNLS = useNNLS, Uprev = Uprev, useSE = useSE, scale = Uscale, useAUC = TRUE + ) + + U <- res$U + num.U.updates <- num.U.updates + 1 + } # end + + Z1 <- mat_mult(Y, t(B)) + + if (!var.prior) { + Z2 <- C %*% U + Z <- (Z1 + L1 * Z2) %*% solve(Matrix::tcrossprod(B) + L1k) + } else { + Z2 <- as.matrix(C %*% U) + if (robust.vp) Z2 <- winsor_topk(Z2, 20) + Zmultiplier <- getVarMultiplier(Zinput, Z2) + + B2 <- B %*% t(B) # k×k + bk2_all <- diag(B2) # length k + YBt <- Y %*% t(B) # n×k + Q <- Z %*% B2 # n×k cache (ZB projected via B) + + if (use_cpp) { + if (!is_fbm) { + updateZcpp(Z, Y, B, B2, bk2_all, YBt, Q, Zmultiplier, L1, multiplier, 3, iter) + } else { + updateZcpp(Z, Y$address, B, B2, bk2_all, YBt, Q, Zmultiplier, + L1, multiplier, 3, iter, + Y_is_fbm = TRUE, n = nrow(Y), p = ncol(Y) + ) + } + } else { + for (inner.iter in seq_len(3)) { + for (k_index in sample.int(clamp_k)) { + gene_var <- L1 * (1 / (multiplier * Zmultiplier[, k_index] + 1)) + + bk2 <- bk2_all[k_index] + denom <- bk2 + gene_var + num <- YBt[, k_index] - Q[, k_index] + Z[, k_index] * bk2 + + newZk <- num / denom + delta <- newZk - Z[, k_index] + Z[, k_index] <- newZk + + Q <- Q + tcrossprod(delta, B2[k_index, ]) # rank-1 n×1 * 1×k + + # if (anyNA(Z)) stop() + } # end for k + } # end inner iter + } # end no CPP + } # end var prior + } # end if full update + else { + Z <- mat_mult(Y, t(B)) %*% solve(Matrix::tcrossprod(B) + L1k) + } + + ## Adaptive thresholding + if (adaptive.p > 0) { + Zraw <- Z + Zraw[Zraw < 0] <- 0 + cutoffs <- apply(Z, 2, getT) + for (j in seq_len(ncol(Z))) Z[Z[, j] < cutoffs[j], j] <- 0 + } else { + Z[Z < 0] <- 0 + Zraw <- Z + } + + ## Update B + oldB <- B + + Z_mat <- if (inherits(Z, "matrix")) Z else as.matrix(Z) + B <- ridge_B(Y, Z_mat, L2k) + + ## Convergence diagnostics + Bdiff <- sum((B - oldB)^2) / sum(B^2) + BdiffTrace <- c(BdiffTrace, Bdiff) + if (trace) { + message(sprintf("\rProgress %d / %d | Bdiff=%.6f", iter, max.iter, Bdiff)) + utils::flush.console() + } + if (iter > 52 && Bdiff > BdiffTrace[iter - 50]) { + BdiffCount <- BdiffCount + 1 + message("Bdiff is not decreasing") + } else if (BdiffCount > 1) { + BdiffCount <- BdiffCount - 1 + } + if (Bdiff < tol && iter > u.iter + num.U.updates * 2 + 5) { + message(sprintf("\rConverged at %d / %d | Bdiff=%.6f", iter, max.iter, Bdiff)) + break + } + if (BdiffCount > 5) { + message("Converged early: Bdiff not decreasing") + break + } + } + + rownames(U) <- colnames(priorMat) + colnames(U) <- rownames(B) <- colnames(Z) <- paste0("LV", seq_len(clamp_k)) + rownames(Z) <- rownames(Y) + if (!is.null(colnames(Y))) colnames(B) <- colnames(Y) + + out <- list(B = B, Z = Z, U = U, C = C, L1 = L1, L2 = L2, Z2 = Z2, heldOutGenes = heldOutGenes) + + if (doCrossval) { + if (adaptive.p != 0) { + message("Updating Z for CV") + out$Z <- Zraw + out$Z[out$Z < 0] <- 0 + } + message("crossValidation") + priorMat_m <- as.matrix(priorMat) + priorMatCV_m <- if (exists("priorMatCV")) as.matrix(priorMatCV) else as.matrix(priorMat) + outAUC <- crossVal(out, priorMat, if (exists("priorMatCV")) priorMatCV else priorMat) + out$Z <- Z + out$Uauc <- outAUC$Uauc + out$Up <- outAUC$Upval + out$summary <- outAUC$summary + if (exists("priorMatCV")) out$priorMatCV <- priorMatCV + out$priorMat <- priorMat + out$withPrior <- which(colSums(out$U) > 0) + tt <- apply(out$Uauc, 2, max) + message("There are ", sum(tt > 0.70), " LVs with AUC>0.70") + message("There are ", sum(tt > 0.90), " LVs with AUC>0.90") + } else { + message("Not using cross-validation. No AUCs or p-values") + } + + out$call <- match.call() + out$Z <- as.matrix(out$Z) + out$B <- as.matrix(out$B) + out } #' Subset and filter multiple pathway matrices to match target genes @@ -1992,11 +2001,13 @@ CLAMPfull <- function( #' pathways2 <- paste0("Path", 6:10) #' #' mat1 <- matrix(sample(c(0, 1), 100 * 5, replace = TRUE, prob = c(0.9, 0.1)), -#' nrow = 100, ncol = 5, -#' dimnames = list(genes, pathways1)) +#' nrow = 100, ncol = 5, +#' dimnames = list(genes, pathways1) +#' ) #' mat2 <- matrix(sample(c(0, 1), 100 * 5, replace = TRUE, prob = c(0.9, 0.1)), -#' nrow = 100, ncol = 5, -#' dimnames = list(genes, pathways2)) +#' nrow = 100, ncol = 5, +#' dimnames = list(genes, pathways2) +#' ) #' #' # Define target genes (subset of total) #' new.genes <- sample(genes, 50) @@ -2004,45 +2015,52 @@ CLAMPfull <- function( #' # Match and filter pathways with at least 5 genes #' matched <- getMatchedPathwayMatList(mat1, mat2, new.genes = new.genes, min.genes = 5) getMatchedPathwayMatList <- function(..., new.genes, min.genes = 10) { - pathMats <- list(...) + pathMats <- list(...) - stopifnot(is.character(new.genes), length(new.genes) > 0) - - filtered <- lapply(pathMats, function(pathMat) { - # coerce to sparse - if (!inherits(pathMat, "Matrix")) { - pathMat <- Matrix::Matrix(pathMat, sparse = TRUE) - } + stopifnot(is.character(new.genes), length(new.genes) > 0) - cm <- intersect(rownames(pathMat), new.genes) - message("There are ", length(cm), - " genes in the intersection between data and prior") + filtered <- lapply(pathMats, function(pathMat) { + # coerce to sparse + if (!inherits(pathMat, "Matrix")) { + pathMat <- Matrix::Matrix(pathMat, sparse = TRUE) + } - if (length(cm) == 0L) { - return(Matrix::Matrix(0, nrow = length(new.genes), ncol = 0, - sparse = TRUE, - dimnames = list(new.genes, character()))) - } + cm <- intersect(rownames(pathMat), new.genes) + message( + "There are ", length(cm), + " genes in the intersection between data and prior" + ) - # create aligned matrix - matchPathMat <- Matrix::Matrix(0, nrow = length(new.genes), - ncol = ncol(pathMat), sparse = TRUE, - dimnames = list(new.genes, colnames(pathMat))) + if (length(cm) == 0L) { + return(Matrix::Matrix(0, + nrow = length(new.genes), ncol = 0, + sparse = TRUE, + dimnames = list(new.genes, character()) + )) + } - matchPathMat[cm, ] <- pathMat[cm, , drop = FALSE] + # create aligned matrix + matchPathMat <- Matrix::Matrix(0, + nrow = length(new.genes), + ncol = ncol(pathMat), sparse = TRUE, + dimnames = list(new.genes, colnames(pathMat)) + ) - genesInPath <- Matrix::colSums(matchPathMat) - ii <- which(genesInPath >= min.genes) + matchPathMat[cm, ] <- pathMat[cm, , drop = FALSE] - message(sprintf("Removing %d pathways", - ncol(matchPathMat) - length(ii))) + genesInPath <- Matrix::colSums(matchPathMat) + ii <- which(genesInPath >= min.genes) - matchPathMat[, ii, drop = FALSE] - }) + message(sprintf( + "Removing %d pathways", + ncol(matchPathMat) - length(ii) + )) - if (length(filtered) == 1L) { - return(filtered[[1L]]) - } - do.call(cbind, filtered) + matchPathMat[, ii, drop = FALSE] + }) + if (length(filtered) == 1L) { + return(filtered[[1L]]) + } + do.call(cbind, filtered) } diff --git a/R/utils.R b/R/utils.R index 0b668f7..441e4f2 100644 --- a/R/utils.R +++ b/R/utils.R @@ -20,21 +20,22 @@ #' @importFrom matrixStats colRanks #' @export allAgainstAllAUCs <- function(B, target) { - B <- as.matrix(B) - target <- as.matrix(target) - if (!all(dim(B)[1] == dim(target)[1])) - stop("B and target must have the same number of rows") + B <- as.matrix(B) + target <- as.matrix(target) + if (!all(dim(B)[1] == dim(target)[1])) { + stop("B and target must have the same number of rows") + } - ranks <- matrixStats::colRanks(B, ties.method = "average") + ranks <- matrixStats::colRanks(B, ties.method = "average") - n_pos <- colSums(target == 1, na.rm = TRUE) - n_neg <- colSums(target == 0, na.rm = TRUE) + n_pos <- colSums(target == 1, na.rm = TRUE) + n_neg <- colSums(target == 0, na.rm = TRUE) - pos_mean_rank <- ranks %*% (target == 1) - pos_mean_rank <- sweep(pos_mean_rank, 2, n_pos * (n_pos + 1) / 2, "-") + pos_mean_rank <- ranks %*% (target == 1) + pos_mean_rank <- sweep(pos_mean_rank, 2, n_pos * (n_pos + 1) / 2, "-") - auc_matrix <- sweep(pos_mean_rank, 2, n_pos * n_neg, "/") - return(auc_matrix) + auc_matrix <- sweep(pos_mean_rank, 2, n_pos * n_neg, "/") + return(auc_matrix) } @@ -59,20 +60,18 @@ allAgainstAllAUCs <- function(B, target) { #' #' @export tscale <- function(x) { - if (!is.matrix(x) || !is.numeric(x)) { - stop("Input 'x' must be a numeric matrix.") - } - - row_means <- rowMeans(x, na.rm = TRUE) - row_sds <- sqrt(rowMeans((x - row_means)^2, na.rm = TRUE)) - row_sds[row_sds == 0 | is.na(row_sds)] <- 1 # avoid division by zero - - scaled <- sweep(sweep(x, 1, row_means, "-"), 1, row_sds, "/") - dimnames(scaled) <- dimnames(x) - scaled -} + if (!is.matrix(x) || !is.numeric(x)) { + stop("Input 'x' must be a numeric matrix.") + } + row_means <- rowMeans(x, na.rm = TRUE) + row_sds <- sqrt(rowMeans((x - row_means)^2, na.rm = TRUE)) + row_sds[row_sds == 0 | is.na(row_sds)] <- 1 # avoid division by zero + scaled <- sweep(sweep(x, 1, row_means, "-"), 1, row_sds, "/") + dimnames(scaled) <- dimnames(x) + scaled +} #' Print a concatenated message @@ -81,7 +80,7 @@ tscale <- function(x) { #' @param ... Character strings to concatenate and print. #' @return Invisibly returns NULL. Called for side effects (messages). mymessage <- function(...) { - message(...) + message(...) } #' Get maximum AUC per latent variable @@ -94,16 +93,16 @@ mymessage <- function(...) { #' #' @return A data frame with columns LV index and max_AUC. getMaxAUC <- function(summary, verbose = FALSE) { - max_auc_per_lv <- summary %>% - group_by(.data$`LV index`) %>% - summarize(max_AUC = max(.data$AUC, na.rm = TRUE)) %>% - ungroup() - - if (verbose) { - message("There are ", sum(max_auc_per_lv$max_AUC > 0.7), " LVs with AUC>0.70") - message("There are ", sum(max_auc_per_lv$max_AUC > 0.9), " LVs with AUC>0.90") - } - max_auc_per_lv + max_auc_per_lv <- summary %>% + group_by(.data$`LV index`) %>% + summarize(max_AUC = max(.data$AUC, na.rm = TRUE)) %>% + ungroup() + + if (verbose) { + message("There are ", sum(max_auc_per_lv$max_AUC > 0.7), " LVs with AUC>0.70") + message("There are ", sum(max_auc_per_lv$max_AUC > 0.9), " LVs with AUC>0.90") + } + max_auc_per_lv } #' Count number of latent variables exceeding AUC thresholds @@ -115,10 +114,10 @@ getMaxAUC <- function(summary, verbose = FALSE) { #' #' @return A named numeric vector with counts for thresholds 0.7, 0.8, and 0.9. getAUCstats <- function(summary) { - out <- getMaxAUC(summary) - unlist(lapply(c(0.7, 0.8, 0.9), function(x) { - sum(out$max_AUC > x) - })) + out <- getMaxAUC(summary) + unlist(lapply(c(0.7, 0.8, 0.9), function(x) { + sum(out$max_AUC > x) + })) } #' Greedy maximum correspondence from correlation matrix @@ -129,26 +128,26 @@ getAUCstats <- function(summary) { #' @param cor_mat A square numeric matrix of pairwise correlations (rows = items, cols = items). #' @return A vector of assignments (integer indices). max_correspondence_greedy <- function(cor_mat) { - n <- nrow(cor_mat) - used_rows <- rep(FALSE, n) - used_cols <- rep(FALSE, n) - assignment <- integer(n) - - corr_entries <- as.data.frame(which(!is.na(cor_mat), arr.ind = TRUE)) - corr_entries$val <- cor_mat[cbind(corr_entries$row, corr_entries$col)] - corr_entries <- corr_entries[order(-corr_entries$val), ] - - for (i in seq_len(nrow(corr_entries))) { - r <- corr_entries$row[i] - c <- corr_entries$col[i] - if (!used_rows[r] && !used_cols[c]) { - assignment[r] <- c - used_rows[r] <- TRUE - used_cols[c] <- TRUE + n <- nrow(cor_mat) + used_rows <- rep(FALSE, n) + used_cols <- rep(FALSE, n) + assignment <- integer(n) + + corr_entries <- as.data.frame(which(!is.na(cor_mat), arr.ind = TRUE)) + corr_entries$val <- cor_mat[cbind(corr_entries$row, corr_entries$col)] + corr_entries <- corr_entries[order(-corr_entries$val), ] + + for (i in seq_len(nrow(corr_entries))) { + r <- corr_entries$row[i] + c <- corr_entries$col[i] + if (!used_rows[r] && !used_cols[c]) { + assignment[r] <- c + used_rows[r] <- TRUE + used_cols[c] <- TRUE + } } - } - list(permutation = assignment, sum = sum(cor_mat[cbind(seq_len(n), assignment)])) + list(permutation = assignment, sum = sum(cor_mat[cbind(seq_len(n), assignment)])) } #' Download and read a GMT file from a URL @@ -164,7 +163,7 @@ max_correspondence_greedy <- function(cor_mat) { #' @return A named list where each element is a character vector of gene names for a given gene set. #' #' @examples -#' url <- 'https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=KEGG_2019_Human' +#' url <- "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=KEGG_2019_Human" #' gmt_list <- getGMT(url) #' # list available gene sets #' names(gmt_list) @@ -177,8 +176,8 @@ getGMT <- function(url, name = NULL, cache_dir = NULL, redownload = FALSE) { message("Auto-detected name: ", name) } if (is.null(cache_dir)) { - cache_dir <- tools::R_user_dir("CLAMP", "cache") - } + cache_dir <- tools::R_user_dir("CLAMP", "cache") + } cache_file <- file.path(cache_dir, paste0(name, ".gmt")) if (!file.exists(cache_file) || redownload) { message("Downloading ", name, " from Enrichr...") @@ -200,25 +199,27 @@ getGMT <- function(url, name = NULL, cache_dir = NULL, redownload = FALSE) { #' #' @param filename A \code{character(1)} string giving the path to a .gmt file. #' -#' @return A \code{list} where each element is a character vector of gene names, +#' @return A \code{list} where each element is a character vector of gene names, #' named by the gene set ID. #' #' @importFrom utils read.table #' @export #' #' @examples -#' # Bioconductor requires runnable examples. +#' # Bioconductor requires runnable examples. #' # We create a dummy GMT file for this example: #' gmt_file <- tempfile(fileext = ".gmt") #' writeLines( -#' c("PATHWAY_A\thttp://link.com\tGENE1\tGENE2\tGENE3", -#' "PATHWAY_B\thttp://link.com\tGENE2\tGENE4"), +#' c( +#' "PATHWAY_A\thttp://link.com\tGENE1\tGENE2\tGENE3", +#' "PATHWAY_B\thttp://link.com\tGENE2\tGENE4" +#' ), #' con = gmt_file #' ) -#' +#' #' # Run the function #' gs <- read_gmt(gmt_file) -#' +#' #' # Inspect results #' length(gs) #' names(gs) @@ -229,21 +230,21 @@ read_gmt <- function(filename) { } gmt <- list() - lines <- readLines(filename, encoding = "UTF-8") - lines <- iconv(lines, from = "UTF-8", to = "UTF-8", sub = "") - + lines <- readLines(filename, warn = FALSE) + lines <- iconv(lines, to = "UTF-8", sub = "") + for (line in lines) { # Bioc style: avoid complex nested regex if possible for clarity sp <- unlist(strsplit(trimws(line), "\t")) - + if (length(sp) < 3) next # Skip malformed lines - + set_name <- sp[1] # Columns 3 onwards are genes; removing potential comma-based metadata genes <- gsub(",.*$", "", sp[3:length(sp)]) gmt[[set_name]] <- sort(unique(genes)) } - + return(gmt) } @@ -259,12 +260,12 @@ read_gmt <- function(filename) { #' @examples #' # define a simple nested GMT list #' gmt1 <- list( -#' PathwayA = c('Gene1', 'Gene2', 'Gene3'), -#' PathwayB = c('Gene2', 'Gene4') +#' PathwayA = c("Gene1", "Gene2", "Gene3"), +#' PathwayB = c("Gene2", "Gene4") #' ) #' gmt2 <- list( -#' PathwayC = c('Gene1', 'Gene4'), -#' PathwayD = c('Gene3', 'Gene5') +#' PathwayC = c("Gene1", "Gene4"), +#' PathwayD = c("Gene3", "Gene5") #' ) #' # combine into a nested list #' nestedList <- list(gmt1 = gmt1, gmt2 = gmt2) @@ -272,34 +273,36 @@ read_gmt <- function(filename) { #' sparseMat <- gmtListToSparseMat(nestedList) #' @export gmtListToSparseMat <- function(gmtList) { - allnames <- unlist(lapply(gmtList, names)) - # there are usually no duplicates - stopifnot(all(table(allnames) == 1)) - allGenes <- unique(unlist(lapply(gmtList, unlist))) - - row_indices <- integer(0) - col_indices <- integer(0) - values <- integer(0) - for (gmt in seq_along(gmtList)) { - for (path in names(gmtList[[gmt]])) { - thisPathGenes <- gmtList[[gmt]][[path]] - iiGenes <- match(thisPathGenes, allGenes) - iPath <- match(path, allnames) - - # Store indices and values - row_indices <- c(row_indices, iiGenes) - col_indices <- c(col_indices, rep(iPath, length(iiGenes))) - values <- c(values, rep(1, length(iiGenes))) + allnames <- unlist(lapply(gmtList, names)) + # there are usually no duplicates + stopifnot(all(table(allnames) == 1)) + allGenes <- unique(unlist(lapply(gmtList, unlist))) + + row_indices <- integer(0) + col_indices <- integer(0) + values <- integer(0) + for (gmt in seq_along(gmtList)) { + for (path in names(gmtList[[gmt]])) { + thisPathGenes <- gmtList[[gmt]][[path]] + iiGenes <- match(thisPathGenes, allGenes) + iPath <- match(path, allnames) + + # Store indices and values + row_indices <- c(row_indices, iiGenes) + col_indices <- c(col_indices, rep(iPath, length(iiGenes))) + values <- c(values, rep(1, length(iiGenes))) + } } - } - # Use sparseMatrix to create the matrix in one go + # Use sparseMatrix to create the matrix in one go - pathMat <- Matrix::sparseMatrix(i = row_indices, j = col_indices, x = values, dims = c(length(allGenes), - length(allnames))) - rownames(pathMat) <- allGenes - colnames(pathMat) <- allnames - pathMat + pathMat <- Matrix::sparseMatrix(i = row_indices, j = col_indices, x = values, dims = c( + length(allGenes), + length(allnames) + )) + rownames(pathMat) <- allGenes + colnames(pathMat) <- allnames + pathMat } #' Find common row names between two matrices or data frames @@ -311,7 +314,7 @@ gmtListToSparseMat <- function(gmtList) { #' #' @return A character vector of row names common to both inputs. commonRows <- function(data1, data2) { - intersect(rownames(data1), rownames(data2)) + intersect(rownames(data1), rownames(data2)) } #' Clean a Filebacked Big Matrix (FBM) by log-transforming and handling NAs @@ -340,42 +343,42 @@ commonRows <- function(data1, data2) { #' #' @export cleanFBM <- function(fbm, ncores = 1) { - # Block‐wise scan for max and NA - stats <- big_apply(fbm, a.FUN = function(X, ind) { - vals <- X[, ind, drop = FALSE] - list(max = if (all(is.na(vals))) NA_real_ else max(vals, na.rm = TRUE), na = anyNA(vals)) - }, a.combine = function(...) { - Reduce(function(a, b) { - list(max = max(a$max, b$max, na.rm = TRUE), na = a$na || b$na) - }, list(...)) - }, ind = bigstatsr::cols_along(fbm), ncores = ncores, ) - - max_value <- stats$max - has_na <- stats$na - - # Log2 transform if necessary - if (!is.na(max_value) && max_value >= 100) { - message("Applying log2 transformation") - big_apply(fbm, a.FUN = function(X, ind) { - X[, ind] <- log2(X[, ind] + 1) - NULL - }, ind = bigstatsr::cols_along(fbm), ncores = ncores, ) - } else { - message("Already on log scale or all NA") - } - - # Fill NAs if present - if (has_na) { - message("Filling NAs with 0") - big_apply(fbm, a.FUN = function(X, ind) { - X[, ind][is.na(X[, ind])] <- 0 - NULL + # Block‐wise scan for max and NA + stats <- big_apply(fbm, a.FUN = function(X, ind) { + vals <- X[, ind, drop = FALSE] + list(max = if (all(is.na(vals))) NA_real_ else max(vals, na.rm = TRUE), na = anyNA(vals)) + }, a.combine = function(...) { + Reduce(function(a, b) { + list(max = max(a$max, b$max, na.rm = TRUE), na = a$na || b$na) + }, list(...)) }, ind = bigstatsr::cols_along(fbm), ncores = ncores, ) - } else { - message("No NA values found") - } - return(list(max_value = max_value, had_na = has_na)) + max_value <- stats$max + has_na <- stats$na + + # Log2 transform if necessary + if (!is.na(max_value) && max_value >= 100) { + message("Applying log2 transformation") + big_apply(fbm, a.FUN = function(X, ind) { + X[, ind] <- log2(X[, ind] + 1) + NULL + }, ind = bigstatsr::cols_along(fbm), ncores = ncores, ) + } else { + message("Already on log scale or all NA") + } + + # Fill NAs if present + if (has_na) { + message("Filling NAs with 0") + big_apply(fbm, a.FUN = function(X, ind) { + X[, ind][is.na(X[, ind])] <- 0 + NULL + }, ind = bigstatsr::cols_along(fbm), ncores = ncores, ) + } else { + message("No NA values found") + } + + return(list(max_value = max_value, had_na = has_na)) } #' Compute row-wise sum and sum of squares for a Filebacked Big Matrix @@ -392,20 +395,24 @@ cleanFBM <- function(fbm, ncores = 1) { #' } #' computeRowStatsFBM <- function(fbm, ncores = 1) { - # Compute row sums in blocks - row_sums <- big_apply(fbm, a.FUN = function(X, ind) rowSums(X[, ind]), a.combine = "plus", - ncores = ncores) + # Compute row sums in blocks + row_sums <- big_apply(fbm, + a.FUN = function(X, ind) rowSums(X[, ind]), a.combine = "plus", + ncores = ncores + ) - # Compute row sums of squares in blocks - row_sums_sq <- big_apply(fbm, a.FUN = function(X, ind) rowSums(X[, ind]^2), a.combine = "plus", - ncores = ncores) + # Compute row sums of squares in blocks + row_sums_sq <- big_apply(fbm, + a.FUN = function(X, ind) rowSums(X[, ind]^2), a.combine = "plus", + ncores = ncores + ) - n_cols <- ncol(fbm) - # Final means and variances - row_means <- row_sums/n_cols - row_variances <- (row_sums_sq/n_cols) - (row_means^2) + n_cols <- ncol(fbm) + # Final means and variances + row_means <- row_sums / n_cols + row_variances <- (row_sums_sq / n_cols) - (row_means^2) - list(row_means = row_means, row_variances = row_variances) + list(row_means = row_means, row_variances = row_variances) } #' Filter rows of a Filebacked Big Matrix based on mean and variance @@ -438,41 +445,41 @@ computeRowStatsFBM <- function(fbm, ncores = 1) { #' } #' @importFrom bigstatsr cols_along big_copy #' @export -filterFBM<- function(fbm, rowStats, keep_samples_idx=NULL, mean_cutoff = NULL, var_cutoff = NULL, backingfile = "filtered_fbm") { - row_means <- rowStats$row_means - row_variances <- rowStats$row_variances - - # Determine rows to keep based on cutoffs - keep_rows <- rep(TRUE, length(row_means)) # Default: keep all rows - - if (!is.null(mean_cutoff)) { - keep_rows <- keep_rows & (row_means >= mean_cutoff) - } - - if (!is.null(var_cutoff)) { - keep_rows <- keep_rows & (row_variances >= var_cutoff) - } - - if (is.null(keep_samples_idx)) { - keep_samples_idx <- cols_along(fbm) - } - - # Number of rows to keep - n_kept <- sum(keep_rows) - - if (n_kept == 0) { - stop("No rows meet the filtering criteria.") - } - - # Create a new FBM with the filtered data - fbm_filtered <- big_copy( - X = fbm, - ind.row = which(keep_rows), - ind.col = keep_samples_idx, - backingfile = backingfile - ) - - return(list(fbm_filtered = fbm_filtered, kept_rows = which(keep_rows))) +filterFBM <- function(fbm, rowStats, keep_samples_idx = NULL, mean_cutoff = NULL, var_cutoff = NULL, backingfile = "filtered_fbm") { + row_means <- rowStats$row_means + row_variances <- rowStats$row_variances + + # Determine rows to keep based on cutoffs + keep_rows <- rep(TRUE, length(row_means)) # Default: keep all rows + + if (!is.null(mean_cutoff)) { + keep_rows <- keep_rows & (row_means >= mean_cutoff) + } + + if (!is.null(var_cutoff)) { + keep_rows <- keep_rows & (row_variances >= var_cutoff) + } + + if (is.null(keep_samples_idx)) { + keep_samples_idx <- cols_along(fbm) + } + + # Number of rows to keep + n_kept <- sum(keep_rows) + + if (n_kept == 0) { + stop("No rows meet the filtering criteria.") + } + + # Create a new FBM with the filtered data + fbm_filtered <- big_copy( + X = fbm, + ind.row = which(keep_rows), + ind.col = keep_samples_idx, + backingfile = backingfile + ) + + return(list(fbm_filtered = fbm_filtered, kept_rows = which(keep_rows))) } #' Z-score a filtered expression matrix for CLAMP @@ -492,7 +499,7 @@ filterFBM<- function(fbm, rowStats, keep_samples_idx=NULL, mean_cutoff = NULL, v #' 8, 10, 12 # gene2 counts #' ), #' nrow = 2, byrow = TRUE, -#' dimnames = list(c('gene1', 'gene2'), paste0('sample', seq_len(3))) +#' dimnames = list(c("gene1", "gene2"), paste0("sample", seq_len(3))) #' ) #' #' # compute per‐gene mean and variance @@ -562,66 +569,70 @@ zscoreCLAMP <- function(Y_filtered, rowStats) { #' 100, 200, 300 # geneC #' ), #' nrow = 3, byrow = TRUE, -#' dimnames = list(c('geneA', 'geneB', 'geneC'), paste0('s', seq_len(3))) +#' dimnames = list(c("geneA", "geneB", "geneC"), paste0("s", seq_len(3))) #' ) #' fbm <- FBM(nrow(mat), ncol(mat), init = mat) #' #' # preprocess without filtering (all genes kept) #' res_all <- preprocessCLAMPFBM(fbm) #' @export -preprocessCLAMPFBM <- function(fbm, mean_cutoff = NULL, var_cutoff = NULL, backingfile = NULL, - block_size = 1000, ncores = 1) { +preprocessCLAMPFBM <- function( + fbm, mean_cutoff = NULL, var_cutoff = NULL, backingfile = NULL, + block_size = 1000, ncores = 1 +) { n_r <- nrow(fbm) n_c <- ncol(fbm) - base_bk <- if (is.null(backingfile)) { - # remove the .bk extension if it exists in the original path - clean_path <- sub("\\.bk$", "", fbm$backingfile) - paste0(clean_path, "_preproc") + base_bk <- if (is.null(backingfile)) { + # remove the .bk extension if it exists in the original path + clean_path <- sub("\\.bk$", "", fbm$backingfile) + paste0(clean_path, "_preproc") } else { - # remove .bk if they included it - sub("\\.bk$", "", backingfile) + # remove .bk if they included it + sub("\\.bk$", "", backingfile) } - # Make a writable copy - fbm_copy <- FBM(nrow = n_r, ncol = n_c, backingfile = base_bk, create_bk = TRUE) + # Make a writable copy + fbm_copy <- FBM(nrow = n_r, ncol = n_c, backingfile = base_bk, create_bk = TRUE) - # copy all data - for (rs in seq(1, n_r, by = block_size)) { - rows <- rs:min(rs + block_size - 1L, n_r) - fbm_copy[rows, ] <- fbm[rows, ] - } + # copy all data + for (rs in seq(1, n_r, by = block_size)) { + rows <- rs:min(rs + block_size - 1L, n_r) + fbm_copy[rows, ] <- fbm[rows, ] + } - if (ncores > 1) { - # if we are parallelizing, then disable BLAS parallelization - options(bigstatsr.check.parallel.blas = FALSE) - blas_nproc <- getOption("default.nproc.blas") - options(default.nproc.blas = NULL) - } + if (ncores > 1) { + # if we are parallelizing, then disable BLAS parallelization + options(bigstatsr.check.parallel.blas = FALSE) + blas_nproc <- getOption("default.nproc.blas") + options(default.nproc.blas = NULL) + } - # Clean in-place (log2 if needed, fill NAs) - cleanFBM(fbm_copy, ncores) + # Clean in-place (log2 if needed, fill NAs) + cleanFBM(fbm_copy, ncores) - # Compute row stats on cleaned copy - rs_all <- computeRowStatsFBM(fbm_copy, ncores) + # Compute row stats on cleaned copy + rs_all <- computeRowStatsFBM(fbm_copy, ncores) - if (ncores > 1) { - options(bigstatsr.check.parallel.blas = TRUE) - options(default.nproc.blas = blas_nproc) - } + if (ncores > 1) { + options(bigstatsr.check.parallel.blas = TRUE) + options(default.nproc.blas = blas_nproc) + } - # Filter rows, writing to a new filtered FBM - filt_bk <- paste0(base_bk, "_filtered") - filter_res <- filterFBM(fbm_copy, rowStats = rs_all, mean_cutoff = mean_cutoff, - var_cutoff = var_cutoff, backingfile = filt_bk) + # Filter rows, writing to a new filtered FBM + filt_bk <- paste0(base_bk, "_filtered") + filter_res <- filterFBM(fbm_copy, + rowStats = rs_all, mean_cutoff = mean_cutoff, + var_cutoff = var_cutoff, backingfile = filt_bk + ) - fbm_filtered <- filter_res$fbm_filtered - kept_rows <- filter_res$kept_rows + fbm_filtered <- filter_res$fbm_filtered + kept_rows <- filter_res$kept_rows - # Subset stats to kept rows - stats_filt <- list(row_means = rs_all$row_means[kept_rows], row_variances = rs_all$row_variances[kept_rows]) + # Subset stats to kept rows + stats_filt <- list(row_means = rs_all$row_means[kept_rows], row_variances = rs_all$row_variances[kept_rows]) - list(fbm_filtered = fbm_filtered, rowStats = stats_filt, kept_rows = kept_rows) + list(fbm_filtered = fbm_filtered, rowStats = stats_filt, kept_rows = kept_rows) } #' Z-score a filtered FBM in-place @@ -651,26 +662,31 @@ zscoreCLAMPFBM <- function(fbm_filtered, rowStats, chunk_size = 1000, ncores = 1 sds <- sqrt(rowStats$row_variances) sds[!is.finite(sds) | sds == 0] <- 1 - if (ncores > 1) { - options(bigstatsr.check.parallel.blas = FALSE) - old_blas <- getOption("default.nproc.blas") - options(default.nproc.blas = NULL) - on.exit({ - options(bigstatsr.check.parallel.blas = TRUE) - options(default.nproc.blas = old_blas) - }, add = TRUE) - } - - bigstatsr::big_apply(fbm_filtered, a.FUN = function(X, ind, means, sds) { - block <- X[, ind, drop = FALSE] - block <- sweep(block, 1, means, "-") - block <- sweep(block, 1, sds, "/") - X[, ind] <- block - integer(0) - }, a.combine = "c", ind = bigstatsr::cols_along(fbm_filtered), block.size = chunk_size, - ncores = ncores, means = means, sds = sds) - - invisible(NULL) + if (ncores > 1) { + options(bigstatsr.check.parallel.blas = FALSE) + old_blas <- getOption("default.nproc.blas") + options(default.nproc.blas = NULL) + on.exit( + { + options(bigstatsr.check.parallel.blas = TRUE) + options(default.nproc.blas = old_blas) + }, + add = TRUE + ) + } + + bigstatsr::big_apply(fbm_filtered, + a.FUN = function(X, ind, means, sds) { + block <- X[, ind, drop = FALSE] + block <- sweep(block, 1, means, "-") + block <- sweep(block, 1, sds, "/") + X[, ind] <- block + integer(0) + }, a.combine = "c", ind = bigstatsr::cols_along(fbm_filtered), block.size = chunk_size, + ncores = ncores, means = means, sds = sds + ) + + invisible(NULL) } #' Preprocess an expression matrix for CLAMP @@ -697,7 +713,7 @@ zscoreCLAMPFBM <- function(fbm_filtered, rowStats, chunk_size = 1000, ncores = 1 #' 4, 8, 13 #' ), #' nrow = 4, byrow = FALSE, -#' dimnames = list(paste0('gene', seq_len(4)), paste0('sample', seq_len(3))) +#' dimnames = list(paste0("gene", seq_len(4)), paste0("sample", seq_len(3))) #' ) #' #' # keep genes with mean >= 6 and variance >= 2 @@ -711,20 +727,20 @@ preprocessCLAMP <- function(Y, mean_cutoff = 0, var_cutoff = 0) { row_mean <- rowMeans(Y, na.rm = TRUE) row_var <- apply(Y, 1, stats::var, na.rm = TRUE) - rowStats <- data.frame(mean = row_mean, variance = row_var, stringsAsFactors = FALSE) - rownames(rowStats) <- rownames(Y) + rowStats <- data.frame(mean = row_mean, variance = row_var, stringsAsFactors = FALSE) + rownames(rowStats) <- rownames(Y) - # Identify genes passing both thresholds - keep <- which(rowStats$mean >= mean_cutoff & rowStats$variance >= var_cutoff) - if (length(keep) == 0) { - stop("No genes passed the mean/variance filters.") - } + # Identify genes passing both thresholds + keep <- which(rowStats$mean >= mean_cutoff & rowStats$variance >= var_cutoff) + if (length(keep) == 0) { + stop("No genes passed the mean/variance filters.") + } - # Subset matrix and stats - Y_filtered <- Y[keep, , drop = FALSE] - rowStats_filtered <- rowStats[keep, , drop = FALSE] + # Subset matrix and stats + Y_filtered <- Y[keep, , drop = FALSE] + rowStats_filtered <- rowStats[keep, , drop = FALSE] - return(list(Y_filtered = Y_filtered, rowStats = rowStats_filtered, kept_rows = keep)) + return(list(Y_filtered = Y_filtered, rowStats = rowStats_filtered, kept_rows = keep)) } #' Compute counts-per-million (CPM) for CLAMP pipelines @@ -760,7 +776,7 @@ cpmCLAMP <- function(counts) { #' library(bigstatsr) #' mat <- matrix(c(10, 20, 30, 40, 50, 60), #' nrow = 2, -#' dimnames = list(c('gene1', 'gene2'), paste0('sample', seq_len(3))) +#' dimnames = list(c("gene1", "gene2"), paste0("sample", seq_len(3))) #' ) #' fbm <- FBM(nrow(mat), ncol(mat), init = mat) #' cpmCLAMPFBM(fbm, block_size = 1) @@ -774,34 +790,41 @@ cpmCLAMPFBM <- function(fbm_counts, block_size = 1000, ncores = 1) { stop("`block_size` must be a positive integer.") } - # Avoid BLAS oversubscription when parallelizing - if (ncores > 1) { - options(bigstatsr.check.parallel.blas = FALSE) - old_blas <- getOption("default.nproc.blas") - options(default.nproc.blas = NULL) - on.exit({ - options(bigstatsr.check.parallel.blas = TRUE) - options(default.nproc.blas = old_blas) - }, add = TRUE) - } - - # Library sizes (sum per column), processed in column chunks - lib_sizes <- bigstatsr::big_apply(fbm_counts, a.FUN = function(X, ind) { - colSums(X[, ind, drop = FALSE]) - }, a.combine = "c", ind = bigstatsr::cols_along(fbm_counts), block.size = block_size, - ncores = ncores) - lib_sizes[lib_sizes == 0] <- 1 - - # Divide each column by its library size and scale to CPM, in-place - bigstatsr::big_apply(fbm_counts, a.FUN = function(X, ind, libs) { - blk <- X[, ind, drop = FALSE] - blk <- sweep(blk, 2, libs[ind], "/") * 1e+06 - X[, ind] <- blk - integer(0) - }, a.combine = "c", ind = bigstatsr::cols_along(fbm_counts), block.size = block_size, - ncores = ncores, libs = lib_sizes) - - invisible(fbm_counts) + # Avoid BLAS oversubscription when parallelizing + if (ncores > 1) { + options(bigstatsr.check.parallel.blas = FALSE) + old_blas <- getOption("default.nproc.blas") + options(default.nproc.blas = NULL) + on.exit( + { + options(bigstatsr.check.parallel.blas = TRUE) + options(default.nproc.blas = old_blas) + }, + add = TRUE + ) + } + + # Library sizes (sum per column), processed in column chunks + lib_sizes <- bigstatsr::big_apply(fbm_counts, + a.FUN = function(X, ind) { + colSums(X[, ind, drop = FALSE]) + }, a.combine = "c", ind = bigstatsr::cols_along(fbm_counts), block.size = block_size, + ncores = ncores + ) + lib_sizes[lib_sizes == 0] <- 1 + + # Divide each column by its library size and scale to CPM, in-place + bigstatsr::big_apply(fbm_counts, + a.FUN = function(X, ind, libs) { + blk <- X[, ind, drop = FALSE] + blk <- sweep(blk, 2, libs[ind], "/") * 1e+06 + X[, ind] <- blk + integer(0) + }, a.combine = "c", ind = bigstatsr::cols_along(fbm_counts), block.size = block_size, + ncores = ncores, libs = lib_sizes + ) + + invisible(fbm_counts) } #' Find the location of the maximum of a smoothing spline #' @@ -823,12 +846,12 @@ cpmCLAMPFBM <- function(fbm_counts, block_size = 1000, ncores = 1) { #' @importFrom stats smooth.spline predict #' @export findSplineMax <- function(x, y, n = 1000, spar = NULL) { - stopifnot(is.numeric(x), is.numeric(y), length(x) == length(y)) - fit <- stats::smooth.spline(x, y, spar = spar) - grid <- seq(min(x), max(x), length.out = n) - pred <- stats::predict(fit, grid) - max_idx <- which.max(pred$y) - list(x = pred$x[max_idx], y = pred$y[max_idx]) + stopifnot(is.numeric(x), is.numeric(y), length(x) == length(y)) + fit <- stats::smooth.spline(x, y, spar = spar) + grid <- seq(min(x), max(x), length.out = n) + pred <- stats::predict(fit, grid) + max_idx <- which.max(pred$y) + list(x = pred$x[max_idx], y = pred$y[max_idx]) } #' Squash extreme z-scores @@ -845,8 +868,8 @@ findSplineMax <- function(x, y, n = 1000, spar = NULL) { #' #' @export squashZscore <- function(zdata, maxScore = 2) { - stopifnot(is.numeric(zdata), is.numeric(maxScore), length(maxScore) == 1) - maxScore * tanh(zdata / maxScore) + stopifnot(is.numeric(zdata), is.numeric(maxScore), length(maxScore) == 1) + maxScore * tanh(zdata / maxScore) } @@ -873,52 +896,51 @@ squashZscore <- function(zdata, maxScore = 2) { #' #' @export getScaleFromSVs <- function(sv, n, min_r2 = 0.95) { - k <- length(sv) - if(k<20){ - - stop("Need at least 20 singular values ") - } - if (k ==n){ - #drop the last few - sv <- sv[seq_len(k-5)] k <- length(sv) - } - fallback <- sv[ceiling(0.75 * k)] + if (k < 20) { + stop("Need at least 20 singular values ") + } + if (k == n) { + # drop the last few + sv <- sv[seq_len(k - 5)] + k <- length(sv) + } + fallback <- sv[ceiling(0.75 * k)] + + best_r2 <- -Inf + best_drop <- 0 + + for (frac_drop in seq(0, 0.8, by = 0.01)) { + drop <- ceiling(k * frac_drop) + if (k - drop < 4) next + x <- (drop + 1):k + fit <- lm(sv[x] ~ x) + r2 <- summary(fit)$r.squared + if (r2 > best_r2) { + best_r2 <- r2 + best_drop <- drop + } + } + + if (best_r2 < min_r2) { + scale <- fallback + k <- NULL + return(list(scale = scale)) + } - best_r2 <- -Inf - best_drop <- 0 - for (frac_drop in seq(0, 0.8, by = 0.01)) { - drop <- ceiling(k * frac_drop) - if (k - drop < 4) next - x <- (drop + 1):k + x <- (best_drop + 1):k fit <- lm(sv[x] ~ x) - r2 <- summary(fit)$r.squared - if (r2 > best_r2) { - best_r2 <- r2 - best_drop <- drop + y_pred <- predict(fit, newdata = data.frame(x = seq_len(n))) + + if (any(y_pred < 0)) { + scale <- fallback + k <- NULL + return(list(scale = scale)) } - } - - if (best_r2 < min_r2){ - scale <- fallback - k <- NULL - return(list(scale=scale)) - } - - - x <- (best_drop + 1):k - fit <- lm(sv[x] ~ x) - y_pred <- predict(fit, newdata = data.frame(x = seq_len(n))) - - if (any(y_pred < 0)){ - scale <- fallback - k <- NULL - return(list(scale=scale)) - } - scale <- median(y_pred) - k <- best_drop - return(list(scale=scale, k=k)) + scale <- median(y_pred) + k <- best_drop + return(list(scale = scale, k = k)) } #' One-to-one masking of maximum associations @@ -940,16 +962,16 @@ getScaleFromSVs <- function(sv, n, min_r2 = 0.95) { #' #' @export oneToOneMask <- function(cc) { - cc <- as.matrix(cc) - cc_out <- matrix(-100, nrow(cc), ncol(cc)) - tmp <- cc - for (i in seq_len(ncol(cc))) { - imax <- which(tmp == max(tmp, na.rm = TRUE), arr.ind = TRUE)[1, ] - cc_out[imax[1], imax[2]] <- cc[imax[1], imax[2]] - tmp[imax[1], ] <- -100 - tmp[, imax[2]] <- -100 - } - return(cc_out) + cc <- as.matrix(cc) + cc_out <- matrix(-100, nrow(cc), ncol(cc)) + tmp <- cc + for (i in seq_len(ncol(cc))) { + imax <- which(tmp == max(tmp, na.rm = TRUE), arr.ind = TRUE)[1, ] + cc_out[imax[1], imax[2]] <- cc[imax[1], imax[2]] + tmp[imax[1], ] <- -100 + tmp[, imax[2]] <- -100 + } + return(cc_out) } #' Select default number of components for a CLAMP solver SVD @@ -959,15 +981,15 @@ oneToOneMask <- function(cc) { #' not provided explicitly. Other SVD contexts use their own heuristics. #' #' @param Y A matrix-like object (dense matrix, `dgCMatrix`, or `FBM`). -#' +#' #' @return An integer: `max(2, floor((min(nrow(Y), ncol(Y)) - 1) / 4))`. -#' +#' #' @examples #' select_svd_k(matrix(0, nrow = 100, ncol = 20)) -#' +#' #' @export select_svd_k <- function(Y) { - return(max(2, floor((min(nrow(Y), ncol(Y)) - 1) / 4))) + return(max(2, floor((min(nrow(Y), ncol(Y)) - 1) / 4))) } #' Compute a truncated SVD for a CLAMP input matrix @@ -980,22 +1002,26 @@ select_svd_k <- function(Y) { #' @param Y A matrix-like object (dense matrix, `dgCMatrix`, or `FBM`). #' @param k Integer number of components to compute. If `NULL` (the #' default), `select_svd_k(Y)` is used. -#' +#' #' @return A list with `d`, `u`, `v` components (structure depends on the #' backend but these three fields are always present). -#' +#' #' @examples #' set.seed(1) #' Y <- matrix(rnorm(100), nrow = 20, ncol = 5) #' res <- compute_svd(Y, k = 3) #' length(res$d) -#' +#' #' @export compute_svd <- function(Y, k = NULL) { - if (is.null(k)) k <- select_svd_k(Y) - if (inherits(Y, "FBM")) return(bigstatsr::big_SVD(X = Y, k = k)) - if (inherits(Y, "dgCMatrix")) return(irlba::irlba(Y, nv = k)) - rsvd::rsvd(Y, k = k) + if (is.null(k)) k <- select_svd_k(Y) + if (inherits(Y, "FBM")) { + return(bigstatsr::big_SVD(X = Y, k = k)) + } + if (inherits(Y, "dgCMatrix")) { + return(irlba::irlba(Y, nv = k)) + } + rsvd::rsvd(Y, k = k) } #' Select default number of CLAMP latent variables from an SVD @@ -1027,46 +1053,48 @@ compute_svd <- function(Y, k = NULL) { #' @param data Raw data matrix. Required for `"permutation"` (row-normalized #' internally) and `"gavish_donoho"` (used for `n_genes`). #' @param B Number of permutations for `"permutation"`. -#' +#' #' @return A list with: #' \describe{ #' \item{`clamp_k`}{Selected number of latent variables.} #' \item{`scale`}{Scale value used downstream for default L1 / L2 #' regularization.} #' } -#' +#' #' @export select_clamp_k <- function(svdres, n_samples, svd_k, - method = c("elbow", "permutation", - "gavish_donoho", "scaleSVs"), + method = c( + "elbow", "permutation", + "gavish_donoho", "scaleSVs" + ), data = NULL, B = 20) { - method <- match.arg(method) - - if (method == "scaleSVs") { - scale.res <- getScaleFromSVs(svdres$d, n_samples) - clamp_k <- min(floor(scale.res$k * 1.5), svd_k) - return(list(clamp_k = clamp_k, scale = scale.res$scale)) - } - - if (method == "elbow") { - clamp_k <- num.pc(list(d = svdres$d), method = "elbow") - } else if (method == "permutation") { - if (is.null(data)) { - stop("`data` (raw row-normalized matrix) is required for method = 'permutation'.") + method <- match.arg(method) + + if (method == "scaleSVs") { + scale.res <- getScaleFromSVs(svdres$d, n_samples) + clamp_k <- min(floor(scale.res$k * 1.5), svd_k) + return(list(clamp_k = clamp_k, scale = scale.res$scale)) } - clamp_k <- num.pc(data, method = "permutation", B = B) - } else if (method == "gavish_donoho") { - if (is.null(data)) { - stop("`data` is required for method = 'gavish_donoho'.") + + if (method == "elbow") { + clamp_k <- num.pc(list(d = svdres$d), method = "elbow") + } else if (method == "permutation") { + if (is.null(data)) { + stop("`data` (raw row-normalized matrix) is required for method = 'permutation'.") + } + clamp_k <- num.pc(data, method = "permutation", B = B) + } else if (method == "gavish_donoho") { + if (is.null(data)) { + stop("`data` is required for method = 'gavish_donoho'.") + } + eigenvalues <- sort(svdres$d^2 / (n_samples - 1), decreasing = TRUE) + clamp_k <- PCAtools::chooseGavishDonoho( + .dim = c(nrow(data), n_samples), + var.explained = eigenvalues, + noise = median(eigenvalues) + ) } - eigenvalues <- sort(svdres$d^2 / (n_samples - 1), decreasing = TRUE) - clamp_k <- PCAtools::chooseGavishDonoho( - .dim = c(nrow(data), n_samples), - var.explained = eigenvalues, - noise = median(eigenvalues) - ) - } - clamp_k <- min(clamp_k * 2, svd_k) - list(clamp_k = clamp_k, scale = svdres$d[clamp_k]) -} \ No newline at end of file + clamp_k <- min(clamp_k * 2, svd_k) + list(clamp_k = clamp_k, scale = svdres$d[clamp_k]) +} diff --git a/R/zzz.R b/R/zzz.R index e892fa7..a502c7a 100644 --- a/R/zzz.R +++ b/R/zzz.R @@ -23,4 +23,4 @@ utils::globalVariables(c("Cor1", "Cor2", "Label")) utils::globalVariables(c("iter.full.start")) -NULL \ No newline at end of file +NULL diff --git a/tests/testthat/test-CLAMPbase.R b/tests/testthat/test-CLAMPbase.R index 1f20eda..e141f16 100644 --- a/tests/testthat/test-CLAMPbase.R +++ b/tests/testthat/test-CLAMPbase.R @@ -1,27 +1,27 @@ test_that("CLAMPbase and returns B, Z, U", { - set.seed(1) + set.seed(1) - data("dataWholeBlood", package = "CLAMP") - data("xCell", package = "CLAMP") + data("dataWholeBlood", package = "CLAMP") + data("xCell", package = "CLAMP") - matchedPaths <- getMatchedPathwayMatList( - xCell, - new.genes = rownames(dataWholeBlood), - min.genes = 3 - ) - - base <- CLAMPbase( - Y = dataWholeBlood, - trace = FALSE, - adaptive.p = 0.05 - ) - - expect_type(base, "list") - expect_true(all(c("B", "Z") %in% names(base))) - expect_true(is.matrix(base$B)) - expect_true(is.matrix(base$Z)) - expect_equal(rownames(base$Z), rownames(dataWholeBlood)) - expect_equal(colnames(base$B), colnames(dataWholeBlood)) - expect_equal(rownames(base$B), colnames(base$Z)) - expect_equal(rownames(base$B), paste0("LV", seq_len(nrow(base$B)))) + matchedPaths <- getMatchedPathwayMatList( + xCell, + new.genes = rownames(dataWholeBlood), + min.genes = 3 + ) + + base <- CLAMPbase( + Y = dataWholeBlood, + trace = FALSE, + adaptive.p = 0.05 + ) + + expect_type(base, "list") + expect_true(all(c("B", "Z") %in% names(base))) + expect_true(is.matrix(base$B)) + expect_true(is.matrix(base$Z)) + expect_equal(rownames(base$Z), rownames(dataWholeBlood)) + expect_equal(colnames(base$B), colnames(dataWholeBlood)) + expect_equal(rownames(base$B), colnames(base$Z)) + expect_equal(rownames(base$B), paste0("LV", seq_len(nrow(base$B)))) }) diff --git a/tests/testthat/test-CLAMPfull.R b/tests/testthat/test-CLAMPfull.R index 62a4227..33db96d 100644 --- a/tests/testthat/test-CLAMPfull.R +++ b/tests/testthat/test-CLAMPfull.R @@ -1,82 +1,82 @@ test_that("CLAMPfull and returns B, Z, U", { - set.seed(1) + set.seed(1) - data("dataWholeBlood", package = "CLAMP") - data("xCell", package = "CLAMP") + data("dataWholeBlood", package = "CLAMP") + data("xCell", package = "CLAMP") - matchedPaths <- getMatchedPathwayMatList( - xCell, - new.genes = rownames(dataWholeBlood), - min.genes = 3 - ) - - base <- CLAMPbase( - Y = dataWholeBlood, - trace = FALSE, - adaptive.p = 0.05 - ) - - full <- CLAMPfull( - Y = dataWholeBlood, - priorMat = matchedPaths, - clamp.base.result = base, - trace = FALSE, - max.iter = 1, - max.U.updates = 0 - ) + matchedPaths <- getMatchedPathwayMatList( + xCell, + new.genes = rownames(dataWholeBlood), + min.genes = 3 + ) - expect_type(full, "list") - expect_true(all(c("B", "Z", "U") %in% names(full))) - expect_true(is.matrix(full$B)) - expect_true(is.matrix(full$Z)) - expect_true(is.matrix(full$U)) - expect_equal(rownames(full$Z), rownames(dataWholeBlood)) - expect_equal(colnames(full$B), colnames(dataWholeBlood)) - expect_equal(rownames(full$B), colnames(full$Z)) - expect_equal(colnames(full$U), rownames(full$B)) - expect_equal(rownames(full$U), colnames(matchedPaths)) + base <- CLAMPbase( + Y = dataWholeBlood, + trace = FALSE, + adaptive.p = 0.05 + ) + + full <- CLAMPfull( + Y = dataWholeBlood, + priorMat = matchedPaths, + clamp.base.result = base, + trace = FALSE, + max.iter = 1, + max.U.updates = 0 + ) + + expect_type(full, "list") + expect_true(all(c("B", "Z", "U") %in% names(full))) + expect_true(is.matrix(full$B)) + expect_true(is.matrix(full$Z)) + expect_true(is.matrix(full$U)) + expect_equal(rownames(full$Z), rownames(dataWholeBlood)) + expect_equal(colnames(full$B), colnames(dataWholeBlood)) + expect_equal(rownames(full$B), colnames(full$Z)) + expect_equal(colnames(full$U), rownames(full$B)) + expect_equal(rownames(full$U), colnames(matchedPaths)) }) test_that("CLAMPfullnVP returns matrix B and Z with labels", { - set.seed(2) + set.seed(2) - mat <- matrix( - rnorm(80), - nrow = 10, - dimnames = list(paste0("Gene", 1:10), paste0("Sample", 1:8)) - ) - prior <- matrix( - sample(0:1, 30, replace = TRUE), - nrow = 10, - dimnames = list(rownames(mat), paste0("Path", 1:3)) - ) - prior[, 1] <- 1 - svdres <- rsvd::rsvd(mat, k = 4) + mat <- matrix( + rnorm(80), + nrow = 10, + dimnames = list(paste0("Gene", 1:10), paste0("Sample", 1:8)) + ) + prior <- matrix( + sample(0:1, 30, replace = TRUE), + nrow = 10, + dimnames = list(rownames(mat), paste0("Path", 1:3)) + ) + prior[, 1] <- 1 + svdres <- rsvd::rsvd(mat, k = 4) - base <- CLAMPbase( - Y = mat, - clamp_k = 3, - svdres = svdres, - trace = FALSE, - max.iter = 1 - ) + base <- CLAMPbase( + Y = mat, + clamp_k = 3, + svdres = svdres, + trace = FALSE, + max.iter = 1 + ) - full <- CLAMPfullnVP( - Y = mat, - priorMat = prior, - svdres = svdres, - clamp.base.result = base, - clamp_k = 3, - doCrossval = FALSE, - trace = FALSE, - max.iter = 1, - max.U.updates = 0, - minGenes = 0 - ) + full <- CLAMPfullnVP( + Y = mat, + priorMat = prior, + svdres = svdres, + clamp.base.result = base, + clamp_k = 3, + doCrossval = FALSE, + trace = FALSE, + max.iter = 1, + max.U.updates = 0, + minGenes = 0 + ) - expect_true(is.matrix(full$B)) - expect_true(is.matrix(full$Z)) - expect_equal(rownames(full$Z), rownames(mat)) - expect_equal(colnames(full$B), colnames(mat)) - expect_equal(rownames(full$B), colnames(full$Z)) + expect_true(is.matrix(full$B)) + expect_true(is.matrix(full$Z)) + expect_equal(rownames(full$Z), rownames(mat)) + expect_equal(colnames(full$B), colnames(mat)) + expect_equal(rownames(full$B), colnames(full$Z)) }) diff --git a/tests/testthat/test-compute_svd.R b/tests/testthat/test-compute_svd.R index 5e14048..3cfc70c 100644 --- a/tests/testthat/test-compute_svd.R +++ b/tests/testthat/test-compute_svd.R @@ -1,43 +1,43 @@ test_that("compute_svd returns d, u, v for a dense matrix", { - set.seed(1) - Y <- matrix(rnorm(100), nrow = 20, ncol = 5) - res <- compute_svd(Y, k = 3) - expect_true(all(c("d", "u", "v") %in% names(res))) - expect_length(res$d, 3) - expect_equal(dim(res$u), c(20, 3)) - expect_equal(dim(res$v), c(5, 3)) + set.seed(1) + Y <- matrix(rnorm(100), nrow = 20, ncol = 5) + res <- compute_svd(Y, k = 3) + expect_true(all(c("d", "u", "v") %in% names(res))) + expect_length(res$d, 3) + expect_equal(dim(res$u), c(20, 3)) + expect_equal(dim(res$v), c(5, 3)) }) test_that("compute_svd works on sparse dgCMatrix", { - set.seed(1) - Y <- Matrix::rsparsematrix(20, 10, density = 0.3) - res <- compute_svd(Y, k = 3) - expect_length(res$d, 3) - expect_equal(dim(res$u), c(20, 3)) - expect_equal(dim(res$v), c(10, 3)) + set.seed(1) + Y <- Matrix::rsparsematrix(20, 10, density = 0.3) + res <- compute_svd(Y, k = 3) + expect_length(res$d, 3) + expect_equal(dim(res$u), c(20, 3)) + expect_equal(dim(res$v), c(10, 3)) }) test_that("compute_svd works on FBM", { - skip_if_not_installed("bigstatsr") - set.seed(1) - Y <- bigstatsr::FBM(nrow = 30, ncol = 10, init = rnorm(300)) - res <- compute_svd(Y, k = 3) - expect_length(res$d, 3) + skip_if_not_installed("bigstatsr") + set.seed(1) + Y <- bigstatsr::FBM(nrow = 30, ncol = 10, init = rnorm(300)) + res <- compute_svd(Y, k = 3) + expect_length(res$d, 3) }) test_that("compute_svd defaults k to select_svd_k(Y) when k is NULL", { - set.seed(1) - Y <- matrix(rnorm(200), nrow = 20, ncol = 10) - res <- compute_svd(Y) - expect_length(res$d, select_svd_k(Y)) + set.seed(1) + Y <- matrix(rnorm(200), nrow = 20, ncol = 10) + res <- compute_svd(Y) + expect_length(res$d, select_svd_k(Y)) }) test_that("compute_svd recovers singular values on a known rank-k matrix", { - set.seed(1) - u <- qr.Q(qr(matrix(rnorm(50), 10, 5))) - v <- qr.Q(qr(matrix(rnorm(25), 5, 5))) - d_true <- c(10, 5, 3, 1, 0.5) - Y <- u %*% diag(d_true) %*% t(v) - res <- compute_svd(Y, k = 5) - expect_equal(sort(res$d, decreasing = TRUE), d_true, tolerance = 1e-6) + set.seed(1) + u <- qr.Q(qr(matrix(rnorm(50), 10, 5))) + v <- qr.Q(qr(matrix(rnorm(25), 5, 5))) + d_true <- c(10, 5, 3, 1, 0.5) + Y <- u %*% diag(d_true) %*% t(v) + res <- compute_svd(Y, k = 5) + expect_equal(sort(res$d, decreasing = TRUE), d_true, tolerance = 1e-6) }) diff --git a/tests/testthat/test-getGMT.R b/tests/testthat/test-getGMT.R index f13cb8f..55f8296 100644 --- a/tests/testthat/test-getGMT.R +++ b/tests/testthat/test-getGMT.R @@ -1,5 +1,8 @@ test_that("getGMT reads a GMT file into a named list", { - url <- "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=GTEx_Tissues_V8_2023" + url <- paste0( + "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=", + "GTEx_Tissues_V8_2023" + ) gmt <- getGMT(url) expect_type(gmt, "list") diff --git a/tests/testthat/test-gmtListToSparseMat.R b/tests/testthat/test-gmtListToSparseMat.R index f39db67..b9eeaa3 100644 --- a/tests/testthat/test-gmtListToSparseMat.R +++ b/tests/testthat/test-gmtListToSparseMat.R @@ -1,4 +1,4 @@ -test_that("gmtListToSparseMat builds a sparse matrix with correct dims and values", { +test_that("gmtListToSparseMat builds sparse matrix with correct dims/values", { nested <- list( lib1 = list(A = letters[1:3], B = letters[2:4]), lib2 = list(C = letters[5:6]) diff --git a/tests/testthat/test-plots.R b/tests/testthat/test-plots.R index aea58fc..3dde644 100644 --- a/tests/testthat/test-plots.R +++ b/tests/testthat/test-plots.R @@ -1,55 +1,55 @@ test_that("CLAMPdotplot can use AUC or -log10(FDR) on the x-axis", { - summ <- data.frame( - pathway = c("Path A", "Path B", "Path C"), - LV = rep("LV2", 3), - AUC = c(0.99, 0.70, 0.80), - FDR = c(0.05, 0.001, 0.01), - stringsAsFactors = FALSE - ) + summ <- data.frame( + pathway = c("Path A", "Path B", "Path C"), + LV = rep("LV2", 3), + AUC = c(0.99, 0.70, 0.80), + FDR = c(0.05, 0.001, 0.01), + stringsAsFactors = FALSE + ) - p_auc <- CLAMPdotplot( - list(summary = summ), - lv = "LV2", - top = 2, - auc.cutoff = 0.6, - fdr.cutoff = 0.1, - x.axis = "AUC", - order.by = "AUC" - ) + p_auc <- CLAMPdotplot( + list(summary = summ), + lv = "LV2", + top = 2, + auc.cutoff = 0.6, + fdr.cutoff = 0.1, + x.axis = "AUC", + order.by = "AUC" + ) - expect_s3_class(p_auc, "ggplot") - expect_equal(p_auc$theme$plot.title$hjust, 0.5) - expect_equal(p_auc$data$x_value, p_auc$data$AUC) + expect_s3_class(p_auc, "ggplot") + expect_equal(p_auc$theme$plot.title$hjust, 0.5) + expect_equal(p_auc$data$x_value, p_auc$data$AUC) - p_fdr <- CLAMPdotplot( - list(summary = summ), - lv = "LV2", - top = 2, - auc.cutoff = 0.6, - fdr.cutoff = 0.1, - x.axis = "-log10(FDR)", - order.by = "-log10(FDR)" - ) + p_fdr <- CLAMPdotplot( + list(summary = summ), + lv = "LV2", + top = 2, + auc.cutoff = 0.6, + fdr.cutoff = 0.1, + x.axis = "-log10(FDR)", + order.by = "-log10(FDR)" + ) - expect_s3_class(p_fdr, "ggplot") - expect_equal(p_fdr$data$x_value, p_fdr$data$log10_fdr) - expect_equal(p_fdr$labels$x, "-log10(FDR)") - expect_setequal(p_fdr$data$pathway_label, c("Path B", "Path C")) + expect_s3_class(p_fdr, "ggplot") + expect_equal(p_fdr$data$x_value, p_fdr$data$log10_fdr) + expect_equal(p_fdr$labels$x, "-log10(FDR)") + expect_setequal(p_fdr$data$pathway_label, c("Path B", "Path C")) }) test_that("CLAMPplotTopZ returns a loading plot for selected LVs", { - set.seed(1) - Z <- matrix( - runif(20), - nrow = 10, - dimnames = list(paste0("Gene", seq_len(10)), c("LV1", "LV2")) - ) - U <- matrix(1, nrow = 2, ncol = 2) - clampRes <- list(Z = Z, U = U) + set.seed(1) + Z <- matrix( + runif(20), + nrow = 10, + dimnames = list(paste0("Gene", seq_len(10)), c("LV1", "LV2")) + ) + U <- matrix(1, nrow = 2, ncol = 2) + clampRes <- list(Z = Z, U = U) - p <- CLAMPplotTopZ(clampRes, top = 5, index = "LV2", label.top = 3) + p <- CLAMPplotTopZ(clampRes, top = 5, index = "LV2", label.top = 3) - expect_s3_class(p, "ggplot") - expect_equal(p$labels$title, "LV2") - expect_equal(p$theme$plot.title$hjust, 0.5) + expect_s3_class(p, "ggplot") + expect_equal(p$labels$title, "LV2") + expect_equal(p$theme$plot.title$hjust, 0.5) }) diff --git a/tests/testthat/test-preprocessCLAMP.R b/tests/testthat/test-preprocessCLAMP.R index 8bbcfc3..abd5b47 100644 --- a/tests/testthat/test-preprocessCLAMP.R +++ b/tests/testthat/test-preprocessCLAMP.R @@ -7,5 +7,8 @@ test_that("preprocessCLAMP filters and returns correct structure", { }) test_that("preprocessCLAMP errors on non-numeric input", { - expect_error(preprocessCLAMP(Y = data.frame(a = letters[1:5]), mean_cutoff = 0, var_cutoff = 0)) + expect_error(preprocessCLAMP( + Y = data.frame(a = letters[1:5]), + mean_cutoff = 0, var_cutoff = 0 + )) }) diff --git a/tests/testthat/test-select_clamp_k.R b/tests/testthat/test-select_clamp_k.R index be8e35a..6683d2a 100644 --- a/tests/testthat/test-select_clamp_k.R +++ b/tests/testthat/test-select_clamp_k.R @@ -1,107 +1,126 @@ test_that("select_clamp_k returns a list with clamp_k and scale", { - set.seed(1) - Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) - svdres <- compute_svd(Y, k = 25) - res <- select_clamp_k(svdres, n_samples = 30, svd_k = 25) - expect_true(all(c("clamp_k", "scale") %in% names(res))) - expect_true(is.numeric(res$clamp_k)) - expect_true(is.numeric(res$scale)) + set.seed(1) + Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) + svdres <- compute_svd(Y, k = 25) + res <- select_clamp_k(svdres, n_samples = 30, svd_k = 25) + expect_true(all(c("clamp_k", "scale") %in% names(res))) + expect_true(is.numeric(res$clamp_k)) + expect_true(is.numeric(res$scale)) }) test_that("select_clamp_k caps clamp_k at svd_k (default method)", { - set.seed(1) - Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) - svdres <- compute_svd(Y, k = 25) - res <- select_clamp_k(svdres, n_samples = 30, svd_k = 3) - expect_lte(res$clamp_k, 3) + set.seed(1) + Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) + svdres <- compute_svd(Y, k = 25) + res <- select_clamp_k(svdres, n_samples = 30, svd_k = 3) + expect_lte(res$clamp_k, 3) }) test_that("select_clamp_k caps clamp_k at svd_k (scaleSVs method)", { - set.seed(1) - d <- sort(runif(30, min = 1, max = 100), decreasing = TRUE) - svdres <- list(d = d) - res <- select_clamp_k(svdres, n_samples = 50, svd_k = 5, method = "scaleSVs") - expect_lte(res$clamp_k, 5) + set.seed(1) + d <- sort(runif(30, min = 1, max = 100), decreasing = TRUE) + svdres <- list(d = d) + res <- select_clamp_k(svdres, + n_samples = 50, svd_k = 5, method = "scaleSVs" + ) + expect_lte(res$clamp_k, 5) }) -test_that("select_clamp_k method='scaleSVs' matches the previous inline behavior", { - # regression check: scaleSVs method should reproduce the former inline logic - set.seed(1) - d <- sort(runif(30, min = 1, max = 100), decreasing = TRUE) - svdres <- list(d = d) - svd_k <- 30 - n_samples <- 50 +test_that("select_clamp_k scaleSVs matches inline behavior", { + # regression check: scaleSVs method should reproduce the former inline logic + set.seed(1) + d <- sort(runif(30, min = 1, max = 100), decreasing = TRUE) + svdres <- list(d = d) + svd_k <- 30 + n_samples <- 50 - scale.res <- getScaleFromSVs(svdres$d, n_samples) - expected_k <- min(floor(scale.res$k * 1.5), svd_k) - expected_scale <- scale.res$scale + scale.res <- getScaleFromSVs(svdres$d, n_samples) + expected_k <- min(floor(scale.res$k * 1.5), svd_k) + expected_scale <- scale.res$scale - res <- select_clamp_k(svdres, n_samples = n_samples, svd_k = svd_k, - method = "scaleSVs") - expect_equal(res$clamp_k, expected_k) - expect_equal(res$scale, expected_scale) + res <- select_clamp_k(svdres, + n_samples = n_samples, svd_k = svd_k, + method = "scaleSVs" + ) + expect_equal(res$clamp_k, expected_k) + expect_equal(res$scale, expected_scale) }) test_that("select_clamp_k default method is 'elbow'", { - set.seed(1) - Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) - svdres <- compute_svd(Y, k = 25) - res_default <- select_clamp_k(svdres, n_samples = ncol(Y), svd_k = 25) - res_elbow <- select_clamp_k(svdres, n_samples = ncol(Y), svd_k = 25, - method = "elbow") - expect_equal(res_default, res_elbow) + set.seed(1) + Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) + svdres <- compute_svd(Y, k = 25) + res_default <- select_clamp_k(svdres, n_samples = ncol(Y), svd_k = 25) + res_elbow <- select_clamp_k(svdres, + n_samples = ncol(Y), svd_k = 25, + method = "elbow" + ) + expect_equal(res_default, res_elbow) }) -test_that("select_clamp_k non-scaleSVs methods return scale = svdres$d[clamp_k]", { - set.seed(1) - Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) - svdres <- compute_svd(Y, k = 25) - res <- select_clamp_k(svdres, n_samples = ncol(Y), svd_k = 25, - method = "elbow") - expect_equal(res$scale, svdres$d[res$clamp_k]) +test_that(paste( + "select_clamp_k non-scaleSVs methods return", + "scale = svdres$d[clamp_k]" +), { + set.seed(1) + Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) + svdres <- compute_svd(Y, k = 25) + res <- select_clamp_k(svdres, + n_samples = ncol(Y), svd_k = 25, + method = "elbow" + ) + expect_equal(res$scale, svdres$d[res$clamp_k]) }) test_that("select_clamp_k permutation method works with raw data", { - set.seed(1) - Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) - svdres <- compute_svd(Y, k = 25) - res <- select_clamp_k(svdres, n_samples = ncol(Y), svd_k = 25, - method = "permutation", data = Y, B = 3) - expect_true(is.numeric(res$clamp_k)) - expect_lte(res$clamp_k, 25) - expect_equal(res$scale, svdres$d[res$clamp_k]) + set.seed(1) + Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) + svdres <- compute_svd(Y, k = 25) + res <- select_clamp_k(svdres, + n_samples = ncol(Y), svd_k = 25, + method = "permutation", data = Y, B = 3 + ) + expect_true(is.numeric(res$clamp_k)) + expect_lte(res$clamp_k, 25) + expect_equal(res$scale, svdres$d[res$clamp_k]) }) test_that("select_clamp_k permutation method errors without data", { - set.seed(1) - Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) - svdres <- compute_svd(Y, k = 25) - expect_error( - select_clamp_k(svdres, n_samples = ncol(Y), svd_k = 25, - method = "permutation"), - "data" - ) + set.seed(1) + Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) + svdres <- compute_svd(Y, k = 25) + expect_error( + select_clamp_k(svdres, + n_samples = ncol(Y), svd_k = 25, + method = "permutation" + ), + "data" + ) }) test_that("select_clamp_k gavish_donoho method works with raw data", { - skip_if_not_installed("PCAtools") - set.seed(1) - Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) - svdres <- compute_svd(Y, k = 25) - res <- select_clamp_k(svdres, n_samples = ncol(Y), svd_k = 25, - method = "gavish_donoho", data = Y) - expect_true(is.numeric(res$clamp_k)) - expect_lte(res$clamp_k, 25) - expect_equal(res$scale, svdres$d[res$clamp_k]) + skip_if_not_installed("PCAtools") + set.seed(1) + Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) + svdres <- compute_svd(Y, k = 25) + res <- select_clamp_k(svdres, + n_samples = ncol(Y), svd_k = 25, + method = "gavish_donoho", data = Y + ) + expect_true(is.numeric(res$clamp_k)) + expect_lte(res$clamp_k, 25) + expect_equal(res$scale, svdres$d[res$clamp_k]) }) test_that("select_clamp_k gavish_donoho method errors without data", { - set.seed(1) - Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) - svdres <- compute_svd(Y, k = 25) - expect_error( - select_clamp_k(svdres, n_samples = ncol(Y), svd_k = 25, - method = "gavish_donoho"), - "data" - ) + set.seed(1) + Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) + svdres <- compute_svd(Y, k = 25) + expect_error( + select_clamp_k(svdres, + n_samples = ncol(Y), svd_k = 25, + method = "gavish_donoho" + ), + "data" + ) }) diff --git a/tests/testthat/test-select_svd_k.R b/tests/testthat/test-select_svd_k.R index 2f7d783..0aa82ac 100644 --- a/tests/testthat/test-select_svd_k.R +++ b/tests/testthat/test-select_svd_k.R @@ -1,4 +1,4 @@ test_that("select_svd_k returns floor((min(nrow, ncol) - 1) / 4)", { - Y <- matrix(0, nrow = 100, ncol = 20) - expect_equal(select_svd_k(Y), 4) + Y <- matrix(0, nrow = 100, ncol = 20) + expect_equal(select_svd_k(Y), 4) }) diff --git a/vignettes/comparing_clampbase_clampfull.Rmd b/vignettes/comparing_clampbase_clampfull.Rmd index 18bfdbd..f72d748 100644 --- a/vignettes/comparing_clampbase_clampfull.Rmd +++ b/vignettes/comparing_clampbase_clampfull.Rmd @@ -15,12 +15,12 @@ vignette: > ```{r setup, include=FALSE} knitr::opts_chunk$set( - echo = TRUE, - message = FALSE, - warning = FALSE, - cache = FALSE, - dev = "png", - dev.args = list(type = "cairo") + echo = TRUE, + message = FALSE, + warning = FALSE, + cache = FALSE, + dev = "png", + dev.args = list(type = "cairo") ) library(CLAMP) ``` @@ -46,7 +46,7 @@ We illustrate how to: ```{r load-data} data("dataWholeBlood") data("majorCellTypes") -data('celltypeTargets') +data("celltypeTargets") # Scale each gene to mean 0 and variance 1 dataWholeBlood <- tscale(dataWholeBlood) @@ -54,17 +54,27 @@ dataWholeBlood <- tscale(dataWholeBlood) ## 2. Load Prior Knowledge Matrices +```{r load-priors-download, eval=FALSE} +# How to download pathway and cell marker libraries from Enrichr. +# Not run during vignette build to avoid network calls; pre-fetched +# .rds files are loaded in the next chunk instead. +gmtList <- list( + CellMarkers = getGMT( + "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=CellMarker_2024", + "CellMarker_2024" + ), + KEGG = getGMT( + "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=KEGG_2021_Human", + "KEGG_2021_Human" + ) +) +``` + ```{r load-priors} -# Download pathway and cell marker libraries from Enrichr +# Load pre-fetched gene set libraries bundled with the package gmtList <- list( - CellMarkers = getGMT( - "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=CellMarker_2024", - "CellMarker_2024" - ), - KEGG = getGMT( - "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=KEGG_2021_Human", - "KEGG_2021_Human" - ) + CellMarkers = readRDS(system.file("extdata", "CellMarker_2024.rds", package = "CLAMP")), + KEGG = readRDS(system.file("extdata", "KEGG_2021_Human.rds", package = "CLAMP")) ) # Combine into a single sparse matrix @@ -75,10 +85,10 @@ data("xCell") # Match pathways to the gene space of whole blood matchedPathsWB <- getMatchedPathwayMatList( - pathMatCell, - xCell, - new.genes = rownames(dataWholeBlood), - min.genes = 2 + pathMatCell, + xCell, + new.genes = rownames(dataWholeBlood), + min.genes = 2 ) ``` @@ -100,24 +110,24 @@ wb_clamp_k ```{r fit-clampbase} # Fit baseline CLAMP wb.clamp.base <- CLAMPbase( - dataWholeBlood, - svdres = dataWholeBlood.svd, - clamp_k = wb_clamp_k, - trace = FALSE, - adaptive.p = 0.05 + dataWholeBlood, + svdres = dataWholeBlood.svd, + clamp_k = wb_clamp_k, + trace = FALSE, + adaptive.p = 0.05 ) ``` ```{r fit-clampfull} # Fit variance-prior extended CLAMP model wb.clamp.full <- CLAMPfull( - dataWholeBlood, - priorMat = matchedPathsWB, - svdres = dataWholeBlood.svd, - clamp.base.result = wb.clamp.base, - clamp_k = wb_clamp_k, - trace = TRUE, - use_cpp = TRUE + dataWholeBlood, + priorMat = matchedPathsWB, + svdres = dataWholeBlood.svd, + clamp.base.result = wb.clamp.base, + clamp_k = wb_clamp_k, + trace = TRUE, + use_cpp = TRUE ) ``` @@ -131,12 +141,12 @@ Most cell types show higher correlations under `CLAMPfull`, demonstrating that i ```{r compare-models, fig.width=6, fig.height=5} output <- compareBs( - wb.clamp.base, - wb.clamp.full, - celltypeTargets, - "CLAMPbase", - "CLAMPfull", - m = "s" + wb.clamp.base, + wb.clamp.full, + celltypeTargets, + "CLAMPbase", + "CLAMPfull", + m = "s" ) output$plot @@ -149,13 +159,13 @@ We verify that `CLAMPfull` produces identical results when using a file-backed m dataWholeBloodFBM <- bigstatsr::as_FBM(dataWholeBlood) wb.clamp.full.fbm <- CLAMPfull( - dataWholeBloodFBM, - priorMat = matchedPathsWB, - svdres = dataWholeBlood.svd, - clamp.base.result = wb.clamp.base, - clamp_k = wb_clamp_k, - trace = TRUE, - use_cpp = TRUE + dataWholeBloodFBM, + priorMat = matchedPathsWB, + svdres = dataWholeBlood.svd, + clamp.base.result = wb.clamp.base, + clamp_k = wb_clamp_k, + trace = TRUE, + use_cpp = TRUE ) ``` @@ -163,12 +173,12 @@ The FBM implementation produces identical results: ```{r compare-fbm, fig.width=6, fig.height=5} output <- compareBs( - wb.clamp.full, - wb.clamp.full.fbm, - celltypeTargets, - "CLAMPbase", - "CLAMPfull", - m = "s" + wb.clamp.full, + wb.clamp.full.fbm, + celltypeTargets, + "CLAMPbase", + "CLAMPfull", + m = "s" ) output$plot @@ -178,4 +188,4 @@ output$plot ```{r session-info} sessionInfo() -``` \ No newline at end of file +``` diff --git a/vignettes/get_started.Rmd b/vignettes/get_started.Rmd index dc39141..a70eeb6 100644 --- a/vignettes/get_started.Rmd +++ b/vignettes/get_started.Rmd @@ -152,8 +152,9 @@ grViz(' full -> summaryTbl full -> Umat }', - width = "100%", - height = "900px") + width = "100%", + height = "900px" +) ``` # Quick Start @@ -268,17 +269,27 @@ wb_baseRes <- CLAMPbase( Next, we build a prior matrix from curated gene sets and compute the Chat object for `CLAMPfull`. +```{r priors-download, eval=FALSE} +# How to download pathway and cell marker libraries from Enrichr. +# Not run during vignette build to avoid network calls; pre-fetched +# .rds files are loaded in the next chunk instead. +gmtList <- list( + CellMarkers = getGMT( + "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=CellMarker_2024", + "CellMarker_2024" + ), + KEGG = getGMT( + "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=KEGG_2021_Human", + "KEGG_2021_Human" + ) +) +``` + ```{r priors, message=FALSE} -# Download pathway and cell marker libraries from Enrichr +# Load pre-fetched gene set libraries bundled with the package gmtList <- list( - CellMarkers = getGMT( - "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=CellMarker_2024", - "CellMarker_2024" - ), - KEGG = getGMT( - "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=KEGG_2021_Human", - "KEGG_2021_Human" - ) + CellMarkers = readRDS(system.file("extdata", "CellMarker_2024.rds", package = "CLAMP")), + KEGG = readRDS(system.file("extdata", "KEGG_2021_Human.rds", package = "CLAMP")) ) # Combine into a single sparse matrix @@ -289,9 +300,9 @@ data("xCell") # Match pathways to the gene space of whole blood matchedPathsWB <- getMatchedPathwayMatList( - pathMatCell, xCell, - new.genes = rownames(dataWholeBlood), - min.genes = 2 + pathMatCell, xCell, + new.genes = rownames(dataWholeBlood), + min.genes = 2 ) ``` @@ -314,7 +325,7 @@ wb_fullRes <- CLAMPfull( svdres = wb_svd, clamp_k = wb_clamp_k, use_cpp = TRUE - ) +) ``` ## Display significant latent variables @@ -324,8 +335,6 @@ wb_fullRes <- CLAMPfull( wb_summary_df <- as.data.frame(wb_fullRes$summary) %>% dplyr::filter(FDR < 0.05 & AUC > 0.7) %>% dplyr::arrange(FDR) %>% - dplyr::rename(LV = "LV_index") %>% - dplyr::mutate(LV = paste0("LV", LV)) %>% dplyr::select(LV, pathway, FDR, AUC) datatable( @@ -426,12 +435,21 @@ alz_baseRes <- CLAMPbase( ## Prepare pathway priors -```{r fbm-priors, message=FALSE} +```{r fbm-priors-download, eval=FALSE} +# How to fetch the libraries; not run during vignette build. alz_gmtList <- list( GTEx_Tissues = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=GTEx_Tissues_V8_2023"), BP = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=GO_Biological_Process_2025"), MSigDB = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=MSigDB_Hallmark_2020") ) +``` + +```{r fbm-priors, message=FALSE} +alz_gmtList <- list( + GTEx_Tissues = readRDS(system.file("extdata", "GTEx_Tissues_V8_2023.rds", package = "CLAMP")), + BP = readRDS(system.file("extdata", "GO_Biological_Process_2025.rds", package = "CLAMP")), + MSigDB = readRDS(system.file("extdata", "MSigDB_Hallmark_2020.rds", package = "CLAMP")) +) alz_pathMat <- gmtListToSparseMat(alz_gmtList) alz_matched <- getMatchedPathwayMat(alz_pathMat, alz_genes) @@ -447,7 +465,7 @@ alz_fullRes <- CLAMPfull( svdres = alz_svd, clamp_k = alz_clamp_k, use_cpp = TRUE - ) +) ``` ## Display significant latent variables @@ -455,9 +473,7 @@ alz_fullRes <- CLAMPfull( ```{r fbm-summary} alz_summary_df <- as.data.frame(alz_fullRes$summary) %>% filter(FDR < 0.05 & AUC > 0.7) %>% - dplyr::arrange(FDR) %>% - dplyr::rename(LV = "LV_index") %>% - dplyr::mutate(LV = paste0("LV", LV)) %>% + dplyr::arrange(FDR) %>% dplyr::select(LV, pathway, FDR, AUC) datatable( @@ -485,13 +501,14 @@ diabetic (T2D) samples. ```{r islet-load, message=FALSE} islet_file <- GSE164416_DP_htseq_counts_txt_gz() -islet_df <- read.table(gzfile(islet_file), header = TRUE, stringsAsFactors = FALSE) +islet_df <- read.table(gzfile(islet_file), header = TRUE, stringsAsFactors = FALSE) -islet_df$symbol <- mapIds( org.Hs.eg.db, - keys = islet_df$ensembl, - column = "SYMBOL", - keytype = "ENSEMBL", - multiVals = "first" ) +islet_df$symbol <- mapIds(org.Hs.eg.db, + keys = islet_df$ensembl, + column = "SYMBOL", + keytype = "ENSEMBL", + multiVals = "first" +) islet_df <- islet_df[!is.na(islet_df$symbol), ] ``` @@ -521,9 +538,10 @@ prep_is <- preprocessCLAMP( iso_Yf <- prep_is$Y_filtered iso_rowS <- prep_is$rowStats -iso_Yz <- zscoreCLAMP(Y_filtered = iso_Yf, - rowStats = iso_rowS) - +iso_Yz <- zscoreCLAMP( + Y_filtered = iso_Yf, + rowStats = iso_rowS +) ``` ## Compute SVD and infer k @@ -550,12 +568,21 @@ islet_baseRes <- CLAMPbase( ## Prepare pathway priors -```{r islet-priors, message=FALSE} +```{r islet-priors-download, eval=FALSE} +# How to fetch the libraries; not run during vignette build. islet_gmtList <- list( GTEx_Tissues = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=GTEx_Tissues_V8_2023"), Diabetes_Perturbations = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=Diabetes_Perturbations_GEO_2022"), MSigDB_Hallmark = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=MSigDB_Hallmark_2020") ) +``` + +```{r islet-priors, message=FALSE} +islet_gmtList <- list( + GTEx_Tissues = readRDS(system.file("extdata", "GTEx_Tissues_V8_2023.rds", package = "CLAMP")), + Diabetes_Perturbations = readRDS(system.file("extdata", "Diabetes_Perturbations_GEO_2022.rds", package = "CLAMP")), + MSigDB_Hallmark = readRDS(system.file("extdata", "MSigDB_Hallmark_2020.rds", package = "CLAMP")) +) islet_pathMat <- gmtListToSparseMat(islet_gmtList) islet_matched <- getMatchedPathwayMat(islet_pathMat, rownames(iso_Yz)) @@ -572,7 +599,7 @@ islet_fullRes <- CLAMPfull( svdres = islet_svd, clamp_k = islet_clamp_k, use_cpp = TRUE - ) +) ``` ## Display significant latent variables @@ -581,8 +608,6 @@ islet_fullRes <- CLAMPfull( islet_summary_df <- as.data.frame(islet_fullRes$summary) %>% filter(FDR < 0.05 & AUC > 0.7) %>% dplyr::arrange(FDR) %>% - dplyr::rename(LV = "LV_index") %>% - dplyr::mutate(LV = paste0("LV", LV)) %>% dplyr::select(LV, pathway, FDR, AUC) datatable( @@ -742,10 +767,10 @@ scan which pathways drive each latent variable. ```{r plot-U, message=FALSE, fig.width=14, fig.height=10} CLAMPplotU( - wb_fullRes, - auc.cutoff = 0.6, - fdr.cutoff = 0.05, - top = 3 + wb_fullRes, + auc.cutoff = 0.6, + fdr.cutoff = 0.05, + top = 3 ) ``` @@ -760,10 +785,10 @@ are labelled directly. lv_with_paths <- wb_fullRes$withPrior[seq_len(min(4, length(wb_fullRes$withPrior)))] CLAMPplotTopZ( - wb_fullRes, - top = 50, - label.top = 10, - index = lv_with_paths + wb_fullRes, + top = 50, + label.top = 10, + index = lv_with_paths ) ``` @@ -773,10 +798,10 @@ Only one LV: lv_with_paths <- wb_fullRes$withPrior[1] CLAMPplotTopZ( - wb_fullRes, - top = 50, - label.top = 10, - index = lv_with_paths + wb_fullRes, + top = 50, + label.top = 10, + index = lv_with_paths ) ``` ## Single-LV pathway dot plot (`CLAMPdotplot`) @@ -790,13 +815,13 @@ Plot order by AUC: ```{r plot-dot, message=FALSE, fig.width=7, fig.height=4, out.width='100%'} CLAMPdotplot( - wb_fullRes, - lv = 'LV2', - top = 15, - auc.cutoff = 0.6, - fdr.cutoff = 0.1, - x.axis = "AUC", - order.by = "AUC" + wb_fullRes, + lv = "LV2", + top = 15, + auc.cutoff = 0.6, + fdr.cutoff = 0.1, + x.axis = "AUC", + order.by = "AUC" ) ``` @@ -804,13 +829,13 @@ Plot order by FDR: ```{r plot-dot-fdr, message=FALSE, fig.width=7, fig.height=4, out.width='100%'} CLAMPdotplot( - wb_fullRes, - lv = 'LV2', - top = 15, - auc.cutoff = 0.6, - fdr.cutoff = 0.1, - x.axis = "-log10(FDR)", - order.by = "-log10(FDR)" + wb_fullRes, + lv = "LV2", + top = 15, + auc.cutoff = 0.6, + fdr.cutoff = 0.1, + x.axis = "-log10(FDR)", + order.by = "-log10(FDR)" ) ``` @@ -822,10 +847,10 @@ encodes `-log10(FDR)`. ```{r plot-dotAll, message=FALSE, fig.width=10, fig.height=7.5, out.width='100%'} CLAMPdotplotAll( - wb_fullRes, - auc.cutoff = 0.65, - fdr.cutoff = 0.05, - top.per.lv = 5 + wb_fullRes, + auc.cutoff = 0.65, + fdr.cutoff = 0.05, + top.per.lv = 5 ) ``` From a9b9b496dcc8061abecb27ae961ab534053da1ac Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Tue, 5 May 2026 16:37:30 -0600 Subject: [PATCH 08/20] updating indentation --- R/plots.R | 2 +- R/solvers.R | 655 +++++++++++++++++++++++++++++++++++----------------- R/utils.R | 241 +++++++++++++------ 3 files changed, 610 insertions(+), 288 deletions(-) diff --git a/R/plots.R b/R/plots.R index 34fc658..2f62e37 100644 --- a/R/plots.R +++ b/R/plots.R @@ -45,7 +45,7 @@ #' method = "p", xlab = "SVD1", ylab = "SVD2" #' ) compareBs <- function(res1, res2, target, method = "p", xlab = "1", ylab = "2", - stat.method = "t", oneToOne = TRUE) { + stat.method = "t", oneToOne = TRUE) { extract_B <- function(res) { if (is.list(res) & !is.null(res$B)) { return(as.matrix(res$B)) diff --git a/R/solvers.R b/R/solvers.R index ddbac17..9b94802 100644 --- a/R/solvers.R +++ b/R/solvers.R @@ -69,7 +69,8 @@ mat_mult <- function(mat1, mat2, ncores = 1) { #' #' @param m A symmetric numeric matrix (e.g., from \code{crossprod()}). #' @param alpha Non-negative scalar specifying the ridge penalty. -#' A small positive value stabilizes the inversion by shrinking large singular values. +#' A small positive value stabilizes the inversion by shrinking large +#' singular values. #' #' @return A numeric matrix representing the ridge-regularized #' pseudoinverse of \code{m}. @@ -88,12 +89,14 @@ pinv.ridge <- function(m, alpha = 0) { #' Rotate SVD components to make dominant directions positive #' -#' Ensures consistency in SVD output by flipping signs so that each left singular vector -#' has a majority of positive entries. +#' Ensures consistency in SVD output by flipping signs so that each left +#' singular vector has a majority of positive entries. #' -#' @param svdres A list as returned by \code{svd()}, with components \code{u}, \code{d}, and \code{v}. -#' @return A modified \code{svd}‐result list where each column of \code{$u} has been sign‐flipped -#' so that its entries sum to a nonnegative value; \code{$v} is flipped correspondingly. +#' @param svdres A list as returned by \code{svd()}, with components +#' \code{u}, \code{d}, and \code{v}. +#' @return A modified \code{svd}-result list where each column of \code{$u} +#' has been sign-flipped so that its entries sum to a nonnegative value; +#' \code{$v} is flipped correspondingly. rotateSVD <- function(svdres) { upos <- svdres$u uneg <- svdres$u @@ -115,11 +118,13 @@ rotateSVD <- function(svdres) { #' Binarize matrix by top-k values per column #' -#' Keeps only the top \code{top} values in each column of a matrix, setting others to 0. +#' Keeps only the top \code{top} values in each column of a matrix, setting +#' others to 0. #' #' @param Z A numeric matrix. #' @param top Number of top entries to keep in each column. -#' @param keepVals If \code{TRUE}, retains original values above the cutoff; otherwise, sets them to 1. +#' @param keepVals If \code{TRUE}, retains original values above the cutoff; +#' otherwise, sets them to 1. #' @return A modified matrix with only top entries retained per column. binarizeTop <- function(Z, top, keepVals = TRUE) { for (i in seq_len(ncol(Z))) { @@ -135,32 +140,47 @@ binarizeTop <- function(Z, top, keepVals = TRUE) { #' Fit the loading matrix Z using sparse regression of prior information U #' -#' For each column of a target matrix \code{Z} using pathway or prior annotation \code{priorMat}. -#' It performs regularization selection using cross-validation and can apply either -#' Supports continuous or binary response models. Relaxed refitting is supported for final -#' coefficient estimation. +#' For each column of a target matrix \code{Z} using pathway or prior +#' annotation \code{priorMat}. It performs regularization selection using +#' cross-validation and can apply either Supports continuous or binary +#' response models. Relaxed refitting is supported for final coefficient +#' estimation. #' #' @param Z A numeric matrix with features (rows) and samples (columns). -#' @param Chat (Optional) Precomputed pseudo-inverse of \code{priorMat}; if \code{NULL}, -#' it is calculated using ridge regularization. -#' @param priorMat A numeric matrix with prior information (features x pathways). -#' @param penalty.factor Optional penalty weights for features in \code{priorMat}. -#' @param pathwaySelection Method to select candidate pathways: \code{"fast"} (default) or \code{"complete"}. -#' @param alpha Elastic net mixing parameter (0 = ridge, 1 = lasso). Default is 0.9. -#' @param maxPath Maximum number of pathways/features selected per column. Default is 10. +#' @param Chat (Optional) Precomputed pseudo-inverse of \code{priorMat}; +#' if \code{NULL}, it is calculated using ridge regularization. +#' @param priorMat A numeric matrix with prior information +#' (features x pathways). +#' @param penalty.factor Optional penalty weights for features in +#' \code{priorMat}. +#' @param pathwaySelection Method to select candidate pathways: \code{"fast"} +#' (default) or \code{"complete"}. +#' @param alpha Elastic net mixing parameter (0 = ridge, 1 = lasso). +#' Default is 0.9. +#' @param maxPath Maximum number of pathways/features selected per column. +#' Default is 10. #' @param nfolds Number of cross-validation folds. Default is 5. -#' @param useSE Whether to use the 1-standard-error rule for lambda selection. Default is \code{FALSE}. -#' @param top If set, sets to 0 all but the top entries of \code{Z} per column before fitting. -#' @param binary If \code{TRUE}, fits a binomial model (e.g., classification) to \code{Z}>0. -#' Can be used incombination with \code{top}. Default is \code{FALSE}. +#' @param useSE Whether to use the 1-standard-error rule for lambda selection. +#' Default is \code{FALSE}. +#' @param top If set, sets to 0 all but the top entries of \code{Z} per +#' column before fitting. +#' @param binary If \code{TRUE}, fits a binomial model (e.g., classification) +#' to \code{Z}>0. Can be used in combination with \code{top}. +#' Default is \code{FALSE}. #' @param nlambda Number of lambda values for glmnet. Default is 20. -#' @param scale Whether to standardize predictors in glmnet. Default is \code{TRUE}. -#' @param refit Whether to perform relaxed refitting using selected predictors. Default is \code{TRUE}. -#' @param Uprev (Optional) Previous U matrix to reuse. In this mode only the columns of \code{U} -#' that are all zero are estimated. Used internally in \code{CLAMP}. -#' @param ... Additional arguments passed to \code{glmnet()} or \code{cv.glmnet()}. -#' @param useAUC Logical; whether to compute pathway–LV associations using AUC (default TRUE) instead of OLS. -#' @param intercept Logical; whether to include an intercept term in glmnet models. Default is TRUE. +#' @param scale Whether to standardize predictors in glmnet. +#' Default is \code{TRUE}. +#' @param refit Whether to perform relaxed refitting using selected +#' predictors. Default is \code{TRUE}. +#' @param Uprev (Optional) Previous U matrix to reuse. In this mode only +#' the columns of \code{U} that are all zero are estimated. Used +#' internally in \code{CLAMP}. +#' @param ... Additional arguments passed to \code{glmnet()} or +#' \code{cv.glmnet()}. +#' @param useAUC Logical; whether to compute pathway-LV associations using +#' AUC (default TRUE) instead of OLS. +#' @param intercept Logical; whether to include an intercept term in glmnet +#' models. Default is TRUE. #' @return A list with one element: #' \describe{ #' \item{\code{U}}{A matrix of loadings (features x components). @@ -192,8 +212,8 @@ binarizeTop <- function(Z, top, keepVals = TRUE) { solveU <- function( Z, Chat = NULL, priorMat, penalty.factor, pathwaySelection = "fast", alpha = 0.9, maxPath = 10, nfolds = 5, useSE = FALSE, top = NULL, - binary = FALSE, nlambda = 20, scale = TRUE, refit = TRUE, Uprev = NULL, useAUC = TRUE, intercept = TRUE, ... -) { + binary = FALSE, nlambda = 20, scale = TRUE, refit = TRUE, + Uprev = NULL, useAUC = TRUE, intercept = TRUE, ...) { if (nrow(Z) != nrow(priorMat)) { cm <- commonRows(Z, priorMat) Z <- Z[cm, ] @@ -222,7 +242,10 @@ solveU <- function( # Zhat <- matrix(0, nrow = nrow(Z), ncol = ncol(Z)) if (is.null(Uprev)) { - U <- Matrix::Matrix(0, nrow = ncol(priorMat), ncol = ncol(Z), sparse = TRUE) + U <- Matrix::Matrix( + 0, + nrow = ncol(priorMat), ncol = ncol(Z), sparse = TRUE + ) # U=matrix(0,nrow=ncol(priorMat), ncol=ncol(Z)) } else { U <- Uprev @@ -251,9 +274,12 @@ solveU <- function( if (!binary) { # not doing a binary prediction gres <- cv.glmnet( - y = Z[, i], x = priorMat[, iip], alpha = alpha, lower.limits = 0, - foldid = ((seq_len(nrow(Z))) %% nfolds) + 1, keep = TRUE, nfolds = nfolds, - standardize = scale, dfmax = maxPath, nlambda = nlambda, intercept = intercept, ... + y = Z[, i], x = priorMat[, iip], + alpha = alpha, lower.limits = 0, + foldid = ((seq_len(nrow(Z))) %% nfolds) + 1, + keep = TRUE, nfolds = nfolds, + standardize = scale, dfmax = maxPath, + nlambda = nlambda, intercept = intercept, ... ) # plot(gres) @@ -261,9 +287,11 @@ solveU <- function( gres <- cv.glmnet( y = (Z[, i] > 0) + 1 - 1, x = priorMat[, iip], family = "binomial", alpha = alpha, lower.limits = 0, - foldid = ((seq_len(nrow(Z))) %% nfolds) + 1, keep = FALSE, - nfolds = nfolds, type.measure = "auc", dfmax = maxPath, nlambda = nlambda, - standardize = scale, nlambda = nlambda, intercept = intercept, ... + foldid = ((seq_len(nrow(Z))) %% nfolds) + 1, + keep = FALSE, + nfolds = nfolds, type.measure = "auc", + dfmax = maxPath, nlambda = nlambda, + standardize = scale, intercept = intercept, ... ) } } # end if all U[,i]==0 @@ -306,7 +334,8 @@ solveU <- function( coefs <- as.vector(coef(fit_relaxed))[-1] if (add_dummy) coefs <- coefs[-length(coefs)] U[selected_features, i] <- coefs - # Zhat[, i] <- predict(fit_relaxed, newx = X_sel, s = 0, type = "response")[,1] + # Zhat[, i] <- predict(fit_relaxed, newx = X_sel, + # s = 0, type = "response")[,1] } } else { s_best <- if (useSE) gres$lambda.1se else gres$lambda.min @@ -316,7 +345,8 @@ solveU <- function( } # end for i in Z } - # message(sprintf(", Number of annotated columns is %d", sum(Matrix::colSums(U) > 0))) + # message(sprintf(", Number of annotated columns is %d", + # sum(Matrix::colSums(U) > 0))) # rownames(U)=substr(colnames(priorMat),1,30) rownames(U) <- colnames(priorMat) colnames(U) <- colnames(Z) @@ -334,12 +364,15 @@ solveU <- function( #' Compute Chat matrix from prior annotation #' -#' Computes the transformation matrix \code{Chat} used to map from observed data to latent space, -#' based on a pseudo-inverse of the prior annotation matrix. Optionally standardizes the columns +#' Computes the transformation matrix \code{Chat} used to map from observed +#' data to latent space, based on a pseudo-inverse of the prior annotation +#' matrix. Optionally standardizes the columns #' of \code{priorMat} before computing. #' -#' @param priorMat A numeric or sparse matrix (features x pathways) containing prior annotations. -#' @param scale Logical; if \code{TRUE} (default), standardizes the columns of \code{priorMat} +#' @param priorMat A numeric or sparse matrix (features x pathways) +#' containing prior annotations. +#' @param scale Logical; if \code{TRUE} (default), standardizes the columns +#' of \code{priorMat} #' before computing \code{Chat}. #' #' @return A numeric matrix \code{Chat} of dimensions (pathways x features). @@ -382,9 +415,11 @@ getChat <- function(priorMat, scale = TRUE) { #' #' @param pathMat A sparse binary matrix of genes (rows) x pathways (columns). #' @param new.genes Character vector of gene names to match. -#' @param min.genes Minimum number of overlapping genes required to keep a pathway. +#' @param min.genes Minimum number of overlapping genes required to keep +#' a pathway. #' -#' @return A sparse matrix of dimensions \code{length(new.genes)} x filtered pathways. +#' @return A sparse matrix of dimensions \code{length(new.genes)} x +#' filtered pathways. #' @examples #' library(Matrix) #' # create a toy gene-by-pathway sparse matrix @@ -402,7 +437,10 @@ getChat <- function(priorMat, scale = TRUE) { #' @export getMatchedPathwayMat <- function(pathMat, new.genes, min.genes = 10) { cm <- intersect(rownames(pathMat), new.genes) - mymessage("There are ", length(cm), " genes in the intersection between data and prior") + mymessage( + "There are ", length(cm), + " genes in the intersection between data and prior" + ) matchPathMat <- Matrix::sparseMatrix( i = match(cm, new.genes), @@ -428,15 +466,20 @@ getMatchedPathwayMat <- function(pathMat, new.genes, min.genes = 10) { #' #' @param ... One or more sparse binary matrices (genes x pathways). #' @param new.genes Character vector of gene names to match. -#' @param min.genes Minimum number of overlapping genes required to keep a pathway. +#' @param min.genes Minimum number of overlapping genes required to keep +#' a pathway. #' -#' @return A sparse matrix with rows = \code{new.genes} and columns = filtered pathways from all inputs. +#' @return A sparse matrix with rows = \code{new.genes} and columns = +#' filtered pathways from all inputs. getMatchedPathwayMat2 <- function(..., new.genes, min.genes = 10) { pathMats <- list(...) filtered <- lapply(pathMats, function(pathMat) { cm <- intersect(rownames(pathMat), new.genes) - message("There are ", length(cm), " genes in the intersection between data and prior") + message( + "There are ", length(cm), + " genes in the intersection between data and prior" + ) matchPathMat <- Matrix::sparseMatrix( i = match(cm, new.genes), @@ -451,7 +494,9 @@ getMatchedPathwayMat2 <- function(..., new.genes, min.genes = 10) { ii <- which(genesInPath >= min.genes) - message(sprintf("Removing %d pathways", ncol(matchPathMat) - length(ii))) + message(sprintf( + "Removing %d pathways", ncol(matchPathMat) - length(ii) + )) matchPathMat[, ii, drop = FALSE] }) @@ -471,12 +516,17 @@ getMatchedPathwayMat2 <- function(..., new.genes, min.genes = 10) { #' #' @param pathMat A sparse binary matrix of genes (rows) x pathways (columns). #' @param new.genes Character vector of gene names to match. -#' @param min.genes Minimum number of overlapping genes required to keep a pathway. +#' @param min.genes Minimum number of overlapping genes required to keep +#' a pathway. #' -#' @return A sparse matrix of dimensions \code{length(new.genes)} x filtered pathways. +#' @return A sparse matrix of dimensions \code{length(new.genes)} x +#' filtered pathways. getMatchedPathwayMatOld <- function(pathMat, new.genes, min.genes = 10) { cm <- intersect(rownames(pathMat), new.genes) - mymessage("There are ", length(cm), " genes in the intersection between data and prior") + mymessage( + "There are ", length(cm), + " genes in the intersection between data and prior" + ) matchPathMat <- Matrix::sparseMatrix( i = match(cm, new.genes), @@ -496,17 +546,21 @@ getMatchedPathwayMatOld <- function(pathMat, new.genes, min.genes = 10) { #' Compute AUC using Wilcoxon rank-sum test #' -#' Computes the area under the ROC curve (AUC) by applying a Wilcoxon rank-sum test -#' between predicted values for positive and negative labels. This is equivalent to +#' Computes the area under the ROC curve (AUC) by applying a Wilcoxon +#' rank-sum test between predicted values for positive and negative labels. +#' This is equivalent to #' computing the Mann-Whitney U statistic. #' -#' @param labels A numeric or logical vector indicating class labels. Values > 0 are treated as positive. -#' @param values A numeric vector of prediction scores corresponding to \code{labels}. +#' @param labels A numeric or logical vector indicating class labels. +#' Values > 0 are treated as positive. +#' @param values A numeric vector of prediction scores corresponding to +#' \code{labels}. #' #' @return A list with: #' \describe{ #' \item{\code{auc}}{Estimated AUC, or 0.5 if one class is missing} -#' \item{\code{pval}}{Wilcoxon test p-value, or \code{NA} if one class is missing} +#' \item{\code{pval}}{Wilcoxon test p-value, or \code{NA} if one class +#' is missing} #' } AUC <- function(labels, values) { pos <- labels > 0 @@ -529,25 +583,37 @@ AUC <- function(labels, values) { #' Cross-validation AUC for CLAMP latent variables and pathways #' -#' Evaluates how well each latent variable in a CLAMP model captures held-out pathway annotations, -#' using cross-validation over the prior matrix. For each latent variable and associated pathway, -#' held-out genes are selected and the AUC is computed using their scores in \code{clampRes$Z}. +#' Evaluates how well each latent variable in a CLAMP model captures +#' held-out pathway annotations, using cross-validation over the prior +#' matrix. For each latent variable and associated pathway, held-out genes +#' are selected and the AUC is computed using their scores in +#' \code{clampRes$Z}. #' -#' @param clampRes A list containing \code{U} (loadings) and \code{Z} (scores) from a CLAMP model. -#' @param priorMat A binary matrix (genes x pathways) indicating original pathway annotations. -#' @param priorMatcv A version of \code{priorMat} used to mask held-out annotations for cross-validation. +#' @param clampRes A list containing \code{U} (loadings) and \code{Z} +#' (scores) from a CLAMP model. +#' @param priorMat A binary matrix (genes x pathways) indicating original +#' pathway annotations. +#' @param priorMatcv A version of \code{priorMat} used to mask held-out +#' annotations for cross-validation. #' #' @return A list with: #' \describe{ #' \item{\code{Uauc}}{Matrix of AUC values (pathways x LVs)} #' \item{\code{Upval}}{Matrix of \code{-log10(p)} values (pathways x LVs)} -#' \item{\code{summary}}{Data frame with pathway, LV index, AUC, p-value, and FDR} +#' \item{\code{summary}}{Data frame with pathway, LV index, AUC, p-value, +#' and FDR} #' } crossVal <- function(clampRes, priorMat, priorMatcv) { ii <- which(Matrix::colSums(clampRes$U) > 0) - Uauc <- Matrix::Matrix(0, nrow = nrow(clampRes$U), ncol = ncol(clampRes$U), sparse = TRUE) - Up <- Matrix::Matrix(0, nrow = nrow(clampRes$U), ncol = ncol(clampRes$U), sparse = TRUE) + Uauc <- Matrix::Matrix( + 0, + nrow = nrow(clampRes$U), ncol = ncol(clampRes$U), sparse = TRUE + ) + Up <- Matrix::Matrix( + 0, + nrow = nrow(clampRes$U), ncol = ncol(clampRes$U), sparse = TRUE + ) results <- list() @@ -555,8 +621,10 @@ crossVal <- function(clampRes, priorMat, priorMatcv) { iipath <- which(clampRes$U[, i] > 0) for (j in iipath) { - iiheldout <- which((rowSums(priorMat[, iipath, drop = FALSE]) == 0) | - (priorMat[, j] > 0 & priorMatcv[, j] == 0)) + iiheldout <- which( + (rowSums(priorMat[, iipath, drop = FALSE]) == 0) | + (priorMat[, j] > 0 & priorMatcv[, j] == 0) + ) aucres <- AUC(priorMat[iiheldout, j], clampRes$Z[iiheldout, i]) @@ -587,35 +655,48 @@ crossVal <- function(clampRes, priorMat, priorMatcv) { #' CLAMP base matrix factorization #' #' Runs the core matrix factorization procedure of CLAMP, -#' decomposing the gene expression matrix \code{Y} into latent variables \code{Z} and loadings \code{B}. -#' It supports sparse, dense, and Filebacked Big Matrices (FBM) as input and includes options for +#' decomposing the gene expression matrix \code{Y} into latent variables +#' \code{Z} and loadings \code{B}. It supports sparse, dense, and Filebacked +#' Big Matrices (FBM) as input and includes options for #' adaptive sparsity, positive constraints, and regularization. #' -#' @param Y Input gene expression matrix (genes x samples). Can be dense, sparse (\code{dgCMatrix}), or FBM. +#' @param Y Input gene expression matrix (genes x samples). Can be dense, +#' sparse (\code{dgCMatrix}), or FBM. #' @param clamp_k Number of latent variables for CLAMP (final model rank). #' If \code{NULL}, it is chosen from the SVD via \code{getScaleFromSVs}. #' @param svd_k Number of singular values/components to compute in the SVD. #' If \code{NULL}, defaults to \code{max(2, min(n_genes, n_samples) - 1)}. -#' @param svdres Optional precomputed SVD result. If not supplied, it is computed internally. -#' @param L1 L1 regularization strength for Z. Defaults to scaled singular value. -#' @param L2 L2 regularization strength for B. Defaults to scaled singular value. -#' @param Zpos Logical; if \code{TRUE}, negative entries in Z are zeroed. Default is \code{TRUE}. +#' @param svdres Optional precomputed SVD result. If not supplied, it is +#' computed internally. +#' @param L1 L1 regularization strength for Z. Defaults to scaled singular +#' value. +#' @param L2 L2 regularization strength for B. Defaults to scaled singular +#' value. +#' @param Zpos Logical; if \code{TRUE}, negative entries in Z are zeroed. +#' Default is \code{TRUE}. #' @param max.iter Maximum number of optimization iterations. Default is 200. #' @param tol Convergence tolerance for B update. Default is 5e-4. -#' @param trace Logical; if \code{TRUE}, prints progress. Default is \code{FALSE}. +#' @param trace Logical; if \code{TRUE}, prints progress. Default is +#' \code{FALSE}. #' @param rseed Optional integer for reproducible random initialization of B. -#' @param B Optional initial matrix for B. If not provided, initialized from SVD. +#' @param B Optional initial matrix for B. If not provided, initialized +#' from SVD. #' @param scale Scaling factor for L1 and L2 when not provided. Default is 1. #' @param pos.adj Positive constraint adjustment divisor for L1. Default is 3. -#' @param adaptive.p Controls adaptive sparsity in \code{Z}. After each ALS update, +#' @param adaptive.p Controls adaptive sparsity in \code{Z}. After each ALS +#' update, #' negative entries in \code{Z} are assumed to reflect noise. -#' The cutoff for thresholding is set according to the probability of positive values under -#' a reflected negative distribution—effectively zeroing out small positive entries likely to be noise. +#' The cutoff for thresholding is set according to the probability of +#' positive values under a reflected negative distribution-effectively +#' zeroing out small positive entries likely to be noise. #' Smaller values lead to more sparsity. Default is 0.05. -#' @param adaptive.iter Number of iterations before adaptive sparsity is applied. Default is 20. -#' @param cutoff Scalar threshold to zero Z values when \code{Zpos = TRUE} and adaptive thresholding +#' @param adaptive.iter Number of iterations before adaptive sparsity is +#' applied. Default is 20. +#' @param cutoff Scalar threshold to zero Z values when \code{Zpos = TRUE} +#' and adaptive thresholding #' is not used. Default is 0. -#' @param ncores Number of cores to use for parallel computation (only used if Y is an FBM). Default is 1. +#' @param ncores Number of cores to use for parallel computation (only used +#' if Y is an FBM). Default is 1. #' @param clamp_k_method Method for selecting `clamp_k` when not provided. #' One of `"elbow"` (default), `"permutation"`, `"gavish_donoho"`, or #' `"scaleSVs"`. Passed to [select_clamp_k()]. @@ -629,9 +710,10 @@ crossVal <- function(clampRes, priorMat, priorMatcv) { #' } #' #' @details -#' This function is the low-level implementation of CLAMP. It alternates between solving for \code{Z} -#' given \code{B} and solving for \code{B} given \code{Z}, with optional sparsity and non-negativity -#' constraints on \code{Z}. Convergence is assessed via relative change in \code{B}. +#' This function is the low-level implementation of CLAMP. It alternates +#' between solving for \code{Z} given \code{B} and solving for \code{B} +#' given \code{Z}, with optional sparsity and non-negativity constraints on +#' \code{Z}. Convergence is assessed via relative change in \code{B}. #' #' @examples #' # small toy dataset: 5 genes x 4 samples @@ -646,7 +728,8 @@ crossVal <- function(clampRes, priorMat, priorMatcv) { CLAMPbase <- function( Y, clamp_k = NULL, svd_k = NULL, svdres = NULL, L1 = NULL, L2 = NULL, Zpos = TRUE, max.iter = 200, tol = 5e-4, trace = FALSE, - rseed = NULL, B = NULL, scale = 1, pos.adj = 3, adaptive.p = 0.05, adaptive.iter = 20, + rseed = NULL, B = NULL, scale = 1, pos.adj = 3, + adaptive.p = 0.05, adaptive.iter = 20, cutoff = 0, ncores = 1, clamp_k_method = "elbow" ) { if (ncores > 1) { @@ -715,11 +798,15 @@ CLAMPbase <- function( if (is.null(B)) { # initialize B with svd - B <- t(svdres$v[, seq_len(clamp_k)] %*% diag(sqrt(svdres$d[seq_len(clamp_k)]))) + B <- t( + svdres$v[, seq_len(clamp_k)] %*% + diag(sqrt(svdres$d[seq_len(clamp_k)])) + ) # alternative initializations # seem to be not as good - # B <- t(svdres$v[seq_len(ncol(Y)), seq_len(k)] %*% diag(svdres$d[seq_len(k)])) + # B <- t(svdres$v[seq_len(ncol(Y)), seq_len(k)] %*% + # diag(svdres$d[seq_len(k)])) # B <- t(svdres$v[seq_len(ncol(Y)), seq_len(k)]) } else { message("B given") @@ -740,7 +827,8 @@ CLAMPbase <- function( for (i in seq_len(max.iter)) { # main loop - Zraw <- Z <- mat_mult(Y, t(B), ncores = ncores) %*% solve(tcrossprod(B) + L1 * diag(clamp_k)) + Zraw <- Z <- mat_mult(Y, t(B), ncores = ncores) %*% + solve(tcrossprod(B) + L1 * diag(clamp_k)) if (i >= adaptive.iter && adaptive.p > 0) { cutoffs <- apply(Zraw, 2, getT) @@ -759,7 +847,8 @@ CLAMPbase <- function( ZY <- Matrix::t(ZYt) B <- solve(Matrix::t(Z) %*% Z + L2k) %*% ZY } else { - B <- solve(Matrix::t(Z) %*% Z + L2k) %*% mat_mult(Matrix::t(Z), Y, ncores = ncores) + B <- solve(Matrix::t(Z) %*% Z + L2k) %*% + mat_mult(Matrix::t(Z), Y, ncores = ncores) } # update error @@ -771,7 +860,10 @@ CLAMPbase <- function( BdiffTrace <- c(BdiffTrace, Bdiff) if (trace) { - message(sprintf("\rProgress %d / %d | Bdiff=%.6f, minCor=%.6f", i, max.iter, Bdiff, minCor)) + message(sprintf( + "\rProgress %d / %d | Bdiff=%.6f, minCor=%.6f", + i, max.iter, Bdiff, minCor + )) flush.console() } @@ -783,7 +875,10 @@ CLAMPbase <- function( } if (Bdiff < tol && i > adaptive.iter + 10) { - message(sprintf("Converged at iteration= %d | Bdiff=%.6f, tol=%.6f ", i, Bdiff, tol)) + message(sprintf( + "Converged at iteration= %d | Bdiff=%.6f, tol=%.6f ", + i, Bdiff, tol + )) break } if (BdiffCount > 5 && i > adaptive.iter + 10) { @@ -802,51 +897,72 @@ CLAMPbase <- function( options(default.nproc.blas = blas_nproc) } - return(list(B = as.matrix(B), Z = as.matrix(Z), Zraw = Zraw, L1 = L1, L2 = L2)) + return(list( + B = as.matrix(B), Z = as.matrix(Z), + Zraw = Zraw, L1 = L1, L2 = L2 + )) } #' Full CLAMP model with prior information and cross-validation #' #' Runs the full CLAMP model using a gene expression matrix -#' and prior pathway annotation matrix. This function performs latent variable decomposition -#' guided by prior knowledge and includes optional cross-validation to evaluate pathway associations. -#' -#' @param Y Gene expression matrix (genes x samples). Can be dense, sparse (dgCMatrix), or FBM. -#' @param priorMat Binary matrix (genes x pathways) representing prior annotations. +#' and prior pathway annotation matrix. This function performs latent +#' variable decomposition guided by prior knowledge and includes optional +#' cross-validation to evaluate pathway associations. +#' +#' @param Y Gene expression matrix (genes x samples). Can be dense, sparse +#' (dgCMatrix), or FBM. +#' @param priorMat Binary matrix (genes x pathways) representing prior +#' annotations. #' @param svdres Optional SVD result used for initialization. -#' @param clamp.base.result Optional result from \code{CLAMPbase()} to initialize B. +#' @param clamp.base.result Optional result from \code{CLAMPbase()} to +#' initialize B. #' @param clamp_k Number of latent variables for CLAMP (final model rank). #' If \code{NULL}, it is chosen from the SVD via \code{getScaleFromSVs}. #' @param svd_k Number of singular values/components to compute in the SVD. #' If \code{NULL}, defaults to \code{max(2, min(n_genes, n_samples) - 1)}. -#' @param L1 Regularization strength for Z. If \code{NULL}, initialized from SVD or \code{clamp.base.result}. -#' @param L2 Regularization strength for B. If \code{NULL}, initialized from SVD or \code{clamp.base.result}. +#' @param L1 Regularization strength for Z. If \code{NULL}, initialized from +#' SVD or \code{clamp.base.result}. +#' @param L2 Regularization strength for B. If \code{NULL}, initialized from +#' SVD or \code{clamp.base.result}. #' @param top If set, keeps only top-n values per column in Z during U updates. #' @param cvn Number of folds for cross-validation in U updates. Default is 5. #' @param max.iter Maximum number of iterations. Default is 350. #' @param trace Logical; if \code{TRUE}, prints iteration progress. #' @param Chat Optional precomputed matrix for solving U. -#' @param maxPath Maximum number of pathways/features selected per LV. Default is 10. -#' @param doCrossval Whether to perform pathway-level cross-validation. Default is \code{TRUE}. -#' @param penalty.factor Vector of feature-specific penalties for glmnet. Default: all ones. +#' @param maxPath Maximum number of pathways/features selected per LV. +#' Default is 10. +#' @param doCrossval Whether to perform pathway-level cross-validation. +#' Default is \code{TRUE}. +#' @param penalty.factor Vector of feature-specific penalties for glmnet. +#' Default: all ones. #' @param glm_alpha Elastic net mixing parameter for glmnet. Default is 0.9. #' @param minGenes Minimum number of genes per pathway to retain. Default is 10. #' @param tol Convergence tolerance on relative change in B. Default is 5e-4. -#' @param seed Seed for reproducibility of cross-validation masking. Default is 123456. -#' @param allGenes If \code{TRUE}, zero-fills \code{priorMat} for genes not present. Default is \code{FALSE}. +#' @param seed Seed for reproducibility of cross-validation masking. +#' Default is 123456. +#' @param allGenes If \code{TRUE}, zero-fills \code{priorMat} for genes not +#' present. Default is \code{FALSE}. #' @param rseed Optional seed for randomly reinitializing B and Z. #' @param max.U.updates Maximum number of U updates. Default is 5. -#' @param pathwaySelection Pathway selection mode: \code{"fast"} or \code{"complete"}. +#' @param pathwaySelection Pathway selection mode: \code{"fast"} or +#' \code{"complete"}. #' @param multiplier Scaling factor for adjusting L1 and L2. -#' @param adaptive.p Quantile threshold for adaptively zeroing small Z values. After each update, -#' the \code{adaptive.p}-quantile of negative entries in Z is used (flipped positive) to threshold +#' @param adaptive.p Quantile threshold for adaptively zeroing small Z +#' values. After each update, the \code{adaptive.p}-quantile of negative +#' entries in Z is used (flipped positive) to threshold #' small positive values, assuming they reflect noise. Default is 0.05. -#' @param useNNLS If \code{TRUE}, uses non-negative least squares in U estimation. Default is \code{TRUE}. -#' @param useRaw If \code{TRUE}, uses unthresholded Z for solving U. Default is \code{TRUE}. -#' @param refitAll If \code{TRUE}, refits all U columns every update. Default is \code{FALSE}. -#' @param useSE Logical; passed to the internal \code{solveU()} call. If \code{TRUE}, -#' enables standard-error–aware selection when fitting U (pathway coefficients). Default is \code{FALSE}. -#' @param ncores Number of cores to use for parallel computation (only used if Y is an FBM). Default is 1. +#' @param useNNLS If \code{TRUE}, uses non-negative least squares in U +#' estimation. Default is \code{TRUE}. +#' @param useRaw If \code{TRUE}, uses unthresholded Z for solving U. +#' Default is \code{TRUE}. +#' @param refitAll If \code{TRUE}, refits all U columns every update. +#' Default is \code{FALSE}. +#' @param useSE Logical; passed to the internal \code{solveU()} call. If +#' \code{TRUE}, enables standard-error-aware selection when fitting U +#' (pathway coefficients). Default is \code{FALSE}. +#' @param ncores Number of cores to use for parallel computation (only used +#' if Y is an FBM). Default is 1. #' @param clamp_k_method Method for selecting `clamp_k` when not provided. #' One of `"elbow"` (default), `"permutation"`, `"gavish_donoho"`, or #' `"scaleSVs"`. Passed to [select_clamp_k()]. @@ -857,10 +973,12 @@ CLAMPbase <- function( #' \item{\code{U}}{Pathway loadings matrix (pathways x LVs)} #' \item{\code{C}}{Masked prior matrix used for training} #' \item{\code{L1}, \code{L2}}{Regularization parameters} -#' \item{\code{heldOutGenes}}{List of held-out genes per pathway (if CV is enabled)} +#' \item{\code{heldOutGenes}}{List of held-out genes per pathway (if CV +#' is enabled)} #' \item{\code{Uauc}}{AUC matrix from CV evaluation (if enabled)} #' \item{\code{Up}}{-\code{log10(p)} values from CV evaluation (if enabled)} -#' \item{\code{summary}}{Data frame of AUC, p-values, and FDR per pathway x LV (if enabled)} +#' \item{\code{summary}}{Data frame of AUC, p-values, and FDR per pathway +#' x LV (if enabled)} #' \item{\code{priorMatCV}}{Masked prior matrix used during CV} #' \item{\code{priorMat}}{Final filtered prior matrix} #' \item{\code{withPrior}}{Indices of LVs with non-zero pathway loadings} @@ -868,9 +986,11 @@ CLAMPbase <- function( #' } #' #' @details -#' The model alternates between solving \code{Z}, \code{B}, and \code{U}. Adaptive sparsity is applied -#' to \code{Z} using a dynamic threshold based on the negative tail of its distribution. Cross-validation -#' is used to hold out gene annotations in \code{priorMat} and evaluate latent variable specificity. +#' The model alternates between solving \code{Z}, \code{B}, and \code{U}. +#' Adaptive sparsity is applied to \code{Z} using a dynamic threshold based +#' on the negative tail of its distribution. Cross-validation is used to +#' hold out gene annotations in \code{priorMat} and evaluate latent variable +#' specificity. #' #' @examples #' mat <- matrix(rnorm(100), 10, 10) @@ -885,13 +1005,16 @@ CLAMPbase <- function( #' @export CLAMPfullnVP <- function( Y, priorMat, svdres = NULL, clamp.base.result = NULL, clamp_k = NULL, - svd_k = NULL, L1 = NULL, L2 = NULL, top = NULL, cvn = 5, max.iter = 350, trace = FALSE, Chat = NULL, maxPath = 10, doCrossval = TRUE, + svd_k = NULL, L1 = NULL, L2 = NULL, top = NULL, + cvn = 5, max.iter = 350, trace = FALSE, Chat = NULL, + maxPath = 10, doCrossval = TRUE, penalty.factor = rep(1, ncol(priorMat)), glm_alpha = 0.9, - minGenes = 10, tol = 5e-4, seed = 123456, allGenes = FALSE, rseed = NULL, + minGenes = 10, tol = 5e-4, seed = 123456, + allGenes = FALSE, rseed = NULL, max.U.updates = 5, pathwaySelection = c("fast"), multiplier = 1, - adaptive.p = 0.05, useNNLS = TRUE, useRaw = TRUE, refitAll = FALSE, useSE = FALSE, ncores = 1, - clamp_k_method = "elbow" -) { + adaptive.p = 0.05, useNNLS = TRUE, useRaw = TRUE, + refitAll = FALSE, useSE = FALSE, ncores = 1, + clamp_k_method = "elbow") { if (ncores > 1) { # if we are parallelizing, then disable BLAS parallelization options(bigstatsr.check.parallel.blas = FALSE) @@ -939,7 +1062,9 @@ CLAMPfullnVP <- function( if (doCrossval) { priorMatCV <- as.matrix(priorMat) if (!is.null(seed)) { - warning("`seed` is deprecated and ignored. Use set.seed(seed) before calling this function.", + warning( + "`seed` is deprecated and ignored. Use set.seed(seed) ", + "before calling this function.", call. = FALSE ) } @@ -1002,7 +1127,10 @@ CLAMPfullnVP <- function( message("using provided CLAMPbase result") if (nrow(Y) != nrow(clamp.base.result$Z)) { if (is.null(rownames(Y)) | is.null(rownames(clamp.base.result$Z))) { - stop("Y and clamp.base.result$Z must have equal row numbers or row names") + stop( + "Y and clamp.base.result$Z must have equal row ", + "numbers or row names" + ) } clamp.base.result$Z <- clamp.base.result$Z[rownames(Y), ] } @@ -1031,7 +1159,8 @@ CLAMPfullnVP <- function( if (!is.null(rseed)) { message("Using random start") - # reproducibility is controlled by user calling set.seed before this function + # reproducibility is controlled by user calling set.seed before + # this function B <- t(apply(B, 1, sample)) Z <- apply(Z, 2, sample) } @@ -1055,7 +1184,8 @@ CLAMPfullnVP <- function( ZY <- Matrix::t(ZYt) B <- solve(Matrix::t(Z) %*% Z + L2k) %*% ZY } else { - B <- solve(Matrix::t(Z) %*% Z + L2k) %*% mat_mult(Matrix::t(Z), Y, ncores = ncores) + B <- solve(Matrix::t(Z) %*% Z + L2k) %*% + mat_mult(Matrix::t(Z), Y, ncores = ncores) } Zraw <- Z @@ -1078,7 +1208,9 @@ CLAMPfullnVP <- function( } if (useRaw) { - res <- solveU(Zraw, Chat, C, penalty.factor, pathwaySelection, + res <- solveU( + Zraw, Chat, C, + penalty.factor, pathwaySelection, glm_alpha, maxPath, binary = FALSE, nfolds = cvn, top = top, useNNLS = useNNLS, Uprev = Uprev, useSE = useSE @@ -1109,7 +1241,8 @@ CLAMPfullnVP <- function( Z <- (Z1 + Z2) %*% solve(tcrossprod(B) + L1k) } else { - Z <- mat_mult(Y, t(B), ncores = ncores) %*% solve(tcrossprod(B) + L1k) + Z <- mat_mult(Y, t(B), ncores = ncores) %*% + solve(tcrossprod(B) + L1k) } if (adaptive.p > 0) { @@ -1133,7 +1266,8 @@ CLAMPfullnVP <- function( B <- solve(Matrix::t(Z) %*% Z + L2k) %*% ZY } else { Z_mat <- if (inherits(Z, "matrix")) Z else as.matrix(Z) - B <- solve(Matrix::t(Z_mat) %*% Z + L2k) %*% mat_mult(Matrix::t(Z), Y, ncores = ncores) + B <- solve(Matrix::t(Z_mat) %*% Z + L2k) %*% + mat_mult(Matrix::t(Z), Y, ncores = ncores) } Bdiff <- sum((B - oldB)^2) / sum(B^2) @@ -1142,7 +1276,10 @@ CLAMPfullnVP <- function( BdiffTrace <- c(BdiffTrace, Bdiff) if (trace) { - message(sprintf("\rProgress %d / %d | Bdiff=%.6f", iter, max.iter, Bdiff)) + message(sprintf( + "\rProgress %d / %d | Bdiff=%.6f", + iter, max.iter, Bdiff + )) flush.console() } @@ -1155,8 +1292,8 @@ CLAMPfullnVP <- function( if (Bdiff < tol & iter > u.iter + num.U.updates * 2 + 5) { message(sprintf( - "\rConverged at %d / %d | Bdiff=%.6f, minCor=%.6f\n", iter, max.iter, - Bdiff, minCor + "\rConverged at %d / %d | Bdiff=%.6f, minCor=%.6f\n", + iter, max.iter, Bdiff, minCor )) break } @@ -1171,7 +1308,10 @@ CLAMPfullnVP <- function( if (!is.null(rownames(Y))) rownames(Z) <- rownames(Y) if (!is.null(colnames(Y))) colnames(B) <- colnames(Y) - out <- list(B = B, Z = Z, U = U, C = C, L1 = L1, L2 = L2, heldOutGenes = heldOutGenes) + out <- list( + B = B, Z = Z, U = U, C = C, + L1 = L1, L2 = L2, heldOutGenes = heldOutGenes + ) if (doCrossval) { if (adaptive.p != 0) { @@ -1221,8 +1361,10 @@ CLAMPfullnVP <- function( #' \code{CLAMPbase()}, containing at least \code{Z} and \code{L2}. #' @param newdata A gene expression matrix (genes x samples) to be projected. #' Can be a standard matrix, sparse matrix, or FBM/big.matrix. -#' @param scale Optional numeric multiplier for the L2 regularization terms. Default is 1. -#' @param ncores Number of cores to use for parallel computation (only used if newdata is an FBM). +#' @param scale Optional numeric multiplier for the L2 regularization terms. +#' Default is 1. +#' @param ncores Number of cores to use for parallel computation (only used +#' if newdata is an FBM). #' Default is 1. #' @param align Logical; if \code{TRUE} (default), row names shared by #' \code{CLAMPres$Z} and \code{newdata} are used to align both matrices to @@ -1230,7 +1372,8 @@ CLAMPfullnVP <- function( #' available, dimensions must already match. #' @param verbose Logical; if \code{TRUE} (default), report how many common #' rows are used for projection. -#' @return A matrix \code{B} of projected latent loadings (LVs x samples) for the new dataset. +#' @return A matrix \code{B} of projected latent loadings (LVs x samples) +#' for the new dataset. #' #' @details #' This function uses ridge-regularized least squares to compute @@ -1287,12 +1430,13 @@ projectCLAMP <- function(CLAMPres, newdata, scale = 1, ncores = 1, } else { if (nrow(Z_matrix) != nrow(newdata)) { stop( - "CLAMPres$Z and newdata have different numbers of rows and cannot ", - "be aligned because row names are missing." + "CLAMPres$Z and newdata have different numbers of rows ", + "and cannot be aligned because row names are missing." ) } - if (!is.null(z_genes) && !is.null(new_genes) && !identical(z_genes, new_genes)) { + if (!is.null(z_genes) && !is.null(new_genes) && + !identical(z_genes, new_genes)) { stop( "CLAMPres$Z and newdata row names are not in the same order. ", "Use align = TRUE to align common genes automatically." @@ -1300,7 +1444,10 @@ projectCLAMP <- function(CLAMPres, newdata, scale = 1, ncores = 1, } if (verbose && (is.null(z_genes) || is.null(new_genes))) { - message("Row names unavailable; assuming CLAMPres$Z and newdata are already aligned.") + message( + "Row names unavailable; assuming CLAMPres$Z and newdata ", + "are already aligned." + ) } } @@ -1389,7 +1536,8 @@ run_permutation <- function(data, d, B = 20) { #' Estimate number of principal components via elbow or permutation method #' -#' @param data Either a matrix (e.g. z-scored data) or an SVD result (list with $d). +#' @param data Either a matrix (e.g. z-scored data) or an SVD result +#' (list with $d). #' @param method One of "elbow" (fast) or "permutation" (slower). #' @param B Number of permutations (for method = "permutation"). #' @param seed Seed for reproducibility. @@ -1402,7 +1550,8 @@ run_permutation <- function(data, d, B = 20) { #' # slower permutation estimate (use fewer perms for example speed) #' num.pc(mat, method = "permutation", B = 5) #' @export -num.pc <- function(data, method = c("elbow", "permutation"), B = 20, seed = NULL) { +num.pc <- function(data, method = c("elbow", "permutation"), + B = 20, seed = NULL) { method <- match.arg(method) if (!is.null(seed)) { warning( @@ -1449,7 +1598,8 @@ num.pc <- function(data, method = c("elbow", "permutation"), B = 20, seed = NULL #' #' @param M A numeric matrix. #' @param k Integer; number of top elements to cap. Must be >= 1 and <= nrow(M). -#' @return A numeric matrix of the same dimensions as \code{M}, winsorized per column. +#' @return A numeric matrix of the same dimensions as \code{M}, winsorized +#' per column. #' @export #' @examples #' set.seed(123) @@ -1524,7 +1674,10 @@ cross_ZY <- function(Y, Z) { #' k <- 5 #' #' Y <- matrix(rnorm(50 * 20), nrow = 50, dimnames = list(genes, samples)) -#' Z <- matrix(rnorm(50 * k), nrow = 50, dimnames = list(genes, paste0("LV", 1:k))) +#' Z <- matrix(rnorm(50 * k), +#' nrow = 50, +#' dimnames = list(genes, paste0("LV", 1:k)) +#' ) #' #' lambda <- 0.1 #' L2k <- diag(lambda, k) @@ -1542,53 +1695,73 @@ ridge_B <- function(Y, Z, L2k) { #' Runs the streamlined full CLAMP model. #' -#' This version performs latent-variable decomposition of a gene expression matrix \code{Y} -#' guided by prior pathway annotations \code{priorMat}, with simplified and lighter regularization -#' compared to the original extended CLAMP variant. The algorithm alternates updates of \code{Z}, -#' \code{B}, and \code{U}, where \code{U} captures pathway–latent variable associations inferred -#' directly from the data without ridge-regularized projections (\code{Chat} is not used). -#' -#' Cross-validation can be used to evaluate pathway–LV specificity, and a variance-based prior -#' (\code{var.prior = TRUE}) introduces adaptive shrinkage of \code{Z} based on how strongly -#' each latent component aligns with prior pathways. The scaling factor \code{multiplier} (default 5) +#' This version performs latent-variable decomposition of a gene expression +#' matrix \code{Y} guided by prior pathway annotations \code{priorMat}, with +#' simplified and lighter regularization compared to the original extended +#' CLAMP variant. The algorithm alternates updates of \code{Z}, \code{B}, +#' and \code{U}, where \code{U} captures pathway-latent variable +#' associations inferred directly from the data without ridge-regularized +#' projections (\code{Chat} is not used). +#' +#' Cross-validation can be used to evaluate pathway-LV specificity, and a +#' variance-based prior (\code{var.prior = TRUE}) introduces adaptive +#' shrinkage of \code{Z} based on how strongly each latent component aligns +#' with prior pathways. The scaling factor \code{multiplier} (default 5) #' controls the strength of this adaptive shrinkage. #' -#' @param Y Gene expression matrix (genes × samples). Can be dense, sparse (dgCMatrix), or FBM. -#' @param priorMat Binary or weighted prior matrix (genes × pathways) linking genes to pathways. +#' @param Y Gene expression matrix (genes x samples). Can be dense, sparse +#' (dgCMatrix), or FBM. +#' @param priorMat Binary or weighted prior matrix (genes x pathways) +#' linking genes to pathways. #' @param Chat Ignored in this version (kept for interface compatibility). #' @param svdres Optional precomputed SVD result for initialization. -#' @param clamp.base.result Optional result from \code{CLAMPbase()} providing initial values. +#' @param clamp.base.result Optional result from \code{CLAMPbase()} +#' providing initial values. #' @param clamp_k Number of latent variables for CLAMP (final model rank). #' If \code{NULL}, it is chosen from the SVD via \code{getScaleFromSVs}. #' @param svd_k Number of singular values/components to compute in the SVD. #' If \code{NULL}, defaults to \code{max(2, min(n_genes, n_samples) - 1)}. -#' @param L1,L2 Regularization parameters for \code{Z} and \code{B}. Defaults use values from +#' @param L1,L2 Regularization parameters for \code{Z} and \code{B}. +#' Defaults use values from #' \code{clamp.base.result}. #' @param cvn Number of folds for pathway-level cross-validation. Default: 5. #' @param max.iter Maximum number of outer iterations. Default: 30. #' @param trace Logical; print iteration progress. Default: \code{TRUE}. -#' @param maxPath Maximum number of pathways per LV during U-fitting. Default: 10. -#' @param doCrossval Whether to mask prior entries for CV evaluation. Default: \code{TRUE}. -#' @param penalty.factor Optional vector of per-pathway penalties for glmnet. Default: 1. +#' @param maxPath Maximum number of pathways per LV during U-fitting. +#' Default: 10. +#' @param doCrossval Whether to mask prior entries for CV evaluation. +#' Default: \code{TRUE}. +#' @param penalty.factor Optional vector of per-pathway penalties for glmnet. +#' Default: 1. #' @param glm_alpha Elastic net mixing parameter for U estimation. Default: 0.9. #' @param minGenes Minimum number of genes per pathway. Default: 0. #' @param tol Convergence tolerance for B updates. Default: 5e-4. #' @param seed Random seed for CV masking. Default: 123456. -#' @param allGenes If \code{TRUE}, adds zero-filled rows for missing genes. Default: \code{FALSE}. -#' @param rseed Reproducibility, coordinate descent updates are done in random order. +#' @param allGenes If \code{TRUE}, adds zero-filled rows for missing genes. +#' Default: \code{FALSE}. +#' @param rseed Reproducibility, coordinate descent updates are done in +#' random order. #' @param max.U.updates Maximum number of U updates (capped by max.iter). -#' @param pathwaySelection Pathway selection mode for U fitting (\code{"fast"} or \code{"complete"}). +#' @param pathwaySelection Pathway selection mode for U fitting +#' (\code{"fast"} or \code{"complete"}). #' @param multiplier Variance-prior scaling factor. Default: 5. -#' @param adaptive.p Quantile of negative Z values used to define adaptive thresholding. Default: 0.05. -#' @param useNNLS Whether to use non-negative least squares for U estimation. Default: \code{TRUE}. -#' @param useRaw If \code{TRUE}, uses unthresholded Z in U updates. Default: \code{TRUE}. +#' @param adaptive.p Quantile of negative Z values used to define adaptive +#' thresholding. Default: 0.05. +#' @param useNNLS Whether to use non-negative least squares for U estimation. +#' Default: \code{TRUE}. +#' @param useRaw If \code{TRUE}, uses unthresholded Z in U updates. +#' Default: \code{TRUE}. #' @param refitEvery Frequency (in U updates) of full refits. Default: 3. -#' @param var.prior Logical; if \code{TRUE}, enables adaptive variance prior updates for Z. +#' @param var.prior Logical; if \code{TRUE}, enables adaptive variance prior +#' updates for Z. #' Default: \code{TRUE}. #' @param Uscale Logical; whether to scale U columns. Default: \code{FALSE}. -#' @param robust.vp Logical; winsorize prior-predicted Z2 values to reduce outlier effects. Default: \code{TRUE}. -#' @param useSE Logical; whether to use the 1-standard-error rule for internal glmnet fitting. Default is FALSE. -#' @param use_cpp Logical; if TRUE, use C++ implementation for Z updates. Default is FALSE. +#' @param robust.vp Logical; winsorize prior-predicted Z2 values to reduce +#' outlier effects. Default: \code{TRUE}. +#' @param useSE Logical; whether to use the 1-standard-error rule for +#' internal glmnet fitting. Default is FALSE. +#' @param use_cpp Logical; if TRUE, use C++ implementation for Z updates. +#' Default is FALSE. #' @param clamp_k_method Method for selecting `clamp_k` when not provided. #' One of `"elbow"` (default), `"permutation"`, `"gavish_donoho"`, or #' `"scaleSVs"`. Passed to [select_clamp_k()]. @@ -1606,10 +1779,13 @@ ridge_B <- function(Y, Z, L2k) { #' } #' #' @details -#' This implementation omits ridge-projected priors (\code{Chat}) and uses a lighter variance prior -#' with a lower default \code{multiplier = 5}, allowing more flexible latent representations. -#' Setting \code{var.prior = FALSE} reproduces standard CLAMP-like updates. Cross-validation, if -#' enabled, masks 20% of gene–pathway associations per column to estimate pathway–LV specificity +#' This implementation omits ridge-projected priors (\code{Chat}) and uses +#' a lighter variance prior with a lower default \code{multiplier = 5}, +#' allowing more flexible latent representations. Setting +#' \code{var.prior = FALSE} reproduces standard CLAMP-like updates. +#' Cross-validation, if +#' enabled, masks 20% of gene-pathway associations per column to estimate +#' pathway-LV specificity #' (reported via AUC and p-values). #' #' @examples @@ -1631,15 +1807,19 @@ ridge_B <- function(Y, Z, L2k) { #' ) #' @export CLAMPfull <- function( - Y, priorMat, Chat = NULL, svdres = NULL, clamp.base.result = NULL, clamp_k = NULL, - svd_k = NULL, L1 = NULL, L2 = NULL, cvn = 5, max.iter = 30, trace = TRUE, maxPath = 10, doCrossval = TRUE, + Y, priorMat, Chat = NULL, svdres = NULL, + clamp.base.result = NULL, clamp_k = NULL, + svd_k = NULL, L1 = NULL, L2 = NULL, cvn = 5, + max.iter = 30, trace = TRUE, maxPath = 10, doCrossval = TRUE, penalty.factor = rep(1, ncol(priorMat)), glm_alpha = 0.9, - minGenes = 0, tol = 5e-4, seed = 123456, allGenes = FALSE, rseed = NULL, - max.U.updates = Inf, pathwaySelection = c("fast", "complete"), multiplier = 5, + minGenes = 0, tol = 5e-4, seed = 123456, + allGenes = FALSE, rseed = NULL, + max.U.updates = Inf, + pathwaySelection = c("fast", "complete"), multiplier = 5, adaptive.p = 0.05, useNNLS = TRUE, useRaw = TRUE, refitEvery = 3, - useSE = FALSE, var.prior = TRUE, Uscale = FALSE, robust.vp = TRUE, use_cpp = FALSE, - clamp_k_method = "elbow" -) { + useSE = FALSE, var.prior = TRUE, Uscale = FALSE, + robust.vp = TRUE, use_cpp = FALSE, + clamp_k_method = "elbow") { if (is.infinite(max.U.updates)) max.U.updates <- max.iter getT <- function(x) -stats::quantile(x[x < 0], adaptive.p) @@ -1667,13 +1847,15 @@ CLAMPfull <- function( mvarForward <- mean(Zinput[iiiforward, zi]^2) # foreground predicted in Z2 mvarPredicted <- mean(Z2[iiiforward, zi]^2) - # this offset will use the implied foreground variance scale from actual Z + # this offset will use the implied foreground variance scale + # from actual Z # as opposed to the predcicted on in Z2 offset <- mvarForward / mvarPredicted # compute the predicted variance Z2var <- Z2[, zi]^2 * offset # compute a fold change - 1 and clip at 0 - # 1 will be added later ensuring that the background variance scale is always L1 + # 1 will be added later ensuring that the background variance + # scale is always L1 Zmultiplier[, zi] <- pmax((Z2var / mvarBack) - 1, 0) } Zmultiplier @@ -1763,7 +1945,10 @@ CLAMPfull <- function( message("using provided CLAMPbase result") if (nrow(Y) != nrow(clamp.base.result$Z)) { if (is.null(rownames(Y)) | is.null(rownames(clamp.base.result$Z))) { - stop("Y and clamp.base.result$Z must have equal row numbers or row names") + stop( + "Y and clamp.base.result$Z must have equal row ", + "numbers or row names" + ) } clamp.base.result$Z <- clamp.base.result$Z[rownames(Y), ] } @@ -1823,14 +2008,26 @@ CLAMPfull <- function( start_time <- Sys.time() for (iter in seq_len(max.iter)) { if (iter == 4) { - iter_time <- as.numeric(difftime(Sys.time(), start_time, units = "secs")) + iter_time <- as.numeric( + difftime(Sys.time(), start_time, units = "secs") + ) est_total <- iter_time * max.iter / 4 - message(sprintf("Estimated total runtime: ~%.1f min", est_total / 60)) + message(sprintf( + "Estimated total runtime: ~%.1f min", est_total / 60 + )) } if (iter >= u.iter) { # do U if (num.U.updates < max.U.updates) { # actually update U - if (any(Zraw < 0)) stop("Zraw has negative entries before U update") - Uprev <- if (num.U.updates %% refitEvery == 0 || iter == u.iter) NULL else U + if (any(Zraw < 0)) { + stop("Zraw has negative entries before U update") + } + Uprev <- if ( + num.U.updates %% refitEvery == 0 || iter == u.iter + ) { + NULL + } else { + U + } if (!is.null(Uprev)) { # print("Reusing previous") } else { @@ -1841,7 +2038,8 @@ CLAMPfull <- function( res <- solveU(Zinput, NULL, C, penalty.factor, pathwaySelection, glm_alpha, maxPath, binary = FALSE, nfolds = cvn, - useNNLS = useNNLS, Uprev = Uprev, useSE = useSE, scale = Uscale, useAUC = TRUE + useNNLS = useNNLS, Uprev = Uprev, useSE = useSE, + scale = Uscale, useAUC = TRUE ) U <- res$U @@ -1865,27 +2063,34 @@ CLAMPfull <- function( if (use_cpp) { if (!is_fbm) { - updateZcpp(Z, Y, B, B2, bk2_all, YBt, Q, Zmultiplier, L1, multiplier, 3, iter) + updateZcpp( + Z, Y, B, B2, bk2_all, YBt, Q, + Zmultiplier, L1, multiplier, 3, iter + ) } else { - updateZcpp(Z, Y$address, B, B2, bk2_all, YBt, Q, Zmultiplier, - L1, multiplier, 3, iter, + updateZcpp( + Z, Y$address, B, B2, bk2_all, YBt, Q, + Zmultiplier, L1, multiplier, 3, iter, Y_is_fbm = TRUE, n = nrow(Y), p = ncol(Y) ) } } else { for (inner.iter in seq_len(3)) { for (k_index in sample.int(clamp_k)) { - gene_var <- L1 * (1 / (multiplier * Zmultiplier[, k_index] + 1)) + gene_var <- L1 * + (1 / (multiplier * Zmultiplier[, k_index] + 1)) bk2 <- bk2_all[k_index] denom <- bk2 + gene_var - num <- YBt[, k_index] - Q[, k_index] + Z[, k_index] * bk2 + num <- YBt[, k_index] - Q[, k_index] + + Z[, k_index] * bk2 newZk <- num / denom delta <- newZk - Z[, k_index] Z[, k_index] <- newZk - Q <- Q + tcrossprod(delta, B2[k_index, ]) # rank-1 n×1 * 1×k + # rank-1 n*1 * 1*k + Q <- Q + tcrossprod(delta, B2[k_index, ]) # if (anyNA(Z)) stop() } # end for k @@ -1918,7 +2123,10 @@ CLAMPfull <- function( Bdiff <- sum((B - oldB)^2) / sum(B^2) BdiffTrace <- c(BdiffTrace, Bdiff) if (trace) { - message(sprintf("\rProgress %d / %d | Bdiff=%.6f", iter, max.iter, Bdiff)) + message(sprintf( + "\rProgress %d / %d | Bdiff=%.6f", + iter, max.iter, Bdiff + )) utils::flush.console() } if (iter > 52 && Bdiff > BdiffTrace[iter - 50]) { @@ -1928,7 +2136,10 @@ CLAMPfull <- function( BdiffCount <- BdiffCount - 1 } if (Bdiff < tol && iter > u.iter + num.U.updates * 2 + 5) { - message(sprintf("\rConverged at %d / %d | Bdiff=%.6f", iter, max.iter, Bdiff)) + message(sprintf( + "\rConverged at %d / %d | Bdiff=%.6f", + iter, max.iter, Bdiff + )) break } if (BdiffCount > 5) { @@ -1942,7 +2153,11 @@ CLAMPfull <- function( rownames(Z) <- rownames(Y) if (!is.null(colnames(Y))) colnames(B) <- colnames(Y) - out <- list(B = B, Z = Z, U = U, C = C, L1 = L1, L2 = L2, Z2 = Z2, heldOutGenes = heldOutGenes) + out <- list( + B = B, Z = Z, U = U, C = C, + L1 = L1, L2 = L2, Z2 = Z2, + heldOutGenes = heldOutGenes + ) if (doCrossval) { if (adaptive.p != 0) { @@ -1952,8 +2167,15 @@ CLAMPfull <- function( } message("crossValidation") priorMat_m <- as.matrix(priorMat) - priorMatCV_m <- if (exists("priorMatCV")) as.matrix(priorMatCV) else as.matrix(priorMat) - outAUC <- crossVal(out, priorMat, if (exists("priorMatCV")) priorMatCV else priorMat) + priorMatCV_m <- if (exists("priorMatCV")) { + as.matrix(priorMatCV) + } else { + as.matrix(priorMat) + } + outAUC <- crossVal( + out, priorMat, + if (exists("priorMatCV")) priorMatCV else priorMat + ) out$Z <- Z out$Uauc <- outAUC$Uauc out$Up <- outAUC$Upval @@ -1976,19 +2198,24 @@ CLAMPfull <- function( #' Subset and filter multiple pathway matrices to match target genes #' -#' Filters one or more gene-by-pathway annotation matrices to retain only pathways +#' Filters one or more gene-by-pathway annotation matrices to retain only +#' pathways #' with sufficient overlap with a given target gene set. Each input matrix is #' restricted to \code{new.genes}, and pathways with fewer than \code{min.genes} #' overlapping genes are removed. The resulting matrices are column-bound into a #' single sparse matrix aligned to \code{new.genes}. #' -#' @param ... One or more binary matrices (genes × pathways), either base \code{matrix} +#' @param ... One or more binary matrices (genes x pathways), either base +#' \code{matrix} #' or sparse \code{Matrix} objects. Row names must be gene identifiers. -#' @param new.genes Character vector of gene names to align all pathway matrices to. -#' @param min.genes Integer; minimum number of overlapping genes required for a pathway +#' @param new.genes Character vector of gene names to align all pathway +#' matrices to. +#' @param min.genes Integer; minimum number of overlapping genes required +#' for a pathway #' to be retained. Default is 10. #' -#' @return A sparse binary matrix with rows equal to \code{new.genes} and columns equal to +#' @return A sparse binary matrix with rows equal to \code{new.genes} and +#' columns equal to #' the union of filtered pathways from all input matrices. #' @export #' @examples @@ -2013,7 +2240,9 @@ CLAMPfull <- function( #' new.genes <- sample(genes, 50) #' #' # Match and filter pathways with at least 5 genes -#' matched <- getMatchedPathwayMatList(mat1, mat2, new.genes = new.genes, min.genes = 5) +#' matched <- getMatchedPathwayMatList(mat1, mat2, +#' new.genes = new.genes, min.genes = 5 +#' ) getMatchedPathwayMatList <- function(..., new.genes, min.genes = 10) { pathMats <- list(...) diff --git a/R/utils.R b/R/utils.R index 441e4f2..988d11b 100644 --- a/R/utils.R +++ b/R/utils.R @@ -76,7 +76,8 @@ tscale <- function(x) { #' Print a concatenated message #' -#' Wrapper around `message()` that pastes arguments together into a single string. +#' Wrapper around `message()` that pastes arguments together into a single +#' string. #' @param ... Character strings to concatenate and print. #' @return Invisibly returns NULL. Called for side effects (messages). mymessage <- function(...) { @@ -85,11 +86,12 @@ mymessage <- function(...) { #' Get maximum AUC per latent variable #' -#' Summarizes a cross-validation results data frame to extract the highest AUC value -#' associated with each latent variable (LV). +#' Summarizes a cross-validation results data frame to extract the highest +#' AUC value associated with each latent variable (LV). #' #' @param summary A data frame (e.g., from `crossVal()`) . -#' @param verbose Logical; if `TRUE`, prints counts of LVs exceeding AUC thresholds. Default is `FALSE`. +#' @param verbose Logical; if `TRUE`, prints counts of LVs exceeding AUC +#' thresholds. Default is `FALSE`. #' #' @return A data frame with columns LV index and max_AUC. getMaxAUC <- function(summary, verbose = FALSE) { @@ -99,16 +101,22 @@ getMaxAUC <- function(summary, verbose = FALSE) { ungroup() if (verbose) { - message("There are ", sum(max_auc_per_lv$max_AUC > 0.7), " LVs with AUC>0.70") - message("There are ", sum(max_auc_per_lv$max_AUC > 0.9), " LVs with AUC>0.90") + message( + "There are ", sum(max_auc_per_lv$max_AUC > 0.7), + " LVs with AUC>0.70" + ) + message( + "There are ", sum(max_auc_per_lv$max_AUC > 0.9), + " LVs with AUC>0.90" + ) } max_auc_per_lv } #' Count number of latent variables exceeding AUC thresholds #' -#' Given a summary data frame from cross-validation, reports the number of latent variables -#' with maximum AUC exceeding 0.7, 0.8, and 0.9. +#' Given a summary data frame from cross-validation, reports the number of +#' latent variables with maximum AUC exceeding 0.7, 0.8, and 0.9. #' #' @param summary A data frame with `LV index` and `AUC` columns. #' @@ -122,10 +130,12 @@ getAUCstats <- function(summary) { #' Greedy maximum correspondence from correlation matrix #' -#' Finds a one-to-one assignment (permutation) between rows and columns of a square correlation matrix -#' that maximizes the total correlation score, using a greedy algorithm. +#' Finds a one-to-one assignment (permutation) between rows and columns of a +#' square correlation matrix that maximizes the total correlation score, +#' using a greedy algorithm. #' -#' @param cor_mat A square numeric matrix of pairwise correlations (rows = items, cols = items). +#' @param cor_mat A square numeric matrix of pairwise correlations +#' (rows = items, cols = items). #' @return A vector of assignments (integer indices). max_correspondence_greedy <- function(cor_mat) { n <- nrow(cor_mat) @@ -147,23 +157,31 @@ max_correspondence_greedy <- function(cor_mat) { } } - list(permutation = assignment, sum = sum(cor_mat[cbind(seq_len(n), assignment)])) + list( + permutation = assignment, + sum = sum(cor_mat[cbind(seq_len(n), assignment)]) + ) } #' Download and read a GMT file from a URL #' -#' Downloads a Gene Matrix Transposed (GMT) file from a specified URL, reads it into R as a list, -#' and removes the temporary file afterward. +#' Downloads a Gene Matrix Transposed (GMT) file from a specified URL, reads +#' it into R as a list, and removes the temporary file afterward. #' #' @param url A character string specifying the URL to a GMT file. -#' @param name Optional name for the GMT file (defaults to the portion after the last '=' in the URL). +#' @param name Optional name for the GMT file (defaults to the portion after +#' the last '=' in the URL). #' @param cache_dir Optional directory in which to cache/download the GMT file. #' @param redownload Logical; if `TRUE`, forces re-download even if cached. #' -#' @return A named list where each element is a character vector of gene names for a given gene set. +#' @return A named list where each element is a character vector of gene +#' names for a given gene set. #' #' @examples -#' url <- "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=KEGG_2019_Human" +#' url <- paste0( +#' "https://maayanlab.cloud/Enrichr/geneSetLibrary", +#' "?mode=text&libraryName=KEGG_2019_Human" +#' ) #' gmt_list <- getGMT(url) #' # list available gene sets #' names(gmt_list) @@ -250,11 +268,12 @@ read_gmt <- function(filename) { #' Convert a list of GMT gene sets to a sparse matrix #' -#' Converts a list of named gene sets (e.g., from `getGMT()`) into a sparse binary matrix -#' where rows are genes, columns are gene sets, and entries are 1 if the gene is in the set. +#' Converts a list of named gene sets (e.g., from `getGMT()`) into a sparse +#' binary matrix where rows are genes, columns are gene sets, and entries +#' are 1 if the gene is in the set. #' -#' @param gmtList A nested list of gene sets. Outer names are gene set names; each entry is a character -#' vector of gene names. +#' @param gmtList A nested list of gene sets. Outer names are gene set names; +#' each entry is a character vector of gene names. #' #' @return A sparse binary matrix with genes as rows and gene sets as columns. #' @examples @@ -296,10 +315,10 @@ gmtListToSparseMat <- function(gmtList) { # Use sparseMatrix to create the matrix in one go - pathMat <- Matrix::sparseMatrix(i = row_indices, j = col_indices, x = values, dims = c( - length(allGenes), - length(allnames) - )) + pathMat <- Matrix::sparseMatrix( + i = row_indices, j = col_indices, x = values, + dims = c(length(allGenes), length(allnames)) + ) rownames(pathMat) <- allGenes colnames(pathMat) <- allnames pathMat @@ -319,25 +338,33 @@ commonRows <- function(data1, data2) { #' Clean a Filebacked Big Matrix (FBM) by log-transforming and handling NAs #' -#' This function inspects an FBM to determine if log-transformation is needed (based on value range) -#' and whether NA values are present. If the maximum value is >= 100, it applies a log2(x + 1) -#' transformation in-place. If any NA values are detected, they are replaced with 0. +#' This function inspects an FBM to determine if log-transformation is needed +#' (based on value range) and whether NA values are present. If the maximum +#' value is >= 100, it applies a log2(x + 1) transformation in-place. If any +#' NA values are detected, they are replaced with 0. #' #' @param fbm A `bigmemory::FBM` or `bigstatsr::FBM` object. -#' @param ncores Integer; number of cores to use for parallel operations (default 1). +#' @param ncores Integer; number of cores to use for parallel operations +#' (default 1). #' @return A list with: #' \describe{ -#' \item{max_value}{The maximum value encountered in the FBM (after log transformation if applied).} -#' \item{had_na}{Logical indicating whether any NA values were found and filled.} +#' \item{max_value}{The maximum value encountered in the FBM (after log +#' transformation if applied).} +#' \item{had_na}{Logical indicating whether any NA values were found +#' and filled.} #' } #' #' @details -#' Modifies the FBM in place. Uses `bigstatsr::big_apply()` to process in parallel-safe chunks. +#' Modifies the FBM in place. Uses `bigstatsr::big_apply()` to process in +#' parallel-safe chunks. #' @importFrom bigstatsr big_apply rows_along FBM #' @examples #' \donttest{ #' library(bigstatsr) -#' fbm <- FBM(3, 4, init = matrix(c(0, 1, 2, NA, 100, 200, 300, 400, 5, 6, 7, 8), nrow = 3)) +#' fbm <- FBM(3, 4, init = matrix( +#' c(0, 1, 2, NA, 100, 200, 300, 400, 5, 6, 7, 8), +#' nrow = 3 +#' )) #' cleanFBM(fbm, ncores = 1) #' } #' @@ -346,7 +373,10 @@ cleanFBM <- function(fbm, ncores = 1) { # Block‐wise scan for max and NA stats <- big_apply(fbm, a.FUN = function(X, ind) { vals <- X[, ind, drop = FALSE] - list(max = if (all(is.na(vals))) NA_real_ else max(vals, na.rm = TRUE), na = anyNA(vals)) + list( + max = if (all(is.na(vals))) NA_real_ else max(vals, na.rm = TRUE), + na = anyNA(vals) + ) }, a.combine = function(...) { Reduce(function(a, b) { list(max = max(a$max, b$max, na.rm = TRUE), na = a$na || b$na) @@ -383,11 +413,13 @@ cleanFBM <- function(fbm, ncores = 1) { #' Compute row-wise sum and sum of squares for a Filebacked Big Matrix #' -#' Efficiently computes row sums and row sum-of-squares for a `bigstatsr::FBM` using -#' column-wise chunking, suitable for large datasets that cannot be loaded fully into memory. +#' Efficiently computes row sums and row sum-of-squares for a +#' `bigstatsr::FBM` using column-wise chunking, suitable for large datasets +#' that cannot be loaded fully into memory. #' #' @param fbm A `bigstatsr::FBM` object. -#' @param ncores Integer; number of cores to use for parallel operations (default 1). +#' @param ncores Integer; number of cores to use for parallel operations +#' (default 1). #' @return A list with two numeric vectors: #' \describe{ #' \item{row_sums}{Sum of each row.} @@ -417,14 +449,18 @@ computeRowStatsFBM <- function(fbm, ncores = 1) { #' Filter rows of a Filebacked Big Matrix based on mean and variance #' -#' Filters an FBM based on row-level mean and variance thresholds, returning a new FBM +#' Filters an FBM based on row-level mean and variance thresholds, returning +#' a new FBM #' with only the selected rows. #' #' @param fbm A `bigstatsr::FBM` object. #' @param rowStats A list with numeric vectors `row_means` and `row_variances`. -#' @param mean_cutoff Optional minimum mean threshold; rows with means below this are removed. -#' @param var_cutoff Optional minimum variance threshold; rows with variances below this are removed. -#' @param backingfile A character string specifying the filename (without extension) for the new FBM. +#' @param mean_cutoff Optional minimum mean threshold; rows with means below +#' this are removed. +#' @param var_cutoff Optional minimum variance threshold; rows with variances +#' below this are removed. +#' @param backingfile A character string specifying the filename (without +#' extension) for the new FBM. #' @param keep_samples_idx Optional integer vector of column indices to retain. #' Default is `filtered_fbm`. #' @@ -434,18 +470,24 @@ computeRowStatsFBM <- function(fbm, ncores = 1) { #' \item{kept_rows}{Indices of rows retained in the filtering step.} #' } #' @details -#' This function creates a new FBM and copies over only the rows that pass the filtering criteria. +#' This function creates a new FBM and copies over only the rows that pass +#' the filtering criteria. #' The original FBM is unchanged. #' @examples #' \donttest{ #' library(bigstatsr) #' fbm <- FBM(5, 3, init = matrix(rnorm(15), nrow = 5)) #' rs <- list(row_means = rowMeans(fbm[]), row_variances = apply(fbm[], 1, var)) -#' out <- filterFBM(fbm, rs, mean_cutoff = -0.2, var_cutoff = 0.5, backingfile = tempfile()) +#' out <- filterFBM(fbm, rs, +#' mean_cutoff = -0.2, var_cutoff = 0.5, +#' backingfile = tempfile() +#' ) #' } #' @importFrom bigstatsr cols_along big_copy #' @export -filterFBM <- function(fbm, rowStats, keep_samples_idx = NULL, mean_cutoff = NULL, var_cutoff = NULL, backingfile = "filtered_fbm") { +filterFBM <- function(fbm, rowStats, keep_samples_idx = NULL, + mean_cutoff = NULL, var_cutoff = NULL, + backingfile = "filtered_fbm") { row_means <- rowStats$row_means row_variances <- rowStats$row_variances @@ -486,11 +528,13 @@ filterFBM <- function(fbm, rowStats, keep_samples_idx = NULL, mean_cutoff = NULL #' #' Centers each gene to mean 0 and scales to unit variance. #' -#' @param Y_filtered Numeric matrix (genes x samples) returned by preprocessCLAMP +#' @param Y_filtered Numeric matrix (genes x samples) returned by +#' preprocessCLAMP #' @param rowStats Data frame with numeric columns `mean` and `variance`, #' row-named to match `rownames(Y_filtered)` #' -#' @return Numeric matrix of the same dimensions as Y_filtered, with each row centered and scaled. +#' @return Numeric matrix of the same dimensions as Y_filtered, with each +#' row centered and scaled. #' @examples #' # simple 2 genes x 3 samples matrix #' Y <- matrix( @@ -517,8 +561,12 @@ zscoreCLAMP <- function(Y_filtered, rowStats) { if (!is.matrix(Y_filtered) || !is.numeric(Y_filtered)) { stop("`Y_filtered` must be a numeric matrix (genes x samples).") } - if (!is.data.frame(rowStats) || !all(c("mean", "variance") %in% colnames(rowStats))) { - stop("`rowStats` must be a data.frame with columns 'mean' and 'variance'.") + if (!is.data.frame(rowStats) || + !all(c("mean", "variance") %in% colnames(rowStats))) { + stop( + "`rowStats` must be a data.frame with columns 'mean' ", + "and 'variance'." + ) } # Align rowStats to Y_filtered if (!all(rownames(Y_filtered) %in% rownames(rowStats))) { @@ -545,20 +593,27 @@ zscoreCLAMP <- function(Y_filtered, rowStats) { #' Preprocess a bigstatsr FBM for CLAMP #' -#' Makes a writable copy of the input FBM, cleans it (log2 transform if needed, fill NAs), -#' filters rows by mean/variance, and returns the filtered FBM plus stats and indices. +#' Makes a writable copy of the input FBM, cleans it (log2 transform if +#' needed, fill NAs), filters rows by mean/variance, and returns the filtered +#' FBM plus stats and indices. #' #' @param fbm A bigstatsr::FBM (genes x samples), possibly read-only. -#' @param mean_cutoff Numeric or NULL. Minimum row mean to keep (NULL = no mean filter). -#' @param var_cutoff Numeric or NULL. Minimum row variance to keep (NULL = no var filter). -#' @param backingfile Character or NULL. Base name for the *copy* FBM and filtered FBM on disk. -#' If NULL, defaults to paste0(fbm$backingfile, '_preproc') and '_filtered'. -#' @param ncores Integer; number of cores to use for parallel operations (default 1). -#' @param block_size Number of rows to process at a time when copying data. Default is 1000. +#' @param mean_cutoff Numeric or NULL. Minimum row mean to keep +#' (NULL = no mean filter). +#' @param var_cutoff Numeric or NULL. Minimum row variance to keep +#' (NULL = no var filter). +#' @param backingfile Character or NULL. Base name for the *copy* FBM and +#' filtered FBM on disk. If NULL, defaults to +#' paste0(fbm$backingfile, '_preproc') and '_filtered'. +#' @param ncores Integer; number of cores to use for parallel operations +#' (default 1). +#' @param block_size Number of rows to process at a time when copying data. +#' Default is 1000. #' @return A list with: #' \item{fbm_filtered}{The filtered FBM (writable).} #' \item{rowStats}{List with row_means & row_variances for fbm_filtered.} -#' \item{kept_rows}{Integer vector of original row indices that were retained.} +#' \item{kept_rows}{Integer vector of original row indices that were +#' retained.} #' @examples #' library(bigstatsr) #' # create a toy matrix and back it with an FBM @@ -593,7 +648,10 @@ preprocessCLAMPFBM <- function( } # Make a writable copy - fbm_copy <- FBM(nrow = n_r, ncol = n_c, backingfile = base_bk, create_bk = TRUE) + fbm_copy <- FBM( + nrow = n_r, ncol = n_c, + backingfile = base_bk, create_bk = TRUE + ) # copy all data for (rs in seq(1, n_r, by = block_size)) { @@ -630,9 +688,16 @@ preprocessCLAMPFBM <- function( kept_rows <- filter_res$kept_rows # Subset stats to kept rows - stats_filt <- list(row_means = rs_all$row_means[kept_rows], row_variances = rs_all$row_variances[kept_rows]) + stats_filt <- list( + row_means = rs_all$row_means[kept_rows], + row_variances = rs_all$row_variances[kept_rows] + ) - list(fbm_filtered = fbm_filtered, rowStats = stats_filt, kept_rows = kept_rows) + list( + fbm_filtered = fbm_filtered, + rowStats = stats_filt, + kept_rows = kept_rows + ) } #' Z-score a filtered FBM in-place @@ -642,7 +707,8 @@ preprocessCLAMPFBM <- function( #' @param fbm_filtered A bigstatsr::FBM produced by preprocessCLAMPFBM(). #' @param rowStats A list with row_means and row_variances from that FBM. #' @param chunk_size Columns per block (default 1000). -#' @param ncores Integer; number of cores to use for parallel operations (default 1). +#' @param ncores Integer; number of cores to use for parallel operations +#' (default 1). #' @examples #' library(bigstatsr) #' fbm <- FBM( @@ -656,7 +722,8 @@ preprocessCLAMPFBM <- function( #' zscoreCLAMPFBM(fbm, stats, chunk_size = 2) #' @return A normalized FBM with z-scored rows. #' @export -zscoreCLAMPFBM <- function(fbm_filtered, rowStats, chunk_size = 1000, ncores = 1) { +zscoreCLAMPFBM <- function(fbm_filtered, rowStats, + chunk_size = 1000, ncores = 1) { message("Applying Z-score transformation") means <- rowStats$row_means sds <- sqrt(rowStats$row_variances) @@ -682,7 +749,10 @@ zscoreCLAMPFBM <- function(fbm_filtered, rowStats, chunk_size = 1000, ncores = 1 block <- sweep(block, 1, sds, "/") X[, ind] <- block integer(0) - }, a.combine = "c", ind = bigstatsr::cols_along(fbm_filtered), block.size = chunk_size, + }, + a.combine = "c", + ind = bigstatsr::cols_along(fbm_filtered), + block.size = chunk_size, ncores = ncores, means = means, sds = sds ) @@ -695,8 +765,10 @@ zscoreCLAMPFBM <- function(fbm_filtered, rowStats, chunk_size = 1000, ncores = 1 #' and per-gene statistics. #' #' @param Y Numeric matrix of gene expression (rows = genes, cols = samples) -#' @param mean_cutoff Numeric. Minimum row-mean required to keep a gene (default 0). -#' @param var_cutoff Numeric. Minimum row-variance required to keep a gene (default 0). +#' @param mean_cutoff Numeric. Minimum row-mean required to keep a gene +#' (default 0). +#' @param var_cutoff Numeric. Minimum row-variance required to keep a gene +#' (default 0). #' #' @return A list with components: #' - Y_filtered: filtered matrix (genes x samples) @@ -727,11 +799,16 @@ preprocessCLAMP <- function(Y, mean_cutoff = 0, var_cutoff = 0) { row_mean <- rowMeans(Y, na.rm = TRUE) row_var <- apply(Y, 1, stats::var, na.rm = TRUE) - rowStats <- data.frame(mean = row_mean, variance = row_var, stringsAsFactors = FALSE) + rowStats <- data.frame( + mean = row_mean, variance = row_var, + stringsAsFactors = FALSE + ) rownames(rowStats) <- rownames(Y) # Identify genes passing both thresholds - keep <- which(rowStats$mean >= mean_cutoff & rowStats$variance >= var_cutoff) + keep <- which( + rowStats$mean >= mean_cutoff & rowStats$variance >= var_cutoff + ) if (length(keep) == 0) { stop("No genes passed the mean/variance filters.") } @@ -740,13 +817,18 @@ preprocessCLAMP <- function(Y, mean_cutoff = 0, var_cutoff = 0) { Y_filtered <- Y[keep, , drop = FALSE] rowStats_filtered <- rowStats[keep, , drop = FALSE] - return(list(Y_filtered = Y_filtered, rowStats = rowStats_filtered, kept_rows = keep)) + return(list( + Y_filtered = Y_filtered, + rowStats = rowStats_filtered, + kept_rows = keep + )) } #' Compute counts-per-million (CPM) for CLAMP pipelines #' #' @param counts A numeric matrix or data.frame of raw counts (genes x samples). -#' @return A numeric matrix of CPM values (same dimensions), ready for CLAMP input. +#' @return A numeric matrix of CPM values (same dimensions), ready for CLAMP +#' input. #' @examples #' mat <- matrix(seq_len(12), nrow = 3) #' cpmCLAMP(mat) @@ -770,7 +852,8 @@ cpmCLAMP <- function(counts) { #' #' @param fbm_counts A bigstatsr::FBM of raw counts (genes x samples). #' @param block_size Integer; columns per block (default 1000). -#' @param ncores Integer; number of cores to use for parallel operations (default 1). +#' @param ncores Integer; number of cores to use for parallel operations +#' (default 1). #' @return Invisibly returns the modified FBM (now holding CPM values). #' @examples #' library(bigstatsr) @@ -808,7 +891,10 @@ cpmCLAMPFBM <- function(fbm_counts, block_size = 1000, ncores = 1) { lib_sizes <- bigstatsr::big_apply(fbm_counts, a.FUN = function(X, ind) { colSums(X[, ind, drop = FALSE]) - }, a.combine = "c", ind = bigstatsr::cols_along(fbm_counts), block.size = block_size, + }, + a.combine = "c", + ind = bigstatsr::cols_along(fbm_counts), + block.size = block_size, ncores = ncores ) lib_sizes[lib_sizes == 0] <- 1 @@ -820,7 +906,10 @@ cpmCLAMPFBM <- function(fbm_counts, block_size = 1000, ncores = 1) { blk <- sweep(blk, 2, libs[ind], "/") * 1e+06 X[, ind] <- blk integer(0) - }, a.combine = "c", ind = bigstatsr::cols_along(fbm_counts), block.size = block_size, + }, + a.combine = "c", + ind = bigstatsr::cols_along(fbm_counts), + block.size = block_size, ncores = ncores, libs = lib_sizes ) @@ -875,7 +964,8 @@ squashZscore <- function(zdata, maxScore = 2) { #' Estimate noise scale from singular values with linear tail extrapolation #' -#' This function estimates a characteristic scale from a vector of singular values +#' This function estimates a characteristic scale from a vector of singular +#' values #' by fitting a linear model to the tail and extrapolating to length \code{n}. #' The median of the extrapolated values is returned as the estimate. #' If no sufficiently linear tail is detected (based on \code{min_r2}) or @@ -1080,7 +1170,10 @@ select_clamp_k <- function(svdres, n_samples, svd_k, clamp_k <- num.pc(list(d = svdres$d), method = "elbow") } else if (method == "permutation") { if (is.null(data)) { - stop("`data` (raw row-normalized matrix) is required for method = 'permutation'.") + stop( + "`data` (raw row-normalized matrix) is required for ", + "method = 'permutation'." + ) } clamp_k <- num.pc(data, method = "permutation", B = B) } else if (method == "gavish_donoho") { From ae2e9b5dbf0d1c82c15a618fbcd77bdbcbbaaee3 Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Wed, 6 May 2026 10:53:41 -0600 Subject: [PATCH 09/20] line breaks in vignette --- vignettes/comparing_clampbase_clampfull.Rmd | 13 +- vignettes/get_started.Rmd | 173 ++++++++++++++------ 2 files changed, 131 insertions(+), 55 deletions(-) diff --git a/vignettes/comparing_clampbase_clampfull.Rmd b/vignettes/comparing_clampbase_clampfull.Rmd index f72d748..1740fe5 100644 --- a/vignettes/comparing_clampbase_clampfull.Rmd +++ b/vignettes/comparing_clampbase_clampfull.Rmd @@ -58,13 +58,14 @@ dataWholeBlood <- tscale(dataWholeBlood) # How to download pathway and cell marker libraries from Enrichr. # Not run during vignette build to avoid network calls; pre-fetched # .rds files are loaded in the next chunk instead. +enrichr_url <- "https://maayanlab.cloud/Enrichr/geneSetLibrary" gmtList <- list( CellMarkers = getGMT( - "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=CellMarker_2024", + paste0(enrichr_url, "?mode=text&libraryName=CellMarker_2024"), "CellMarker_2024" ), KEGG = getGMT( - "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=KEGG_2021_Human", + paste0(enrichr_url, "?mode=text&libraryName=KEGG_2021_Human"), "KEGG_2021_Human" ) ) @@ -73,8 +74,12 @@ gmtList <- list( ```{r load-priors} # Load pre-fetched gene set libraries bundled with the package gmtList <- list( - CellMarkers = readRDS(system.file("extdata", "CellMarker_2024.rds", package = "CLAMP")), - KEGG = readRDS(system.file("extdata", "KEGG_2021_Human.rds", package = "CLAMP")) + CellMarkers = readRDS( + system.file("extdata", "CellMarker_2024.rds", package = "CLAMP") + ), + KEGG = readRDS( + system.file("extdata", "KEGG_2021_Human.rds", package = "CLAMP") + ) ) # Combine into a single sparse matrix diff --git a/vignettes/get_started.Rmd b/vignettes/get_started.Rmd index a70eeb6..3beff13 100644 --- a/vignettes/get_started.Rmd +++ b/vignettes/get_started.Rmd @@ -85,8 +85,10 @@ grViz(' // ---- Inputs & Priors (gray) ---- DF [shape=folder, style=filled, fillcolor=Gray90, label="data.frame"] H5 [shape=folder, style=filled, fillcolor=Gray90, label="H5 file"] - GO [shape=cylinder, style=filled, fillcolor=Gray90, label="GO Biological Process"] - MSIGDB [shape=cylinder, style=filled, fillcolor=Gray90, label="MSigDB Hallmark"] + GO [shape=cylinder, style=filled, fillcolor=Gray90, + label="GO Biological Process"] + MSIGDB [shape=cylinder, style=filled, fillcolor=Gray90, + label="MSigDB Hallmark"] GTEx [shape=cylinder, style=filled, fillcolor=Gray90, label="GTEx Tissues"] // ---- Functions (white) ---- @@ -126,7 +128,8 @@ grViz(' Umat [label="U"] // ---- In-memory branch ---- - DF -> cpmDF -> cpmOut -> preDF -> filtered -> zDF -> zscored -> svdMem -> svdRes + DF -> cpmDF -> cpmOut -> preDF -> filtered -> + zDF -> zscored -> svdMem -> svdRes svdRes -> numPC -> clampK svdRes -> base clampK -> base @@ -134,7 +137,8 @@ grViz(' base -> baseResult -> full // ---- On-disk branch ---- - H5 -> cpmFBM -> cpmFBMOut -> preFBM -> filteredFBM -> zFBM -> zscoredFBM -> svdFBM -> svdResFBM + H5 -> cpmFBM -> cpmFBMOut -> preFBM -> filteredFBM -> + zFBM -> zscoredFBM -> svdFBM -> svdResFBM svdResFBM -> numPC svdResFBM -> base zscoredFBM -> base @@ -162,15 +166,15 @@ grViz(' We provide three examples: 1. **Data-frame example (whole blood):** - A small dataset loaded entirely into memory. Shows basic preprocessing, + A small dataset loaded entirely into memory. Shows basic preprocessing, z-scoring, and running CLAMP without on-disk storage. 2. **HDF5 example (Alzheimer’s brain):** - Demonstrates how to import expression from an HDF5 file, create a file-backed FBM object, + Demonstrates how to import expression from an HDF5 file, create a file-backed FBM object, and process larger datasets using the FBM interface. 3. **Table example (pancreatic islets):** - Illustrates reading a tab-delimited count file and comparing conditions via the B matrix. + Illustrates reading a tab-delimited count file and comparing conditions via the B matrix. Each example follows these steps: @@ -206,8 +210,8 @@ head(dataWholeBlood) # genes x samples ## Preprocess and z-score -We first CPM-normalize the data (when needed), filter for genes with mean expression ≥ 0.5 -and variance ≥ 0.1, and then apply z-score normalization. +We first CPM-normalize the data (when needed), filter for genes with mean +expression ≥ 0.5 and variance ≥ 0.1, and then apply z-score normalization. ```{r preprocess, message=TRUE} # CPM normalization @@ -234,7 +238,8 @@ wb_Y_z <- zscoreCLAMP( ## Compute SVD and infer k -We compute the SVD using `rsvd::rsvd()` and infer the optimal number of latent variables using `num.pc()`. +We compute the SVD using `rsvd::rsvd()` and infer the optimal number of latent +variables using `num.pc()`. ```{r wb-svd, message=FALSE} # Compute SVD (k = n_samples - 1) @@ -248,14 +253,21 @@ wb_clamp_k ## CLAMPbase initialization -We initialize latent variables using `CLAMPbase`, providing the pre-computed SVD and inferred `k`. +We initialize latent variables using `CLAMPbase`, providing the pre-computed SVD +and inferred `k`. -The argument `adaptive.p` defines the percentile used to determine the adaptive sparsity threshold applied to each latent variable's gene loadings. -During alternating updates, negative entries in `Z` are treated as noise, and CLAMP estimates a cutoff based on the `adaptive.p` quantile of these negative values. -All genes with loadings below this cutoff are set to zero. -This produces **data-driven sparsity**, automatically filtering weak or noisy signals while retaining genes with the strongest positive contributions. -Lower values of `adaptive.p` (e.g., 0.01) result in stronger sparsity, while higher values (e.g., 0.1) retain more genes. -The default `adaptive.p = 0.05` typically yields interpretable, well-separated latent variables in large transcriptomic datasets. +The argument `adaptive.p` defines the percentile used to determine the adaptive +sparsity threshold applied to each latent variable's gene loadings. +During alternating updates, negative entries in `Z` are treated as noise, and +CLAMP estimates a cutoff based on the `adaptive.p` quantile of these negative +values. All genes with loadings below this cutoff are set to zero. + +This produces **data-driven sparsity**, automatically filtering weak or noisy +signals while retaining genes with the strongest positive contributions. +Lower values of `adaptive.p` (e.g., 0.01) result in stronger sparsity, while +higher values (e.g., 0.1) retain more genes. +The default `adaptive.p = 0.05` typically yields interpretable, well-separated +latent variables in large transcriptomic datasets. ```{r CLAMPbase, message=FALSE} wb_baseRes <- CLAMPbase( @@ -267,19 +279,21 @@ wb_baseRes <- CLAMPbase( ## Prepare pathway priors -Next, we build a prior matrix from curated gene sets and compute the Chat object for `CLAMPfull`. +Next, we build a prior matrix from curated gene sets and compute the Chat +object for `CLAMPfull`. ```{r priors-download, eval=FALSE} # How to download pathway and cell marker libraries from Enrichr. # Not run during vignette build to avoid network calls; pre-fetched # .rds files are loaded in the next chunk instead. +enrichr_url <- "https://maayanlab.cloud/Enrichr/geneSetLibrary" gmtList <- list( CellMarkers = getGMT( - "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=CellMarker_2024", + paste0(enrichr_url, "?mode=text&libraryName=CellMarker_2024"), "CellMarker_2024" ), KEGG = getGMT( - "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=KEGG_2021_Human", + paste0(enrichr_url, "?mode=text&libraryName=KEGG_2021_Human"), "KEGG_2021_Human" ) ) @@ -288,8 +302,12 @@ gmtList <- list( ```{r priors, message=FALSE} # Load pre-fetched gene set libraries bundled with the package gmtList <- list( - CellMarkers = readRDS(system.file("extdata", "CellMarker_2024.rds", package = "CLAMP")), - KEGG = readRDS(system.file("extdata", "KEGG_2021_Human.rds", package = "CLAMP")) + CellMarkers = readRDS( + system.file("extdata", "CellMarker_2024.rds", package = "CLAMP") + ), + KEGG = readRDS( + system.file("extdata", "KEGG_2021_Human.rds", package = "CLAMP") + ) ) # Combine into a single sparse matrix @@ -307,15 +325,17 @@ matchedPathsWB <- getMatchedPathwayMatList( ``` **Note**: GMT files can also be loaded from local storage using `read_gmt()`. -This allows you to integrate custom or curated gene set libraries, such as *MSigDB* canonical pathways, directly into your analysis pipeline alongside remote resources. +This allows you to integrate custom or curated gene set libraries, such as +*MSigDB* canonical pathways, directly into your analysis pipeline alongside +remote resources. ## CLAMPfull -Finally, we refine the base model by integrating pathway priors using `CLAMPfull`, -which applies cross-validation to optimize latent variable regularization. -In this new version, `CLAMPfull` incorporates **variable priors** that adjust -the influence of each pathway adaptively, improving convergence and stability -across heterogeneous datasets. +Finally, we refine the base model by integrating pathway priors using +`CLAMPfull`, which applies cross-validation to optimize latent variable +regularization. In this new version, `CLAMPfull` incorporates +**variable priors** that adjust the influence of each pathway adaptively, +improving convergence and stability across heterogeneous datasets. ```{r CLAMPfull, message=FALSE} wb_fullRes <- CLAMPfull( @@ -365,8 +385,9 @@ file.remove(bk_paths[file.exists(bk_paths)]) ### Computing CPM on a File-Backed Matrix (FBM) -For file-backed matrices (FBMs), you can compute counts-per-million (CPM) in-place—without loading the entire dataset into -RAM—using the `cpmCLAMPFBM()` function from **CLAMP**: +For file-backed matrices (FBMs), you can compute counts-per-million (CPM) +in-place—without loading the entire dataset into RAM—using the +`cpmCLAMPFBM()` function from **CLAMP**: ## Load HDF5 expression @@ -385,7 +406,10 @@ rownames(expr_mat) <- genes ```{r fbm-construct, message=FALSE} dir.create(output_dir, recursive = TRUE, showWarnings = FALSE) -alzFBM <- FBM(nrow = nrow(expr_mat), ncol = ncol(expr_mat), backingfile = fbm_base) +alzFBM <- FBM( + nrow = nrow(expr_mat), ncol = ncol(expr_mat), + backingfile = fbm_base +) blk <- 1000 for (i in seq_len(ceiling(nrow(expr_mat) / blk))) { @@ -411,7 +435,8 @@ alz_genes <- genes[prep_alz$kept_rows] ## Compute SVD and infer k -For file-backed matrices, we use `bigstatsr::big_randomSVD()` to compute the SVD without loading the entire matrix into RAM. +For file-backed matrices, we use `bigstatsr::big_randomSVD()` to compute the +SVD without loading the entire matrix into RAM. ```{r fbm-svd, message=FALSE} # Compute SVD (k = n_samples - 1) @@ -437,18 +462,34 @@ alz_baseRes <- CLAMPbase( ```{r fbm-priors-download, eval=FALSE} # How to fetch the libraries; not run during vignette build. +enrichr_url <- "https://maayanlab.cloud/Enrichr/geneSetLibrary" alz_gmtList <- list( - GTEx_Tissues = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=GTEx_Tissues_V8_2023"), - BP = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=GO_Biological_Process_2025"), - MSigDB = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=MSigDB_Hallmark_2020") + GTEx_Tissues = getGMT( + paste0(enrichr_url, "?mode=text&libraryName=GTEx_Tissues_V8_2023") + ), + BP = getGMT( + paste0(enrichr_url, "?mode=text&libraryName=GO_Biological_Process_2025") + ), + MSigDB = getGMT( + paste0(enrichr_url, "?mode=text&libraryName=MSigDB_Hallmark_2020") + ) ) ``` ```{r fbm-priors, message=FALSE} alz_gmtList <- list( - GTEx_Tissues = readRDS(system.file("extdata", "GTEx_Tissues_V8_2023.rds", package = "CLAMP")), - BP = readRDS(system.file("extdata", "GO_Biological_Process_2025.rds", package = "CLAMP")), - MSigDB = readRDS(system.file("extdata", "MSigDB_Hallmark_2020.rds", package = "CLAMP")) + GTEx_Tissues = readRDS( + system.file("extdata", "GTEx_Tissues_V8_2023.rds", package = "CLAMP") + ), + BP = readRDS( + system.file( + "extdata", "GO_Biological_Process_2025.rds", + package = "CLAMP" + ) + ), + MSigDB = readRDS( + system.file("extdata", "MSigDB_Hallmark_2020.rds", package = "CLAMP") + ) ) alz_pathMat <- gmtListToSparseMat(alz_gmtList) @@ -501,7 +542,10 @@ diabetic (T2D) samples. ```{r islet-load, message=FALSE} islet_file <- GSE164416_DP_htseq_counts_txt_gz() -islet_df <- read.table(gzfile(islet_file), header = TRUE, stringsAsFactors = FALSE) +islet_df <- read.table( + gzfile(islet_file), + header = TRUE, stringsAsFactors = FALSE +) islet_df$symbol <- mapIds(org.Hs.eg.db, keys = islet_df$ensembl, @@ -570,18 +614,37 @@ islet_baseRes <- CLAMPbase( ```{r islet-priors-download, eval=FALSE} # How to fetch the libraries; not run during vignette build. +enrichr_url <- "https://maayanlab.cloud/Enrichr/geneSetLibrary" islet_gmtList <- list( - GTEx_Tissues = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=GTEx_Tissues_V8_2023"), - Diabetes_Perturbations = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=Diabetes_Perturbations_GEO_2022"), - MSigDB_Hallmark = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=MSigDB_Hallmark_2020") + GTEx_Tissues = getGMT( + paste0(enrichr_url, "?mode=text&libraryName=GTEx_Tissues_V8_2023") + ), + Diabetes_Perturbations = getGMT( + paste0( + enrichr_url, + "?mode=text&libraryName=Diabetes_Perturbations_GEO_2022" + ) + ), + MSigDB_Hallmark = getGMT( + paste0(enrichr_url, "?mode=text&libraryName=MSigDB_Hallmark_2020") + ) ) ``` ```{r islet-priors, message=FALSE} islet_gmtList <- list( - GTEx_Tissues = readRDS(system.file("extdata", "GTEx_Tissues_V8_2023.rds", package = "CLAMP")), - Diabetes_Perturbations = readRDS(system.file("extdata", "Diabetes_Perturbations_GEO_2022.rds", package = "CLAMP")), - MSigDB_Hallmark = readRDS(system.file("extdata", "MSigDB_Hallmark_2020.rds", package = "CLAMP")) + GTEx_Tissues = readRDS( + system.file("extdata", "GTEx_Tissues_V8_2023.rds", package = "CLAMP") + ), + Diabetes_Perturbations = readRDS( + system.file( + "extdata", "Diabetes_Perturbations_GEO_2022.rds", + package = "CLAMP" + ) + ), + MSigDB_Hallmark = readRDS( + system.file("extdata", "MSigDB_Hallmark_2020.rds", package = "CLAMP") + ) ) islet_pathMat <- gmtListToSparseMat(islet_gmtList) @@ -625,8 +688,9 @@ datatable( ## Differential latent-variable expression between conditions -Rows of the B matrix correspond to LVs and columns to samples. By grouping samples by condition (ND vs T2D), -we compute average LV expression per group to identify LVs that differ between healthy and diabetic islets +Rows of the B matrix correspond to LVs and columns to samples. By grouping +samples by condition (ND vs T2D), we compute average LV expression per group to +identify LVs that differ between healthy and diabetic islets ```{r islet-diff, message=FALSE} B_df <- as.data.frame(as.matrix(islet_fullRes$B)) %>% @@ -706,7 +770,10 @@ common_genes <- intersect(islet_model_genes, wb_project_genes) cat( "Overlapping genes:", length(common_genes), "/", length(islet_model_genes), "islet model genes", - sprintf("(%.1f%%)\n", 100 * length(common_genes) / length(islet_model_genes)) + sprintf( + "(%.1f%%)\n", + 100 * length(common_genes) / length(islet_model_genes) + ) ) # projectCLAMP aligns common row names in the model's gene order @@ -782,7 +849,9 @@ are labelled directly. ```{r plot-topZ, message=FALSE, fig.width=9, fig.height=7} # Use the first few LVs that have pathway support -lv_with_paths <- wb_fullRes$withPrior[seq_len(min(4, length(wb_fullRes$withPrior)))] +lv_with_paths <- wb_fullRes$withPrior[ + seq_len(min(4, length(wb_fullRes$withPrior))) +] CLAMPplotTopZ( wb_fullRes, @@ -856,8 +925,10 @@ CLAMPdotplotAll( # Parallelization in CLAMP -CLAMP supports multi-core parallelization for computationally intensive operations, particularly when working with large datasets and file-backed matrices (FBMs). -The `ncores` parameter can be used in several key functions to speed up processing. +CLAMP supports multi-core parallelization for computationally intensive +operations, particularly when working with large datasets +and file-backed matrices (FBMs). The `ncores` parameter can be used in several +key functions to speed up processing. The following CLAMP functions accept an `ncores` parameter: From f0414703da9565d65cd1fc440d6c89aa94ea1072 Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Wed, 6 May 2026 11:41:35 -0600 Subject: [PATCH 10/20] Cleaned formatting and adding inst data --- R/utils.R | 18 ++-- .../Diabetes_Perturbations_GEO_2022.rds | Bin 0 -> 395987 bytes inst/extdata/GO_Biological_Process_2025.rds | Bin 0 -> 600815 bytes inst/extdata/GTEx_Tissues_V8_2023.rds | Bin 0 -> 171429 bytes inst/extdata/KEGG_2021_Human.rds | Bin 0 -> 81578 bytes inst/extdata/MSigDB_Hallmark_2020.rds | Bin 0 -> 26869 bytes tests/testthat/test-select_clamp_k.R | 79 ++++++++++-------- vignettes/comparing_clampbase_clampfull.Rmd | 71 ++++++++-------- vignettes/get_started.Rmd | 42 +++++----- 9 files changed, 112 insertions(+), 98 deletions(-) create mode 100644 inst/extdata/Diabetes_Perturbations_GEO_2022.rds create mode 100644 inst/extdata/GO_Biological_Process_2025.rds create mode 100644 inst/extdata/GTEx_Tissues_V8_2023.rds create mode 100644 inst/extdata/KEGG_2021_Human.rds create mode 100644 inst/extdata/MSigDB_Hallmark_2020.rds diff --git a/R/utils.R b/R/utils.R index b78d87c..d1e6647 100644 --- a/R/utils.R +++ b/R/utils.R @@ -562,7 +562,7 @@ zscoreCLAMP <- function(Y_filtered, rowStats) { stop("`Y_filtered` must be a numeric matrix (genes x samples).") } if (!is.data.frame(rowStats) || - !all(c("mean", "variance") %in% colnames(rowStats))) { + !all(c("mean", "variance") %in% colnames(rowStats))) { stop( "`rowStats` must be a data.frame with columns 'mean' ", "and 'variance'." @@ -632,8 +632,8 @@ zscoreCLAMP <- function(Y_filtered, rowStats) { #' res_all <- preprocessCLAMPFBM(fbm) #' @export preprocessCLAMPFBM <- function( - fbm, mean_cutoff = NULL, var_cutoff = NULL, backingfile = NULL, - block_size = 1000, ncores = 1 + fbm, mean_cutoff = NULL, var_cutoff = NULL, backingfile = NULL, + block_size = 1000, ncores = 1 ) { n_r <- nrow(fbm) n_c <- ncol(fbm) @@ -1143,7 +1143,7 @@ compute_svd <- function(Y, k = NULL) { #' @param data Raw data matrix. Required for `"permutation"` (row-normalized #' internally) and `"gavish_donoho"` (used for `n_genes`). #' @param B Number of permutations for `"permutation"`. -#' +#' #' @return An integer: the selected number of latent variables. #' #' @export @@ -1155,10 +1155,10 @@ select_clamp_k <- function(svdres, n_samples, svd_k, data = NULL, B = 20) { method <- match.arg(method) - if (method == "scaleSVs") { - scale.res <- getScaleFromSVs(svdres$d, n_samples) - return(min(floor(scale.res$k * 1.5), svd_k)) - } + if (method == "scaleSVs") { + scale.res <- getScaleFromSVs(svdres$d, n_samples) + return(min(floor(scale.res$k * 1.5), svd_k)) + } if (method == "elbow") { clamp_k <- num.pc(list(d = svdres$d), method = "elbow") @@ -1182,5 +1182,5 @@ select_clamp_k <- function(svdres, n_samples, svd_k, ) } - min(clamp_k * 2, svd_k) + min(clamp_k * 2, svd_k) } diff --git a/inst/extdata/Diabetes_Perturbations_GEO_2022.rds b/inst/extdata/Diabetes_Perturbations_GEO_2022.rds new file mode 100644 index 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-> svdKFBM svdKFBM -> svdFBM zscoredFBM -> svdFBM -> svdResFBM svdResFBM -> numPC @@ -456,7 +458,8 @@ alz_svd_k <- select_svd_k(alz_fbm_filt) alz_svd <- compute_svd(alz_fbm_filt, k = alz_svd_k) # Select clamp_k (elbow method by default) -alz_clamp_k <- select_clamp_k(alz_svd, n_samples = ncol(alz_fbm_filt), svd_k = alz_svd_k) +alz_clamp_k <- select_clamp_k(alz_svd, n_samples = ncol(alz_fbm_filt), + svd_k = alz_svd_k) alz_clamp_k ``` @@ -608,7 +611,8 @@ islet_svd_k <- select_svd_k(iso_Yz) islet_svd <- compute_svd(iso_Yz, k = islet_svd_k) # Select clamp_k (elbow method by default) -islet_clamp_k <- select_clamp_k(islet_svd, n_samples = ncol(iso_Yz), svd_k = islet_svd_k) +islet_clamp_k <- select_clamp_k(islet_svd, n_samples = ncol(iso_Yz), + svd_k = islet_svd_k) islet_clamp_k ``` @@ -816,10 +820,10 @@ option and works well when the signal-to-noise boundary is clear. ```{r k-elbow} select_clamp_k( - wb_svd, - n_samples = ncol(wb_Y_z), - svd_k = wb_svd_k, - method = "elbow" + wb_svd, + n_samples = ncol(wb_Y_z), + svd_k = wb_svd_k, + method = "elbow" ) ``` @@ -833,12 +837,12 @@ slower, but robust to smooth scree plots. ```{r k-permutation, eval=FALSE} select_clamp_k( - wb_svd, - n_samples = ncol(wb_Y_z), - svd_k = wb_svd_k, - method = "permutation", - data = wb_Y_z, - B = 2 + wb_svd, + n_samples = ncol(wb_Y_z), + svd_k = wb_svd_k, + method = "permutation", + data = wb_Y_z, + B = 2 ) ``` @@ -851,11 +855,11 @@ noise level. **PCAtools** implements this via `chooseGavishDonoho()`. ```{r k-gavish, eval=FALSE} select_clamp_k( - wb_svd, - n_samples = ncol(wb_Y_z), - svd_k = wb_svd_k, - method = "gavish_donoho", - data = wb_Y_z + wb_svd, + n_samples = ncol(wb_Y_z), + svd_k = wb_svd_k, + method = "gavish_donoho", + data = wb_Y_z ) ``` From 88d3005b38af5700ef2e1ad36da6259ca03b3b3d Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Wed, 6 May 2026 11:42:04 -0600 Subject: [PATCH 11/20] Readme badges --- README.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 382b184..a4fd966 100644 --- a/README.md +++ b/README.md @@ -3,7 +3,9 @@ [![GitHub issues](https://img.shields.io/github/issues/mchikina/CLAMP)](https://github.com/mchikina/mchikina/CLAMP) [![Lifecycle: stable](https://img.shields.io/badge/lifecycle-stable-green.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable) -[![R-CMD-check-bioc](https://github.com/mchikina/CLAMP/workflows/R-CMD-check-bioc/badge.svg)](https://github.com/mchikina/CLAMP/actions) +[![BiocCheck](https://github.com/chikinalab/CLAMP/actions/workflows/BiocCheck.yaml/badge.svg)](https://github.com/chikinalab/CLAMP/actions/workflows/BiocCheck.yaml) +[![R-CMD-check](https://github.com/chikinalab/CLAMP/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/chikinalab/CLAMP/actions/workflows/R-CMD-check.yaml) + ## Bioconductor release status From f65f2c7ff1517189ccb6270cd2fbe1dfa02dc848 Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Wed, 6 May 2026 11:42:30 -0600 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zXE(Dm^XR=^p=&KUZ>{hE`&#W6v-7~;nO?rXJrhl)&{7`{u&BXP-tlHVo~LCkC3}=K z_b^qp+om^L-o@4V^uuSlR@;TA(PC@l9ZzZJJ)Da8VPn4aG({B$j%rD2>@-DqY~Qnx}(Y-|e=c)3a^ zLy}tIRpwRk^YTsxXZxb~d^Oo>>){dGf!}udIzCoi23zUnM7+-)I{AEoBd+i{^`mj7 zFZikK;N7`L=gvL+)q8wh_Nf2XpDLu4AN%s?>I(D{txA(tCZjo?Uf*JV181-Hs=b~a z%_ovUIos;oE-d^`_o(lVBqL)9H&=h>o8V|Zt7L5#Z*%{+KH~X1Xg3Umy6W}^H>xdC z53sonN|BP|JoYVK#gD3t3nOuze72_6I(RGk?+AJ_{`Gu%{YlJ_AX8`KGOR_XKc+?W z%eR*|Ems)!_n+e2-?@=8uXJUrSL-}Fzqp7dpWjbEI)%ht9wKn3;+UO|*dRNtcxz`X nPsitie(daTz1S-Hr%mzSGHX`(q<{LS|M&j`V){%FbxI2W(?Rdg literal 0 HcmV?d00001 From 53c9aa09323f4ae87751f960b7225f0759081611 Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Wed, 6 May 2026 11:57:34 -0600 Subject: [PATCH 13/20] getting rid of block duplicate --- vignettes/get_started.Rmd | 4 ---- 1 file changed, 4 deletions(-) diff --git a/vignettes/get_started.Rmd b/vignettes/get_started.Rmd index 68c65da..16993d7 100644 --- a/vignettes/get_started.Rmd +++ b/vignettes/get_started.Rmd @@ -297,10 +297,6 @@ wb_baseRes <- CLAMPbase( Next, we build a prior matrix from curated gene sets and compute the Chat object for `CLAMPfull`. -```{r priors-download, eval=FALSE} -# How to download pathway and cell marker libraries from Enrichr. -# Not run during vignette build to avoid network calls; pre-fetched -# .rds files are loaded in the next chunk instead. ```{r priors-download, eval=FALSE} # How to download pathway and cell marker libraries from Enrichr. # Not run during vignette build to avoid network calls; pre-fetched From 7fe69a009fa573a52f438e097af3034a68458ec1 Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Wed, 6 May 2026 13:05:02 -0600 Subject: [PATCH 14/20] adding inst/scripts --- inst/scripts/fetch_vignette_gmts.R | 25 +++++++++++++++++++++++++ 1 file changed, 25 insertions(+) create mode 100644 inst/scripts/fetch_vignette_gmts.R diff --git a/inst/scripts/fetch_vignette_gmts.R b/inst/scripts/fetch_vignette_gmts.R new file mode 100644 index 0000000..d0e0ebb --- /dev/null +++ b/inst/scripts/fetch_vignette_gmts.R @@ -0,0 +1,25 @@ +# Fetches GMT gene set libraries from Enrichr and saves them as .rds files +# in inst/extdata/ for use in vignettes. +# +# Usage: Rscript inst/scripts/fetch_vignette_gmts.R +library(CLAMP) + +out_dir <- file.path("inst", "extdata") +enrichr_url <- "https://maayanlab.cloud/Enrichr/geneSetLibrary" +libs <- c( + "CellMarker_2024", + "KEGG_2021_Human", + "GO_Biological_Process_2025", + "GTEx_Tissues_V8_2023", + "MSigDB_Hallmark_2020", + "Diabetes_Perturbations_GEO_2022" +) + +for (name in libs) { + message("Fetching ", name, "...") + url <- paste0(enrichr_url, "?mode=text&libraryName=", name) + gmt <- getGMT(url, name = name) + out_path <- file.path(out_dir, paste0(name, ".rds")) + saveRDS(gmt, out_path) + message("Saved to ", out_path, " (", length(gmt), " gene sets)") +} \ No newline at end of file From 8b5112ac5c9b6988c679d7913d1538b6c7ada8d3 Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Wed, 6 May 2026 13:20:42 -0600 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-/*.Rcheck/ - -# RStudio files -.Rproj.user/ - -# produced vignettes -vignettes/*.html -vignettes/*.pdf - -# OAuth2 token, see https://github.com/hadley/httr/releases/tag/v0.3 -.httr-oauth - -# knitr and R markdown default cache directories -*_cache/ -/cache/ - -# Temporary files created by R markdown -*.utf8.md -*.knit.md - -# R Environment Variables -.Renviron - -# translation temp files -po/*~ - -# RStudio Connect folder -rsconnect/ - - -#Scratch -scratch/ - -.vscode/ - -src/*.o -src/*.so diff --git a/_pkgdown.yml b/_pkgdown.yml deleted file mode 100644 index bb31289..0000000 --- a/_pkgdown.yml +++ /dev/null @@ -1,62 +0,0 @@ -url: https://mchikina.github.io/CLAMP/ - -template: - bootstrap: 5 - -navbar: - structure: - left: [intro, articles, reference, news] - right: [search, github] - components: - github: - icon: fab fa-github - href: https://github.com/mchikina/CLAMP - aria-label: GitHub - -articles: - - title: "Vignettes" - navbar: ~ - contents: - - get_started - - comparing_clampbase_clampfull - -reference: - - title: "Main CLAMP functions" - contents: [CLAMPbase, CLAMPfull, CLAMPfullnVP, projectCLAMP] - - title: "SVD and rank selection" - contents: [select_svd_k, compute_svd, select_clamp_k, num.pc, getScaleFromSVs] - - title: "Preprocessing" - contents: [cpmCLAMP, cpmCLAMPFBM, preprocessCLAMP, preprocessCLAMPFBM, - zscoreCLAMP, zscoreCLAMPFBM, tscale] - - title: "Prior knowledge" - contents: [getGMT, read_gmt, gmtListToSparseMat, getMatchedPathwayMat, - getMatchedPathwayMatList, getChat] - - title: "Evaluation and visualization" - contents: [compareBs, allAgainstAllAUCs, CLAMPplotU, CLAMPplotTopZ, - CLAMPdotplot, CLAMPdotplotAll, plotTopZ_Complex] - - title: "FBM utilities" - contents: [cleanFBM, filterFBM] - - title: "Solvers and helpers" - contents: [cross_ZY, ridge_B, solveU, mat_mult, findSplineMax, - oneToOneMask, squashZscore, winsor_topk] - - title: "Datasets" - contents: [dataWholeBlood, celltypeTargets, majorCellTypes, panDB, xCell] - - title: internal - contents: - - AUC - - BH - - binarizeTop - - commonRows - - computeRowStatsFBM - - crossVal - - getAUCstats - - getMatchedPathwayMat2 - - getMatchedPathwayMatOld - - getMaxAUC - - max_correspondence_greedy - - mymessage - - pinv.ridge - - rotateSVD - - row_cor - - run_elbow - - run_permutation diff --git a/docs/404.html b/docs/404.html deleted file mode 100644 index 73ad8dc..0000000 --- a/docs/404.html +++ /dev/null @@ -1,82 +0,0 @@ - - - - - - - -Page not found (404) • CLAMP - - - - - - - - Skip to contents - - -

        -
        -
        - -

        Page not found (404)

        - -
        - -Content not found. Please use links in the navbar. - -
        -
        - - -
        -

        Developed by Marc Subirana-Granes, Maria Chikina.

        -
        - -
        -

        Site built with pkgdown 2.2.0.

        -
        - -
        -
        - - - - - - - diff --git a/docs/articles/comparing_clampbase_clampfull.html b/docs/articles/comparing_clampbase_clampfull.html deleted file mode 100644 index a4b2b69..0000000 --- a/docs/articles/comparing_clampbase_clampfull.html +++ /dev/null @@ -1,321 +0,0 @@ - - - - - - - -Comparing CLAMPbase and CLAMPfull • CLAMP - - - - - - - - Skip to contents - - -
        - - - -
        -
        - -

        Comparing CLAMPbase and CLAMPfull

        -

        Maria Chikina

        - - - Source: vignettes/comparing_clampbase_clampfull.Rmd -
        comparing_clampbase_clampfull.Rmd
        -
        - - - -
        -

        Overview -

        -

        This vignette compares the two main models in the CLAMP package:

        -
          -
        1. -CLAMPbase: Unsupervised matrix factorization for dimensionality reduction without prior knowledge.
          2. -
        2. -CLAMPfull: Pathway-guided refinement that integrates biological prior knowledge to improve interpretability.
          3. -
        -

        Using a small human whole blood RNA-Seq dataset, we demonstrate that incorporating pathway priors in CLAMPfull improves the biological interpretability of latent variables compared to the baseline CLAMPbase model.

        -

        We illustrate how to:

        -
          -
        • Fit both CLAMPbase and CLAMPfull models,
          • -
        • Compare their performance using cell type correlations, and
          • -
        • Verify that the FBM (Filebacked Big Matrix) implementation produces identical results.
          • -
        -
        -

        1. Load Data and Normalize -

        -
        -data("dataWholeBlood")
-data("majorCellTypes")
-data('celltypeTargets')
-
-# Scale each gene to mean 0 and variance 1
-dataWholeBlood <- tscale(dataWholeBlood)
        -
        -
        -

        2. Load Prior Knowledge Matrices -

        -
        -# Download pathway and cell marker libraries from Enrichr
-gmtList <- list(
-  CellMarkers = getGMT(
-    "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=CellMarker_2024",
-    "CellMarker_2024"
-  ),
-  KEGG = getGMT(
-    "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=KEGG_2021_Human",
-    "KEGG_2021_Human"
-  )
-)
-
-# Combine into a single sparse matrix
-pathMatCell <- gmtListToSparseMat(gmtList)
-
-# Load additional xCell reference matrix
-data("xCell")
-
-# Match pathways to the gene space of whole blood
-matchedPathsWB <- getMatchedPathwayMatList(
-  pathMatCell,
-  xCell,
-  new.genes = rownames(dataWholeBlood),
-  min.genes = 2
-)
        -
        -
        -

        3. Compute SVD and Infer k -

        -
        -set.seed(1)
-wb_svd_k   <- select_svd_k(dataWholeBlood)
-wb_svd     <- compute_svd(dataWholeBlood, k = wb_svd_k)
-wb_clamp_k <- select_clamp_k(wb_svd, n_samples = ncol(dataWholeBlood), svd_k = wb_svd_k)
-wb_clamp_k
        -
        ## [1] 8
        -
        -
        -

        4. Fit CLAMPbase and CLAMPfull -

        -
        -wb_clamp_base <- CLAMPbase(
-  dataWholeBlood,
-  svdres     = wb_svd,
-  clamp_k    = wb_clamp_k,
-  trace      = FALSE,
-  adaptive.p = 0.05
-)
        -
        -wb_clamp_full <- CLAMPfull(
-  dataWholeBlood,
-  priorMat          = matchedPathsWB,
-  svdres            = wb_svd,
-  clamp.base.result = wb_clamp_base,
-  clamp_k           = wb_clamp_k,
-  trace             = TRUE,
-  use_cpp           = TRUE
-)
        -
        -
        -

        5. Compare CLAMPbase vs CLAMPfull -

        -

        This plot compares the maximum Spearman correlation for each major blood cell type between CLAMPbase and CLAMPfull.

        -

        Points above the red dashed line indicate improved correspondence when biological priors are included.

        -

        Most cell types show higher correlations under CLAMPfull, demonstrating that integrating pathway information helps capture more biologically meaningful latent variables.

        -
        -output <- compareBs(
-  wb_clamp_base,
-  wb_clamp_full,
-  celltypeTargets,
-  method = "s",
-  xlab   = "CLAMPbase",
-  ylab   = "CLAMPfull"
-)
        -
        ## [1]  8 36
-## [1]  8 36
        -
        -output$plot
        -

        -
        -
        -

        6. Inspect Named Matrix Outputs -

        -

        CLAMPbase and CLAMPfull now return B (gene loadings, LVs × genes) and Z (sample scores, LVs × samples) as proper named matrices.

        -
        -# B: gene loadings (LVs × genes)
-dim(wb_clamp_full$B)
        -
        ## [1]  8 36
        -
        -wb_clamp_full$B[1:3, 1:4]
        -
        ##         BD8001    BD8002      BD8003    BD8004
-## LV1  1.5208805  1.019819  1.52010647  1.723528
-## LV2 -0.3858266  1.290221 -2.01065989 -2.148343
-## LV3 -0.7590255 -1.089290 -0.02649019 -3.321543
        -
        -# Z: sample scores (LVs × samples)
-dim(wb_clamp_full$Z)
        -
        ## [1] 11530     8
        -
        -wb_clamp_full$Z[1:3, 1:4]
        -
        ##          LV1       LV2 LV3 LV4
-## GAS6       0 0.0000000   0   0
-## MMP14      0 0.0000000   0   0
-## MARCKSL1   0 0.3406663   0   0
        -
        -
        -

        7. Verify FBM Implementation -

        -

        We verify that CLAMPfull produces identical results when using a file-backed matrix (FBM) input instead of an in-memory matrix. We reuse the same pre-computed SVD and clamp_k so that any differences are attributable solely to the matrix format, not the randomized SVD.

        -
        -dataWholeBloodFBM <- bigstatsr::as_FBM(dataWholeBlood)
-
-wb_clamp_full_fbm <- CLAMPfull(
-  dataWholeBloodFBM,
-  priorMat          = matchedPathsWB,
-  svdres            = wb_svd,
-  clamp.base.result = wb_clamp_base,
-  clamp_k           = wb_clamp_k,
-  trace             = TRUE,
-  use_cpp           = TRUE
-)
        -

        The FBM implementation produces identical results:

        -
        -output <- compareBs(
-  wb_clamp_full,
-  wb_clamp_full_fbm,
-  celltypeTargets,
-  method = "s",
-  xlab   = "CLAMPfull (matrix)",
-  ylab   = "CLAMPfull (FBM)"
-)
        -
        ## [1]  8 36
-## [1]  8 36
        -
        -output$plot
        -

        -
        -
        -
        -

        Session Information -

        - -
        ## R Under development (unstable) (2026-02-02 r89367)
-## Platform: x86_64-pc-linux-gnu
-## Running under: Pop!_OS 22.04 LTS
-## 
-## Matrix products: default
-## BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so;  LAPACK version 3.10.0
-## 
-## locale:
-##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
-##  [3] LC_TIME=es_ES.UTF-8        LC_COLLATE=en_US.UTF-8    
-##  [5] LC_MONETARY=es_ES.UTF-8    LC_MESSAGES=en_US.UTF-8   
-##  [7] LC_PAPER=es_ES.UTF-8       LC_NAME=C                 
-##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
-## [11] LC_MEASUREMENT=es_ES.UTF-8 LC_IDENTIFICATION=C       
-## 
-## time zone: America/Denver
-## tzcode source: system (glibc)
-## 
-## attached base packages:
-## [1] stats     graphics  grDevices utils     datasets  methods   base     
-## 
-## other attached packages:
-## [1] bigstatsr_1.6.2  CLAMP_0.99.0     BiocStyle_2.39.0
-## 
-## loaded via a namespace (and not attached):
-##  [1] gtable_0.3.6          circlize_0.4.17       shape_1.4.6.1        
-##  [4] rjson_0.2.23          xfun_0.56             bslib_0.10.0         
-##  [7] ggplot2_4.0.2         htmlwidgets_1.6.4     GlobalOptions_0.1.3  
-## [10] ggrepel_0.9.6         lattice_0.22-7        bigassertr_0.1.7     
-## [13] ps_1.9.1              vctrs_0.7.1           tools_4.6.0          
-## [16] generics_0.1.4        stats4_4.6.0          parallel_4.6.0       
-## [19] tibble_3.3.1          cluster_2.1.8.1       pkgconfig_2.0.3      
-## [22] Matrix_1.7-4          RColorBrewer_1.1-3    S7_0.2.1             
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        Developed by Marc Subirana-Granes, Maria Chikina.

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        Site built with pkgdown 2.2.0.

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        - - - - - - - - - - - -
        -
        - -

        Analyzing human RNA-Seq data with CLAMP

        -

        Marc Subirana-Granés

        - - - Source: vignettes/get_started.Rmd -
        get_started.Rmd
        -
        - - - -

        -
        -

        Introduction -

        -

        The CLAMP (Curated Latent-variable Analysis with Molecular Priors) package provides a two-stage framework to extract interpretable latent variables from high-dimensional transcriptomic data. It combines a standard matrix decomposition (CLAMPbase) with pathway-guided factor refinement (CLAMPfull), enabling:

        -
          -
        1. -Dimensionality reduction of gene expression matrices
          -
          2. -
        2. -Incorporation of prior knowledge (e.g., Gene Ontology or MSigDB)
          -
          3. -
        3. -Adaptive regularization of gene weights based on their agreement with pathway priors
          -
          4. -
        4. -Cross-validation to select robust latent variables
          5. -
        -

        In CLAMPfull, pathway information is integrated through an adaptive variance prior that dynamically modulates the contribution of each gene according to how well its latent signal aligns with pathway predictions. This mechanism allows CLAMP to emphasize biologically consistent genes while maintaining flexibility to discover novel, data-driven components.
        -By combining prior-guided regularization with scalable matrix updates, CLAMPfull produces interpretable latent variables that capture both known and emergent biological processes across large transcriptomic datasets.

        -
        -

        Workflow overview -

        -
        - -
        -
        -
        -

        Quick Start -

        -

        We provide three examples:

        -
          -

        1. Data-frame example (whole blood):
          -A small dataset loaded entirely into memory. Shows basic preprocessing, z-scoring, and running CLAMP without on-disk storage.

          2. -

        2. HDF5 example (Alzheimer’s brain):
          -Demonstrates how to import expression from an HDF5 file, create a file-backed FBM object, and process larger datasets using the FBM interface.

          3. -

        3. Table example (pancreatic islets):
          -Illustrates reading a tab-delimited count file and comparing conditions via the B matrix.

          4. -
        -

        Each example follows these steps:

        -
          -
        1. -Load & preprocess data (filter by mean/variance, then z-score).
          2. -
        2. -Compute SVD and infer the model dimension k.
          3. -
        3. -Prepare pathway annotations via getGMT() and construct the prior matrix.
          4. -
        4. -Run CLAMPbase with the pre-computed SVD result and k to initialize the latent variables.
          5. -
        5. -Run CLAMPfull to refine latent variables using pathway priors and variance-adaptive regularization, producing the final model and summary statistics.
          6. -
        -
        -

        Computing the SVD and inferring k -

        -

        CLAMP requires a truncated Singular Value Decomposition (SVD) of the z-scored expression matrix as input. The choice of SVD function depends on dataset size:

        -
          -

        • Small to medium datasets (in-memory): Use rsvd::rsvd() from the rsvd package. This is efficient for matrices that fit comfortably in RAM.

          • -

        • Large datasets (file-backed): Use bigstatsr::big_randomSVD() for file-backed matrices (FBM). This function computes the SVD without loading the entire matrix into memory, enabling analysis of datasets too large for RAM.

          • -
        -

        After computing the SVD, infer the optimal number of latent variables (clamp_k) using num.pc():

        -
        -
        -
        -

        Example 1: In-memory data.frame (Whole Blood) -

        -
        -

        Load example data -

        -

        In this chunk, we load the whole-blood expression matrix.

        -
        -data("dataWholeBlood") # expression matrix
-dim(dataWholeBlood) # genes x samples
-#> [1] 11530    36
-head(dataWholeBlood) # genes x samples
-#>             BD8001    BD8002    BD8003    BD8004    BD8005    BD8006    BD8007
-#> GAS6      7.123563  7.846633  8.356313  7.387916  7.859675  7.057541  8.960098
-#> MMP14     6.636157  7.523565  7.033673  6.895476  6.860524  7.268107  7.121380
-#> MARCKSL1 10.632837 11.208832 10.519870 10.804867 10.940891 10.984602 11.258157
-#> SPARC    12.206811 11.462327 12.391210 12.457026 12.036049 12.010138 11.342475
-#> CTSD     13.147963 13.218464 12.574546 12.710222 13.151780 13.131948 13.466095
-#> EPAS1     7.011590  6.196898  6.621782  7.251964  6.792337  6.813567  6.785256
-#>             BD8008    BD8009    BD8010    BD8011    BD8012    BD8013    BD8015
-#> GAS6      8.120199  7.061915  7.467680  7.593766  7.980510  7.608529  7.524665
-#> MMP14     7.196859  6.764261  7.788809  6.925929  6.658480  7.035367  7.105207
-#> MARCKSL1 10.943532 11.242130 11.001261 11.094241 10.827391 10.850013 11.201983
-#> SPARC    10.979392 12.464739 11.297043 11.613255 12.116145 12.598474 12.364565
-#> CTSD     13.326034 12.885950 13.818859 13.065856 12.869455 12.964527 13.407112
-#> EPAS1     6.434220  6.310941  5.269084  6.223021  6.383971  5.728530  6.633363
-#>             BD8017    BD8018    BD8019    BD8020    BD8021    BD8024    BD8025
-#> GAS6      7.939325  8.391950  7.950956  7.560154  7.852542  8.388111  8.465422
-#> MMP14     6.905814  7.408872  6.958392  7.166190  6.294972  7.360992  7.649716
-#> MARCKSL1 11.088379 11.074874 10.699760 10.778236 11.107787 11.249868 11.004432
-#> SPARC    11.935750 12.469152 11.950393 11.285404 12.836662 12.553092 11.980064
-#> CTSD     13.669278 13.345946 13.097458 12.637596 13.481647 13.920715 13.477684
-#> EPAS1     7.215680  6.401987  6.834593  6.820674  6.909808  6.242905  6.770166
-#>             BD8026    BD8027    BD8028    BD8029    BD8030    BD8031    BD8032
-#> GAS6      7.924237  7.438211  7.562134  7.941111  7.476552  7.837566  7.576831
-#> MMP14     7.265736  6.875840  7.166484  7.365906  7.163581  7.026309  6.822608
-#> MARCKSL1 10.861711 10.859864 10.908438 10.817281 10.879364 10.540350 11.192079
-#> SPARC    11.762774 11.171782 12.461855 11.742365 13.040843 10.445423 11.940918
-#> CTSD     13.034718 12.819660 12.713603 12.618206 12.903100 12.837019 13.388076
-#> EPAS1     6.792149  6.321837  7.195378  6.219153  6.971319  7.149990  6.572446
-#>             BD8033    BD8034    BD8038    BD8041    BD8042    BD8043    BD8044
-#> GAS6      7.589572  7.751689  7.764586  7.526250  7.144113  7.874906  7.362536
-#> MMP14     7.197420  7.060375  6.712708  6.758632  6.506008  7.371407  7.299790
-#> MARCKSL1 10.913452 10.910316 10.731734 10.960063 10.852984 10.863946 11.093211
-#> SPARC    12.454682 11.457722 11.688371 11.563955 12.331355 11.409792 11.690587
-#> CTSD     12.851351 12.840063 12.448499 13.271724 12.993058 13.506943 13.312904
-#> EPAS1     6.573068  5.614770  7.084063  5.418134  6.325518  6.446405  6.739370
-#>             BD8045
-#> GAS6      8.315021
-#> MMP14     7.354577
-#> MARCKSL1 11.404975
-#> SPARC    12.448106
-#> CTSD     14.070121
-#> EPAS1     6.382976
        -
        -
        -

        Preprocess and z-score -

        -

        We first CPM-normalize the data (when needed), filter for genes with mean expression ≥ 0.5 and variance ≥ 0.1, and then apply z-score normalization.

        -
        -#  CPM normalization
-dataWholeBlood_cpm <- cpmCLAMP(dataWholeBlood)
-
-# Filter and compute row statistics
-prep_wb <- preprocessCLAMP(
-    Y = dataWholeBlood_cpm,
-    mean_cutoff = 0.5,
-    var_cutoff = 0.1
-)
-
-# Extract filtered matrix and rowStats
-wb_Y_filtered <- prep_wb$Y_filtered
-wb_rowStats <- prep_wb$rowStats
-
-
-# Z-score normalization
-wb_Y_z <- zscoreCLAMP(
-    Y_filtered = wb_Y_filtered,
-    rowStats = wb_rowStats
-)
        -
        -
        -

        Compute SVD and infer k -

        -

        We compute the SVD using select_svd_k() and compute_svd(), then select clamp_k with select_clamp_k().

        -
        -# Select SVD rank and compute SVD
-wb_svd_k   <- select_svd_k(wb_Y_z)
-wb_svd     <- compute_svd(wb_Y_z, k = wb_svd_k)
-
-# Select clamp_k (elbow method by default)
-wb_clamp_k <- select_clamp_k(wb_svd, n_samples = ncol(wb_Y_z), svd_k = wb_svd_k)
-wb_clamp_k
-#> [1] 8
        -
        -
        -

        CLAMPbase initialization -

        -

        We initialize latent variables using CLAMPbase, providing the pre-computed SVD and inferred k.

        -

        The argument adaptive.p defines the percentile used to determine the adaptive sparsity threshold applied to each latent variable’s gene loadings. During alternating updates, negative entries in Z are treated as noise, and CLAMP estimates a cutoff based on the adaptive.p quantile of these negative values. All genes with loadings below this cutoff are set to zero. This produces data-driven sparsity, automatically filtering weak or noisy signals while retaining genes with the strongest positive contributions. Lower values of adaptive.p (e.g., 0.01) result in stronger sparsity, while higher values (e.g., 0.1) retain more genes. The default adaptive.p = 0.05 typically yields interpretable, well-separated latent variables in large transcriptomic datasets.

        -
        -wb_baseRes <- CLAMPbase(
-    Y = wb_Y_z,
-    svdres = wb_svd,
-    clamp_k = wb_clamp_k
-)
        -
        -
        -

        Prepare pathway priors -

        -

        Next, we build a prior matrix from curated gene sets and compute the Chat object for CLAMPfull.

        -
        -# Download pathway and cell marker libraries from Enrichr
-gmtList <- list(
-  CellMarkers = getGMT(
-    "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=CellMarker_2024",
-    "CellMarker_2024"
-  ),
-  KEGG = getGMT(
-    "https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=KEGG_2021_Human",
-    "KEGG_2021_Human"
-  )
-)
-
-# Combine into a single sparse matrix
-pathMatCell <- gmtListToSparseMat(gmtList)
-
-# Load additional xCell reference matrix
-data("xCell")
-
-# Match pathways to the gene space of whole blood
-matchedPathsWB <- getMatchedPathwayMatList(
-  pathMatCell, xCell,
-  new.genes = rownames(dataWholeBlood),
-  min.genes = 2
-)
        -

        Note: GMT files can also be loaded from local storage using read_gmt(). This allows you to integrate custom or curated gene set libraries, such as MSigDB canonical pathways, directly into your analysis pipeline alongside remote resources.

        -
        -
        -

        CLAMPfull -

        -

        Finally, we refine the base model by integrating pathway priors using CLAMPfull, which applies cross-validation to optimize latent variable regularization. In this new version, CLAMPfull incorporates variable priors that adjust the influence of each pathway adaptively, improving convergence and stability across heterogeneous datasets.

        -
        -wb_fullRes <- CLAMPfull(
-    wb_Y_z,
-    priorMat = matchedPathsWB,
-    clamp.base.result = wb_baseRes,
-    svdres = wb_svd,
-    clamp_k = wb_clamp_k,
-    use_cpp = TRUE
-  )
        -
        -
        -

        Display significant latent variables -

        -
        -# Display significant latent variables
-wb_summary_df <- as.data.frame(wb_fullRes$summary) %>%
-    dplyr::filter(FDR < 0.05 & AUC > 0.7) %>%
-    dplyr::arrange(FDR) %>%
-    dplyr::select(LV, pathway, FDR, AUC)
-
-datatable(
-    wb_summary_df,
-    filter = "top",
-    options = list(
-        pageLength = 10,
-        autoWidth  = TRUE
-    ),
-    rownames = FALSE,
-    class = "stripe hover compact"
-) %>%
-    formatSignif(c("AUC", "FDR"), 3)
        -
        - -
        -
        -
        -

        Example 2: File-Backed Matrix (Alzheimer’s Brain) -

        -

        This example uses data from Alzheimer’s brain samples from a Neurobiology of Disease study (Barbash et al., 2017; DOI: https://doi.org/10.1016/j.nbd.2017.06.008). It demonstrates the on‑disk workflow with a file‑backed FBM to handle large‑scale transcriptomic datasets.

        -
        -

        Cleanup old FBM files -

        -
        -output_dir <- here("output", "alzFBM")
-fbm_base <- file.path(output_dir, "FBMalz")
-bk_paths <- paste0(fbm_base, c(".bk", "_preproc.bk", "_preproc_filtered.bk"))
-file.remove(bk_paths[file.exists(bk_paths)])
-#> [1] TRUE TRUE TRUE
        -
        -

        Computing CPM on a File-Backed Matrix (FBM) -

        -

        For file-backed matrices (FBMs), you can compute counts-per-million (CPM) in-place—without loading the entire dataset into RAM—using the cpmCLAMPFBM() function from CLAMP:

        -
        -
        -
        -

        Load HDF5 expression -

        -
        -alz_path <- human_gene_v2_5_alz_h5()
-h5 <- H5File$new(alz_path, mode = "r")
-expr_mat <- t(h5[["data/expression"]]$read())
-genes <- h5[["meta/genes/symbol"]]$read()
-samples <- h5[["meta/samples/geo_accession"]]$read()
-h5$close_all()
-colnames(expr_mat) <- samples
-rownames(expr_mat) <- genes
        -
        -
        -

        Construct file‑backed FBM -

        -
        -dir.create(output_dir, recursive = TRUE, showWarnings = FALSE)
-alzFBM <- FBM(nrow = nrow(expr_mat), ncol = ncol(expr_mat), backingfile = fbm_base)
-blk <- 1000
-
-for (i in seq_len(ceiling(nrow(expr_mat) / blk))) {
-    rows <- ((i - 1) * blk + 1):min(i * blk, nrow(expr_mat))
-    alzFBM[rows, ] <- expr_mat[rows, , drop = FALSE]
-}
        -
        -
        -

        CPM, preprocess and z‑score FBM -

        -
        -prep_alz <- preprocessCLAMPFBM(
-    fbm = alzFBM,
-    mean_cutoff = 0.5,
-    var_cutoff = 0.1
-)
-
-alz_fbm_filt <- prep_alz$fbm_filtered
-alz_rowStats <- prep_alz$rowStats
-zscoreCLAMPFBM(alz_fbm_filt, alz_rowStats)
-alz_genes <- genes[prep_alz$kept_rows]
        -
        -
        -

        Compute SVD and infer k -

        -

        For file-backed matrices, compute_svd() dispatches to bigstatsr::big_SVD() automatically, avoiding loading the entire matrix into RAM.

        -
        -# Select SVD rank and compute SVD (dispatches to bigstatsr for FBM)
-alz_svd_k   <- select_svd_k(alz_fbm_filt)
-alz_svd     <- compute_svd(alz_fbm_filt, k = alz_svd_k)
-
-# Select clamp_k (elbow method by default)
-alz_clamp_k <- select_clamp_k(alz_svd, n_samples = ncol(alz_fbm_filt), svd_k = alz_svd_k)
-alz_clamp_k
-#> [1] 13
        -
        -
        -

        CLAMPbase -

        -
        -alz_baseRes <- CLAMPbase(
-    Y = alz_fbm_filt,
-    svdres = alz_svd,
-    clamp_k = alz_clamp_k
-)
        -
        -
        -

        Prepare pathway priors -

        -
        -alz_gmtList <- list(
-    GTEx_Tissues = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=GTEx_Tissues_V8_2023"),
-    BP = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=GO_Biological_Process_2025"),
-    MSigDB = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=MSigDB_Hallmark_2020")
-)
-
-alz_pathMat <- gmtListToSparseMat(alz_gmtList)
-alz_matched <- getMatchedPathwayMat(alz_pathMat, alz_genes)
        -
        -
        -

        CLAMPfull -

        -
        -alz_fullRes <- CLAMPfull(
-    alz_fbm_filt,
-    priorMat = alz_matched,
-    clamp.base.result = alz_baseRes,
-    svdres = alz_svd,
-    clamp_k = alz_clamp_k,
-    use_cpp = TRUE
-  )
        -
        -
        -

        Display significant latent variables -

        -
        -alz_summary_df <- as.data.frame(alz_fullRes$summary) %>%
-    dplyr::filter(FDR < 0.05 & AUC > 0.7) %>%
-    dplyr::arrange(FDR) %>%
-    dplyr::select(LV, pathway, FDR, AUC)
-
-datatable(
-    alz_summary_df,
-    filter = "top",
-    options = list(
-        pageLength = 10,
-        autoWidth  = TRUE
-    ),
-    rownames = FALSE,
-    class = "stripe hover compact"
-) %>%
-    formatSignif(c("AUC", "FDR"), 3)
        -
        - -
        -
        -
        -

        Example 3: Tab-Delimited Count File (Pancreatic Islets) -

        -

        In this example, we apply the in‑memory CLAMP workflow to RNA‑Seq count data from GEO accession GSE164416 (Wigger et al. 2021; “Multi‑omics profiling of living human pancreatic islet donors reveals heterogeneous beta-cell trajectories towards type 2 diabetes”, DOI: 10.1038/s42255-021-00420-9). After preprocessing the raw counts and fitting the CLAMP model, we perform a differential analysis of latent‑variable activities to compare non‑diabetic (ND) and type 2 diabetic (T2D) samples.

        -
        -

        Load count data and map gene symbols -

        -
        -islet_file <- GSE164416_DP_htseq_counts_txt_gz()
-islet_df <- read.table(gzfile(islet_file), header = TRUE, stringsAsFactors = FALSE) 
-
-islet_df$symbol <- mapIds( org.Hs.eg.db,
-                           keys = islet_df$ensembl,
-                           column = "SYMBOL",
-                           keytype = "ENSEMBL",
-                           multiVals = "first" )
-
-islet_df <- islet_df[!is.na(islet_df$symbol), ]
        -
        -
        -

        Aggregate counts by gene symbol -

        -
        -# Sum counts per symbol
-setDT(islet_df)
-num_cols <- names(islet_df)[sapply(islet_df, is.numeric)]
-expr <- islet_df[, lapply(.SD, sum), by = symbol, .SDcols = num_cols]
-expr <- as.data.frame(expr)
-rownames(expr) <- expr$symbol
-expr$symbol <- NULL
-expr <- as.matrix(expr)
        -
        -
        -

        CPM, preprocess and z-score -

        -
        -prep_is <- preprocessCLAMP(
-    Y = expr,
-    mean_cutoff = 0.5,
-    var_cutoff = 0.1
-)
-
-iso_Yf <- prep_is$Y_filtered
-iso_rowS <- prep_is$rowStats
-
-iso_Yz <- zscoreCLAMP(Y_filtered = iso_Yf,
-                      rowStats = iso_rowS)
        -
        -
        -

        Compute SVD and infer k -

        -
        -# Select SVD rank and compute SVD
-islet_svd_k   <- select_svd_k(iso_Yz)
-islet_svd     <- compute_svd(iso_Yz, k = islet_svd_k)
-
-# Select clamp_k (elbow method by default)
-islet_clamp_k <- select_clamp_k(islet_svd, n_samples = ncol(iso_Yz), svd_k = islet_svd_k)
-islet_clamp_k
-#> [1] 22
        -
        -
        -

        CLAMPbase -

        -
        -islet_baseRes <- CLAMPbase(
-    Y = iso_Yz,
-    svdres = islet_svd,
-    clamp_k = islet_clamp_k
-)
        -
        -
        -

        Prepare pathway priors -

        -
        -islet_gmtList <- list(
-    GTEx_Tissues = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=GTEx_Tissues_V8_2023"),
-    Diabetes_Perturbations = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=Diabetes_Perturbations_GEO_2022"),
-    MSigDB_Hallmark = getGMT("https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=MSigDB_Hallmark_2020")
-)
-
-islet_pathMat <- gmtListToSparseMat(islet_gmtList)
-islet_matched <- getMatchedPathwayMat(islet_pathMat, rownames(iso_Yz))
-islet_chatObj <- getChat(islet_matched)
        -
        -
        -

        CLAMPfull -

        -
        -islet_fullRes <- CLAMPfull(
-    iso_Yz,
-    priorMat = islet_matched,
-    clamp.base.result = islet_baseRes,
-    svdres = islet_svd,
-    clamp_k = islet_clamp_k,
-    use_cpp = TRUE
-  )
        -
        -
        -

        Display significant latent variables -

        -
        -islet_summary_df <- as.data.frame(islet_fullRes$summary) %>%
-    dplyr::filter(FDR < 0.05 & AUC > 0.7) %>%
-    dplyr::arrange(FDR) %>%
-    dplyr::select(LV, pathway, FDR, AUC)
-
-datatable(
-    islet_summary_df,
-    filter = "top",
-    options = list(
-        pageLength = 10,
-        autoWidth  = TRUE
-    ),
-    rownames = FALSE,
-    class = "stripe hover compact"
-) %>%
-    formatSignif(c("AUC", "FDR"), 3)
        -
        - -
        -
        -

        Differential latent-variable expression between conditions -

        -

        Rows of the B matrix correspond to LVs and columns to samples. By grouping samples by condition (ND vs T2D), we compute average LV expression per group to identify LVs that differ between healthy and diabetic islets

        -
        -B_df <- as.data.frame(as.matrix(islet_fullRes$B)) %>%
-    dplyr::mutate(LV = rownames(.))
-
-islet_meta <- islets_metadata_csv()
-iselt_metadata <- read.csv(islet_meta, header = TRUE)
-
-sample_types <- iselt_metadata %>%
-    dplyr::mutate(
-        id   = as.character(id),
-        type = as.character(type)
-    )
-
-sample_cols <- setdiff(colnames(B_df), "LV")
-nd_cols <- intersect(sample_cols, sample_types$id[sample_types$type == "ND"])
-other_cols <- intersect(sample_cols, sample_types$id[sample_types$type != "ND"])
-
-if (length(nd_cols) == 0 || length(other_cols) == 0) {
-    stop("No matching ND or non-ND sample columns found")
-}
-
-lv_stats_all_vs_nd <- B_df %>%
-    dplyr::rowwise() %>%
-    dplyr::mutate(
-        Mean_ND = mean(dplyr::c_across(dplyr::all_of(nd_cols))),
-        Mean_All = mean(dplyr::c_across(dplyr::all_of(other_cols))),
-        Mean_Diff = Mean_All - Mean_ND,
-        P_Value = stats::wilcox.test(
-            dplyr::c_across(dplyr::all_of(nd_cols)),
-            dplyr::c_across(dplyr::all_of(other_cols))
-        )$p.value
-    ) %>%
-    dplyr::ungroup() %>%
-    dplyr::mutate(FDR = stats::p.adjust(P_Value, method = "fdr")) %>%
-    dplyr::select(LV, Mean_ND, Mean_All, Mean_Diff, P_Value, FDR) %>%
-    dplyr::arrange(FDR)
-
-sig_lv_all_vs_nd <- lv_stats_all_vs_nd %>%
-    dplyr::filter(FDR < 0.1)
-
-sig_pathway <- islet_summary_df %>%
-    dplyr::filter(FDR < 0.05 & AUC > 0.7) %>%
-    dplyr::filter(LV %in% sig_lv_all_vs_nd$LV) %>%
-    dplyr::arrange(FDR) %>%
-    dplyr::select(LV, pathway, FDR, AUC)
-
-datatable(
-    sig_pathway,
-    filter = "top",
-    options = list(
-        pageLength = 10,
-        autoWidth  = TRUE
-    ),
-    rownames = FALSE,
-    class = "stripe hover compact"
-) %>%
-    formatSignif(c("AUC", "FDR"), 3)
        -
        - -
        -
        -
        -

        Projection: Applying one CLAMP model to another dataset -

        -

        projectCLAMP() reuses the gene loadings (Z) from a fitted CLAMP model and estimates latent-variable activities (B) for a new expression matrix. Projection uses the same genes in the same order; when both matrices have row names, projectCLAMP() aligns the common genes automatically before solving for B.

        -

        Here we project the whole-blood expression matrix from Example 1 into the full latent-variable space learned from the pancreatic islet model in Example 3.

        -
        -islet_model_genes <- rownames(islet_fullRes$Z)
-wb_project_genes <- rownames(wb_Y_z)
-
-common_genes <- intersect(islet_model_genes, wb_project_genes)
-cat(
-    "Overlapping genes:", length(common_genes), "/", length(islet_model_genes),
-    "islet model genes",
-    sprintf("(%.1f%%)\n", 100 * length(common_genes) / length(islet_model_genes))
-)
-#> Overlapping genes: 10586 / 23039 islet model genes (45.9%)
-
-# projectCLAMP aligns common row names in the model's gene order
-wb_projected_B <- projectCLAMP(islet_fullRes, wb_Y_z)
-#> 10586 common rows found
-
-dim(wb_projected_B)
-#> [1] 22 36
-wb_projected_B[
-    seq_len(min(5, nrow(wb_projected_B))),
-    seq_len(min(5, ncol(wb_projected_B))),
-    drop = FALSE
-]
-#>          BD8001       BD8002      BD8003     BD8004       BD8005
-#> LV1  0.98521309  1.046757632  0.19772194  0.8948816  0.131300761
-#> LV2  0.01851305  0.002911559 -0.02800981  0.1362209  0.054224722
-#> LV3  0.04820368 -0.079046902 -0.22656763  0.2756472  0.076745853
-#> LV4 -0.97916755 -0.268646192 -0.77135039 -1.4454377 -0.019894025
-#> LV5 -0.06890388 -0.051123284 -0.27982148  0.1247173 -0.002581457
        -
        -
        -

        Choosing the Number of Latent Variables (CLAMP_K) -

        -

        CLAMP_K controls how many latent variables the model learns. Too few and biologically distinct signals merge; too many and noise is absorbed into spurious components. select_clamp_k() is the unified interface: it takes the SVD result, the number of samples, the SVD truncation rank, and an optional method argument, and returns a list with $clamp_k (number of LVs) and $scale (regularization scale used downstream).

        -
        -

        Elbow method (default) -

        -

        The elbow heuristic fits a smoothing spline to the singular-value scree plot and returns the index at which curvature is maximised. This is the fastest option and works well when the signal-to-noise boundary is clear.

        -
        -select_clamp_k(
-  wb_svd,
-  n_samples = ncol(wb_Y_z),
-  svd_k     = wb_svd_k,
-  method    = "elbow"
-)
-#> [1] 8
        -
        -
        -

        Permutation method -

        -

        The permutation approach shuffles each row of the input matrix independently B times and recomputes the SVD to build a null distribution of singular values. The number of components whose observed singular value exceeds the 95th percentile of the null is returned. This is more conservative and slower, but robust to smooth scree plots.

        -
        -select_clamp_k(
-  wb_svd,
-  n_samples = ncol(wb_Y_z),
-  svd_k     = wb_svd_k,
-  method    = "permutation",
-  data      = wb_Y_z,
-  B         = 2
-)
        -
        -
        -

        Gavish–Donoho optimal hard threshold (PCAtools) -

        -

        The Gavish–Donoho threshold (Gavish & Donoho, 2014) identifies the singular-value cutoff below which components are statistically indistinguishable from noise, given matrix dimensions and an estimate of the noise level. PCAtools implements this via chooseGavishDonoho().

        -
        -select_clamp_k(
-  wb_svd,
-  n_samples = ncol(wb_Y_z),
-  svd_k     = wb_svd_k,
-  method    = "gavish_donoho",
-  data      = wb_Y_z
-)
        -
        -
        -
        -

        Visualization -

        -

        CLAMP provides dedicated plotting functions built on ggplot2, prefixed CLAMPplot or CLAMPdotplot. The examples below use the whole-blood result wb_fullRes computed in Example 1.

        -
        -

        Pathway–LV association heatmap (CLAMPplotU) -

        -

        CLAMPplotU displays the pathway loading matrix U after filtering by AUC and FDR. Only the top-top pathways per LV are shown, making it easy to scan which pathways drive each latent variable.

        -
        -CLAMPplotU(
-  wb_fullRes,
-  auc.cutoff = 0.6,
-  fdr.cutoff = 0.05,
-  top        = 3
-)
        -

        -
        -
        -

        Top-gene loading plot (CLAMPplotTopZ) -

        -

        CLAMPplotTopZ ranks genes by their Z loading for each selected LV and plots the top genes as loading-versus-rank scatter plots. The highest-loading genes are labelled directly.

        -
        -# Use the first few LVs that have pathway support
-lv_with_paths <- wb_fullRes$withPrior[seq_len(min(4, length(wb_fullRes$withPrior)))]
-
-CLAMPplotTopZ(
-  wb_fullRes,
-  top       = 50,
-  label.top = 10,
-  index     = lv_with_paths
-)
        -

        -

        Only one LV:

        -
        -# Use the first few LVs that have pathway support
-lv_with_paths <- wb_fullRes$withPrior[1]
-
-CLAMPplotTopZ(
-  wb_fullRes,
-  top       = 50,
-  label.top = 10,
-  index     = lv_with_paths
-)
        -

        ## Single-LV pathway dot plot (CLAMPdotplot)

        -

        CLAMPdotplot shows the top pathways for one selected LV as a lollipop chart. Dot size encodes AUC; dot colour encodes -log10(FDR). Use x.axis and order.by to choose whether the x-axis and pathway ranking use AUC or -log10(FDR).

        -

        Plot order by AUC:

        -
        -CLAMPdotplot(
-  wb_fullRes,
-  lv         = 'LV2',
-  top        = 15,
-  auc.cutoff = 0.6,
-  fdr.cutoff = 0.1,
-  x.axis     = "AUC",
-  order.by   = "AUC"
-)
        -

        -

        Plot order by FDR:

        -
        -CLAMPdotplot(
-  wb_fullRes,
-  lv         = 'LV2',
-  top        = 15,
-  auc.cutoff = 0.6,
-  fdr.cutoff = 0.1,
-  x.axis     = "-log10(FDR)",
-  order.by   = "-log10(FDR)"
-)
        -

        -
        -
        -

        All-LV pathway dot plot (CLAMPdotplotAll) -

        -

        CLAMPdotplotAll gives a compact overview of all significant pathway–LV associations across every latent variable. Dot size encodes AUC and dot colour encodes -log10(FDR).

        -
        -CLAMPdotplotAll(
-  wb_fullRes,
-  auc.cutoff = 0.65,
-  fdr.cutoff = 0.05,
-  top.per.lv = 5
-)
        -

        -
        -
        -
        -

        Parallelization in CLAMP -

        -

        CLAMP supports multi-core parallelization for computationally intensive operations, particularly when working with large datasets and file-backed matrices (FBMs). The ncores parameter can be used in several key functions to speed up processing.

        -

        The following CLAMP functions accept an ncores parameter:

        - -
        -
        -

        Session Information -

        -
        -sessionInfo()
-#> R Under development (unstable) (2026-02-02 r89367)
-#> Platform: x86_64-pc-linux-gnu
-#> Running under: Pop!_OS 22.04 LTS
-#> 
-#> Matrix products: default
-#> BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so;  LAPACK version 3.10.0
-#> 
-#> locale:
-#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
-#>  [3] LC_TIME=es_ES.UTF-8        LC_COLLATE=en_US.UTF-8    
-#>  [5] LC_MONETARY=es_ES.UTF-8    LC_MESSAGES=en_US.UTF-8   
-#>  [7] LC_PAPER=es_ES.UTF-8       LC_NAME=C                 
-#>  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
-#> [11] LC_MEASUREMENT=es_ES.UTF-8 LC_IDENTIFICATION=C       
-#> 
-#> time zone: America/Denver
-#> tzcode source: system (glibc)
-#> 
-#> attached base packages:
-#> [1] stats4    stats     graphics  grDevices utils     datasets  methods  
-#> [8] base     
-#> 
-#> other attached packages:
-#>  [1] DiagrammeR_1.0.11    DT_0.34.0            org.Hs.eg.db_3.22.0 
-#>  [4] AnnotationDbi_1.73.0 IRanges_2.45.0       S4Vectors_0.49.0    
-#>  [7] Biobase_2.71.0       BiocGenerics_0.57.0  generics_0.1.4      
-#> [10] here_1.0.2           bigstatsr_1.6.2      data.table_1.18.2.1 
-#> [13] hdf5r_1.3.12         glmnet_4.1-10        Matrix_1.7-4        
-#> [16] rsvd_1.0.5           CLAMPData_0.99.2     CLAMP_0.99.0        
-#> [19] dplyr_1.2.0          BiocStyle_2.39.0    
-#> 
-#> loaded via a namespace (and not attached):
-#>   [1] DBI_1.2.3             httr2_1.2.2           rlang_1.1.7          
-#>   [4] magrittr_2.0.4        clue_0.3-66           GetoptLong_1.1.0     
-#>   [7] otel_0.2.0            matrixStats_1.5.0     compiler_4.6.0       
-#>  [10] RSQLite_2.4.5         png_0.1-8             systemfonts_1.3.1    
-#>  [13] vctrs_0.7.1           pkgconfig_2.0.3       shape_1.4.6.1        
-#>  [16] crayon_1.5.3          fastmap_1.2.0         dbplyr_2.5.1         
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-#>  [22] ps_1.9.1              ragg_1.5.0            purrr_1.2.1          
-#>  [25] bit_4.6.0             xfun_0.56             cachem_1.1.0         
-#>  [28] rmio_0.4.0            jsonlite_2.0.0        blob_1.3.0           
-#>  [31] irlba_2.3.7           parallel_4.6.0        cluster_2.1.8.1      
-#>  [34] R6_2.6.1              bslib_0.10.0          RColorBrewer_1.1-3   
-#>  [37] jquerylib_0.1.4       Rcpp_1.1.1            Seqinfo_1.1.0        
-#>  [40] bookdown_0.46         iterators_1.0.14      knitr_1.51           
-#>  [43] splines_4.6.0         tidyselect_1.2.1      rstudioapi_0.18.0    
-#>  [46] yaml_2.3.12           doParallel_1.0.17     codetools_0.2-20     
-#>  [49] curl_7.0.0            lattice_0.22-7        tibble_3.3.1         
-#>  [52] withr_3.0.2           KEGGREST_1.51.1       S7_0.2.1             
-#>  [55] evaluate_1.0.5        desc_1.4.3            survival_3.8-6       
-#>  [58] BiocFileCache_3.1.0   ExperimentHub_3.1.0   circlize_0.4.17      
-#>  [61] Biostrings_2.79.4     filelock_1.0.3        pillar_1.11.1        
-#>  [64] BiocManager_1.30.27   foreach_1.5.2         bigassertr_0.1.7     
-#>  [67] rprojroot_2.1.1       BiocVersion_3.23.1    ggplot2_4.0.2        
-#>  [70] scales_1.4.0          ff_4.5.2              glue_1.8.0           
-#>  [73] tools_4.6.0           AnnotationHub_4.1.0   RSpectra_0.16-2      
-#>  [76] visNetwork_2.1.4      fs_1.6.6              cowplot_1.2.0        
-#>  [79] grid_4.6.0            crosstalk_1.2.2       colorspace_2.1-2     
-#>  [82] patchwork_1.3.2       flock_0.7             cli_3.6.5            
-#>  [85] rappdirs_0.3.4        textshaping_1.0.4     bigparallelr_0.3.2   
-#>  [88] ComplexHeatmap_2.27.1 gtable_0.3.6          sass_0.4.10          
-#>  [91] digest_0.6.39         ggrepel_0.9.6         rjson_0.2.23         
-#>  [94] htmlwidgets_1.6.4     farver_2.1.2          memoise_2.0.1        
-#>  [97] htmltools_0.5.9       pkgdown_2.2.0         lifecycle_1.0.5      
-#> [100] httr_1.4.7            GlobalOptions_0.1.3   bit64_4.6.0-1
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        Developed by Marc Subirana-Granes, Maria Chikina.

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        Site built with pkgdown 2.2.0.

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        - - - - - - - diff --git a/docs/articles/get_started_files/DiagrammeR-styles-0.2/styles.css b/docs/articles/get_started_files/DiagrammeR-styles-0.2/styles.css deleted file mode 100644 index d6446ab..0000000 --- a/docs/articles/get_started_files/DiagrammeR-styles-0.2/styles.css +++ /dev/null @@ -1,14 +0,0 @@ -.DiagrammeR,.grViz pre { - white-space: pre-wrap; /* CSS 3 */ - white-space: -moz-pre-wrap; /* Mozilla, since 1999 */ - white-space: -pre-wrap; /* Opera 4-6 */ - white-space: -o-pre-wrap; /* Opera 7 */ - word-wrap: break-word; /* Internet Explorer 5.5+ */ -} - -.DiagrammeR g .label { - font-family: Helvetica; - font-size: 14px; - color: #333333; -} - diff --git a/docs/articles/get_started_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/articles/get_started_files/accessible-code-block-0.0.1/empty-anchor.js deleted file mode 100644 index ca349fd..0000000 --- a/docs/articles/get_started_files/accessible-code-block-0.0.1/empty-anchor.js +++ /dev/null @@ -1,15 +0,0 @@ -// Hide empty tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) --> -// v0.0.1 -// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020. - -document.addEventListener('DOMContentLoaded', function() { - const codeList = document.getElementsByClassName("sourceCode"); - for (var i = 0; i < codeList.length; i++) { - var linkList = codeList[i].getElementsByTagName('a'); - for (var j = 0; j < linkList.length; j++) { - if (linkList[j].innerHTML === "") { - linkList[j].setAttribute('aria-hidden', 'true'); - } - } - } -}); diff --git a/docs/articles/get_started_files/crosstalk-1.2.1/css/crosstalk.min.css b/docs/articles/get_started_files/crosstalk-1.2.1/css/crosstalk.min.css deleted file mode 100644 index 6b45382..0000000 --- a/docs/articles/get_started_files/crosstalk-1.2.1/css/crosstalk.min.css +++ /dev/null @@ -1 +0,0 @@ -.container-fluid.crosstalk-bscols{margin-left:-30px;margin-right:-30px;white-space:normal}body>.container-fluid.crosstalk-bscols{margin-left:auto;margin-right:auto}.crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column{display:inline-block;padding-right:12px;vertical-align:top}@media only screen and (max-width: 480px){.crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column{display:block;padding-right:inherit}}.crosstalk-input{margin-bottom:15px}.crosstalk-input .control-label{margin-bottom:0;vertical-align:middle}.crosstalk-input input[type="checkbox"]{margin:4px 0 0;margin-top:1px;line-height:normal}.crosstalk-input .checkbox{position:relative;display:block;margin-top:10px;margin-bottom:10px}.crosstalk-input .checkbox>label{padding-left:20px;margin-bottom:0;font-weight:400;cursor:pointer}.crosstalk-input .checkbox input[type="checkbox"],.crosstalk-input .checkbox-inline input[type="checkbox"]{position:absolute;margin-top:2px;margin-left:-20px}.crosstalk-input .checkbox+.checkbox{margin-top:-5px}.crosstalk-input .checkbox-inline{position:relative;display:inline-block;padding-left:20px;margin-bottom:0;font-weight:400;vertical-align:middle;cursor:pointer}.crosstalk-input .checkbox-inline+.checkbox-inline{margin-top:0;margin-left:10px} diff --git a/docs/articles/get_started_files/crosstalk-1.2.1/js/crosstalk.js b/docs/articles/get_started_files/crosstalk-1.2.1/js/crosstalk.js deleted file mode 100644 index fd9eb53..0000000 --- a/docs/articles/get_started_files/crosstalk-1.2.1/js/crosstalk.js +++ /dev/null @@ -1,1474 +0,0 @@ -(function(){function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require=="function"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);var f=new Error("Cannot find module '"+o+"'");throw f.code="MODULE_NOT_FOUND",f}var l=n[o]={exports:{}};t[o][0].call(l.exports,function(e){var n=t[o][1][e];return s(n?n:e)},l,l.exports,e,t,n,r)}return n[o].exports}var i=typeof require=="function"&&require;for(var o=0;o b) { - return 1; - } -} - -/** - * @private - */ - -var FilterSet = function () { - function FilterSet() { - _classCallCheck(this, FilterSet); - - this.reset(); - } - - _createClass(FilterSet, [{ - key: "reset", - value: function reset() { - // Key: handle ID, Value: array of selected keys, or null - this._handles = {}; - // Key: key string, Value: count of handles that include it - this._keys = {}; - this._value = null; - this._activeHandles = 0; - } - }, { - key: "update", - value: function update(handleId, keys) { - if (keys !== null) { - keys = keys.slice(0); // clone before sorting - keys.sort(naturalComparator); - } - - var _diffSortedLists = (0, _util.diffSortedLists)(this._handles[handleId], keys), - added = _diffSortedLists.added, - removed = _diffSortedLists.removed; - - this._handles[handleId] = keys; - - for (var i = 0; i < added.length; i++) { - this._keys[added[i]] = (this._keys[added[i]] || 0) + 1; - } - for (var _i = 0; _i < removed.length; _i++) { - this._keys[removed[_i]]--; - } - - this._updateValue(keys); - } - - /** - * @param {string[]} keys Sorted array of strings that indicate - * a superset of possible keys. - * @private - */ - - }, { - key: "_updateValue", - value: function _updateValue() { - var keys = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : this._allKeys; - - var handleCount = Object.keys(this._handles).length; - if (handleCount === 0) { - this._value = null; - } else { - this._value = []; - for (var i = 0; i < keys.length; i++) { - var count = this._keys[keys[i]]; - if (count === handleCount) { - this._value.push(keys[i]); - } - } - } - } - }, { - key: "clear", - value: function clear(handleId) { - if (typeof this._handles[handleId] === "undefined") { - return; - } - - var keys = this._handles[handleId]; - if (!keys) { - keys = []; - } - - for (var i = 0; i < keys.length; i++) { - this._keys[keys[i]]--; - } - delete this._handles[handleId]; - - this._updateValue(); - } - }, { - key: "value", - get: function get() { - return this._value; - } - }, { - key: "_allKeys", - get: function get() { - var allKeys = Object.keys(this._keys); - allKeys.sort(naturalComparator); - return allKeys; - } - }]); - - return FilterSet; -}(); - -exports.default = FilterSet; - -},{"./util":11}],4:[function(require,module,exports){ -(function (global){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); - -var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }(); - -var _typeof = typeof Symbol === "function" && typeof Symbol.iterator === "symbol" ? function (obj) { return typeof obj; } : function (obj) { return obj && typeof Symbol === "function" && obj.constructor === Symbol && obj !== Symbol.prototype ? "symbol" : typeof obj; }; - -exports.default = group; - -var _var2 = require("./var"); - -var _var3 = _interopRequireDefault(_var2); - -function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } - -function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } - -// Use a global so that multiple copies of crosstalk.js can be loaded and still -// have groups behave as singletons across all copies. -global.__crosstalk_groups = global.__crosstalk_groups || {}; -var groups = global.__crosstalk_groups; - -function group(groupName) { - if (groupName && typeof groupName === "string") { - if (!groups.hasOwnProperty(groupName)) { - groups[groupName] = new Group(groupName); - } - return groups[groupName]; - } else if ((typeof groupName === "undefined" ? "undefined" : _typeof(groupName)) === "object" && groupName._vars && groupName.var) { - // Appears to already be a group object - return groupName; - } else if (Array.isArray(groupName) && groupName.length == 1 && typeof groupName[0] === "string") { - return group(groupName[0]); - } else { - throw new Error("Invalid groupName argument"); - } -} - -var Group = function () { - function Group(name) { - _classCallCheck(this, Group); - - this.name = name; - this._vars = {}; - } - - _createClass(Group, [{ - key: "var", - value: function _var(name) { - if (!name || typeof name !== "string") { - throw new Error("Invalid var name"); - } - - if (!this._vars.hasOwnProperty(name)) this._vars[name] = new _var3.default(this, name); - return this._vars[name]; - } - }, { - key: "has", - value: function has(name) { - if (!name || typeof name !== "string") { - throw new Error("Invalid var name"); - } - - return this._vars.hasOwnProperty(name); - } - }]); - - return Group; -}(); - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./var":12}],5:[function(require,module,exports){ -(function (global){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); - -var _group = require("./group"); - -var _group2 = _interopRequireDefault(_group); - -var _selection = require("./selection"); - -var _filter = require("./filter"); - -var _input = require("./input"); - -require("./input_selectize"); - -require("./input_checkboxgroup"); - -require("./input_slider"); - -function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } - -var defaultGroup = (0, _group2.default)("default"); - -function var_(name) { - return defaultGroup.var(name); -} - -function has(name) { - return defaultGroup.has(name); -} - -if (global.Shiny) { - global.Shiny.addCustomMessageHandler("update-client-value", function (message) { - if (typeof message.group === "string") { - (0, _group2.default)(message.group).var(message.name).set(message.value); - } else { - var_(message.name).set(message.value); - } - }); -} - -var crosstalk = { - group: _group2.default, - var: var_, - has: has, - SelectionHandle: _selection.SelectionHandle, - FilterHandle: _filter.FilterHandle, - bind: _input.bind -}; - -/** - * @namespace crosstalk - */ -exports.default = crosstalk; - -global.crosstalk = crosstalk; - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./filter":2,"./group":4,"./input":6,"./input_checkboxgroup":7,"./input_selectize":8,"./input_slider":9,"./selection":10}],6:[function(require,module,exports){ -(function (global){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); -exports.register = register; -exports.bind = bind; -var $ = global.jQuery; - -var bindings = {}; - -function register(reg) { - bindings[reg.className] = reg; - if (global.document && global.document.readyState !== "complete") { - $(function () { - bind(); - }); - } else if (global.document) { - setTimeout(bind, 100); - } -} - -function bind() { - Object.keys(bindings).forEach(function (className) { - var binding = bindings[className]; - $("." + binding.className).not(".crosstalk-input-bound").each(function (i, el) { - bindInstance(binding, el); - }); - }); -} - -// Escape jQuery identifier -function $escape(val) { - return val.replace(/([!"#$%&'()*+,./:;<=>?@[\\\]^`{|}~])/g, "\\$1"); -} - -function bindEl(el) { - var $el = $(el); - Object.keys(bindings).forEach(function (className) { - if ($el.hasClass(className) && !$el.hasClass("crosstalk-input-bound")) { - var binding = bindings[className]; - bindInstance(binding, el); - } - }); -} - -function bindInstance(binding, el) { - var jsonEl = $(el).find("script[type='application/json'][data-for='" + $escape(el.id) + "']"); - var data = JSON.parse(jsonEl[0].innerText); - - var instance = binding.factory(el, data); - $(el).data("crosstalk-instance", instance); - $(el).addClass("crosstalk-input-bound"); -} - -if (global.Shiny) { - var inputBinding = new global.Shiny.InputBinding(); - var _$ = global.jQuery; - _$.extend(inputBinding, { - find: function find(scope) { - return _$(scope).find(".crosstalk-input"); - }, - initialize: function initialize(el) { - if (!_$(el).hasClass("crosstalk-input-bound")) { - bindEl(el); - } - }, - getId: function getId(el) { - return el.id; - }, - getValue: function getValue(el) {}, - setValue: function setValue(el, value) {}, - receiveMessage: function receiveMessage(el, data) {}, - subscribe: function subscribe(el, callback) { - _$(el).data("crosstalk-instance").resume(); - }, - unsubscribe: function unsubscribe(el) { - _$(el).data("crosstalk-instance").suspend(); - } - }); - global.Shiny.inputBindings.register(inputBinding, "crosstalk.inputBinding"); -} - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{}],7:[function(require,module,exports){ -(function (global){ -"use strict"; - -var _input = require("./input"); - -var input = _interopRequireWildcard(_input); - -var _filter = require("./filter"); - -function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } } - -var $ = global.jQuery; - -input.register({ - className: "crosstalk-input-checkboxgroup", - - factory: function factory(el, data) { - /* - * map: {"groupA": ["keyA", "keyB", ...], ...} - * group: "ct-groupname" - */ - var ctHandle = new _filter.FilterHandle(data.group); - - var lastKnownKeys = void 0; - var $el = $(el); - $el.on("change", "input[type='checkbox']", function () { - var checked = $el.find("input[type='checkbox']:checked"); - if (checked.length === 0) { - lastKnownKeys = null; - ctHandle.clear(); - } else { - var keys = {}; - checked.each(function () { - data.map[this.value].forEach(function (key) { - keys[key] = true; - }); - }); - var keyArray = Object.keys(keys); - keyArray.sort(); - lastKnownKeys = keyArray; - ctHandle.set(keyArray); - } - }); - - return { - suspend: function suspend() { - ctHandle.clear(); - }, - resume: function resume() { - if (lastKnownKeys) ctHandle.set(lastKnownKeys); - } - }; - } -}); - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./filter":2,"./input":6}],8:[function(require,module,exports){ -(function (global){ -"use strict"; - -var _input = require("./input"); - -var input = _interopRequireWildcard(_input); - -var _util = require("./util"); - -var util = _interopRequireWildcard(_util); - -var _filter = require("./filter"); - -function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } } - -var $ = global.jQuery; - -input.register({ - className: "crosstalk-input-select", - - factory: function factory(el, data) { - /* - * items: {value: [...], label: [...]} - * map: {"groupA": ["keyA", "keyB", ...], ...} - * group: "ct-groupname" - */ - - var first = [{ value: "", label: "(All)" }]; - var items = util.dataframeToD3(data.items); - var opts = { - options: first.concat(items), - valueField: "value", - labelField: "label", - searchField: "label" - }; - - var select = $(el).find("select")[0]; - - var selectize = $(select).selectize(opts)[0].selectize; - - var ctHandle = new _filter.FilterHandle(data.group); - - var lastKnownKeys = void 0; - selectize.on("change", function () { - if (selectize.items.length === 0) { - lastKnownKeys = null; - ctHandle.clear(); - } else { - var keys = {}; - selectize.items.forEach(function (group) { - data.map[group].forEach(function (key) { - keys[key] = true; - }); - }); - var keyArray = Object.keys(keys); - keyArray.sort(); - lastKnownKeys = keyArray; - ctHandle.set(keyArray); - } - }); - - return { - suspend: function suspend() { - ctHandle.clear(); - }, - resume: function resume() { - if (lastKnownKeys) ctHandle.set(lastKnownKeys); - } - }; - } -}); - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./filter":2,"./input":6,"./util":11}],9:[function(require,module,exports){ -(function (global){ -"use strict"; - -var _slicedToArray = function () { function sliceIterator(arr, i) { var _arr = []; var _n = true; var _d = false; var _e = undefined; try { for (var _i = arr[Symbol.iterator](), _s; !(_n = (_s = _i.next()).done); _n = true) { _arr.push(_s.value); if (i && _arr.length === i) break; } } catch (err) { _d = true; _e = err; } finally { try { if (!_n && _i["return"]) _i["return"](); } finally { if (_d) throw _e; } } return _arr; } return function (arr, i) { if (Array.isArray(arr)) { return arr; } else if (Symbol.iterator in Object(arr)) { return sliceIterator(arr, i); } else { throw new TypeError("Invalid attempt to destructure non-iterable instance"); } }; }(); - -var _input = require("./input"); - -var input = _interopRequireWildcard(_input); - -var _filter = require("./filter"); - -function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } } - -var $ = global.jQuery; -var strftime = global.strftime; - -input.register({ - className: "crosstalk-input-slider", - - factory: function factory(el, data) { - /* - * map: {"groupA": ["keyA", "keyB", ...], ...} - * group: "ct-groupname" - */ - var ctHandle = new _filter.FilterHandle(data.group); - - var opts = {}; - var $el = $(el).find("input"); - var dataType = $el.data("data-type"); - var timeFormat = $el.data("time-format"); - var round = $el.data("round"); - var timeFormatter = void 0; - - // Set up formatting functions - if (dataType === "date") { - timeFormatter = strftime.utc(); - opts.prettify = function (num) { - return timeFormatter(timeFormat, new Date(num)); - }; - } else if (dataType === "datetime") { - var timezone = $el.data("timezone"); - if (timezone) timeFormatter = strftime.timezone(timezone);else timeFormatter = strftime; - - opts.prettify = function (num) { - return timeFormatter(timeFormat, new Date(num)); - }; - } else if (dataType === "number") { - if (typeof round !== "undefined") opts.prettify = function (num) { - var factor = Math.pow(10, round); - return Math.round(num * factor) / factor; - }; - } - - $el.ionRangeSlider(opts); - - function getValue() { - var result = $el.data("ionRangeSlider").result; - - // Function for converting numeric value from slider to appropriate type. - var convert = void 0; - var dataType = $el.data("data-type"); - if (dataType === "date") { - convert = function convert(val) { - return formatDateUTC(new Date(+val)); - }; - } else if (dataType === "datetime") { - convert = function convert(val) { - // Convert ms to s - return +val / 1000; - }; - } else { - convert = function convert(val) { - return +val; - }; - } - - if ($el.data("ionRangeSlider").options.type === "double") { - return [convert(result.from), convert(result.to)]; - } else { - return convert(result.from); - } - } - - var lastKnownKeys = null; - - $el.on("change.crosstalkSliderInput", function (event) { - if (!$el.data("updating") && !$el.data("animating")) { - var _getValue = getValue(), - _getValue2 = _slicedToArray(_getValue, 2), - from = _getValue2[0], - to = _getValue2[1]; - - var keys = []; - for (var i = 0; i < data.values.length; i++) { - var val = data.values[i]; - if (val >= from && val <= to) { - keys.push(data.keys[i]); - } - } - keys.sort(); - ctHandle.set(keys); - lastKnownKeys = keys; - } - }); - - // let $el = $(el); - // $el.on("change", "input[type="checkbox"]", function() { - // let checked = $el.find("input[type="checkbox"]:checked"); - // if (checked.length === 0) { - // ctHandle.clear(); - // } else { - // let keys = {}; - // checked.each(function() { - // data.map[this.value].forEach(function(key) { - // keys[key] = true; - // }); - // }); - // let keyArray = Object.keys(keys); - // keyArray.sort(); - // ctHandle.set(keyArray); - // } - // }); - - return { - suspend: function suspend() { - ctHandle.clear(); - }, - resume: function resume() { - if (lastKnownKeys) ctHandle.set(lastKnownKeys); - } - }; - } -}); - -// Convert a number to a string with leading zeros -function padZeros(n, digits) { - var str = n.toString(); - while (str.length < digits) { - str = "0" + str; - }return str; -} - -// Given a Date object, return a string in yyyy-mm-dd format, using the -// UTC date. This may be a day off from the date in the local time zone. -function formatDateUTC(date) { - if (date instanceof Date) { - return date.getUTCFullYear() + "-" + padZeros(date.getUTCMonth() + 1, 2) + "-" + padZeros(date.getUTCDate(), 2); - } else { - return null; - } -} - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./filter":2,"./input":6}],10:[function(require,module,exports){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); -exports.SelectionHandle = undefined; - -var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }(); - -var _events = require("./events"); - -var _events2 = _interopRequireDefault(_events); - -var _group = require("./group"); - -var _group2 = _interopRequireDefault(_group); - -var _util = require("./util"); - -var util = _interopRequireWildcard(_util); - -function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } } - -function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } - -function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } - -/** - * Use this class to read and write (and listen for changes to) the selection - * for a Crosstalk group. This is intended to be used for linked brushing. - * - * If two (or more) `SelectionHandle` instances in the same webpage share the - * same group name, they will share the same state. Setting the selection using - * one `SelectionHandle` instance will result in the `value` property instantly - * changing across the others, and `"change"` event listeners on all instances - * (including the one that initiated the sending) will fire. - * - * @param {string} [group] - The name of the Crosstalk group, or if none, - * null or undefined (or any other falsy value). This can be changed later - * via the [SelectionHandle#setGroup](#setGroup) method. - * @param {Object} [extraInfo] - An object whose properties will be copied to - * the event object whenever an event is emitted. - */ -var SelectionHandle = exports.SelectionHandle = function () { - function SelectionHandle() { - var group = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : null; - var extraInfo = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : null; - - _classCallCheck(this, SelectionHandle); - - this._eventRelay = new _events2.default(); - this._emitter = new util.SubscriptionTracker(this._eventRelay); - - // Name of the group we're currently tracking, if any. Can change over time. - this._group = null; - // The Var we're currently tracking, if any. Can change over time. - this._var = null; - // The event handler subscription we currently have on var.on("change"). - this._varOnChangeSub = null; - - this._extraInfo = util.extend({ sender: this }, extraInfo); - - this.setGroup(group); - } - - /** - * Changes the Crosstalk group membership of this SelectionHandle. The group - * being switched away from (if any) will not have its selection value - * modified as a result of calling `setGroup`, even if this handle was the - * most recent handle to set the selection of the group. - * - * The group being switched to (if any) will also not have its selection value - * modified as a result of calling `setGroup`. If you want to set the - * selection value of the new group, call `set` explicitly. - * - * @param {string} group - The name of the Crosstalk group, or null (or - * undefined) to clear the group. - */ - - - _createClass(SelectionHandle, [{ - key: "setGroup", - value: function setGroup(group) { - var _this = this; - - // If group is unchanged, do nothing - if (this._group === group) return; - // Treat null, undefined, and other falsy values the same - if (!this._group && !group) return; - - if (this._var) { - this._var.off("change", this._varOnChangeSub); - this._var = null; - this._varOnChangeSub = null; - } - - this._group = group; - - if (group) { - this._var = (0, _group2.default)(group).var("selection"); - var sub = this._var.on("change", function (e) { - _this._eventRelay.trigger("change", e, _this); - }); - this._varOnChangeSub = sub; - } - } - - /** - * Retrieves the current selection for the group represented by this - * `SelectionHandle`. - * - * - If no selection is active, then this value will be falsy. - * - If a selection is active, but no data points are selected, then this - * value will be an empty array. - * - If a selection is active, and data points are selected, then the keys - * of the selected data points will be present in the array. - */ - - }, { - key: "_mergeExtraInfo", - - - /** - * Combines the given `extraInfo` (if any) with the handle's default - * `_extraInfo` (if any). - * @private - */ - value: function _mergeExtraInfo(extraInfo) { - // Important incidental effect: shallow clone is returned - return util.extend({}, this._extraInfo ? this._extraInfo : null, extraInfo ? extraInfo : null); - } - - /** - * Overwrites the current selection for the group, and raises the `"change"` - * event among all of the group's '`SelectionHandle` instances (including - * this one). - * - * @fires SelectionHandle#change - * @param {string[]} selectedKeys - Falsy, empty array, or array of keys (see - * {@link SelectionHandle#value}). - * @param {Object} [extraInfo] - Extra properties to be included on the event - * object that's passed to listeners (in addition to any options that were - * passed into the `SelectionHandle` constructor). - */ - - }, { - key: "set", - value: function set(selectedKeys, extraInfo) { - if (this._var) this._var.set(selectedKeys, this._mergeExtraInfo(extraInfo)); - } - - /** - * Overwrites the current selection for the group, and raises the `"change"` - * event among all of the group's '`SelectionHandle` instances (including - * this one). - * - * @fires SelectionHandle#change - * @param {Object} [extraInfo] - Extra properties to be included on the event - * object that's passed to listeners (in addition to any that were passed - * into the `SelectionHandle` constructor). - */ - - }, { - key: "clear", - value: function clear(extraInfo) { - if (this._var) this.set(void 0, this._mergeExtraInfo(extraInfo)); - } - - /** - * Subscribes to events on this `SelectionHandle`. - * - * @param {string} eventType - Indicates the type of events to listen to. - * Currently, only `"change"` is supported. - * @param {SelectionHandle~listener} listener - The callback function that - * will be invoked when the event occurs. - * @return {string} - A token to pass to {@link SelectionHandle#off} to cancel - * this subscription. - */ - - }, { - key: "on", - value: function on(eventType, listener) { - return this._emitter.on(eventType, listener); - } - - /** - * Cancels event subscriptions created by {@link SelectionHandle#on}. - * - * @param {string} eventType - The type of event to unsubscribe. - * @param {string|SelectionHandle~listener} listener - Either the callback - * function previously passed into {@link SelectionHandle#on}, or the - * string that was returned from {@link SelectionHandle#on}. - */ - - }, { - key: "off", - value: function off(eventType, listener) { - return this._emitter.off(eventType, listener); - } - - /** - * Shuts down the `SelectionHandle` object. - * - * Removes all event listeners that were added through this handle. - */ - - }, { - key: "close", - value: function close() { - this._emitter.removeAllListeners(); - this.setGroup(null); - } - }, { - key: "value", - get: function get() { - return this._var ? this._var.get() : null; - } - }]); - - return SelectionHandle; -}(); - -/** - * @callback SelectionHandle~listener - * @param {Object} event - An object containing details of the event. For - * `"change"` events, this includes the properties `value` (the new - * value of the selection, or `undefined` if no selection is active), - * `oldValue` (the previous value of the selection), and `sender` (the - * `SelectionHandle` instance that made the change). - */ - -/** - * @event SelectionHandle#change - * @type {object} - * @property {object} value - The new value of the selection, or `undefined` - * if no selection is active. - * @property {object} oldValue - The previous value of the selection. - * @property {SelectionHandle} sender - The `SelectionHandle` instance that - * changed the value. - */ - -},{"./events":1,"./group":4,"./util":11}],11:[function(require,module,exports){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); - -var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }(); - -var _typeof = typeof Symbol === "function" && typeof Symbol.iterator === "symbol" ? function (obj) { return typeof obj; } : function (obj) { return obj && typeof Symbol === "function" && obj.constructor === Symbol && obj !== Symbol.prototype ? "symbol" : typeof obj; }; - -exports.extend = extend; -exports.checkSorted = checkSorted; -exports.diffSortedLists = diffSortedLists; -exports.dataframeToD3 = dataframeToD3; - -function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } - -function extend(target) { - for (var _len = arguments.length, sources = Array(_len > 1 ? _len - 1 : 0), _key = 1; _key < _len; _key++) { - sources[_key - 1] = arguments[_key]; - } - - for (var i = 0; i < sources.length; i++) { - var src = sources[i]; - if (typeof src === "undefined" || src === null) continue; - - for (var key in src) { - if (src.hasOwnProperty(key)) { - target[key] = src[key]; - } - } - } - return target; -} - -function checkSorted(list) { - for (var i = 1; i < list.length; i++) { - if (list[i] <= list[i - 1]) { - throw new Error("List is not sorted or contains duplicate"); - } - } -} - -function diffSortedLists(a, b) { - var i_a = 0; - var i_b = 0; - - if (!a) a = []; - if (!b) b = []; - - var a_only = []; - var b_only = []; - - checkSorted(a); - checkSorted(b); - - while (i_a < a.length && i_b < b.length) { - if (a[i_a] === b[i_b]) { - i_a++; - i_b++; - } else if (a[i_a] < b[i_b]) { - a_only.push(a[i_a++]); - } else { - b_only.push(b[i_b++]); - } - } - - if (i_a < a.length) a_only = a_only.concat(a.slice(i_a)); - if (i_b < b.length) b_only = b_only.concat(b.slice(i_b)); - return { - removed: a_only, - added: b_only - }; -} - -// Convert from wide: { colA: [1,2,3], colB: [4,5,6], ... } -// to long: [ {colA: 1, colB: 4}, {colA: 2, colB: 5}, ... ] -function dataframeToD3(df) { - var names = []; - var length = void 0; - for (var name in df) { - if (df.hasOwnProperty(name)) names.push(name); - if (_typeof(df[name]) !== "object" || typeof df[name].length === "undefined") { - throw new Error("All fields must be arrays"); - } else if (typeof length !== "undefined" && length !== df[name].length) { - throw new Error("All fields must be arrays of the same length"); - } - length = df[name].length; - } - var results = []; - var item = void 0; - for (var row = 0; row < length; row++) { - item = {}; - for (var col = 0; col < names.length; col++) { - item[names[col]] = df[names[col]][row]; - } - results.push(item); - } - return results; -} - -/** - * Keeps track of all event listener additions/removals and lets all active - * listeners be removed with a single operation. - * - * @private - */ - -var SubscriptionTracker = exports.SubscriptionTracker = function () { - function SubscriptionTracker(emitter) { - _classCallCheck(this, SubscriptionTracker); - - this._emitter = emitter; - this._subs = {}; - } - - _createClass(SubscriptionTracker, [{ - key: "on", - value: function on(eventType, listener) { - var sub = this._emitter.on(eventType, listener); - this._subs[sub] = eventType; - return sub; - } - }, { - key: "off", - value: function off(eventType, listener) { - var sub = this._emitter.off(eventType, listener); - if (sub) { - delete this._subs[sub]; - } - return sub; - } - }, { - key: "removeAllListeners", - value: function removeAllListeners() { - var _this = this; - - var current_subs = this._subs; - this._subs = {}; - Object.keys(current_subs).forEach(function (sub) { - _this._emitter.off(current_subs[sub], sub); - }); - } - }]); - - return SubscriptionTracker; -}(); - -},{}],12:[function(require,module,exports){ -(function (global){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); - -var _typeof = typeof Symbol === "function" && typeof Symbol.iterator === "symbol" ? function (obj) { return typeof obj; } : function (obj) { return obj && typeof Symbol === "function" && obj.constructor === Symbol && obj !== Symbol.prototype ? "symbol" : typeof obj; }; - -var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }(); - -var _events = require("./events"); - -var _events2 = _interopRequireDefault(_events); - -function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } - -function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } - -var Var = function () { - function Var(group, name, /*optional*/value) { - _classCallCheck(this, Var); - - this._group = group; - this._name = name; - this._value = value; - this._events = new _events2.default(); - } - - _createClass(Var, [{ - key: "get", - value: function get() { - return this._value; - } - }, { - key: "set", - value: function set(value, /*optional*/event) { - if (this._value === value) { - // Do nothing; the value hasn't changed - return; - } - var oldValue = this._value; - this._value = value; - // Alert JavaScript listeners that the value has changed - var evt = {}; - if (event && (typeof event === "undefined" ? "undefined" : _typeof(event)) === "object") { - for (var k in event) { - if (event.hasOwnProperty(k)) evt[k] = event[k]; - } - } - evt.oldValue = oldValue; - evt.value = value; - this._events.trigger("change", evt, this); - - // TODO: Make this extensible, to let arbitrary back-ends know that - // something has changed - if (global.Shiny && global.Shiny.onInputChange) { - global.Shiny.onInputChange(".clientValue-" + (this._group.name !== null ? this._group.name + "-" : "") + this._name, typeof value === "undefined" ? null : value); - } - } - }, { - key: "on", - value: function on(eventType, listener) { - return this._events.on(eventType, listener); - } - }, { - key: "off", - value: function off(eventType, listener) { - return this._events.off(eventType, listener); - } - }]); - - return Var; -}(); - -exports.default = Var; - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./events":1}]},{},[5]) -//# sourceMappingURL=crosstalk.js.map diff --git a/docs/articles/get_started_files/crosstalk-1.2.1/js/crosstalk.js.map b/docs/articles/get_started_files/crosstalk-1.2.1/js/crosstalk.js.map deleted file mode 100644 index cff94f0..0000000 --- a/docs/articles/get_started_files/crosstalk-1.2.1/js/crosstalk.js.map +++ /dev/null @@ -1,37 +0,0 @@ -{ - "version": 3, - "sources": [ - "node_modules/browser-pack/_prelude.js", - "javascript/src/events.js", - "javascript/src/filter.js", - "javascript/src/filterset.js", - "javascript/src/group.js", - "javascript/src/index.js", - "javascript/src/input.js", - "javascript/src/input_checkboxgroup.js", - "javascript/src/input_selectize.js", - "javascript/src/input_slider.js", - "javascript/src/selection.js", - "javascript/src/util.js", - "javascript/src/var.js" - ], - "names": [], - "mappings": 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- "file": "generated.js", - "sourceRoot": "", - "sourcesContent": [ - "(function(){function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require==\"function\"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);var f=new Error(\"Cannot find module '\"+o+\"'\");throw f.code=\"MODULE_NOT_FOUND\",f}var l=n[o]={exports:{}};t[o][0].call(l.exports,function(e){var n=t[o][1][e];return s(n?n:e)},l,l.exports,e,t,n,r)}return n[o].exports}var i=typeof require==\"function\"&&require;for(var o=0;o {\n this._eventRelay.trigger(\"change\", e, this);\n });\n this._varOnChangeSub = sub;\n }\n }\n\n /**\n * Combine the given `extraInfo` (if any) with the handle's default\n * `_extraInfo` (if any).\n * @private\n */\n _mergeExtraInfo(extraInfo) {\n return util.extend({},\n this._extraInfo ? this._extraInfo : null,\n extraInfo ? extraInfo : null);\n }\n\n /**\n * Close the handle. This clears this handle's contribution to the filter set,\n * and unsubscribes all event listeners.\n */\n close() {\n this._emitter.removeAllListeners();\n this.clear();\n this.setGroup(null);\n }\n\n /**\n * Clear this handle's contribution to the filter set.\n *\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `FilterHandle` constructor).\n * \n * @fires FilterHandle#change\n */\n clear(extraInfo) {\n if (!this._filterSet)\n return;\n this._filterSet.clear(this._id);\n this._onChange(extraInfo);\n }\n\n /**\n * Set this handle's contribution to the filter set. This array should consist\n * of the keys of the rows that _should_ be displayed; any keys that are not\n * present in the array will be considered _filtered out_. Note that multiple\n * `FilterHandle` instances in the group may each contribute an array of keys,\n * and only those keys that appear in _all_ of the arrays make it through the\n * filter.\n *\n * @param {string[]} keys - Empty array, or array of keys. To clear the\n * filter, don't pass an empty array; instead, use the\n * {@link FilterHandle#clear} method.\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `FilterHandle` constructor).\n * \n * @fires FilterHandle#change\n */\n set(keys, extraInfo) {\n if (!this._filterSet)\n return;\n this._filterSet.update(this._id, keys);\n this._onChange(extraInfo);\n }\n\n /**\n * @return {string[]|null} - Either: 1) an array of keys that made it through\n * all of the `FilterHandle` instances, or, 2) `null`, which means no filter\n * is being applied (all data should be displayed).\n */\n get filteredKeys() {\n return this._filterSet ? this._filterSet.value : null;\n }\n\n /**\n * Subscribe to events on this `FilterHandle`.\n *\n * @param {string} eventType - Indicates the type of events to listen to.\n * Currently, only `\"change\"` is supported.\n * @param {FilterHandle~listener} listener - The callback function that\n * will be invoked when the event occurs.\n * @return {string} - A token to pass to {@link FilterHandle#off} to cancel\n * this subscription.\n */\n on(eventType, listener) {\n return this._emitter.on(eventType, listener);\n }\n\n /**\n * Cancel event subscriptions created by {@link FilterHandle#on}.\n *\n * @param {string} eventType - The type of event to unsubscribe.\n * @param {string|FilterHandle~listener} listener - Either the callback\n * function previously passed into {@link FilterHandle#on}, or the\n * string that was returned from {@link FilterHandle#on}.\n */\n off(eventType, listener) {\n return this._emitter.off(eventType, listener);\n }\n\n _onChange(extraInfo) {\n if (!this._filterSet)\n return;\n this._filterVar.set(this._filterSet.value, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * @callback FilterHandle~listener\n * @param {Object} event - An object containing details of the event. For\n * `\"change\"` events, this includes the properties `value` (the new\n * value of the filter set, or `null` if no filter set is active),\n * `oldValue` (the previous value of the filter set), and `sender` (the\n * `FilterHandle` instance that made the change).\n */\n\n}\n\n/**\n * @event FilterHandle#change\n * @type {object}\n * @property {object} value - The new value of the filter set, or `null`\n * if no filter set is active.\n * @property {object} oldValue - The previous value of the filter set.\n * @property {FilterHandle} sender - The `FilterHandle` instance that\n * changed the value.\n */\n", - "import { diffSortedLists } from \"./util\";\n\nfunction naturalComparator(a, b) {\n if (a === b) {\n return 0;\n } else if (a < b) {\n return -1;\n } else if (a > b) {\n return 1;\n }\n}\n\n/**\n * @private\n */\nexport default class FilterSet {\n constructor() {\n this.reset();\n }\n\n reset() {\n // Key: handle ID, Value: array of selected keys, or null\n this._handles = {};\n // Key: key string, Value: count of handles that include it\n this._keys = {};\n this._value = null;\n this._activeHandles = 0;\n }\n\n get value() {\n return this._value;\n }\n\n update(handleId, keys) {\n if (keys !== null) {\n keys = keys.slice(0); // clone before sorting\n keys.sort(naturalComparator);\n }\n\n let {added, removed} = diffSortedLists(this._handles[handleId], keys);\n this._handles[handleId] = keys;\n\n for (let i = 0; i < added.length; i++) {\n this._keys[added[i]] = (this._keys[added[i]] || 0) + 1;\n }\n for (let i = 0; i < removed.length; i++) {\n this._keys[removed[i]]--;\n }\n\n this._updateValue(keys);\n }\n\n /**\n * @param {string[]} keys Sorted array of strings that indicate\n * a superset of possible keys.\n * @private\n */\n _updateValue(keys = this._allKeys) {\n let handleCount = Object.keys(this._handles).length;\n if (handleCount === 0) {\n this._value = null;\n } else {\n this._value = [];\n for (let i = 0; i < keys.length; i++) {\n let count = this._keys[keys[i]];\n if (count === handleCount) {\n this._value.push(keys[i]);\n }\n }\n }\n }\n\n clear(handleId) {\n if (typeof(this._handles[handleId]) === \"undefined\") {\n return;\n }\n\n let keys = this._handles[handleId];\n if (!keys) {\n keys = [];\n }\n\n for (let i = 0; i < keys.length; i++) {\n this._keys[keys[i]]--;\n }\n delete this._handles[handleId];\n\n this._updateValue();\n }\n\n get _allKeys() {\n let allKeys = Object.keys(this._keys);\n allKeys.sort(naturalComparator);\n return allKeys;\n }\n}\n", - "import Var from \"./var\";\n\n// Use a global so that multiple copies of crosstalk.js can be loaded and still\n// have groups behave as singletons across all copies.\nglobal.__crosstalk_groups = global.__crosstalk_groups || {};\nlet groups = global.__crosstalk_groups;\n\nexport default function group(groupName) {\n if (groupName && typeof(groupName) === \"string\") {\n if (!groups.hasOwnProperty(groupName)) {\n groups[groupName] = new Group(groupName);\n }\n return groups[groupName];\n } else if (typeof(groupName) === \"object\" && groupName._vars && groupName.var) {\n // Appears to already be a group object\n return groupName;\n } else if (Array.isArray(groupName) &&\n groupName.length == 1 &&\n typeof(groupName[0]) === \"string\") {\n return group(groupName[0]);\n } else {\n throw new Error(\"Invalid groupName argument\");\n }\n}\n\nclass Group {\n constructor(name) {\n this.name = name;\n this._vars = {};\n }\n\n var(name) {\n if (!name || typeof(name) !== \"string\") {\n throw new Error(\"Invalid var name\");\n }\n\n if (!this._vars.hasOwnProperty(name))\n this._vars[name] = new Var(this, name);\n return this._vars[name];\n }\n\n has(name) {\n if (!name || typeof(name) !== \"string\") {\n throw new Error(\"Invalid var name\");\n }\n\n return this._vars.hasOwnProperty(name);\n }\n}\n", - "import group from \"./group\";\nimport { SelectionHandle } from \"./selection\";\nimport { FilterHandle } from \"./filter\";\nimport { bind } from \"./input\";\nimport \"./input_selectize\";\nimport \"./input_checkboxgroup\";\nimport \"./input_slider\";\n\nconst defaultGroup = group(\"default\");\n\nfunction var_(name) {\n return defaultGroup.var(name);\n}\n\nfunction has(name) {\n return defaultGroup.has(name);\n}\n\nif (global.Shiny) {\n global.Shiny.addCustomMessageHandler(\"update-client-value\", function(message) {\n if (typeof(message.group) === \"string\") {\n group(message.group).var(message.name).set(message.value);\n } else {\n var_(message.name).set(message.value);\n }\n });\n}\n\nconst crosstalk = {\n group: group,\n var: var_,\n has: has,\n SelectionHandle: SelectionHandle,\n FilterHandle: FilterHandle,\n bind: bind\n};\n\n/**\n * @namespace crosstalk\n */\nexport default crosstalk;\nglobal.crosstalk = crosstalk;\n", - "let $ = global.jQuery;\n\nlet bindings = {};\n\nexport function register(reg) {\n bindings[reg.className] = reg;\n if (global.document && global.document.readyState !== \"complete\") {\n $(() => {\n bind();\n });\n } else if (global.document) {\n setTimeout(bind, 100);\n }\n}\n\nexport function bind() {\n Object.keys(bindings).forEach(function(className) {\n let binding = bindings[className];\n $(\".\" + binding.className).not(\".crosstalk-input-bound\").each(function(i, el) {\n bindInstance(binding, el);\n });\n });\n}\n\n// Escape jQuery identifier\nfunction $escape(val) {\n return val.replace(/([!\"#$%&'()*+,./:;<=>?@[\\\\\\]^`{|}~])/g, \"\\\\$1\");\n}\n\nfunction bindEl(el) {\n let $el = $(el);\n Object.keys(bindings).forEach(function(className) {\n if ($el.hasClass(className) && !$el.hasClass(\"crosstalk-input-bound\")) {\n let binding = bindings[className];\n bindInstance(binding, el);\n }\n });\n}\n\nfunction bindInstance(binding, el) {\n let jsonEl = $(el).find(\"script[type='application/json'][data-for='\" + $escape(el.id) + \"']\");\n let data = JSON.parse(jsonEl[0].innerText);\n\n let instance = binding.factory(el, data);\n $(el).data(\"crosstalk-instance\", instance);\n $(el).addClass(\"crosstalk-input-bound\");\n}\n\nif (global.Shiny) {\n let inputBinding = new global.Shiny.InputBinding();\n let $ = global.jQuery;\n $.extend(inputBinding, {\n find: function(scope) {\n return $(scope).find(\".crosstalk-input\");\n },\n initialize: function(el) {\n if (!$(el).hasClass(\"crosstalk-input-bound\")) {\n bindEl(el);\n }\n },\n getId: function(el) {\n return el.id;\n },\n getValue: function(el) {\n\n },\n setValue: function(el, value) {\n\n },\n receiveMessage: function(el, data) {\n\n },\n subscribe: function(el, callback) {\n $(el).data(\"crosstalk-instance\").resume();\n },\n unsubscribe: function(el) {\n $(el).data(\"crosstalk-instance\").suspend();\n }\n });\n global.Shiny.inputBindings.register(inputBinding, \"crosstalk.inputBinding\");\n}\n", - "import * as input from \"./input\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\n\ninput.register({\n className: \"crosstalk-input-checkboxgroup\",\n\n factory: function(el, data) {\n /*\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n let ctHandle = new FilterHandle(data.group);\n\n let lastKnownKeys;\n let $el = $(el);\n $el.on(\"change\", \"input[type='checkbox']\", function() {\n let checked = $el.find(\"input[type='checkbox']:checked\");\n if (checked.length === 0) {\n lastKnownKeys = null;\n ctHandle.clear();\n } else {\n let keys = {};\n checked.each(function() {\n data.map[this.value].forEach(function(key) {\n keys[key] = true;\n });\n });\n let keyArray = Object.keys(keys);\n keyArray.sort();\n lastKnownKeys = keyArray;\n ctHandle.set(keyArray);\n }\n });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n", - "import * as input from \"./input\";\nimport * as util from \"./util\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\n\ninput.register({\n className: \"crosstalk-input-select\",\n\n factory: function(el, data) {\n /*\n * items: {value: [...], label: [...]}\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n\n let first = [{value: \"\", label: \"(All)\"}];\n let items = util.dataframeToD3(data.items);\n let opts = {\n options: first.concat(items),\n valueField: \"value\",\n labelField: \"label\",\n searchField: \"label\"\n };\n\n let select = $(el).find(\"select\")[0];\n\n let selectize = $(select).selectize(opts)[0].selectize;\n\n let ctHandle = new FilterHandle(data.group);\n\n let lastKnownKeys;\n selectize.on(\"change\", function() {\n if (selectize.items.length === 0) {\n lastKnownKeys = null;\n ctHandle.clear();\n } else {\n let keys = {};\n selectize.items.forEach(function(group) {\n data.map[group].forEach(function(key) {\n keys[key] = true;\n });\n });\n let keyArray = Object.keys(keys);\n keyArray.sort();\n lastKnownKeys = keyArray;\n ctHandle.set(keyArray);\n }\n });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n", - "import * as input from \"./input\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\nlet strftime = global.strftime;\n\ninput.register({\n className: \"crosstalk-input-slider\",\n\n factory: function(el, data) {\n /*\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n let ctHandle = new FilterHandle(data.group);\n\n let opts = {};\n let $el = $(el).find(\"input\");\n let dataType = $el.data(\"data-type\");\n let timeFormat = $el.data(\"time-format\");\n let round = $el.data(\"round\");\n let timeFormatter;\n\n // Set up formatting functions\n if (dataType === \"date\") {\n timeFormatter = strftime.utc();\n opts.prettify = function(num) {\n return timeFormatter(timeFormat, new Date(num));\n };\n\n } else if (dataType === \"datetime\") {\n let timezone = $el.data(\"timezone\");\n if (timezone)\n timeFormatter = strftime.timezone(timezone);\n else\n timeFormatter = strftime;\n\n opts.prettify = function(num) {\n return timeFormatter(timeFormat, new Date(num));\n };\n } else if (dataType === \"number\") {\n if (typeof round !== \"undefined\")\n opts.prettify = function(num) {\n let factor = Math.pow(10, round);\n return Math.round(num * factor) / factor;\n };\n }\n\n $el.ionRangeSlider(opts);\n\n function getValue() {\n let result = $el.data(\"ionRangeSlider\").result;\n\n // Function for converting numeric value from slider to appropriate type.\n let convert;\n let dataType = $el.data(\"data-type\");\n if (dataType === \"date\") {\n convert = function(val) {\n return formatDateUTC(new Date(+val));\n };\n } else if (dataType === \"datetime\") {\n convert = function(val) {\n // Convert ms to s\n return +val / 1000;\n };\n } else {\n convert = function(val) { return +val; };\n }\n\n if ($el.data(\"ionRangeSlider\").options.type === \"double\") {\n return [convert(result.from), convert(result.to)];\n } else {\n return convert(result.from);\n }\n }\n\n let lastKnownKeys = null;\n\n $el.on(\"change.crosstalkSliderInput\", function(event) {\n if (!$el.data(\"updating\") && !$el.data(\"animating\")) {\n let [from, to] = getValue();\n let keys = [];\n for (let i = 0; i < data.values.length; i++) {\n let val = data.values[i];\n if (val >= from && val <= to) {\n keys.push(data.keys[i]);\n }\n }\n keys.sort();\n ctHandle.set(keys);\n lastKnownKeys = keys;\n }\n });\n\n\n // let $el = $(el);\n // $el.on(\"change\", \"input[type=\"checkbox\"]\", function() {\n // let checked = $el.find(\"input[type=\"checkbox\"]:checked\");\n // if (checked.length === 0) {\n // ctHandle.clear();\n // } else {\n // let keys = {};\n // checked.each(function() {\n // data.map[this.value].forEach(function(key) {\n // keys[key] = true;\n // });\n // });\n // let keyArray = Object.keys(keys);\n // keyArray.sort();\n // ctHandle.set(keyArray);\n // }\n // });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n\n\n// Convert a number to a string with leading zeros\nfunction padZeros(n, digits) {\n let str = n.toString();\n while (str.length < digits)\n str = \"0\" + str;\n return str;\n}\n\n// Given a Date object, return a string in yyyy-mm-dd format, using the\n// UTC date. This may be a day off from the date in the local time zone.\nfunction formatDateUTC(date) {\n if (date instanceof Date) {\n return date.getUTCFullYear() + \"-\" +\n padZeros(date.getUTCMonth()+1, 2) + \"-\" +\n padZeros(date.getUTCDate(), 2);\n\n } else {\n return null;\n }\n}\n", - "import Events from \"./events\";\nimport grp from \"./group\";\nimport * as util from \"./util\";\n\n/**\n * Use this class to read and write (and listen for changes to) the selection\n * for a Crosstalk group. This is intended to be used for linked brushing.\n *\n * If two (or more) `SelectionHandle` instances in the same webpage share the\n * same group name, they will share the same state. Setting the selection using\n * one `SelectionHandle` instance will result in the `value` property instantly\n * changing across the others, and `\"change\"` event listeners on all instances\n * (including the one that initiated the sending) will fire.\n *\n * @param {string} [group] - The name of the Crosstalk group, or if none,\n * null or undefined (or any other falsy value). This can be changed later\n * via the [SelectionHandle#setGroup](#setGroup) method.\n * @param {Object} [extraInfo] - An object whose properties will be copied to\n * the event object whenever an event is emitted.\n */\nexport class SelectionHandle {\n\n constructor(group = null, extraInfo = null) {\n this._eventRelay = new Events();\n this._emitter = new util.SubscriptionTracker(this._eventRelay);\n\n // Name of the group we're currently tracking, if any. Can change over time.\n this._group = null;\n // The Var we're currently tracking, if any. Can change over time.\n this._var = null;\n // The event handler subscription we currently have on var.on(\"change\").\n this._varOnChangeSub = null;\n\n this._extraInfo = util.extend({ sender: this }, extraInfo);\n\n this.setGroup(group);\n }\n\n /**\n * Changes the Crosstalk group membership of this SelectionHandle. The group\n * being switched away from (if any) will not have its selection value\n * modified as a result of calling `setGroup`, even if this handle was the\n * most recent handle to set the selection of the group.\n *\n * The group being switched to (if any) will also not have its selection value\n * modified as a result of calling `setGroup`. If you want to set the\n * selection value of the new group, call `set` explicitly.\n *\n * @param {string} group - The name of the Crosstalk group, or null (or\n * undefined) to clear the group.\n */\n setGroup(group) {\n // If group is unchanged, do nothing\n if (this._group === group)\n return;\n // Treat null, undefined, and other falsy values the same\n if (!this._group && !group)\n return;\n\n if (this._var) {\n this._var.off(\"change\", this._varOnChangeSub);\n this._var = null;\n this._varOnChangeSub = null;\n }\n\n this._group = group;\n\n if (group) {\n this._var = grp(group).var(\"selection\");\n let sub = this._var.on(\"change\", (e) => {\n this._eventRelay.trigger(\"change\", e, this);\n });\n this._varOnChangeSub = sub;\n }\n }\n\n /**\n * Retrieves the current selection for the group represented by this\n * `SelectionHandle`.\n *\n * - If no selection is active, then this value will be falsy.\n * - If a selection is active, but no data points are selected, then this\n * value will be an empty array.\n * - If a selection is active, and data points are selected, then the keys\n * of the selected data points will be present in the array.\n */\n get value() {\n return this._var ? this._var.get() : null;\n }\n\n /**\n * Combines the given `extraInfo` (if any) with the handle's default\n * `_extraInfo` (if any).\n * @private\n */\n _mergeExtraInfo(extraInfo) {\n // Important incidental effect: shallow clone is returned\n return util.extend({},\n this._extraInfo ? this._extraInfo : null,\n extraInfo ? extraInfo : null);\n }\n\n /**\n * Overwrites the current selection for the group, and raises the `\"change\"`\n * event among all of the group's '`SelectionHandle` instances (including\n * this one).\n *\n * @fires SelectionHandle#change\n * @param {string[]} selectedKeys - Falsy, empty array, or array of keys (see\n * {@link SelectionHandle#value}).\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `SelectionHandle` constructor).\n */\n set(selectedKeys, extraInfo) {\n if (this._var)\n this._var.set(selectedKeys, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * Overwrites the current selection for the group, and raises the `\"change\"`\n * event among all of the group's '`SelectionHandle` instances (including\n * this one).\n *\n * @fires SelectionHandle#change\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any that were passed\n * into the `SelectionHandle` constructor).\n */\n clear(extraInfo) {\n if (this._var)\n this.set(void 0, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * Subscribes to events on this `SelectionHandle`.\n *\n * @param {string} eventType - Indicates the type of events to listen to.\n * Currently, only `\"change\"` is supported.\n * @param {SelectionHandle~listener} listener - The callback function that\n * will be invoked when the event occurs.\n * @return {string} - A token to pass to {@link SelectionHandle#off} to cancel\n * this subscription.\n */\n on(eventType, listener) {\n return this._emitter.on(eventType, listener);\n }\n\n /**\n * Cancels event subscriptions created by {@link SelectionHandle#on}.\n *\n * @param {string} eventType - The type of event to unsubscribe.\n * @param {string|SelectionHandle~listener} listener - Either the callback\n * function previously passed into {@link SelectionHandle#on}, or the\n * string that was returned from {@link SelectionHandle#on}.\n */\n off(eventType, listener) {\n return this._emitter.off(eventType, listener);\n }\n\n /**\n * Shuts down the `SelectionHandle` object.\n *\n * Removes all event listeners that were added through this handle.\n */\n close() {\n this._emitter.removeAllListeners();\n this.setGroup(null);\n }\n}\n\n/**\n * @callback SelectionHandle~listener\n * @param {Object} event - An object containing details of the event. For\n * `\"change\"` events, this includes the properties `value` (the new\n * value of the selection, or `undefined` if no selection is active),\n * `oldValue` (the previous value of the selection), and `sender` (the\n * `SelectionHandle` instance that made the change).\n */\n\n/**\n * @event SelectionHandle#change\n * @type {object}\n * @property {object} value - The new value of the selection, or `undefined`\n * if no selection is active.\n * @property {object} oldValue - The previous value of the selection.\n * @property {SelectionHandle} sender - The `SelectionHandle` instance that\n * changed the value.\n */\n", - "export function extend(target, ...sources) {\n for (let i = 0; i < sources.length; i++) {\n let src = sources[i];\n if (typeof(src) === \"undefined\" || src === null)\n continue;\n\n for (let key in src) {\n if (src.hasOwnProperty(key)) {\n target[key] = src[key];\n }\n }\n }\n return target;\n}\n\nexport function checkSorted(list) {\n for (let i = 1; i < list.length; i++) {\n if (list[i] <= list[i-1]) {\n throw new Error(\"List is not sorted or contains duplicate\");\n }\n }\n}\n\nexport function diffSortedLists(a, b) {\n let i_a = 0;\n let i_b = 0;\n\n if (!a) a = [];\n if (!b) b = [];\n\n let a_only = [];\n let b_only = [];\n\n checkSorted(a);\n checkSorted(b);\n\n while (i_a < a.length && i_b < b.length) {\n if (a[i_a] === b[i_b]) {\n i_a++;\n i_b++;\n } else if (a[i_a] < b[i_b]) {\n a_only.push(a[i_a++]);\n } else {\n b_only.push(b[i_b++]);\n }\n }\n\n if (i_a < a.length)\n a_only = a_only.concat(a.slice(i_a));\n if (i_b < b.length)\n b_only = b_only.concat(b.slice(i_b));\n return {\n removed: a_only,\n added: b_only\n };\n}\n\n// Convert from wide: { colA: [1,2,3], colB: [4,5,6], ... }\n// to long: [ {colA: 1, colB: 4}, {colA: 2, colB: 5}, ... ]\nexport function dataframeToD3(df) {\n let names = [];\n let length;\n for (let name in df) {\n if (df.hasOwnProperty(name))\n names.push(name);\n if (typeof(df[name]) !== \"object\" || typeof(df[name].length) === \"undefined\") {\n throw new Error(\"All fields must be arrays\");\n } else if (typeof(length) !== \"undefined\" && length !== df[name].length) {\n throw new Error(\"All fields must be arrays of the same length\");\n }\n length = df[name].length;\n }\n let results = [];\n let item;\n for (let row = 0; row < length; row++) {\n item = {};\n for (let col = 0; col < names.length; col++) {\n item[names[col]] = df[names[col]][row];\n }\n results.push(item);\n }\n return results;\n}\n\n/**\n * Keeps track of all event listener additions/removals and lets all active\n * listeners be removed with a single operation.\n *\n * @private\n */\nexport class SubscriptionTracker {\n constructor(emitter) {\n this._emitter = emitter;\n this._subs = {};\n }\n\n on(eventType, listener) {\n let sub = this._emitter.on(eventType, listener);\n this._subs[sub] = eventType;\n return sub;\n }\n\n off(eventType, listener) {\n let sub = this._emitter.off(eventType, listener);\n if (sub) {\n delete this._subs[sub];\n }\n return sub;\n }\n\n removeAllListeners() {\n let current_subs = this._subs;\n this._subs = {};\n Object.keys(current_subs).forEach((sub) => {\n this._emitter.off(current_subs[sub], sub);\n });\n }\n}\n", - "import Events from \"./events\";\n\nexport default class Var {\n constructor(group, name, /*optional*/ value) {\n this._group = group;\n this._name = name;\n this._value = value;\n this._events = new Events();\n }\n\n get() {\n return this._value;\n }\n\n set(value, /*optional*/ event) {\n if (this._value === value) {\n // Do nothing; the value hasn't changed\n return;\n }\n let oldValue = this._value;\n this._value = value;\n // Alert JavaScript listeners that the value has changed\n let evt = {};\n if (event && typeof(event) === \"object\") {\n for (let k in event) {\n if (event.hasOwnProperty(k))\n evt[k] = event[k];\n }\n }\n evt.oldValue = oldValue;\n evt.value = value;\n this._events.trigger(\"change\", evt, this);\n\n // TODO: Make this extensible, to let arbitrary back-ends know that\n // something has changed\n if (global.Shiny && global.Shiny.onInputChange) {\n global.Shiny.onInputChange(\n \".clientValue-\" +\n (this._group.name !== null ? this._group.name + \"-\" : \"\") +\n this._name,\n typeof(value) === \"undefined\" ? null : value\n );\n }\n }\n\n on(eventType, listener) {\n return this._events.on(eventType, listener);\n }\n\n off(eventType, listener) {\n return this._events.off(eventType, listener);\n }\n}\n" - ] -} \ No newline at end of file diff --git a/docs/articles/get_started_files/crosstalk-1.2.1/js/crosstalk.min.js b/docs/articles/get_started_files/crosstalk-1.2.1/js/crosstalk.min.js deleted file mode 100644 index b7ec0ac..0000000 --- a/docs/articles/get_started_files/crosstalk-1.2.1/js/crosstalk.min.js +++ /dev/null @@ -1,2 +0,0 @@ -!function o(u,a,l){function s(n,e){if(!a[n]){if(!u[n]){var t="function"==typeof require&&require;if(!e&&t)return t(n,!0);if(f)return f(n,!0);var r=new Error("Cannot find module '"+n+"'");throw r.code="MODULE_NOT_FOUND",r}var i=a[n]={exports:{}};u[n][0].call(i.exports,function(e){var t=u[n][1][e];return s(t||e)},i,i.exports,o,u,a,l)}return a[n].exports}for(var f="function"==typeof require&&require,e=0;e?@[\\\]^`{|}~])/g,"\\$1")+"']"),r=JSON.parse(n[0].innerText),i=e.factory(t,r);o(t).data("crosstalk-instance",i),o(t).addClass("crosstalk-input-bound")}if(t.Shiny){var e=new t.Shiny.InputBinding,u=t.jQuery;u.extend(e,{find:function(e){return u(e).find(".crosstalk-input")},initialize:function(e){var t,n;u(e).hasClass("crosstalk-input-bound")||(n=o(t=e),Object.keys(r).forEach(function(e){n.hasClass(e)&&!n.hasClass("crosstalk-input-bound")&&i(r[e],t)}))},getId:function(e){return e.id},getValue:function(e){},setValue:function(e,t){},receiveMessage:function(e,t){},subscribe:function(e,t){u(e).data("crosstalk-instance").resume()},unsubscribe:function(e){u(e).data("crosstalk-instance").suspend()}}),t.Shiny.inputBindings.register(e,"crosstalk.inputBinding")}}).call(this,"undefined"!=typeof global?global:"undefined"!=typeof self?self:"undefined"!=typeof window?window:{})},{}],7:[function(r,e,t){(function(e){"use strict";var t=function(e){{if(e&&e.__esModule)return e;var t={};if(null!=e)for(var n in e)Object.prototype.hasOwnProperty.call(e,n)&&(t[n]=e[n]);return t.default=e,t}}(r("./input")),n=r("./filter");var a=e.jQuery;t.register({className:"crosstalk-input-checkboxgroup",factory:function(e,r){var i=new n.FilterHandle(r.group),o=void 0,u=a(e);return u.on("change","input[type='checkbox']",function(){var e=u.find("input[type='checkbox']:checked");if(0===e.length)o=null,i.clear();else{var t={};e.each(function(){r.map[this.value].forEach(function(e){t[e]=!0})});var n=Object.keys(t);n.sort(),o=n,i.set(n)}}),{suspend:function(){i.clear()},resume:function(){o&&i.set(o)}}}})}).call(this,"undefined"!=typeof global?global:"undefined"!=typeof self?self:"undefined"!=typeof window?window:{})},{"./filter":2,"./input":6}],8:[function(r,e,t){(function(e){"use strict";var t=n(r("./input")),l=n(r("./util")),s=r("./filter");function n(e){if(e&&e.__esModule)return e;var t={};if(null!=e)for(var n in e)Object.prototype.hasOwnProperty.call(e,n)&&(t[n]=e[n]);return t.default=e,t}var f=e.jQuery;t.register({className:"crosstalk-input-select",factory:function(e,n){var t=l.dataframeToD3(n.items),r={options:[{value:"",label:"(All)"}].concat(t),valueField:"value",labelField:"label",searchField:"label"},i=f(e).find("select")[0],o=f(i).selectize(r)[0].selectize,u=new s.FilterHandle(n.group),a=void 0;return o.on("change",function(){if(0===o.items.length)a=null,u.clear();else{var t={};o.items.forEach(function(e){n.map[e].forEach(function(e){t[e]=!0})});var e=Object.keys(t);e.sort(),a=e,u.set(e)}}),{suspend:function(){u.clear()},resume:function(){a&&u.set(a)}}}})}).call(this,"undefined"!=typeof global?global:"undefined"!=typeof self?self:"undefined"!=typeof window?window:{})},{"./filter":2,"./input":6,"./util":11}],9:[function(n,e,t){(function(e){"use strict";var d=function(e,t){if(Array.isArray(e))return e;if(Symbol.iterator in Object(e))return function(e,t){var n=[],r=!0,i=!1,o=void 0;try{for(var u,a=e[Symbol.iterator]();!(r=(u=a.next()).done)&&(n.push(u.value),!t||n.length!==t);r=!0);}catch(e){i=!0,o=e}finally{try{!r&&a.return&&a.return()}finally{if(i)throw o}}return n}(e,t);throw new TypeError("Invalid attempt to destructure non-iterable instance")},t=function(e){{if(e&&e.__esModule)return e;var t={};if(null!=e)for(var n in e)Object.prototype.hasOwnProperty.call(e,n)&&(t[n]=e[n]);return t.default=e,t}}(n("./input")),a=n("./filter");var v=e.jQuery,p=e.strftime;function y(e,t){for(var n=e.toString();n.length {\n this._eventRelay.trigger(\"change\", e, this);\n });\n this._varOnChangeSub = sub;\n }\n }\n\n /**\n * Combine the given `extraInfo` (if any) with the handle's default\n * `_extraInfo` (if any).\n * @private\n */\n _mergeExtraInfo(extraInfo) {\n return util.extend({},\n this._extraInfo ? this._extraInfo : null,\n extraInfo ? extraInfo : null);\n }\n\n /**\n * Close the handle. This clears this handle's contribution to the filter set,\n * and unsubscribes all event listeners.\n */\n close() {\n this._emitter.removeAllListeners();\n this.clear();\n this.setGroup(null);\n }\n\n /**\n * Clear this handle's contribution to the filter set.\n *\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `FilterHandle` constructor).\n * \n * @fires FilterHandle#change\n */\n clear(extraInfo) {\n if (!this._filterSet)\n return;\n this._filterSet.clear(this._id);\n this._onChange(extraInfo);\n }\n\n /**\n * Set this handle's contribution to the filter set. This array should consist\n * of the keys of the rows that _should_ be displayed; any keys that are not\n * present in the array will be considered _filtered out_. Note that multiple\n * `FilterHandle` instances in the group may each contribute an array of keys,\n * and only those keys that appear in _all_ of the arrays make it through the\n * filter.\n *\n * @param {string[]} keys - Empty array, or array of keys. To clear the\n * filter, don't pass an empty array; instead, use the\n * {@link FilterHandle#clear} method.\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `FilterHandle` constructor).\n * \n * @fires FilterHandle#change\n */\n set(keys, extraInfo) {\n if (!this._filterSet)\n return;\n this._filterSet.update(this._id, keys);\n this._onChange(extraInfo);\n }\n\n /**\n * @return {string[]|null} - Either: 1) an array of keys that made it through\n * all of the `FilterHandle` instances, or, 2) `null`, which means no filter\n * is being applied (all data should be displayed).\n */\n get filteredKeys() {\n return this._filterSet ? this._filterSet.value : null;\n }\n\n /**\n * Subscribe to events on this `FilterHandle`.\n *\n * @param {string} eventType - Indicates the type of events to listen to.\n * Currently, only `\"change\"` is supported.\n * @param {FilterHandle~listener} listener - The callback function that\n * will be invoked when the event occurs.\n * @return {string} - A token to pass to {@link FilterHandle#off} to cancel\n * this subscription.\n */\n on(eventType, listener) {\n return this._emitter.on(eventType, listener);\n }\n\n /**\n * Cancel event subscriptions created by {@link FilterHandle#on}.\n *\n * @param {string} eventType - The type of event to unsubscribe.\n * @param {string|FilterHandle~listener} listener - Either the callback\n * function previously passed into {@link FilterHandle#on}, or the\n * string that was returned from {@link FilterHandle#on}.\n */\n off(eventType, listener) {\n return this._emitter.off(eventType, listener);\n }\n\n _onChange(extraInfo) {\n if (!this._filterSet)\n return;\n this._filterVar.set(this._filterSet.value, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * @callback FilterHandle~listener\n * @param {Object} event - An object containing details of the event. For\n * `\"change\"` events, this includes the properties `value` (the new\n * value of the filter set, or `null` if no filter set is active),\n * `oldValue` (the previous value of the filter set), and `sender` (the\n * `FilterHandle` instance that made the change).\n */\n\n}\n\n/**\n * @event FilterHandle#change\n * @type {object}\n * @property {object} value - The new value of the filter set, or `null`\n * if no filter set is active.\n * @property {object} oldValue - The previous value of the filter set.\n * @property {FilterHandle} sender - The `FilterHandle` instance that\n * changed the value.\n */\n","import { diffSortedLists } from \"./util\";\n\nfunction naturalComparator(a, b) {\n if (a === b) {\n return 0;\n } else if (a < b) {\n return -1;\n } else if (a > b) {\n return 1;\n }\n}\n\n/**\n * @private\n */\nexport default class FilterSet {\n constructor() {\n this.reset();\n }\n\n reset() {\n // Key: handle ID, Value: array of selected keys, or null\n this._handles = {};\n // Key: key string, Value: count of handles that include it\n this._keys = {};\n this._value = null;\n this._activeHandles = 0;\n }\n\n get value() {\n return this._value;\n }\n\n update(handleId, keys) {\n if (keys !== null) {\n keys = keys.slice(0); // clone before sorting\n keys.sort(naturalComparator);\n }\n\n let {added, removed} = diffSortedLists(this._handles[handleId], keys);\n this._handles[handleId] = keys;\n\n for (let i = 0; i < added.length; i++) {\n this._keys[added[i]] = (this._keys[added[i]] || 0) + 1;\n }\n for (let i = 0; i < removed.length; i++) {\n this._keys[removed[i]]--;\n }\n\n this._updateValue(keys);\n }\n\n /**\n * @param {string[]} keys Sorted array of strings that indicate\n * a superset of possible keys.\n * @private\n */\n _updateValue(keys = this._allKeys) {\n let handleCount = Object.keys(this._handles).length;\n if (handleCount === 0) {\n this._value = null;\n } else {\n this._value = [];\n for (let i = 0; i < keys.length; i++) {\n let count = this._keys[keys[i]];\n if (count === handleCount) {\n this._value.push(keys[i]);\n }\n }\n }\n }\n\n clear(handleId) {\n if (typeof(this._handles[handleId]) === \"undefined\") {\n return;\n }\n\n let keys = this._handles[handleId];\n if (!keys) {\n keys = [];\n }\n\n for (let i = 0; i < keys.length; i++) {\n this._keys[keys[i]]--;\n }\n delete this._handles[handleId];\n\n this._updateValue();\n }\n\n get _allKeys() {\n let allKeys = Object.keys(this._keys);\n allKeys.sort(naturalComparator);\n return allKeys;\n }\n}\n","import Var from \"./var\";\n\n// Use a global so that multiple copies of crosstalk.js can be loaded and still\n// have groups behave as singletons across all copies.\nglobal.__crosstalk_groups = global.__crosstalk_groups || {};\nlet groups = global.__crosstalk_groups;\n\nexport default function group(groupName) {\n if (groupName && typeof(groupName) === \"string\") {\n if (!groups.hasOwnProperty(groupName)) {\n groups[groupName] = new Group(groupName);\n }\n return groups[groupName];\n } else if (typeof(groupName) === \"object\" && groupName._vars && groupName.var) {\n // Appears to already be a group object\n return groupName;\n } else if (Array.isArray(groupName) &&\n groupName.length == 1 &&\n typeof(groupName[0]) === \"string\") {\n return group(groupName[0]);\n } else {\n throw new Error(\"Invalid groupName argument\");\n }\n}\n\nclass Group {\n constructor(name) {\n this.name = name;\n this._vars = {};\n }\n\n var(name) {\n if (!name || typeof(name) !== \"string\") {\n throw new Error(\"Invalid var name\");\n }\n\n if (!this._vars.hasOwnProperty(name))\n this._vars[name] = new Var(this, name);\n return this._vars[name];\n }\n\n has(name) {\n if (!name || typeof(name) !== \"string\") {\n throw new Error(\"Invalid var name\");\n }\n\n return this._vars.hasOwnProperty(name);\n }\n}\n","import group from \"./group\";\nimport { SelectionHandle } from \"./selection\";\nimport { FilterHandle } from \"./filter\";\nimport { bind } from \"./input\";\nimport \"./input_selectize\";\nimport \"./input_checkboxgroup\";\nimport \"./input_slider\";\n\nconst defaultGroup = group(\"default\");\n\nfunction var_(name) {\n return defaultGroup.var(name);\n}\n\nfunction has(name) {\n return defaultGroup.has(name);\n}\n\nif (global.Shiny) {\n global.Shiny.addCustomMessageHandler(\"update-client-value\", function(message) {\n if (typeof(message.group) === \"string\") {\n group(message.group).var(message.name).set(message.value);\n } else {\n var_(message.name).set(message.value);\n }\n });\n}\n\nconst crosstalk = {\n group: group,\n var: var_,\n has: has,\n SelectionHandle: SelectionHandle,\n FilterHandle: FilterHandle,\n bind: bind\n};\n\n/**\n * @namespace crosstalk\n */\nexport default crosstalk;\nglobal.crosstalk = crosstalk;\n","let $ = global.jQuery;\n\nlet bindings = {};\n\nexport function register(reg) {\n bindings[reg.className] = reg;\n if (global.document && global.document.readyState !== \"complete\") {\n $(() => {\n bind();\n });\n } else if (global.document) {\n setTimeout(bind, 100);\n }\n}\n\nexport function bind() {\n Object.keys(bindings).forEach(function(className) {\n let binding = bindings[className];\n $(\".\" + binding.className).not(\".crosstalk-input-bound\").each(function(i, el) {\n bindInstance(binding, el);\n });\n });\n}\n\n// Escape jQuery identifier\nfunction $escape(val) {\n return val.replace(/([!\"#$%&'()*+,./:;<=>?@[\\\\\\]^`{|}~])/g, \"\\\\$1\");\n}\n\nfunction bindEl(el) {\n let $el = $(el);\n Object.keys(bindings).forEach(function(className) {\n if ($el.hasClass(className) && !$el.hasClass(\"crosstalk-input-bound\")) {\n let binding = bindings[className];\n bindInstance(binding, el);\n }\n });\n}\n\nfunction bindInstance(binding, el) {\n let jsonEl = $(el).find(\"script[type='application/json'][data-for='\" + $escape(el.id) + \"']\");\n let data = JSON.parse(jsonEl[0].innerText);\n\n let instance = binding.factory(el, data);\n $(el).data(\"crosstalk-instance\", instance);\n $(el).addClass(\"crosstalk-input-bound\");\n}\n\nif (global.Shiny) {\n let inputBinding = new global.Shiny.InputBinding();\n let $ = global.jQuery;\n $.extend(inputBinding, {\n find: function(scope) {\n return $(scope).find(\".crosstalk-input\");\n },\n initialize: function(el) {\n if (!$(el).hasClass(\"crosstalk-input-bound\")) {\n bindEl(el);\n }\n },\n getId: function(el) {\n return el.id;\n },\n getValue: function(el) {\n\n },\n setValue: function(el, value) {\n\n },\n receiveMessage: function(el, data) {\n\n },\n subscribe: function(el, callback) {\n $(el).data(\"crosstalk-instance\").resume();\n },\n unsubscribe: function(el) {\n $(el).data(\"crosstalk-instance\").suspend();\n }\n });\n global.Shiny.inputBindings.register(inputBinding, \"crosstalk.inputBinding\");\n}\n","import * as input from \"./input\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\n\ninput.register({\n className: \"crosstalk-input-checkboxgroup\",\n\n factory: function(el, data) {\n /*\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n let ctHandle = new FilterHandle(data.group);\n\n let lastKnownKeys;\n let $el = $(el);\n $el.on(\"change\", \"input[type='checkbox']\", function() {\n let checked = $el.find(\"input[type='checkbox']:checked\");\n if (checked.length === 0) {\n lastKnownKeys = null;\n ctHandle.clear();\n } else {\n let keys = {};\n checked.each(function() {\n data.map[this.value].forEach(function(key) {\n keys[key] = true;\n });\n });\n let keyArray = Object.keys(keys);\n keyArray.sort();\n lastKnownKeys = keyArray;\n ctHandle.set(keyArray);\n }\n });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n","import * as input from \"./input\";\nimport * as util from \"./util\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\n\ninput.register({\n className: \"crosstalk-input-select\",\n\n factory: function(el, data) {\n /*\n * items: {value: [...], label: [...]}\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n\n let first = [{value: \"\", label: \"(All)\"}];\n let items = util.dataframeToD3(data.items);\n let opts = {\n options: first.concat(items),\n valueField: \"value\",\n labelField: \"label\",\n searchField: \"label\"\n };\n\n let select = $(el).find(\"select\")[0];\n\n let selectize = $(select).selectize(opts)[0].selectize;\n\n let ctHandle = new FilterHandle(data.group);\n\n let lastKnownKeys;\n selectize.on(\"change\", function() {\n if (selectize.items.length === 0) {\n lastKnownKeys = null;\n ctHandle.clear();\n } else {\n let keys = {};\n selectize.items.forEach(function(group) {\n data.map[group].forEach(function(key) {\n keys[key] = true;\n });\n });\n let keyArray = Object.keys(keys);\n keyArray.sort();\n lastKnownKeys = keyArray;\n ctHandle.set(keyArray);\n }\n });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n","import * as input from \"./input\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\nlet strftime = global.strftime;\n\ninput.register({\n className: \"crosstalk-input-slider\",\n\n factory: function(el, data) {\n /*\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n let ctHandle = new FilterHandle(data.group);\n\n let opts = {};\n let $el = $(el).find(\"input\");\n let dataType = $el.data(\"data-type\");\n let timeFormat = $el.data(\"time-format\");\n let round = $el.data(\"round\");\n let timeFormatter;\n\n // Set up formatting functions\n if (dataType === \"date\") {\n timeFormatter = strftime.utc();\n opts.prettify = function(num) {\n return timeFormatter(timeFormat, new Date(num));\n };\n\n } else if (dataType === \"datetime\") {\n let timezone = $el.data(\"timezone\");\n if (timezone)\n timeFormatter = strftime.timezone(timezone);\n else\n timeFormatter = strftime;\n\n opts.prettify = function(num) {\n return timeFormatter(timeFormat, new Date(num));\n };\n } else if (dataType === \"number\") {\n if (typeof round !== \"undefined\")\n opts.prettify = function(num) {\n let factor = Math.pow(10, round);\n return Math.round(num * factor) / factor;\n };\n }\n\n $el.ionRangeSlider(opts);\n\n function getValue() {\n let result = $el.data(\"ionRangeSlider\").result;\n\n // Function for converting numeric value from slider to appropriate type.\n let convert;\n let dataType = $el.data(\"data-type\");\n if (dataType === \"date\") {\n convert = function(val) {\n return formatDateUTC(new Date(+val));\n };\n } else if (dataType === \"datetime\") {\n convert = function(val) {\n // Convert ms to s\n return +val / 1000;\n };\n } else {\n convert = function(val) { return +val; };\n }\n\n if ($el.data(\"ionRangeSlider\").options.type === \"double\") {\n return [convert(result.from), convert(result.to)];\n } else {\n return convert(result.from);\n }\n }\n\n let lastKnownKeys = null;\n\n $el.on(\"change.crosstalkSliderInput\", function(event) {\n if (!$el.data(\"updating\") && !$el.data(\"animating\")) {\n let [from, to] = getValue();\n let keys = [];\n for (let i = 0; i < data.values.length; i++) {\n let val = data.values[i];\n if (val >= from && val <= to) {\n keys.push(data.keys[i]);\n }\n }\n keys.sort();\n ctHandle.set(keys);\n lastKnownKeys = keys;\n }\n });\n\n\n // let $el = $(el);\n // $el.on(\"change\", \"input[type=\"checkbox\"]\", function() {\n // let checked = $el.find(\"input[type=\"checkbox\"]:checked\");\n // if (checked.length === 0) {\n // ctHandle.clear();\n // } else {\n // let keys = {};\n // checked.each(function() {\n // data.map[this.value].forEach(function(key) {\n // keys[key] = true;\n // });\n // });\n // let keyArray = Object.keys(keys);\n // keyArray.sort();\n // ctHandle.set(keyArray);\n // }\n // });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n\n\n// Convert a number to a string with leading zeros\nfunction padZeros(n, digits) {\n let str = n.toString();\n while (str.length < digits)\n str = \"0\" + str;\n return str;\n}\n\n// Given a Date object, return a string in yyyy-mm-dd format, using the\n// UTC date. This may be a day off from the date in the local time zone.\nfunction formatDateUTC(date) {\n if (date instanceof Date) {\n return date.getUTCFullYear() + \"-\" +\n padZeros(date.getUTCMonth()+1, 2) + \"-\" +\n padZeros(date.getUTCDate(), 2);\n\n } else {\n return null;\n }\n}\n","import Events from \"./events\";\nimport grp from \"./group\";\nimport * as util from \"./util\";\n\n/**\n * Use this class to read and write (and listen for changes to) the selection\n * for a Crosstalk group. This is intended to be used for linked brushing.\n *\n * If two (or more) `SelectionHandle` instances in the same webpage share the\n * same group name, they will share the same state. Setting the selection using\n * one `SelectionHandle` instance will result in the `value` property instantly\n * changing across the others, and `\"change\"` event listeners on all instances\n * (including the one that initiated the sending) will fire.\n *\n * @param {string} [group] - The name of the Crosstalk group, or if none,\n * null or undefined (or any other falsy value). This can be changed later\n * via the [SelectionHandle#setGroup](#setGroup) method.\n * @param {Object} [extraInfo] - An object whose properties will be copied to\n * the event object whenever an event is emitted.\n */\nexport class SelectionHandle {\n\n constructor(group = null, extraInfo = null) {\n this._eventRelay = new Events();\n this._emitter = new util.SubscriptionTracker(this._eventRelay);\n\n // Name of the group we're currently tracking, if any. Can change over time.\n this._group = null;\n // The Var we're currently tracking, if any. Can change over time.\n this._var = null;\n // The event handler subscription we currently have on var.on(\"change\").\n this._varOnChangeSub = null;\n\n this._extraInfo = util.extend({ sender: this }, extraInfo);\n\n this.setGroup(group);\n }\n\n /**\n * Changes the Crosstalk group membership of this SelectionHandle. The group\n * being switched away from (if any) will not have its selection value\n * modified as a result of calling `setGroup`, even if this handle was the\n * most recent handle to set the selection of the group.\n *\n * The group being switched to (if any) will also not have its selection value\n * modified as a result of calling `setGroup`. If you want to set the\n * selection value of the new group, call `set` explicitly.\n *\n * @param {string} group - The name of the Crosstalk group, or null (or\n * undefined) to clear the group.\n */\n setGroup(group) {\n // If group is unchanged, do nothing\n if (this._group === group)\n return;\n // Treat null, undefined, and other falsy values the same\n if (!this._group && !group)\n return;\n\n if (this._var) {\n this._var.off(\"change\", this._varOnChangeSub);\n this._var = null;\n this._varOnChangeSub = null;\n }\n\n this._group = group;\n\n if (group) {\n this._var = grp(group).var(\"selection\");\n let sub = this._var.on(\"change\", (e) => {\n this._eventRelay.trigger(\"change\", e, this);\n });\n this._varOnChangeSub = sub;\n }\n }\n\n /**\n * Retrieves the current selection for the group represented by this\n * `SelectionHandle`.\n *\n * - If no selection is active, then this value will be falsy.\n * - If a selection is active, but no data points are selected, then this\n * value will be an empty array.\n * - If a selection is active, and data points are selected, then the keys\n * of the selected data points will be present in the array.\n */\n get value() {\n return this._var ? this._var.get() : null;\n }\n\n /**\n * Combines the given `extraInfo` (if any) with the handle's default\n * `_extraInfo` (if any).\n * @private\n */\n _mergeExtraInfo(extraInfo) {\n // Important incidental effect: shallow clone is returned\n return util.extend({},\n this._extraInfo ? this._extraInfo : null,\n extraInfo ? extraInfo : null);\n }\n\n /**\n * Overwrites the current selection for the group, and raises the `\"change\"`\n * event among all of the group's '`SelectionHandle` instances (including\n * this one).\n *\n * @fires SelectionHandle#change\n * @param {string[]} selectedKeys - Falsy, empty array, or array of keys (see\n * {@link SelectionHandle#value}).\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `SelectionHandle` constructor).\n */\n set(selectedKeys, extraInfo) {\n if (this._var)\n this._var.set(selectedKeys, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * Overwrites the current selection for the group, and raises the `\"change\"`\n * event among all of the group's '`SelectionHandle` instances (including\n * this one).\n *\n * @fires SelectionHandle#change\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any that were passed\n * into the `SelectionHandle` constructor).\n */\n clear(extraInfo) {\n if (this._var)\n this.set(void 0, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * Subscribes to events on this `SelectionHandle`.\n *\n * @param {string} eventType - Indicates the type of events to listen to.\n * Currently, only `\"change\"` is supported.\n * @param {SelectionHandle~listener} listener - The callback function that\n * will be invoked when the event occurs.\n * @return {string} - A token to pass to {@link SelectionHandle#off} to cancel\n * this subscription.\n */\n on(eventType, listener) {\n return this._emitter.on(eventType, listener);\n }\n\n /**\n * Cancels event subscriptions created by {@link SelectionHandle#on}.\n *\n * @param {string} eventType - The type of event to unsubscribe.\n * @param {string|SelectionHandle~listener} listener - Either the callback\n * function previously passed into {@link SelectionHandle#on}, or the\n * string that was returned from {@link SelectionHandle#on}.\n */\n off(eventType, listener) {\n return this._emitter.off(eventType, listener);\n }\n\n /**\n * Shuts down the `SelectionHandle` object.\n *\n * Removes all event listeners that were added through this handle.\n */\n close() {\n this._emitter.removeAllListeners();\n this.setGroup(null);\n }\n}\n\n/**\n * @callback SelectionHandle~listener\n * @param {Object} event - An object containing details of the event. For\n * `\"change\"` events, this includes the properties `value` (the new\n * value of the selection, or `undefined` if no selection is active),\n * `oldValue` (the previous value of the selection), and `sender` (the\n * `SelectionHandle` instance that made the change).\n */\n\n/**\n * @event SelectionHandle#change\n * @type {object}\n * @property {object} value - The new value of the selection, or `undefined`\n * if no selection is active.\n * @property {object} oldValue - The previous value of the selection.\n * @property {SelectionHandle} sender - The `SelectionHandle` instance that\n * changed the value.\n */\n","export function extend(target, ...sources) {\n for (let i = 0; i < sources.length; i++) {\n let src = sources[i];\n if (typeof(src) === \"undefined\" || src === null)\n continue;\n\n for (let key in src) {\n if (src.hasOwnProperty(key)) {\n target[key] = src[key];\n }\n }\n }\n return target;\n}\n\nexport function checkSorted(list) {\n for (let i = 1; i < list.length; i++) {\n if (list[i] <= list[i-1]) {\n throw new Error(\"List is not sorted or contains duplicate\");\n }\n }\n}\n\nexport function diffSortedLists(a, b) {\n let i_a = 0;\n let i_b = 0;\n\n if (!a) a = [];\n if (!b) b = [];\n\n let a_only = [];\n let b_only = [];\n\n checkSorted(a);\n checkSorted(b);\n\n while (i_a < a.length && i_b < b.length) {\n if (a[i_a] === b[i_b]) {\n i_a++;\n i_b++;\n } else if (a[i_a] < b[i_b]) {\n a_only.push(a[i_a++]);\n } else {\n b_only.push(b[i_b++]);\n }\n }\n\n if (i_a < a.length)\n a_only = a_only.concat(a.slice(i_a));\n if (i_b < b.length)\n b_only = b_only.concat(b.slice(i_b));\n return {\n removed: a_only,\n added: b_only\n };\n}\n\n// Convert from wide: { colA: [1,2,3], colB: [4,5,6], ... }\n// to long: [ {colA: 1, colB: 4}, {colA: 2, colB: 5}, ... ]\nexport function dataframeToD3(df) {\n let names = [];\n let length;\n for (let name in df) {\n if (df.hasOwnProperty(name))\n names.push(name);\n if (typeof(df[name]) !== \"object\" || typeof(df[name].length) === \"undefined\") {\n throw new Error(\"All fields must be arrays\");\n } else if (typeof(length) !== \"undefined\" && length !== df[name].length) {\n throw new Error(\"All fields must be arrays of the same length\");\n }\n length = df[name].length;\n }\n let results = [];\n let item;\n for (let row = 0; row < length; row++) {\n item = {};\n for (let col = 0; col < names.length; col++) {\n item[names[col]] = df[names[col]][row];\n }\n results.push(item);\n }\n return results;\n}\n\n/**\n * Keeps track of all event listener additions/removals and lets all active\n * listeners be removed with a single operation.\n *\n * @private\n */\nexport class SubscriptionTracker {\n constructor(emitter) {\n this._emitter = emitter;\n this._subs = {};\n }\n\n on(eventType, listener) {\n let sub = this._emitter.on(eventType, listener);\n this._subs[sub] = eventType;\n return sub;\n }\n\n off(eventType, listener) {\n let sub = this._emitter.off(eventType, listener);\n if (sub) {\n delete this._subs[sub];\n }\n return sub;\n }\n\n removeAllListeners() {\n let current_subs = this._subs;\n this._subs = {};\n Object.keys(current_subs).forEach((sub) => {\n this._emitter.off(current_subs[sub], sub);\n });\n }\n}\n","import Events from \"./events\";\n\nexport default class Var {\n constructor(group, name, /*optional*/ value) {\n this._group = group;\n this._name = name;\n this._value = value;\n this._events = new Events();\n }\n\n get() {\n return this._value;\n }\n\n set(value, /*optional*/ event) {\n if (this._value === value) {\n // Do nothing; the value hasn't changed\n return;\n }\n let oldValue = this._value;\n this._value = value;\n // Alert JavaScript listeners that the value has changed\n let evt = {};\n if (event && typeof(event) === \"object\") {\n for (let k in event) {\n if (event.hasOwnProperty(k))\n evt[k] = event[k];\n }\n }\n evt.oldValue = oldValue;\n evt.value = value;\n this._events.trigger(\"change\", evt, this);\n\n // TODO: Make this extensible, to let arbitrary back-ends know that\n // something has changed\n if (global.Shiny && global.Shiny.onInputChange) {\n global.Shiny.onInputChange(\n \".clientValue-\" +\n (this._group.name !== null ? this._group.name + \"-\" : \"\") +\n this._name,\n typeof(value) === \"undefined\" ? null : value\n );\n }\n }\n\n on(eventType, listener) {\n return this._events.on(eventType, listener);\n }\n\n off(eventType, listener) {\n return this._events.off(eventType, listener);\n }\n}\n"]} \ No newline at end of file diff --git a/docs/articles/get_started_files/crosstalk-1.2.1/scss/crosstalk.scss b/docs/articles/get_started_files/crosstalk-1.2.1/scss/crosstalk.scss deleted file mode 100644 index 3566561..0000000 --- a/docs/articles/get_started_files/crosstalk-1.2.1/scss/crosstalk.scss +++ /dev/null @@ -1,75 +0,0 @@ -/* Adjust margins outwards, so column contents line up with the edges of the - parent of container-fluid. */ -.container-fluid.crosstalk-bscols { - margin-left: -30px; - margin-right: -30px; - white-space: normal; -} - -/* But don't adjust the margins outwards if we're directly under the body, - i.e. we were the top-level of something at the console. */ -body > .container-fluid.crosstalk-bscols { - margin-left: auto; - margin-right: auto; -} - -.crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column { - display: inline-block; - padding-right: 12px; - vertical-align: top; -} - -@media only screen and (max-width:480px) { - .crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column { - display: block; - padding-right: inherit; - } -} - -/* Relevant BS3 styles to make filter_checkbox() look reasonable without Bootstrap */ -.crosstalk-input { - margin-bottom: 15px; /* a la .form-group */ - .control-label { - margin-bottom: 0; - vertical-align: middle; - } - input[type="checkbox"] { - margin: 4px 0 0; - margin-top: 1px; - line-height: normal; - } - .checkbox { - position: relative; - display: block; - margin-top: 10px; - margin-bottom: 10px; - } - .checkbox > label{ - padding-left: 20px; - margin-bottom: 0; - font-weight: 400; - cursor: pointer; - } - .checkbox input[type="checkbox"], - .checkbox-inline input[type="checkbox"] { - position: absolute; - margin-top: 2px; - margin-left: -20px; - } - .checkbox + .checkbox { - margin-top: -5px; - } - .checkbox-inline { - position: relative; - display: inline-block; - padding-left: 20px; - margin-bottom: 0; - font-weight: 400; - vertical-align: middle; - cursor: pointer; - } - .checkbox-inline + .checkbox-inline { - margin-top: 0; - margin-left: 10px; - } -} diff --git a/docs/articles/get_started_files/crosstalk-1.2.2/css/crosstalk.min.css b/docs/articles/get_started_files/crosstalk-1.2.2/css/crosstalk.min.css deleted file mode 100644 index 6b45382..0000000 --- a/docs/articles/get_started_files/crosstalk-1.2.2/css/crosstalk.min.css +++ /dev/null @@ -1 +0,0 @@ -.container-fluid.crosstalk-bscols{margin-left:-30px;margin-right:-30px;white-space:normal}body>.container-fluid.crosstalk-bscols{margin-left:auto;margin-right:auto}.crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column{display:inline-block;padding-right:12px;vertical-align:top}@media only screen and (max-width: 480px){.crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column{display:block;padding-right:inherit}}.crosstalk-input{margin-bottom:15px}.crosstalk-input .control-label{margin-bottom:0;vertical-align:middle}.crosstalk-input input[type="checkbox"]{margin:4px 0 0;margin-top:1px;line-height:normal}.crosstalk-input .checkbox{position:relative;display:block;margin-top:10px;margin-bottom:10px}.crosstalk-input .checkbox>label{padding-left:20px;margin-bottom:0;font-weight:400;cursor:pointer}.crosstalk-input .checkbox input[type="checkbox"],.crosstalk-input .checkbox-inline input[type="checkbox"]{position:absolute;margin-top:2px;margin-left:-20px}.crosstalk-input .checkbox+.checkbox{margin-top:-5px}.crosstalk-input .checkbox-inline{position:relative;display:inline-block;padding-left:20px;margin-bottom:0;font-weight:400;vertical-align:middle;cursor:pointer}.crosstalk-input .checkbox-inline+.checkbox-inline{margin-top:0;margin-left:10px} diff --git a/docs/articles/get_started_files/crosstalk-1.2.2/js/crosstalk.js b/docs/articles/get_started_files/crosstalk-1.2.2/js/crosstalk.js deleted file mode 100644 index fd9eb53..0000000 --- a/docs/articles/get_started_files/crosstalk-1.2.2/js/crosstalk.js +++ /dev/null @@ -1,1474 +0,0 @@ -(function(){function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require=="function"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);var f=new Error("Cannot find module '"+o+"'");throw f.code="MODULE_NOT_FOUND",f}var l=n[o]={exports:{}};t[o][0].call(l.exports,function(e){var n=t[o][1][e];return s(n?n:e)},l,l.exports,e,t,n,r)}return n[o].exports}var i=typeof require=="function"&&require;for(var o=0;o b) { - return 1; - } -} - -/** - * @private - */ - -var FilterSet = function () { - function FilterSet() { - _classCallCheck(this, FilterSet); - - this.reset(); - } - - _createClass(FilterSet, [{ - key: "reset", - value: function reset() { - // Key: handle ID, Value: array of selected keys, or null - this._handles = {}; - // Key: key string, Value: count of handles that include it - this._keys = {}; - this._value = null; - this._activeHandles = 0; - } - }, { - key: "update", - value: function update(handleId, keys) { - if (keys !== null) { - keys = keys.slice(0); // clone before sorting - keys.sort(naturalComparator); - } - - var _diffSortedLists = (0, _util.diffSortedLists)(this._handles[handleId], keys), - added = _diffSortedLists.added, - removed = _diffSortedLists.removed; - - this._handles[handleId] = keys; - - for (var i = 0; i < added.length; i++) { - this._keys[added[i]] = (this._keys[added[i]] || 0) + 1; - } - for (var _i = 0; _i < removed.length; _i++) { - this._keys[removed[_i]]--; - } - - this._updateValue(keys); - } - - /** - * @param {string[]} keys Sorted array of strings that indicate - * a superset of possible keys. - * @private - */ - - }, { - key: "_updateValue", - value: function _updateValue() { - var keys = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : this._allKeys; - - var handleCount = Object.keys(this._handles).length; - if (handleCount === 0) { - this._value = null; - } else { - this._value = []; - for (var i = 0; i < keys.length; i++) { - var count = this._keys[keys[i]]; - if (count === handleCount) { - this._value.push(keys[i]); - } - } - } - } - }, { - key: "clear", - value: function clear(handleId) { - if (typeof this._handles[handleId] === "undefined") { - return; - } - - var keys = this._handles[handleId]; - if (!keys) { - keys = []; - } - - for (var i = 0; i < keys.length; i++) { - this._keys[keys[i]]--; - } - delete this._handles[handleId]; - - this._updateValue(); - } - }, { - key: "value", - get: function get() { - return this._value; - } - }, { - key: "_allKeys", - get: function get() { - var allKeys = Object.keys(this._keys); - allKeys.sort(naturalComparator); - return allKeys; - } - }]); - - return FilterSet; -}(); - -exports.default = FilterSet; - -},{"./util":11}],4:[function(require,module,exports){ -(function (global){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); - -var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }(); - -var _typeof = typeof Symbol === "function" && typeof Symbol.iterator === "symbol" ? function (obj) { return typeof obj; } : function (obj) { return obj && typeof Symbol === "function" && obj.constructor === Symbol && obj !== Symbol.prototype ? "symbol" : typeof obj; }; - -exports.default = group; - -var _var2 = require("./var"); - -var _var3 = _interopRequireDefault(_var2); - -function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } - -function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } - -// Use a global so that multiple copies of crosstalk.js can be loaded and still -// have groups behave as singletons across all copies. -global.__crosstalk_groups = global.__crosstalk_groups || {}; -var groups = global.__crosstalk_groups; - -function group(groupName) { - if (groupName && typeof groupName === "string") { - if (!groups.hasOwnProperty(groupName)) { - groups[groupName] = new Group(groupName); - } - return groups[groupName]; - } else if ((typeof groupName === "undefined" ? "undefined" : _typeof(groupName)) === "object" && groupName._vars && groupName.var) { - // Appears to already be a group object - return groupName; - } else if (Array.isArray(groupName) && groupName.length == 1 && typeof groupName[0] === "string") { - return group(groupName[0]); - } else { - throw new Error("Invalid groupName argument"); - } -} - -var Group = function () { - function Group(name) { - _classCallCheck(this, Group); - - this.name = name; - this._vars = {}; - } - - _createClass(Group, [{ - key: "var", - value: function _var(name) { - if (!name || typeof name !== "string") { - throw new Error("Invalid var name"); - } - - if (!this._vars.hasOwnProperty(name)) this._vars[name] = new _var3.default(this, name); - return this._vars[name]; - } - }, { - key: "has", - value: function has(name) { - if (!name || typeof name !== "string") { - throw new Error("Invalid var name"); - } - - return this._vars.hasOwnProperty(name); - } - }]); - - return Group; -}(); - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./var":12}],5:[function(require,module,exports){ -(function (global){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); - -var _group = require("./group"); - -var _group2 = _interopRequireDefault(_group); - -var _selection = require("./selection"); - -var _filter = require("./filter"); - -var _input = require("./input"); - -require("./input_selectize"); - -require("./input_checkboxgroup"); - -require("./input_slider"); - -function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } - -var defaultGroup = (0, _group2.default)("default"); - -function var_(name) { - return defaultGroup.var(name); -} - -function has(name) { - return defaultGroup.has(name); -} - -if (global.Shiny) { - global.Shiny.addCustomMessageHandler("update-client-value", function (message) { - if (typeof message.group === "string") { - (0, _group2.default)(message.group).var(message.name).set(message.value); - } else { - var_(message.name).set(message.value); - } - }); -} - -var crosstalk = { - group: _group2.default, - var: var_, - has: has, - SelectionHandle: _selection.SelectionHandle, - FilterHandle: _filter.FilterHandle, - bind: _input.bind -}; - -/** - * @namespace crosstalk - */ -exports.default = crosstalk; - -global.crosstalk = crosstalk; - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./filter":2,"./group":4,"./input":6,"./input_checkboxgroup":7,"./input_selectize":8,"./input_slider":9,"./selection":10}],6:[function(require,module,exports){ -(function (global){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); -exports.register = register; -exports.bind = bind; -var $ = global.jQuery; - -var bindings = {}; - -function register(reg) { - bindings[reg.className] = reg; - if (global.document && global.document.readyState !== "complete") { - $(function () { - bind(); - }); - } else if (global.document) { - setTimeout(bind, 100); - } -} - -function bind() { - Object.keys(bindings).forEach(function (className) { - var binding = bindings[className]; - $("." + binding.className).not(".crosstalk-input-bound").each(function (i, el) { - bindInstance(binding, el); - }); - }); -} - -// Escape jQuery identifier -function $escape(val) { - return val.replace(/([!"#$%&'()*+,./:;<=>?@[\\\]^`{|}~])/g, "\\$1"); -} - -function bindEl(el) { - var $el = $(el); - Object.keys(bindings).forEach(function (className) { - if ($el.hasClass(className) && !$el.hasClass("crosstalk-input-bound")) { - var binding = bindings[className]; - bindInstance(binding, el); - } - }); -} - -function bindInstance(binding, el) { - var jsonEl = $(el).find("script[type='application/json'][data-for='" + $escape(el.id) + "']"); - var data = JSON.parse(jsonEl[0].innerText); - - var instance = binding.factory(el, data); - $(el).data("crosstalk-instance", instance); - $(el).addClass("crosstalk-input-bound"); -} - -if (global.Shiny) { - var inputBinding = new global.Shiny.InputBinding(); - var _$ = global.jQuery; - _$.extend(inputBinding, { - find: function find(scope) { - return _$(scope).find(".crosstalk-input"); - }, - initialize: function initialize(el) { - if (!_$(el).hasClass("crosstalk-input-bound")) { - bindEl(el); - } - }, - getId: function getId(el) { - return el.id; - }, - getValue: function getValue(el) {}, - setValue: function setValue(el, value) {}, - receiveMessage: function receiveMessage(el, data) {}, - subscribe: function subscribe(el, callback) { - _$(el).data("crosstalk-instance").resume(); - }, - unsubscribe: function unsubscribe(el) { - _$(el).data("crosstalk-instance").suspend(); - } - }); - global.Shiny.inputBindings.register(inputBinding, "crosstalk.inputBinding"); -} - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{}],7:[function(require,module,exports){ -(function (global){ -"use strict"; - -var _input = require("./input"); - -var input = _interopRequireWildcard(_input); - -var _filter = require("./filter"); - -function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } } - -var $ = global.jQuery; - -input.register({ - className: "crosstalk-input-checkboxgroup", - - factory: function factory(el, data) { - /* - * map: {"groupA": ["keyA", "keyB", ...], ...} - * group: "ct-groupname" - */ - var ctHandle = new _filter.FilterHandle(data.group); - - var lastKnownKeys = void 0; - var $el = $(el); - $el.on("change", "input[type='checkbox']", function () { - var checked = $el.find("input[type='checkbox']:checked"); - if (checked.length === 0) { - lastKnownKeys = null; - ctHandle.clear(); - } else { - var keys = {}; - checked.each(function () { - data.map[this.value].forEach(function (key) { - keys[key] = true; - }); - }); - var keyArray = Object.keys(keys); - keyArray.sort(); - lastKnownKeys = keyArray; - ctHandle.set(keyArray); - } - }); - - return { - suspend: function suspend() { - ctHandle.clear(); - }, - resume: function resume() { - if (lastKnownKeys) ctHandle.set(lastKnownKeys); - } - }; - } -}); - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./filter":2,"./input":6}],8:[function(require,module,exports){ -(function (global){ -"use strict"; - -var _input = require("./input"); - -var input = _interopRequireWildcard(_input); - -var _util = require("./util"); - -var util = _interopRequireWildcard(_util); - -var _filter = require("./filter"); - -function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } } - -var $ = global.jQuery; - -input.register({ - className: "crosstalk-input-select", - - factory: function factory(el, data) { - /* - * items: {value: [...], label: [...]} - * map: {"groupA": ["keyA", "keyB", ...], ...} - * group: "ct-groupname" - */ - - var first = [{ value: "", label: "(All)" }]; - var items = util.dataframeToD3(data.items); - var opts = { - options: first.concat(items), - valueField: "value", - labelField: "label", - searchField: "label" - }; - - var select = $(el).find("select")[0]; - - var selectize = $(select).selectize(opts)[0].selectize; - - var ctHandle = new _filter.FilterHandle(data.group); - - var lastKnownKeys = void 0; - selectize.on("change", function () { - if (selectize.items.length === 0) { - lastKnownKeys = null; - ctHandle.clear(); - } else { - var keys = {}; - selectize.items.forEach(function (group) { - data.map[group].forEach(function (key) { - keys[key] = true; - }); - }); - var keyArray = Object.keys(keys); - keyArray.sort(); - lastKnownKeys = keyArray; - ctHandle.set(keyArray); - } - }); - - return { - suspend: function suspend() { - ctHandle.clear(); - }, - resume: function resume() { - if (lastKnownKeys) ctHandle.set(lastKnownKeys); - } - }; - } -}); - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./filter":2,"./input":6,"./util":11}],9:[function(require,module,exports){ -(function (global){ -"use strict"; - -var _slicedToArray = function () { function sliceIterator(arr, i) { var _arr = []; var _n = true; var _d = false; var _e = undefined; try { for (var _i = arr[Symbol.iterator](), _s; !(_n = (_s = _i.next()).done); _n = true) { _arr.push(_s.value); if (i && _arr.length === i) break; } } catch (err) { _d = true; _e = err; } finally { try { if (!_n && _i["return"]) _i["return"](); } finally { if (_d) throw _e; } } return _arr; } return function (arr, i) { if (Array.isArray(arr)) { return arr; } else if (Symbol.iterator in Object(arr)) { return sliceIterator(arr, i); } else { throw new TypeError("Invalid attempt to destructure non-iterable instance"); } }; }(); - -var _input = require("./input"); - -var input = _interopRequireWildcard(_input); - -var _filter = require("./filter"); - -function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } } - -var $ = global.jQuery; -var strftime = global.strftime; - -input.register({ - className: "crosstalk-input-slider", - - factory: function factory(el, data) { - /* - * map: {"groupA": ["keyA", "keyB", ...], ...} - * group: "ct-groupname" - */ - var ctHandle = new _filter.FilterHandle(data.group); - - var opts = {}; - var $el = $(el).find("input"); - var dataType = $el.data("data-type"); - var timeFormat = $el.data("time-format"); - var round = $el.data("round"); - var timeFormatter = void 0; - - // Set up formatting functions - if (dataType === "date") { - timeFormatter = strftime.utc(); - opts.prettify = function (num) { - return timeFormatter(timeFormat, new Date(num)); - }; - } else if (dataType === "datetime") { - var timezone = $el.data("timezone"); - if (timezone) timeFormatter = strftime.timezone(timezone);else timeFormatter = strftime; - - opts.prettify = function (num) { - return timeFormatter(timeFormat, new Date(num)); - }; - } else if (dataType === "number") { - if (typeof round !== "undefined") opts.prettify = function (num) { - var factor = Math.pow(10, round); - return Math.round(num * factor) / factor; - }; - } - - $el.ionRangeSlider(opts); - - function getValue() { - var result = $el.data("ionRangeSlider").result; - - // Function for converting numeric value from slider to appropriate type. - var convert = void 0; - var dataType = $el.data("data-type"); - if (dataType === "date") { - convert = function convert(val) { - return formatDateUTC(new Date(+val)); - }; - } else if (dataType === "datetime") { - convert = function convert(val) { - // Convert ms to s - return +val / 1000; - }; - } else { - convert = function convert(val) { - return +val; - }; - } - - if ($el.data("ionRangeSlider").options.type === "double") { - return [convert(result.from), convert(result.to)]; - } else { - return convert(result.from); - } - } - - var lastKnownKeys = null; - - $el.on("change.crosstalkSliderInput", function (event) { - if (!$el.data("updating") && !$el.data("animating")) { - var _getValue = getValue(), - _getValue2 = _slicedToArray(_getValue, 2), - from = _getValue2[0], - to = _getValue2[1]; - - var keys = []; - for (var i = 0; i < data.values.length; i++) { - var val = data.values[i]; - if (val >= from && val <= to) { - keys.push(data.keys[i]); - } - } - keys.sort(); - ctHandle.set(keys); - lastKnownKeys = keys; - } - }); - - // let $el = $(el); - // $el.on("change", "input[type="checkbox"]", function() { - // let checked = $el.find("input[type="checkbox"]:checked"); - // if (checked.length === 0) { - // ctHandle.clear(); - // } else { - // let keys = {}; - // checked.each(function() { - // data.map[this.value].forEach(function(key) { - // keys[key] = true; - // }); - // }); - // let keyArray = Object.keys(keys); - // keyArray.sort(); - // ctHandle.set(keyArray); - // } - // }); - - return { - suspend: function suspend() { - ctHandle.clear(); - }, - resume: function resume() { - if (lastKnownKeys) ctHandle.set(lastKnownKeys); - } - }; - } -}); - -// Convert a number to a string with leading zeros -function padZeros(n, digits) { - var str = n.toString(); - while (str.length < digits) { - str = "0" + str; - }return str; -} - -// Given a Date object, return a string in yyyy-mm-dd format, using the -// UTC date. This may be a day off from the date in the local time zone. -function formatDateUTC(date) { - if (date instanceof Date) { - return date.getUTCFullYear() + "-" + padZeros(date.getUTCMonth() + 1, 2) + "-" + padZeros(date.getUTCDate(), 2); - } else { - return null; - } -} - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./filter":2,"./input":6}],10:[function(require,module,exports){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); -exports.SelectionHandle = undefined; - -var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }(); - -var _events = require("./events"); - -var _events2 = _interopRequireDefault(_events); - -var _group = require("./group"); - -var _group2 = _interopRequireDefault(_group); - -var _util = require("./util"); - -var util = _interopRequireWildcard(_util); - -function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } } - -function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } - -function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } - -/** - * Use this class to read and write (and listen for changes to) the selection - * for a Crosstalk group. This is intended to be used for linked brushing. - * - * If two (or more) `SelectionHandle` instances in the same webpage share the - * same group name, they will share the same state. Setting the selection using - * one `SelectionHandle` instance will result in the `value` property instantly - * changing across the others, and `"change"` event listeners on all instances - * (including the one that initiated the sending) will fire. - * - * @param {string} [group] - The name of the Crosstalk group, or if none, - * null or undefined (or any other falsy value). This can be changed later - * via the [SelectionHandle#setGroup](#setGroup) method. - * @param {Object} [extraInfo] - An object whose properties will be copied to - * the event object whenever an event is emitted. - */ -var SelectionHandle = exports.SelectionHandle = function () { - function SelectionHandle() { - var group = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : null; - var extraInfo = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : null; - - _classCallCheck(this, SelectionHandle); - - this._eventRelay = new _events2.default(); - this._emitter = new util.SubscriptionTracker(this._eventRelay); - - // Name of the group we're currently tracking, if any. Can change over time. - this._group = null; - // The Var we're currently tracking, if any. Can change over time. - this._var = null; - // The event handler subscription we currently have on var.on("change"). - this._varOnChangeSub = null; - - this._extraInfo = util.extend({ sender: this }, extraInfo); - - this.setGroup(group); - } - - /** - * Changes the Crosstalk group membership of this SelectionHandle. The group - * being switched away from (if any) will not have its selection value - * modified as a result of calling `setGroup`, even if this handle was the - * most recent handle to set the selection of the group. - * - * The group being switched to (if any) will also not have its selection value - * modified as a result of calling `setGroup`. If you want to set the - * selection value of the new group, call `set` explicitly. - * - * @param {string} group - The name of the Crosstalk group, or null (or - * undefined) to clear the group. - */ - - - _createClass(SelectionHandle, [{ - key: "setGroup", - value: function setGroup(group) { - var _this = this; - - // If group is unchanged, do nothing - if (this._group === group) return; - // Treat null, undefined, and other falsy values the same - if (!this._group && !group) return; - - if (this._var) { - this._var.off("change", this._varOnChangeSub); - this._var = null; - this._varOnChangeSub = null; - } - - this._group = group; - - if (group) { - this._var = (0, _group2.default)(group).var("selection"); - var sub = this._var.on("change", function (e) { - _this._eventRelay.trigger("change", e, _this); - }); - this._varOnChangeSub = sub; - } - } - - /** - * Retrieves the current selection for the group represented by this - * `SelectionHandle`. - * - * - If no selection is active, then this value will be falsy. - * - If a selection is active, but no data points are selected, then this - * value will be an empty array. - * - If a selection is active, and data points are selected, then the keys - * of the selected data points will be present in the array. - */ - - }, { - key: "_mergeExtraInfo", - - - /** - * Combines the given `extraInfo` (if any) with the handle's default - * `_extraInfo` (if any). - * @private - */ - value: function _mergeExtraInfo(extraInfo) { - // Important incidental effect: shallow clone is returned - return util.extend({}, this._extraInfo ? this._extraInfo : null, extraInfo ? extraInfo : null); - } - - /** - * Overwrites the current selection for the group, and raises the `"change"` - * event among all of the group's '`SelectionHandle` instances (including - * this one). - * - * @fires SelectionHandle#change - * @param {string[]} selectedKeys - Falsy, empty array, or array of keys (see - * {@link SelectionHandle#value}). - * @param {Object} [extraInfo] - Extra properties to be included on the event - * object that's passed to listeners (in addition to any options that were - * passed into the `SelectionHandle` constructor). - */ - - }, { - key: "set", - value: function set(selectedKeys, extraInfo) { - if (this._var) this._var.set(selectedKeys, this._mergeExtraInfo(extraInfo)); - } - - /** - * Overwrites the current selection for the group, and raises the `"change"` - * event among all of the group's '`SelectionHandle` instances (including - * this one). - * - * @fires SelectionHandle#change - * @param {Object} [extraInfo] - Extra properties to be included on the event - * object that's passed to listeners (in addition to any that were passed - * into the `SelectionHandle` constructor). - */ - - }, { - key: "clear", - value: function clear(extraInfo) { - if (this._var) this.set(void 0, this._mergeExtraInfo(extraInfo)); - } - - /** - * Subscribes to events on this `SelectionHandle`. - * - * @param {string} eventType - Indicates the type of events to listen to. - * Currently, only `"change"` is supported. - * @param {SelectionHandle~listener} listener - The callback function that - * will be invoked when the event occurs. - * @return {string} - A token to pass to {@link SelectionHandle#off} to cancel - * this subscription. - */ - - }, { - key: "on", - value: function on(eventType, listener) { - return this._emitter.on(eventType, listener); - } - - /** - * Cancels event subscriptions created by {@link SelectionHandle#on}. - * - * @param {string} eventType - The type of event to unsubscribe. - * @param {string|SelectionHandle~listener} listener - Either the callback - * function previously passed into {@link SelectionHandle#on}, or the - * string that was returned from {@link SelectionHandle#on}. - */ - - }, { - key: "off", - value: function off(eventType, listener) { - return this._emitter.off(eventType, listener); - } - - /** - * Shuts down the `SelectionHandle` object. - * - * Removes all event listeners that were added through this handle. - */ - - }, { - key: "close", - value: function close() { - this._emitter.removeAllListeners(); - this.setGroup(null); - } - }, { - key: "value", - get: function get() { - return this._var ? this._var.get() : null; - } - }]); - - return SelectionHandle; -}(); - -/** - * @callback SelectionHandle~listener - * @param {Object} event - An object containing details of the event. For - * `"change"` events, this includes the properties `value` (the new - * value of the selection, or `undefined` if no selection is active), - * `oldValue` (the previous value of the selection), and `sender` (the - * `SelectionHandle` instance that made the change). - */ - -/** - * @event SelectionHandle#change - * @type {object} - * @property {object} value - The new value of the selection, or `undefined` - * if no selection is active. - * @property {object} oldValue - The previous value of the selection. - * @property {SelectionHandle} sender - The `SelectionHandle` instance that - * changed the value. - */ - -},{"./events":1,"./group":4,"./util":11}],11:[function(require,module,exports){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); - -var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }(); - -var _typeof = typeof Symbol === "function" && typeof Symbol.iterator === "symbol" ? function (obj) { return typeof obj; } : function (obj) { return obj && typeof Symbol === "function" && obj.constructor === Symbol && obj !== Symbol.prototype ? "symbol" : typeof obj; }; - -exports.extend = extend; -exports.checkSorted = checkSorted; -exports.diffSortedLists = diffSortedLists; -exports.dataframeToD3 = dataframeToD3; - -function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } - -function extend(target) { - for (var _len = arguments.length, sources = Array(_len > 1 ? _len - 1 : 0), _key = 1; _key < _len; _key++) { - sources[_key - 1] = arguments[_key]; - } - - for (var i = 0; i < sources.length; i++) { - var src = sources[i]; - if (typeof src === "undefined" || src === null) continue; - - for (var key in src) { - if (src.hasOwnProperty(key)) { - target[key] = src[key]; - } - } - } - return target; -} - -function checkSorted(list) { - for (var i = 1; i < list.length; i++) { - if (list[i] <= list[i - 1]) { - throw new Error("List is not sorted or contains duplicate"); - } - } -} - -function diffSortedLists(a, b) { - var i_a = 0; - var i_b = 0; - - if (!a) a = []; - if (!b) b = []; - - var a_only = []; - var b_only = []; - - checkSorted(a); - checkSorted(b); - - while (i_a < a.length && i_b < b.length) { - if (a[i_a] === b[i_b]) { - i_a++; - i_b++; - } else if (a[i_a] < b[i_b]) { - a_only.push(a[i_a++]); - } else { - b_only.push(b[i_b++]); - } - } - - if (i_a < a.length) a_only = a_only.concat(a.slice(i_a)); - if (i_b < b.length) b_only = b_only.concat(b.slice(i_b)); - return { - removed: a_only, - added: b_only - }; -} - -// Convert from wide: { colA: [1,2,3], colB: [4,5,6], ... } -// to long: [ {colA: 1, colB: 4}, {colA: 2, colB: 5}, ... ] -function dataframeToD3(df) { - var names = []; - var length = void 0; - for (var name in df) { - if (df.hasOwnProperty(name)) names.push(name); - if (_typeof(df[name]) !== "object" || typeof df[name].length === "undefined") { - throw new Error("All fields must be arrays"); - } else if (typeof length !== "undefined" && length !== df[name].length) { - throw new Error("All fields must be arrays of the same length"); - } - length = df[name].length; - } - var results = []; - var item = void 0; - for (var row = 0; row < length; row++) { - item = {}; - for (var col = 0; col < names.length; col++) { - item[names[col]] = df[names[col]][row]; - } - results.push(item); - } - return results; -} - -/** - * Keeps track of all event listener additions/removals and lets all active - * listeners be removed with a single operation. - * - * @private - */ - -var SubscriptionTracker = exports.SubscriptionTracker = function () { - function SubscriptionTracker(emitter) { - _classCallCheck(this, SubscriptionTracker); - - this._emitter = emitter; - this._subs = {}; - } - - _createClass(SubscriptionTracker, [{ - key: "on", - value: function on(eventType, listener) { - var sub = this._emitter.on(eventType, listener); - this._subs[sub] = eventType; - return sub; - } - }, { - key: "off", - value: function off(eventType, listener) { - var sub = this._emitter.off(eventType, listener); - if (sub) { - delete this._subs[sub]; - } - return sub; - } - }, { - key: "removeAllListeners", - value: function removeAllListeners() { - var _this = this; - - var current_subs = this._subs; - this._subs = {}; - Object.keys(current_subs).forEach(function (sub) { - _this._emitter.off(current_subs[sub], sub); - }); - } - }]); - - return SubscriptionTracker; -}(); - -},{}],12:[function(require,module,exports){ -(function (global){ -"use strict"; - -Object.defineProperty(exports, "__esModule", { - value: true -}); - -var _typeof = typeof Symbol === "function" && typeof Symbol.iterator === "symbol" ? function (obj) { return typeof obj; } : function (obj) { return obj && typeof Symbol === "function" && obj.constructor === Symbol && obj !== Symbol.prototype ? "symbol" : typeof obj; }; - -var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }(); - -var _events = require("./events"); - -var _events2 = _interopRequireDefault(_events); - -function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; } - -function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } } - -var Var = function () { - function Var(group, name, /*optional*/value) { - _classCallCheck(this, Var); - - this._group = group; - this._name = name; - this._value = value; - this._events = new _events2.default(); - } - - _createClass(Var, [{ - key: "get", - value: function get() { - return this._value; - } - }, { - key: "set", - value: function set(value, /*optional*/event) { - if (this._value === value) { - // Do nothing; the value hasn't changed - return; - } - var oldValue = this._value; - this._value = value; - // Alert JavaScript listeners that the value has changed - var evt = {}; - if (event && (typeof event === "undefined" ? "undefined" : _typeof(event)) === "object") { - for (var k in event) { - if (event.hasOwnProperty(k)) evt[k] = event[k]; - } - } - evt.oldValue = oldValue; - evt.value = value; - this._events.trigger("change", evt, this); - - // TODO: Make this extensible, to let arbitrary back-ends know that - // something has changed - if (global.Shiny && global.Shiny.onInputChange) { - global.Shiny.onInputChange(".clientValue-" + (this._group.name !== null ? this._group.name + "-" : "") + this._name, typeof value === "undefined" ? null : value); - } - } - }, { - key: "on", - value: function on(eventType, listener) { - return this._events.on(eventType, listener); - } - }, { - key: "off", - value: function off(eventType, listener) { - return this._events.off(eventType, listener); - } - }]); - - return Var; -}(); - -exports.default = Var; - -}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {}) - -},{"./events":1}]},{},[5]) -//# sourceMappingURL=crosstalk.js.map diff --git a/docs/articles/get_started_files/crosstalk-1.2.2/js/crosstalk.js.map b/docs/articles/get_started_files/crosstalk-1.2.2/js/crosstalk.js.map deleted file mode 100644 index cff94f0..0000000 --- a/docs/articles/get_started_files/crosstalk-1.2.2/js/crosstalk.js.map +++ /dev/null @@ -1,37 +0,0 @@ -{ - "version": 3, - "sources": [ - "node_modules/browser-pack/_prelude.js", - "javascript/src/events.js", - "javascript/src/filter.js", - "javascript/src/filterset.js", - "javascript/src/group.js", - "javascript/src/index.js", - "javascript/src/input.js", - "javascript/src/input_checkboxgroup.js", - "javascript/src/input_selectize.js", - "javascript/src/input_slider.js", - "javascript/src/selection.js", - "javascript/src/util.js", - "javascript/src/var.js" - ], - "names": [], - "mappings": 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- "file": "generated.js", - "sourceRoot": "", - "sourcesContent": [ - "(function(){function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require==\"function\"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);var f=new Error(\"Cannot find module '\"+o+\"'\");throw f.code=\"MODULE_NOT_FOUND\",f}var l=n[o]={exports:{}};t[o][0].call(l.exports,function(e){var n=t[o][1][e];return s(n?n:e)},l,l.exports,e,t,n,r)}return n[o].exports}var i=typeof require==\"function\"&&require;for(var o=0;o {\n this._eventRelay.trigger(\"change\", e, this);\n });\n this._varOnChangeSub = sub;\n }\n }\n\n /**\n * Combine the given `extraInfo` (if any) with the handle's default\n * `_extraInfo` (if any).\n * @private\n */\n _mergeExtraInfo(extraInfo) {\n return util.extend({},\n this._extraInfo ? this._extraInfo : null,\n extraInfo ? extraInfo : null);\n }\n\n /**\n * Close the handle. This clears this handle's contribution to the filter set,\n * and unsubscribes all event listeners.\n */\n close() {\n this._emitter.removeAllListeners();\n this.clear();\n this.setGroup(null);\n }\n\n /**\n * Clear this handle's contribution to the filter set.\n *\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `FilterHandle` constructor).\n * \n * @fires FilterHandle#change\n */\n clear(extraInfo) {\n if (!this._filterSet)\n return;\n this._filterSet.clear(this._id);\n this._onChange(extraInfo);\n }\n\n /**\n * Set this handle's contribution to the filter set. This array should consist\n * of the keys of the rows that _should_ be displayed; any keys that are not\n * present in the array will be considered _filtered out_. Note that multiple\n * `FilterHandle` instances in the group may each contribute an array of keys,\n * and only those keys that appear in _all_ of the arrays make it through the\n * filter.\n *\n * @param {string[]} keys - Empty array, or array of keys. To clear the\n * filter, don't pass an empty array; instead, use the\n * {@link FilterHandle#clear} method.\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `FilterHandle` constructor).\n * \n * @fires FilterHandle#change\n */\n set(keys, extraInfo) {\n if (!this._filterSet)\n return;\n this._filterSet.update(this._id, keys);\n this._onChange(extraInfo);\n }\n\n /**\n * @return {string[]|null} - Either: 1) an array of keys that made it through\n * all of the `FilterHandle` instances, or, 2) `null`, which means no filter\n * is being applied (all data should be displayed).\n */\n get filteredKeys() {\n return this._filterSet ? this._filterSet.value : null;\n }\n\n /**\n * Subscribe to events on this `FilterHandle`.\n *\n * @param {string} eventType - Indicates the type of events to listen to.\n * Currently, only `\"change\"` is supported.\n * @param {FilterHandle~listener} listener - The callback function that\n * will be invoked when the event occurs.\n * @return {string} - A token to pass to {@link FilterHandle#off} to cancel\n * this subscription.\n */\n on(eventType, listener) {\n return this._emitter.on(eventType, listener);\n }\n\n /**\n * Cancel event subscriptions created by {@link FilterHandle#on}.\n *\n * @param {string} eventType - The type of event to unsubscribe.\n * @param {string|FilterHandle~listener} listener - Either the callback\n * function previously passed into {@link FilterHandle#on}, or the\n * string that was returned from {@link FilterHandle#on}.\n */\n off(eventType, listener) {\n return this._emitter.off(eventType, listener);\n }\n\n _onChange(extraInfo) {\n if (!this._filterSet)\n return;\n this._filterVar.set(this._filterSet.value, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * @callback FilterHandle~listener\n * @param {Object} event - An object containing details of the event. For\n * `\"change\"` events, this includes the properties `value` (the new\n * value of the filter set, or `null` if no filter set is active),\n * `oldValue` (the previous value of the filter set), and `sender` (the\n * `FilterHandle` instance that made the change).\n */\n\n}\n\n/**\n * @event FilterHandle#change\n * @type {object}\n * @property {object} value - The new value of the filter set, or `null`\n * if no filter set is active.\n * @property {object} oldValue - The previous value of the filter set.\n * @property {FilterHandle} sender - The `FilterHandle` instance that\n * changed the value.\n */\n", - "import { diffSortedLists } from \"./util\";\n\nfunction naturalComparator(a, b) {\n if (a === b) {\n return 0;\n } else if (a < b) {\n return -1;\n } else if (a > b) {\n return 1;\n }\n}\n\n/**\n * @private\n */\nexport default class FilterSet {\n constructor() {\n this.reset();\n }\n\n reset() {\n // Key: handle ID, Value: array of selected keys, or null\n this._handles = {};\n // Key: key string, Value: count of handles that include it\n this._keys = {};\n this._value = null;\n this._activeHandles = 0;\n }\n\n get value() {\n return this._value;\n }\n\n update(handleId, keys) {\n if (keys !== null) {\n keys = keys.slice(0); // clone before sorting\n keys.sort(naturalComparator);\n }\n\n let {added, removed} = diffSortedLists(this._handles[handleId], keys);\n this._handles[handleId] = keys;\n\n for (let i = 0; i < added.length; i++) {\n this._keys[added[i]] = (this._keys[added[i]] || 0) + 1;\n }\n for (let i = 0; i < removed.length; i++) {\n this._keys[removed[i]]--;\n }\n\n this._updateValue(keys);\n }\n\n /**\n * @param {string[]} keys Sorted array of strings that indicate\n * a superset of possible keys.\n * @private\n */\n _updateValue(keys = this._allKeys) {\n let handleCount = Object.keys(this._handles).length;\n if (handleCount === 0) {\n this._value = null;\n } else {\n this._value = [];\n for (let i = 0; i < keys.length; i++) {\n let count = this._keys[keys[i]];\n if (count === handleCount) {\n this._value.push(keys[i]);\n }\n }\n }\n }\n\n clear(handleId) {\n if (typeof(this._handles[handleId]) === \"undefined\") {\n return;\n }\n\n let keys = this._handles[handleId];\n if (!keys) {\n keys = [];\n }\n\n for (let i = 0; i < keys.length; i++) {\n this._keys[keys[i]]--;\n }\n delete this._handles[handleId];\n\n this._updateValue();\n }\n\n get _allKeys() {\n let allKeys = Object.keys(this._keys);\n allKeys.sort(naturalComparator);\n return allKeys;\n }\n}\n", - "import Var from \"./var\";\n\n// Use a global so that multiple copies of crosstalk.js can be loaded and still\n// have groups behave as singletons across all copies.\nglobal.__crosstalk_groups = global.__crosstalk_groups || {};\nlet groups = global.__crosstalk_groups;\n\nexport default function group(groupName) {\n if (groupName && typeof(groupName) === \"string\") {\n if (!groups.hasOwnProperty(groupName)) {\n groups[groupName] = new Group(groupName);\n }\n return groups[groupName];\n } else if (typeof(groupName) === \"object\" && groupName._vars && groupName.var) {\n // Appears to already be a group object\n return groupName;\n } else if (Array.isArray(groupName) &&\n groupName.length == 1 &&\n typeof(groupName[0]) === \"string\") {\n return group(groupName[0]);\n } else {\n throw new Error(\"Invalid groupName argument\");\n }\n}\n\nclass Group {\n constructor(name) {\n this.name = name;\n this._vars = {};\n }\n\n var(name) {\n if (!name || typeof(name) !== \"string\") {\n throw new Error(\"Invalid var name\");\n }\n\n if (!this._vars.hasOwnProperty(name))\n this._vars[name] = new Var(this, name);\n return this._vars[name];\n }\n\n has(name) {\n if (!name || typeof(name) !== \"string\") {\n throw new Error(\"Invalid var name\");\n }\n\n return this._vars.hasOwnProperty(name);\n }\n}\n", - "import group from \"./group\";\nimport { SelectionHandle } from \"./selection\";\nimport { FilterHandle } from \"./filter\";\nimport { bind } from \"./input\";\nimport \"./input_selectize\";\nimport \"./input_checkboxgroup\";\nimport \"./input_slider\";\n\nconst defaultGroup = group(\"default\");\n\nfunction var_(name) {\n return defaultGroup.var(name);\n}\n\nfunction has(name) {\n return defaultGroup.has(name);\n}\n\nif (global.Shiny) {\n global.Shiny.addCustomMessageHandler(\"update-client-value\", function(message) {\n if (typeof(message.group) === \"string\") {\n group(message.group).var(message.name).set(message.value);\n } else {\n var_(message.name).set(message.value);\n }\n });\n}\n\nconst crosstalk = {\n group: group,\n var: var_,\n has: has,\n SelectionHandle: SelectionHandle,\n FilterHandle: FilterHandle,\n bind: bind\n};\n\n/**\n * @namespace crosstalk\n */\nexport default crosstalk;\nglobal.crosstalk = crosstalk;\n", - "let $ = global.jQuery;\n\nlet bindings = {};\n\nexport function register(reg) {\n bindings[reg.className] = reg;\n if (global.document && global.document.readyState !== \"complete\") {\n $(() => {\n bind();\n });\n } else if (global.document) {\n setTimeout(bind, 100);\n }\n}\n\nexport function bind() {\n Object.keys(bindings).forEach(function(className) {\n let binding = bindings[className];\n $(\".\" + binding.className).not(\".crosstalk-input-bound\").each(function(i, el) {\n bindInstance(binding, el);\n });\n });\n}\n\n// Escape jQuery identifier\nfunction $escape(val) {\n return val.replace(/([!\"#$%&'()*+,./:;<=>?@[\\\\\\]^`{|}~])/g, \"\\\\$1\");\n}\n\nfunction bindEl(el) {\n let $el = $(el);\n Object.keys(bindings).forEach(function(className) {\n if ($el.hasClass(className) && !$el.hasClass(\"crosstalk-input-bound\")) {\n let binding = bindings[className];\n bindInstance(binding, el);\n }\n });\n}\n\nfunction bindInstance(binding, el) {\n let jsonEl = $(el).find(\"script[type='application/json'][data-for='\" + $escape(el.id) + \"']\");\n let data = JSON.parse(jsonEl[0].innerText);\n\n let instance = binding.factory(el, data);\n $(el).data(\"crosstalk-instance\", instance);\n $(el).addClass(\"crosstalk-input-bound\");\n}\n\nif (global.Shiny) {\n let inputBinding = new global.Shiny.InputBinding();\n let $ = global.jQuery;\n $.extend(inputBinding, {\n find: function(scope) {\n return $(scope).find(\".crosstalk-input\");\n },\n initialize: function(el) {\n if (!$(el).hasClass(\"crosstalk-input-bound\")) {\n bindEl(el);\n }\n },\n getId: function(el) {\n return el.id;\n },\n getValue: function(el) {\n\n },\n setValue: function(el, value) {\n\n },\n receiveMessage: function(el, data) {\n\n },\n subscribe: function(el, callback) {\n $(el).data(\"crosstalk-instance\").resume();\n },\n unsubscribe: function(el) {\n $(el).data(\"crosstalk-instance\").suspend();\n }\n });\n global.Shiny.inputBindings.register(inputBinding, \"crosstalk.inputBinding\");\n}\n", - "import * as input from \"./input\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\n\ninput.register({\n className: \"crosstalk-input-checkboxgroup\",\n\n factory: function(el, data) {\n /*\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n let ctHandle = new FilterHandle(data.group);\n\n let lastKnownKeys;\n let $el = $(el);\n $el.on(\"change\", \"input[type='checkbox']\", function() {\n let checked = $el.find(\"input[type='checkbox']:checked\");\n if (checked.length === 0) {\n lastKnownKeys = null;\n ctHandle.clear();\n } else {\n let keys = {};\n checked.each(function() {\n data.map[this.value].forEach(function(key) {\n keys[key] = true;\n });\n });\n let keyArray = Object.keys(keys);\n keyArray.sort();\n lastKnownKeys = keyArray;\n ctHandle.set(keyArray);\n }\n });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n", - "import * as input from \"./input\";\nimport * as util from \"./util\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\n\ninput.register({\n className: \"crosstalk-input-select\",\n\n factory: function(el, data) {\n /*\n * items: {value: [...], label: [...]}\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n\n let first = [{value: \"\", label: \"(All)\"}];\n let items = util.dataframeToD3(data.items);\n let opts = {\n options: first.concat(items),\n valueField: \"value\",\n labelField: \"label\",\n searchField: \"label\"\n };\n\n let select = $(el).find(\"select\")[0];\n\n let selectize = $(select).selectize(opts)[0].selectize;\n\n let ctHandle = new FilterHandle(data.group);\n\n let lastKnownKeys;\n selectize.on(\"change\", function() {\n if (selectize.items.length === 0) {\n lastKnownKeys = null;\n ctHandle.clear();\n } else {\n let keys = {};\n selectize.items.forEach(function(group) {\n data.map[group].forEach(function(key) {\n keys[key] = true;\n });\n });\n let keyArray = Object.keys(keys);\n keyArray.sort();\n lastKnownKeys = keyArray;\n ctHandle.set(keyArray);\n }\n });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n", - "import * as input from \"./input\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\nlet strftime = global.strftime;\n\ninput.register({\n className: \"crosstalk-input-slider\",\n\n factory: function(el, data) {\n /*\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n let ctHandle = new FilterHandle(data.group);\n\n let opts = {};\n let $el = $(el).find(\"input\");\n let dataType = $el.data(\"data-type\");\n let timeFormat = $el.data(\"time-format\");\n let round = $el.data(\"round\");\n let timeFormatter;\n\n // Set up formatting functions\n if (dataType === \"date\") {\n timeFormatter = strftime.utc();\n opts.prettify = function(num) {\n return timeFormatter(timeFormat, new Date(num));\n };\n\n } else if (dataType === \"datetime\") {\n let timezone = $el.data(\"timezone\");\n if (timezone)\n timeFormatter = strftime.timezone(timezone);\n else\n timeFormatter = strftime;\n\n opts.prettify = function(num) {\n return timeFormatter(timeFormat, new Date(num));\n };\n } else if (dataType === \"number\") {\n if (typeof round !== \"undefined\")\n opts.prettify = function(num) {\n let factor = Math.pow(10, round);\n return Math.round(num * factor) / factor;\n };\n }\n\n $el.ionRangeSlider(opts);\n\n function getValue() {\n let result = $el.data(\"ionRangeSlider\").result;\n\n // Function for converting numeric value from slider to appropriate type.\n let convert;\n let dataType = $el.data(\"data-type\");\n if (dataType === \"date\") {\n convert = function(val) {\n return formatDateUTC(new Date(+val));\n };\n } else if (dataType === \"datetime\") {\n convert = function(val) {\n // Convert ms to s\n return +val / 1000;\n };\n } else {\n convert = function(val) { return +val; };\n }\n\n if ($el.data(\"ionRangeSlider\").options.type === \"double\") {\n return [convert(result.from), convert(result.to)];\n } else {\n return convert(result.from);\n }\n }\n\n let lastKnownKeys = null;\n\n $el.on(\"change.crosstalkSliderInput\", function(event) {\n if (!$el.data(\"updating\") && !$el.data(\"animating\")) {\n let [from, to] = getValue();\n let keys = [];\n for (let i = 0; i < data.values.length; i++) {\n let val = data.values[i];\n if (val >= from && val <= to) {\n keys.push(data.keys[i]);\n }\n }\n keys.sort();\n ctHandle.set(keys);\n lastKnownKeys = keys;\n }\n });\n\n\n // let $el = $(el);\n // $el.on(\"change\", \"input[type=\"checkbox\"]\", function() {\n // let checked = $el.find(\"input[type=\"checkbox\"]:checked\");\n // if (checked.length === 0) {\n // ctHandle.clear();\n // } else {\n // let keys = {};\n // checked.each(function() {\n // data.map[this.value].forEach(function(key) {\n // keys[key] = true;\n // });\n // });\n // let keyArray = Object.keys(keys);\n // keyArray.sort();\n // ctHandle.set(keyArray);\n // }\n // });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n\n\n// Convert a number to a string with leading zeros\nfunction padZeros(n, digits) {\n let str = n.toString();\n while (str.length < digits)\n str = \"0\" + str;\n return str;\n}\n\n// Given a Date object, return a string in yyyy-mm-dd format, using the\n// UTC date. This may be a day off from the date in the local time zone.\nfunction formatDateUTC(date) {\n if (date instanceof Date) {\n return date.getUTCFullYear() + \"-\" +\n padZeros(date.getUTCMonth()+1, 2) + \"-\" +\n padZeros(date.getUTCDate(), 2);\n\n } else {\n return null;\n }\n}\n", - "import Events from \"./events\";\nimport grp from \"./group\";\nimport * as util from \"./util\";\n\n/**\n * Use this class to read and write (and listen for changes to) the selection\n * for a Crosstalk group. This is intended to be used for linked brushing.\n *\n * If two (or more) `SelectionHandle` instances in the same webpage share the\n * same group name, they will share the same state. Setting the selection using\n * one `SelectionHandle` instance will result in the `value` property instantly\n * changing across the others, and `\"change\"` event listeners on all instances\n * (including the one that initiated the sending) will fire.\n *\n * @param {string} [group] - The name of the Crosstalk group, or if none,\n * null or undefined (or any other falsy value). This can be changed later\n * via the [SelectionHandle#setGroup](#setGroup) method.\n * @param {Object} [extraInfo] - An object whose properties will be copied to\n * the event object whenever an event is emitted.\n */\nexport class SelectionHandle {\n\n constructor(group = null, extraInfo = null) {\n this._eventRelay = new Events();\n this._emitter = new util.SubscriptionTracker(this._eventRelay);\n\n // Name of the group we're currently tracking, if any. Can change over time.\n this._group = null;\n // The Var we're currently tracking, if any. Can change over time.\n this._var = null;\n // The event handler subscription we currently have on var.on(\"change\").\n this._varOnChangeSub = null;\n\n this._extraInfo = util.extend({ sender: this }, extraInfo);\n\n this.setGroup(group);\n }\n\n /**\n * Changes the Crosstalk group membership of this SelectionHandle. The group\n * being switched away from (if any) will not have its selection value\n * modified as a result of calling `setGroup`, even if this handle was the\n * most recent handle to set the selection of the group.\n *\n * The group being switched to (if any) will also not have its selection value\n * modified as a result of calling `setGroup`. If you want to set the\n * selection value of the new group, call `set` explicitly.\n *\n * @param {string} group - The name of the Crosstalk group, or null (or\n * undefined) to clear the group.\n */\n setGroup(group) {\n // If group is unchanged, do nothing\n if (this._group === group)\n return;\n // Treat null, undefined, and other falsy values the same\n if (!this._group && !group)\n return;\n\n if (this._var) {\n this._var.off(\"change\", this._varOnChangeSub);\n this._var = null;\n this._varOnChangeSub = null;\n }\n\n this._group = group;\n\n if (group) {\n this._var = grp(group).var(\"selection\");\n let sub = this._var.on(\"change\", (e) => {\n this._eventRelay.trigger(\"change\", e, this);\n });\n this._varOnChangeSub = sub;\n }\n }\n\n /**\n * Retrieves the current selection for the group represented by this\n * `SelectionHandle`.\n *\n * - If no selection is active, then this value will be falsy.\n * - If a selection is active, but no data points are selected, then this\n * value will be an empty array.\n * - If a selection is active, and data points are selected, then the keys\n * of the selected data points will be present in the array.\n */\n get value() {\n return this._var ? this._var.get() : null;\n }\n\n /**\n * Combines the given `extraInfo` (if any) with the handle's default\n * `_extraInfo` (if any).\n * @private\n */\n _mergeExtraInfo(extraInfo) {\n // Important incidental effect: shallow clone is returned\n return util.extend({},\n this._extraInfo ? this._extraInfo : null,\n extraInfo ? extraInfo : null);\n }\n\n /**\n * Overwrites the current selection for the group, and raises the `\"change\"`\n * event among all of the group's '`SelectionHandle` instances (including\n * this one).\n *\n * @fires SelectionHandle#change\n * @param {string[]} selectedKeys - Falsy, empty array, or array of keys (see\n * {@link SelectionHandle#value}).\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `SelectionHandle` constructor).\n */\n set(selectedKeys, extraInfo) {\n if (this._var)\n this._var.set(selectedKeys, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * Overwrites the current selection for the group, and raises the `\"change\"`\n * event among all of the group's '`SelectionHandle` instances (including\n * this one).\n *\n * @fires SelectionHandle#change\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any that were passed\n * into the `SelectionHandle` constructor).\n */\n clear(extraInfo) {\n if (this._var)\n this.set(void 0, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * Subscribes to events on this `SelectionHandle`.\n *\n * @param {string} eventType - Indicates the type of events to listen to.\n * Currently, only `\"change\"` is supported.\n * @param {SelectionHandle~listener} listener - The callback function that\n * will be invoked when the event occurs.\n * @return {string} - A token to pass to {@link SelectionHandle#off} to cancel\n * this subscription.\n */\n on(eventType, listener) {\n return this._emitter.on(eventType, listener);\n }\n\n /**\n * Cancels event subscriptions created by {@link SelectionHandle#on}.\n *\n * @param {string} eventType - The type of event to unsubscribe.\n * @param {string|SelectionHandle~listener} listener - Either the callback\n * function previously passed into {@link SelectionHandle#on}, or the\n * string that was returned from {@link SelectionHandle#on}.\n */\n off(eventType, listener) {\n return this._emitter.off(eventType, listener);\n }\n\n /**\n * Shuts down the `SelectionHandle` object.\n *\n * Removes all event listeners that were added through this handle.\n */\n close() {\n this._emitter.removeAllListeners();\n this.setGroup(null);\n }\n}\n\n/**\n * @callback SelectionHandle~listener\n * @param {Object} event - An object containing details of the event. For\n * `\"change\"` events, this includes the properties `value` (the new\n * value of the selection, or `undefined` if no selection is active),\n * `oldValue` (the previous value of the selection), and `sender` (the\n * `SelectionHandle` instance that made the change).\n */\n\n/**\n * @event SelectionHandle#change\n * @type {object}\n * @property {object} value - The new value of the selection, or `undefined`\n * if no selection is active.\n * @property {object} oldValue - The previous value of the selection.\n * @property {SelectionHandle} sender - The `SelectionHandle` instance that\n * changed the value.\n */\n", - "export function extend(target, ...sources) {\n for (let i = 0; i < sources.length; i++) {\n let src = sources[i];\n if (typeof(src) === \"undefined\" || src === null)\n continue;\n\n for (let key in src) {\n if (src.hasOwnProperty(key)) {\n target[key] = src[key];\n }\n }\n }\n return target;\n}\n\nexport function checkSorted(list) {\n for (let i = 1; i < list.length; i++) {\n if (list[i] <= list[i-1]) {\n throw new Error(\"List is not sorted or contains duplicate\");\n }\n }\n}\n\nexport function diffSortedLists(a, b) {\n let i_a = 0;\n let i_b = 0;\n\n if (!a) a = [];\n if (!b) b = [];\n\n let a_only = [];\n let b_only = [];\n\n checkSorted(a);\n checkSorted(b);\n\n while (i_a < a.length && i_b < b.length) {\n if (a[i_a] === b[i_b]) {\n i_a++;\n i_b++;\n } else if (a[i_a] < b[i_b]) {\n a_only.push(a[i_a++]);\n } else {\n b_only.push(b[i_b++]);\n }\n }\n\n if (i_a < a.length)\n a_only = a_only.concat(a.slice(i_a));\n if (i_b < b.length)\n b_only = b_only.concat(b.slice(i_b));\n return {\n removed: a_only,\n added: b_only\n };\n}\n\n// Convert from wide: { colA: [1,2,3], colB: [4,5,6], ... }\n// to long: [ {colA: 1, colB: 4}, {colA: 2, colB: 5}, ... ]\nexport function dataframeToD3(df) {\n let names = [];\n let length;\n for (let name in df) {\n if (df.hasOwnProperty(name))\n names.push(name);\n if (typeof(df[name]) !== \"object\" || typeof(df[name].length) === \"undefined\") {\n throw new Error(\"All fields must be arrays\");\n } else if (typeof(length) !== \"undefined\" && length !== df[name].length) {\n throw new Error(\"All fields must be arrays of the same length\");\n }\n length = df[name].length;\n }\n let results = [];\n let item;\n for (let row = 0; row < length; row++) {\n item = {};\n for (let col = 0; col < names.length; col++) {\n item[names[col]] = df[names[col]][row];\n }\n results.push(item);\n }\n return results;\n}\n\n/**\n * Keeps track of all event listener additions/removals and lets all active\n * listeners be removed with a single operation.\n *\n * @private\n */\nexport class SubscriptionTracker {\n constructor(emitter) {\n this._emitter = emitter;\n this._subs = {};\n }\n\n on(eventType, listener) {\n let sub = this._emitter.on(eventType, listener);\n this._subs[sub] = eventType;\n return sub;\n }\n\n off(eventType, listener) {\n let sub = this._emitter.off(eventType, listener);\n if (sub) {\n delete this._subs[sub];\n }\n return sub;\n }\n\n removeAllListeners() {\n let current_subs = this._subs;\n this._subs = {};\n Object.keys(current_subs).forEach((sub) => {\n this._emitter.off(current_subs[sub], sub);\n });\n }\n}\n", - "import Events from \"./events\";\n\nexport default class Var {\n constructor(group, name, /*optional*/ value) {\n this._group = group;\n this._name = name;\n this._value = value;\n this._events = new Events();\n }\n\n get() {\n return this._value;\n }\n\n set(value, /*optional*/ event) {\n if (this._value === value) {\n // Do nothing; the value hasn't changed\n return;\n }\n let oldValue = this._value;\n this._value = value;\n // Alert JavaScript listeners that the value has changed\n let evt = {};\n if (event && typeof(event) === \"object\") {\n for (let k in event) {\n if (event.hasOwnProperty(k))\n evt[k] = event[k];\n }\n }\n evt.oldValue = oldValue;\n evt.value = value;\n this._events.trigger(\"change\", evt, this);\n\n // TODO: Make this extensible, to let arbitrary back-ends know that\n // something has changed\n if (global.Shiny && global.Shiny.onInputChange) {\n global.Shiny.onInputChange(\n \".clientValue-\" +\n (this._group.name !== null ? this._group.name + \"-\" : \"\") +\n this._name,\n typeof(value) === \"undefined\" ? null : value\n );\n }\n }\n\n on(eventType, listener) {\n return this._events.on(eventType, listener);\n }\n\n off(eventType, listener) {\n return this._events.off(eventType, listener);\n }\n}\n" - ] -} \ No newline at end of file diff --git a/docs/articles/get_started_files/crosstalk-1.2.2/js/crosstalk.min.js b/docs/articles/get_started_files/crosstalk-1.2.2/js/crosstalk.min.js deleted file mode 100644 index b7ec0ac..0000000 --- a/docs/articles/get_started_files/crosstalk-1.2.2/js/crosstalk.min.js +++ /dev/null @@ -1,2 +0,0 @@ -!function o(u,a,l){function s(n,e){if(!a[n]){if(!u[n]){var t="function"==typeof require&&require;if(!e&&t)return t(n,!0);if(f)return f(n,!0);var r=new Error("Cannot find module '"+n+"'");throw r.code="MODULE_NOT_FOUND",r}var i=a[n]={exports:{}};u[n][0].call(i.exports,function(e){var t=u[n][1][e];return s(t||e)},i,i.exports,o,u,a,l)}return a[n].exports}for(var f="function"==typeof require&&require,e=0;e?@[\\\]^`{|}~])/g,"\\$1")+"']"),r=JSON.parse(n[0].innerText),i=e.factory(t,r);o(t).data("crosstalk-instance",i),o(t).addClass("crosstalk-input-bound")}if(t.Shiny){var e=new t.Shiny.InputBinding,u=t.jQuery;u.extend(e,{find:function(e){return u(e).find(".crosstalk-input")},initialize:function(e){var t,n;u(e).hasClass("crosstalk-input-bound")||(n=o(t=e),Object.keys(r).forEach(function(e){n.hasClass(e)&&!n.hasClass("crosstalk-input-bound")&&i(r[e],t)}))},getId:function(e){return e.id},getValue:function(e){},setValue:function(e,t){},receiveMessage:function(e,t){},subscribe:function(e,t){u(e).data("crosstalk-instance").resume()},unsubscribe:function(e){u(e).data("crosstalk-instance").suspend()}}),t.Shiny.inputBindings.register(e,"crosstalk.inputBinding")}}).call(this,"undefined"!=typeof global?global:"undefined"!=typeof self?self:"undefined"!=typeof window?window:{})},{}],7:[function(r,e,t){(function(e){"use strict";var t=function(e){{if(e&&e.__esModule)return e;var t={};if(null!=e)for(var n in e)Object.prototype.hasOwnProperty.call(e,n)&&(t[n]=e[n]);return t.default=e,t}}(r("./input")),n=r("./filter");var a=e.jQuery;t.register({className:"crosstalk-input-checkboxgroup",factory:function(e,r){var i=new n.FilterHandle(r.group),o=void 0,u=a(e);return u.on("change","input[type='checkbox']",function(){var e=u.find("input[type='checkbox']:checked");if(0===e.length)o=null,i.clear();else{var t={};e.each(function(){r.map[this.value].forEach(function(e){t[e]=!0})});var n=Object.keys(t);n.sort(),o=n,i.set(n)}}),{suspend:function(){i.clear()},resume:function(){o&&i.set(o)}}}})}).call(this,"undefined"!=typeof global?global:"undefined"!=typeof self?self:"undefined"!=typeof window?window:{})},{"./filter":2,"./input":6}],8:[function(r,e,t){(function(e){"use strict";var t=n(r("./input")),l=n(r("./util")),s=r("./filter");function n(e){if(e&&e.__esModule)return e;var t={};if(null!=e)for(var n in e)Object.prototype.hasOwnProperty.call(e,n)&&(t[n]=e[n]);return t.default=e,t}var f=e.jQuery;t.register({className:"crosstalk-input-select",factory:function(e,n){var t=l.dataframeToD3(n.items),r={options:[{value:"",label:"(All)"}].concat(t),valueField:"value",labelField:"label",searchField:"label"},i=f(e).find("select")[0],o=f(i).selectize(r)[0].selectize,u=new s.FilterHandle(n.group),a=void 0;return o.on("change",function(){if(0===o.items.length)a=null,u.clear();else{var t={};o.items.forEach(function(e){n.map[e].forEach(function(e){t[e]=!0})});var e=Object.keys(t);e.sort(),a=e,u.set(e)}}),{suspend:function(){u.clear()},resume:function(){a&&u.set(a)}}}})}).call(this,"undefined"!=typeof global?global:"undefined"!=typeof self?self:"undefined"!=typeof window?window:{})},{"./filter":2,"./input":6,"./util":11}],9:[function(n,e,t){(function(e){"use strict";var d=function(e,t){if(Array.isArray(e))return e;if(Symbol.iterator in Object(e))return function(e,t){var n=[],r=!0,i=!1,o=void 0;try{for(var u,a=e[Symbol.iterator]();!(r=(u=a.next()).done)&&(n.push(u.value),!t||n.length!==t);r=!0);}catch(e){i=!0,o=e}finally{try{!r&&a.return&&a.return()}finally{if(i)throw o}}return n}(e,t);throw new TypeError("Invalid attempt to destructure non-iterable instance")},t=function(e){{if(e&&e.__esModule)return e;var t={};if(null!=e)for(var n in e)Object.prototype.hasOwnProperty.call(e,n)&&(t[n]=e[n]);return t.default=e,t}}(n("./input")),a=n("./filter");var v=e.jQuery,p=e.strftime;function y(e,t){for(var n=e.toString();n.length {\n this._eventRelay.trigger(\"change\", e, this);\n });\n this._varOnChangeSub = sub;\n }\n }\n\n /**\n * Combine the given `extraInfo` (if any) with the handle's default\n * `_extraInfo` (if any).\n * @private\n */\n _mergeExtraInfo(extraInfo) {\n return util.extend({},\n this._extraInfo ? this._extraInfo : null,\n extraInfo ? extraInfo : null);\n }\n\n /**\n * Close the handle. This clears this handle's contribution to the filter set,\n * and unsubscribes all event listeners.\n */\n close() {\n this._emitter.removeAllListeners();\n this.clear();\n this.setGroup(null);\n }\n\n /**\n * Clear this handle's contribution to the filter set.\n *\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `FilterHandle` constructor).\n * \n * @fires FilterHandle#change\n */\n clear(extraInfo) {\n if (!this._filterSet)\n return;\n this._filterSet.clear(this._id);\n this._onChange(extraInfo);\n }\n\n /**\n * Set this handle's contribution to the filter set. This array should consist\n * of the keys of the rows that _should_ be displayed; any keys that are not\n * present in the array will be considered _filtered out_. Note that multiple\n * `FilterHandle` instances in the group may each contribute an array of keys,\n * and only those keys that appear in _all_ of the arrays make it through the\n * filter.\n *\n * @param {string[]} keys - Empty array, or array of keys. To clear the\n * filter, don't pass an empty array; instead, use the\n * {@link FilterHandle#clear} method.\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `FilterHandle` constructor).\n * \n * @fires FilterHandle#change\n */\n set(keys, extraInfo) {\n if (!this._filterSet)\n return;\n this._filterSet.update(this._id, keys);\n this._onChange(extraInfo);\n }\n\n /**\n * @return {string[]|null} - Either: 1) an array of keys that made it through\n * all of the `FilterHandle` instances, or, 2) `null`, which means no filter\n * is being applied (all data should be displayed).\n */\n get filteredKeys() {\n return this._filterSet ? this._filterSet.value : null;\n }\n\n /**\n * Subscribe to events on this `FilterHandle`.\n *\n * @param {string} eventType - Indicates the type of events to listen to.\n * Currently, only `\"change\"` is supported.\n * @param {FilterHandle~listener} listener - The callback function that\n * will be invoked when the event occurs.\n * @return {string} - A token to pass to {@link FilterHandle#off} to cancel\n * this subscription.\n */\n on(eventType, listener) {\n return this._emitter.on(eventType, listener);\n }\n\n /**\n * Cancel event subscriptions created by {@link FilterHandle#on}.\n *\n * @param {string} eventType - The type of event to unsubscribe.\n * @param {string|FilterHandle~listener} listener - Either the callback\n * function previously passed into {@link FilterHandle#on}, or the\n * string that was returned from {@link FilterHandle#on}.\n */\n off(eventType, listener) {\n return this._emitter.off(eventType, listener);\n }\n\n _onChange(extraInfo) {\n if (!this._filterSet)\n return;\n this._filterVar.set(this._filterSet.value, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * @callback FilterHandle~listener\n * @param {Object} event - An object containing details of the event. For\n * `\"change\"` events, this includes the properties `value` (the new\n * value of the filter set, or `null` if no filter set is active),\n * `oldValue` (the previous value of the filter set), and `sender` (the\n * `FilterHandle` instance that made the change).\n */\n\n}\n\n/**\n * @event FilterHandle#change\n * @type {object}\n * @property {object} value - The new value of the filter set, or `null`\n * if no filter set is active.\n * @property {object} oldValue - The previous value of the filter set.\n * @property {FilterHandle} sender - The `FilterHandle` instance that\n * changed the value.\n */\n","import { diffSortedLists } from \"./util\";\n\nfunction naturalComparator(a, b) {\n if (a === b) {\n return 0;\n } else if (a < b) {\n return -1;\n } else if (a > b) {\n return 1;\n }\n}\n\n/**\n * @private\n */\nexport default class FilterSet {\n constructor() {\n this.reset();\n }\n\n reset() {\n // Key: handle ID, Value: array of selected keys, or null\n this._handles = {};\n // Key: key string, Value: count of handles that include it\n this._keys = {};\n this._value = null;\n this._activeHandles = 0;\n }\n\n get value() {\n return this._value;\n }\n\n update(handleId, keys) {\n if (keys !== null) {\n keys = keys.slice(0); // clone before sorting\n keys.sort(naturalComparator);\n }\n\n let {added, removed} = diffSortedLists(this._handles[handleId], keys);\n this._handles[handleId] = keys;\n\n for (let i = 0; i < added.length; i++) {\n this._keys[added[i]] = (this._keys[added[i]] || 0) + 1;\n }\n for (let i = 0; i < removed.length; i++) {\n this._keys[removed[i]]--;\n }\n\n this._updateValue(keys);\n }\n\n /**\n * @param {string[]} keys Sorted array of strings that indicate\n * a superset of possible keys.\n * @private\n */\n _updateValue(keys = this._allKeys) {\n let handleCount = Object.keys(this._handles).length;\n if (handleCount === 0) {\n this._value = null;\n } else {\n this._value = [];\n for (let i = 0; i < keys.length; i++) {\n let count = this._keys[keys[i]];\n if (count === handleCount) {\n this._value.push(keys[i]);\n }\n }\n }\n }\n\n clear(handleId) {\n if (typeof(this._handles[handleId]) === \"undefined\") {\n return;\n }\n\n let keys = this._handles[handleId];\n if (!keys) {\n keys = [];\n }\n\n for (let i = 0; i < keys.length; i++) {\n this._keys[keys[i]]--;\n }\n delete this._handles[handleId];\n\n this._updateValue();\n }\n\n get _allKeys() {\n let allKeys = Object.keys(this._keys);\n allKeys.sort(naturalComparator);\n return allKeys;\n }\n}\n","import Var from \"./var\";\n\n// Use a global so that multiple copies of crosstalk.js can be loaded and still\n// have groups behave as singletons across all copies.\nglobal.__crosstalk_groups = global.__crosstalk_groups || {};\nlet groups = global.__crosstalk_groups;\n\nexport default function group(groupName) {\n if (groupName && typeof(groupName) === \"string\") {\n if (!groups.hasOwnProperty(groupName)) {\n groups[groupName] = new Group(groupName);\n }\n return groups[groupName];\n } else if (typeof(groupName) === \"object\" && groupName._vars && groupName.var) {\n // Appears to already be a group object\n return groupName;\n } else if (Array.isArray(groupName) &&\n groupName.length == 1 &&\n typeof(groupName[0]) === \"string\") {\n return group(groupName[0]);\n } else {\n throw new Error(\"Invalid groupName argument\");\n }\n}\n\nclass Group {\n constructor(name) {\n this.name = name;\n this._vars = {};\n }\n\n var(name) {\n if (!name || typeof(name) !== \"string\") {\n throw new Error(\"Invalid var name\");\n }\n\n if (!this._vars.hasOwnProperty(name))\n this._vars[name] = new Var(this, name);\n return this._vars[name];\n }\n\n has(name) {\n if (!name || typeof(name) !== \"string\") {\n throw new Error(\"Invalid var name\");\n }\n\n return this._vars.hasOwnProperty(name);\n }\n}\n","import group from \"./group\";\nimport { SelectionHandle } from \"./selection\";\nimport { FilterHandle } from \"./filter\";\nimport { bind } from \"./input\";\nimport \"./input_selectize\";\nimport \"./input_checkboxgroup\";\nimport \"./input_slider\";\n\nconst defaultGroup = group(\"default\");\n\nfunction var_(name) {\n return defaultGroup.var(name);\n}\n\nfunction has(name) {\n return defaultGroup.has(name);\n}\n\nif (global.Shiny) {\n global.Shiny.addCustomMessageHandler(\"update-client-value\", function(message) {\n if (typeof(message.group) === \"string\") {\n group(message.group).var(message.name).set(message.value);\n } else {\n var_(message.name).set(message.value);\n }\n });\n}\n\nconst crosstalk = {\n group: group,\n var: var_,\n has: has,\n SelectionHandle: SelectionHandle,\n FilterHandle: FilterHandle,\n bind: bind\n};\n\n/**\n * @namespace crosstalk\n */\nexport default crosstalk;\nglobal.crosstalk = crosstalk;\n","let $ = global.jQuery;\n\nlet bindings = {};\n\nexport function register(reg) {\n bindings[reg.className] = reg;\n if (global.document && global.document.readyState !== \"complete\") {\n $(() => {\n bind();\n });\n } else if (global.document) {\n setTimeout(bind, 100);\n }\n}\n\nexport function bind() {\n Object.keys(bindings).forEach(function(className) {\n let binding = bindings[className];\n $(\".\" + binding.className).not(\".crosstalk-input-bound\").each(function(i, el) {\n bindInstance(binding, el);\n });\n });\n}\n\n// Escape jQuery identifier\nfunction $escape(val) {\n return val.replace(/([!\"#$%&'()*+,./:;<=>?@[\\\\\\]^`{|}~])/g, \"\\\\$1\");\n}\n\nfunction bindEl(el) {\n let $el = $(el);\n Object.keys(bindings).forEach(function(className) {\n if ($el.hasClass(className) && !$el.hasClass(\"crosstalk-input-bound\")) {\n let binding = bindings[className];\n bindInstance(binding, el);\n }\n });\n}\n\nfunction bindInstance(binding, el) {\n let jsonEl = $(el).find(\"script[type='application/json'][data-for='\" + $escape(el.id) + \"']\");\n let data = JSON.parse(jsonEl[0].innerText);\n\n let instance = binding.factory(el, data);\n $(el).data(\"crosstalk-instance\", instance);\n $(el).addClass(\"crosstalk-input-bound\");\n}\n\nif (global.Shiny) {\n let inputBinding = new global.Shiny.InputBinding();\n let $ = global.jQuery;\n $.extend(inputBinding, {\n find: function(scope) {\n return $(scope).find(\".crosstalk-input\");\n },\n initialize: function(el) {\n if (!$(el).hasClass(\"crosstalk-input-bound\")) {\n bindEl(el);\n }\n },\n getId: function(el) {\n return el.id;\n },\n getValue: function(el) {\n\n },\n setValue: function(el, value) {\n\n },\n receiveMessage: function(el, data) {\n\n },\n subscribe: function(el, callback) {\n $(el).data(\"crosstalk-instance\").resume();\n },\n unsubscribe: function(el) {\n $(el).data(\"crosstalk-instance\").suspend();\n }\n });\n global.Shiny.inputBindings.register(inputBinding, \"crosstalk.inputBinding\");\n}\n","import * as input from \"./input\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\n\ninput.register({\n className: \"crosstalk-input-checkboxgroup\",\n\n factory: function(el, data) {\n /*\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n let ctHandle = new FilterHandle(data.group);\n\n let lastKnownKeys;\n let $el = $(el);\n $el.on(\"change\", \"input[type='checkbox']\", function() {\n let checked = $el.find(\"input[type='checkbox']:checked\");\n if (checked.length === 0) {\n lastKnownKeys = null;\n ctHandle.clear();\n } else {\n let keys = {};\n checked.each(function() {\n data.map[this.value].forEach(function(key) {\n keys[key] = true;\n });\n });\n let keyArray = Object.keys(keys);\n keyArray.sort();\n lastKnownKeys = keyArray;\n ctHandle.set(keyArray);\n }\n });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n","import * as input from \"./input\";\nimport * as util from \"./util\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\n\ninput.register({\n className: \"crosstalk-input-select\",\n\n factory: function(el, data) {\n /*\n * items: {value: [...], label: [...]}\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n\n let first = [{value: \"\", label: \"(All)\"}];\n let items = util.dataframeToD3(data.items);\n let opts = {\n options: first.concat(items),\n valueField: \"value\",\n labelField: \"label\",\n searchField: \"label\"\n };\n\n let select = $(el).find(\"select\")[0];\n\n let selectize = $(select).selectize(opts)[0].selectize;\n\n let ctHandle = new FilterHandle(data.group);\n\n let lastKnownKeys;\n selectize.on(\"change\", function() {\n if (selectize.items.length === 0) {\n lastKnownKeys = null;\n ctHandle.clear();\n } else {\n let keys = {};\n selectize.items.forEach(function(group) {\n data.map[group].forEach(function(key) {\n keys[key] = true;\n });\n });\n let keyArray = Object.keys(keys);\n keyArray.sort();\n lastKnownKeys = keyArray;\n ctHandle.set(keyArray);\n }\n });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n","import * as input from \"./input\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\nlet strftime = global.strftime;\n\ninput.register({\n className: \"crosstalk-input-slider\",\n\n factory: function(el, data) {\n /*\n * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n * group: \"ct-groupname\"\n */\n let ctHandle = new FilterHandle(data.group);\n\n let opts = {};\n let $el = $(el).find(\"input\");\n let dataType = $el.data(\"data-type\");\n let timeFormat = $el.data(\"time-format\");\n let round = $el.data(\"round\");\n let timeFormatter;\n\n // Set up formatting functions\n if (dataType === \"date\") {\n timeFormatter = strftime.utc();\n opts.prettify = function(num) {\n return timeFormatter(timeFormat, new Date(num));\n };\n\n } else if (dataType === \"datetime\") {\n let timezone = $el.data(\"timezone\");\n if (timezone)\n timeFormatter = strftime.timezone(timezone);\n else\n timeFormatter = strftime;\n\n opts.prettify = function(num) {\n return timeFormatter(timeFormat, new Date(num));\n };\n } else if (dataType === \"number\") {\n if (typeof round !== \"undefined\")\n opts.prettify = function(num) {\n let factor = Math.pow(10, round);\n return Math.round(num * factor) / factor;\n };\n }\n\n $el.ionRangeSlider(opts);\n\n function getValue() {\n let result = $el.data(\"ionRangeSlider\").result;\n\n // Function for converting numeric value from slider to appropriate type.\n let convert;\n let dataType = $el.data(\"data-type\");\n if (dataType === \"date\") {\n convert = function(val) {\n return formatDateUTC(new Date(+val));\n };\n } else if (dataType === \"datetime\") {\n convert = function(val) {\n // Convert ms to s\n return +val / 1000;\n };\n } else {\n convert = function(val) { return +val; };\n }\n\n if ($el.data(\"ionRangeSlider\").options.type === \"double\") {\n return [convert(result.from), convert(result.to)];\n } else {\n return convert(result.from);\n }\n }\n\n let lastKnownKeys = null;\n\n $el.on(\"change.crosstalkSliderInput\", function(event) {\n if (!$el.data(\"updating\") && !$el.data(\"animating\")) {\n let [from, to] = getValue();\n let keys = [];\n for (let i = 0; i < data.values.length; i++) {\n let val = data.values[i];\n if (val >= from && val <= to) {\n keys.push(data.keys[i]);\n }\n }\n keys.sort();\n ctHandle.set(keys);\n lastKnownKeys = keys;\n }\n });\n\n\n // let $el = $(el);\n // $el.on(\"change\", \"input[type=\"checkbox\"]\", function() {\n // let checked = $el.find(\"input[type=\"checkbox\"]:checked\");\n // if (checked.length === 0) {\n // ctHandle.clear();\n // } else {\n // let keys = {};\n // checked.each(function() {\n // data.map[this.value].forEach(function(key) {\n // keys[key] = true;\n // });\n // });\n // let keyArray = Object.keys(keys);\n // keyArray.sort();\n // ctHandle.set(keyArray);\n // }\n // });\n\n return {\n suspend: function() {\n ctHandle.clear();\n },\n resume: function() {\n if (lastKnownKeys)\n ctHandle.set(lastKnownKeys);\n }\n };\n }\n});\n\n\n// Convert a number to a string with leading zeros\nfunction padZeros(n, digits) {\n let str = n.toString();\n while (str.length < digits)\n str = \"0\" + str;\n return str;\n}\n\n// Given a Date object, return a string in yyyy-mm-dd format, using the\n// UTC date. This may be a day off from the date in the local time zone.\nfunction formatDateUTC(date) {\n if (date instanceof Date) {\n return date.getUTCFullYear() + \"-\" +\n padZeros(date.getUTCMonth()+1, 2) + \"-\" +\n padZeros(date.getUTCDate(), 2);\n\n } else {\n return null;\n }\n}\n","import Events from \"./events\";\nimport grp from \"./group\";\nimport * as util from \"./util\";\n\n/**\n * Use this class to read and write (and listen for changes to) the selection\n * for a Crosstalk group. This is intended to be used for linked brushing.\n *\n * If two (or more) `SelectionHandle` instances in the same webpage share the\n * same group name, they will share the same state. Setting the selection using\n * one `SelectionHandle` instance will result in the `value` property instantly\n * changing across the others, and `\"change\"` event listeners on all instances\n * (including the one that initiated the sending) will fire.\n *\n * @param {string} [group] - The name of the Crosstalk group, or if none,\n * null or undefined (or any other falsy value). This can be changed later\n * via the [SelectionHandle#setGroup](#setGroup) method.\n * @param {Object} [extraInfo] - An object whose properties will be copied to\n * the event object whenever an event is emitted.\n */\nexport class SelectionHandle {\n\n constructor(group = null, extraInfo = null) {\n this._eventRelay = new Events();\n this._emitter = new util.SubscriptionTracker(this._eventRelay);\n\n // Name of the group we're currently tracking, if any. Can change over time.\n this._group = null;\n // The Var we're currently tracking, if any. Can change over time.\n this._var = null;\n // The event handler subscription we currently have on var.on(\"change\").\n this._varOnChangeSub = null;\n\n this._extraInfo = util.extend({ sender: this }, extraInfo);\n\n this.setGroup(group);\n }\n\n /**\n * Changes the Crosstalk group membership of this SelectionHandle. The group\n * being switched away from (if any) will not have its selection value\n * modified as a result of calling `setGroup`, even if this handle was the\n * most recent handle to set the selection of the group.\n *\n * The group being switched to (if any) will also not have its selection value\n * modified as a result of calling `setGroup`. If you want to set the\n * selection value of the new group, call `set` explicitly.\n *\n * @param {string} group - The name of the Crosstalk group, or null (or\n * undefined) to clear the group.\n */\n setGroup(group) {\n // If group is unchanged, do nothing\n if (this._group === group)\n return;\n // Treat null, undefined, and other falsy values the same\n if (!this._group && !group)\n return;\n\n if (this._var) {\n this._var.off(\"change\", this._varOnChangeSub);\n this._var = null;\n this._varOnChangeSub = null;\n }\n\n this._group = group;\n\n if (group) {\n this._var = grp(group).var(\"selection\");\n let sub = this._var.on(\"change\", (e) => {\n this._eventRelay.trigger(\"change\", e, this);\n });\n this._varOnChangeSub = sub;\n }\n }\n\n /**\n * Retrieves the current selection for the group represented by this\n * `SelectionHandle`.\n *\n * - If no selection is active, then this value will be falsy.\n * - If a selection is active, but no data points are selected, then this\n * value will be an empty array.\n * - If a selection is active, and data points are selected, then the keys\n * of the selected data points will be present in the array.\n */\n get value() {\n return this._var ? this._var.get() : null;\n }\n\n /**\n * Combines the given `extraInfo` (if any) with the handle's default\n * `_extraInfo` (if any).\n * @private\n */\n _mergeExtraInfo(extraInfo) {\n // Important incidental effect: shallow clone is returned\n return util.extend({},\n this._extraInfo ? this._extraInfo : null,\n extraInfo ? extraInfo : null);\n }\n\n /**\n * Overwrites the current selection for the group, and raises the `\"change\"`\n * event among all of the group's '`SelectionHandle` instances (including\n * this one).\n *\n * @fires SelectionHandle#change\n * @param {string[]} selectedKeys - Falsy, empty array, or array of keys (see\n * {@link SelectionHandle#value}).\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any options that were\n * passed into the `SelectionHandle` constructor).\n */\n set(selectedKeys, extraInfo) {\n if (this._var)\n this._var.set(selectedKeys, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * Overwrites the current selection for the group, and raises the `\"change\"`\n * event among all of the group's '`SelectionHandle` instances (including\n * this one).\n *\n * @fires SelectionHandle#change\n * @param {Object} [extraInfo] - Extra properties to be included on the event\n * object that's passed to listeners (in addition to any that were passed\n * into the `SelectionHandle` constructor).\n */\n clear(extraInfo) {\n if (this._var)\n this.set(void 0, this._mergeExtraInfo(extraInfo));\n }\n\n /**\n * Subscribes to events on this `SelectionHandle`.\n *\n * @param {string} eventType - Indicates the type of events to listen to.\n * Currently, only `\"change\"` is supported.\n * @param {SelectionHandle~listener} listener - The callback function that\n * will be invoked when the event occurs.\n * @return {string} - A token to pass to {@link SelectionHandle#off} to cancel\n * this subscription.\n */\n on(eventType, listener) {\n return this._emitter.on(eventType, listener);\n }\n\n /**\n * Cancels event subscriptions created by {@link SelectionHandle#on}.\n *\n * @param {string} eventType - The type of event to unsubscribe.\n * @param {string|SelectionHandle~listener} listener - Either the callback\n * function previously passed into {@link SelectionHandle#on}, or the\n * string that was returned from {@link SelectionHandle#on}.\n */\n off(eventType, listener) {\n return this._emitter.off(eventType, listener);\n }\n\n /**\n * Shuts down the `SelectionHandle` object.\n *\n * Removes all event listeners that were added through this handle.\n */\n close() {\n this._emitter.removeAllListeners();\n this.setGroup(null);\n }\n}\n\n/**\n * @callback SelectionHandle~listener\n * @param {Object} event - An object containing details of the event. For\n * `\"change\"` events, this includes the properties `value` (the new\n * value of the selection, or `undefined` if no selection is active),\n * `oldValue` (the previous value of the selection), and `sender` (the\n * `SelectionHandle` instance that made the change).\n */\n\n/**\n * @event SelectionHandle#change\n * @type {object}\n * @property {object} value - The new value of the selection, or `undefined`\n * if no selection is active.\n * @property {object} oldValue - The previous value of the selection.\n * @property {SelectionHandle} sender - The `SelectionHandle` instance that\n * changed the value.\n */\n","export function extend(target, ...sources) {\n for (let i = 0; i < sources.length; i++) {\n let src = sources[i];\n if (typeof(src) === \"undefined\" || src === null)\n continue;\n\n for (let key in src) {\n if (src.hasOwnProperty(key)) {\n target[key] = src[key];\n }\n }\n }\n return target;\n}\n\nexport function checkSorted(list) {\n for (let i = 1; i < list.length; i++) {\n if (list[i] <= list[i-1]) {\n throw new Error(\"List is not sorted or contains duplicate\");\n }\n }\n}\n\nexport function diffSortedLists(a, b) {\n let i_a = 0;\n let i_b = 0;\n\n if (!a) a = [];\n if (!b) b = [];\n\n let a_only = [];\n let b_only = [];\n\n checkSorted(a);\n checkSorted(b);\n\n while (i_a < a.length && i_b < b.length) {\n if (a[i_a] === b[i_b]) {\n i_a++;\n i_b++;\n } else if (a[i_a] < b[i_b]) {\n a_only.push(a[i_a++]);\n } else {\n b_only.push(b[i_b++]);\n }\n }\n\n if (i_a < a.length)\n a_only = a_only.concat(a.slice(i_a));\n if (i_b < b.length)\n b_only = b_only.concat(b.slice(i_b));\n return {\n removed: a_only,\n added: b_only\n };\n}\n\n// Convert from wide: { colA: [1,2,3], colB: [4,5,6], ... }\n// to long: [ {colA: 1, colB: 4}, {colA: 2, colB: 5}, ... ]\nexport function dataframeToD3(df) {\n let names = [];\n let length;\n for (let name in df) {\n if (df.hasOwnProperty(name))\n names.push(name);\n if (typeof(df[name]) !== \"object\" || typeof(df[name].length) === \"undefined\") {\n throw new Error(\"All fields must be arrays\");\n } else if (typeof(length) !== \"undefined\" && length !== df[name].length) {\n throw new Error(\"All fields must be arrays of the same length\");\n }\n length = df[name].length;\n }\n let results = [];\n let item;\n for (let row = 0; row < length; row++) {\n item = {};\n for (let col = 0; col < names.length; col++) {\n item[names[col]] = df[names[col]][row];\n }\n results.push(item);\n }\n return results;\n}\n\n/**\n * Keeps track of all event listener additions/removals and lets all active\n * listeners be removed with a single operation.\n *\n * @private\n */\nexport class SubscriptionTracker {\n constructor(emitter) {\n this._emitter = emitter;\n this._subs = {};\n }\n\n on(eventType, listener) {\n let sub = this._emitter.on(eventType, listener);\n this._subs[sub] = eventType;\n return sub;\n }\n\n off(eventType, listener) {\n let sub = this._emitter.off(eventType, listener);\n if (sub) {\n delete this._subs[sub];\n }\n return sub;\n }\n\n removeAllListeners() {\n let current_subs = this._subs;\n this._subs = {};\n Object.keys(current_subs).forEach((sub) => {\n this._emitter.off(current_subs[sub], sub);\n });\n }\n}\n","import Events from \"./events\";\n\nexport default class Var {\n constructor(group, name, /*optional*/ value) {\n this._group = group;\n this._name = name;\n this._value = value;\n this._events = new Events();\n }\n\n get() {\n return this._value;\n }\n\n set(value, /*optional*/ event) {\n if (this._value === value) {\n // Do nothing; the value hasn't changed\n return;\n }\n let oldValue = this._value;\n this._value = value;\n // Alert JavaScript listeners that the value has changed\n let evt = {};\n if (event && typeof(event) === \"object\") {\n for (let k in event) {\n if (event.hasOwnProperty(k))\n evt[k] = event[k];\n }\n }\n evt.oldValue = oldValue;\n evt.value = value;\n this._events.trigger(\"change\", evt, this);\n\n // TODO: Make this extensible, to let arbitrary back-ends know that\n // something has changed\n if (global.Shiny && global.Shiny.onInputChange) {\n global.Shiny.onInputChange(\n \".clientValue-\" +\n (this._group.name !== null ? this._group.name + \"-\" : \"\") +\n this._name,\n typeof(value) === \"undefined\" ? null : value\n );\n }\n }\n\n on(eventType, listener) {\n return this._events.on(eventType, listener);\n }\n\n off(eventType, listener) {\n return this._events.off(eventType, listener);\n }\n}\n"]} \ No newline at end of file diff --git a/docs/articles/get_started_files/crosstalk-1.2.2/scss/crosstalk.scss b/docs/articles/get_started_files/crosstalk-1.2.2/scss/crosstalk.scss deleted file mode 100644 index 3566561..0000000 --- a/docs/articles/get_started_files/crosstalk-1.2.2/scss/crosstalk.scss +++ /dev/null @@ -1,75 +0,0 @@ -/* Adjust margins outwards, so column contents line up with the edges of the - parent of container-fluid. */ -.container-fluid.crosstalk-bscols { - margin-left: -30px; - margin-right: -30px; - white-space: normal; -} - -/* But don't adjust the margins outwards if we're directly under the body, - i.e. we were the top-level of something at the console. */ -body > .container-fluid.crosstalk-bscols { - margin-left: auto; - margin-right: auto; -} - -.crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column { - display: inline-block; - padding-right: 12px; - vertical-align: top; -} - -@media only screen and (max-width:480px) { - .crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column { - display: block; - padding-right: inherit; - } -} - -/* Relevant BS3 styles to make filter_checkbox() look reasonable without Bootstrap */ -.crosstalk-input { - margin-bottom: 15px; /* a la .form-group */ - .control-label { - margin-bottom: 0; - vertical-align: middle; - } - input[type="checkbox"] { - margin: 4px 0 0; - margin-top: 1px; - line-height: normal; - } - .checkbox { - position: relative; - display: block; - margin-top: 10px; - margin-bottom: 10px; - } - .checkbox > label{ - padding-left: 20px; - margin-bottom: 0; - font-weight: 400; - cursor: pointer; - } - .checkbox input[type="checkbox"], - .checkbox-inline input[type="checkbox"] { - position: absolute; - margin-top: 2px; - margin-left: -20px; - } - .checkbox + .checkbox { - margin-top: -5px; - } - .checkbox-inline { - position: relative; - display: inline-block; - padding-left: 20px; - margin-bottom: 0; - font-weight: 400; - vertical-align: middle; - cursor: pointer; - } - .checkbox-inline + .checkbox-inline { - margin-top: 0; - margin-left: 10px; - } -} diff --git a/docs/articles/get_started_files/datatables-binding-0.33/datatables.js b/docs/articles/get_started_files/datatables-binding-0.33/datatables.js deleted file mode 100644 index 765b53c..0000000 --- a/docs/articles/get_started_files/datatables-binding-0.33/datatables.js +++ /dev/null @@ -1,1539 +0,0 @@ -(function() { - -// some helper functions: using a global object DTWidget so that it can be used -// in JS() code, e.g. datatable(options = list(foo = JS('code'))); unlike R's -// dynamic scoping, when 'code' is eval'ed, JavaScript does not know objects -// from the "parent frame", e.g. JS('DTWidget') will not work unless it was made -// a global object -var DTWidget = {}; - -// 123456666.7890 -> 123,456,666.7890 -var markInterval = function(d, digits, interval, mark, decMark, precision) { - x = precision ? d.toPrecision(digits) : d.toFixed(digits); - if (!/^-?[\d.]+$/.test(x)) return x; - var xv = x.split('.'); - if (xv.length > 2) return x; // should have at most one decimal point - xv[0] = xv[0].replace(new RegExp('\\B(?=(\\d{' + interval + '})+(?!\\d))', 'g'), mark); - return xv.join(decMark); -}; - -DTWidget.formatCurrency = function(data, currency, digits, interval, mark, decMark, before, zeroPrint) { - var d = parseFloat(data); - if (isNaN(d)) return ''; - if (zeroPrint !== null && d === 0.0) return zeroPrint; - var res = markInterval(d, digits, interval, mark, decMark); - res = before ? (/^-/.test(res) ? '-' + currency + res.replace(/^-/, '') : currency + res) : - res + currency; - return res; -}; - -DTWidget.formatString = function(data, prefix, suffix) { - var d = data; - if (d === null) return ''; - return prefix + d + suffix; -}; - -DTWidget.formatPercentage = function(data, digits, interval, mark, decMark, zeroPrint) { - var d = parseFloat(data); - if (isNaN(d)) return ''; - if (zeroPrint !== null && d === 0.0) return zeroPrint; - return markInterval(d * 100, digits, interval, mark, decMark) + '%'; -}; - -DTWidget.formatRound = function(data, digits, interval, mark, decMark, zeroPrint) { - var d = parseFloat(data); - if (isNaN(d)) return ''; - if (zeroPrint !== null && d === 0.0) return zeroPrint; - return markInterval(d, digits, interval, mark, decMark); -}; - -DTWidget.formatSignif = function(data, digits, interval, mark, decMark, zeroPrint) { - var d = parseFloat(data); - if (isNaN(d)) return ''; - if (zeroPrint !== null && d === 0.0) return zeroPrint; - return markInterval(d, digits, interval, mark, decMark, true); -}; - -DTWidget.formatDate = function(data, method, params) { - var d = data; - if (d === null) return ''; - // (new Date('2015-10-28')).toDateString() may return 2015-10-27 because the - // actual time created could be like 'Tue Oct 27 2015 19:00:00 GMT-0500 (CDT)', - // i.e. the date-only string is treated as UTC time instead of local time - if ((method === 'toDateString' || method === 'toLocaleDateString') && /^\d{4,}\D\d{2}\D\d{2}$/.test(d)) { - d = d.split(/\D/); - d = new Date(d[0], d[1] - 1, d[2]); - } else { - d = new Date(d); - } - return d[method].apply(d, params); -}; - -window.DTWidget = DTWidget; - -// A helper function to update the properties of existing filters -var setFilterProps = function(td, props) { - // Update enabled/disabled state - var $input = $(td).find('input').first(); - var searchable = $input.data('searchable'); - $input.prop('disabled', !searchable || props.disabled); - - // Based on the filter type, set its new values - var type = td.getAttribute('data-type'); - if (['factor', 'logical'].includes(type)) { - // Reformat the new dropdown options for use with selectize - var new_vals = props.params.options.map(function(item) { - return { text: item, value: item }; - }); - - // Find the selectize object - var dropdown = $(td).find('.selectized').eq(0)[0].selectize; - - // Note the current values - var old_vals = dropdown.getValue(); - - // Remove the existing values - dropdown.clearOptions(); - - // Add the new options - dropdown.addOption(new_vals); - - // Preserve the existing values - dropdown.setValue(old_vals); - - } else if (['number', 'integer', 'date', 'time'].includes(type)) { - // Apply internal scaling to new limits. Updating scale not yet implemented. - var slider = $(td).find('.noUi-target').eq(0); - var scale = Math.pow(10, Math.max(0, +slider.data('scale') || 0)); - var new_vals = [props.params.min * scale, props.params.max * scale]; - - // Note what the new limits will be just for this filter - var new_lims = new_vals.slice(); - - // Determine the current values and limits - var old_vals = slider.val().map(Number); - var old_lims = slider.noUiSlider('options').range; - old_lims = [old_lims.min, old_lims.max]; - - // Preserve the current values if filters have been applied; otherwise, apply no filtering - if (old_vals[0] != old_lims[0]) { - new_vals[0] = Math.max(old_vals[0], new_vals[0]); - } - - if (old_vals[1] != old_lims[1]) { - new_vals[1] = Math.min(old_vals[1], new_vals[1]); - } - - // Update the endpoints of the slider - slider.noUiSlider({ - start: new_vals, - range: {'min': new_lims[0], 'max': new_lims[1]} - }, true); - } -}; - -var transposeArray2D = function(a) { - return a.length === 0 ? a : HTMLWidgets.transposeArray2D(a); -}; - -var crosstalkPluginsInstalled = false; - -function maybeInstallCrosstalkPlugins() { - if (crosstalkPluginsInstalled) - return; - crosstalkPluginsInstalled = true; - - $.fn.dataTable.ext.afnFiltering.push( - function(oSettings, aData, iDataIndex) { - var ctfilter = oSettings.nTable.ctfilter; - if (ctfilter && !ctfilter[iDataIndex]) - return false; - - var ctselect = oSettings.nTable.ctselect; - if (ctselect && !ctselect[iDataIndex]) - return false; - - return true; - } - ); -} - -HTMLWidgets.widget({ - name: "datatables", - type: "output", - renderOnNullValue: true, - initialize: function(el, width, height) { - // in order that the type=number inputs return a number - $.valHooks.number = { - get: function(el) { - var value = parseFloat(el.value); - return isNaN(value) ? "" : value; - } - }; - $(el).html(' '); - return { - data: null, - ctfilterHandle: new crosstalk.FilterHandle(), - ctfilterSubscription: null, - ctselectHandle: new crosstalk.SelectionHandle(), - ctselectSubscription: null - }; - }, - renderValue: function(el, data, instance) { - if (el.offsetWidth === 0 || el.offsetHeight === 0) { - instance.data = data; - return; - } - instance.data = null; - var $el = $(el); - $el.empty(); - - if (data === null) { - $el.append(' '); - // clear previous Shiny inputs (if any) - for (var i in instance.clearInputs) instance.clearInputs[i](); - instance.clearInputs = {}; - return; - } - - var crosstalkOptions = data.crosstalkOptions; - if (!crosstalkOptions) crosstalkOptions = { - 'key': null, 'group': null - }; - if (crosstalkOptions.group) { - maybeInstallCrosstalkPlugins(); - instance.ctfilterHandle.setGroup(crosstalkOptions.group); - instance.ctselectHandle.setGroup(crosstalkOptions.group); - } - - // if we are in the viewer then we always want to fillContainer and - // and autoHideNavigation (unless the user has explicitly set these) - if (window.HTMLWidgets.viewerMode) { - if (!data.hasOwnProperty("fillContainer")) - data.fillContainer = true; - if (!data.hasOwnProperty("autoHideNavigation")) - data.autoHideNavigation = true; - } - - // propagate fillContainer to instance (so we have it in resize) - instance.fillContainer = data.fillContainer; - - var cells = data.data; - - if (cells instanceof Array) cells = transposeArray2D(cells); - - $el.append(data.container); - var $table = $el.find('table'); - if (data.class) $table.addClass(data.class); - if (data.caption) $table.prepend(data.caption); - - if (!data.selection) data.selection = { - mode: 'none', selected: null, target: 'row', selectable: null - }; - if (HTMLWidgets.shinyMode && data.selection.mode !== 'none' && - data.selection.target === 'row+column') { - if ($table.children('tfoot').length === 0) { - $table.append($('')); - $table.find('thead tr').clone().appendTo($table.find('tfoot')); - } - } - - // column filters - var filterRow; - switch (data.filter) { - case 'top': - $table.children('thead').append(data.filterHTML); - filterRow = $table.find('thead tr:last td'); - break; - case 'bottom': - if ($table.children('tfoot').length === 0) { - $table.append($('')); - } - $table.children('tfoot').prepend(data.filterHTML); - filterRow = $table.find('tfoot tr:first td'); - break; - } - - var options = { searchDelay: 1000 }; - if (cells !== null) $.extend(options, { - data: cells - }); - - // options for fillContainer - var bootstrapActive = typeof($.fn.popover) != 'undefined'; - if (instance.fillContainer) { - - // force scrollX/scrollY and turn off autoWidth - options.scrollX = true; - options.scrollY = "100px"; // can be any value, we'll adjust below - - // if we aren't paginating then move around the info/filter controls - // to save space at the bottom and rephrase the info callback - if (data.options.paging === false) { - - // we know how to do this cleanly for bootstrap, not so much - // for other themes/layouts - if (bootstrapActive) { - options.dom = "<'row'<'col-sm-4'i><'col-sm-8'f>>" + - "<'row'<'col-sm-12'tr>>"; - } - - options.fnInfoCallback = function(oSettings, iStart, iEnd, - iMax, iTotal, sPre) { - return Number(iTotal).toLocaleString() + " records"; - }; - } - } - - // auto hide navigation if requested - // Note, this only works on client-side processing mode as on server-side, - // cells (data.data) is null; In addition, we require the pageLength option - // being provided explicitly to enable this. Despite we may be able to deduce - // the default value of pageLength, it may complicate things so we'd rather - // put this responsiblity to users and warn them on the R side. - if (data.autoHideNavigation === true && data.options.paging !== false) { - // strip all nav if length >= cells - if ((cells instanceof Array) && data.options.pageLength >= cells.length) - options.dom = bootstrapActive ? "<'row'<'col-sm-12'tr>>" : "t"; - // alternatively lean things out for flexdashboard mobile portrait - else if (bootstrapActive && window.FlexDashboard && window.FlexDashboard.isMobilePhone()) - options.dom = "<'row'<'col-sm-12'f>>" + - "<'row'<'col-sm-12'tr>>" + - "<'row'<'col-sm-12'p>>"; - } - - $.extend(true, options, data.options || {}); - - var searchCols = options.searchCols; - if (searchCols) { - searchCols = searchCols.map(function(x) { - return x === null ? '' : x.search; - }); - // FIXME: this means I don't respect the escapeRegex setting - delete options.searchCols; - } - - // server-side processing? - var server = options.serverSide === true; - - // use the dataSrc function to pre-process JSON data returned from R - var DT_rows_all = [], DT_rows_current = []; - if (server && HTMLWidgets.shinyMode && typeof options.ajax === 'object' && - /^session\/[\da-z]+\/dataobj/.test(options.ajax.url) && !options.ajax.dataSrc) { - options.ajax.dataSrc = function(json) { - DT_rows_all = $.makeArray(json.DT_rows_all); - DT_rows_current = $.makeArray(json.DT_rows_current); - var data = json.data; - if (!colReorderEnabled()) return data; - var table = $table.DataTable(), order = table.colReorder.order(), flag = true, i, j, row; - for (i = 0; i < order.length; ++i) if (order[i] !== i) flag = false; - if (flag) return data; - for (i = 0; i < data.length; ++i) { - row = data[i].slice(); - for (j = 0; j < order.length; ++j) data[i][j] = row[order[j]]; - } - return data; - }; - } - - var thiz = this; - if (instance.fillContainer) $table.on('init.dt', function(e) { - thiz.fillAvailableHeight(el, $(el).innerHeight()); - }); - // If the page contains serveral datatables and one of which enables colReorder, - // the table.colReorder.order() function will exist but throws error when called. - // So it seems like the only way to know if colReorder is enabled or not is to - // check the options. - var colReorderEnabled = function() { return "colReorder" in options; }; - var table = $table.DataTable(options); - $el.data('datatable', table); - - if ('rowGroup' in options) { - // Maintain RowGroup dataSrc when columns are reordered (#1109) - table.on('column-reorder', function(e, settings, details) { - var oldDataSrc = table.rowGroup().dataSrc(); - var newDataSrc = details.mapping[oldDataSrc]; - table.rowGroup().dataSrc(newDataSrc); - }); - } - - // Unregister previous Crosstalk event subscriptions, if they exist - if (instance.ctfilterSubscription) { - instance.ctfilterHandle.off("change", instance.ctfilterSubscription); - instance.ctfilterSubscription = null; - } - if (instance.ctselectSubscription) { - instance.ctselectHandle.off("change", instance.ctselectSubscription); - instance.ctselectSubscription = null; - } - - if (!crosstalkOptions.group) { - $table[0].ctfilter = null; - $table[0].ctselect = null; - } else { - var key = crosstalkOptions.key; - function keysToMatches(keys) { - if (!keys) { - return null; - } else { - var selectedKeys = {}; - for (var i = 0; i < keys.length; i++) { - selectedKeys[keys[i]] = true; - } - var matches = {}; - for (var j = 0; j < key.length; j++) { - if (selectedKeys[key[j]]) - matches[j] = true; - } - return matches; - } - } - - function applyCrosstalkFilter(e) { - $table[0].ctfilter = keysToMatches(e.value); - table.draw(); - } - instance.ctfilterSubscription = instance.ctfilterHandle.on("change", applyCrosstalkFilter); - applyCrosstalkFilter({value: instance.ctfilterHandle.filteredKeys}); - - function applyCrosstalkSelection(e) { - if (e.sender !== instance.ctselectHandle) { - table - .rows('.' + selClass, {search: 'applied'}) - .nodes() - .to$() - .removeClass(selClass); - if (selectedRows) - changeInput('rows_selected', selectedRows(), void 0, true); - } - - if (e.sender !== instance.ctselectHandle && e.value && e.value.length) { - var matches = keysToMatches(e.value); - - // persistent selection with plotly (& leaflet) - var ctOpts = crosstalk.var("plotlyCrosstalkOpts").get() || {}; - if (ctOpts.persistent === true) { - var matches = $.extend(matches, $table[0].ctselect); - } - - $table[0].ctselect = matches; - table.draw(); - } else { - if ($table[0].ctselect) { - $table[0].ctselect = null; - table.draw(); - } - } - } - instance.ctselectSubscription = instance.ctselectHandle.on("change", applyCrosstalkSelection); - // TODO: This next line doesn't seem to work when renderDataTable is used - applyCrosstalkSelection({value: instance.ctselectHandle.value}); - } - - var inArray = function(val, array) { - return $.inArray(val, $.makeArray(array)) > -1; - }; - - // search the i-th column - var searchColumn = function(i, value) { - var regex = false, ci = true; - if (options.search) { - regex = options.search.regex, - ci = options.search.caseInsensitive !== false; - } - // need to transpose the column index when colReorder is enabled - if (table.colReorder) i = table.colReorder.transpose(i); - return table.column(i).search(value, regex, !regex, ci); - }; - - if (data.filter !== 'none') { - if (!data.hasOwnProperty('filterSettings')) data.filterSettings = {}; - - filterRow.each(function(i, td) { - - var $td = $(td), type = $td.data('type'), filter; - var $input = $td.children('div').first().children('input'); - var disabled = $input.prop('disabled'); - var searchable = table.settings()[0].aoColumns[i].bSearchable; - $input.prop('disabled', !searchable || disabled); - $input.data('searchable', searchable); // for updating later - $input.on('input blur', function() { - $input.next('span').toggle(Boolean($input.val())); - }); - // Bootstrap sets pointer-events to none and we won't be able to click - // the clear button - $input.next('span').css('pointer-events', 'auto').hide().click(function() { - $(this).hide().prev('input').val('').trigger('input').focus(); - }); - var searchCol; // search string for this column - if (searchCols && searchCols[i]) { - searchCol = searchCols[i]; - $input.val(searchCol).trigger('input'); - } - var $x = $td.children('div').last(); - - // remove the overflow: hidden attribute of the scrollHead - // (otherwise the scrolling table body obscures the filters) - // The workaround and the discussion from - // https://github.com/rstudio/DT/issues/554#issuecomment-518007347 - // Otherwise the filter selection will not be anchored to the values - // when the columns number is many and scrollX is enabled. - var scrollHead = $(el).find('.dataTables_scrollHead,.dataTables_scrollFoot'); - var cssOverflowHead = scrollHead.css('overflow'); - var scrollBody = $(el).find('.dataTables_scrollBody'); - var cssOverflowBody = scrollBody.css('overflow'); - var scrollTable = $(el).find('.dataTables_scroll'); - var cssOverflowTable = scrollTable.css('overflow'); - if (cssOverflowHead === 'hidden') { - $x.on('show hide', function(e) { - if (e.type === 'show') { - scrollHead.css('overflow', 'visible'); - scrollBody.css('overflow', 'visible'); - scrollTable.css('overflow-x', 'scroll'); - } else { - scrollHead.css('overflow', cssOverflowHead); - scrollBody.css('overflow', cssOverflowBody); - scrollTable.css('overflow-x', cssOverflowTable); - } - }); - $x.css('z-index', 25); - } - - if (inArray(type, ['factor', 'logical'])) { - $input.on({ - click: function() { - $input.parent().hide(); $x.show().trigger('show'); filter[0].selectize.focus(); - }, - input: function() { - var v1 = JSON.stringify(filter[0].selectize.getValue()), v2 = $input.val(); - if (v1 === '[]') v1 = ''; - if (v1 !== v2) filter[0].selectize.setValue(v2 === '' ? [] : JSON.parse(v2)); - } - }); - var $input2 = $x.children('select'); - filter = $input2.selectize($.extend({ - options: $input2.data('options').map(function(v, i) { - return ({text: v, value: v}); - }), - plugins: ['remove_button'], - hideSelected: true, - onChange: function(value) { - if (value === null) value = []; // compatibility with jQuery 3.0 - $input.val(value.length ? JSON.stringify(value) : ''); - if (value.length) $input.trigger('input'); - $input.attr('title', $input.val()); - if (server) { - searchColumn(i, value.length ? JSON.stringify(value) : '').draw(); - return; - } - // turn off filter if nothing selected - $td.data('filter', value.length > 0); - table.draw(); // redraw table, and filters will be applied - } - }, data.filterSettings.select)); - filter[0].selectize.on('blur', function() { - $x.hide().trigger('hide'); $input.parent().show(); $input.trigger('blur'); - }); - filter.next('div').css('margin-bottom', 'auto'); - } else if (type === 'character') { - var fun = function() { - searchColumn(i, $input.val()).draw(); - }; - // throttle searching for server-side processing - var throttledFun = $.fn.dataTable.util.throttle(fun, options.searchDelay); - $input.on('input', function(e, immediate) { - // always bypass throttling when immediate = true (via the updateSearch method) - (immediate || !server) ? fun() : throttledFun(); - }); - } else if (inArray(type, ['number', 'integer', 'date', 'time'])) { - var $x0 = $x; - $x = $x0.children('div').first(); - $x0.css({ - 'background-color': '#fff', - 'border': '1px #ddd solid', - 'border-radius': '4px', - 'padding': data.vertical ? '35px 20px': '20px 20px 10px 20px' - }); - var $spans = $x0.children('span').css({ - 'margin-top': data.vertical ? '0' : '10px', - 'white-space': 'nowrap' - }); - var $span1 = $spans.first(), $span2 = $spans.last(); - var r1 = +$x.data('min'), r2 = +$x.data('max'); - // when the numbers are too small or have many decimal places, the - // slider may have numeric precision problems (#150) - var scale = Math.pow(10, Math.max(0, +$x.data('scale') || 0)); - r1 = Math.round(r1 * scale); r2 = Math.round(r2 * scale); - var scaleBack = function(x, scale) { - if (scale === 1) return x; - var d = Math.round(Math.log(scale) / Math.log(10)); - // to avoid problems like 3.423/100 -> 0.034230000000000003 - return (x / scale).toFixed(d); - }; - var slider_min = function() { - return filter.noUiSlider('options').range.min; - }; - var slider_max = function() { - return filter.noUiSlider('options').range.max; - }; - $input.on({ - focus: function() { - $x0.show().trigger('show'); - // first, make sure the slider div leaves at least 20px between - // the two (slider value) span's - $x0.width(Math.max(160, $span1.outerWidth() + $span2.outerWidth() + 20)); - // then, if the input is really wide or slider is vertical, - // make the slider the same width as the input - if ($x0.outerWidth() < $input.outerWidth() || data.vertical) { - $x0.outerWidth($input.outerWidth()); - } - // make sure the slider div does not reach beyond the right margin - if ($(window).width() < $x0.offset().left + $x0.width()) { - $x0.offset({ - 'left': $input.offset().left + $input.outerWidth() - $x0.outerWidth() - }); - } - }, - blur: function() { - $x0.hide().trigger('hide'); - }, - input: function() { - if ($input.val() === '') filter.val([slider_min(), slider_max()]); - }, - change: function() { - var v = $input.val().replace(/\s/g, ''); - if (v === '') return; - v = v.split('...'); - if (v.length !== 2) { - $input.parent().addClass('has-error'); - return; - } - if (v[0] === '') v[0] = slider_min(); - if (v[1] === '') v[1] = slider_max(); - $input.parent().removeClass('has-error'); - // treat date as UTC time at midnight - var strTime = function(x) { - var s = type === 'date' ? 'T00:00:00Z' : ''; - var t = new Date(x + s).getTime(); - // add 10 minutes to date since it does not hurt the date, and - // it helps avoid the tricky floating point arithmetic problems, - // e.g. sometimes the date may be a few milliseconds earlier - // than the midnight due to precision problems in noUiSlider - return type === 'date' ? t + 3600000 : t; - }; - if (inArray(type, ['date', 'time'])) { - v[0] = strTime(v[0]); - v[1] = strTime(v[1]); - } - if (v[0] != slider_min()) v[0] *= scale; - if (v[1] != slider_max()) v[1] *= scale; - filter.val(v); - } - }); - var formatDate = function(d) { - d = scaleBack(d, scale); - if (type === 'number') return d; - if (type === 'integer') return parseInt(d); - var x = new Date(+d); - if (type === 'date') { - var pad0 = function(x) { - return ('0' + x).substr(-2, 2); - }; - return x.getUTCFullYear() + '-' + pad0(1 + x.getUTCMonth()) - + '-' + pad0(x.getUTCDate()); - } else { - return x.toISOString(); - } - }; - var opts = type === 'date' ? { step: 60 * 60 * 1000 } : - type === 'integer' ? { step: 1 } : {}; - - opts.orientation = data.vertical ? 'vertical': 'horizontal'; - opts.direction = data.vertical ? 'rtl': 'ltr'; - - filter = $x.noUiSlider($.extend({ - start: [r1, r2], - range: {min: r1, max: r2}, - connect: true - }, opts, data.filterSettings.slider)); - if (scale > 1) (function() { - var t1 = r1, t2 = r2; - var val = filter.val(); - while (val[0] > r1 || val[1] < r2) { - if (val[0] > r1) { - t1 -= val[0] - r1; - } - if (val[1] < r2) { - t2 += r2 - val[1]; - } - filter = $x.noUiSlider($.extend({ - start: [t1, t2], - range: {min: t1, max: t2}, - connect: true - }, opts, data.filterSettings.slider), true); - val = filter.val(); - } - r1 = t1; r2 = t2; - })(); - // format with active column renderer, if defined - var colDef = data.options.columnDefs.find(function(def) { - return (def.targets === i || inArray(i, def.targets)) && 'render' in def; - }); - var updateSliderText = function(v1, v2) { - // we only know how to use function renderers - if (colDef && typeof colDef.render === 'function') { - var restore = function(v) { - v = scaleBack(v, scale); - return inArray(type, ['date', 'time']) ? new Date(+v) : v; - } - $span1.text(colDef.render(restore(v1), 'display')); - $span2.text(colDef.render(restore(v2), 'display')); - } else { - $span1.text(formatDate(v1)); - $span2.text(formatDate(v2)); - } - }; - updateSliderText(r1, r2); - var updateSlider = function(e) { - var val = filter.val(); - // turn off filter if in full range - $td.data('filter', val[0] > slider_min() || val[1] < slider_max()); - var v1 = formatDate(val[0]), v2 = formatDate(val[1]), ival; - if ($td.data('filter')) { - ival = v1 + ' ... ' + v2; - $input.attr('title', ival).val(ival).trigger('input'); - } else { - $input.attr('title', '').val(''); - } - updateSliderText(val[0], val[1]); - if (e.type === 'slide') return; // no searching when sliding only - if (server) { - searchColumn(i, $td.data('filter') ? ival : '').draw(); - return; - } - table.draw(); - }; - filter.on({ - set: updateSlider, - slide: updateSlider - }); - } - - // server-side processing will be handled by R (or whatever server - // language you use); the following code is only needed for client-side - // processing - if (server) { - // if a search string has been pre-set, search now - if (searchCol) $input.trigger('input').trigger('change'); - return; - } - - var customFilter = function(settings, data, dataIndex) { - // there is no way to attach a search function to a specific table, - // and we need to make sure a global search function is not applied to - // all tables (i.e. a range filter in a previous table should not be - // applied to the current table); we use the settings object to - // determine if we want to perform searching on the current table, - // since settings.sTableId will be different to different tables - if (table.settings()[0] !== settings) return true; - // no filter on this column or no need to filter this column - if (typeof filter === 'undefined' || !$td.data('filter')) return true; - - var r = filter.val(), v, r0, r1; - var i_data = function(i) { - if (!colReorderEnabled()) return i; - var order = table.colReorder.order(), k; - for (k = 0; k < order.length; ++k) if (order[k] === i) return k; - return i; // in theory it will never be here... - } - v = data[i_data(i)]; - if (type === 'number' || type === 'integer') { - v = parseFloat(v); - // how to handle NaN? currently exclude these rows - if (isNaN(v)) return(false); - r0 = parseFloat(scaleBack(r[0], scale)) - r1 = parseFloat(scaleBack(r[1], scale)); - if (v >= r0 && v <= r1) return true; - } else if (type === 'date' || type === 'time') { - v = new Date(v); - r0 = new Date(r[0] / scale); r1 = new Date(r[1] / scale); - if (v >= r0 && v <= r1) return true; - } else if (type === 'factor') { - if (r.length === 0 || inArray(v, r)) return true; - } else if (type === 'logical') { - if (r.length === 0) return true; - if (inArray(v === '' ? 'na' : v, r)) return true; - } - return false; - }; - - $.fn.dataTable.ext.search.push(customFilter); - - // search for the preset search strings if it is non-empty - if (searchCol) $input.trigger('input').trigger('change'); - - }); - - } - - // highlight search keywords - var highlight = function() { - var body = $(table.table().body()); - // removing the old highlighting first - body.unhighlight(); - - // don't highlight the "not found" row, so we get the rows using the api - if (table.rows({ filter: 'applied' }).data().length === 0) return; - // highlight global search keywords - body.highlight($.trim(table.search()).split(/\s+/)); - // then highlight keywords from individual column filters - if (filterRow) filterRow.each(function(i, td) { - var $td = $(td), type = $td.data('type'); - if (type !== 'character') return; - var $input = $td.children('div').first().children('input'); - var column = table.column(i).nodes().to$(), - val = $.trim($input.val()); - if (type !== 'character' || val === '') return; - column.highlight(val.split(/\s+/)); - }); - }; - - if (options.searchHighlight) { - table - .on('draw.dt.dth column-visibility.dt.dth column-reorder.dt.dth', highlight) - .on('destroy', function() { - // remove event handler - table.off('draw.dt.dth column-visibility.dt.dth column-reorder.dt.dth'); - }); - - // Set the option for escaping regex characters in our search string. This will be used - // for all future matching. - jQuery.fn.highlight.options.escapeRegex = (!options.search || !options.search.regex); - - // initial highlight for state saved conditions and initial states - highlight(); - } - - // run the callback function on the table instance - if (typeof data.callback === 'function') data.callback(table); - - // double click to edit the cell, row, column, or all cells - if (data.editable) table.on('dblclick.dt', 'tbody td', function(e) { - // only bring up the editor when the cell itself is dbclicked, and ignore - // other dbclick events bubbled up (e.g. from the ) - if (e.target !== this) return; - var target = [], immediate = false; - switch (data.editable.target) { - case 'cell': - target = [this]; - immediate = true; // edit will take effect immediately - break; - case 'row': - target = table.cells(table.cell(this).index().row, '*').nodes(); - break; - case 'column': - target = table.cells('*', table.cell(this).index().column).nodes(); - break; - case 'all': - target = table.cells().nodes(); - break; - default: - throw 'The editable parameter must be "cell", "row", "column", or "all"'; - } - var disableCols = data.editable.disable ? data.editable.disable.columns : null; - var numericCols = data.editable.numeric; - var areaCols = data.editable.area; - var dateCols = data.editable.date; - for (var i = 0; i < target.length; i++) { - (function(cell, current) { - var $cell = $(cell), html = $cell.html(); - var _cell = table.cell(cell), value = _cell.data(), index = _cell.index().column; - var $input; - if (inArray(index, numericCols)) { - $input = $(''); - } else if (inArray(index, areaCols)) { - $input = $(''); - } else if (inArray(index, dateCols)) { - $input = $(''); - } else { - $input = $(''); - } - if (!immediate) { - $cell.data('input', $input).data('html', html); - $input.attr('title', 'Hit Ctrl+Enter to finish editing, or Esc to cancel'); - } - $input.val(value); - if (inArray(index, disableCols)) { - $input.attr('readonly', '').css('filter', 'invert(25%)'); - } - $cell.empty().append($input); - if (cell === current) $input.focus(); - $input.css('width', '100%'); - - if (immediate) $input.on('blur', function(e) { - var valueNew = $input.val(); - if (valueNew !== value) { - _cell.data(valueNew); - if (HTMLWidgets.shinyMode) { - changeInput('cell_edit', [cellInfo(cell)], 'DT.cellInfo', null, {priority: 'event'}); - } - // for server-side processing, users have to call replaceData() to update the table - if (!server) table.draw(false); - } else { - $cell.html(html); - } - }).on('keyup', function(e) { - // hit Escape to cancel editing - if (e.keyCode === 27) $input.trigger('blur'); - }); - - // bulk edit (row, column, or all) - if (!immediate) $input.on('keyup', function(e) { - var removeInput = function($cell, restore) { - $cell.data('input').remove(); - if (restore) $cell.html($cell.data('html')); - } - if (e.keyCode === 27) { - for (var i = 0; i < target.length; i++) { - removeInput($(target[i]), true); - } - } else if (e.keyCode === 13 && e.ctrlKey) { - // Ctrl + Enter - var cell, $cell, _cell, cellData = []; - for (var i = 0; i < target.length; i++) { - cell = target[i]; $cell = $(cell); _cell = table.cell(cell); - _cell.data($cell.data('input').val()); - HTMLWidgets.shinyMode && cellData.push(cellInfo(cell)); - removeInput($cell, false); - } - if (HTMLWidgets.shinyMode) { - changeInput('cell_edit', cellData, 'DT.cellInfo', null, {priority: "event"}); - } - if (!server) table.draw(false); - } - }); - })(target[i], this); - } - }); - - // interaction with shiny - if (!HTMLWidgets.shinyMode && !crosstalkOptions.group) return; - - var methods = {}; - var shinyData = {}; - - methods.updateCaption = function(caption) { - if (!caption) return; - $table.children('caption').replaceWith(caption); - } - - // register clear functions to remove input values when the table is removed - instance.clearInputs = {}; - - var changeInput = function(id, value, type, noCrosstalk, opts) { - var event = id; - id = el.id + '_' + id; - if (type) id = id + ':' + type; - // do not update if the new value is the same as old value - if (event !== 'cell_edit' && !/_clicked$/.test(event) && shinyData.hasOwnProperty(id) && shinyData[id] === JSON.stringify(value)) - return; - shinyData[id] = JSON.stringify(value); - if (HTMLWidgets.shinyMode && Shiny.setInputValue) { - Shiny.setInputValue(id, value, opts); - if (!instance.clearInputs[id]) instance.clearInputs[id] = function() { - Shiny.setInputValue(id, null); - } - } - - // HACK - if (event === "rows_selected" && !noCrosstalk) { - if (crosstalkOptions.group) { - var keys = crosstalkOptions.key; - var selectedKeys = null; - if (value) { - selectedKeys = []; - for (var i = 0; i < value.length; i++) { - // The value array's contents use 1-based row numbers, so we must - // convert to 0-based before indexing into the keys array. - selectedKeys.push(keys[value[i] - 1]); - } - } - instance.ctselectHandle.set(selectedKeys); - } - } - }; - - var addOne = function(x) { - return x.map(function(i) { return 1 + i; }); - }; - - var unique = function(x) { - var ux = []; - $.each(x, function(i, el){ - if ($.inArray(el, ux) === -1) ux.push(el); - }); - return ux; - } - - // change the row index of a cell - var tweakCellIndex = function(cell) { - var info = cell.index(); - // some cell may not be valid. e.g, #759 - // when using the RowGroup extension, datatables will - // generate the row label and the cells are not part of - // the data thus contain no row/col info - if (info === undefined) - return {row: null, col: null}; - if (server) { - info.row = DT_rows_current[info.row]; - } else { - info.row += 1; - } - return {row: info.row, col: info.column}; - } - - var cleanSelectedValues = function() { - changeInput('rows_selected', []); - changeInput('columns_selected', []); - changeInput('cells_selected', transposeArray2D([]), 'shiny.matrix'); - } - // #828 we should clean the selection on the server-side when the table reloads - cleanSelectedValues(); - - // a flag to indicates if select extension is initialized or not - var flagSelectExt = table.settings()[0]._select !== undefined; - // the Select extension should only be used in the client mode and - // when the selection.mode is set to none - if (data.selection.mode === 'none' && !server && flagSelectExt) { - var updateRowsSelected = function() { - var rows = table.rows({selected: true}); - var selected = []; - $.each(rows.indexes().toArray(), function(i, v) { - selected.push(v + 1); - }); - changeInput('rows_selected', selected); - } - var updateColsSelected = function() { - var columns = table.columns({selected: true}); - changeInput('columns_selected', columns.indexes().toArray()); - } - var updateCellsSelected = function() { - var cells = table.cells({selected: true}); - var selected = []; - cells.every(function() { - var row = this.index().row; - var col = this.index().column; - selected = selected.concat([[row + 1, col]]); - }); - changeInput('cells_selected', transposeArray2D(selected), 'shiny.matrix'); - } - table.on('select deselect', function(e, dt, type, indexes) { - updateRowsSelected(); - updateColsSelected(); - updateCellsSelected(); - }) - updateRowsSelected(); - updateColsSelected(); - updateCellsSelected(); - } - - var selMode = data.selection.mode, selTarget = data.selection.target; - var selDisable = data.selection.selectable === false; - if (inArray(selMode, ['single', 'multiple'])) { - var selClass = inArray(data.style, ['bootstrap', 'bootstrap4']) ? 'active' : 'selected'; - // selected1: row indices; selected2: column indices - var initSel = function(x) { - if (x === null || typeof x === 'boolean' || selTarget === 'cell') { - return {rows: [], cols: []}; - } else if (selTarget === 'row') { - return {rows: $.makeArray(x), cols: []}; - } else if (selTarget === 'column') { - return {rows: [], cols: $.makeArray(x)}; - } else if (selTarget === 'row+column') { - return {rows: $.makeArray(x.rows), cols: $.makeArray(x.cols)}; - } - } - var selected = data.selection.selected; - var selected1 = initSel(selected).rows, selected2 = initSel(selected).cols; - // selectable should contain either all positive or all non-positive values, not both - // positive values indicate "selectable" while non-positive values means "nonselectable" - // the assertion is performed on R side. (only column indicides could be zero which indicates - // the row name) - var selectable = data.selection.selectable; - var selectable1 = initSel(selectable).rows, selectable2 = initSel(selectable).cols; - - // After users reorder the rows or filter the table, we cannot use the table index - // directly. Instead, we need this function to find out the rows between the two clicks. - // If user filter the table again between the start click and the end click, the behavior - // would be undefined, but it should not be a problem. - var shiftSelRowsIndex = function(start, end) { - var indexes = server ? DT_rows_all : table.rows({ search: 'applied' }).indexes().toArray(); - start = indexes.indexOf(start); end = indexes.indexOf(end); - // if start is larger than end, we need to swap - if (start > end) { - var tmp = end; end = start; start = tmp; - } - return indexes.slice(start, end + 1); - } - - var serverRowIndex = function(clientRowIndex) { - return server ? DT_rows_current[clientRowIndex] : clientRowIndex + 1; - } - - // row, column, or cell selection - var lastClickedRow; - if (inArray(selTarget, ['row', 'row+column'])) { - // Get the current selected rows. It will also - // update the selected1's value based on the current row selection state - // Note we can't put this function inside selectRows() directly, - // the reason is method.selectRows() will override selected1's value but this - // function will add rows to selected1 (keep the existing selection), which is - // inconsistent with column and cell selection. - var selectedRows = function() { - var rows = table.rows('.' + selClass); - var idx = rows.indexes().toArray(); - if (!server) { - selected1 = addOne(idx); - return selected1; - } - idx = idx.map(function(i) { - return DT_rows_current[i]; - }); - selected1 = selMode === 'multiple' ? unique(selected1.concat(idx)) : idx; - return selected1; - } - // Change selected1's value based on selectable1, then refresh the row state - var onlyKeepSelectableRows = function() { - if (selDisable) { // users can't select; useful when only want backend select - selected1 = []; - return; - } - if (selectable1.length === 0) return; - var nonselectable = selectable1[0] <= 0; - if (nonselectable) { - // should make selectable1 positive - selected1 = $(selected1).not(selectable1.map(function(i) { return -i; })).get(); - } else { - selected1 = $(selected1).filter(selectable1).get(); - } - } - // Change selected1's value based on selectable1, then - // refresh the row selection state according to values in selected1 - var selectRows = function(ignoreSelectable) { - if (!ignoreSelectable) onlyKeepSelectableRows(); - table.$('tr.' + selClass).removeClass(selClass); - if (selected1.length === 0) return; - if (server) { - table.rows({page: 'current'}).every(function() { - if (inArray(DT_rows_current[this.index()], selected1)) { - $(this.node()).addClass(selClass); - } - }); - } else { - var selected0 = selected1.map(function(i) { return i - 1; }); - $(table.rows(selected0).nodes()).addClass(selClass); - } - } - table.on('mousedown.dt', 'tbody tr', function(e) { - var $this = $(this), thisRow = table.row(this); - if (selMode === 'multiple') { - if (e.shiftKey && lastClickedRow !== undefined) { - // select or de-select depends on the last clicked row's status - var flagSel = !$this.hasClass(selClass); - var crtClickedRow = serverRowIndex(thisRow.index()); - if (server) { - var rowsIndex = shiftSelRowsIndex(lastClickedRow, crtClickedRow); - // update current page's selClass - rowsIndex.map(function(i) { - var rowIndex = DT_rows_current.indexOf(i); - if (rowIndex >= 0) { - var row = table.row(rowIndex).nodes().to$(); - var flagRowSel = !row.hasClass(selClass); - if (flagSel === flagRowSel) row.toggleClass(selClass); - } - }); - // update selected1 - if (flagSel) { - selected1 = unique(selected1.concat(rowsIndex)); - } else { - selected1 = selected1.filter(function(index) { - return !inArray(index, rowsIndex); - }); - } - } else { - // js starts from 0 - shiftSelRowsIndex(lastClickedRow - 1, crtClickedRow - 1).map(function(value) { - var row = table.row(value).nodes().to$(); - var flagRowSel = !row.hasClass(selClass); - if (flagSel === flagRowSel) row.toggleClass(selClass); - }); - } - e.preventDefault(); - } else { - $this.toggleClass(selClass); - } - } else { - if ($this.hasClass(selClass)) { - $this.removeClass(selClass); - } else { - table.$('tr.' + selClass).removeClass(selClass); - $this.addClass(selClass); - } - } - if (server && !$this.hasClass(selClass)) { - var id = DT_rows_current[thisRow.index()]; - // remove id from selected1 since its class .selected has been removed - if (inArray(id, selected1)) selected1.splice($.inArray(id, selected1), 1); - } - selectedRows(); // update selected1's value based on selClass - selectRows(false); // only keep the selectable rows - changeInput('rows_selected', selected1); - changeInput('row_last_clicked', serverRowIndex(thisRow.index()), null, null, {priority: 'event'}); - lastClickedRow = serverRowIndex(thisRow.index()); - }); - selectRows(false); // in case users have specified pre-selected rows - // restore selected rows after the table is redrawn (e.g. sort/search/page); - // client-side tables will preserve the selections automatically; for - // server-side tables, we have to *real* row indices are in `selected1` - changeInput('rows_selected', selected1); - if (server) table.on('draw.dt', function(e) { selectRows(false); }); - methods.selectRows = function(selected, ignoreSelectable) { - selected1 = $.makeArray(selected); - selectRows(ignoreSelectable); - changeInput('rows_selected', selected1); - } - } - - if (inArray(selTarget, ['column', 'row+column'])) { - if (selTarget === 'row+column') { - $(table.columns().footer()).css('cursor', 'pointer'); - } - // update selected2's value based on selectable2 - var onlyKeepSelectableCols = function() { - if (selDisable) { // users can't select; useful when only want backend select - selected2 = []; - return; - } - if (selectable2.length === 0) return; - var nonselectable = selectable2[0] <= 0; - if (nonselectable) { - // need to make selectable2 positive - selected2 = $(selected2).not(selectable2.map(function(i) { return -i; })).get(); - } else { - selected2 = $(selected2).filter(selectable2).get(); - } - } - // update selected2 and then - // refresh the col selection state according to values in selected2 - var selectCols = function(ignoreSelectable) { - if (!ignoreSelectable) onlyKeepSelectableCols(); - // if selected2 is not a valide index (e.g., larger than the column number) - // table.columns(selected2) will fail and result in a blank table - // this is different from the table.rows(), where the out-of-range indexes - // doesn't affect at all - selected2 = $(selected2).filter(table.columns().indexes()).get(); - table.columns().nodes().flatten().to$().removeClass(selClass); - if (selected2.length > 0) - table.columns(selected2).nodes().flatten().to$().addClass(selClass); - } - var callback = function() { - var colIdx = selTarget === 'column' ? table.cell(this).index().column : - $.inArray(this, table.columns().footer()), - thisCol = $(table.column(colIdx).nodes()); - if (colIdx === -1) return; - if (thisCol.hasClass(selClass)) { - thisCol.removeClass(selClass); - selected2.splice($.inArray(colIdx, selected2), 1); - } else { - if (selMode === 'single') $(table.cells().nodes()).removeClass(selClass); - thisCol.addClass(selClass); - selected2 = selMode === 'single' ? [colIdx] : unique(selected2.concat([colIdx])); - } - selectCols(false); // update selected2 based on selectable - changeInput('columns_selected', selected2); - } - if (selTarget === 'column') { - $(table.table().body()).on('click.dt', 'td', callback); - } else { - $(table.table().footer()).on('click.dt', 'tr th', callback); - } - selectCols(false); // in case users have specified pre-selected columns - changeInput('columns_selected', selected2); - if (server) table.on('draw.dt', function(e) { selectCols(false); }); - methods.selectColumns = function(selected, ignoreSelectable) { - selected2 = $.makeArray(selected); - selectCols(ignoreSelectable); - changeInput('columns_selected', selected2); - } - } - - if (selTarget === 'cell') { - var selected3 = [], selectable3 = []; - if (selected !== null) selected3 = selected; - if (selectable !== null && typeof selectable !== 'boolean') selectable3 = selectable; - var findIndex = function(ij, sel) { - for (var i = 0; i < sel.length; i++) { - if (ij[0] === sel[i][0] && ij[1] === sel[i][1]) return i; - } - return -1; - } - // Change selected3's value based on selectable3, then refresh the cell state - var onlyKeepSelectableCells = function() { - if (selDisable) { // users can't select; useful when only want backend select - selected3 = []; - return; - } - if (selectable3.length === 0) return; - var nonselectable = selectable3[0][0] <= 0; - var out = []; - if (nonselectable) { - selected3.map(function(ij) { - // should make selectable3 positive - if (findIndex([-ij[0], -ij[1]], selectable3) === -1) { out.push(ij); } - }); - } else { - selected3.map(function(ij) { - if (findIndex(ij, selectable3) > -1) { out.push(ij); } - }); - } - selected3 = out; - } - // Change selected3's value based on selectable3, then - // refresh the cell selection state according to values in selected3 - var selectCells = function(ignoreSelectable) { - if (!ignoreSelectable) onlyKeepSelectableCells(); - table.$('td.' + selClass).removeClass(selClass); - if (selected3.length === 0) return; - if (server) { - table.cells({page: 'current'}).every(function() { - var info = tweakCellIndex(this); - if (findIndex([info.row, info.col], selected3) > -1) - $(this.node()).addClass(selClass); - }); - } else { - selected3.map(function(ij) { - $(table.cell(ij[0] - 1, ij[1]).node()).addClass(selClass); - }); - } - }; - table.on('click.dt', 'tbody td', function() { - var $this = $(this), info = tweakCellIndex(table.cell(this)); - if ($this.hasClass(selClass)) { - $this.removeClass(selClass); - selected3.splice(findIndex([info.row, info.col], selected3), 1); - } else { - if (selMode === 'single') $(table.cells().nodes()).removeClass(selClass); - $this.addClass(selClass); - selected3 = selMode === 'single' ? [[info.row, info.col]] : - unique(selected3.concat([[info.row, info.col]])); - } - selectCells(false); // must call this to update selected3 based on selectable3 - changeInput('cells_selected', transposeArray2D(selected3), 'shiny.matrix'); - }); - selectCells(false); // in case users have specified pre-selected columns - changeInput('cells_selected', transposeArray2D(selected3), 'shiny.matrix'); - - if (server) table.on('draw.dt', function(e) { selectCells(false); }); - methods.selectCells = function(selected, ignoreSelectable) { - selected3 = selected ? selected : []; - selectCells(ignoreSelectable); - changeInput('cells_selected', transposeArray2D(selected3), 'shiny.matrix'); - } - } - } - - // expose some table info to Shiny - var updateTableInfo = function(e, settings) { - // TODO: is anyone interested in the page info? - // changeInput('page_info', table.page.info()); - var updateRowInfo = function(id, modifier) { - var idx; - if (server) { - idx = modifier.page === 'current' ? DT_rows_current : DT_rows_all; - } else { - var rows = table.rows($.extend({ - search: 'applied', - page: 'all' - }, modifier)); - idx = addOne(rows.indexes().toArray()); - } - changeInput('rows' + '_' + id, idx); - }; - updateRowInfo('current', {page: 'current'}); - updateRowInfo('all', {}); - } - table.on('draw.dt', updateTableInfo); - updateTableInfo(); - - // state info - table.on('draw.dt column-visibility.dt', function() { - changeInput('state', table.state()); - }); - changeInput('state', table.state()); - - // search info - var updateSearchInfo = function() { - changeInput('search', table.search()); - if (filterRow) changeInput('search_columns', filterRow.toArray().map(function(td) { - return $(td).find('input').first().val(); - })); - } - table.on('draw.dt', updateSearchInfo); - updateSearchInfo(); - - var cellInfo = function(thiz) { - var info = tweakCellIndex(table.cell(thiz)); - info.value = table.cell(thiz).data(); - return info; - } - // the current cell clicked on - table.on('click.dt', 'tbody td', function() { - changeInput('cell_clicked', cellInfo(this), null, null, {priority: 'event'}); - }) - changeInput('cell_clicked', {}); - - // do not trigger table selection when clicking on links unless they have classes - table.on('mousedown.dt', 'tbody td a', function(e) { - if (this.className === '') e.stopPropagation(); - }); - - methods.addRow = function(data, rowname, resetPaging) { - var n = table.columns().indexes().length, d = n - data.length; - if (d === 1) { - data = rowname.concat(data) - } else if (d !== 0) { - console.log(data); - console.log(table.columns().indexes()); - throw 'New data must be of the same length as current data (' + n + ')'; - }; - table.row.add(data).draw(resetPaging); - } - - methods.updateSearch = function(keywords) { - if (keywords.global !== null) - $(table.table().container()).find('input[type=search]').first() - .val(keywords.global).trigger('input'); - var columns = keywords.columns; - if (!filterRow || columns === null) return; - filterRow.toArray().map(function(td, i) { - var v = typeof columns === 'string' ? columns : columns[i]; - if (typeof v === 'undefined') { - console.log('The search keyword for column ' + i + ' is undefined') - return; - } - // Update column search string and values on linked filter widgets. - // 'input' for factor and char filters, 'change' for numeric filters. - $(td).find('input').first().val(v).trigger('input', [true]).trigger('change'); - }); - table.draw(); - } - - methods.hideCols = function(hide, reset) { - if (reset) table.columns().visible(true, false); - table.columns(hide).visible(false); - } - - methods.showCols = function(show, reset) { - if (reset) table.columns().visible(false, false); - table.columns(show).visible(true); - } - - methods.colReorder = function(order, origOrder) { - table.colReorder.order(order, origOrder); - } - - methods.selectPage = function(page) { - if (table.page.info().pages < page || page < 1) { - throw 'Selected page is out of range'; - }; - table.page(page - 1).draw(false); - } - - methods.reloadData = function(resetPaging, clearSelection) { - // empty selections first if necessary - if (methods.selectRows && inArray('row', clearSelection)) methods.selectRows([]); - if (methods.selectColumns && inArray('column', clearSelection)) methods.selectColumns([]); - if (methods.selectCells && inArray('cell', clearSelection)) methods.selectCells([]); - table.ajax.reload(null, resetPaging); - } - - // update table filters (set new limits of sliders) - methods.updateFilters = function(newProps) { - // loop through each filter in the filter row - filterRow.each(function(i, td) { - var k = i; - if (filterRow.length > newProps.length) { - if (i === 0) return; // first column is row names - k = i - 1; - } - // Update the filters to reflect the updated data. - // Allow "falsy" (e.g. NULL) to signify a no-op. - if (newProps[k]) { - setFilterProps(td, newProps[k]); - } - }); - }; - - table.shinyMethods = methods; - }, - resize: function(el, width, height, instance) { - if (instance.data) this.renderValue(el, instance.data, instance); - - // dynamically adjust height if fillContainer = TRUE - if (instance.fillContainer) - this.fillAvailableHeight(el, height); - - this.adjustWidth(el); - }, - - // dynamically set the scroll body to fill available height - // (used with fillContainer = TRUE) - fillAvailableHeight: function(el, availableHeight) { - - // see how much of the table is occupied by header/footer elements - // and use that to compute a target scroll body height - var dtWrapper = $(el).find('div.dataTables_wrapper'); - var dtScrollBody = $(el).find($('div.dataTables_scrollBody')); - var framingHeight = dtWrapper.innerHeight() - dtScrollBody.innerHeight(); - var scrollBodyHeight = availableHeight - framingHeight; - - // we need to set `max-height` to none as datatables library now sets this - // to a fixed height, disabling the ability to resize to fill the window, - // as it will be set to a fixed 100px under such circumstances, e.g., RStudio IDE, - // or FlexDashboard - // see https://github.com/rstudio/DT/issues/951#issuecomment-1026464509 - dtScrollBody.css('max-height', 'none'); - // set the height - dtScrollBody.height(scrollBodyHeight + 'px'); - }, - - // adjust the width of columns; remove the hard-coded widths on table and the - // scroll header when scrollX/Y are enabled - adjustWidth: function(el) { - var $el = $(el), table = $el.data('datatable'); - if (table) table.columns.adjust(); - $el.find('.dataTables_scrollHeadInner').css('width', '') - .children('table').css('margin-left', ''); - } -}); - - if (!HTMLWidgets.shinyMode) return; - - Shiny.addCustomMessageHandler('datatable-calls', function(data) { - var id = data.id; - var el = document.getElementById(id); - var table = el ? $(el).data('datatable') : null; - if (!table) { - console.log("Couldn't find table with id " + id); - return; - } - - var methods = table.shinyMethods, call = data.call; - if (methods[call.method]) { - methods[call.method].apply(table, call.args); - } else { - console.log("Unknown method " + call.method); - } - }); - -})(); diff --git a/docs/articles/get_started_files/datatables-binding-0.34.0/datatables.js b/docs/articles/get_started_files/datatables-binding-0.34.0/datatables.js deleted file mode 100644 index 136a8b9..0000000 --- a/docs/articles/get_started_files/datatables-binding-0.34.0/datatables.js +++ /dev/null @@ -1,1539 +0,0 @@ -(function() { - -// some helper functions: using a global object DTWidget so that it can be used -// in JS() code, e.g. datatable(options = list(foo = JS('code'))); unlike R's -// dynamic scoping, when 'code' is eval'ed, JavaScript does not know objects -// from the "parent frame", e.g. JS('DTWidget') will not work unless it was made -// a global object -var DTWidget = {}; - -// 123456666.7890 -> 123,456,666.7890 -var markInterval = function(d, digits, interval, mark, decMark, precision) { - x = precision ? d.toPrecision(digits) : d.toFixed(digits); - if (!/^-?[\d.]+$/.test(x)) return x; - var xv = x.split('.'); - if (xv.length > 2) return x; // should have at most one decimal point - xv[0] = xv[0].replace(new RegExp('\\B(?=(\\d{' + interval + '})+(?!\\d))', 'g'), mark); - return xv.join(decMark); -}; - -DTWidget.formatCurrency = function(data, currency, digits, interval, mark, decMark, before, zeroPrint) { - var d = parseFloat(data); - if (isNaN(d)) return ''; - if (zeroPrint !== null && d === 0.0) return zeroPrint; - var res = markInterval(d, digits, interval, mark, decMark); - res = before ? (/^-/.test(res) ? '-' + currency + res.replace(/^-/, '') : currency + res) : - res + currency; - return res; -}; - -DTWidget.formatString = function(data, prefix, suffix) { - var d = data; - if (d === null) return ''; - return prefix + d + suffix; -}; - -DTWidget.formatPercentage = function(data, digits, interval, mark, decMark, zeroPrint) { - var d = parseFloat(data); - if (isNaN(d)) return ''; - if (zeroPrint !== null && d === 0.0) return zeroPrint; - return markInterval(d * 100, digits, interval, mark, decMark) + '%'; -}; - -DTWidget.formatRound = function(data, digits, interval, mark, decMark, zeroPrint) { - var d = parseFloat(data); - if (isNaN(d)) return ''; - if (zeroPrint !== null && d === 0.0) return zeroPrint; - return markInterval(d, digits, interval, mark, decMark); -}; - -DTWidget.formatSignif = function(data, digits, interval, mark, decMark, zeroPrint) { - var d = parseFloat(data); - if (isNaN(d)) return ''; - if (zeroPrint !== null && d === 0.0) return zeroPrint; - return markInterval(d, digits, interval, mark, decMark, true); -}; - -DTWidget.formatDate = function(data, method, params) { - var d = data; - if (d === null) return ''; - // (new Date('2015-10-28')).toDateString() may return 2015-10-27 because the - // actual time created could be like 'Tue Oct 27 2015 19:00:00 GMT-0500 (CDT)', - // i.e. the date-only string is treated as UTC time instead of local time - if ((method === 'toDateString' || method === 'toLocaleDateString') && /^\d{4,}\D\d{2}\D\d{2}$/.test(d)) { - d = d.split(/\D/); - d = new Date(d[0], d[1] - 1, d[2]); - } else { - d = new Date(d); - } - return d[method].apply(d, params); -}; - -window.DTWidget = DTWidget; - -// A helper function to update the properties of existing filters -var setFilterProps = function(td, props) { - // Update enabled/disabled state - var $input = $(td).find('input').first(); - var searchable = $input.data('searchable'); - $input.prop('disabled', !searchable || props.disabled); - - // Based on the filter type, set its new values - var type = td.getAttribute('data-type'); - if (['factor', 'logical'].includes(type)) { - // Reformat the new dropdown options for use with selectize - var new_vals = props.params.options.map(function(item) { - return { text: item, value: item }; - }); - - // Find the selectize object - var dropdown = $(td).find('.selectized').eq(0)[0].selectize; - - // Note the current values - var old_vals = dropdown.getValue(); - - // Remove the existing values - dropdown.clearOptions(); - - // Add the new options - dropdown.addOption(new_vals); - - // Preserve the existing values - dropdown.setValue(old_vals); - - } else if (['number', 'integer', 'date', 'time'].includes(type)) { - // Apply internal scaling to new limits. Updating scale not yet implemented. - var slider = $(td).find('.noUi-target').eq(0); - var scale = Math.pow(10, Math.max(0, +slider.data('scale') || 0)); - var new_vals = [props.params.min * scale, props.params.max * scale]; - - // Note what the new limits will be just for this filter - var new_lims = new_vals.slice(); - - // Determine the current values and limits - var old_vals = slider.val().map(Number); - var old_lims = slider.noUiSlider('options').range; - old_lims = [old_lims.min, old_lims.max]; - - // Preserve the current values if filters have been applied; otherwise, apply no filtering - if (old_vals[0] != old_lims[0]) { - new_vals[0] = Math.max(old_vals[0], new_vals[0]); - } - - if (old_vals[1] != old_lims[1]) { - new_vals[1] = Math.min(old_vals[1], new_vals[1]); - } - - // Update the endpoints of the slider - slider.noUiSlider({ - start: new_vals, - range: {'min': new_lims[0], 'max': new_lims[1]} - }, true); - } -}; - -var transposeArray2D = function(a) { - return a.length === 0 ? a : HTMLWidgets.transposeArray2D(a); -}; - -var crosstalkPluginsInstalled = false; - -function maybeInstallCrosstalkPlugins() { - if (crosstalkPluginsInstalled) - return; - crosstalkPluginsInstalled = true; - - $.fn.dataTable.ext.afnFiltering.push( - function(oSettings, aData, iDataIndex) { - var ctfilter = oSettings.nTable.ctfilter; - if (ctfilter && !ctfilter[iDataIndex]) - return false; - - var ctselect = oSettings.nTable.ctselect; - if (ctselect && !ctselect[iDataIndex]) - return false; - - return true; - } - ); -} - -HTMLWidgets.widget({ - name: "datatables", - type: "output", - renderOnNullValue: true, - initialize: function(el, width, height) { - // in order that the type=number inputs return a number - $.valHooks.number = { - get: function(el) { - var value = parseFloat(el.value); - return isNaN(value) ? "" : value; - } - }; - $(el).html(' '); - return { - data: null, - ctfilterHandle: new crosstalk.FilterHandle(), - ctfilterSubscription: null, - ctselectHandle: new crosstalk.SelectionHandle(), - ctselectSubscription: null - }; - }, - renderValue: function(el, data, instance) { - if ((el.offsetWidth === 0 || el.offsetHeight === 0) && data.lazyRender !== false) { - instance.data = data; - return; - } - instance.data = null; - var $el = $(el); - $el.empty(); - - if (data === null) { - $el.append(' '); - // clear previous Shiny inputs (if any) - for (var i in instance.clearInputs) instance.clearInputs[i](); - instance.clearInputs = {}; - return; - } - - var crosstalkOptions = data.crosstalkOptions; - if (!crosstalkOptions) crosstalkOptions = { - 'key': null, 'group': null - }; - if (crosstalkOptions.group) { - maybeInstallCrosstalkPlugins(); - instance.ctfilterHandle.setGroup(crosstalkOptions.group); - instance.ctselectHandle.setGroup(crosstalkOptions.group); - } - - // if we are in the viewer then we always want to fillContainer and - // and autoHideNavigation (unless the user has explicitly set these) - if (window.HTMLWidgets.viewerMode) { - if (!data.hasOwnProperty("fillContainer")) - data.fillContainer = true; - if (!data.hasOwnProperty("autoHideNavigation")) - data.autoHideNavigation = true; - } - - // propagate fillContainer to instance (so we have it in resize) - instance.fillContainer = data.fillContainer; - - var cells = data.data; - - if (cells instanceof Array) cells = transposeArray2D(cells); - - $el.append(data.container); - var $table = $el.find('table'); - if (data.class) $table.addClass(data.class); - if (data.caption) $table.prepend(data.caption); - - if (!data.selection) data.selection = { - mode: 'none', selected: null, target: 'row', selectable: null - }; - if (HTMLWidgets.shinyMode && data.selection.mode !== 'none' && - data.selection.target === 'row+column') { - if ($table.children('tfoot').length === 0) { - $table.append($('')); - $table.find('thead tr').clone().appendTo($table.find('tfoot')); - } - } - - // column filters - var filterRow; - switch (data.filter) { - case 'top': - $table.children('thead').append(data.filterHTML); - filterRow = $table.find('thead tr:last td'); - break; - case 'bottom': - if ($table.children('tfoot').length === 0) { - $table.append($('')); - } - $table.children('tfoot').prepend(data.filterHTML); - filterRow = $table.find('tfoot tr:first td'); - break; - } - - var options = { searchDelay: 1000 }; - if (cells !== null) $.extend(options, { - data: cells - }); - - // options for fillContainer - var bootstrapActive = typeof($.fn.popover) != 'undefined'; - if (instance.fillContainer) { - - // force scrollX/scrollY and turn off autoWidth - options.scrollX = true; - options.scrollY = "100px"; // can be any value, we'll adjust below - - // if we aren't paginating then move around the info/filter controls - // to save space at the bottom and rephrase the info callback - if (data.options.paging === false) { - - // we know how to do this cleanly for bootstrap, not so much - // for other themes/layouts - if (bootstrapActive) { - options.dom = "<'row'<'col-sm-4'i><'col-sm-8'f>>" + - "<'row'<'col-sm-12'tr>>"; - } - - options.fnInfoCallback = function(oSettings, iStart, iEnd, - iMax, iTotal, sPre) { - return Number(iTotal).toLocaleString() + " records"; - }; - } - } - - // auto hide navigation if requested - // Note, this only works on client-side processing mode as on server-side, - // cells (data.data) is null; In addition, we require the pageLength option - // being provided explicitly to enable this. Despite we may be able to deduce - // the default value of pageLength, it may complicate things so we'd rather - // put this responsiblity to users and warn them on the R side. - if (data.autoHideNavigation === true && data.options.paging !== false) { - // strip all nav if length >= cells - if ((cells instanceof Array) && data.options.pageLength >= cells.length) - options.dom = bootstrapActive ? "<'row'<'col-sm-12'tr>>" : "t"; - // alternatively lean things out for flexdashboard mobile portrait - else if (bootstrapActive && window.FlexDashboard && window.FlexDashboard.isMobilePhone()) - options.dom = "<'row'<'col-sm-12'f>>" + - "<'row'<'col-sm-12'tr>>" + - "<'row'<'col-sm-12'p>>"; - } - - $.extend(true, options, data.options || {}); - - var searchCols = options.searchCols; - if (searchCols) { - searchCols = searchCols.map(function(x) { - return x === null ? '' : x.search; - }); - // FIXME: this means I don't respect the escapeRegex setting - delete options.searchCols; - } - - // server-side processing? - var server = options.serverSide === true; - - // use the dataSrc function to pre-process JSON data returned from R - var DT_rows_all = [], DT_rows_current = []; - if (server && HTMLWidgets.shinyMode && typeof options.ajax === 'object' && - /^session\/[\da-z]+\/dataobj/.test(options.ajax.url) && !options.ajax.dataSrc) { - options.ajax.dataSrc = function(json) { - DT_rows_all = $.makeArray(json.DT_rows_all); - DT_rows_current = $.makeArray(json.DT_rows_current); - var data = json.data; - if (!colReorderEnabled()) return data; - var table = $table.DataTable(), order = table.colReorder.order(), flag = true, i, j, row; - for (i = 0; i < order.length; ++i) if (order[i] !== i) flag = false; - if (flag) return data; - for (i = 0; i < data.length; ++i) { - row = data[i].slice(); - for (j = 0; j < order.length; ++j) data[i][j] = row[order[j]]; - } - return data; - }; - } - - var thiz = this; - if (instance.fillContainer) $table.on('init.dt', function(e) { - thiz.fillAvailableHeight(el, $(el).innerHeight()); - }); - // If the page contains serveral datatables and one of which enables colReorder, - // the table.colReorder.order() function will exist but throws error when called. - // So it seems like the only way to know if colReorder is enabled or not is to - // check the options. - var colReorderEnabled = function() { return "colReorder" in options; }; - var table = $table.DataTable(options); - $el.data('datatable', table); - - if ('rowGroup' in options) { - // Maintain RowGroup dataSrc when columns are reordered (#1109) - table.on('column-reorder', function(e, settings, details) { - var oldDataSrc = table.rowGroup().dataSrc(); - var newDataSrc = details.mapping[oldDataSrc]; - table.rowGroup().dataSrc(newDataSrc); - }); - } - - // Unregister previous Crosstalk event subscriptions, if they exist - if (instance.ctfilterSubscription) { - instance.ctfilterHandle.off("change", instance.ctfilterSubscription); - instance.ctfilterSubscription = null; - } - if (instance.ctselectSubscription) { - instance.ctselectHandle.off("change", instance.ctselectSubscription); - instance.ctselectSubscription = null; - } - - if (!crosstalkOptions.group) { - $table[0].ctfilter = null; - $table[0].ctselect = null; - } else { - var key = crosstalkOptions.key; - function keysToMatches(keys) { - if (!keys) { - return null; - } else { - var selectedKeys = {}; - for (var i = 0; i < keys.length; i++) { - selectedKeys[keys[i]] = true; - } - var matches = {}; - for (var j = 0; j < key.length; j++) { - if (selectedKeys[key[j]]) - matches[j] = true; - } - return matches; - } - } - - function applyCrosstalkFilter(e) { - $table[0].ctfilter = keysToMatches(e.value); - table.draw(); - } - instance.ctfilterSubscription = instance.ctfilterHandle.on("change", applyCrosstalkFilter); - applyCrosstalkFilter({value: instance.ctfilterHandle.filteredKeys}); - - function applyCrosstalkSelection(e) { - if (e.sender !== instance.ctselectHandle) { - table - .rows('.' + selClass, {search: 'applied'}) - .nodes() - .to$() - .removeClass(selClass); - if (selectedRows) - changeInput('rows_selected', selectedRows(), void 0, true); - } - - if (e.sender !== instance.ctselectHandle && e.value && e.value.length) { - var matches = keysToMatches(e.value); - - // persistent selection with plotly (& leaflet) - var ctOpts = crosstalk.var("plotlyCrosstalkOpts").get() || {}; - if (ctOpts.persistent === true) { - var matches = $.extend(matches, $table[0].ctselect); - } - - $table[0].ctselect = matches; - table.draw(); - } else { - if ($table[0].ctselect) { - $table[0].ctselect = null; - table.draw(); - } - } - } - instance.ctselectSubscription = instance.ctselectHandle.on("change", applyCrosstalkSelection); - // TODO: This next line doesn't seem to work when renderDataTable is used - applyCrosstalkSelection({value: instance.ctselectHandle.value}); - } - - var inArray = function(val, array) { - return $.inArray(val, $.makeArray(array)) > -1; - }; - - // search the i-th column - var searchColumn = function(i, value) { - var regex = false, ci = true; - if (options.search) { - regex = options.search.regex, - ci = options.search.caseInsensitive !== false; - } - // need to transpose the column index when colReorder is enabled - if (table.colReorder) i = table.colReorder.transpose(i); - return table.column(i).search(value, regex, !regex, ci); - }; - - if (data.filter !== 'none') { - if (!data.hasOwnProperty('filterSettings')) data.filterSettings = {}; - - filterRow.each(function(i, td) { - - var $td = $(td), type = $td.data('type'), filter; - var $input = $td.children('div').first().children('input'); - var disabled = $input.prop('disabled'); - var searchable = table.settings()[0].aoColumns[i].bSearchable; - $input.prop('disabled', !searchable || disabled); - $input.data('searchable', searchable); // for updating later - $input.on('input blur', function() { - $input.next('span').toggle(Boolean($input.val())); - }); - // Bootstrap sets pointer-events to none and we won't be able to click - // the clear button - $input.next('span').css('pointer-events', 'auto').hide().click(function() { - $(this).hide().prev('input').val('').trigger('input').focus(); - }); - var searchCol; // search string for this column - if (searchCols && searchCols[i]) { - searchCol = searchCols[i]; - $input.val(searchCol).trigger('input'); - } - var $x = $td.children('div').last(); - - // remove the overflow: hidden attribute of the scrollHead - // (otherwise the scrolling table body obscures the filters) - // The workaround and the discussion from - // https://github.com/rstudio/DT/issues/554#issuecomment-518007347 - // Otherwise the filter selection will not be anchored to the values - // when the columns number is many and scrollX is enabled. - var scrollHead = $(el).find('.dataTables_scrollHead,.dataTables_scrollFoot'); - var cssOverflowHead = scrollHead.css('overflow'); - var scrollBody = $(el).find('.dataTables_scrollBody'); - var cssOverflowBody = scrollBody.css('overflow'); - var scrollTable = $(el).find('.dataTables_scroll'); - var cssOverflowTable = scrollTable.css('overflow'); - if (cssOverflowHead === 'hidden') { - $x.on('show hide', function(e) { - if (e.type === 'show') { - scrollHead.css('overflow', 'visible'); - scrollBody.css('overflow', 'visible'); - scrollTable.css('overflow-x', 'scroll'); - } else { - scrollHead.css('overflow', cssOverflowHead); - scrollBody.css('overflow', cssOverflowBody); - scrollTable.css('overflow-x', cssOverflowTable); - } - }); - $x.css('z-index', 25); - } - - if (inArray(type, ['factor', 'logical'])) { - $input.on({ - click: function() { - $input.parent().hide(); $x.show().trigger('show'); filter[0].selectize.focus(); - }, - input: function() { - var v1 = JSON.stringify(filter[0].selectize.getValue()), v2 = $input.val(); - if (v1 === '[]') v1 = ''; - if (v1 !== v2) filter[0].selectize.setValue(v2 === '' ? [] : JSON.parse(v2)); - } - }); - var $input2 = $x.children('select'); - filter = $input2.selectize($.extend({ - options: $input2.data('options').map(function(v, i) { - return ({text: v, value: v}); - }), - plugins: ['remove_button'], - hideSelected: true, - onChange: function(value) { - if (value === null) value = []; // compatibility with jQuery 3.0 - $input.val(value.length ? JSON.stringify(value) : ''); - if (value.length) $input.trigger('input'); - $input.attr('title', $input.val()); - if (server) { - searchColumn(i, value.length ? JSON.stringify(value) : '').draw(); - return; - } - // turn off filter if nothing selected - $td.data('filter', value.length > 0); - table.draw(); // redraw table, and filters will be applied - } - }, data.filterSettings.select)); - filter[0].selectize.on('blur', function() { - $x.hide().trigger('hide'); $input.parent().show(); $input.trigger('blur'); - }); - filter.next('div').css('margin-bottom', 'auto'); - } else if (type === 'character') { - var fun = function() { - searchColumn(i, $input.val()).draw(); - }; - // throttle searching for server-side processing - var throttledFun = $.fn.dataTable.util.throttle(fun, options.searchDelay); - $input.on('input', function(e, immediate) { - // always bypass throttling when immediate = true (via the updateSearch method) - (immediate || !server) ? fun() : throttledFun(); - }); - } else if (inArray(type, ['number', 'integer', 'date', 'time'])) { - var $x0 = $x; - $x = $x0.children('div').first(); - $x0.css({ - 'background-color': '#fff', - 'border': '1px #ddd solid', - 'border-radius': '4px', - 'padding': data.vertical ? '35px 20px': '20px 20px 10px 20px' - }); - var $spans = $x0.children('span').css({ - 'margin-top': data.vertical ? '0' : '10px', - 'white-space': 'nowrap' - }); - var $span1 = $spans.first(), $span2 = $spans.last(); - var r1 = +$x.data('min'), r2 = +$x.data('max'); - // when the numbers are too small or have many decimal places, the - // slider may have numeric precision problems (#150) - var scale = Math.pow(10, Math.max(0, +$x.data('scale') || 0)); - r1 = Math.round(r1 * scale); r2 = Math.round(r2 * scale); - var scaleBack = function(x, scale) { - if (scale === 1) return x; - var d = Math.round(Math.log(scale) / Math.log(10)); - // to avoid problems like 3.423/100 -> 0.034230000000000003 - return (x / scale).toFixed(d); - }; - var slider_min = function() { - return filter.noUiSlider('options').range.min; - }; - var slider_max = function() { - return filter.noUiSlider('options').range.max; - }; - $input.on({ - focus: function() { - $x0.show().trigger('show'); - // first, make sure the slider div leaves at least 20px between - // the two (slider value) span's - $x0.width(Math.max(160, $span1.outerWidth() + $span2.outerWidth() + 20)); - // then, if the input is really wide or slider is vertical, - // make the slider the same width as the input - if ($x0.outerWidth() < $input.outerWidth() || data.vertical) { - $x0.outerWidth($input.outerWidth()); - } - // make sure the slider div does not reach beyond the right margin - if ($(window).width() < $x0.offset().left + $x0.width()) { - $x0.offset({ - 'left': $input.offset().left + $input.outerWidth() - $x0.outerWidth() - }); - } - }, - blur: function() { - $x0.hide().trigger('hide'); - }, - input: function() { - if ($input.val() === '') filter.val([slider_min(), slider_max()]); - }, - change: function() { - var v = $input.val().replace(/\s/g, ''); - if (v === '') return; - v = v.split('...'); - if (v.length !== 2) { - $input.parent().addClass('has-error'); - return; - } - if (v[0] === '') v[0] = slider_min(); - if (v[1] === '') v[1] = slider_max(); - $input.parent().removeClass('has-error'); - // treat date as UTC time at midnight - var strTime = function(x) { - var s = type === 'date' ? 'T00:00:00Z' : ''; - var t = new Date(x + s).getTime(); - // add 10 minutes to date since it does not hurt the date, and - // it helps avoid the tricky floating point arithmetic problems, - // e.g. sometimes the date may be a few milliseconds earlier - // than the midnight due to precision problems in noUiSlider - return type === 'date' ? t + 3600000 : t; - }; - if (inArray(type, ['date', 'time'])) { - v[0] = strTime(v[0]); - v[1] = strTime(v[1]); - } - if (v[0] != slider_min()) v[0] *= scale; - if (v[1] != slider_max()) v[1] *= scale; - filter.val(v); - } - }); - var formatDate = function(d) { - d = scaleBack(d, scale); - if (type === 'number') return d; - if (type === 'integer') return parseInt(d); - var x = new Date(+d); - if (type === 'date') { - var pad0 = function(x) { - return ('0' + x).substr(-2, 2); - }; - return x.getUTCFullYear() + '-' + pad0(1 + x.getUTCMonth()) - + '-' + pad0(x.getUTCDate()); - } else { - return x.toISOString(); - } - }; - var opts = type === 'date' ? { step: 60 * 60 * 1000 } : - type === 'integer' ? { step: 1 } : {}; - - opts.orientation = data.vertical ? 'vertical': 'horizontal'; - opts.direction = data.vertical ? 'rtl': 'ltr'; - - filter = $x.noUiSlider($.extend({ - start: [r1, r2], - range: {min: r1, max: r2}, - connect: true - }, opts, data.filterSettings.slider)); - if (scale > 1) (function() { - var t1 = r1, t2 = r2; - var val = filter.val(); - while (val[0] > r1 || val[1] < r2) { - if (val[0] > r1) { - t1 -= val[0] - r1; - } - if (val[1] < r2) { - t2 += r2 - val[1]; - } - filter = $x.noUiSlider($.extend({ - start: [t1, t2], - range: {min: t1, max: t2}, - connect: true - }, opts, data.filterSettings.slider), true); - val = filter.val(); - } - r1 = t1; r2 = t2; - })(); - // format with active column renderer, if defined - var colDef = data.options.columnDefs.find(function(def) { - return (def.targets === i || inArray(i, def.targets)) && 'render' in def; - }); - var updateSliderText = function(v1, v2) { - // we only know how to use function renderers - if (colDef && typeof colDef.render === 'function') { - var restore = function(v) { - v = scaleBack(v, scale); - return inArray(type, ['date', 'time']) ? new Date(+v) : v; - } - $span1.text(colDef.render(restore(v1), 'display')); - $span2.text(colDef.render(restore(v2), 'display')); - } else { - $span1.text(formatDate(v1)); - $span2.text(formatDate(v2)); - } - }; - updateSliderText(r1, r2); - var updateSlider = function(e) { - var val = filter.val(); - // turn off filter if in full range - $td.data('filter', val[0] > slider_min() || val[1] < slider_max()); - var v1 = formatDate(val[0]), v2 = formatDate(val[1]), ival; - if ($td.data('filter')) { - ival = v1 + ' ... ' + v2; - $input.attr('title', ival).val(ival).trigger('input'); - } else { - $input.attr('title', '').val(''); - } - updateSliderText(val[0], val[1]); - if (e.type === 'slide') return; // no searching when sliding only - if (server) { - searchColumn(i, $td.data('filter') ? ival : '').draw(); - return; - } - table.draw(); - }; - filter.on({ - set: updateSlider, - slide: updateSlider - }); - } - - // server-side processing will be handled by R (or whatever server - // language you use); the following code is only needed for client-side - // processing - if (server) { - // if a search string has been pre-set, search now - if (searchCol) $input.trigger('input').trigger('change'); - return; - } - - var customFilter = function(settings, data, dataIndex) { - // there is no way to attach a search function to a specific table, - // and we need to make sure a global search function is not applied to - // all tables (i.e. a range filter in a previous table should not be - // applied to the current table); we use the settings object to - // determine if we want to perform searching on the current table, - // since settings.sTableId will be different to different tables - if (table.settings()[0] !== settings) return true; - // no filter on this column or no need to filter this column - if (typeof filter === 'undefined' || !$td.data('filter')) return true; - - var r = filter.val(), v, r0, r1; - var i_data = function(i) { - if (!colReorderEnabled()) return i; - var order = table.colReorder.order(), k; - for (k = 0; k < order.length; ++k) if (order[k] === i) return k; - return i; // in theory it will never be here... - } - v = data[i_data(i)]; - if (type === 'number' || type === 'integer') { - v = parseFloat(v); - // how to handle NaN? currently exclude these rows - if (isNaN(v)) return(false); - r0 = parseFloat(scaleBack(r[0], scale)) - r1 = parseFloat(scaleBack(r[1], scale)); - if (v >= r0 && v <= r1) return true; - } else if (type === 'date' || type === 'time') { - v = new Date(v); - r0 = new Date(r[0] / scale); r1 = new Date(r[1] / scale); - if (v >= r0 && v <= r1) return true; - } else if (type === 'factor') { - if (r.length === 0 || inArray(v, r)) return true; - } else if (type === 'logical') { - if (r.length === 0) return true; - if (inArray(v === '' ? 'na' : v, r)) return true; - } - return false; - }; - - $.fn.dataTable.ext.search.push(customFilter); - - // search for the preset search strings if it is non-empty - if (searchCol) $input.trigger('input').trigger('change'); - - }); - - } - - // highlight search keywords - var highlight = function() { - var body = $(table.table().body()); - // removing the old highlighting first - body.unhighlight(); - - // don't highlight the "not found" row, so we get the rows using the api - if (table.rows({ filter: 'applied' }).data().length === 0) return; - // highlight global search keywords - body.highlight($.trim(table.search()).split(/\s+/)); - // then highlight keywords from individual column filters - if (filterRow) filterRow.each(function(i, td) { - var $td = $(td), type = $td.data('type'); - if (type !== 'character') return; - var $input = $td.children('div').first().children('input'); - var column = table.column(i).nodes().to$(), - val = $.trim($input.val()); - if (type !== 'character' || val === '') return; - column.highlight(val.split(/\s+/)); - }); - }; - - if (options.searchHighlight) { - table - .on('draw.dt.dth column-visibility.dt.dth column-reorder.dt.dth', highlight) - .on('destroy', function() { - // remove event handler - table.off('draw.dt.dth column-visibility.dt.dth column-reorder.dt.dth'); - }); - - // Set the option for escaping regex characters in our search string. This will be used - // for all future matching. - jQuery.fn.highlight.options.escapeRegex = (!options.search || !options.search.regex); - - // initial highlight for state saved conditions and initial states - highlight(); - } - - // run the callback function on the table instance - if (typeof data.callback === 'function') data.callback(table); - - // double click to edit the cell, row, column, or all cells - if (data.editable) table.on('dblclick.dt', 'tbody td', function(e) { - // only bring up the editor when the cell itself is dbclicked, and ignore - // other dbclick events bubbled up (e.g. from the ) - if (e.target !== this) return; - var target = [], immediate = false; - switch (data.editable.target) { - case 'cell': - target = [this]; - immediate = true; // edit will take effect immediately - break; - case 'row': - target = table.cells(table.cell(this).index().row, '*').nodes(); - break; - case 'column': - target = table.cells('*', table.cell(this).index().column).nodes(); - break; - case 'all': - target = table.cells().nodes(); - break; - default: - throw 'The editable parameter must be "cell", "row", "column", or "all"'; - } - var disableCols = data.editable.disable ? data.editable.disable.columns : null; - var numericCols = data.editable.numeric; - var areaCols = data.editable.area; - var dateCols = data.editable.date; - for (var i = 0; i < target.length; i++) { - (function(cell, current) { - var $cell = $(cell), html = $cell.html(); - var _cell = table.cell(cell), value = _cell.data(), index = _cell.index().column; - var $input; - if (inArray(index, numericCols)) { - $input = $(''); - } else if (inArray(index, areaCols)) { - $input = $(''); - } else if (inArray(index, dateCols)) { - $input = $(''); - } else { - $input = $(''); - } - if (!immediate) { - $cell.data('input', $input).data('html', html); - $input.attr('title', 'Hit Ctrl+Enter to finish editing, or Esc to cancel'); - } - $input.val(value); - if (inArray(index, disableCols)) { - $input.attr('readonly', '').css('filter', 'invert(25%)'); - } - $cell.empty().append($input); - if (cell === current) $input.focus(); - $input.css('width', '100%'); - - if (immediate) $input.on('blur', function(e) { - var valueNew = $input.val(); - if (valueNew !== value) { - _cell.data(valueNew); - if (HTMLWidgets.shinyMode) { - changeInput('cell_edit', [cellInfo(cell)], 'DT.cellInfo', null, {priority: 'event'}); - } - // for server-side processing, users have to call replaceData() to update the table - if (!server) table.draw(false); - } else { - $cell.html(html); - } - }).on('keyup', function(e) { - // hit Escape to cancel editing - if (e.keyCode === 27) $input.trigger('blur'); - }); - - // bulk edit (row, column, or all) - if (!immediate) $input.on('keyup', function(e) { - var removeInput = function($cell, restore) { - $cell.data('input').remove(); - if (restore) $cell.html($cell.data('html')); - } - if (e.keyCode === 27) { - for (var i = 0; i < target.length; i++) { - removeInput($(target[i]), true); - } - } else if (e.keyCode === 13 && e.ctrlKey) { - // Ctrl + Enter - var cell, $cell, _cell, cellData = []; - for (var i = 0; i < target.length; i++) { - cell = target[i]; $cell = $(cell); _cell = table.cell(cell); - _cell.data($cell.data('input').val()); - HTMLWidgets.shinyMode && cellData.push(cellInfo(cell)); - removeInput($cell, false); - } - if (HTMLWidgets.shinyMode) { - changeInput('cell_edit', cellData, 'DT.cellInfo', null, {priority: "event"}); - } - if (!server) table.draw(false); - } - }); - })(target[i], this); - } - }); - - // interaction with shiny - if (!HTMLWidgets.shinyMode && !crosstalkOptions.group) return; - - var methods = {}; - var shinyData = {}; - - methods.updateCaption = function(caption) { - if (!caption) return; - $table.children('caption').replaceWith(caption); - } - - // register clear functions to remove input values when the table is removed - instance.clearInputs = {}; - - var changeInput = function(id, value, type, noCrosstalk, opts) { - var event = id; - id = el.id + '_' + id; - if (type) id = id + ':' + type; - // do not update if the new value is the same as old value - if (event !== 'cell_edit' && !/_clicked$/.test(event) && shinyData.hasOwnProperty(id) && shinyData[id] === JSON.stringify(value)) - return; - shinyData[id] = JSON.stringify(value); - if (HTMLWidgets.shinyMode && Shiny.setInputValue) { - Shiny.setInputValue(id, value, opts); - if (!instance.clearInputs[id]) instance.clearInputs[id] = function() { - Shiny.setInputValue(id, null); - } - } - - // HACK - if (event === "rows_selected" && !noCrosstalk) { - if (crosstalkOptions.group) { - var keys = crosstalkOptions.key; - var selectedKeys = null; - if (value) { - selectedKeys = []; - for (var i = 0; i < value.length; i++) { - // The value array's contents use 1-based row numbers, so we must - // convert to 0-based before indexing into the keys array. - selectedKeys.push(keys[value[i] - 1]); - } - } - instance.ctselectHandle.set(selectedKeys); - } - } - }; - - var addOne = function(x) { - return x.map(function(i) { return 1 + i; }); - }; - - var unique = function(x) { - var ux = []; - $.each(x, function(i, el){ - if ($.inArray(el, ux) === -1) ux.push(el); - }); - return ux; - } - - // change the row index of a cell - var tweakCellIndex = function(cell) { - var info = cell.index(); - // some cell may not be valid. e.g, #759 - // when using the RowGroup extension, datatables will - // generate the row label and the cells are not part of - // the data thus contain no row/col info - if (info === undefined) - return {row: null, col: null}; - if (server) { - info.row = DT_rows_current[info.row]; - } else { - info.row += 1; - } - return {row: info.row, col: info.column}; - } - - var cleanSelectedValues = function() { - changeInput('rows_selected', []); - changeInput('columns_selected', []); - changeInput('cells_selected', transposeArray2D([]), 'shiny.matrix'); - } - // #828 we should clean the selection on the server-side when the table reloads - cleanSelectedValues(); - - // a flag to indicates if select extension is initialized or not - var flagSelectExt = table.settings()[0]._select !== undefined; - // the Select extension should only be used in the client mode and - // when the selection.mode is set to none - if (data.selection.mode === 'none' && !server && flagSelectExt) { - var updateRowsSelected = function() { - var rows = table.rows({selected: true}); - var selected = []; - $.each(rows.indexes().toArray(), function(i, v) { - selected.push(v + 1); - }); - changeInput('rows_selected', selected); - } - var updateColsSelected = function() { - var columns = table.columns({selected: true}); - changeInput('columns_selected', columns.indexes().toArray()); - } - var updateCellsSelected = function() { - var cells = table.cells({selected: true}); - var selected = []; - cells.every(function() { - var row = this.index().row; - var col = this.index().column; - selected = selected.concat([[row + 1, col]]); - }); - changeInput('cells_selected', transposeArray2D(selected), 'shiny.matrix'); - } - table.on('select deselect', function(e, dt, type, indexes) { - updateRowsSelected(); - updateColsSelected(); - updateCellsSelected(); - }) - updateRowsSelected(); - updateColsSelected(); - updateCellsSelected(); - } - - var selMode = data.selection.mode, selTarget = data.selection.target; - var selDisable = data.selection.selectable === false; - if (inArray(selMode, ['single', 'multiple'])) { - var selClass = inArray(data.style, ['bootstrap', 'bootstrap4']) ? 'active' : 'selected'; - // selected1: row indices; selected2: column indices - var initSel = function(x) { - if (x === null || typeof x === 'boolean' || selTarget === 'cell') { - return {rows: [], cols: []}; - } else if (selTarget === 'row') { - return {rows: $.makeArray(x), cols: []}; - } else if (selTarget === 'column') { - return {rows: [], cols: $.makeArray(x)}; - } else if (selTarget === 'row+column') { - return {rows: $.makeArray(x.rows), cols: $.makeArray(x.cols)}; - } - } - var selected = data.selection.selected; - var selected1 = initSel(selected).rows, selected2 = initSel(selected).cols; - // selectable should contain either all positive or all non-positive values, not both - // positive values indicate "selectable" while non-positive values means "nonselectable" - // the assertion is performed on R side. (only column indicides could be zero which indicates - // the row name) - var selectable = data.selection.selectable; - var selectable1 = initSel(selectable).rows, selectable2 = initSel(selectable).cols; - - // After users reorder the rows or filter the table, we cannot use the table index - // directly. Instead, we need this function to find out the rows between the two clicks. - // If user filter the table again between the start click and the end click, the behavior - // would be undefined, but it should not be a problem. - var shiftSelRowsIndex = function(start, end) { - var indexes = server ? DT_rows_all : table.rows({ search: 'applied' }).indexes().toArray(); - start = indexes.indexOf(start); end = indexes.indexOf(end); - // if start is larger than end, we need to swap - if (start > end) { - var tmp = end; end = start; start = tmp; - } - return indexes.slice(start, end + 1); - } - - var serverRowIndex = function(clientRowIndex) { - return server ? DT_rows_current[clientRowIndex] : clientRowIndex + 1; - } - - // row, column, or cell selection - var lastClickedRow; - if (inArray(selTarget, ['row', 'row+column'])) { - // Get the current selected rows. It will also - // update the selected1's value based on the current row selection state - // Note we can't put this function inside selectRows() directly, - // the reason is method.selectRows() will override selected1's value but this - // function will add rows to selected1 (keep the existing selection), which is - // inconsistent with column and cell selection. - var selectedRows = function() { - var rows = table.rows('.' + selClass); - var idx = rows.indexes().toArray(); - if (!server) { - selected1 = addOne(idx); - return selected1; - } - idx = idx.map(function(i) { - return DT_rows_current[i]; - }); - selected1 = selMode === 'multiple' ? unique(selected1.concat(idx)) : idx; - return selected1; - } - // Change selected1's value based on selectable1, then refresh the row state - var onlyKeepSelectableRows = function() { - if (selDisable) { // users can't select; useful when only want backend select - selected1 = []; - return; - } - if (selectable1.length === 0) return; - var nonselectable = selectable1[0] <= 0; - if (nonselectable) { - // should make selectable1 positive - selected1 = $(selected1).not(selectable1.map(function(i) { return -i; })).get(); - } else { - selected1 = $(selected1).filter(selectable1).get(); - } - } - // Change selected1's value based on selectable1, then - // refresh the row selection state according to values in selected1 - var selectRows = function(ignoreSelectable) { - if (!ignoreSelectable) onlyKeepSelectableRows(); - table.$('tr.' + selClass).removeClass(selClass); - if (selected1.length === 0) return; - if (server) { - table.rows({page: 'current'}).every(function() { - if (inArray(DT_rows_current[this.index()], selected1)) { - $(this.node()).addClass(selClass); - } - }); - } else { - var selected0 = selected1.map(function(i) { return i - 1; }); - $(table.rows(selected0).nodes()).addClass(selClass); - } - } - table.on('mousedown.dt', 'tbody tr', function(e) { - var $this = $(this), thisRow = table.row(this); - if (selMode === 'multiple') { - if (e.shiftKey && lastClickedRow !== undefined) { - // select or de-select depends on the last clicked row's status - var flagSel = !$this.hasClass(selClass); - var crtClickedRow = serverRowIndex(thisRow.index()); - if (server) { - var rowsIndex = shiftSelRowsIndex(lastClickedRow, crtClickedRow); - // update current page's selClass - rowsIndex.map(function(i) { - var rowIndex = DT_rows_current.indexOf(i); - if (rowIndex >= 0) { - var row = table.row(rowIndex).nodes().to$(); - var flagRowSel = !row.hasClass(selClass); - if (flagSel === flagRowSel) row.toggleClass(selClass); - } - }); - // update selected1 - if (flagSel) { - selected1 = unique(selected1.concat(rowsIndex)); - } else { - selected1 = selected1.filter(function(index) { - return !inArray(index, rowsIndex); - }); - } - } else { - // js starts from 0 - shiftSelRowsIndex(lastClickedRow - 1, crtClickedRow - 1).map(function(value) { - var row = table.row(value).nodes().to$(); - var flagRowSel = !row.hasClass(selClass); - if (flagSel === flagRowSel) row.toggleClass(selClass); - }); - } - e.preventDefault(); - } else { - $this.toggleClass(selClass); - } - } else { - if ($this.hasClass(selClass)) { - $this.removeClass(selClass); - } else { - table.$('tr.' + selClass).removeClass(selClass); - $this.addClass(selClass); - } - } - if (server && !$this.hasClass(selClass)) { - var id = DT_rows_current[thisRow.index()]; - // remove id from selected1 since its class .selected has been removed - if (inArray(id, selected1)) selected1.splice($.inArray(id, selected1), 1); - } - selectedRows(); // update selected1's value based on selClass - selectRows(false); // only keep the selectable rows - changeInput('rows_selected', selected1); - changeInput('row_last_clicked', serverRowIndex(thisRow.index()), null, null, {priority: 'event'}); - lastClickedRow = serverRowIndex(thisRow.index()); - }); - selectRows(false); // in case users have specified pre-selected rows - // restore selected rows after the table is redrawn (e.g. sort/search/page); - // client-side tables will preserve the selections automatically; for - // server-side tables, we have to *real* row indices are in `selected1` - changeInput('rows_selected', selected1); - if (server) table.on('draw.dt', function(e) { selectRows(false); }); - methods.selectRows = function(selected, ignoreSelectable) { - selected1 = $.makeArray(selected); - selectRows(ignoreSelectable); - changeInput('rows_selected', selected1); - } - } - - if (inArray(selTarget, ['column', 'row+column'])) { - if (selTarget === 'row+column') { - $(table.columns().footer()).css('cursor', 'pointer'); - } - // update selected2's value based on selectable2 - var onlyKeepSelectableCols = function() { - if (selDisable) { // users can't select; useful when only want backend select - selected2 = []; - return; - } - if (selectable2.length === 0) return; - var nonselectable = selectable2[0] <= 0; - if (nonselectable) { - // need to make selectable2 positive - selected2 = $(selected2).not(selectable2.map(function(i) { return -i; })).get(); - } else { - selected2 = $(selected2).filter(selectable2).get(); - } - } - // update selected2 and then - // refresh the col selection state according to values in selected2 - var selectCols = function(ignoreSelectable) { - if (!ignoreSelectable) onlyKeepSelectableCols(); - // if selected2 is not a valide index (e.g., larger than the column number) - // table.columns(selected2) will fail and result in a blank table - // this is different from the table.rows(), where the out-of-range indexes - // doesn't affect at all - selected2 = $(selected2).filter(table.columns().indexes()).get(); - table.columns().nodes().flatten().to$().removeClass(selClass); - if (selected2.length > 0) - table.columns(selected2).nodes().flatten().to$().addClass(selClass); - } - var callback = function() { - var colIdx = selTarget === 'column' ? table.cell(this).index().column : - $.inArray(this, table.columns().footer()), - thisCol = $(table.column(colIdx).nodes()); - if (colIdx === -1) return; - if (thisCol.hasClass(selClass)) { - thisCol.removeClass(selClass); - selected2.splice($.inArray(colIdx, selected2), 1); - } else { - if (selMode === 'single') $(table.cells().nodes()).removeClass(selClass); - thisCol.addClass(selClass); - selected2 = selMode === 'single' ? [colIdx] : unique(selected2.concat([colIdx])); - } - selectCols(false); // update selected2 based on selectable - changeInput('columns_selected', selected2); - } - if (selTarget === 'column') { - $(table.table().body()).on('click.dt', 'td', callback); - } else { - $(table.table().footer()).on('click.dt', 'tr th', callback); - } - selectCols(false); // in case users have specified pre-selected columns - changeInput('columns_selected', selected2); - if (server) table.on('draw.dt', function(e) { selectCols(false); }); - methods.selectColumns = function(selected, ignoreSelectable) { - selected2 = $.makeArray(selected); - selectCols(ignoreSelectable); - changeInput('columns_selected', selected2); - } - } - - if (selTarget === 'cell') { - var selected3 = [], selectable3 = []; - if (selected !== null) selected3 = selected; - if (selectable !== null && typeof selectable !== 'boolean') selectable3 = selectable; - var findIndex = function(ij, sel) { - for (var i = 0; i < sel.length; i++) { - if (ij[0] === sel[i][0] && ij[1] === sel[i][1]) return i; - } - return -1; - } - // Change selected3's value based on selectable3, then refresh the cell state - var onlyKeepSelectableCells = function() { - if (selDisable) { // users can't select; useful when only want backend select - selected3 = []; - return; - } - if (selectable3.length === 0) return; - var nonselectable = selectable3[0][0] <= 0; - var out = []; - if (nonselectable) { - selected3.map(function(ij) { - // should make selectable3 positive - if (findIndex([-ij[0], -ij[1]], selectable3) === -1) { out.push(ij); } - }); - } else { - selected3.map(function(ij) { - if (findIndex(ij, selectable3) > -1) { out.push(ij); } - }); - } - selected3 = out; - } - // Change selected3's value based on selectable3, then - // refresh the cell selection state according to values in selected3 - var selectCells = function(ignoreSelectable) { - if (!ignoreSelectable) onlyKeepSelectableCells(); - table.$('td.' + selClass).removeClass(selClass); - if (selected3.length === 0) return; - if (server) { - table.cells({page: 'current'}).every(function() { - var info = tweakCellIndex(this); - if (findIndex([info.row, info.col], selected3) > -1) - $(this.node()).addClass(selClass); - }); - } else { - selected3.map(function(ij) { - $(table.cell(ij[0] - 1, ij[1]).node()).addClass(selClass); - }); - } - }; - table.on('click.dt', 'tbody td', function() { - var $this = $(this), info = tweakCellIndex(table.cell(this)); - if ($this.hasClass(selClass)) { - $this.removeClass(selClass); - selected3.splice(findIndex([info.row, info.col], selected3), 1); - } else { - if (selMode === 'single') $(table.cells().nodes()).removeClass(selClass); - $this.addClass(selClass); - selected3 = selMode === 'single' ? [[info.row, info.col]] : - unique(selected3.concat([[info.row, info.col]])); - } - selectCells(false); // must call this to update selected3 based on selectable3 - changeInput('cells_selected', transposeArray2D(selected3), 'shiny.matrix'); - }); - selectCells(false); // in case users have specified pre-selected columns - changeInput('cells_selected', transposeArray2D(selected3), 'shiny.matrix'); - - if (server) table.on('draw.dt', function(e) { selectCells(false); }); - methods.selectCells = function(selected, ignoreSelectable) { - selected3 = selected ? selected : []; - selectCells(ignoreSelectable); - changeInput('cells_selected', transposeArray2D(selected3), 'shiny.matrix'); - } - } - } - - // expose some table info to Shiny - var updateTableInfo = function(e, settings) { - // TODO: is anyone interested in the page info? - // changeInput('page_info', table.page.info()); - var updateRowInfo = function(id, modifier) { - var idx; - if (server) { - idx = modifier.page === 'current' ? DT_rows_current : DT_rows_all; - } else { - var rows = table.rows($.extend({ - search: 'applied', - page: 'all' - }, modifier)); - idx = addOne(rows.indexes().toArray()); - } - changeInput('rows' + '_' + id, idx); - }; - updateRowInfo('current', {page: 'current'}); - updateRowInfo('all', {}); - } - table.on('draw.dt', updateTableInfo); - updateTableInfo(); - - // state info - table.on('draw.dt column-visibility.dt', function() { - changeInput('state', table.state()); - }); - changeInput('state', table.state()); - - // search info - var updateSearchInfo = function() { - changeInput('search', table.search()); - if (filterRow) changeInput('search_columns', filterRow.toArray().map(function(td) { - return $(td).find('input').first().val(); - })); - } - table.on('draw.dt', updateSearchInfo); - updateSearchInfo(); - - var cellInfo = function(thiz) { - var info = tweakCellIndex(table.cell(thiz)); - info.value = table.cell(thiz).data(); - return info; - } - // the current cell clicked on - table.on('click.dt', 'tbody td', function() { - changeInput('cell_clicked', cellInfo(this), null, null, {priority: 'event'}); - }) - changeInput('cell_clicked', {}); - - // do not trigger table selection when clicking on links unless they have classes - table.on('mousedown.dt', 'tbody td a', function(e) { - if (this.className === '') e.stopPropagation(); - }); - - methods.addRow = function(data, rowname, resetPaging) { - var n = table.columns().indexes().length, d = n - data.length; - if (d === 1) { - data = rowname.concat(data) - } else if (d !== 0) { - console.log(data); - console.log(table.columns().indexes()); - throw 'New data must be of the same length as current data (' + n + ')'; - }; - table.row.add(data).draw(resetPaging); - } - - methods.updateSearch = function(keywords) { - if (keywords.global !== null) - $(table.table().container()).find('input[type=search]').first() - .val(keywords.global).trigger('input'); - var columns = keywords.columns; - if (!filterRow || columns === null) return; - filterRow.toArray().map(function(td, i) { - var v = typeof columns === 'string' ? columns : columns[i]; - if (typeof v === 'undefined') { - console.log('The search keyword for column ' + i + ' is undefined') - return; - } - // Update column search string and values on linked filter widgets. - // 'input' for factor and char filters, 'change' for numeric filters. - $(td).find('input').first().val(v).trigger('input', [true]).trigger('change'); - }); - table.draw(); - } - - methods.hideCols = function(hide, reset) { - if (reset) table.columns().visible(true, false); - table.columns(hide).visible(false); - } - - methods.showCols = function(show, reset) { - if (reset) table.columns().visible(false, false); - table.columns(show).visible(true); - } - - methods.colReorder = function(order, origOrder) { - table.colReorder.order(order, origOrder); - } - - methods.selectPage = function(page) { - if (table.page.info().pages < page || page < 1) { - throw 'Selected page is out of range'; - }; - table.page(page - 1).draw(false); - } - - methods.reloadData = function(resetPaging, clearSelection) { - // empty selections first if necessary - if (methods.selectRows && inArray('row', clearSelection)) methods.selectRows([]); - if (methods.selectColumns && inArray('column', clearSelection)) methods.selectColumns([]); - if (methods.selectCells && inArray('cell', clearSelection)) methods.selectCells([]); - table.ajax.reload(null, resetPaging); - } - - // update table filters (set new limits of sliders) - methods.updateFilters = function(newProps) { - // loop through each filter in the filter row - filterRow.each(function(i, td) { - var k = i; - if (filterRow.length > newProps.length) { - if (i === 0) return; // first column is row names - k = i - 1; - } - // Update the filters to reflect the updated data. - // Allow "falsy" (e.g. NULL) to signify a no-op. - if (newProps[k]) { - setFilterProps(td, newProps[k]); - } - }); - }; - - table.shinyMethods = methods; - }, - resize: function(el, width, height, instance) { - if (instance.data) this.renderValue(el, instance.data, instance); - - // dynamically adjust height if fillContainer = TRUE - if (instance.fillContainer) - this.fillAvailableHeight(el, height); - - this.adjustWidth(el); - }, - - // dynamically set the scroll body to fill available height - // (used with fillContainer = TRUE) - fillAvailableHeight: function(el, availableHeight) { - - // see how much of the table is occupied by header/footer elements - // and use that to compute a target scroll body height - var dtWrapper = $(el).find('div.dataTables_wrapper'); - var dtScrollBody = $(el).find($('div.dataTables_scrollBody')); - var framingHeight = dtWrapper.innerHeight() - dtScrollBody.innerHeight(); - var scrollBodyHeight = availableHeight - framingHeight; - - // we need to set `max-height` to none as datatables library now sets this - // to a fixed height, disabling the ability to resize to fill the window, - // as it will be set to a fixed 100px under such circumstances, e.g., RStudio IDE, - // or FlexDashboard - // see https://github.com/rstudio/DT/issues/951#issuecomment-1026464509 - dtScrollBody.css('max-height', 'none'); - // set the height - dtScrollBody.height(scrollBodyHeight + 'px'); - }, - - // adjust the width of columns; remove the hard-coded widths on table and the - // scroll header when scrollX/Y are enabled - adjustWidth: function(el) { - var $el = $(el), table = $el.data('datatable'); - if (table) table.columns.adjust(); - $el.find('.dataTables_scrollHeadInner').css('width', '') - .children('table').css('margin-left', ''); - } -}); - - if (!HTMLWidgets.shinyMode) return; - - Shiny.addCustomMessageHandler('datatable-calls', function(data) { - var id = data.id; - var el = document.getElementById(id); - var table = el ? $(el).data('datatable') : null; - if (!table) { - console.log("Couldn't find table with id " + id); - return; - } - - var methods = table.shinyMethods, call = data.call; - if (methods[call.method]) { - methods[call.method].apply(table, call.args); - } else { - console.log("Unknown method " + call.method); - } - }); - -})(); diff --git a/docs/articles/get_started_files/datatables-css-0.0.0/datatables-crosstalk.css b/docs/articles/get_started_files/datatables-css-0.0.0/datatables-crosstalk.css deleted file mode 100644 index bd1159c..0000000 --- a/docs/articles/get_started_files/datatables-css-0.0.0/datatables-crosstalk.css +++ /dev/null @@ -1,32 +0,0 @@ -.dt-crosstalk-fade { - opacity: 0.2; -} - -html body div.DTS div.dataTables_scrollBody { - background: none; -} - - -/* -Fix https://github.com/rstudio/DT/issues/563 -If the `table.display` is set to "block" (e.g., pkgdown), the browser will display -datatable objects strangely. The search panel and the page buttons will still be -in full-width but the table body will be "compact" and shorter. -In therory, having this attributes will affect `dom="t"` -with `display: block` users. But in reality, there should be no one. -We may remove the below lines in the future if the upstream agree to have this there. -See https://github.com/DataTables/DataTablesSrc/issues/160 -*/ - -table.dataTable { - display: table; -} - - -/* -When DTOutput(fill = TRUE), it receives a .html-fill-item class (via htmltools::bindFillRole()), which effectively amounts to `flex: 1 1 auto`. That's mostly fine, but the case where `fillContainer=TRUE`+`height:auto`+`flex-basis:auto` and the container (e.g., a bslib::card()) doesn't have a defined height is a bit problematic since the table wants to fit the parent but the parent wants to fit the table, which results pretty small table height (maybe because there is a minimum height somewhere?). It seems better in this case to impose a 400px height default for the table, which we can do by setting `flex-basis` to 400px (the table is still allowed to grow/shrink when the container has an opinionated height). -*/ - -.html-fill-container > .html-fill-item.datatables { - flex-basis: 400px; -} diff --git a/docs/articles/get_started_files/dt-core-1.13.6/css/jquery.dataTables.extra.css b/docs/articles/get_started_files/dt-core-1.13.6/css/jquery.dataTables.extra.css deleted file mode 100644 index b2dd141..0000000 --- a/docs/articles/get_started_files/dt-core-1.13.6/css/jquery.dataTables.extra.css +++ /dev/null @@ -1,28 +0,0 @@ -/* Selected rows/cells */ -table.dataTable tr.selected td, table.dataTable td.selected { - background-color: #b0bed9 !important; -} -/* In case of scrollX/Y or FixedHeader */ -.dataTables_scrollBody .dataTables_sizing { - visibility: hidden; -} - -/* The datatables' theme CSS file doesn't define -the color but with white background. It leads to an issue that -when the HTML's body color is set to 'white', the user can't -see the text since the background is white. One case happens in the -RStudio's IDE when inline viewing the DT table inside an Rmd file, -if the IDE theme is set to "Cobalt". - -See https://github.com/rstudio/DT/issues/447 for more info - -This fixes should have little side-effects because all the other elements -of the default theme use the #333 font color. - -TODO: The upstream may use relative colors for both the table background -and the color. It means the table can display well without this patch -then. At that time, we need to remove the below CSS attributes. -*/ -div.datatables { - color: #333; -} diff --git a/docs/articles/get_started_files/dt-core-1.13.6/css/jquery.dataTables.min.css b/docs/articles/get_started_files/dt-core-1.13.6/css/jquery.dataTables.min.css deleted file mode 100644 index ad59f84..0000000 --- a/docs/articles/get_started_files/dt-core-1.13.6/css/jquery.dataTables.min.css +++ /dev/null @@ -1 +0,0 @@ -:root{--dt-row-selected: 13, 110, 253;--dt-row-selected-text: 255, 255, 255;--dt-row-selected-link: 9, 10, 11;--dt-row-stripe: 0, 0, 0;--dt-row-hover: 0, 0, 0;--dt-column-ordering: 0, 0, 0;--dt-html-background: white}:root.dark{--dt-html-background: rgb(33, 37, 41)}table.dataTable td.dt-control{text-align:center;cursor:pointer}table.dataTable td.dt-control:before{display:inline-block;color:rgba(0, 0, 0, 0.5);content:"►"}table.dataTable tr.dt-hasChild td.dt-control:before{content:"▼"}html.dark table.dataTable td.dt-control:before{color:rgba(255, 255, 255, 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        Articles

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        Vignettes

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        Analyzing human RNA-Seq data with CLAMP
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        Comparing CLAMPbase and CLAMPfull
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        Developed by Marc Subirana-Granes, Maria Chikina.

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        Site built with pkgdown 2.2.0.

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        - - - - - - - diff --git a/docs/authors.html b/docs/authors.html deleted file mode 100644 index d406526..0000000 --- a/docs/authors.html +++ /dev/null @@ -1,88 +0,0 @@ - -Authors and Citation • CLAMP - Skip to contents - - -
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        Authors and Citation

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        Authors

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          Marc Subirana-Granes. Author, maintainer. -

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          Maria Chikina. Author. -

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        Citation

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        Source: DESCRIPTION

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        Subirana-Granes M, Chikina M (2026). -CLAMP: Curated Latent-variable Analysis with Molecular Priors. -R package version 0.99.0, https://mchikina.github.io/CLAMP/. -

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        @Manual{,
-  title = {CLAMP: Curated Latent-variable Analysis with Molecular Priors},
-  author = {Marc Subirana-Granes and Maria Chikina},
-  year = {2026},
-  note = {R package version 0.99.0},
-  url = {https://mchikina.github.io/CLAMP/},
-}
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        Developed by Marc Subirana-Granes, Maria Chikina.

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        Site built with pkgdown 2.2.0.

        -
        - -
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this._getItems().indexOf(t)}_setActiveIndicatorElement(t){if(!this._indicatorsElement)return;const e=z.findOne(wt,this._indicatorsElement);e.classList.remove(yt),e.removeAttribute("aria-current");const i=z.findOne(`[data-bs-slide-to="${t}"]`,this._indicatorsElement);i&&(i.classList.add(yt),i.setAttribute("aria-current","true"))}_updateInterval(){const t=this._activeElement||this._getActive();if(!t)return;const e=Number.parseInt(t.getAttribute("data-bs-interval"),10);this._config.interval=e||this._config.defaultInterval}_slide(t,e=null){if(this._isSliding)return;const i=this._getActive(),n=t===at,s=e||b(this._getItems(),i,n,this._config.wrap);if(s===i)return;const o=this._getItemIndex(s),r=e=>N.trigger(this._element,e,{relatedTarget:s,direction:this._orderToDirection(t),from:this._getItemIndex(i),to:o});if(r(dt).defaultPrevented)return;if(!i||!s)return;const a=Boolean(this._interval);this.pause(),this._isSliding=!0,this._setActiveIndicatorElement(o),this._activeElement=s;const 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Object.keys(f).sort((function(t,e){return f[t]-f[e]}))}const si={name:"flip",enabled:!0,phase:"main",fn:function(t){var e=t.state,i=t.options,n=t.name;if(!e.modifiersData[n]._skip){for(var s=i.mainAxis,o=void 0===s||s,r=i.altAxis,a=void 0===r||r,l=i.fallbackPlacements,c=i.padding,h=i.boundary,d=i.rootBoundary,u=i.altBoundary,f=i.flipVariations,p=void 0===f||f,m=i.allowedAutoPlacements,g=e.options.placement,_=be(g),b=l||(_!==g&&p?function(t){if(be(t)===Kt)return[];var e=Ve(t);return[Qe(t),e,Qe(e)]}(g):[Ve(g)]),v=[g].concat(b).reduce((function(t,i){return t.concat(be(i)===Kt?ni(e,{placement:i,boundary:h,rootBoundary:d,padding:c,flipVariations:p,allowedAutoPlacements:m}):i)}),[]),y=e.rects.reference,w=e.rects.popper,A=new Map,E=!0,T=v[0],C=0;C=0,S=L?"width":"height",D=ii(e,{placement:O,boundary:h,rootBoundary:d,altBoundary:u,padding:c}),$=L?k?qt:Vt:k?Rt:zt;y[S]>w[S]&&($=Ve($));var I=Ve($),N=[];if(o&&N.push(D[x]<=0),a&&N.push(D[$]<=0,D[I]<=0),N.every((function(t){return t}))){T=O,E=!1;break}A.set(O,N)}if(E)for(var P=function(t){var e=v.find((function(e){var i=A.get(e);if(i)return i.slice(0,t).every((function(t){return t}))}));if(e)return T=e,"break"},M=p?3:1;M>0&&"break"!==P(M);M--);e.placement!==T&&(e.modifiersData[n]._skip=!0,e.placement=T,e.reset=!0)}},requiresIfExists:["offset"],data:{_skip:!1}};function oi(t,e,i){return void 0===i&&(i={x:0,y:0}),{top:t.top-e.height-i.y,right:t.right-e.width+i.x,bottom:t.bottom-e.height+i.y,left:t.left-e.width-i.x}}function ri(t){return[zt,qt,Rt,Vt].some((function(e){return t[e]>=0}))}const ai={name:"hide",enabled:!0,phase:"main",requiresIfExists:["preventOverflow"],fn:function(t){var 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m?m(Object.assign({},e.rects,{placement:e.placement})):m,O="number"==typeof C?{mainAxis:C,altAxis:C}:Object.assign({mainAxis:0,altAxis:0},C),x=e.modifiersData.offset?e.modifiersData.offset[e.placement]:null,k={x:0,y:0};if(A){if(o){var L,S="y"===y?zt:Vt,D="y"===y?Rt:qt,$="y"===y?"height":"width",I=A[y],N=I+g[S],P=I-g[D],M=f?-T[$]/2:0,j=b===Xt?E[$]:T[$],F=b===Xt?-T[$]:-E[$],H=e.elements.arrow,W=f&&H?Ce(H):{width:0,height:0},B=e.modifiersData["arrow#persistent"]?e.modifiersData["arrow#persistent"].padding:{top:0,right:0,bottom:0,left:0},z=B[S],R=B[D],q=Ne(0,E[$],W[$]),V=v?E[$]/2-M-q-z-O.mainAxis:j-q-z-O.mainAxis,K=v?-E[$]/2+M+q+R+O.mainAxis:F+q+R+O.mainAxis,Q=e.elements.arrow&&$e(e.elements.arrow),X=Q?"y"===y?Q.clientTop||0:Q.clientLeft||0:0,Y=null!=(L=null==x?void 0:x[y])?L:0,U=I+K-Y,G=Ne(f?ye(N,I+V-Y-X):N,I,f?ve(P,U):P);A[y]=G,k[y]=G-I}if(a){var J,Z="x"===y?zt:Vt,tt="x"===y?Rt:qt,et=A[w],it="y"===w?"height":"width",nt=et+g[Z],st=et-g[tt],ot=-1!==[zt,Vt].indexOf(_),rt=null!=(J=null==x?void 0:x[w])?J:0,at=ot?nt:et-E[it]-T[it]-rt+O.altAxis,lt=ot?et+E[it]+T[it]-rt-O.altAxis:st,ct=f&&ot?function(t,e,i){var n=Ne(t,e,i);return n>i?i:n}(at,et,lt):Ne(f?at:nt,et,f?lt:st);A[w]=ct,k[w]=ct-et}e.modifiersData[n]=k}},requiresIfExists:["offset"]};function di(t,e,i){void 0===i&&(i=!1);var n,s,o=me(e),r=me(e)&&function(t){var e=t.getBoundingClientRect(),i=we(e.width)/t.offsetWidth||1,n=we(e.height)/t.offsetHeight||1;return 1!==i||1!==n}(e),a=Le(e),l=Te(t,r,i),c={scrollLeft:0,scrollTop:0},h={x:0,y:0};return(o||!o&&!i)&&(("body"!==ue(e)||Ue(a))&&(c=(n=e)!==fe(n)&&me(n)?{scrollLeft:(s=n).scrollLeft,scrollTop:s.scrollTop}:Xe(n)),me(e)?((h=Te(e,!0)).x+=e.clientLeft,h.y+=e.clientTop):a&&(h.x=Ye(a))),{x:l.left+c.scrollLeft-h.x,y:l.top+c.scrollTop-h.y,width:l.width,height:l.height}}function ui(t){var e=new Map,i=new Set,n=[];function s(t){i.add(t.name),[].concat(t.requires||[],t.requiresIfExists||[]).forEach((function(t){if(!i.has(t)){var n=e.get(t);n&&s(n)}})),n.push(t)}return t.forEach((function(t){e.set(t.name,t)})),t.forEach((function(t){i.has(t.name)||s(t)})),n}var fi={placement:"bottom",modifiers:[],strategy:"absolute"};function pi(){for(var t=arguments.length,e=new Array(t),i=0;iNumber.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return(this._inNavbar||"static"===this._config.display)&&(F.setDataAttribute(this._menu,"popper","static"),t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,...g(this._config.popperConfig,[t])}}_selectMenuItem({key:t,target:e}){const i=z.find(".dropdown-menu 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e=/input|textarea/i.test(t.target.tagName),i="Escape"===t.key,n=[Ei,Ti].includes(t.key);if(!n&&!i)return;if(e&&!i)return;t.preventDefault();const s=this.matches(Ii)?this:z.prev(this,Ii)[0]||z.next(this,Ii)[0]||z.findOne(Ii,t.delegateTarget.parentNode),o=qi.getOrCreateInstance(s);if(n)return t.stopPropagation(),o.show(),void o._selectMenuItem(t);o._isShown()&&(t.stopPropagation(),o.hide(),s.focus())}}N.on(document,Si,Ii,qi.dataApiKeydownHandler),N.on(document,Si,Pi,qi.dataApiKeydownHandler),N.on(document,Li,qi.clearMenus),N.on(document,Di,qi.clearMenus),N.on(document,Li,Ii,(function(t){t.preventDefault(),qi.getOrCreateInstance(this).toggle()})),m(qi);const Vi="backdrop",Ki="show",Qi=`mousedown.bs.${Vi}`,Xi={className:"modal-backdrop",clickCallback:null,isAnimated:!1,isVisible:!0,rootElement:"body"},Yi={className:"string",clickCallback:"(function|null)",isAnimated:"boolean",isVisible:"boolean",rootElement:"(element|string)"};class Ui extends H{constructor(t){super(),this._config=this._getConfig(t),this._isAppended=!1,this._element=null}static get Default(){return Xi}static get DefaultType(){return Yi}static get NAME(){return Vi}show(t){if(!this._config.isVisible)return void g(t);this._append();const e=this._getElement();this._config.isAnimated&&d(e),e.classList.add(Ki),this._emulateAnimation((()=>{g(t)}))}hide(t){this._config.isVisible?(this._getElement().classList.remove(Ki),this._emulateAnimation((()=>{this.dispose(),g(t)}))):g(t)}dispose(){this._isAppended&&(N.off(this._element,Qi),this._element.remove(),this._isAppended=!1)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_configAfterMerge(t){return t.rootElement=r(t.rootElement),t}_append(){if(this._isAppended)return;const t=this._getElement();this._config.rootElement.append(t),N.on(t,Qi,(()=>{g(this._config.clickCallback)})),this._isAppended=!0}_emulateAnimation(t){_(t,this._getElement(),this._config.isAnimated)}}const Gi=".bs.focustrap",Ji=`focusin${Gi}`,Zi=`keydown.tab${Gi}`,tn="backward",en={autofocus:!0,trapElement:null},nn={autofocus:"boolean",trapElement:"element"};class sn extends H{constructor(t){super(),this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}static get Default(){return en}static get DefaultType(){return nn}static get NAME(){return"focustrap"}activate(){this._isActive||(this._config.autofocus&&this._config.trapElement.focus(),N.off(document,Gi),N.on(document,Ji,(t=>this._handleFocusin(t))),N.on(document,Zi,(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,N.off(document,Gi))}_handleFocusin(t){const{trapElement:e}=this._config;if(t.target===document||t.target===e||e.contains(t.target))return;const i=z.focusableChildren(e);0===i.length?e.focus():this._lastTabNavDirection===tn?i[i.length-1].focus():i[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?tn:"forward")}}const on=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",rn=".sticky-top",an="padding-right",ln="margin-right";class cn{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,an,(e=>e+t)),this._setElementAttributes(on,an,(e=>e+t)),this._setElementAttributes(rn,ln,(e=>e-t))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,an),this._resetElementAttributes(on,an),this._resetElementAttributes(rn,ln)}isOverflowing(){return this.getWidth()>0}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t).getPropertyValue(e);t.style.setProperty(e,`${i(Number.parseFloat(s))}px`)}))}_saveInitialAttribute(t,e){const i=t.style.getPropertyValue(e);i&&F.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=F.getDataAttribute(t,e);null!==i?(F.removeDataAttribute(t,e),t.style.setProperty(e,i)):t.style.removeProperty(e)}))}_applyManipulationCallback(t,e){if(o(t))e(t);else for(const i of z.find(t,this._element))e(i)}}const hn=".bs.modal",dn=`hide${hn}`,un=`hidePrevented${hn}`,fn=`hidden${hn}`,pn=`show${hn}`,mn=`shown${hn}`,gn=`resize${hn}`,_n=`click.dismiss${hn}`,bn=`mousedown.dismiss${hn}`,vn=`keydown.dismiss${hn}`,yn=`click${hn}.data-api`,wn="modal-open",An="show",En="modal-static",Tn={backdrop:!0,focus:!0,keyboard:!0},Cn={backdrop:"(boolean|string)",focus:"boolean",keyboard:"boolean"};class On extends W{constructor(t,e){super(t,e),this._dialog=z.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._isTransitioning=!1,this._scrollBar=new cn,this._addEventListeners()}static get Default(){return Tn}static get DefaultType(){return Cn}static get NAME(){return"modal"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||N.trigger(this._element,pn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isTransitioning=!0,this._scrollBar.hide(),document.body.classList.add(wn),this._adjustDialog(),this._backdrop.show((()=>this._showElement(t))))}hide(){this._isShown&&!this._isTransitioning&&(N.trigger(this._element,dn).defaultPrevented||(this._isShown=!1,this._isTransitioning=!0,this._focustrap.deactivate(),this._element.classList.remove(An),this._queueCallback((()=>this._hideModal()),this._element,this._isAnimated())))}dispose(){N.off(window,hn),N.off(this._dialog,hn),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new Ui({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_showElement(t){document.body.contains(this._element)||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0;const e=z.findOne(".modal-body",this._dialog);e&&(e.scrollTop=0),d(this._element),this._element.classList.add(An),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,N.trigger(this._element,mn,{relatedTarget:t})}),this._dialog,this._isAnimated())}_addEventListeners(){N.on(this._element,vn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():this._triggerBackdropTransition())})),N.on(window,gn,(()=>{this._isShown&&!this._isTransitioning&&this._adjustDialog()})),N.on(this._element,bn,(t=>{N.one(this._element,_n,(e=>{this._element===t.target&&this._element===e.target&&("static"!==this._config.backdrop?this._config.backdrop&&this.hide():this._triggerBackdropTransition())}))}))}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(wn),this._resetAdjustments(),this._scrollBar.reset(),N.trigger(this._element,fn)}))}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(N.trigger(this._element,un).defaultPrevented)return;const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._element.style.overflowY;"hidden"===e||this._element.classList.contains(En)||(t||(this._element.style.overflowY="hidden"),this._element.classList.add(En),this._queueCallback((()=>{this._element.classList.remove(En),this._queueCallback((()=>{this._element.style.overflowY=e}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;if(i&&!t){const t=p()?"paddingLeft":"paddingRight";this._element.style[t]=`${e}px`}if(!i&&t){const t=p()?"paddingRight":"paddingLeft";this._element.style[t]=`${e}px`}}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=On.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}N.on(document,yn,'[data-bs-toggle="modal"]',(function(t){const e=z.getElementFromSelector(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),N.one(e,pn,(t=>{t.defaultPrevented||N.one(e,fn,(()=>{a(this)&&this.focus()}))}));const i=z.findOne(".modal.show");i&&On.getInstance(i).hide(),On.getOrCreateInstance(e).toggle(this)})),R(On),m(On);const xn=".bs.offcanvas",kn=".data-api",Ln=`load${xn}${kn}`,Sn="show",Dn="showing",$n="hiding",In=".offcanvas.show",Nn=`show${xn}`,Pn=`shown${xn}`,Mn=`hide${xn}`,jn=`hidePrevented${xn}`,Fn=`hidden${xn}`,Hn=`resize${xn}`,Wn=`click${xn}${kn}`,Bn=`keydown.dismiss${xn}`,zn={backdrop:!0,keyboard:!0,scroll:!1},Rn={backdrop:"(boolean|string)",keyboard:"boolean",scroll:"boolean"};class qn extends W{constructor(t,e){super(t,e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get Default(){return zn}static get DefaultType(){return Rn}static get NAME(){return"offcanvas"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||N.trigger(this._element,Nn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._backdrop.show(),this._config.scroll||(new cn).hide(),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add(Dn),this._queueCallback((()=>{this._config.scroll&&!this._config.backdrop||this._focustrap.activate(),this._element.classList.add(Sn),this._element.classList.remove(Dn),N.trigger(this._element,Pn,{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(N.trigger(this._element,Mn).defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.add($n),this._backdrop.hide(),this._queueCallback((()=>{this._element.classList.remove(Sn,$n),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._config.scroll||(new cn).reset(),N.trigger(this._element,Fn)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_initializeBackDrop(){const t=Boolean(this._config.backdrop);return new Ui({className:"offcanvas-backdrop",isVisible:t,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:t?()=>{"static"!==this._config.backdrop?this.hide():N.trigger(this._element,jn)}:null})}_initializeFocusTrap(){return new sn({trapElement:this._element})}_addEventListeners(){N.on(this._element,Bn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():N.trigger(this._element,jn))}))}static jQueryInterface(t){return this.each((function(){const e=qn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}N.on(document,Wn,'[data-bs-toggle="offcanvas"]',(function(t){const e=z.getElementFromSelector(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),l(this))return;N.one(e,Fn,(()=>{a(this)&&this.focus()}));const i=z.findOne(In);i&&i!==e&&qn.getInstance(i).hide(),qn.getOrCreateInstance(e).toggle(this)})),N.on(window,Ln,(()=>{for(const t of z.find(In))qn.getOrCreateInstance(t).show()})),N.on(window,Hn,(()=>{for(const t of z.find("[aria-modal][class*=show][class*=offcanvas-]"))"fixed"!==getComputedStyle(t).position&&qn.getOrCreateInstance(t).hide()})),R(qn),m(qn);const Vn={"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],div:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},Kn=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Qn=/^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i,Xn=(t,e)=>{const i=t.nodeName.toLowerCase();return e.includes(i)?!Kn.has(i)||Boolean(Qn.test(t.nodeValue)):e.filter((t=>t instanceof RegExp)).some((t=>t.test(i)))},Yn={allowList:Vn,content:{},extraClass:"",html:!1,sanitize:!0,sanitizeFn:null,template:"
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")),e}_typeCheckConfig(t){super._typeCheckConfig(t),this._checkContent(t.content)}_checkContent(t){for(const[e,i]of Object.entries(t))super._typeCheckConfig({selector:e,entry:i},Gn)}_setContent(t,e,i){const n=z.findOne(i,t);n&&((e=this._resolvePossibleFunction(e))?o(e)?this._putElementInTemplate(r(e),n):this._config.html?n.innerHTML=this._maybeSanitize(e):n.textContent=e:n.remove())}_maybeSanitize(t){return this._config.sanitize?function(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(const t of s){const i=t.nodeName.toLowerCase();if(!Object.keys(e).includes(i)){t.remove();continue}const n=[].concat(...t.attributes),s=[].concat(e["*"]||[],e[i]||[]);for(const e of n)Xn(e,s)||t.removeAttribute(e.nodeName)}return n.body.innerHTML}(t,this._config.allowList,this._config.sanitizeFn):t}_resolvePossibleFunction(t){return g(t,[this])}_putElementInTemplate(t,e){if(this._config.html)return e.innerHTML="",void e.append(t);e.textContent=t.textContent}}const Zn=new Set(["sanitize","allowList","sanitizeFn"]),ts="fade",es="show",is=".modal",ns="hide.bs.modal",ss="hover",os="focus",rs={AUTO:"auto",TOP:"top",RIGHT:p()?"left":"right",BOTTOM:"bottom",LEFT:p()?"right":"left"},as={allowList:Vn,animation:!0,boundary:"clippingParents",container:!1,customClass:"",delay:0,fallbackPlacements:["top","right","bottom","left"],html:!1,offset:[0,6],placement:"top",popperConfig:null,sanitize:!0,sanitizeFn:null,selector:!1,template:'',title:"",trigger:"hover focus"},ls={allowList:"object",animation:"boolean",boundary:"(string|element)",container:"(string|element|boolean)",customClass:"(string|function)",delay:"(number|object)",fallbackPlacements:"array",html:"boolean",offset:"(array|string|function)",placement:"(string|function)",popperConfig:"(null|object|function)",sanitize:"boolean",sanitizeFn:"(null|function)",selector:"(string|boolean)",template:"string",title:"(string|element|function)",trigger:"string"};class cs extends W{constructor(t,e){if(void 0===vi)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t,e),this._isEnabled=!0,this._timeout=0,this._isHovered=null,this._activeTrigger={},this._popper=null,this._templateFactory=null,this._newContent=null,this.tip=null,this._setListeners(),this._config.selector||this._fixTitle()}static get Default(){return as}static get DefaultType(){return ls}static get NAME(){return"tooltip"}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(){this._isEnabled&&(this._activeTrigger.click=!this._activeTrigger.click,this._isShown()?this._leave():this._enter())}dispose(){clearTimeout(this._timeout),N.off(this._element.closest(is),ns,this._hideModalHandler),this._element.getAttribute("data-bs-original-title")&&this._element.setAttribute("title",this._element.getAttribute("data-bs-original-title")),this._disposePopper(),super.dispose()}show(){if("none"===this._element.style.display)throw new Error("Please use show on visible elements");if(!this._isWithContent()||!this._isEnabled)return;const t=N.trigger(this._element,this.constructor.eventName("show")),e=(c(this._element)||this._element.ownerDocument.documentElement).contains(this._element);if(t.defaultPrevented||!e)return;this._disposePopper();const i=this._getTipElement();this._element.setAttribute("aria-describedby",i.getAttribute("id"));const{container:n}=this._config;if(this._element.ownerDocument.documentElement.contains(this.tip)||(n.append(i),N.trigger(this._element,this.constructor.eventName("inserted"))),this._popper=this._createPopper(i),i.classList.add(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.on(t,"mouseover",h);this._queueCallback((()=>{N.trigger(this._element,this.constructor.eventName("shown")),!1===this._isHovered&&this._leave(),this._isHovered=!1}),this.tip,this._isAnimated())}hide(){if(this._isShown()&&!N.trigger(this._element,this.constructor.eventName("hide")).defaultPrevented){if(this._getTipElement().classList.remove(es),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))N.off(t,"mouseover",h);this._activeTrigger.click=!1,this._activeTrigger[os]=!1,this._activeTrigger[ss]=!1,this._isHovered=null,this._queueCallback((()=>{this._isWithActiveTrigger()||(this._isHovered||this._disposePopper(),this._element.removeAttribute("aria-describedby"),N.trigger(this._element,this.constructor.eventName("hidden")))}),this.tip,this._isAnimated())}}update(){this._popper&&this._popper.update()}_isWithContent(){return Boolean(this._getTitle())}_getTipElement(){return this.tip||(this.tip=this._createTipElement(this._newContent||this._getContentForTemplate())),this.tip}_createTipElement(t){const e=this._getTemplateFactory(t).toHtml();if(!e)return null;e.classList.remove(ts,es),e.classList.add(`bs-${this.constructor.NAME}-auto`);const i=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME).toString();return e.setAttribute("id",i),this._isAnimated()&&e.classList.add(ts),e}setContent(t){this._newContent=t,this._isShown()&&(this._disposePopper(),this.show())}_getTemplateFactory(t){return this._templateFactory?this._templateFactory.changeContent(t):this._templateFactory=new Jn({...this._config,content:t,extraClass:this._resolvePossibleFunction(this._config.customClass)}),this._templateFactory}_getContentForTemplate(){return{".tooltip-inner":this._getTitle()}}_getTitle(){return this._resolvePossibleFunction(this._config.title)||this._element.getAttribute("data-bs-original-title")}_initializeOnDelegatedTarget(t){return this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_isAnimated(){return this._config.animation||this.tip&&this.tip.classList.contains(ts)}_isShown(){return this.tip&&this.tip.classList.contains(es)}_createPopper(t){const e=g(this._config.placement,[this,t,this._element]),i=rs[e.toUpperCase()];return bi(this._element,t,this._getPopperConfig(i))}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_resolvePossibleFunction(t){return g(t,[this._element])}_getPopperConfig(t){const e={placement:t,modifiers:[{name:"flip",options:{fallbackPlacements:this._config.fallbackPlacements}},{name:"offset",options:{offset:this._getOffset()}},{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"arrow",options:{element:`.${this.constructor.NAME}-arrow`}},{name:"preSetPlacement",enabled:!0,phase:"beforeMain",fn:t=>{this._getTipElement().setAttribute("data-popper-placement",t.state.placement)}}]};return{...e,...g(this._config.popperConfig,[e])}}_setListeners(){const t=this._config.trigger.split(" ");for(const e of t)if("click"===e)N.on(this._element,this.constructor.eventName("click"),this._config.selector,(t=>{this._initializeOnDelegatedTarget(t).toggle()}));else if("manual"!==e){const t=e===ss?this.constructor.eventName("mouseenter"):this.constructor.eventName("focusin"),i=e===ss?this.constructor.eventName("mouseleave"):this.constructor.eventName("focusout");N.on(this._element,t,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusin"===t.type?os:ss]=!0,e._enter()})),N.on(this._element,i,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusout"===t.type?os:ss]=e._element.contains(t.relatedTarget),e._leave()}))}this._hideModalHandler=()=>{this._element&&this.hide()},N.on(this._element.closest(is),ns,this._hideModalHandler)}_fixTitle(){const t=this._element.getAttribute("title");t&&(this._element.getAttribute("aria-label")||this._element.textContent.trim()||this._element.setAttribute("aria-label",t),this._element.setAttribute("data-bs-original-title",t),this._element.removeAttribute("title"))}_enter(){this._isShown()||this._isHovered?this._isHovered=!0:(this._isHovered=!0,this._setTimeout((()=>{this._isHovered&&this.show()}),this._config.delay.show))}_leave(){this._isWithActiveTrigger()||(this._isHovered=!1,this._setTimeout((()=>{this._isHovered||this.hide()}),this._config.delay.hide))}_setTimeout(t,e){clearTimeout(this._timeout),this._timeout=setTimeout(t,e)}_isWithActiveTrigger(){return Object.values(this._activeTrigger).includes(!0)}_getConfig(t){const e=F.getDataAttributes(this._element);for(const t of Object.keys(e))Zn.has(t)&&delete e[t];return t={...e,..."object"==typeof t&&t?t:{}},t=this._mergeConfigObj(t),t=this._configAfterMerge(t),this._typeCheckConfig(t),t}_configAfterMerge(t){return t.container=!1===t.container?document.body:r(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),t}_getDelegateConfig(){const t={};for(const[e,i]of Object.entries(this._config))this.constructor.Default[e]!==i&&(t[e]=i);return t.selector=!1,t.trigger="manual",t}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null),this.tip&&(this.tip.remove(),this.tip=null)}static jQueryInterface(t){return this.each((function(){const e=cs.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}m(cs);const hs={...cs.Default,content:"",offset:[0,8],placement:"right",template:'',trigger:"click"},ds={...cs.DefaultType,content:"(null|string|element|function)"};class us extends cs{static get Default(){return hs}static get DefaultType(){return ds}static get 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e=this._observableSections.get(t.target.hash);if(e){t.preventDefault();const i=this._rootElement||window,n=e.offsetTop-this._element.offsetTop;if(i.scrollTo)return void i.scrollTo({top:n,behavior:"smooth"});i.scrollTop=n}})))}_getNewObserver(){const t={root:this._rootElement,threshold:this._config.threshold,rootMargin:this._config.rootMargin};return new IntersectionObserver((t=>this._observerCallback(t)),t)}_observerCallback(t){const e=t=>this._targetLinks.get(`#${t.target.id}`),i=t=>{this._previousScrollData.visibleEntryTop=t.target.offsetTop,this._process(e(t))},n=(this._rootElement||document.documentElement).scrollTop,s=n>=this._previousScrollData.parentScrollTop;this._previousScrollData.parentScrollTop=n;for(const o of t){if(!o.isIntersecting){this._activeTarget=null,this._clearActiveClass(e(o));continue}const t=o.target.offsetTop>=this._previousScrollData.visibleEntryTop;if(s&&t){if(i(o),!n)return}else s||t||i(o)}}_initializeTargetsAndObservables(){this._targetLinks=new Map,this._observableSections=new Map;const t=z.find(bs,this._config.target);for(const e of t){if(!e.hash||l(e))continue;const t=z.findOne(decodeURI(e.hash),this._element);a(t)&&(this._targetLinks.set(decodeURI(e.hash),e),this._observableSections.set(e.hash,t))}}_process(t){this._activeTarget!==t&&(this._clearActiveClass(this._config.target),this._activeTarget=t,t.classList.add(_s),this._activateParents(t),N.trigger(this._element,ps,{relatedTarget:t}))}_activateParents(t){if(t.classList.contains("dropdown-item"))z.findOne(".dropdown-toggle",t.closest(".dropdown")).classList.add(_s);else for(const e of z.parents(t,".nav, .list-group"))for(const t of z.prev(e,ys))t.classList.add(_s)}_clearActiveClass(t){t.classList.remove(_s);const e=z.find(`${bs}.${_s}`,t);for(const t of e)t.classList.remove(_s)}static jQueryInterface(t){return this.each((function(){const e=Es.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}))}}N.on(window,gs,(()=>{for(const t of z.find('[data-bs-spy="scroll"]'))Es.getOrCreateInstance(t)})),m(Es);const Ts=".bs.tab",Cs=`hide${Ts}`,Os=`hidden${Ts}`,xs=`show${Ts}`,ks=`shown${Ts}`,Ls=`click${Ts}`,Ss=`keydown${Ts}`,Ds=`load${Ts}`,$s="ArrowLeft",Is="ArrowRight",Ns="ArrowUp",Ps="ArrowDown",Ms="Home",js="End",Fs="active",Hs="fade",Ws="show",Bs=":not(.dropdown-toggle)",zs='[data-bs-toggle="tab"], [data-bs-toggle="pill"], [data-bs-toggle="list"]',Rs=`.nav-link${Bs}, .list-group-item${Bs}, [role="tab"]${Bs}, ${zs}`,qs=`.${Fs}[data-bs-toggle="tab"], .${Fs}[data-bs-toggle="pill"], .${Fs}[data-bs-toggle="list"]`;class Vs extends W{constructor(t){super(t),this._parent=this._element.closest('.list-group, .nav, [role="tablist"]'),this._parent&&(this._setInitialAttributes(this._parent,this._getChildren()),N.on(this._element,Ss,(t=>this._keydown(t))))}static get NAME(){return"tab"}show(){const t=this._element;if(this._elemIsActive(t))return;const e=this._getActiveElem(),i=e?N.trigger(e,Cs,{relatedTarget:t}):null;N.trigger(t,xs,{relatedTarget:e}).defaultPrevented||i&&i.defaultPrevented||(this._deactivate(e,t),this._activate(t,e))}_activate(t,e){t&&(t.classList.add(Fs),this._activate(z.getElementFromSelector(t)),this._queueCallback((()=>{"tab"===t.getAttribute("role")?(t.removeAttribute("tabindex"),t.setAttribute("aria-selected",!0),this._toggleDropDown(t,!0),N.trigger(t,ks,{relatedTarget:e})):t.classList.add(Ws)}),t,t.classList.contains(Hs)))}_deactivate(t,e){t&&(t.classList.remove(Fs),t.blur(),this._deactivate(z.getElementFromSelector(t)),this._queueCallback((()=>{"tab"===t.getAttribute("role")?(t.setAttribute("aria-selected",!1),t.setAttribute("tabindex","-1"),this._toggleDropDown(t,!1),N.trigger(t,Os,{relatedTarget:e})):t.classList.remove(Ws)}),t,t.classList.contains(Hs)))}_keydown(t){if(![$s,Is,Ns,Ps,Ms,js].includes(t.key))return;t.stopPropagation(),t.preventDefault();const e=this._getChildren().filter((t=>!l(t)));let i;if([Ms,js].includes(t.key))i=e[t.key===Ms?0:e.length-1];else{const n=[Is,Ps].includes(t.key);i=b(e,t.target,n,!0)}i&&(i.focus({preventScroll:!0}),Vs.getOrCreateInstance(i).show())}_getChildren(){return z.find(Rs,this._parent)}_getActiveElem(){return this._getChildren().find((t=>this._elemIsActive(t)))||null}_setInitialAttributes(t,e){this._setAttributeIfNotExists(t,"role","tablist");for(const t of e)this._setInitialAttributesOnChild(t)}_setInitialAttributesOnChild(t){t=this._getInnerElement(t);const e=this._elemIsActive(t),i=this._getOuterElement(t);t.setAttribute("aria-selected",e),i!==t&&this._setAttributeIfNotExists(i,"role","presentation"),e||t.setAttribute("tabindex","-1"),this._setAttributeIfNotExists(t,"role","tab"),this._setInitialAttributesOnTargetPanel(t)}_setInitialAttributesOnTargetPanel(t){const 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* --------------------------------------------------------------------------\n * Bootstrap dom/data.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n/**\n * Constants\n */\n\nconst elementMap = new Map()\n\nexport default {\n set(element, key, instance) {\n if (!elementMap.has(element)) {\n elementMap.set(element, new Map())\n }\n\n const instanceMap = elementMap.get(element)\n\n // make it clear we only want one instance per element\n // can be removed later when multiple key/instances are fine to be used\n if (!instanceMap.has(key) && instanceMap.size !== 0) {\n // eslint-disable-next-line no-console\n console.error(`Bootstrap doesn't allow more than one instance per element. Bound instance: ${Array.from(instanceMap.keys())[0]}.`)\n return\n }\n\n instanceMap.set(key, instance)\n },\n\n get(element, key) {\n if (elementMap.has(element)) {\n return elementMap.get(element).get(key) || null\n }\n\n return null\n },\n\n remove(element, key) {\n if (!elementMap.has(element)) {\n return\n }\n\n const instanceMap = elementMap.get(element)\n\n instanceMap.delete(key)\n\n // free up element references if there are no instances left for an element\n if (instanceMap.size === 0) {\n elementMap.delete(element)\n }\n }\n}\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/index.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nconst MAX_UID = 1_000_000\nconst MILLISECONDS_MULTIPLIER = 1000\nconst TRANSITION_END = 'transitionend'\n\n/**\n * Properly escape IDs selectors to handle weird IDs\n * @param {string} selector\n * @returns {string}\n */\nconst parseSelector = selector => {\n if (selector && window.CSS && window.CSS.escape) {\n // document.querySelector needs escaping to handle IDs (html5+) containing for instance /\n selector = selector.replace(/#([^\\s\"#']+)/g, (match, id) => `#${CSS.escape(id)}`)\n }\n\n return selector\n}\n\n// Shout-out Angus Croll (https://goo.gl/pxwQGp)\nconst toType = object => {\n if (object === null || object === undefined) {\n return `${object}`\n }\n\n return Object.prototype.toString.call(object).match(/\\s([a-z]+)/i)[1].toLowerCase()\n}\n\n/**\n * Public Util API\n */\n\nconst getUID = prefix => {\n do {\n prefix += Math.floor(Math.random() * MAX_UID)\n } while (document.getElementById(prefix))\n\n return prefix\n}\n\nconst getTransitionDurationFromElement = element => {\n if (!element) {\n return 0\n }\n\n // Get transition-duration of the element\n let { transitionDuration, transitionDelay } = window.getComputedStyle(element)\n\n const floatTransitionDuration = Number.parseFloat(transitionDuration)\n const floatTransitionDelay = Number.parseFloat(transitionDelay)\n\n // Return 0 if element or transition duration is not found\n if (!floatTransitionDuration && !floatTransitionDelay) {\n return 0\n }\n\n // If multiple durations are defined, take the first\n transitionDuration = transitionDuration.split(',')[0]\n transitionDelay = transitionDelay.split(',')[0]\n\n return (Number.parseFloat(transitionDuration) + Number.parseFloat(transitionDelay)) * MILLISECONDS_MULTIPLIER\n}\n\nconst triggerTransitionEnd = element => {\n element.dispatchEvent(new Event(TRANSITION_END))\n}\n\nconst isElement = object => {\n if (!object || typeof object !== 'object') {\n return false\n }\n\n if (typeof object.jquery !== 'undefined') {\n object = object[0]\n }\n\n return typeof object.nodeType !== 'undefined'\n}\n\nconst getElement = object => {\n // it's a jQuery object or a node element\n if (isElement(object)) {\n return object.jquery ? object[0] : object\n }\n\n if (typeof object === 'string' && object.length > 0) {\n return document.querySelector(parseSelector(object))\n }\n\n return null\n}\n\nconst isVisible = element => {\n if (!isElement(element) || element.getClientRects().length === 0) {\n return false\n }\n\n const elementIsVisible = getComputedStyle(element).getPropertyValue('visibility') === 'visible'\n // Handle `details` element as its content may falsie appear visible when it is closed\n const closedDetails = element.closest('details:not([open])')\n\n if (!closedDetails) {\n return elementIsVisible\n }\n\n if (closedDetails !== element) {\n const summary = element.closest('summary')\n if (summary && summary.parentNode !== closedDetails) {\n return false\n }\n\n if (summary === null) {\n return false\n }\n }\n\n return elementIsVisible\n}\n\nconst isDisabled = element => {\n if (!element || element.nodeType !== Node.ELEMENT_NODE) {\n return true\n }\n\n if (element.classList.contains('disabled')) {\n return true\n }\n\n if (typeof element.disabled !== 'undefined') {\n return element.disabled\n }\n\n return element.hasAttribute('disabled') && element.getAttribute('disabled') !== 'false'\n}\n\nconst findShadowRoot = element => {\n if (!document.documentElement.attachShadow) {\n return null\n }\n\n // Can find the shadow root otherwise it'll return the document\n if (typeof element.getRootNode === 'function') {\n const root = element.getRootNode()\n return root instanceof ShadowRoot ? root : null\n }\n\n if (element instanceof ShadowRoot) {\n return element\n }\n\n // when we don't find a shadow root\n if (!element.parentNode) {\n return null\n }\n\n return findShadowRoot(element.parentNode)\n}\n\nconst noop = () => {}\n\n/**\n * Trick to restart an element's animation\n *\n * @param {HTMLElement} element\n * @return void\n *\n * @see https://www.charistheo.io/blog/2021/02/restart-a-css-animation-with-javascript/#restarting-a-css-animation\n */\nconst reflow = element => {\n element.offsetHeight // eslint-disable-line no-unused-expressions\n}\n\nconst getjQuery = () => {\n if (window.jQuery && !document.body.hasAttribute('data-bs-no-jquery')) {\n return window.jQuery\n }\n\n return null\n}\n\nconst DOMContentLoadedCallbacks = []\n\nconst onDOMContentLoaded = callback => {\n if (document.readyState === 'loading') {\n // add listener on the first call when the document is in loading state\n if (!DOMContentLoadedCallbacks.length) {\n document.addEventListener('DOMContentLoaded', () => {\n for (const callback of DOMContentLoadedCallbacks) {\n callback()\n }\n })\n }\n\n DOMContentLoadedCallbacks.push(callback)\n } else {\n callback()\n }\n}\n\nconst isRTL = () => document.documentElement.dir === 'rtl'\n\nconst defineJQueryPlugin = plugin => {\n onDOMContentLoaded(() => {\n const $ = getjQuery()\n /* istanbul ignore if */\n if ($) {\n const name = plugin.NAME\n const JQUERY_NO_CONFLICT = $.fn[name]\n $.fn[name] = plugin.jQueryInterface\n $.fn[name].Constructor = plugin\n $.fn[name].noConflict = () => {\n $.fn[name] = JQUERY_NO_CONFLICT\n return plugin.jQueryInterface\n }\n }\n })\n}\n\nconst execute = (possibleCallback, args = [], defaultValue = possibleCallback) => {\n return typeof possibleCallback === 'function' ? possibleCallback(...args) : defaultValue\n}\n\nconst executeAfterTransition = (callback, transitionElement, waitForTransition = true) => {\n if (!waitForTransition) {\n execute(callback)\n return\n }\n\n const durationPadding = 5\n const emulatedDuration = getTransitionDurationFromElement(transitionElement) + durationPadding\n\n let called = false\n\n const handler = ({ target }) => {\n if (target !== transitionElement) {\n return\n }\n\n called = true\n transitionElement.removeEventListener(TRANSITION_END, handler)\n execute(callback)\n }\n\n transitionElement.addEventListener(TRANSITION_END, handler)\n setTimeout(() => {\n if (!called) {\n triggerTransitionEnd(transitionElement)\n }\n }, emulatedDuration)\n}\n\n/**\n * Return the previous/next element of a list.\n *\n * @param {array} list The list of elements\n * @param activeElement The active element\n * @param shouldGetNext Choose to get next or previous element\n * @param isCycleAllowed\n * @return {Element|elem} The proper element\n */\nconst getNextActiveElement = (list, activeElement, shouldGetNext, isCycleAllowed) => {\n const listLength = list.length\n let index = list.indexOf(activeElement)\n\n // if the element does not exist in the list return an element\n // depending on the direction and if cycle is allowed\n if (index === -1) {\n return !shouldGetNext && isCycleAllowed ? list[listLength - 1] : list[0]\n }\n\n index += shouldGetNext ? 1 : -1\n\n if (isCycleAllowed) {\n index = (index + listLength) % listLength\n }\n\n return list[Math.max(0, Math.min(index, listLength - 1))]\n}\n\nexport {\n defineJQueryPlugin,\n execute,\n executeAfterTransition,\n findShadowRoot,\n getElement,\n getjQuery,\n getNextActiveElement,\n getTransitionDurationFromElement,\n getUID,\n isDisabled,\n isElement,\n isRTL,\n isVisible,\n noop,\n onDOMContentLoaded,\n parseSelector,\n reflow,\n triggerTransitionEnd,\n toType\n}\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/event-handler.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport { getjQuery } from '../util/index.js'\n\n/**\n * Constants\n */\n\nconst namespaceRegex = /[^.]*(?=\\..*)\\.|.*/\nconst stripNameRegex = /\\..*/\nconst stripUidRegex = /::\\d+$/\nconst eventRegistry = {} // Events storage\nlet uidEvent = 1\nconst customEvents = {\n mouseenter: 'mouseover',\n mouseleave: 'mouseout'\n}\n\nconst nativeEvents = new Set([\n 'click',\n 'dblclick',\n 'mouseup',\n 'mousedown',\n 'contextmenu',\n 'mousewheel',\n 'DOMMouseScroll',\n 'mouseover',\n 'mouseout',\n 'mousemove',\n 'selectstart',\n 'selectend',\n 'keydown',\n 'keypress',\n 'keyup',\n 'orientationchange',\n 'touchstart',\n 'touchmove',\n 'touchend',\n 'touchcancel',\n 'pointerdown',\n 'pointermove',\n 'pointerup',\n 'pointerleave',\n 'pointercancel',\n 'gesturestart',\n 'gesturechange',\n 'gestureend',\n 'focus',\n 'blur',\n 'change',\n 'reset',\n 'select',\n 'submit',\n 'focusin',\n 'focusout',\n 'load',\n 'unload',\n 'beforeunload',\n 'resize',\n 'move',\n 'DOMContentLoaded',\n 'readystatechange',\n 'error',\n 'abort',\n 'scroll'\n])\n\n/**\n * Private methods\n */\n\nfunction makeEventUid(element, uid) {\n return (uid && `${uid}::${uidEvent++}`) || element.uidEvent || uidEvent++\n}\n\nfunction getElementEvents(element) {\n const uid = makeEventUid(element)\n\n element.uidEvent = uid\n eventRegistry[uid] = eventRegistry[uid] || {}\n\n return eventRegistry[uid]\n}\n\nfunction bootstrapHandler(element, fn) {\n return function handler(event) {\n hydrateObj(event, { delegateTarget: element })\n\n if (handler.oneOff) {\n EventHandler.off(element, event.type, fn)\n }\n\n return fn.apply(element, [event])\n }\n}\n\nfunction bootstrapDelegationHandler(element, selector, fn) {\n return function handler(event) {\n const domElements = element.querySelectorAll(selector)\n\n for (let { target } = event; target && target !== this; target = target.parentNode) {\n for (const domElement of domElements) {\n if (domElement !== target) {\n continue\n }\n\n hydrateObj(event, { delegateTarget: target })\n\n if (handler.oneOff) {\n EventHandler.off(element, event.type, selector, fn)\n }\n\n return fn.apply(target, [event])\n }\n }\n }\n}\n\nfunction findHandler(events, callable, delegationSelector = null) {\n return Object.values(events)\n .find(event => event.callable === callable && event.delegationSelector === delegationSelector)\n}\n\nfunction normalizeParameters(originalTypeEvent, handler, delegationFunction) {\n const isDelegated = typeof handler === 'string'\n // TODO: tooltip passes `false` instead of selector, so we need to check\n const callable = isDelegated ? delegationFunction : (handler || delegationFunction)\n let typeEvent = getTypeEvent(originalTypeEvent)\n\n if (!nativeEvents.has(typeEvent)) {\n typeEvent = originalTypeEvent\n }\n\n return [isDelegated, callable, typeEvent]\n}\n\nfunction addHandler(element, originalTypeEvent, handler, delegationFunction, oneOff) {\n if (typeof originalTypeEvent !== 'string' || !element) {\n return\n }\n\n let [isDelegated, callable, typeEvent] = normalizeParameters(originalTypeEvent, handler, delegationFunction)\n\n // in case of mouseenter or mouseleave wrap the handler within a function that checks for its DOM position\n // this prevents the handler from being dispatched the same way as mouseover or mouseout does\n if (originalTypeEvent in customEvents) {\n const wrapFunction = fn => {\n return function (event) {\n if (!event.relatedTarget || (event.relatedTarget !== event.delegateTarget && !event.delegateTarget.contains(event.relatedTarget))) {\n return fn.call(this, event)\n }\n }\n }\n\n callable = wrapFunction(callable)\n }\n\n const events = getElementEvents(element)\n const handlers = events[typeEvent] || (events[typeEvent] = {})\n const previousFunction = findHandler(handlers, callable, isDelegated ? handler : null)\n\n if (previousFunction) {\n previousFunction.oneOff = previousFunction.oneOff && oneOff\n\n return\n }\n\n const uid = makeEventUid(callable, originalTypeEvent.replace(namespaceRegex, ''))\n const fn = isDelegated ?\n bootstrapDelegationHandler(element, handler, callable) :\n bootstrapHandler(element, callable)\n\n fn.delegationSelector = isDelegated ? handler : null\n fn.callable = callable\n fn.oneOff = oneOff\n fn.uidEvent = uid\n handlers[uid] = fn\n\n element.addEventListener(typeEvent, fn, isDelegated)\n}\n\nfunction removeHandler(element, events, typeEvent, handler, delegationSelector) {\n const fn = findHandler(events[typeEvent], handler, delegationSelector)\n\n if (!fn) {\n return\n }\n\n element.removeEventListener(typeEvent, fn, Boolean(delegationSelector))\n delete events[typeEvent][fn.uidEvent]\n}\n\nfunction removeNamespacedHandlers(element, events, typeEvent, namespace) {\n const storeElementEvent = events[typeEvent] || {}\n\n for (const [handlerKey, event] of Object.entries(storeElementEvent)) {\n if (handlerKey.includes(namespace)) {\n removeHandler(element, events, typeEvent, event.callable, event.delegationSelector)\n }\n }\n}\n\nfunction getTypeEvent(event) {\n // allow to get the native events from namespaced events ('click.bs.button' --> 'click')\n event = event.replace(stripNameRegex, '')\n return customEvents[event] || event\n}\n\nconst EventHandler = {\n on(element, event, handler, delegationFunction) {\n addHandler(element, event, handler, delegationFunction, false)\n },\n\n one(element, event, handler, delegationFunction) {\n addHandler(element, event, handler, delegationFunction, true)\n },\n\n off(element, originalTypeEvent, handler, delegationFunction) {\n if (typeof originalTypeEvent !== 'string' || !element) {\n return\n }\n\n const [isDelegated, callable, typeEvent] = normalizeParameters(originalTypeEvent, handler, delegationFunction)\n const inNamespace = typeEvent !== originalTypeEvent\n const events = getElementEvents(element)\n const storeElementEvent = events[typeEvent] || {}\n const isNamespace = originalTypeEvent.startsWith('.')\n\n if (typeof callable !== 'undefined') {\n // Simplest case: handler is passed, remove that listener ONLY.\n if (!Object.keys(storeElementEvent).length) {\n return\n }\n\n removeHandler(element, events, typeEvent, callable, isDelegated ? handler : null)\n return\n }\n\n if (isNamespace) {\n for (const elementEvent of Object.keys(events)) {\n removeNamespacedHandlers(element, events, elementEvent, originalTypeEvent.slice(1))\n }\n }\n\n for (const [keyHandlers, event] of Object.entries(storeElementEvent)) {\n const handlerKey = keyHandlers.replace(stripUidRegex, '')\n\n if (!inNamespace || originalTypeEvent.includes(handlerKey)) {\n removeHandler(element, events, typeEvent, event.callable, event.delegationSelector)\n }\n }\n },\n\n trigger(element, event, args) {\n if (typeof event !== 'string' || !element) {\n return null\n }\n\n const $ = getjQuery()\n const typeEvent = getTypeEvent(event)\n const inNamespace = event !== typeEvent\n\n let jQueryEvent = null\n let bubbles = true\n let nativeDispatch = true\n let defaultPrevented = false\n\n if (inNamespace && $) {\n jQueryEvent = $.Event(event, args)\n\n $(element).trigger(jQueryEvent)\n bubbles = !jQueryEvent.isPropagationStopped()\n nativeDispatch = !jQueryEvent.isImmediatePropagationStopped()\n defaultPrevented = jQueryEvent.isDefaultPrevented()\n }\n\n const evt = hydrateObj(new Event(event, { bubbles, cancelable: true }), args)\n\n if (defaultPrevented) {\n evt.preventDefault()\n }\n\n if (nativeDispatch) {\n element.dispatchEvent(evt)\n }\n\n if (evt.defaultPrevented && jQueryEvent) {\n jQueryEvent.preventDefault()\n }\n\n return evt\n }\n}\n\nfunction hydrateObj(obj, meta = {}) {\n for (const [key, value] of Object.entries(meta)) {\n try {\n obj[key] = value\n } catch {\n Object.defineProperty(obj, key, {\n configurable: true,\n get() {\n return value\n }\n })\n }\n }\n\n return obj\n}\n\nexport default EventHandler\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/manipulator.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nfunction normalizeData(value) {\n if (value === 'true') {\n return true\n }\n\n if (value === 'false') {\n return false\n }\n\n if (value === Number(value).toString()) {\n return Number(value)\n }\n\n if (value === '' || value === 'null') {\n return null\n }\n\n if (typeof value !== 'string') {\n return value\n }\n\n try {\n return JSON.parse(decodeURIComponent(value))\n } catch {\n return value\n }\n}\n\nfunction normalizeDataKey(key) {\n return key.replace(/[A-Z]/g, chr => `-${chr.toLowerCase()}`)\n}\n\nconst Manipulator = {\n setDataAttribute(element, key, value) {\n element.setAttribute(`data-bs-${normalizeDataKey(key)}`, value)\n },\n\n removeDataAttribute(element, key) {\n element.removeAttribute(`data-bs-${normalizeDataKey(key)}`)\n },\n\n getDataAttributes(element) {\n if (!element) {\n return {}\n }\n\n const attributes = {}\n const bsKeys = Object.keys(element.dataset).filter(key => key.startsWith('bs') && !key.startsWith('bsConfig'))\n\n for (const key of bsKeys) {\n let pureKey = key.replace(/^bs/, '')\n pureKey = pureKey.charAt(0).toLowerCase() + pureKey.slice(1, pureKey.length)\n attributes[pureKey] = normalizeData(element.dataset[key])\n }\n\n return attributes\n },\n\n getDataAttribute(element, key) {\n return normalizeData(element.getAttribute(`data-bs-${normalizeDataKey(key)}`))\n }\n}\n\nexport default Manipulator\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/config.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport Manipulator from '../dom/manipulator.js'\nimport { isElement, toType } from './index.js'\n\n/**\n * Class definition\n */\n\nclass Config {\n // Getters\n static get Default() {\n return {}\n }\n\n static get DefaultType() {\n return {}\n }\n\n static get NAME() {\n throw new Error('You have to implement the static method \"NAME\", for each component!')\n }\n\n _getConfig(config) {\n config = this._mergeConfigObj(config)\n config = this._configAfterMerge(config)\n this._typeCheckConfig(config)\n return config\n }\n\n _configAfterMerge(config) {\n return config\n }\n\n _mergeConfigObj(config, element) {\n const jsonConfig = isElement(element) ? Manipulator.getDataAttribute(element, 'config') : {} // try to parse\n\n return {\n ...this.constructor.Default,\n ...(typeof jsonConfig === 'object' ? jsonConfig : {}),\n ...(isElement(element) ? Manipulator.getDataAttributes(element) : {}),\n ...(typeof config === 'object' ? config : {})\n }\n }\n\n _typeCheckConfig(config, configTypes = this.constructor.DefaultType) {\n for (const [property, expectedTypes] of Object.entries(configTypes)) {\n const value = config[property]\n const valueType = isElement(value) ? 'element' : toType(value)\n\n if (!new RegExp(expectedTypes).test(valueType)) {\n throw new TypeError(\n `${this.constructor.NAME.toUpperCase()}: Option \"${property}\" provided type \"${valueType}\" but expected type \"${expectedTypes}\".`\n )\n }\n }\n }\n}\n\nexport default Config\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap base-component.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport Data from './dom/data.js'\nimport EventHandler from './dom/event-handler.js'\nimport Config from './util/config.js'\nimport { executeAfterTransition, getElement } from './util/index.js'\n\n/**\n * Constants\n */\n\nconst VERSION = '5.3.1'\n\n/**\n * Class definition\n */\n\nclass BaseComponent extends Config {\n constructor(element, config) {\n super()\n\n element = getElement(element)\n if (!element) {\n return\n }\n\n this._element = element\n this._config = this._getConfig(config)\n\n Data.set(this._element, this.constructor.DATA_KEY, this)\n }\n\n // Public\n dispose() {\n Data.remove(this._element, this.constructor.DATA_KEY)\n EventHandler.off(this._element, this.constructor.EVENT_KEY)\n\n for (const propertyName of Object.getOwnPropertyNames(this)) {\n this[propertyName] = null\n }\n }\n\n _queueCallback(callback, element, isAnimated = true) {\n executeAfterTransition(callback, element, isAnimated)\n }\n\n _getConfig(config) {\n config = this._mergeConfigObj(config, this._element)\n config = this._configAfterMerge(config)\n this._typeCheckConfig(config)\n return config\n }\n\n // Static\n static getInstance(element) {\n return Data.get(getElement(element), this.DATA_KEY)\n }\n\n static getOrCreateInstance(element, config = {}) {\n return this.getInstance(element) || new this(element, typeof config === 'object' ? config : null)\n }\n\n static get VERSION() {\n return VERSION\n }\n\n static get DATA_KEY() {\n return `bs.${this.NAME}`\n }\n\n static get EVENT_KEY() {\n return `.${this.DATA_KEY}`\n }\n\n static eventName(name) {\n return `${name}${this.EVENT_KEY}`\n }\n}\n\nexport default BaseComponent\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/selector-engine.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport { isDisabled, isVisible, parseSelector } from '../util/index.js'\n\nconst getSelector = element => {\n let selector = element.getAttribute('data-bs-target')\n\n if (!selector || selector === '#') {\n let hrefAttribute = element.getAttribute('href')\n\n // The only valid content that could double as a selector are IDs or classes,\n // so everything starting with `#` or `.`. If a \"real\" URL is used as the selector,\n // `document.querySelector` will rightfully complain it is invalid.\n // See https://github.com/twbs/bootstrap/issues/32273\n if (!hrefAttribute || (!hrefAttribute.includes('#') && !hrefAttribute.startsWith('.'))) {\n return null\n }\n\n // Just in case some CMS puts out a full URL with the anchor appended\n if (hrefAttribute.includes('#') && !hrefAttribute.startsWith('#')) {\n hrefAttribute = `#${hrefAttribute.split('#')[1]}`\n }\n\n selector = hrefAttribute && hrefAttribute !== '#' ? hrefAttribute.trim() : null\n }\n\n return parseSelector(selector)\n}\n\nconst SelectorEngine = {\n find(selector, element = document.documentElement) {\n return [].concat(...Element.prototype.querySelectorAll.call(element, selector))\n },\n\n findOne(selector, element = document.documentElement) {\n return Element.prototype.querySelector.call(element, selector)\n },\n\n children(element, selector) {\n return [].concat(...element.children).filter(child => child.matches(selector))\n },\n\n parents(element, selector) {\n const parents = []\n let ancestor = element.parentNode.closest(selector)\n\n while (ancestor) {\n parents.push(ancestor)\n ancestor = ancestor.parentNode.closest(selector)\n }\n\n return parents\n },\n\n prev(element, selector) {\n let previous = element.previousElementSibling\n\n while (previous) {\n if (previous.matches(selector)) {\n return [previous]\n }\n\n previous = previous.previousElementSibling\n }\n\n return []\n },\n // TODO: this is now unused; remove later along with prev()\n next(element, selector) {\n let next = element.nextElementSibling\n\n while (next) {\n if (next.matches(selector)) {\n return [next]\n }\n\n next = next.nextElementSibling\n }\n\n return []\n },\n\n focusableChildren(element) {\n const focusables = [\n 'a',\n 'button',\n 'input',\n 'textarea',\n 'select',\n 'details',\n '[tabindex]',\n '[contenteditable=\"true\"]'\n ].map(selector => `${selector}:not([tabindex^=\"-\"])`).join(',')\n\n return this.find(focusables, element).filter(el => !isDisabled(el) && isVisible(el))\n },\n\n getSelectorFromElement(element) {\n const selector = getSelector(element)\n\n if (selector) {\n return SelectorEngine.findOne(selector) ? selector : null\n }\n\n return null\n },\n\n getElementFromSelector(element) {\n const selector = getSelector(element)\n\n return selector ? SelectorEngine.findOne(selector) : null\n },\n\n getMultipleElementsFromSelector(element) {\n const selector = getSelector(element)\n\n return selector ? SelectorEngine.find(selector) : []\n }\n}\n\nexport default SelectorEngine\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/component-functions.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport EventHandler from '../dom/event-handler.js'\nimport SelectorEngine from '../dom/selector-engine.js'\nimport { isDisabled } from './index.js'\n\nconst enableDismissTrigger = (component, method = 'hide') => {\n const clickEvent = `click.dismiss${component.EVENT_KEY}`\n const name = component.NAME\n\n EventHandler.on(document, clickEvent, `[data-bs-dismiss=\"${name}\"]`, function (event) {\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault()\n }\n\n if (isDisabled(this)) {\n return\n }\n\n const target = SelectorEngine.getElementFromSelector(this) || this.closest(`.${name}`)\n const instance = component.getOrCreateInstance(target)\n\n // Method argument is left, for Alert and only, as it doesn't implement the 'hide' method\n instance[method]()\n })\n}\n\nexport {\n enableDismissTrigger\n}\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap alert.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport { enableDismissTrigger } from './util/component-functions.js'\nimport { defineJQueryPlugin } from './util/index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'alert'\nconst DATA_KEY = 'bs.alert'\nconst EVENT_KEY = `.${DATA_KEY}`\n\nconst EVENT_CLOSE = `close${EVENT_KEY}`\nconst EVENT_CLOSED = `closed${EVENT_KEY}`\nconst CLASS_NAME_FADE = 'fade'\nconst CLASS_NAME_SHOW = 'show'\n\n/**\n * Class definition\n */\n\nclass Alert extends BaseComponent {\n // Getters\n static get NAME() {\n return NAME\n }\n\n // Public\n close() {\n const closeEvent = EventHandler.trigger(this._element, EVENT_CLOSE)\n\n if (closeEvent.defaultPrevented) {\n return\n }\n\n this._element.classList.remove(CLASS_NAME_SHOW)\n\n const isAnimated = this._element.classList.contains(CLASS_NAME_FADE)\n this._queueCallback(() => this._destroyElement(), this._element, isAnimated)\n }\n\n // Private\n _destroyElement() {\n this._element.remove()\n EventHandler.trigger(this._element, EVENT_CLOSED)\n this.dispose()\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Alert.getOrCreateInstance(this)\n\n if (typeof config !== 'string') {\n return\n }\n\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`)\n }\n\n data[config](this)\n })\n }\n}\n\n/**\n * Data API implementation\n */\n\nenableDismissTrigger(Alert, 'close')\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Alert)\n\nexport default Alert\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap button.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport { defineJQueryPlugin } from './util/index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'button'\nconst DATA_KEY = 'bs.button'\nconst EVENT_KEY = `.${DATA_KEY}`\nconst DATA_API_KEY = '.data-api'\n\nconst CLASS_NAME_ACTIVE = 'active'\nconst SELECTOR_DATA_TOGGLE = '[data-bs-toggle=\"button\"]'\nconst EVENT_CLICK_DATA_API = `click${EVENT_KEY}${DATA_API_KEY}`\n\n/**\n * Class definition\n */\n\nclass Button extends BaseComponent {\n // Getters\n static get NAME() {\n return NAME\n }\n\n // Public\n toggle() {\n // Toggle class and sync the `aria-pressed` attribute with the return value of the `.toggle()` method\n this._element.setAttribute('aria-pressed', this._element.classList.toggle(CLASS_NAME_ACTIVE))\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Button.getOrCreateInstance(this)\n\n if (config === 'toggle') {\n data[config]()\n }\n })\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API, SELECTOR_DATA_TOGGLE, event => {\n event.preventDefault()\n\n const button = event.target.closest(SELECTOR_DATA_TOGGLE)\n const data = Button.getOrCreateInstance(button)\n\n data.toggle()\n})\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Button)\n\nexport default Button\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/swipe.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport EventHandler from '../dom/event-handler.js'\nimport Config from './config.js'\nimport { execute } from './index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'swipe'\nconst EVENT_KEY = '.bs.swipe'\nconst EVENT_TOUCHSTART = `touchstart${EVENT_KEY}`\nconst EVENT_TOUCHMOVE = `touchmove${EVENT_KEY}`\nconst EVENT_TOUCHEND = `touchend${EVENT_KEY}`\nconst EVENT_POINTERDOWN = `pointerdown${EVENT_KEY}`\nconst EVENT_POINTERUP = `pointerup${EVENT_KEY}`\nconst POINTER_TYPE_TOUCH = 'touch'\nconst POINTER_TYPE_PEN = 'pen'\nconst CLASS_NAME_POINTER_EVENT = 'pointer-event'\nconst SWIPE_THRESHOLD = 40\n\nconst Default = {\n endCallback: null,\n leftCallback: null,\n rightCallback: null\n}\n\nconst DefaultType = {\n endCallback: '(function|null)',\n leftCallback: '(function|null)',\n rightCallback: '(function|null)'\n}\n\n/**\n * Class definition\n */\n\nclass Swipe extends Config {\n constructor(element, config) {\n super()\n this._element = element\n\n if (!element || !Swipe.isSupported()) {\n return\n }\n\n this._config = this._getConfig(config)\n this._deltaX = 0\n this._supportPointerEvents = Boolean(window.PointerEvent)\n this._initEvents()\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n dispose() {\n EventHandler.off(this._element, EVENT_KEY)\n }\n\n // Private\n _start(event) {\n if (!this._supportPointerEvents) {\n this._deltaX = event.touches[0].clientX\n\n return\n }\n\n if (this._eventIsPointerPenTouch(event)) {\n this._deltaX = event.clientX\n }\n }\n\n _end(event) {\n if (this._eventIsPointerPenTouch(event)) {\n this._deltaX = event.clientX - this._deltaX\n }\n\n this._handleSwipe()\n execute(this._config.endCallback)\n }\n\n _move(event) {\n this._deltaX = event.touches && event.touches.length > 1 ?\n 0 :\n event.touches[0].clientX - this._deltaX\n }\n\n _handleSwipe() {\n const absDeltaX = Math.abs(this._deltaX)\n\n if (absDeltaX <= SWIPE_THRESHOLD) {\n return\n }\n\n const direction = absDeltaX / this._deltaX\n\n this._deltaX = 0\n\n if (!direction) {\n return\n }\n\n execute(direction > 0 ? this._config.rightCallback : this._config.leftCallback)\n }\n\n _initEvents() {\n if (this._supportPointerEvents) {\n EventHandler.on(this._element, EVENT_POINTERDOWN, event => this._start(event))\n EventHandler.on(this._element, EVENT_POINTERUP, event => this._end(event))\n\n this._element.classList.add(CLASS_NAME_POINTER_EVENT)\n } else {\n EventHandler.on(this._element, EVENT_TOUCHSTART, event => this._start(event))\n EventHandler.on(this._element, EVENT_TOUCHMOVE, event => this._move(event))\n EventHandler.on(this._element, EVENT_TOUCHEND, event => this._end(event))\n }\n }\n\n _eventIsPointerPenTouch(event) {\n return this._supportPointerEvents && (event.pointerType === POINTER_TYPE_PEN || event.pointerType === POINTER_TYPE_TOUCH)\n }\n\n // Static\n static isSupported() {\n return 'ontouchstart' in document.documentElement || navigator.maxTouchPoints > 0\n }\n}\n\nexport default Swipe\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap carousel.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport Manipulator from './dom/manipulator.js'\nimport SelectorEngine from './dom/selector-engine.js'\nimport {\n defineJQueryPlugin,\n getNextActiveElement,\n isRTL,\n isVisible,\n reflow,\n triggerTransitionEnd\n} from './util/index.js'\nimport Swipe from './util/swipe.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'carousel'\nconst DATA_KEY = 'bs.carousel'\nconst EVENT_KEY = `.${DATA_KEY}`\nconst DATA_API_KEY = '.data-api'\n\nconst ARROW_LEFT_KEY = 'ArrowLeft'\nconst ARROW_RIGHT_KEY = 'ArrowRight'\nconst TOUCHEVENT_COMPAT_WAIT = 500 // Time for mouse compat events to fire after touch\n\nconst ORDER_NEXT = 'next'\nconst ORDER_PREV = 'prev'\nconst DIRECTION_LEFT = 'left'\nconst DIRECTION_RIGHT = 'right'\n\nconst EVENT_SLIDE = `slide${EVENT_KEY}`\nconst EVENT_SLID = `slid${EVENT_KEY}`\nconst EVENT_KEYDOWN = `keydown${EVENT_KEY}`\nconst EVENT_MOUSEENTER = `mouseenter${EVENT_KEY}`\nconst EVENT_MOUSELEAVE = `mouseleave${EVENT_KEY}`\nconst EVENT_DRAG_START = `dragstart${EVENT_KEY}`\nconst EVENT_LOAD_DATA_API = `load${EVENT_KEY}${DATA_API_KEY}`\nconst EVENT_CLICK_DATA_API = `click${EVENT_KEY}${DATA_API_KEY}`\n\nconst CLASS_NAME_CAROUSEL = 'carousel'\nconst CLASS_NAME_ACTIVE = 'active'\nconst CLASS_NAME_SLIDE = 'slide'\nconst CLASS_NAME_END = 'carousel-item-end'\nconst CLASS_NAME_START = 'carousel-item-start'\nconst CLASS_NAME_NEXT = 'carousel-item-next'\nconst CLASS_NAME_PREV = 'carousel-item-prev'\n\nconst SELECTOR_ACTIVE = '.active'\nconst SELECTOR_ITEM = '.carousel-item'\nconst SELECTOR_ACTIVE_ITEM = SELECTOR_ACTIVE + SELECTOR_ITEM\nconst SELECTOR_ITEM_IMG = '.carousel-item img'\nconst SELECTOR_INDICATORS = '.carousel-indicators'\nconst SELECTOR_DATA_SLIDE = '[data-bs-slide], [data-bs-slide-to]'\nconst SELECTOR_DATA_RIDE = '[data-bs-ride=\"carousel\"]'\n\nconst KEY_TO_DIRECTION = {\n [ARROW_LEFT_KEY]: DIRECTION_RIGHT,\n [ARROW_RIGHT_KEY]: DIRECTION_LEFT\n}\n\nconst Default = {\n interval: 5000,\n keyboard: true,\n pause: 'hover',\n ride: false,\n touch: true,\n wrap: true\n}\n\nconst DefaultType = {\n interval: '(number|boolean)', // TODO:v6 remove boolean support\n keyboard: 'boolean',\n pause: '(string|boolean)',\n ride: '(boolean|string)',\n touch: 'boolean',\n wrap: 'boolean'\n}\n\n/**\n * Class definition\n */\n\nclass Carousel extends BaseComponent {\n constructor(element, config) {\n super(element, config)\n\n this._interval = null\n this._activeElement = null\n this._isSliding = false\n this.touchTimeout = null\n this._swipeHelper = null\n\n this._indicatorsElement = SelectorEngine.findOne(SELECTOR_INDICATORS, this._element)\n this._addEventListeners()\n\n if (this._config.ride === CLASS_NAME_CAROUSEL) {\n this.cycle()\n }\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n next() {\n this._slide(ORDER_NEXT)\n }\n\n nextWhenVisible() {\n // FIXME TODO use `document.visibilityState`\n // Don't call next when the page isn't visible\n // or the carousel or its parent isn't visible\n if (!document.hidden && isVisible(this._element)) {\n this.next()\n }\n }\n\n prev() {\n this._slide(ORDER_PREV)\n }\n\n pause() {\n if (this._isSliding) {\n triggerTransitionEnd(this._element)\n }\n\n this._clearInterval()\n }\n\n cycle() {\n this._clearInterval()\n this._updateInterval()\n\n this._interval = setInterval(() => this.nextWhenVisible(), this._config.interval)\n }\n\n _maybeEnableCycle() {\n if (!this._config.ride) {\n return\n }\n\n if (this._isSliding) {\n EventHandler.one(this._element, EVENT_SLID, () => this.cycle())\n return\n }\n\n this.cycle()\n }\n\n to(index) {\n const items = this._getItems()\n if (index > items.length - 1 || index < 0) {\n return\n }\n\n if (this._isSliding) {\n EventHandler.one(this._element, EVENT_SLID, () => this.to(index))\n return\n }\n\n const activeIndex = this._getItemIndex(this._getActive())\n if (activeIndex === index) {\n return\n }\n\n const order = index > activeIndex ? ORDER_NEXT : ORDER_PREV\n\n this._slide(order, items[index])\n }\n\n dispose() {\n if (this._swipeHelper) {\n this._swipeHelper.dispose()\n }\n\n super.dispose()\n }\n\n // Private\n _configAfterMerge(config) {\n config.defaultInterval = config.interval\n return config\n }\n\n _addEventListeners() {\n if (this._config.keyboard) {\n EventHandler.on(this._element, EVENT_KEYDOWN, event => this._keydown(event))\n }\n\n if (this._config.pause === 'hover') {\n EventHandler.on(this._element, EVENT_MOUSEENTER, () => this.pause())\n EventHandler.on(this._element, EVENT_MOUSELEAVE, () => this._maybeEnableCycle())\n }\n\n if (this._config.touch && Swipe.isSupported()) {\n this._addTouchEventListeners()\n }\n }\n\n _addTouchEventListeners() {\n for (const img of SelectorEngine.find(SELECTOR_ITEM_IMG, this._element)) {\n EventHandler.on(img, EVENT_DRAG_START, event => event.preventDefault())\n }\n\n const endCallBack = () => {\n if (this._config.pause !== 'hover') {\n return\n }\n\n // If it's a touch-enabled device, mouseenter/leave are fired as\n // part of the mouse compatibility events on first tap - the carousel\n // would stop cycling until user tapped out of it;\n // here, we listen for touchend, explicitly pause the carousel\n // (as if it's the second time we tap on it, mouseenter compat event\n // is NOT fired) and after a timeout (to allow for mouse compatibility\n // events to fire) we explicitly restart cycling\n\n this.pause()\n if (this.touchTimeout) {\n clearTimeout(this.touchTimeout)\n }\n\n this.touchTimeout = setTimeout(() => this._maybeEnableCycle(), TOUCHEVENT_COMPAT_WAIT + this._config.interval)\n }\n\n const swipeConfig = {\n leftCallback: () => this._slide(this._directionToOrder(DIRECTION_LEFT)),\n rightCallback: () => this._slide(this._directionToOrder(DIRECTION_RIGHT)),\n endCallback: endCallBack\n }\n\n this._swipeHelper = new Swipe(this._element, swipeConfig)\n }\n\n _keydown(event) {\n if (/input|textarea/i.test(event.target.tagName)) {\n return\n }\n\n const direction = KEY_TO_DIRECTION[event.key]\n if (direction) {\n event.preventDefault()\n this._slide(this._directionToOrder(direction))\n }\n }\n\n _getItemIndex(element) {\n return this._getItems().indexOf(element)\n }\n\n _setActiveIndicatorElement(index) {\n if (!this._indicatorsElement) {\n return\n }\n\n const activeIndicator = SelectorEngine.findOne(SELECTOR_ACTIVE, this._indicatorsElement)\n\n activeIndicator.classList.remove(CLASS_NAME_ACTIVE)\n activeIndicator.removeAttribute('aria-current')\n\n const newActiveIndicator = SelectorEngine.findOne(`[data-bs-slide-to=\"${index}\"]`, this._indicatorsElement)\n\n if (newActiveIndicator) {\n newActiveIndicator.classList.add(CLASS_NAME_ACTIVE)\n newActiveIndicator.setAttribute('aria-current', 'true')\n }\n }\n\n _updateInterval() {\n const element = this._activeElement || this._getActive()\n\n if (!element) {\n return\n }\n\n const elementInterval = Number.parseInt(element.getAttribute('data-bs-interval'), 10)\n\n this._config.interval = elementInterval || this._config.defaultInterval\n }\n\n _slide(order, element = null) {\n if (this._isSliding) {\n return\n }\n\n const activeElement = this._getActive()\n const isNext = order === ORDER_NEXT\n const nextElement = element || getNextActiveElement(this._getItems(), activeElement, isNext, this._config.wrap)\n\n if (nextElement === activeElement) {\n return\n }\n\n const nextElementIndex = this._getItemIndex(nextElement)\n\n const triggerEvent = eventName => {\n return EventHandler.trigger(this._element, eventName, {\n relatedTarget: nextElement,\n direction: this._orderToDirection(order),\n from: this._getItemIndex(activeElement),\n to: nextElementIndex\n })\n }\n\n const slideEvent = triggerEvent(EVENT_SLIDE)\n\n if (slideEvent.defaultPrevented) {\n return\n }\n\n if (!activeElement || !nextElement) {\n // Some weirdness is happening, so we bail\n // TODO: change tests that use empty divs to avoid this check\n return\n }\n\n const isCycling = Boolean(this._interval)\n this.pause()\n\n this._isSliding = true\n\n this._setActiveIndicatorElement(nextElementIndex)\n this._activeElement = nextElement\n\n const directionalClassName = isNext ? CLASS_NAME_START : CLASS_NAME_END\n const orderClassName = isNext ? CLASS_NAME_NEXT : CLASS_NAME_PREV\n\n nextElement.classList.add(orderClassName)\n\n reflow(nextElement)\n\n activeElement.classList.add(directionalClassName)\n nextElement.classList.add(directionalClassName)\n\n const completeCallBack = () => {\n nextElement.classList.remove(directionalClassName, orderClassName)\n nextElement.classList.add(CLASS_NAME_ACTIVE)\n\n activeElement.classList.remove(CLASS_NAME_ACTIVE, orderClassName, directionalClassName)\n\n this._isSliding = false\n\n triggerEvent(EVENT_SLID)\n }\n\n this._queueCallback(completeCallBack, activeElement, this._isAnimated())\n\n if (isCycling) {\n this.cycle()\n }\n }\n\n _isAnimated() {\n return this._element.classList.contains(CLASS_NAME_SLIDE)\n }\n\n _getActive() {\n return SelectorEngine.findOne(SELECTOR_ACTIVE_ITEM, this._element)\n }\n\n _getItems() {\n return SelectorEngine.find(SELECTOR_ITEM, this._element)\n }\n\n _clearInterval() {\n if (this._interval) {\n clearInterval(this._interval)\n this._interval = null\n }\n }\n\n _directionToOrder(direction) {\n if (isRTL()) {\n return direction === DIRECTION_LEFT ? ORDER_PREV : ORDER_NEXT\n }\n\n return direction === DIRECTION_LEFT ? ORDER_NEXT : ORDER_PREV\n }\n\n _orderToDirection(order) {\n if (isRTL()) {\n return order === ORDER_PREV ? DIRECTION_LEFT : DIRECTION_RIGHT\n }\n\n return order === ORDER_PREV ? DIRECTION_RIGHT : DIRECTION_LEFT\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Carousel.getOrCreateInstance(this, config)\n\n if (typeof config === 'number') {\n data.to(config)\n return\n }\n\n if (typeof config === 'string') {\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`)\n }\n\n data[config]()\n }\n })\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API, SELECTOR_DATA_SLIDE, function (event) {\n const target = SelectorEngine.getElementFromSelector(this)\n\n if (!target || !target.classList.contains(CLASS_NAME_CAROUSEL)) {\n return\n }\n\n event.preventDefault()\n\n const carousel = Carousel.getOrCreateInstance(target)\n const slideIndex = this.getAttribute('data-bs-slide-to')\n\n if (slideIndex) {\n carousel.to(slideIndex)\n carousel._maybeEnableCycle()\n return\n }\n\n if (Manipulator.getDataAttribute(this, 'slide') === 'next') {\n carousel.next()\n carousel._maybeEnableCycle()\n return\n }\n\n carousel.prev()\n carousel._maybeEnableCycle()\n})\n\nEventHandler.on(window, EVENT_LOAD_DATA_API, () => {\n const carousels = SelectorEngine.find(SELECTOR_DATA_RIDE)\n\n for (const carousel of carousels) {\n Carousel.getOrCreateInstance(carousel)\n }\n})\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Carousel)\n\nexport default Carousel\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap collapse.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport SelectorEngine from './dom/selector-engine.js'\nimport {\n defineJQueryPlugin,\n getElement,\n reflow\n} from './util/index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'collapse'\nconst DATA_KEY = 'bs.collapse'\nconst EVENT_KEY = `.${DATA_KEY}`\nconst DATA_API_KEY = '.data-api'\n\nconst EVENT_SHOW = `show${EVENT_KEY}`\nconst EVENT_SHOWN = `shown${EVENT_KEY}`\nconst EVENT_HIDE = `hide${EVENT_KEY}`\nconst EVENT_HIDDEN = `hidden${EVENT_KEY}`\nconst EVENT_CLICK_DATA_API = `click${EVENT_KEY}${DATA_API_KEY}`\n\nconst CLASS_NAME_SHOW = 'show'\nconst CLASS_NAME_COLLAPSE = 'collapse'\nconst CLASS_NAME_COLLAPSING = 'collapsing'\nconst CLASS_NAME_COLLAPSED = 'collapsed'\nconst CLASS_NAME_DEEPER_CHILDREN = `:scope .${CLASS_NAME_COLLAPSE} .${CLASS_NAME_COLLAPSE}`\nconst CLASS_NAME_HORIZONTAL = 'collapse-horizontal'\n\nconst WIDTH = 'width'\nconst HEIGHT = 'height'\n\nconst SELECTOR_ACTIVES = '.collapse.show, .collapse.collapsing'\nconst SELECTOR_DATA_TOGGLE = '[data-bs-toggle=\"collapse\"]'\n\nconst Default = {\n parent: null,\n toggle: true\n}\n\nconst DefaultType = {\n parent: '(null|element)',\n toggle: 'boolean'\n}\n\n/**\n * Class definition\n */\n\nclass Collapse extends BaseComponent {\n constructor(element, config) {\n super(element, config)\n\n this._isTransitioning = false\n this._triggerArray = []\n\n const toggleList = SelectorEngine.find(SELECTOR_DATA_TOGGLE)\n\n for (const elem of toggleList) {\n const selector = SelectorEngine.getSelectorFromElement(elem)\n const filterElement = SelectorEngine.find(selector)\n .filter(foundElement => foundElement === this._element)\n\n if (selector !== null && filterElement.length) {\n this._triggerArray.push(elem)\n }\n }\n\n this._initializeChildren()\n\n if (!this._config.parent) {\n this._addAriaAndCollapsedClass(this._triggerArray, this._isShown())\n }\n\n if (this._config.toggle) {\n this.toggle()\n }\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n toggle() {\n if (this._isShown()) {\n this.hide()\n } else {\n this.show()\n }\n }\n\n show() {\n if (this._isTransitioning || this._isShown()) {\n return\n }\n\n let activeChildren = []\n\n // find active children\n if (this._config.parent) {\n activeChildren = this._getFirstLevelChildren(SELECTOR_ACTIVES)\n .filter(element => element !== this._element)\n .map(element => Collapse.getOrCreateInstance(element, { toggle: false }))\n }\n\n if (activeChildren.length && activeChildren[0]._isTransitioning) {\n return\n }\n\n const startEvent = EventHandler.trigger(this._element, EVENT_SHOW)\n if (startEvent.defaultPrevented) {\n return\n }\n\n for (const activeInstance of activeChildren) {\n activeInstance.hide()\n }\n\n const dimension = this._getDimension()\n\n this._element.classList.remove(CLASS_NAME_COLLAPSE)\n this._element.classList.add(CLASS_NAME_COLLAPSING)\n\n this._element.style[dimension] = 0\n\n this._addAriaAndCollapsedClass(this._triggerArray, true)\n this._isTransitioning = true\n\n const complete = () => {\n this._isTransitioning = false\n\n this._element.classList.remove(CLASS_NAME_COLLAPSING)\n this._element.classList.add(CLASS_NAME_COLLAPSE, CLASS_NAME_SHOW)\n\n this._element.style[dimension] = ''\n\n EventHandler.trigger(this._element, EVENT_SHOWN)\n }\n\n const capitalizedDimension = dimension[0].toUpperCase() + dimension.slice(1)\n const scrollSize = `scroll${capitalizedDimension}`\n\n this._queueCallback(complete, this._element, true)\n this._element.style[dimension] = `${this._element[scrollSize]}px`\n }\n\n hide() {\n if (this._isTransitioning || !this._isShown()) {\n return\n }\n\n const startEvent = EventHandler.trigger(this._element, EVENT_HIDE)\n if (startEvent.defaultPrevented) {\n return\n }\n\n const dimension = this._getDimension()\n\n this._element.style[dimension] = `${this._element.getBoundingClientRect()[dimension]}px`\n\n reflow(this._element)\n\n this._element.classList.add(CLASS_NAME_COLLAPSING)\n this._element.classList.remove(CLASS_NAME_COLLAPSE, CLASS_NAME_SHOW)\n\n for (const trigger of this._triggerArray) {\n const element = SelectorEngine.getElementFromSelector(trigger)\n\n if (element && !this._isShown(element)) {\n this._addAriaAndCollapsedClass([trigger], false)\n }\n }\n\n this._isTransitioning = true\n\n const complete = () => {\n this._isTransitioning = false\n this._element.classList.remove(CLASS_NAME_COLLAPSING)\n this._element.classList.add(CLASS_NAME_COLLAPSE)\n EventHandler.trigger(this._element, EVENT_HIDDEN)\n }\n\n this._element.style[dimension] = ''\n\n this._queueCallback(complete, this._element, true)\n }\n\n _isShown(element = this._element) {\n return element.classList.contains(CLASS_NAME_SHOW)\n }\n\n // Private\n _configAfterMerge(config) {\n config.toggle = Boolean(config.toggle) // Coerce string values\n config.parent = getElement(config.parent)\n return config\n }\n\n _getDimension() {\n return this._element.classList.contains(CLASS_NAME_HORIZONTAL) ? WIDTH : HEIGHT\n }\n\n _initializeChildren() {\n if (!this._config.parent) {\n return\n }\n\n const children = this._getFirstLevelChildren(SELECTOR_DATA_TOGGLE)\n\n for (const element of children) {\n const selected = SelectorEngine.getElementFromSelector(element)\n\n if (selected) {\n this._addAriaAndCollapsedClass([element], this._isShown(selected))\n }\n }\n }\n\n _getFirstLevelChildren(selector) {\n const children = SelectorEngine.find(CLASS_NAME_DEEPER_CHILDREN, this._config.parent)\n // remove children if greater depth\n return SelectorEngine.find(selector, this._config.parent).filter(element => !children.includes(element))\n }\n\n _addAriaAndCollapsedClass(triggerArray, isOpen) {\n if (!triggerArray.length) {\n return\n }\n\n for (const element of triggerArray) {\n element.classList.toggle(CLASS_NAME_COLLAPSED, !isOpen)\n element.setAttribute('aria-expanded', isOpen)\n }\n }\n\n // Static\n static jQueryInterface(config) {\n const _config = {}\n if (typeof config === 'string' && /show|hide/.test(config)) {\n _config.toggle = false\n }\n\n return this.each(function () {\n const data = Collapse.getOrCreateInstance(this, _config)\n\n if (typeof config === 'string') {\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`)\n }\n\n data[config]()\n }\n })\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API, SELECTOR_DATA_TOGGLE, function (event) {\n // preventDefault only for elements (which change the URL) not inside the collapsible element\n if (event.target.tagName === 'A' || (event.delegateTarget && event.delegateTarget.tagName === 'A')) {\n event.preventDefault()\n }\n\n for (const element of SelectorEngine.getMultipleElementsFromSelector(this)) {\n Collapse.getOrCreateInstance(element, { toggle: false }).toggle()\n }\n})\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Collapse)\n\nexport default Collapse\n","export var top = 'top';\nexport var bottom = 'bottom';\nexport var right = 'right';\nexport var left = 'left';\nexport var auto = 'auto';\nexport var basePlacements = [top, bottom, right, left];\nexport var start = 'start';\nexport var end = 'end';\nexport var clippingParents = 'clippingParents';\nexport var viewport = 'viewport';\nexport var popper = 'popper';\nexport var reference = 'reference';\nexport var variationPlacements = /*#__PURE__*/basePlacements.reduce(function (acc, placement) {\n return acc.concat([placement + \"-\" + start, placement + \"-\" + end]);\n}, []);\nexport var placements = /*#__PURE__*/[].concat(basePlacements, [auto]).reduce(function (acc, placement) {\n return acc.concat([placement, placement + \"-\" + start, placement + \"-\" + end]);\n}, []); // modifiers that need to read the DOM\n\nexport var beforeRead = 'beforeRead';\nexport var read = 'read';\nexport var afterRead = 'afterRead'; // pure-logic modifiers\n\nexport var beforeMain = 'beforeMain';\nexport var main = 'main';\nexport var afterMain = 'afterMain'; // modifier with the purpose to write to the DOM (or write into a framework state)\n\nexport var beforeWrite = 'beforeWrite';\nexport var write = 'write';\nexport var afterWrite = 'afterWrite';\nexport var modifierPhases = [beforeRead, read, afterRead, beforeMain, main, afterMain, beforeWrite, write, afterWrite];","export default function getNodeName(element) {\n return element ? (element.nodeName || '').toLowerCase() : null;\n}","export default function getWindow(node) {\n if (node == null) {\n return window;\n }\n\n if (node.toString() !== '[object Window]') {\n var ownerDocument = node.ownerDocument;\n return ownerDocument ? ownerDocument.defaultView || window : window;\n }\n\n return node;\n}","import getWindow from \"./getWindow.js\";\n\nfunction isElement(node) {\n var OwnElement = getWindow(node).Element;\n return node instanceof OwnElement || node instanceof Element;\n}\n\nfunction isHTMLElement(node) {\n var OwnElement = getWindow(node).HTMLElement;\n return node instanceof OwnElement || node instanceof HTMLElement;\n}\n\nfunction isShadowRoot(node) {\n // IE 11 has no ShadowRoot\n if (typeof ShadowRoot === 'undefined') {\n return false;\n }\n\n var OwnElement = getWindow(node).ShadowRoot;\n return node instanceof OwnElement || node instanceof ShadowRoot;\n}\n\nexport { isElement, isHTMLElement, isShadowRoot };","import getNodeName from \"../dom-utils/getNodeName.js\";\nimport { isHTMLElement } from \"../dom-utils/instanceOf.js\"; // This modifier takes the styles prepared by the `computeStyles` modifier\n// and applies them to the HTMLElements such as popper and arrow\n\nfunction applyStyles(_ref) {\n var state = _ref.state;\n Object.keys(state.elements).forEach(function (name) {\n var style = state.styles[name] || {};\n var attributes = state.attributes[name] || {};\n var element = state.elements[name]; // arrow is optional + virtual elements\n\n if (!isHTMLElement(element) || !getNodeName(element)) {\n return;\n } // Flow doesn't support to extend this property, but it's the most\n // effective way to apply styles to an HTMLElement\n // $FlowFixMe[cannot-write]\n\n\n Object.assign(element.style, style);\n Object.keys(attributes).forEach(function (name) {\n var value = attributes[name];\n\n if (value === false) {\n element.removeAttribute(name);\n } else {\n element.setAttribute(name, value === true ? '' : value);\n }\n });\n });\n}\n\nfunction effect(_ref2) {\n var state = _ref2.state;\n var initialStyles = {\n popper: {\n position: state.options.strategy,\n left: '0',\n top: '0',\n margin: '0'\n },\n arrow: {\n position: 'absolute'\n },\n reference: {}\n };\n Object.assign(state.elements.popper.style, initialStyles.popper);\n state.styles = initialStyles;\n\n if (state.elements.arrow) {\n Object.assign(state.elements.arrow.style, initialStyles.arrow);\n }\n\n return function () {\n Object.keys(state.elements).forEach(function (name) {\n var element = state.elements[name];\n var attributes = state.attributes[name] || {};\n var styleProperties = Object.keys(state.styles.hasOwnProperty(name) ? state.styles[name] : initialStyles[name]); // Set all values to an empty string to unset them\n\n var style = styleProperties.reduce(function (style, property) {\n style[property] = '';\n return style;\n }, {}); // arrow is optional + virtual elements\n\n if (!isHTMLElement(element) || !getNodeName(element)) {\n return;\n }\n\n Object.assign(element.style, style);\n Object.keys(attributes).forEach(function (attribute) {\n element.removeAttribute(attribute);\n });\n });\n };\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'applyStyles',\n enabled: true,\n phase: 'write',\n fn: applyStyles,\n effect: effect,\n requires: ['computeStyles']\n};","import { auto } from \"../enums.js\";\nexport default function getBasePlacement(placement) {\n return placement.split('-')[0];\n}","export var max = Math.max;\nexport var min = Math.min;\nexport var round = Math.round;","export default function getUAString() {\n var uaData = navigator.userAgentData;\n\n if (uaData != null && uaData.brands && Array.isArray(uaData.brands)) {\n return uaData.brands.map(function (item) {\n return item.brand + \"/\" + item.version;\n }).join(' ');\n }\n\n return navigator.userAgent;\n}","import getUAString from \"../utils/userAgent.js\";\nexport default function isLayoutViewport() {\n return !/^((?!chrome|android).)*safari/i.test(getUAString());\n}","import { isElement, isHTMLElement } from \"./instanceOf.js\";\nimport { round } from \"../utils/math.js\";\nimport getWindow from \"./getWindow.js\";\nimport isLayoutViewport from \"./isLayoutViewport.js\";\nexport default function getBoundingClientRect(element, includeScale, isFixedStrategy) {\n if (includeScale === void 0) {\n includeScale = false;\n }\n\n if (isFixedStrategy === void 0) {\n isFixedStrategy = false;\n }\n\n var clientRect = element.getBoundingClientRect();\n var scaleX = 1;\n var scaleY = 1;\n\n if (includeScale && isHTMLElement(element)) {\n scaleX = element.offsetWidth > 0 ? round(clientRect.width) / element.offsetWidth || 1 : 1;\n scaleY = element.offsetHeight > 0 ? round(clientRect.height) / element.offsetHeight || 1 : 1;\n }\n\n var _ref = isElement(element) ? getWindow(element) : window,\n visualViewport = _ref.visualViewport;\n\n var addVisualOffsets = !isLayoutViewport() && isFixedStrategy;\n var x = (clientRect.left + (addVisualOffsets && visualViewport ? visualViewport.offsetLeft : 0)) / scaleX;\n var y = (clientRect.top + (addVisualOffsets && visualViewport ? visualViewport.offsetTop : 0)) / scaleY;\n var width = clientRect.width / scaleX;\n var height = clientRect.height / scaleY;\n return {\n width: width,\n height: height,\n top: y,\n right: x + width,\n bottom: y + height,\n left: x,\n x: x,\n y: y\n };\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\"; // Returns the layout rect of an element relative to its offsetParent. Layout\n// means it doesn't take into account transforms.\n\nexport default function getLayoutRect(element) {\n var clientRect = getBoundingClientRect(element); // Use the clientRect sizes if it's not been transformed.\n // Fixes https://github.com/popperjs/popper-core/issues/1223\n\n var width = element.offsetWidth;\n var height = element.offsetHeight;\n\n if (Math.abs(clientRect.width - width) <= 1) {\n width = clientRect.width;\n }\n\n if (Math.abs(clientRect.height - height) <= 1) {\n height = clientRect.height;\n }\n\n return {\n x: element.offsetLeft,\n y: element.offsetTop,\n width: width,\n height: height\n };\n}","import { isShadowRoot } from \"./instanceOf.js\";\nexport default function contains(parent, child) {\n var rootNode = child.getRootNode && child.getRootNode(); // First, attempt with faster native method\n\n if (parent.contains(child)) {\n return true;\n } // then fallback to custom implementation with Shadow DOM support\n else if (rootNode && isShadowRoot(rootNode)) {\n var next = child;\n\n do {\n if (next && parent.isSameNode(next)) {\n return true;\n } // $FlowFixMe[prop-missing]: need a better way to handle this...\n\n\n next = next.parentNode || next.host;\n } while (next);\n } // Give up, the result is false\n\n\n return false;\n}","import getWindow from \"./getWindow.js\";\nexport default function getComputedStyle(element) {\n return getWindow(element).getComputedStyle(element);\n}","import getNodeName from \"./getNodeName.js\";\nexport default function isTableElement(element) {\n return ['table', 'td', 'th'].indexOf(getNodeName(element)) >= 0;\n}","import { isElement } from \"./instanceOf.js\";\nexport default function getDocumentElement(element) {\n // $FlowFixMe[incompatible-return]: assume body is always available\n return ((isElement(element) ? element.ownerDocument : // $FlowFixMe[prop-missing]\n element.document) || window.document).documentElement;\n}","import getNodeName from \"./getNodeName.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport { isShadowRoot } from \"./instanceOf.js\";\nexport default function getParentNode(element) {\n if (getNodeName(element) === 'html') {\n return element;\n }\n\n return (// this is a quicker (but less type safe) way to save quite some bytes from the bundle\n // $FlowFixMe[incompatible-return]\n // $FlowFixMe[prop-missing]\n element.assignedSlot || // step into the shadow DOM of the parent of a slotted node\n element.parentNode || ( // DOM Element detected\n isShadowRoot(element) ? element.host : null) || // ShadowRoot detected\n // $FlowFixMe[incompatible-call]: HTMLElement is a Node\n getDocumentElement(element) // fallback\n\n );\n}","import getWindow from \"./getWindow.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport { isHTMLElement, isShadowRoot } from \"./instanceOf.js\";\nimport isTableElement from \"./isTableElement.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport getUAString from \"../utils/userAgent.js\";\n\nfunction getTrueOffsetParent(element) {\n if (!isHTMLElement(element) || // https://github.com/popperjs/popper-core/issues/837\n getComputedStyle(element).position === 'fixed') {\n return null;\n }\n\n return element.offsetParent;\n} // `.offsetParent` reports `null` for fixed elements, while absolute elements\n// return the containing block\n\n\nfunction getContainingBlock(element) {\n var isFirefox = /firefox/i.test(getUAString());\n var isIE = /Trident/i.test(getUAString());\n\n if (isIE && isHTMLElement(element)) {\n // In IE 9, 10 and 11 fixed elements containing block is always established by the viewport\n var elementCss = getComputedStyle(element);\n\n if (elementCss.position === 'fixed') {\n return null;\n }\n }\n\n var currentNode = getParentNode(element);\n\n if (isShadowRoot(currentNode)) {\n currentNode = currentNode.host;\n }\n\n while (isHTMLElement(currentNode) && ['html', 'body'].indexOf(getNodeName(currentNode)) < 0) {\n var css = getComputedStyle(currentNode); // This is non-exhaustive but covers the most common CSS properties that\n // create a containing block.\n // https://developer.mozilla.org/en-US/docs/Web/CSS/Containing_block#identifying_the_containing_block\n\n if (css.transform !== 'none' || css.perspective !== 'none' || css.contain === 'paint' || ['transform', 'perspective'].indexOf(css.willChange) !== -1 || isFirefox && css.willChange === 'filter' || isFirefox && css.filter && css.filter !== 'none') {\n return currentNode;\n } else {\n currentNode = currentNode.parentNode;\n }\n }\n\n return null;\n} // Gets the closest ancestor positioned element. Handles some edge cases,\n// such as table ancestors and cross browser bugs.\n\n\nexport default function getOffsetParent(element) {\n var window = getWindow(element);\n var offsetParent = getTrueOffsetParent(element);\n\n while (offsetParent && isTableElement(offsetParent) && getComputedStyle(offsetParent).position === 'static') {\n offsetParent = getTrueOffsetParent(offsetParent);\n }\n\n if (offsetParent && (getNodeName(offsetParent) === 'html' || getNodeName(offsetParent) === 'body' && getComputedStyle(offsetParent).position === 'static')) {\n return window;\n }\n\n return offsetParent || getContainingBlock(element) || window;\n}","export default function getMainAxisFromPlacement(placement) {\n return ['top', 'bottom'].indexOf(placement) >= 0 ? 'x' : 'y';\n}","import { max as mathMax, min as mathMin } from \"./math.js\";\nexport function within(min, value, max) {\n return mathMax(min, mathMin(value, max));\n}\nexport function withinMaxClamp(min, value, max) {\n var v = within(min, value, max);\n return v > max ? max : v;\n}","import getFreshSideObject from \"./getFreshSideObject.js\";\nexport default function mergePaddingObject(paddingObject) {\n return Object.assign({}, getFreshSideObject(), paddingObject);\n}","export default function getFreshSideObject() {\n return {\n top: 0,\n right: 0,\n bottom: 0,\n left: 0\n };\n}","export default function expandToHashMap(value, keys) {\n return keys.reduce(function (hashMap, key) {\n hashMap[key] = value;\n return hashMap;\n }, {});\n}","import getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getLayoutRect from \"../dom-utils/getLayoutRect.js\";\nimport contains from \"../dom-utils/contains.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport getMainAxisFromPlacement from \"../utils/getMainAxisFromPlacement.js\";\nimport { within } from \"../utils/within.js\";\nimport mergePaddingObject from \"../utils/mergePaddingObject.js\";\nimport expandToHashMap from \"../utils/expandToHashMap.js\";\nimport { left, right, basePlacements, top, bottom } from \"../enums.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar toPaddingObject = function toPaddingObject(padding, state) {\n padding = typeof padding === 'function' ? padding(Object.assign({}, state.rects, {\n placement: state.placement\n })) : padding;\n return mergePaddingObject(typeof padding !== 'number' ? padding : expandToHashMap(padding, basePlacements));\n};\n\nfunction arrow(_ref) {\n var _state$modifiersData$;\n\n var state = _ref.state,\n name = _ref.name,\n options = _ref.options;\n var arrowElement = state.elements.arrow;\n var popperOffsets = state.modifiersData.popperOffsets;\n var basePlacement = getBasePlacement(state.placement);\n var axis = getMainAxisFromPlacement(basePlacement);\n var isVertical = [left, right].indexOf(basePlacement) >= 0;\n var len = isVertical ? 'height' : 'width';\n\n if (!arrowElement || !popperOffsets) {\n return;\n }\n\n var paddingObject = toPaddingObject(options.padding, state);\n var arrowRect = getLayoutRect(arrowElement);\n var minProp = axis === 'y' ? top : left;\n var maxProp = axis === 'y' ? bottom : right;\n var endDiff = state.rects.reference[len] + state.rects.reference[axis] - popperOffsets[axis] - state.rects.popper[len];\n var startDiff = popperOffsets[axis] - state.rects.reference[axis];\n var arrowOffsetParent = getOffsetParent(arrowElement);\n var clientSize = arrowOffsetParent ? axis === 'y' ? arrowOffsetParent.clientHeight || 0 : arrowOffsetParent.clientWidth || 0 : 0;\n var centerToReference = endDiff / 2 - startDiff / 2; // Make sure the arrow doesn't overflow the popper if the center point is\n // outside of the popper bounds\n\n var min = paddingObject[minProp];\n var max = clientSize - arrowRect[len] - paddingObject[maxProp];\n var center = clientSize / 2 - arrowRect[len] / 2 + centerToReference;\n var offset = within(min, center, max); // Prevents breaking syntax highlighting...\n\n var axisProp = axis;\n state.modifiersData[name] = (_state$modifiersData$ = {}, _state$modifiersData$[axisProp] = offset, _state$modifiersData$.centerOffset = offset - center, _state$modifiersData$);\n}\n\nfunction effect(_ref2) {\n var state = _ref2.state,\n options = _ref2.options;\n var _options$element = options.element,\n arrowElement = _options$element === void 0 ? '[data-popper-arrow]' : _options$element;\n\n if (arrowElement == null) {\n return;\n } // CSS selector\n\n\n if (typeof arrowElement === 'string') {\n arrowElement = state.elements.popper.querySelector(arrowElement);\n\n if (!arrowElement) {\n return;\n }\n }\n\n if (!contains(state.elements.popper, arrowElement)) {\n return;\n }\n\n state.elements.arrow = arrowElement;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'arrow',\n enabled: true,\n phase: 'main',\n fn: arrow,\n effect: effect,\n requires: ['popperOffsets'],\n requiresIfExists: ['preventOverflow']\n};","export default function getVariation(placement) {\n return placement.split('-')[1];\n}","import { top, left, right, bottom, end } from \"../enums.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport getWindow from \"../dom-utils/getWindow.js\";\nimport getDocumentElement from \"../dom-utils/getDocumentElement.js\";\nimport getComputedStyle from \"../dom-utils/getComputedStyle.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getVariation from \"../utils/getVariation.js\";\nimport { round } from \"../utils/math.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar unsetSides = {\n top: 'auto',\n right: 'auto',\n bottom: 'auto',\n left: 'auto'\n}; // Round the offsets to the nearest suitable subpixel based on the DPR.\n// Zooming can change the DPR, but it seems to report a value that will\n// cleanly divide the values into the appropriate subpixels.\n\nfunction roundOffsetsByDPR(_ref, win) {\n var x = _ref.x,\n y = _ref.y;\n var dpr = win.devicePixelRatio || 1;\n return {\n x: round(x * dpr) / dpr || 0,\n y: round(y * dpr) / dpr || 0\n };\n}\n\nexport function mapToStyles(_ref2) {\n var _Object$assign2;\n\n var popper = _ref2.popper,\n popperRect = _ref2.popperRect,\n placement = _ref2.placement,\n variation = _ref2.variation,\n offsets = _ref2.offsets,\n position = _ref2.position,\n gpuAcceleration = _ref2.gpuAcceleration,\n adaptive = _ref2.adaptive,\n roundOffsets = _ref2.roundOffsets,\n isFixed = _ref2.isFixed;\n var _offsets$x = offsets.x,\n x = _offsets$x === void 0 ? 0 : _offsets$x,\n _offsets$y = offsets.y,\n y = _offsets$y === void 0 ? 0 : _offsets$y;\n\n var _ref3 = typeof roundOffsets === 'function' ? roundOffsets({\n x: x,\n y: y\n }) : {\n x: x,\n y: y\n };\n\n x = _ref3.x;\n y = _ref3.y;\n var hasX = offsets.hasOwnProperty('x');\n var hasY = offsets.hasOwnProperty('y');\n var sideX = left;\n var sideY = top;\n var win = window;\n\n if (adaptive) {\n var offsetParent = getOffsetParent(popper);\n var heightProp = 'clientHeight';\n var widthProp = 'clientWidth';\n\n if (offsetParent === getWindow(popper)) {\n offsetParent = getDocumentElement(popper);\n\n if (getComputedStyle(offsetParent).position !== 'static' && position === 'absolute') {\n heightProp = 'scrollHeight';\n widthProp = 'scrollWidth';\n }\n } // $FlowFixMe[incompatible-cast]: force type refinement, we compare offsetParent with window above, but Flow doesn't detect it\n\n\n offsetParent = offsetParent;\n\n if (placement === top || (placement === left || placement === right) && variation === end) {\n sideY = bottom;\n var offsetY = isFixed && offsetParent === win && win.visualViewport ? win.visualViewport.height : // $FlowFixMe[prop-missing]\n offsetParent[heightProp];\n y -= offsetY - popperRect.height;\n y *= gpuAcceleration ? 1 : -1;\n }\n\n if (placement === left || (placement === top || placement === bottom) && variation === end) {\n sideX = right;\n var offsetX = isFixed && offsetParent === win && win.visualViewport ? win.visualViewport.width : // $FlowFixMe[prop-missing]\n offsetParent[widthProp];\n x -= offsetX - popperRect.width;\n x *= gpuAcceleration ? 1 : -1;\n }\n }\n\n var commonStyles = Object.assign({\n position: position\n }, adaptive && unsetSides);\n\n var _ref4 = roundOffsets === true ? roundOffsetsByDPR({\n x: x,\n y: y\n }, getWindow(popper)) : {\n x: x,\n y: y\n };\n\n x = _ref4.x;\n y = _ref4.y;\n\n if (gpuAcceleration) {\n var _Object$assign;\n\n return Object.assign({}, commonStyles, (_Object$assign = {}, _Object$assign[sideY] = hasY ? '0' : '', _Object$assign[sideX] = hasX ? '0' : '', _Object$assign.transform = (win.devicePixelRatio || 1) <= 1 ? \"translate(\" + x + \"px, \" + y + \"px)\" : \"translate3d(\" + x + \"px, \" + y + \"px, 0)\", _Object$assign));\n }\n\n return Object.assign({}, commonStyles, (_Object$assign2 = {}, _Object$assign2[sideY] = hasY ? y + \"px\" : '', _Object$assign2[sideX] = hasX ? x + \"px\" : '', _Object$assign2.transform = '', _Object$assign2));\n}\n\nfunction computeStyles(_ref5) {\n var state = _ref5.state,\n options = _ref5.options;\n var _options$gpuAccelerat = options.gpuAcceleration,\n gpuAcceleration = _options$gpuAccelerat === void 0 ? true : _options$gpuAccelerat,\n _options$adaptive = options.adaptive,\n adaptive = _options$adaptive === void 0 ? true : _options$adaptive,\n _options$roundOffsets = options.roundOffsets,\n roundOffsets = _options$roundOffsets === void 0 ? true : _options$roundOffsets;\n var commonStyles = {\n placement: getBasePlacement(state.placement),\n variation: getVariation(state.placement),\n popper: state.elements.popper,\n popperRect: state.rects.popper,\n gpuAcceleration: gpuAcceleration,\n isFixed: state.options.strategy === 'fixed'\n };\n\n if (state.modifiersData.popperOffsets != null) {\n state.styles.popper = Object.assign({}, state.styles.popper, mapToStyles(Object.assign({}, commonStyles, {\n offsets: state.modifiersData.popperOffsets,\n position: state.options.strategy,\n adaptive: adaptive,\n roundOffsets: roundOffsets\n })));\n }\n\n if (state.modifiersData.arrow != null) {\n state.styles.arrow = Object.assign({}, state.styles.arrow, mapToStyles(Object.assign({}, commonStyles, {\n offsets: state.modifiersData.arrow,\n position: 'absolute',\n adaptive: false,\n roundOffsets: roundOffsets\n })));\n }\n\n state.attributes.popper = Object.assign({}, state.attributes.popper, {\n 'data-popper-placement': state.placement\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'computeStyles',\n enabled: true,\n phase: 'beforeWrite',\n fn: computeStyles,\n data: {}\n};","import getWindow from \"../dom-utils/getWindow.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar passive = {\n passive: true\n};\n\nfunction effect(_ref) {\n var state = _ref.state,\n instance = _ref.instance,\n options = _ref.options;\n var _options$scroll = options.scroll,\n scroll = _options$scroll === void 0 ? true : _options$scroll,\n _options$resize = options.resize,\n resize = _options$resize === void 0 ? true : _options$resize;\n var window = getWindow(state.elements.popper);\n var scrollParents = [].concat(state.scrollParents.reference, state.scrollParents.popper);\n\n if (scroll) {\n scrollParents.forEach(function (scrollParent) {\n scrollParent.addEventListener('scroll', instance.update, passive);\n });\n }\n\n if (resize) {\n window.addEventListener('resize', instance.update, passive);\n }\n\n return function () {\n if (scroll) {\n scrollParents.forEach(function (scrollParent) {\n scrollParent.removeEventListener('scroll', instance.update, passive);\n });\n }\n\n if (resize) {\n window.removeEventListener('resize', instance.update, passive);\n }\n };\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'eventListeners',\n enabled: true,\n phase: 'write',\n fn: function fn() {},\n effect: effect,\n data: {}\n};","var hash = {\n left: 'right',\n right: 'left',\n bottom: 'top',\n top: 'bottom'\n};\nexport default function getOppositePlacement(placement) {\n return placement.replace(/left|right|bottom|top/g, function (matched) {\n return hash[matched];\n });\n}","var hash = {\n start: 'end',\n end: 'start'\n};\nexport default function getOppositeVariationPlacement(placement) {\n return placement.replace(/start|end/g, function (matched) {\n return hash[matched];\n });\n}","import getWindow from \"./getWindow.js\";\nexport default function getWindowScroll(node) {\n var win = getWindow(node);\n var scrollLeft = win.pageXOffset;\n var scrollTop = win.pageYOffset;\n return {\n scrollLeft: scrollLeft,\n scrollTop: scrollTop\n };\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getWindowScroll from \"./getWindowScroll.js\";\nexport default function getWindowScrollBarX(element) {\n // If has a CSS width greater than the viewport, then this will be\n // incorrect for RTL.\n // Popper 1 is broken in this case and never had a bug report so let's assume\n // it's not an issue. I don't think anyone ever specifies width on \n // anyway.\n // Browsers where the left scrollbar doesn't cause an issue report `0` for\n // this (e.g. Edge 2019, IE11, Safari)\n return getBoundingClientRect(getDocumentElement(element)).left + getWindowScroll(element).scrollLeft;\n}","import getComputedStyle from \"./getComputedStyle.js\";\nexport default function isScrollParent(element) {\n // Firefox wants us to check `-x` and `-y` variations as well\n var _getComputedStyle = getComputedStyle(element),\n overflow = _getComputedStyle.overflow,\n overflowX = _getComputedStyle.overflowX,\n overflowY = _getComputedStyle.overflowY;\n\n return /auto|scroll|overlay|hidden/.test(overflow + overflowY + overflowX);\n}","import getParentNode from \"./getParentNode.js\";\nimport isScrollParent from \"./isScrollParent.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nexport default function getScrollParent(node) {\n if (['html', 'body', '#document'].indexOf(getNodeName(node)) >= 0) {\n // $FlowFixMe[incompatible-return]: assume body is always available\n return node.ownerDocument.body;\n }\n\n if (isHTMLElement(node) && isScrollParent(node)) {\n return node;\n }\n\n return getScrollParent(getParentNode(node));\n}","import getScrollParent from \"./getScrollParent.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport getWindow from \"./getWindow.js\";\nimport isScrollParent from \"./isScrollParent.js\";\n/*\ngiven a DOM element, return the list of all scroll parents, up the list of ancesors\nuntil we get to the top window object. This list is what we attach scroll listeners\nto, because if any of these parent elements scroll, we'll need to re-calculate the\nreference element's position.\n*/\n\nexport default function listScrollParents(element, list) {\n var _element$ownerDocumen;\n\n if (list === void 0) {\n list = [];\n }\n\n var scrollParent = getScrollParent(element);\n var isBody = scrollParent === ((_element$ownerDocumen = element.ownerDocument) == null ? void 0 : _element$ownerDocumen.body);\n var win = getWindow(scrollParent);\n var target = isBody ? [win].concat(win.visualViewport || [], isScrollParent(scrollParent) ? scrollParent : []) : scrollParent;\n var updatedList = list.concat(target);\n return isBody ? updatedList : // $FlowFixMe[incompatible-call]: isBody tells us target will be an HTMLElement here\n updatedList.concat(listScrollParents(getParentNode(target)));\n}","export default function rectToClientRect(rect) {\n return Object.assign({}, rect, {\n left: rect.x,\n top: rect.y,\n right: rect.x + rect.width,\n bottom: rect.y + rect.height\n });\n}","import { viewport } from \"../enums.js\";\nimport getViewportRect from \"./getViewportRect.js\";\nimport getDocumentRect from \"./getDocumentRect.js\";\nimport listScrollParents from \"./listScrollParents.js\";\nimport getOffsetParent from \"./getOffsetParent.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport { isElement, isHTMLElement } from \"./instanceOf.js\";\nimport getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport contains from \"./contains.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport rectToClientRect from \"../utils/rectToClientRect.js\";\nimport { max, min } from \"../utils/math.js\";\n\nfunction getInnerBoundingClientRect(element, strategy) {\n var rect = getBoundingClientRect(element, false, strategy === 'fixed');\n rect.top = rect.top + element.clientTop;\n rect.left = rect.left + element.clientLeft;\n rect.bottom = rect.top + element.clientHeight;\n rect.right = rect.left + element.clientWidth;\n rect.width = element.clientWidth;\n rect.height = element.clientHeight;\n rect.x = rect.left;\n rect.y = rect.top;\n return rect;\n}\n\nfunction getClientRectFromMixedType(element, clippingParent, strategy) {\n return clippingParent === viewport ? rectToClientRect(getViewportRect(element, strategy)) : isElement(clippingParent) ? getInnerBoundingClientRect(clippingParent, strategy) : rectToClientRect(getDocumentRect(getDocumentElement(element)));\n} // A \"clipping parent\" is an overflowable container with the characteristic of\n// clipping (or hiding) overflowing elements with a position different from\n// `initial`\n\n\nfunction getClippingParents(element) {\n var clippingParents = listScrollParents(getParentNode(element));\n var canEscapeClipping = ['absolute', 'fixed'].indexOf(getComputedStyle(element).position) >= 0;\n var clipperElement = canEscapeClipping && isHTMLElement(element) ? getOffsetParent(element) : element;\n\n if (!isElement(clipperElement)) {\n return [];\n } // $FlowFixMe[incompatible-return]: https://github.com/facebook/flow/issues/1414\n\n\n return clippingParents.filter(function (clippingParent) {\n return isElement(clippingParent) && contains(clippingParent, clipperElement) && getNodeName(clippingParent) !== 'body';\n });\n} // Gets the maximum area that the element is visible in due to any number of\n// clipping parents\n\n\nexport default function getClippingRect(element, boundary, rootBoundary, strategy) {\n var mainClippingParents = boundary === 'clippingParents' ? getClippingParents(element) : [].concat(boundary);\n var clippingParents = [].concat(mainClippingParents, [rootBoundary]);\n var firstClippingParent = clippingParents[0];\n var clippingRect = clippingParents.reduce(function (accRect, clippingParent) {\n var rect = getClientRectFromMixedType(element, clippingParent, strategy);\n accRect.top = max(rect.top, accRect.top);\n accRect.right = min(rect.right, accRect.right);\n accRect.bottom = min(rect.bottom, accRect.bottom);\n accRect.left = max(rect.left, accRect.left);\n return accRect;\n }, getClientRectFromMixedType(element, firstClippingParent, strategy));\n clippingRect.width = clippingRect.right - clippingRect.left;\n clippingRect.height = clippingRect.bottom - clippingRect.top;\n clippingRect.x = clippingRect.left;\n clippingRect.y = clippingRect.top;\n return clippingRect;\n}","import getWindow from \"./getWindow.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport isLayoutViewport from \"./isLayoutViewport.js\";\nexport default function getViewportRect(element, strategy) {\n var win = getWindow(element);\n var html = getDocumentElement(element);\n var visualViewport = win.visualViewport;\n var width = html.clientWidth;\n var height = html.clientHeight;\n var x = 0;\n var y = 0;\n\n if (visualViewport) {\n width = visualViewport.width;\n height = visualViewport.height;\n var layoutViewport = isLayoutViewport();\n\n if (layoutViewport || !layoutViewport && strategy === 'fixed') {\n x = visualViewport.offsetLeft;\n y = visualViewport.offsetTop;\n }\n }\n\n return {\n width: width,\n height: height,\n x: x + getWindowScrollBarX(element),\n y: y\n };\n}","import getDocumentElement from \"./getDocumentElement.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport getWindowScroll from \"./getWindowScroll.js\";\nimport { max } from \"../utils/math.js\"; // Gets the entire size of the scrollable document area, even extending outside\n// of the `` and `` rect bounds if horizontally scrollable\n\nexport default function getDocumentRect(element) {\n var _element$ownerDocumen;\n\n var html = getDocumentElement(element);\n var winScroll = getWindowScroll(element);\n var body = (_element$ownerDocumen = element.ownerDocument) == null ? void 0 : _element$ownerDocumen.body;\n var width = max(html.scrollWidth, html.clientWidth, body ? body.scrollWidth : 0, body ? body.clientWidth : 0);\n var height = max(html.scrollHeight, html.clientHeight, body ? body.scrollHeight : 0, body ? body.clientHeight : 0);\n var x = -winScroll.scrollLeft + getWindowScrollBarX(element);\n var y = -winScroll.scrollTop;\n\n if (getComputedStyle(body || html).direction === 'rtl') {\n x += max(html.clientWidth, body ? body.clientWidth : 0) - width;\n }\n\n return {\n width: width,\n height: height,\n x: x,\n y: y\n };\n}","import getBasePlacement from \"./getBasePlacement.js\";\nimport getVariation from \"./getVariation.js\";\nimport getMainAxisFromPlacement from \"./getMainAxisFromPlacement.js\";\nimport { top, right, bottom, left, start, end } from \"../enums.js\";\nexport default function computeOffsets(_ref) {\n var reference = _ref.reference,\n element = _ref.element,\n placement = _ref.placement;\n var basePlacement = placement ? getBasePlacement(placement) : null;\n var variation = placement ? getVariation(placement) : null;\n var commonX = reference.x + reference.width / 2 - element.width / 2;\n var commonY = reference.y + reference.height / 2 - element.height / 2;\n var offsets;\n\n switch (basePlacement) {\n case top:\n offsets = {\n x: commonX,\n y: reference.y - element.height\n };\n break;\n\n case bottom:\n offsets = {\n x: commonX,\n y: reference.y + reference.height\n };\n break;\n\n case right:\n offsets = {\n x: reference.x + reference.width,\n y: commonY\n };\n break;\n\n case left:\n offsets = {\n x: reference.x - element.width,\n y: commonY\n };\n break;\n\n default:\n offsets = {\n x: reference.x,\n y: reference.y\n };\n }\n\n var mainAxis = basePlacement ? getMainAxisFromPlacement(basePlacement) : null;\n\n if (mainAxis != null) {\n var len = mainAxis === 'y' ? 'height' : 'width';\n\n switch (variation) {\n case start:\n offsets[mainAxis] = offsets[mainAxis] - (reference[len] / 2 - element[len] / 2);\n break;\n\n case end:\n offsets[mainAxis] = offsets[mainAxis] + (reference[len] / 2 - element[len] / 2);\n break;\n\n default:\n }\n }\n\n return offsets;\n}","import getClippingRect from \"../dom-utils/getClippingRect.js\";\nimport getDocumentElement from \"../dom-utils/getDocumentElement.js\";\nimport getBoundingClientRect from \"../dom-utils/getBoundingClientRect.js\";\nimport computeOffsets from \"./computeOffsets.js\";\nimport rectToClientRect from \"./rectToClientRect.js\";\nimport { clippingParents, reference, popper, bottom, top, right, basePlacements, viewport } from \"../enums.js\";\nimport { isElement } from \"../dom-utils/instanceOf.js\";\nimport mergePaddingObject from \"./mergePaddingObject.js\";\nimport expandToHashMap from \"./expandToHashMap.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport default function detectOverflow(state, options) {\n if (options === void 0) {\n options = {};\n }\n\n var _options = options,\n _options$placement = _options.placement,\n placement = _options$placement === void 0 ? state.placement : _options$placement,\n _options$strategy = _options.strategy,\n strategy = _options$strategy === void 0 ? state.strategy : _options$strategy,\n _options$boundary = _options.boundary,\n boundary = _options$boundary === void 0 ? clippingParents : _options$boundary,\n _options$rootBoundary = _options.rootBoundary,\n rootBoundary = _options$rootBoundary === void 0 ? viewport : _options$rootBoundary,\n _options$elementConte = _options.elementContext,\n elementContext = _options$elementConte === void 0 ? popper : _options$elementConte,\n _options$altBoundary = _options.altBoundary,\n altBoundary = _options$altBoundary === void 0 ? false : _options$altBoundary,\n _options$padding = _options.padding,\n padding = _options$padding === void 0 ? 0 : _options$padding;\n var paddingObject = mergePaddingObject(typeof padding !== 'number' ? padding : expandToHashMap(padding, basePlacements));\n var altContext = elementContext === popper ? reference : popper;\n var popperRect = state.rects.popper;\n var element = state.elements[altBoundary ? altContext : elementContext];\n var clippingClientRect = getClippingRect(isElement(element) ? element : element.contextElement || getDocumentElement(state.elements.popper), boundary, rootBoundary, strategy);\n var referenceClientRect = getBoundingClientRect(state.elements.reference);\n var popperOffsets = computeOffsets({\n reference: referenceClientRect,\n element: popperRect,\n strategy: 'absolute',\n placement: placement\n });\n var popperClientRect = rectToClientRect(Object.assign({}, popperRect, popperOffsets));\n var elementClientRect = elementContext === popper ? popperClientRect : referenceClientRect; // positive = overflowing the clipping rect\n // 0 or negative = within the clipping rect\n\n var overflowOffsets = {\n top: clippingClientRect.top - elementClientRect.top + paddingObject.top,\n bottom: elementClientRect.bottom - clippingClientRect.bottom + paddingObject.bottom,\n left: clippingClientRect.left - elementClientRect.left + paddingObject.left,\n right: elementClientRect.right - clippingClientRect.right + paddingObject.right\n };\n var offsetData = state.modifiersData.offset; // Offsets can be applied only to the popper element\n\n if (elementContext === popper && offsetData) {\n var offset = offsetData[placement];\n Object.keys(overflowOffsets).forEach(function (key) {\n var multiply = [right, bottom].indexOf(key) >= 0 ? 1 : -1;\n var axis = [top, bottom].indexOf(key) >= 0 ? 'y' : 'x';\n overflowOffsets[key] += offset[axis] * multiply;\n });\n }\n\n return overflowOffsets;\n}","import getVariation from \"./getVariation.js\";\nimport { variationPlacements, basePlacements, placements as allPlacements } from \"../enums.js\";\nimport detectOverflow from \"./detectOverflow.js\";\nimport getBasePlacement from \"./getBasePlacement.js\";\nexport default function computeAutoPlacement(state, options) {\n if (options === void 0) {\n options = {};\n }\n\n var _options = options,\n placement = _options.placement,\n boundary = _options.boundary,\n rootBoundary = _options.rootBoundary,\n padding = _options.padding,\n flipVariations = _options.flipVariations,\n _options$allowedAutoP = _options.allowedAutoPlacements,\n allowedAutoPlacements = _options$allowedAutoP === void 0 ? allPlacements : _options$allowedAutoP;\n var variation = getVariation(placement);\n var placements = variation ? flipVariations ? variationPlacements : variationPlacements.filter(function (placement) {\n return getVariation(placement) === variation;\n }) : basePlacements;\n var allowedPlacements = placements.filter(function (placement) {\n return allowedAutoPlacements.indexOf(placement) >= 0;\n });\n\n if (allowedPlacements.length === 0) {\n allowedPlacements = placements;\n } // $FlowFixMe[incompatible-type]: Flow seems to have problems with two array unions...\n\n\n var overflows = allowedPlacements.reduce(function (acc, placement) {\n acc[placement] = detectOverflow(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding\n })[getBasePlacement(placement)];\n return acc;\n }, {});\n return Object.keys(overflows).sort(function (a, b) {\n return overflows[a] - overflows[b];\n });\n}","import getOppositePlacement from \"../utils/getOppositePlacement.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getOppositeVariationPlacement from \"../utils/getOppositeVariationPlacement.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\nimport computeAutoPlacement from \"../utils/computeAutoPlacement.js\";\nimport { bottom, top, start, right, left, auto } from \"../enums.js\";\nimport getVariation from \"../utils/getVariation.js\"; // eslint-disable-next-line import/no-unused-modules\n\nfunction getExpandedFallbackPlacements(placement) {\n if (getBasePlacement(placement) === auto) {\n return [];\n }\n\n var oppositePlacement = getOppositePlacement(placement);\n return [getOppositeVariationPlacement(placement), oppositePlacement, getOppositeVariationPlacement(oppositePlacement)];\n}\n\nfunction flip(_ref) {\n var state = _ref.state,\n options = _ref.options,\n name = _ref.name;\n\n if (state.modifiersData[name]._skip) {\n return;\n }\n\n var _options$mainAxis = options.mainAxis,\n checkMainAxis = _options$mainAxis === void 0 ? true : _options$mainAxis,\n _options$altAxis = options.altAxis,\n checkAltAxis = _options$altAxis === void 0 ? true : _options$altAxis,\n specifiedFallbackPlacements = options.fallbackPlacements,\n padding = options.padding,\n boundary = options.boundary,\n rootBoundary = options.rootBoundary,\n altBoundary = options.altBoundary,\n _options$flipVariatio = options.flipVariations,\n flipVariations = _options$flipVariatio === void 0 ? true : _options$flipVariatio,\n allowedAutoPlacements = options.allowedAutoPlacements;\n var preferredPlacement = state.options.placement;\n var basePlacement = getBasePlacement(preferredPlacement);\n var isBasePlacement = basePlacement === preferredPlacement;\n var fallbackPlacements = specifiedFallbackPlacements || (isBasePlacement || !flipVariations ? [getOppositePlacement(preferredPlacement)] : getExpandedFallbackPlacements(preferredPlacement));\n var placements = [preferredPlacement].concat(fallbackPlacements).reduce(function (acc, placement) {\n return acc.concat(getBasePlacement(placement) === auto ? computeAutoPlacement(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding,\n flipVariations: flipVariations,\n allowedAutoPlacements: allowedAutoPlacements\n }) : placement);\n }, []);\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var checksMap = new Map();\n var makeFallbackChecks = true;\n var firstFittingPlacement = placements[0];\n\n for (var i = 0; i < placements.length; i++) {\n var placement = placements[i];\n\n var _basePlacement = getBasePlacement(placement);\n\n var isStartVariation = getVariation(placement) === start;\n var isVertical = [top, bottom].indexOf(_basePlacement) >= 0;\n var len = isVertical ? 'width' : 'height';\n var overflow = detectOverflow(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n altBoundary: altBoundary,\n padding: padding\n });\n var mainVariationSide = isVertical ? isStartVariation ? right : left : isStartVariation ? bottom : top;\n\n if (referenceRect[len] > popperRect[len]) {\n mainVariationSide = getOppositePlacement(mainVariationSide);\n }\n\n var altVariationSide = getOppositePlacement(mainVariationSide);\n var checks = [];\n\n if (checkMainAxis) {\n checks.push(overflow[_basePlacement] <= 0);\n }\n\n if (checkAltAxis) {\n checks.push(overflow[mainVariationSide] <= 0, overflow[altVariationSide] <= 0);\n }\n\n if (checks.every(function (check) {\n return check;\n })) {\n firstFittingPlacement = placement;\n makeFallbackChecks = false;\n break;\n }\n\n checksMap.set(placement, checks);\n }\n\n if (makeFallbackChecks) {\n // `2` may be desired in some cases – research later\n var numberOfChecks = flipVariations ? 3 : 1;\n\n var _loop = function _loop(_i) {\n var fittingPlacement = placements.find(function (placement) {\n var checks = checksMap.get(placement);\n\n if (checks) {\n return checks.slice(0, _i).every(function (check) {\n return check;\n });\n }\n });\n\n if (fittingPlacement) {\n firstFittingPlacement = fittingPlacement;\n return \"break\";\n }\n };\n\n for (var _i = numberOfChecks; _i > 0; _i--) {\n var _ret = _loop(_i);\n\n if (_ret === \"break\") break;\n }\n }\n\n if (state.placement !== firstFittingPlacement) {\n state.modifiersData[name]._skip = true;\n state.placement = firstFittingPlacement;\n state.reset = true;\n }\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'flip',\n enabled: true,\n phase: 'main',\n fn: flip,\n requiresIfExists: ['offset'],\n data: {\n _skip: false\n }\n};","import { top, bottom, left, right } from \"../enums.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\n\nfunction getSideOffsets(overflow, rect, preventedOffsets) {\n if (preventedOffsets === void 0) {\n preventedOffsets = {\n x: 0,\n y: 0\n };\n }\n\n return {\n top: overflow.top - rect.height - preventedOffsets.y,\n right: overflow.right - rect.width + preventedOffsets.x,\n bottom: overflow.bottom - rect.height + preventedOffsets.y,\n left: overflow.left - rect.width - preventedOffsets.x\n };\n}\n\nfunction isAnySideFullyClipped(overflow) {\n return [top, right, bottom, left].some(function (side) {\n return overflow[side] >= 0;\n });\n}\n\nfunction hide(_ref) {\n var state = _ref.state,\n name = _ref.name;\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var preventedOffsets = state.modifiersData.preventOverflow;\n var referenceOverflow = detectOverflow(state, {\n elementContext: 'reference'\n });\n var popperAltOverflow = detectOverflow(state, {\n altBoundary: true\n });\n var referenceClippingOffsets = getSideOffsets(referenceOverflow, referenceRect);\n var popperEscapeOffsets = getSideOffsets(popperAltOverflow, popperRect, preventedOffsets);\n var isReferenceHidden = isAnySideFullyClipped(referenceClippingOffsets);\n var hasPopperEscaped = isAnySideFullyClipped(popperEscapeOffsets);\n state.modifiersData[name] = {\n referenceClippingOffsets: referenceClippingOffsets,\n popperEscapeOffsets: popperEscapeOffsets,\n isReferenceHidden: isReferenceHidden,\n hasPopperEscaped: hasPopperEscaped\n };\n state.attributes.popper = Object.assign({}, state.attributes.popper, {\n 'data-popper-reference-hidden': isReferenceHidden,\n 'data-popper-escaped': hasPopperEscaped\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'hide',\n enabled: true,\n phase: 'main',\n requiresIfExists: ['preventOverflow'],\n fn: hide\n};","import getBasePlacement from \"../utils/getBasePlacement.js\";\nimport { top, left, right, placements } from \"../enums.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport function distanceAndSkiddingToXY(placement, rects, offset) {\n var basePlacement = getBasePlacement(placement);\n var invertDistance = [left, top].indexOf(basePlacement) >= 0 ? -1 : 1;\n\n var _ref = typeof offset === 'function' ? offset(Object.assign({}, rects, {\n placement: placement\n })) : offset,\n skidding = _ref[0],\n distance = _ref[1];\n\n skidding = skidding || 0;\n distance = (distance || 0) * invertDistance;\n return [left, right].indexOf(basePlacement) >= 0 ? {\n x: distance,\n y: skidding\n } : {\n x: skidding,\n y: distance\n };\n}\n\nfunction offset(_ref2) {\n var state = _ref2.state,\n options = _ref2.options,\n name = _ref2.name;\n var _options$offset = options.offset,\n offset = _options$offset === void 0 ? [0, 0] : _options$offset;\n var data = placements.reduce(function (acc, placement) {\n acc[placement] = distanceAndSkiddingToXY(placement, state.rects, offset);\n return acc;\n }, {});\n var _data$state$placement = data[state.placement],\n x = _data$state$placement.x,\n y = _data$state$placement.y;\n\n if (state.modifiersData.popperOffsets != null) {\n state.modifiersData.popperOffsets.x += x;\n state.modifiersData.popperOffsets.y += y;\n }\n\n state.modifiersData[name] = data;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'offset',\n enabled: true,\n phase: 'main',\n requires: ['popperOffsets'],\n fn: offset\n};","import computeOffsets from \"../utils/computeOffsets.js\";\n\nfunction popperOffsets(_ref) {\n var state = _ref.state,\n name = _ref.name;\n // Offsets are the actual position the popper needs to have to be\n // properly positioned near its reference element\n // This is the most basic placement, and will be adjusted by\n // the modifiers in the next step\n state.modifiersData[name] = computeOffsets({\n reference: state.rects.reference,\n element: state.rects.popper,\n strategy: 'absolute',\n placement: state.placement\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'popperOffsets',\n enabled: true,\n phase: 'read',\n fn: popperOffsets,\n data: {}\n};","import { top, left, right, bottom, start } from \"../enums.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getMainAxisFromPlacement from \"../utils/getMainAxisFromPlacement.js\";\nimport getAltAxis from \"../utils/getAltAxis.js\";\nimport { within, withinMaxClamp } from \"../utils/within.js\";\nimport getLayoutRect from \"../dom-utils/getLayoutRect.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\nimport getVariation from \"../utils/getVariation.js\";\nimport getFreshSideObject from \"../utils/getFreshSideObject.js\";\nimport { min as mathMin, max as mathMax } from \"../utils/math.js\";\n\nfunction preventOverflow(_ref) {\n var state = _ref.state,\n options = _ref.options,\n name = _ref.name;\n var _options$mainAxis = options.mainAxis,\n checkMainAxis = _options$mainAxis === void 0 ? true : _options$mainAxis,\n _options$altAxis = options.altAxis,\n checkAltAxis = _options$altAxis === void 0 ? false : _options$altAxis,\n boundary = options.boundary,\n rootBoundary = options.rootBoundary,\n altBoundary = options.altBoundary,\n padding = options.padding,\n _options$tether = options.tether,\n tether = _options$tether === void 0 ? true : _options$tether,\n _options$tetherOffset = options.tetherOffset,\n tetherOffset = _options$tetherOffset === void 0 ? 0 : _options$tetherOffset;\n var overflow = detectOverflow(state, {\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding,\n altBoundary: altBoundary\n });\n var basePlacement = getBasePlacement(state.placement);\n var variation = getVariation(state.placement);\n var isBasePlacement = !variation;\n var mainAxis = getMainAxisFromPlacement(basePlacement);\n var altAxis = getAltAxis(mainAxis);\n var popperOffsets = state.modifiersData.popperOffsets;\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var tetherOffsetValue = typeof tetherOffset === 'function' ? tetherOffset(Object.assign({}, state.rects, {\n placement: state.placement\n })) : tetherOffset;\n var normalizedTetherOffsetValue = typeof tetherOffsetValue === 'number' ? {\n mainAxis: tetherOffsetValue,\n altAxis: tetherOffsetValue\n } : Object.assign({\n mainAxis: 0,\n altAxis: 0\n }, tetherOffsetValue);\n var offsetModifierState = state.modifiersData.offset ? state.modifiersData.offset[state.placement] : null;\n var data = {\n x: 0,\n y: 0\n };\n\n if (!popperOffsets) {\n return;\n }\n\n if (checkMainAxis) {\n var _offsetModifierState$;\n\n var mainSide = mainAxis === 'y' ? top : left;\n var altSide = mainAxis === 'y' ? bottom : right;\n var len = mainAxis === 'y' ? 'height' : 'width';\n var offset = popperOffsets[mainAxis];\n var min = offset + overflow[mainSide];\n var max = offset - overflow[altSide];\n var additive = tether ? -popperRect[len] / 2 : 0;\n var minLen = variation === start ? referenceRect[len] : popperRect[len];\n var maxLen = variation === start ? -popperRect[len] : -referenceRect[len]; // We need to include the arrow in the calculation so the arrow doesn't go\n // outside the reference bounds\n\n var arrowElement = state.elements.arrow;\n var arrowRect = tether && arrowElement ? getLayoutRect(arrowElement) : {\n width: 0,\n height: 0\n };\n var arrowPaddingObject = state.modifiersData['arrow#persistent'] ? state.modifiersData['arrow#persistent'].padding : getFreshSideObject();\n var arrowPaddingMin = arrowPaddingObject[mainSide];\n var arrowPaddingMax = arrowPaddingObject[altSide]; // If the reference length is smaller than the arrow length, we don't want\n // to include its full size in the calculation. If the reference is small\n // and near the edge of a boundary, the popper can overflow even if the\n // reference is not overflowing as well (e.g. virtual elements with no\n // width or height)\n\n var arrowLen = within(0, referenceRect[len], arrowRect[len]);\n var minOffset = isBasePlacement ? referenceRect[len] / 2 - additive - arrowLen - arrowPaddingMin - normalizedTetherOffsetValue.mainAxis : minLen - arrowLen - arrowPaddingMin - normalizedTetherOffsetValue.mainAxis;\n var maxOffset = isBasePlacement ? -referenceRect[len] / 2 + additive + arrowLen + arrowPaddingMax + normalizedTetherOffsetValue.mainAxis : maxLen + arrowLen + arrowPaddingMax + normalizedTetherOffsetValue.mainAxis;\n var arrowOffsetParent = state.elements.arrow && getOffsetParent(state.elements.arrow);\n var clientOffset = arrowOffsetParent ? mainAxis === 'y' ? arrowOffsetParent.clientTop || 0 : arrowOffsetParent.clientLeft || 0 : 0;\n var offsetModifierValue = (_offsetModifierState$ = offsetModifierState == null ? void 0 : offsetModifierState[mainAxis]) != null ? _offsetModifierState$ : 0;\n var tetherMin = offset + minOffset - offsetModifierValue - clientOffset;\n var tetherMax = offset + maxOffset - offsetModifierValue;\n var preventedOffset = within(tether ? mathMin(min, tetherMin) : min, offset, tether ? mathMax(max, tetherMax) : max);\n popperOffsets[mainAxis] = preventedOffset;\n data[mainAxis] = preventedOffset - offset;\n }\n\n if (checkAltAxis) {\n var _offsetModifierState$2;\n\n var _mainSide = mainAxis === 'x' ? top : left;\n\n var _altSide = mainAxis === 'x' ? bottom : right;\n\n var _offset = popperOffsets[altAxis];\n\n var _len = altAxis === 'y' ? 'height' : 'width';\n\n var _min = _offset + overflow[_mainSide];\n\n var _max = _offset - overflow[_altSide];\n\n var isOriginSide = [top, left].indexOf(basePlacement) !== -1;\n\n var _offsetModifierValue = (_offsetModifierState$2 = offsetModifierState == null ? void 0 : offsetModifierState[altAxis]) != null ? _offsetModifierState$2 : 0;\n\n var _tetherMin = isOriginSide ? _min : _offset - referenceRect[_len] - popperRect[_len] - _offsetModifierValue + normalizedTetherOffsetValue.altAxis;\n\n var _tetherMax = isOriginSide ? _offset + referenceRect[_len] + popperRect[_len] - _offsetModifierValue - normalizedTetherOffsetValue.altAxis : _max;\n\n var _preventedOffset = tether && isOriginSide ? withinMaxClamp(_tetherMin, _offset, _tetherMax) : within(tether ? _tetherMin : _min, _offset, tether ? _tetherMax : _max);\n\n popperOffsets[altAxis] = _preventedOffset;\n data[altAxis] = _preventedOffset - _offset;\n }\n\n state.modifiersData[name] = data;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'preventOverflow',\n enabled: true,\n phase: 'main',\n fn: preventOverflow,\n requiresIfExists: ['offset']\n};","export default function getAltAxis(axis) {\n return axis === 'x' ? 'y' : 'x';\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getNodeScroll from \"./getNodeScroll.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport isScrollParent from \"./isScrollParent.js\";\nimport { round } from \"../utils/math.js\";\n\nfunction isElementScaled(element) {\n var rect = element.getBoundingClientRect();\n var scaleX = round(rect.width) / element.offsetWidth || 1;\n var scaleY = round(rect.height) / element.offsetHeight || 1;\n return scaleX !== 1 || scaleY !== 1;\n} // Returns the composite rect of an element relative to its offsetParent.\n// Composite means it takes into account transforms as well as layout.\n\n\nexport default function getCompositeRect(elementOrVirtualElement, offsetParent, isFixed) {\n if (isFixed === void 0) {\n isFixed = false;\n }\n\n var isOffsetParentAnElement = isHTMLElement(offsetParent);\n var offsetParentIsScaled = isHTMLElement(offsetParent) && isElementScaled(offsetParent);\n var documentElement = getDocumentElement(offsetParent);\n var rect = getBoundingClientRect(elementOrVirtualElement, offsetParentIsScaled, isFixed);\n var scroll = {\n scrollLeft: 0,\n scrollTop: 0\n };\n var offsets = {\n x: 0,\n y: 0\n };\n\n if (isOffsetParentAnElement || !isOffsetParentAnElement && !isFixed) {\n if (getNodeName(offsetParent) !== 'body' || // https://github.com/popperjs/popper-core/issues/1078\n isScrollParent(documentElement)) {\n scroll = getNodeScroll(offsetParent);\n }\n\n if (isHTMLElement(offsetParent)) {\n offsets = getBoundingClientRect(offsetParent, true);\n offsets.x += offsetParent.clientLeft;\n offsets.y += offsetParent.clientTop;\n } else if (documentElement) {\n offsets.x = getWindowScrollBarX(documentElement);\n }\n }\n\n return {\n x: rect.left + scroll.scrollLeft - offsets.x,\n y: rect.top + scroll.scrollTop - offsets.y,\n width: rect.width,\n height: rect.height\n };\n}","import getWindowScroll from \"./getWindowScroll.js\";\nimport getWindow from \"./getWindow.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nimport getHTMLElementScroll from \"./getHTMLElementScroll.js\";\nexport default function getNodeScroll(node) {\n if (node === getWindow(node) || !isHTMLElement(node)) {\n return getWindowScroll(node);\n } else {\n return getHTMLElementScroll(node);\n }\n}","export default function getHTMLElementScroll(element) {\n return {\n scrollLeft: element.scrollLeft,\n scrollTop: element.scrollTop\n };\n}","import { modifierPhases } from \"../enums.js\"; // source: https://stackoverflow.com/questions/49875255\n\nfunction order(modifiers) {\n var map = new Map();\n var visited = new Set();\n var result = [];\n modifiers.forEach(function (modifier) {\n map.set(modifier.name, modifier);\n }); // On visiting object, check for its dependencies and visit them recursively\n\n function sort(modifier) {\n visited.add(modifier.name);\n var requires = [].concat(modifier.requires || [], modifier.requiresIfExists || []);\n requires.forEach(function (dep) {\n if (!visited.has(dep)) {\n var depModifier = map.get(dep);\n\n if (depModifier) {\n sort(depModifier);\n }\n }\n });\n result.push(modifier);\n }\n\n modifiers.forEach(function (modifier) {\n if (!visited.has(modifier.name)) {\n // check for visited object\n sort(modifier);\n }\n });\n return result;\n}\n\nexport default function orderModifiers(modifiers) {\n // order based on dependencies\n var orderedModifiers = order(modifiers); // order based on phase\n\n return modifierPhases.reduce(function (acc, phase) {\n return acc.concat(orderedModifiers.filter(function (modifier) {\n return modifier.phase === phase;\n }));\n }, []);\n}","import getCompositeRect from \"./dom-utils/getCompositeRect.js\";\nimport getLayoutRect from \"./dom-utils/getLayoutRect.js\";\nimport listScrollParents from \"./dom-utils/listScrollParents.js\";\nimport getOffsetParent from \"./dom-utils/getOffsetParent.js\";\nimport orderModifiers from \"./utils/orderModifiers.js\";\nimport debounce from \"./utils/debounce.js\";\nimport mergeByName from \"./utils/mergeByName.js\";\nimport detectOverflow from \"./utils/detectOverflow.js\";\nimport { isElement } from \"./dom-utils/instanceOf.js\";\nvar DEFAULT_OPTIONS = {\n placement: 'bottom',\n modifiers: [],\n strategy: 'absolute'\n};\n\nfunction areValidElements() {\n for (var _len = arguments.length, args = new Array(_len), _key = 0; _key < _len; _key++) {\n args[_key] = arguments[_key];\n }\n\n return !args.some(function (element) {\n return !(element && typeof element.getBoundingClientRect === 'function');\n });\n}\n\nexport function popperGenerator(generatorOptions) {\n if (generatorOptions === void 0) {\n generatorOptions = {};\n }\n\n var _generatorOptions = generatorOptions,\n _generatorOptions$def = _generatorOptions.defaultModifiers,\n defaultModifiers = _generatorOptions$def === void 0 ? [] : _generatorOptions$def,\n _generatorOptions$def2 = _generatorOptions.defaultOptions,\n defaultOptions = _generatorOptions$def2 === void 0 ? DEFAULT_OPTIONS : _generatorOptions$def2;\n return function createPopper(reference, popper, options) {\n if (options === void 0) {\n options = defaultOptions;\n }\n\n var state = {\n placement: 'bottom',\n orderedModifiers: [],\n options: Object.assign({}, DEFAULT_OPTIONS, defaultOptions),\n modifiersData: {},\n elements: {\n reference: reference,\n popper: popper\n },\n attributes: {},\n styles: {}\n };\n var effectCleanupFns = [];\n var isDestroyed = false;\n var instance = {\n state: state,\n setOptions: function setOptions(setOptionsAction) {\n var options = typeof setOptionsAction === 'function' ? setOptionsAction(state.options) : setOptionsAction;\n cleanupModifierEffects();\n state.options = Object.assign({}, defaultOptions, state.options, options);\n state.scrollParents = {\n reference: isElement(reference) ? listScrollParents(reference) : reference.contextElement ? listScrollParents(reference.contextElement) : [],\n popper: listScrollParents(popper)\n }; // Orders the modifiers based on their dependencies and `phase`\n // properties\n\n var orderedModifiers = orderModifiers(mergeByName([].concat(defaultModifiers, state.options.modifiers))); // Strip out disabled modifiers\n\n state.orderedModifiers = orderedModifiers.filter(function (m) {\n return m.enabled;\n });\n runModifierEffects();\n return instance.update();\n },\n // Sync update – it will always be executed, even if not necessary. This\n // is useful for low frequency updates where sync behavior simplifies the\n // logic.\n // For high frequency updates (e.g. `resize` and `scroll` events), always\n // prefer the async Popper#update method\n forceUpdate: function forceUpdate() {\n if (isDestroyed) {\n return;\n }\n\n var _state$elements = state.elements,\n reference = _state$elements.reference,\n popper = _state$elements.popper; // Don't proceed if `reference` or `popper` are not valid elements\n // anymore\n\n if (!areValidElements(reference, popper)) {\n return;\n } // Store the reference and popper rects to be read by modifiers\n\n\n state.rects = {\n reference: getCompositeRect(reference, getOffsetParent(popper), state.options.strategy === 'fixed'),\n popper: getLayoutRect(popper)\n }; // Modifiers have the ability to reset the current update cycle. The\n // most common use case for this is the `flip` modifier changing the\n // placement, which then needs to re-run all the modifiers, because the\n // logic was previously ran for the previous placement and is therefore\n // stale/incorrect\n\n state.reset = false;\n state.placement = state.options.placement; // On each update cycle, the `modifiersData` property for each modifier\n // is filled with the initial data specified by the modifier. This means\n // it doesn't persist and is fresh on each update.\n // To ensure persistent data, use `${name}#persistent`\n\n state.orderedModifiers.forEach(function (modifier) {\n return state.modifiersData[modifier.name] = Object.assign({}, modifier.data);\n });\n\n for (var index = 0; index < state.orderedModifiers.length; index++) {\n if (state.reset === true) {\n state.reset = false;\n index = -1;\n continue;\n }\n\n var _state$orderedModifie = state.orderedModifiers[index],\n fn = _state$orderedModifie.fn,\n _state$orderedModifie2 = _state$orderedModifie.options,\n _options = _state$orderedModifie2 === void 0 ? {} : _state$orderedModifie2,\n name = _state$orderedModifie.name;\n\n if (typeof fn === 'function') {\n state = fn({\n state: state,\n options: _options,\n name: name,\n instance: instance\n }) || state;\n }\n }\n },\n // Async and optimistically optimized update – it will not be executed if\n // not necessary (debounced to run at most once-per-tick)\n update: debounce(function () {\n return new Promise(function (resolve) {\n instance.forceUpdate();\n resolve(state);\n });\n }),\n destroy: function destroy() {\n cleanupModifierEffects();\n isDestroyed = true;\n }\n };\n\n if (!areValidElements(reference, popper)) {\n return instance;\n }\n\n instance.setOptions(options).then(function (state) {\n if (!isDestroyed && options.onFirstUpdate) {\n options.onFirstUpdate(state);\n }\n }); // Modifiers have the ability to execute arbitrary code before the first\n // update cycle runs. They will be executed in the same order as the update\n // cycle. This is useful when a modifier adds some persistent data that\n // other modifiers need to use, but the modifier is run after the dependent\n // one.\n\n function runModifierEffects() {\n state.orderedModifiers.forEach(function (_ref) {\n var name = _ref.name,\n _ref$options = _ref.options,\n options = _ref$options === void 0 ? {} : _ref$options,\n effect = _ref.effect;\n\n if (typeof effect === 'function') {\n var cleanupFn = effect({\n state: state,\n name: name,\n instance: instance,\n options: options\n });\n\n var noopFn = function noopFn() {};\n\n effectCleanupFns.push(cleanupFn || noopFn);\n }\n });\n }\n\n function cleanupModifierEffects() {\n effectCleanupFns.forEach(function (fn) {\n return fn();\n });\n effectCleanupFns = [];\n }\n\n return instance;\n };\n}\nexport var createPopper = /*#__PURE__*/popperGenerator(); // eslint-disable-next-line import/no-unused-modules\n\nexport { detectOverflow };","export default function debounce(fn) {\n var pending;\n return function () {\n if (!pending) {\n pending = new Promise(function (resolve) {\n Promise.resolve().then(function () {\n pending = undefined;\n resolve(fn());\n });\n });\n }\n\n return pending;\n };\n}","export default function mergeByName(modifiers) {\n var merged = modifiers.reduce(function (merged, current) {\n var existing = merged[current.name];\n merged[current.name] = existing ? Object.assign({}, existing, current, {\n options: Object.assign({}, existing.options, current.options),\n data: Object.assign({}, existing.data, current.data)\n }) : current;\n return merged;\n }, {}); // IE11 does not support Object.values\n\n return Object.keys(merged).map(function (key) {\n return merged[key];\n });\n}","import { popperGenerator, detectOverflow } from \"./createPopper.js\";\nimport eventListeners from \"./modifiers/eventListeners.js\";\nimport popperOffsets from \"./modifiers/popperOffsets.js\";\nimport computeStyles from \"./modifiers/computeStyles.js\";\nimport applyStyles from \"./modifiers/applyStyles.js\";\nvar defaultModifiers = [eventListeners, popperOffsets, computeStyles, applyStyles];\nvar createPopper = /*#__PURE__*/popperGenerator({\n defaultModifiers: defaultModifiers\n}); // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper, popperGenerator, defaultModifiers, detectOverflow };","import { popperGenerator, detectOverflow } from \"./createPopper.js\";\nimport eventListeners from \"./modifiers/eventListeners.js\";\nimport popperOffsets from \"./modifiers/popperOffsets.js\";\nimport computeStyles from \"./modifiers/computeStyles.js\";\nimport applyStyles from \"./modifiers/applyStyles.js\";\nimport offset from \"./modifiers/offset.js\";\nimport flip from \"./modifiers/flip.js\";\nimport preventOverflow from \"./modifiers/preventOverflow.js\";\nimport arrow from \"./modifiers/arrow.js\";\nimport hide from \"./modifiers/hide.js\";\nvar defaultModifiers = [eventListeners, popperOffsets, computeStyles, applyStyles, offset, flip, preventOverflow, arrow, hide];\nvar createPopper = /*#__PURE__*/popperGenerator({\n defaultModifiers: defaultModifiers\n}); // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper, popperGenerator, defaultModifiers, detectOverflow }; // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper as createPopperLite } from \"./popper-lite.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport * from \"./modifiers/index.js\";","/**\n * --------------------------------------------------------------------------\n * Bootstrap dropdown.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport * as Popper from '@popperjs/core'\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport Manipulator from './dom/manipulator.js'\nimport SelectorEngine from './dom/selector-engine.js'\nimport {\n defineJQueryPlugin,\n execute,\n getElement,\n getNextActiveElement,\n isDisabled,\n isElement,\n isRTL,\n isVisible,\n noop\n} from './util/index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'dropdown'\nconst DATA_KEY = 'bs.dropdown'\nconst EVENT_KEY = `.${DATA_KEY}`\nconst DATA_API_KEY = '.data-api'\n\nconst ESCAPE_KEY = 'Escape'\nconst TAB_KEY = 'Tab'\nconst ARROW_UP_KEY = 'ArrowUp'\nconst ARROW_DOWN_KEY = 'ArrowDown'\nconst RIGHT_MOUSE_BUTTON = 2 // MouseEvent.button value for the secondary button, usually the right button\n\nconst EVENT_HIDE = `hide${EVENT_KEY}`\nconst EVENT_HIDDEN = `hidden${EVENT_KEY}`\nconst EVENT_SHOW = `show${EVENT_KEY}`\nconst EVENT_SHOWN = `shown${EVENT_KEY}`\nconst EVENT_CLICK_DATA_API = `click${EVENT_KEY}${DATA_API_KEY}`\nconst EVENT_KEYDOWN_DATA_API = `keydown${EVENT_KEY}${DATA_API_KEY}`\nconst EVENT_KEYUP_DATA_API = `keyup${EVENT_KEY}${DATA_API_KEY}`\n\nconst CLASS_NAME_SHOW = 'show'\nconst CLASS_NAME_DROPUP = 'dropup'\nconst CLASS_NAME_DROPEND = 'dropend'\nconst CLASS_NAME_DROPSTART = 'dropstart'\nconst CLASS_NAME_DROPUP_CENTER = 'dropup-center'\nconst CLASS_NAME_DROPDOWN_CENTER = 'dropdown-center'\n\nconst SELECTOR_DATA_TOGGLE = '[data-bs-toggle=\"dropdown\"]:not(.disabled):not(:disabled)'\nconst SELECTOR_DATA_TOGGLE_SHOWN = `${SELECTOR_DATA_TOGGLE}.${CLASS_NAME_SHOW}`\nconst SELECTOR_MENU = '.dropdown-menu'\nconst SELECTOR_NAVBAR = '.navbar'\nconst SELECTOR_NAVBAR_NAV = '.navbar-nav'\nconst SELECTOR_VISIBLE_ITEMS = '.dropdown-menu .dropdown-item:not(.disabled):not(:disabled)'\n\nconst PLACEMENT_TOP = isRTL() ? 'top-end' : 'top-start'\nconst PLACEMENT_TOPEND = isRTL() ? 'top-start' : 'top-end'\nconst PLACEMENT_BOTTOM = isRTL() ? 'bottom-end' : 'bottom-start'\nconst PLACEMENT_BOTTOMEND = isRTL() ? 'bottom-start' : 'bottom-end'\nconst PLACEMENT_RIGHT = isRTL() ? 'left-start' : 'right-start'\nconst PLACEMENT_LEFT = isRTL() ? 'right-start' : 'left-start'\nconst PLACEMENT_TOPCENTER = 'top'\nconst PLACEMENT_BOTTOMCENTER = 'bottom'\n\nconst Default = {\n autoClose: true,\n boundary: 'clippingParents',\n display: 'dynamic',\n offset: [0, 2],\n popperConfig: null,\n reference: 'toggle'\n}\n\nconst DefaultType = {\n autoClose: '(boolean|string)',\n boundary: '(string|element)',\n display: 'string',\n offset: '(array|string|function)',\n popperConfig: '(null|object|function)',\n reference: '(string|element|object)'\n}\n\n/**\n * Class definition\n */\n\nclass Dropdown extends BaseComponent {\n constructor(element, config) {\n super(element, config)\n\n this._popper = null\n this._parent = this._element.parentNode // dropdown wrapper\n // TODO: v6 revert #37011 & change markup https://getbootstrap.com/docs/5.3/forms/input-group/\n this._menu = SelectorEngine.next(this._element, SELECTOR_MENU)[0] ||\n SelectorEngine.prev(this._element, SELECTOR_MENU)[0] ||\n SelectorEngine.findOne(SELECTOR_MENU, this._parent)\n this._inNavbar = this._detectNavbar()\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n toggle() {\n return this._isShown() ? this.hide() : this.show()\n }\n\n show() {\n if (isDisabled(this._element) || this._isShown()) {\n return\n }\n\n const relatedTarget = {\n relatedTarget: this._element\n }\n\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW, relatedTarget)\n\n if (showEvent.defaultPrevented) {\n return\n }\n\n this._createPopper()\n\n // If this is a touch-enabled device we add extra\n // empty mouseover listeners to the body's immediate children;\n // only needed because of broken event delegation on iOS\n // https://www.quirksmode.org/blog/archives/2014/02/mouse_event_bub.html\n if ('ontouchstart' in document.documentElement && !this._parent.closest(SELECTOR_NAVBAR_NAV)) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.on(element, 'mouseover', noop)\n }\n }\n\n this._element.focus()\n this._element.setAttribute('aria-expanded', true)\n\n this._menu.classList.add(CLASS_NAME_SHOW)\n this._element.classList.add(CLASS_NAME_SHOW)\n EventHandler.trigger(this._element, EVENT_SHOWN, relatedTarget)\n }\n\n hide() {\n if (isDisabled(this._element) || !this._isShown()) {\n return\n }\n\n const relatedTarget = {\n relatedTarget: this._element\n }\n\n this._completeHide(relatedTarget)\n }\n\n dispose() {\n if (this._popper) {\n this._popper.destroy()\n }\n\n super.dispose()\n }\n\n update() {\n this._inNavbar = this._detectNavbar()\n if (this._popper) {\n this._popper.update()\n }\n }\n\n // Private\n _completeHide(relatedTarget) {\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE, relatedTarget)\n if (hideEvent.defaultPrevented) {\n return\n }\n\n // If this is a touch-enabled device we remove the extra\n // empty mouseover listeners we added for iOS support\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.off(element, 'mouseover', noop)\n }\n }\n\n if (this._popper) {\n this._popper.destroy()\n }\n\n this._menu.classList.remove(CLASS_NAME_SHOW)\n this._element.classList.remove(CLASS_NAME_SHOW)\n this._element.setAttribute('aria-expanded', 'false')\n Manipulator.removeDataAttribute(this._menu, 'popper')\n EventHandler.trigger(this._element, EVENT_HIDDEN, relatedTarget)\n }\n\n _getConfig(config) {\n config = super._getConfig(config)\n\n if (typeof config.reference === 'object' && !isElement(config.reference) &&\n typeof config.reference.getBoundingClientRect !== 'function'\n ) {\n // Popper virtual elements require a getBoundingClientRect method\n throw new TypeError(`${NAME.toUpperCase()}: Option \"reference\" provided type \"object\" without a required \"getBoundingClientRect\" method.`)\n }\n\n return config\n }\n\n _createPopper() {\n if (typeof Popper === 'undefined') {\n throw new TypeError('Bootstrap\\'s dropdowns require Popper (https://popper.js.org)')\n }\n\n let referenceElement = this._element\n\n if (this._config.reference === 'parent') {\n referenceElement = this._parent\n } else if (isElement(this._config.reference)) {\n referenceElement = getElement(this._config.reference)\n } else if (typeof this._config.reference === 'object') {\n referenceElement = this._config.reference\n }\n\n const popperConfig = this._getPopperConfig()\n this._popper = Popper.createPopper(referenceElement, this._menu, popperConfig)\n }\n\n _isShown() {\n return this._menu.classList.contains(CLASS_NAME_SHOW)\n }\n\n _getPlacement() {\n const parentDropdown = this._parent\n\n if (parentDropdown.classList.contains(CLASS_NAME_DROPEND)) {\n return PLACEMENT_RIGHT\n }\n\n if (parentDropdown.classList.contains(CLASS_NAME_DROPSTART)) {\n return PLACEMENT_LEFT\n }\n\n if (parentDropdown.classList.contains(CLASS_NAME_DROPUP_CENTER)) {\n return PLACEMENT_TOPCENTER\n }\n\n if (parentDropdown.classList.contains(CLASS_NAME_DROPDOWN_CENTER)) {\n return PLACEMENT_BOTTOMCENTER\n }\n\n // We need to trim the value because custom properties can also include spaces\n const isEnd = getComputedStyle(this._menu).getPropertyValue('--bs-position').trim() === 'end'\n\n if (parentDropdown.classList.contains(CLASS_NAME_DROPUP)) {\n return isEnd ? PLACEMENT_TOPEND : PLACEMENT_TOP\n }\n\n return isEnd ? PLACEMENT_BOTTOMEND : PLACEMENT_BOTTOM\n }\n\n _detectNavbar() {\n return this._element.closest(SELECTOR_NAVBAR) !== null\n }\n\n _getOffset() {\n const { offset } = this._config\n\n if (typeof offset === 'string') {\n return offset.split(',').map(value => Number.parseInt(value, 10))\n }\n\n if (typeof offset === 'function') {\n return popperData => offset(popperData, this._element)\n }\n\n return offset\n }\n\n _getPopperConfig() {\n const defaultBsPopperConfig = {\n placement: this._getPlacement(),\n modifiers: [{\n name: 'preventOverflow',\n options: {\n boundary: this._config.boundary\n }\n },\n {\n name: 'offset',\n options: {\n offset: this._getOffset()\n }\n }]\n }\n\n // Disable Popper if we have a static display or Dropdown is in Navbar\n if (this._inNavbar || this._config.display === 'static') {\n Manipulator.setDataAttribute(this._menu, 'popper', 'static') // TODO: v6 remove\n defaultBsPopperConfig.modifiers = [{\n name: 'applyStyles',\n enabled: false\n }]\n }\n\n return {\n ...defaultBsPopperConfig,\n ...execute(this._config.popperConfig, [defaultBsPopperConfig])\n }\n }\n\n _selectMenuItem({ key, target }) {\n const items = SelectorEngine.find(SELECTOR_VISIBLE_ITEMS, this._menu).filter(element => isVisible(element))\n\n if (!items.length) {\n return\n }\n\n // if target isn't included in items (e.g. when expanding the dropdown)\n // allow cycling to get the last item in case key equals ARROW_UP_KEY\n getNextActiveElement(items, target, key === ARROW_DOWN_KEY, !items.includes(target)).focus()\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Dropdown.getOrCreateInstance(this, config)\n\n if (typeof config !== 'string') {\n return\n }\n\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`)\n }\n\n data[config]()\n })\n }\n\n static clearMenus(event) {\n if (event.button === RIGHT_MOUSE_BUTTON || (event.type === 'keyup' && event.key !== TAB_KEY)) {\n return\n }\n\n const openToggles = SelectorEngine.find(SELECTOR_DATA_TOGGLE_SHOWN)\n\n for (const toggle of openToggles) {\n const context = Dropdown.getInstance(toggle)\n if (!context || context._config.autoClose === false) {\n continue\n }\n\n const composedPath = event.composedPath()\n const isMenuTarget = composedPath.includes(context._menu)\n if (\n composedPath.includes(context._element) ||\n (context._config.autoClose === 'inside' && !isMenuTarget) ||\n (context._config.autoClose === 'outside' && isMenuTarget)\n ) {\n continue\n }\n\n // Tab navigation through the dropdown menu or events from contained inputs shouldn't close the menu\n if (context._menu.contains(event.target) && ((event.type === 'keyup' && event.key === TAB_KEY) || /input|select|option|textarea|form/i.test(event.target.tagName))) {\n continue\n }\n\n const relatedTarget = { relatedTarget: context._element }\n\n if (event.type === 'click') {\n relatedTarget.clickEvent = event\n }\n\n context._completeHide(relatedTarget)\n }\n }\n\n static dataApiKeydownHandler(event) {\n // If not an UP | DOWN | ESCAPE key => not a dropdown command\n // If input/textarea && if key is other than ESCAPE => not a dropdown command\n\n const isInput = /input|textarea/i.test(event.target.tagName)\n const isEscapeEvent = event.key === ESCAPE_KEY\n const isUpOrDownEvent = [ARROW_UP_KEY, ARROW_DOWN_KEY].includes(event.key)\n\n if (!isUpOrDownEvent && !isEscapeEvent) {\n return\n }\n\n if (isInput && !isEscapeEvent) {\n return\n }\n\n event.preventDefault()\n\n // TODO: v6 revert #37011 & change markup https://getbootstrap.com/docs/5.3/forms/input-group/\n const getToggleButton = this.matches(SELECTOR_DATA_TOGGLE) ?\n this :\n (SelectorEngine.prev(this, SELECTOR_DATA_TOGGLE)[0] ||\n SelectorEngine.next(this, SELECTOR_DATA_TOGGLE)[0] ||\n SelectorEngine.findOne(SELECTOR_DATA_TOGGLE, event.delegateTarget.parentNode))\n\n const instance = Dropdown.getOrCreateInstance(getToggleButton)\n\n if (isUpOrDownEvent) {\n event.stopPropagation()\n instance.show()\n instance._selectMenuItem(event)\n return\n }\n\n if (instance._isShown()) { // else is escape and we check if it is shown\n event.stopPropagation()\n instance.hide()\n getToggleButton.focus()\n }\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_KEYDOWN_DATA_API, SELECTOR_DATA_TOGGLE, Dropdown.dataApiKeydownHandler)\nEventHandler.on(document, EVENT_KEYDOWN_DATA_API, SELECTOR_MENU, Dropdown.dataApiKeydownHandler)\nEventHandler.on(document, EVENT_CLICK_DATA_API, Dropdown.clearMenus)\nEventHandler.on(document, EVENT_KEYUP_DATA_API, Dropdown.clearMenus)\nEventHandler.on(document, EVENT_CLICK_DATA_API, SELECTOR_DATA_TOGGLE, function (event) {\n event.preventDefault()\n Dropdown.getOrCreateInstance(this).toggle()\n})\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Dropdown)\n\nexport default Dropdown\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/backdrop.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport EventHandler from '../dom/event-handler.js'\nimport Config from './config.js'\nimport { execute, executeAfterTransition, getElement, reflow } from './index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'backdrop'\nconst CLASS_NAME_FADE = 'fade'\nconst CLASS_NAME_SHOW = 'show'\nconst EVENT_MOUSEDOWN = `mousedown.bs.${NAME}`\n\nconst Default = {\n className: 'modal-backdrop',\n clickCallback: null,\n isAnimated: false,\n isVisible: true, // if false, we use the backdrop helper without adding any element to the dom\n rootElement: 'body' // give the choice to place backdrop under different elements\n}\n\nconst DefaultType = {\n className: 'string',\n clickCallback: '(function|null)',\n isAnimated: 'boolean',\n isVisible: 'boolean',\n rootElement: '(element|string)'\n}\n\n/**\n * Class definition\n */\n\nclass Backdrop extends Config {\n constructor(config) {\n super()\n this._config = this._getConfig(config)\n this._isAppended = false\n this._element = null\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n show(callback) {\n if (!this._config.isVisible) {\n execute(callback)\n return\n }\n\n this._append()\n\n const element = this._getElement()\n if (this._config.isAnimated) {\n reflow(element)\n }\n\n element.classList.add(CLASS_NAME_SHOW)\n\n this._emulateAnimation(() => {\n execute(callback)\n })\n }\n\n hide(callback) {\n if (!this._config.isVisible) {\n execute(callback)\n return\n }\n\n this._getElement().classList.remove(CLASS_NAME_SHOW)\n\n this._emulateAnimation(() => {\n this.dispose()\n execute(callback)\n })\n }\n\n dispose() {\n if (!this._isAppended) {\n return\n }\n\n EventHandler.off(this._element, EVENT_MOUSEDOWN)\n\n this._element.remove()\n this._isAppended = false\n }\n\n // Private\n _getElement() {\n if (!this._element) {\n const backdrop = document.createElement('div')\n backdrop.className = this._config.className\n if (this._config.isAnimated) {\n backdrop.classList.add(CLASS_NAME_FADE)\n }\n\n this._element = backdrop\n }\n\n return this._element\n }\n\n _configAfterMerge(config) {\n // use getElement() with the default \"body\" to get a fresh Element on each instantiation\n config.rootElement = getElement(config.rootElement)\n return config\n }\n\n _append() {\n if (this._isAppended) {\n return\n }\n\n const element = this._getElement()\n this._config.rootElement.append(element)\n\n EventHandler.on(element, EVENT_MOUSEDOWN, () => {\n execute(this._config.clickCallback)\n })\n\n this._isAppended = true\n }\n\n _emulateAnimation(callback) {\n executeAfterTransition(callback, this._getElement(), this._config.isAnimated)\n }\n}\n\nexport default Backdrop\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/focustrap.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport EventHandler from '../dom/event-handler.js'\nimport SelectorEngine from '../dom/selector-engine.js'\nimport Config from './config.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'focustrap'\nconst DATA_KEY = 'bs.focustrap'\nconst EVENT_KEY = `.${DATA_KEY}`\nconst EVENT_FOCUSIN = `focusin${EVENT_KEY}`\nconst EVENT_KEYDOWN_TAB = `keydown.tab${EVENT_KEY}`\n\nconst TAB_KEY = 'Tab'\nconst TAB_NAV_FORWARD = 'forward'\nconst TAB_NAV_BACKWARD = 'backward'\n\nconst Default = {\n autofocus: true,\n trapElement: null // The element to trap focus inside of\n}\n\nconst DefaultType = {\n autofocus: 'boolean',\n trapElement: 'element'\n}\n\n/**\n * Class definition\n */\n\nclass FocusTrap extends Config {\n constructor(config) {\n super()\n this._config = this._getConfig(config)\n this._isActive = false\n this._lastTabNavDirection = null\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n activate() {\n if (this._isActive) {\n return\n }\n\n if (this._config.autofocus) {\n this._config.trapElement.focus()\n }\n\n EventHandler.off(document, EVENT_KEY) // guard against infinite focus loop\n EventHandler.on(document, EVENT_FOCUSIN, event => this._handleFocusin(event))\n EventHandler.on(document, EVENT_KEYDOWN_TAB, event => this._handleKeydown(event))\n\n this._isActive = true\n }\n\n deactivate() {\n if (!this._isActive) {\n return\n }\n\n this._isActive = false\n EventHandler.off(document, EVENT_KEY)\n }\n\n // Private\n _handleFocusin(event) {\n const { trapElement } = this._config\n\n if (event.target === document || event.target === trapElement || trapElement.contains(event.target)) {\n return\n }\n\n const elements = SelectorEngine.focusableChildren(trapElement)\n\n if (elements.length === 0) {\n trapElement.focus()\n } else if (this._lastTabNavDirection === TAB_NAV_BACKWARD) {\n elements[elements.length - 1].focus()\n } else {\n elements[0].focus()\n }\n }\n\n _handleKeydown(event) {\n if (event.key !== TAB_KEY) {\n return\n }\n\n this._lastTabNavDirection = event.shiftKey ? TAB_NAV_BACKWARD : TAB_NAV_FORWARD\n }\n}\n\nexport default FocusTrap\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/scrollBar.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport Manipulator from '../dom/manipulator.js'\nimport SelectorEngine from '../dom/selector-engine.js'\nimport { isElement } from './index.js'\n\n/**\n * Constants\n */\n\nconst SELECTOR_FIXED_CONTENT = '.fixed-top, .fixed-bottom, .is-fixed, .sticky-top'\nconst SELECTOR_STICKY_CONTENT = '.sticky-top'\nconst PROPERTY_PADDING = 'padding-right'\nconst PROPERTY_MARGIN = 'margin-right'\n\n/**\n * Class definition\n */\n\nclass ScrollBarHelper {\n constructor() {\n this._element = document.body\n }\n\n // Public\n getWidth() {\n // https://developer.mozilla.org/en-US/docs/Web/API/Window/innerWidth#usage_notes\n const documentWidth = document.documentElement.clientWidth\n return Math.abs(window.innerWidth - documentWidth)\n }\n\n hide() {\n const width = this.getWidth()\n this._disableOverFlow()\n // give padding to element to balance the hidden scrollbar width\n this._setElementAttributes(this._element, PROPERTY_PADDING, calculatedValue => calculatedValue + width)\n // trick: We adjust positive paddingRight and negative marginRight to sticky-top elements to keep showing fullwidth\n this._setElementAttributes(SELECTOR_FIXED_CONTENT, PROPERTY_PADDING, calculatedValue => calculatedValue + width)\n this._setElementAttributes(SELECTOR_STICKY_CONTENT, PROPERTY_MARGIN, calculatedValue => calculatedValue - width)\n }\n\n reset() {\n this._resetElementAttributes(this._element, 'overflow')\n this._resetElementAttributes(this._element, PROPERTY_PADDING)\n this._resetElementAttributes(SELECTOR_FIXED_CONTENT, PROPERTY_PADDING)\n this._resetElementAttributes(SELECTOR_STICKY_CONTENT, PROPERTY_MARGIN)\n }\n\n isOverflowing() {\n return this.getWidth() > 0\n }\n\n // Private\n _disableOverFlow() {\n this._saveInitialAttribute(this._element, 'overflow')\n this._element.style.overflow = 'hidden'\n }\n\n _setElementAttributes(selector, styleProperty, callback) {\n const scrollbarWidth = this.getWidth()\n const manipulationCallBack = element => {\n if (element !== this._element && window.innerWidth > element.clientWidth + scrollbarWidth) {\n return\n }\n\n this._saveInitialAttribute(element, styleProperty)\n const calculatedValue = window.getComputedStyle(element).getPropertyValue(styleProperty)\n element.style.setProperty(styleProperty, `${callback(Number.parseFloat(calculatedValue))}px`)\n }\n\n this._applyManipulationCallback(selector, manipulationCallBack)\n }\n\n _saveInitialAttribute(element, styleProperty) {\n const actualValue = element.style.getPropertyValue(styleProperty)\n if (actualValue) {\n Manipulator.setDataAttribute(element, styleProperty, actualValue)\n }\n }\n\n _resetElementAttributes(selector, styleProperty) {\n const manipulationCallBack = element => {\n const value = Manipulator.getDataAttribute(element, styleProperty)\n // We only want to remove the property if the value is `null`; the value can also be zero\n if (value === null) {\n element.style.removeProperty(styleProperty)\n return\n }\n\n Manipulator.removeDataAttribute(element, styleProperty)\n element.style.setProperty(styleProperty, value)\n }\n\n this._applyManipulationCallback(selector, manipulationCallBack)\n }\n\n _applyManipulationCallback(selector, callBack) {\n if (isElement(selector)) {\n callBack(selector)\n return\n }\n\n for (const sel of SelectorEngine.find(selector, this._element)) {\n callBack(sel)\n }\n }\n}\n\nexport default ScrollBarHelper\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap modal.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport SelectorEngine from './dom/selector-engine.js'\nimport Backdrop from './util/backdrop.js'\nimport { enableDismissTrigger } from './util/component-functions.js'\nimport FocusTrap from './util/focustrap.js'\nimport { defineJQueryPlugin, isRTL, isVisible, reflow } from './util/index.js'\nimport ScrollBarHelper from './util/scrollbar.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'modal'\nconst DATA_KEY = 'bs.modal'\nconst EVENT_KEY = `.${DATA_KEY}`\nconst DATA_API_KEY = '.data-api'\nconst ESCAPE_KEY = 'Escape'\n\nconst EVENT_HIDE = `hide${EVENT_KEY}`\nconst EVENT_HIDE_PREVENTED = `hidePrevented${EVENT_KEY}`\nconst EVENT_HIDDEN = `hidden${EVENT_KEY}`\nconst EVENT_SHOW = `show${EVENT_KEY}`\nconst EVENT_SHOWN = `shown${EVENT_KEY}`\nconst EVENT_RESIZE = `resize${EVENT_KEY}`\nconst EVENT_CLICK_DISMISS = `click.dismiss${EVENT_KEY}`\nconst EVENT_MOUSEDOWN_DISMISS = `mousedown.dismiss${EVENT_KEY}`\nconst EVENT_KEYDOWN_DISMISS = `keydown.dismiss${EVENT_KEY}`\nconst EVENT_CLICK_DATA_API = `click${EVENT_KEY}${DATA_API_KEY}`\n\nconst CLASS_NAME_OPEN = 'modal-open'\nconst CLASS_NAME_FADE = 'fade'\nconst CLASS_NAME_SHOW = 'show'\nconst CLASS_NAME_STATIC = 'modal-static'\n\nconst OPEN_SELECTOR = '.modal.show'\nconst SELECTOR_DIALOG = '.modal-dialog'\nconst SELECTOR_MODAL_BODY = '.modal-body'\nconst SELECTOR_DATA_TOGGLE = '[data-bs-toggle=\"modal\"]'\n\nconst Default = {\n backdrop: true,\n focus: true,\n keyboard: true\n}\n\nconst DefaultType = {\n backdrop: '(boolean|string)',\n focus: 'boolean',\n keyboard: 'boolean'\n}\n\n/**\n * Class definition\n */\n\nclass Modal extends BaseComponent {\n constructor(element, config) {\n super(element, config)\n\n this._dialog = SelectorEngine.findOne(SELECTOR_DIALOG, this._element)\n this._backdrop = this._initializeBackDrop()\n this._focustrap = this._initializeFocusTrap()\n this._isShown = false\n this._isTransitioning = false\n this._scrollBar = new ScrollBarHelper()\n\n this._addEventListeners()\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n toggle(relatedTarget) {\n return this._isShown ? this.hide() : this.show(relatedTarget)\n }\n\n show(relatedTarget) {\n if (this._isShown || this._isTransitioning) {\n return\n }\n\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW, {\n relatedTarget\n })\n\n if (showEvent.defaultPrevented) {\n return\n }\n\n this._isShown = true\n this._isTransitioning = true\n\n this._scrollBar.hide()\n\n document.body.classList.add(CLASS_NAME_OPEN)\n\n this._adjustDialog()\n\n this._backdrop.show(() => this._showElement(relatedTarget))\n }\n\n hide() {\n if (!this._isShown || this._isTransitioning) {\n return\n }\n\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE)\n\n if (hideEvent.defaultPrevented) {\n return\n }\n\n this._isShown = false\n this._isTransitioning = true\n this._focustrap.deactivate()\n\n this._element.classList.remove(CLASS_NAME_SHOW)\n\n this._queueCallback(() => this._hideModal(), this._element, this._isAnimated())\n }\n\n dispose() {\n EventHandler.off(window, EVENT_KEY)\n EventHandler.off(this._dialog, EVENT_KEY)\n\n this._backdrop.dispose()\n this._focustrap.deactivate()\n\n super.dispose()\n }\n\n handleUpdate() {\n this._adjustDialog()\n }\n\n // Private\n _initializeBackDrop() {\n return new Backdrop({\n isVisible: Boolean(this._config.backdrop), // 'static' option will be translated to true, and booleans will keep their value,\n isAnimated: this._isAnimated()\n })\n }\n\n _initializeFocusTrap() {\n return new FocusTrap({\n trapElement: this._element\n })\n }\n\n _showElement(relatedTarget) {\n // try to append dynamic modal\n if (!document.body.contains(this._element)) {\n document.body.append(this._element)\n }\n\n this._element.style.display = 'block'\n this._element.removeAttribute('aria-hidden')\n this._element.setAttribute('aria-modal', true)\n this._element.setAttribute('role', 'dialog')\n this._element.scrollTop = 0\n\n const modalBody = SelectorEngine.findOne(SELECTOR_MODAL_BODY, this._dialog)\n if (modalBody) {\n modalBody.scrollTop = 0\n }\n\n reflow(this._element)\n\n this._element.classList.add(CLASS_NAME_SHOW)\n\n const transitionComplete = () => {\n if (this._config.focus) {\n this._focustrap.activate()\n }\n\n this._isTransitioning = false\n EventHandler.trigger(this._element, EVENT_SHOWN, {\n relatedTarget\n })\n }\n\n this._queueCallback(transitionComplete, this._dialog, this._isAnimated())\n }\n\n _addEventListeners() {\n EventHandler.on(this._element, EVENT_KEYDOWN_DISMISS, event => {\n if (event.key !== ESCAPE_KEY) {\n return\n }\n\n if (this._config.keyboard) {\n this.hide()\n return\n }\n\n this._triggerBackdropTransition()\n })\n\n EventHandler.on(window, EVENT_RESIZE, () => {\n if (this._isShown && !this._isTransitioning) {\n this._adjustDialog()\n }\n })\n\n EventHandler.on(this._element, EVENT_MOUSEDOWN_DISMISS, event => {\n // a bad trick to segregate clicks that may start inside dialog but end outside, and avoid listen to scrollbar clicks\n EventHandler.one(this._element, EVENT_CLICK_DISMISS, event2 => {\n if (this._element !== event.target || this._element !== event2.target) {\n return\n }\n\n if (this._config.backdrop === 'static') {\n this._triggerBackdropTransition()\n return\n }\n\n if (this._config.backdrop) {\n this.hide()\n }\n })\n })\n }\n\n _hideModal() {\n this._element.style.display = 'none'\n this._element.setAttribute('aria-hidden', true)\n this._element.removeAttribute('aria-modal')\n this._element.removeAttribute('role')\n this._isTransitioning = false\n\n this._backdrop.hide(() => {\n document.body.classList.remove(CLASS_NAME_OPEN)\n this._resetAdjustments()\n this._scrollBar.reset()\n EventHandler.trigger(this._element, EVENT_HIDDEN)\n })\n }\n\n _isAnimated() {\n return this._element.classList.contains(CLASS_NAME_FADE)\n }\n\n _triggerBackdropTransition() {\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED)\n if (hideEvent.defaultPrevented) {\n return\n }\n\n const isModalOverflowing = this._element.scrollHeight > document.documentElement.clientHeight\n const initialOverflowY = this._element.style.overflowY\n // return if the following background transition hasn't yet completed\n if (initialOverflowY === 'hidden' || this._element.classList.contains(CLASS_NAME_STATIC)) {\n return\n }\n\n if (!isModalOverflowing) {\n this._element.style.overflowY = 'hidden'\n }\n\n this._element.classList.add(CLASS_NAME_STATIC)\n this._queueCallback(() => {\n this._element.classList.remove(CLASS_NAME_STATIC)\n this._queueCallback(() => {\n this._element.style.overflowY = initialOverflowY\n }, this._dialog)\n }, this._dialog)\n\n this._element.focus()\n }\n\n /**\n * The following methods are used to handle overflowing modals\n */\n\n _adjustDialog() {\n const isModalOverflowing = this._element.scrollHeight > document.documentElement.clientHeight\n const scrollbarWidth = this._scrollBar.getWidth()\n const isBodyOverflowing = scrollbarWidth > 0\n\n if (isBodyOverflowing && !isModalOverflowing) {\n const property = isRTL() ? 'paddingLeft' : 'paddingRight'\n this._element.style[property] = `${scrollbarWidth}px`\n }\n\n if (!isBodyOverflowing && isModalOverflowing) {\n const property = isRTL() ? 'paddingRight' : 'paddingLeft'\n this._element.style[property] = `${scrollbarWidth}px`\n }\n }\n\n _resetAdjustments() {\n this._element.style.paddingLeft = ''\n this._element.style.paddingRight = ''\n }\n\n // Static\n static jQueryInterface(config, relatedTarget) {\n return this.each(function () {\n const data = Modal.getOrCreateInstance(this, config)\n\n if (typeof config !== 'string') {\n return\n }\n\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`)\n }\n\n data[config](relatedTarget)\n })\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API, SELECTOR_DATA_TOGGLE, function (event) {\n const target = SelectorEngine.getElementFromSelector(this)\n\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault()\n }\n\n EventHandler.one(target, EVENT_SHOW, showEvent => {\n if (showEvent.defaultPrevented) {\n // only register focus restorer if modal will actually get shown\n return\n }\n\n EventHandler.one(target, EVENT_HIDDEN, () => {\n if (isVisible(this)) {\n this.focus()\n }\n })\n })\n\n // avoid conflict when clicking modal toggler while another one is open\n const alreadyOpen = SelectorEngine.findOne(OPEN_SELECTOR)\n if (alreadyOpen) {\n Modal.getInstance(alreadyOpen).hide()\n }\n\n const data = Modal.getOrCreateInstance(target)\n\n data.toggle(this)\n})\n\nenableDismissTrigger(Modal)\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Modal)\n\nexport default Modal\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap offcanvas.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport SelectorEngine from './dom/selector-engine.js'\nimport Backdrop from './util/backdrop.js'\nimport { enableDismissTrigger } from './util/component-functions.js'\nimport FocusTrap from './util/focustrap.js'\nimport {\n defineJQueryPlugin,\n isDisabled,\n isVisible\n} from './util/index.js'\nimport ScrollBarHelper from './util/scrollbar.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'offcanvas'\nconst DATA_KEY = 'bs.offcanvas'\nconst EVENT_KEY = `.${DATA_KEY}`\nconst DATA_API_KEY = '.data-api'\nconst EVENT_LOAD_DATA_API = `load${EVENT_KEY}${DATA_API_KEY}`\nconst ESCAPE_KEY = 'Escape'\n\nconst CLASS_NAME_SHOW = 'show'\nconst CLASS_NAME_SHOWING = 'showing'\nconst CLASS_NAME_HIDING = 'hiding'\nconst CLASS_NAME_BACKDROP = 'offcanvas-backdrop'\nconst OPEN_SELECTOR = '.offcanvas.show'\n\nconst EVENT_SHOW = `show${EVENT_KEY}`\nconst EVENT_SHOWN = `shown${EVENT_KEY}`\nconst EVENT_HIDE = `hide${EVENT_KEY}`\nconst EVENT_HIDE_PREVENTED = `hidePrevented${EVENT_KEY}`\nconst EVENT_HIDDEN = `hidden${EVENT_KEY}`\nconst EVENT_RESIZE = `resize${EVENT_KEY}`\nconst EVENT_CLICK_DATA_API = `click${EVENT_KEY}${DATA_API_KEY}`\nconst EVENT_KEYDOWN_DISMISS = `keydown.dismiss${EVENT_KEY}`\n\nconst SELECTOR_DATA_TOGGLE = '[data-bs-toggle=\"offcanvas\"]'\n\nconst Default = {\n backdrop: true,\n keyboard: true,\n scroll: false\n}\n\nconst DefaultType = {\n backdrop: '(boolean|string)',\n keyboard: 'boolean',\n scroll: 'boolean'\n}\n\n/**\n * Class definition\n */\n\nclass Offcanvas extends BaseComponent {\n constructor(element, config) {\n super(element, config)\n\n this._isShown = false\n this._backdrop = this._initializeBackDrop()\n this._focustrap = this._initializeFocusTrap()\n this._addEventListeners()\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n toggle(relatedTarget) {\n return this._isShown ? this.hide() : this.show(relatedTarget)\n }\n\n show(relatedTarget) {\n if (this._isShown) {\n return\n }\n\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW, { relatedTarget })\n\n if (showEvent.defaultPrevented) {\n return\n }\n\n this._isShown = true\n this._backdrop.show()\n\n if (!this._config.scroll) {\n new ScrollBarHelper().hide()\n }\n\n this._element.setAttribute('aria-modal', true)\n this._element.setAttribute('role', 'dialog')\n this._element.classList.add(CLASS_NAME_SHOWING)\n\n const completeCallBack = () => {\n if (!this._config.scroll || this._config.backdrop) {\n this._focustrap.activate()\n }\n\n this._element.classList.add(CLASS_NAME_SHOW)\n this._element.classList.remove(CLASS_NAME_SHOWING)\n EventHandler.trigger(this._element, EVENT_SHOWN, { relatedTarget })\n }\n\n this._queueCallback(completeCallBack, this._element, true)\n }\n\n hide() {\n if (!this._isShown) {\n return\n }\n\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE)\n\n if (hideEvent.defaultPrevented) {\n return\n }\n\n this._focustrap.deactivate()\n this._element.blur()\n this._isShown = false\n this._element.classList.add(CLASS_NAME_HIDING)\n this._backdrop.hide()\n\n const completeCallback = () => {\n this._element.classList.remove(CLASS_NAME_SHOW, CLASS_NAME_HIDING)\n this._element.removeAttribute('aria-modal')\n this._element.removeAttribute('role')\n\n if (!this._config.scroll) {\n new ScrollBarHelper().reset()\n }\n\n EventHandler.trigger(this._element, EVENT_HIDDEN)\n }\n\n this._queueCallback(completeCallback, this._element, true)\n }\n\n dispose() {\n this._backdrop.dispose()\n this._focustrap.deactivate()\n super.dispose()\n }\n\n // Private\n _initializeBackDrop() {\n const clickCallback = () => {\n if (this._config.backdrop === 'static') {\n EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED)\n return\n }\n\n this.hide()\n }\n\n // 'static' option will be translated to true, and booleans will keep their value\n const isVisible = Boolean(this._config.backdrop)\n\n return new Backdrop({\n className: CLASS_NAME_BACKDROP,\n isVisible,\n isAnimated: true,\n rootElement: this._element.parentNode,\n clickCallback: isVisible ? clickCallback : null\n })\n }\n\n _initializeFocusTrap() {\n return new FocusTrap({\n trapElement: this._element\n })\n }\n\n _addEventListeners() {\n EventHandler.on(this._element, EVENT_KEYDOWN_DISMISS, event => {\n if (event.key !== ESCAPE_KEY) {\n return\n }\n\n if (this._config.keyboard) {\n this.hide()\n return\n }\n\n EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED)\n })\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Offcanvas.getOrCreateInstance(this, config)\n\n if (typeof config !== 'string') {\n return\n }\n\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`)\n }\n\n data[config](this)\n })\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API, SELECTOR_DATA_TOGGLE, function (event) {\n const target = SelectorEngine.getElementFromSelector(this)\n\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault()\n }\n\n if (isDisabled(this)) {\n return\n }\n\n EventHandler.one(target, EVENT_HIDDEN, () => {\n // focus on trigger when it is closed\n if (isVisible(this)) {\n this.focus()\n }\n })\n\n // avoid conflict when clicking a toggler of an offcanvas, while another is open\n const alreadyOpen = SelectorEngine.findOne(OPEN_SELECTOR)\n if (alreadyOpen && alreadyOpen !== target) {\n Offcanvas.getInstance(alreadyOpen).hide()\n }\n\n const data = Offcanvas.getOrCreateInstance(target)\n data.toggle(this)\n})\n\nEventHandler.on(window, EVENT_LOAD_DATA_API, () => {\n for (const selector of SelectorEngine.find(OPEN_SELECTOR)) {\n Offcanvas.getOrCreateInstance(selector).show()\n }\n})\n\nEventHandler.on(window, EVENT_RESIZE, () => {\n for (const element of SelectorEngine.find('[aria-modal][class*=show][class*=offcanvas-]')) {\n if (getComputedStyle(element).position !== 'fixed') {\n Offcanvas.getOrCreateInstance(element).hide()\n }\n }\n})\n\nenableDismissTrigger(Offcanvas)\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Offcanvas)\n\nexport default Offcanvas\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/sanitizer.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n// js-docs-start allow-list\nconst ARIA_ATTRIBUTE_PATTERN = /^aria-[\\w-]*$/i\n\nexport const DefaultAllowlist = {\n // Global attributes allowed on any supplied element below.\n '*': ['class', 'dir', 'id', 'lang', 'role', ARIA_ATTRIBUTE_PATTERN],\n a: ['target', 'href', 'title', 'rel'],\n area: [],\n b: [],\n br: [],\n col: [],\n code: [],\n div: [],\n em: [],\n hr: [],\n h1: [],\n h2: [],\n h3: [],\n h4: [],\n h5: [],\n h6: [],\n i: [],\n img: ['src', 'srcset', 'alt', 'title', 'width', 'height'],\n li: [],\n ol: [],\n p: [],\n pre: [],\n s: [],\n small: [],\n span: [],\n sub: [],\n sup: [],\n strong: [],\n u: [],\n ul: []\n}\n// js-docs-end allow-list\n\nconst uriAttributes = new Set([\n 'background',\n 'cite',\n 'href',\n 'itemtype',\n 'longdesc',\n 'poster',\n 'src',\n 'xlink:href'\n])\n\n/**\n * A pattern that recognizes URLs that are safe wrt. XSS in URL navigation\n * contexts.\n *\n * Shout-out to Angular https://github.com/angular/angular/blob/15.2.8/packages/core/src/sanitization/url_sanitizer.ts#L38\n */\n// eslint-disable-next-line unicorn/better-regex\nconst SAFE_URL_PATTERN = /^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i\n\nconst allowedAttribute = (attribute, allowedAttributeList) => {\n const attributeName = attribute.nodeName.toLowerCase()\n\n if (allowedAttributeList.includes(attributeName)) {\n if (uriAttributes.has(attributeName)) {\n return Boolean(SAFE_URL_PATTERN.test(attribute.nodeValue))\n }\n\n return true\n }\n\n // Check if a regular expression validates the attribute.\n return allowedAttributeList.filter(attributeRegex => attributeRegex instanceof RegExp)\n .some(regex => regex.test(attributeName))\n}\n\nexport function sanitizeHtml(unsafeHtml, allowList, sanitizeFunction) {\n if (!unsafeHtml.length) {\n return unsafeHtml\n }\n\n if (sanitizeFunction && typeof sanitizeFunction === 'function') {\n return sanitizeFunction(unsafeHtml)\n }\n\n const domParser = new window.DOMParser()\n const createdDocument = domParser.parseFromString(unsafeHtml, 'text/html')\n const elements = [].concat(...createdDocument.body.querySelectorAll('*'))\n\n for (const element of elements) {\n const elementName = element.nodeName.toLowerCase()\n\n if (!Object.keys(allowList).includes(elementName)) {\n element.remove()\n continue\n }\n\n const attributeList = [].concat(...element.attributes)\n const allowedAttributes = [].concat(allowList['*'] || [], allowList[elementName] || [])\n\n for (const attribute of attributeList) {\n if (!allowedAttribute(attribute, allowedAttributes)) {\n element.removeAttribute(attribute.nodeName)\n }\n }\n }\n\n return createdDocument.body.innerHTML\n}\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap util/template-factory.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport SelectorEngine from '../dom/selector-engine.js'\nimport Config from './config.js'\nimport { DefaultAllowlist, sanitizeHtml } from './sanitizer.js'\nimport { execute, getElement, isElement } from './index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'TemplateFactory'\n\nconst Default = {\n allowList: DefaultAllowlist,\n content: {}, // { selector : text , selector2 : text2 , }\n extraClass: '',\n html: false,\n sanitize: true,\n sanitizeFn: null,\n template: '
          '\n}\n\nconst DefaultType = {\n allowList: 'object',\n content: 'object',\n extraClass: '(string|function)',\n html: 'boolean',\n sanitize: 'boolean',\n sanitizeFn: '(null|function)',\n template: 'string'\n}\n\nconst DefaultContentType = {\n entry: '(string|element|function|null)',\n selector: '(string|element)'\n}\n\n/**\n * Class definition\n */\n\nclass TemplateFactory extends Config {\n constructor(config) {\n super()\n this._config = this._getConfig(config)\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n getContent() {\n return Object.values(this._config.content)\n .map(config => this._resolvePossibleFunction(config))\n .filter(Boolean)\n }\n\n hasContent() {\n return this.getContent().length > 0\n }\n\n changeContent(content) {\n this._checkContent(content)\n this._config.content = { ...this._config.content, ...content }\n return this\n }\n\n toHtml() {\n const templateWrapper = document.createElement('div')\n templateWrapper.innerHTML = this._maybeSanitize(this._config.template)\n\n for (const [selector, text] of Object.entries(this._config.content)) {\n this._setContent(templateWrapper, text, selector)\n }\n\n const template = templateWrapper.children[0]\n const extraClass = this._resolvePossibleFunction(this._config.extraClass)\n\n if (extraClass) {\n template.classList.add(...extraClass.split(' '))\n }\n\n return template\n }\n\n // Private\n _typeCheckConfig(config) {\n super._typeCheckConfig(config)\n this._checkContent(config.content)\n }\n\n _checkContent(arg) {\n for (const [selector, content] of Object.entries(arg)) {\n super._typeCheckConfig({ selector, entry: content }, DefaultContentType)\n }\n }\n\n _setContent(template, content, selector) {\n const templateElement = SelectorEngine.findOne(selector, template)\n\n if (!templateElement) {\n return\n }\n\n content = this._resolvePossibleFunction(content)\n\n if (!content) {\n templateElement.remove()\n return\n }\n\n if (isElement(content)) {\n this._putElementInTemplate(getElement(content), templateElement)\n return\n }\n\n if (this._config.html) {\n templateElement.innerHTML = this._maybeSanitize(content)\n return\n }\n\n templateElement.textContent = content\n }\n\n _maybeSanitize(arg) {\n return this._config.sanitize ? sanitizeHtml(arg, this._config.allowList, this._config.sanitizeFn) : arg\n }\n\n _resolvePossibleFunction(arg) {\n return execute(arg, [this])\n }\n\n _putElementInTemplate(element, templateElement) {\n if (this._config.html) {\n templateElement.innerHTML = ''\n templateElement.append(element)\n return\n }\n\n templateElement.textContent = element.textContent\n }\n}\n\nexport default TemplateFactory\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap tooltip.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport * as Popper from '@popperjs/core'\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport Manipulator from './dom/manipulator.js'\nimport { defineJQueryPlugin, execute, findShadowRoot, getElement, getUID, isRTL, noop } from './util/index.js'\nimport { DefaultAllowlist } from './util/sanitizer.js'\nimport TemplateFactory from './util/template-factory.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'tooltip'\nconst DISALLOWED_ATTRIBUTES = new Set(['sanitize', 'allowList', 'sanitizeFn'])\n\nconst CLASS_NAME_FADE = 'fade'\nconst CLASS_NAME_MODAL = 'modal'\nconst CLASS_NAME_SHOW = 'show'\n\nconst SELECTOR_TOOLTIP_INNER = '.tooltip-inner'\nconst SELECTOR_MODAL = `.${CLASS_NAME_MODAL}`\n\nconst EVENT_MODAL_HIDE = 'hide.bs.modal'\n\nconst TRIGGER_HOVER = 'hover'\nconst TRIGGER_FOCUS = 'focus'\nconst TRIGGER_CLICK = 'click'\nconst TRIGGER_MANUAL = 'manual'\n\nconst EVENT_HIDE = 'hide'\nconst EVENT_HIDDEN = 'hidden'\nconst EVENT_SHOW = 'show'\nconst EVENT_SHOWN = 'shown'\nconst EVENT_INSERTED = 'inserted'\nconst EVENT_CLICK = 'click'\nconst EVENT_FOCUSIN = 'focusin'\nconst EVENT_FOCUSOUT = 'focusout'\nconst EVENT_MOUSEENTER = 'mouseenter'\nconst EVENT_MOUSELEAVE = 'mouseleave'\n\nconst AttachmentMap = {\n AUTO: 'auto',\n TOP: 'top',\n RIGHT: isRTL() ? 'left' : 'right',\n BOTTOM: 'bottom',\n LEFT: isRTL() ? 'right' : 'left'\n}\n\nconst Default = {\n allowList: DefaultAllowlist,\n animation: true,\n boundary: 'clippingParents',\n container: false,\n customClass: '',\n delay: 0,\n fallbackPlacements: ['top', 'right', 'bottom', 'left'],\n html: false,\n offset: [0, 6],\n placement: 'top',\n popperConfig: null,\n sanitize: true,\n sanitizeFn: null,\n selector: false,\n template: '
          ' +\n '
          ' +\n '
          ' +\n '
          ',\n title: '',\n trigger: 'hover focus'\n}\n\nconst DefaultType = {\n allowList: 'object',\n animation: 'boolean',\n boundary: '(string|element)',\n container: '(string|element|boolean)',\n customClass: '(string|function)',\n delay: '(number|object)',\n fallbackPlacements: 'array',\n html: 'boolean',\n offset: '(array|string|function)',\n placement: '(string|function)',\n popperConfig: '(null|object|function)',\n sanitize: 'boolean',\n sanitizeFn: '(null|function)',\n selector: '(string|boolean)',\n template: 'string',\n title: '(string|element|function)',\n trigger: 'string'\n}\n\n/**\n * Class definition\n */\n\nclass Tooltip extends BaseComponent {\n constructor(element, config) {\n if (typeof Popper === 'undefined') {\n throw new TypeError('Bootstrap\\'s tooltips require Popper (https://popper.js.org)')\n }\n\n super(element, config)\n\n // Private\n this._isEnabled = true\n this._timeout = 0\n this._isHovered = null\n this._activeTrigger = {}\n this._popper = null\n this._templateFactory = null\n this._newContent = null\n\n // Protected\n this.tip = null\n\n this._setListeners()\n\n if (!this._config.selector) {\n this._fixTitle()\n }\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n enable() {\n this._isEnabled = true\n }\n\n disable() {\n this._isEnabled = false\n }\n\n toggleEnabled() {\n this._isEnabled = !this._isEnabled\n }\n\n toggle() {\n if (!this._isEnabled) {\n return\n }\n\n this._activeTrigger.click = !this._activeTrigger.click\n if (this._isShown()) {\n this._leave()\n return\n }\n\n this._enter()\n }\n\n dispose() {\n clearTimeout(this._timeout)\n\n EventHandler.off(this._element.closest(SELECTOR_MODAL), EVENT_MODAL_HIDE, this._hideModalHandler)\n\n if (this._element.getAttribute('data-bs-original-title')) {\n this._element.setAttribute('title', this._element.getAttribute('data-bs-original-title'))\n }\n\n this._disposePopper()\n super.dispose()\n }\n\n show() {\n if (this._element.style.display === 'none') {\n throw new Error('Please use show on visible elements')\n }\n\n if (!(this._isWithContent() && this._isEnabled)) {\n return\n }\n\n const showEvent = EventHandler.trigger(this._element, this.constructor.eventName(EVENT_SHOW))\n const shadowRoot = findShadowRoot(this._element)\n const isInTheDom = (shadowRoot || this._element.ownerDocument.documentElement).contains(this._element)\n\n if (showEvent.defaultPrevented || !isInTheDom) {\n return\n }\n\n // TODO: v6 remove this or make it optional\n this._disposePopper()\n\n const tip = this._getTipElement()\n\n this._element.setAttribute('aria-describedby', tip.getAttribute('id'))\n\n const { container } = this._config\n\n if (!this._element.ownerDocument.documentElement.contains(this.tip)) {\n container.append(tip)\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_INSERTED))\n }\n\n this._popper = this._createPopper(tip)\n\n tip.classList.add(CLASS_NAME_SHOW)\n\n // If this is a touch-enabled device we add extra\n // empty mouseover listeners to the body's immediate children;\n // only needed because of broken event delegation on iOS\n // https://www.quirksmode.org/blog/archives/2014/02/mouse_event_bub.html\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.on(element, 'mouseover', noop)\n }\n }\n\n const complete = () => {\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_SHOWN))\n\n if (this._isHovered === false) {\n this._leave()\n }\n\n this._isHovered = false\n }\n\n this._queueCallback(complete, this.tip, this._isAnimated())\n }\n\n hide() {\n if (!this._isShown()) {\n return\n }\n\n const hideEvent = EventHandler.trigger(this._element, this.constructor.eventName(EVENT_HIDE))\n if (hideEvent.defaultPrevented) {\n return\n }\n\n const tip = this._getTipElement()\n tip.classList.remove(CLASS_NAME_SHOW)\n\n // If this is a touch-enabled device we remove the extra\n // empty mouseover listeners we added for iOS support\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.off(element, 'mouseover', noop)\n }\n }\n\n this._activeTrigger[TRIGGER_CLICK] = false\n this._activeTrigger[TRIGGER_FOCUS] = false\n this._activeTrigger[TRIGGER_HOVER] = false\n this._isHovered = null // it is a trick to support manual triggering\n\n const complete = () => {\n if (this._isWithActiveTrigger()) {\n return\n }\n\n if (!this._isHovered) {\n this._disposePopper()\n }\n\n this._element.removeAttribute('aria-describedby')\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_HIDDEN))\n }\n\n this._queueCallback(complete, this.tip, this._isAnimated())\n }\n\n update() {\n if (this._popper) {\n this._popper.update()\n }\n }\n\n // Protected\n _isWithContent() {\n return Boolean(this._getTitle())\n }\n\n _getTipElement() {\n if (!this.tip) {\n this.tip = this._createTipElement(this._newContent || this._getContentForTemplate())\n }\n\n return this.tip\n }\n\n _createTipElement(content) {\n const tip = this._getTemplateFactory(content).toHtml()\n\n // TODO: remove this check in v6\n if (!tip) {\n return null\n }\n\n tip.classList.remove(CLASS_NAME_FADE, CLASS_NAME_SHOW)\n // TODO: v6 the following can be achieved with CSS only\n tip.classList.add(`bs-${this.constructor.NAME}-auto`)\n\n const tipId = getUID(this.constructor.NAME).toString()\n\n tip.setAttribute('id', tipId)\n\n if (this._isAnimated()) {\n tip.classList.add(CLASS_NAME_FADE)\n }\n\n return tip\n }\n\n setContent(content) {\n this._newContent = content\n if (this._isShown()) {\n this._disposePopper()\n this.show()\n }\n }\n\n _getTemplateFactory(content) {\n if (this._templateFactory) {\n this._templateFactory.changeContent(content)\n } else {\n this._templateFactory = new TemplateFactory({\n ...this._config,\n // the `content` var has to be after `this._config`\n // to override config.content in case of popover\n content,\n extraClass: this._resolvePossibleFunction(this._config.customClass)\n })\n }\n\n return this._templateFactory\n }\n\n _getContentForTemplate() {\n return {\n [SELECTOR_TOOLTIP_INNER]: this._getTitle()\n }\n }\n\n _getTitle() {\n return this._resolvePossibleFunction(this._config.title) || this._element.getAttribute('data-bs-original-title')\n }\n\n // Private\n _initializeOnDelegatedTarget(event) {\n return this.constructor.getOrCreateInstance(event.delegateTarget, this._getDelegateConfig())\n }\n\n _isAnimated() {\n return this._config.animation || (this.tip && this.tip.classList.contains(CLASS_NAME_FADE))\n }\n\n _isShown() {\n return this.tip && this.tip.classList.contains(CLASS_NAME_SHOW)\n }\n\n _createPopper(tip) {\n const placement = execute(this._config.placement, [this, tip, this._element])\n const attachment = AttachmentMap[placement.toUpperCase()]\n return Popper.createPopper(this._element, tip, this._getPopperConfig(attachment))\n }\n\n _getOffset() {\n const { offset } = this._config\n\n if (typeof offset === 'string') {\n return offset.split(',').map(value => Number.parseInt(value, 10))\n }\n\n if (typeof offset === 'function') {\n return popperData => offset(popperData, this._element)\n }\n\n return offset\n }\n\n _resolvePossibleFunction(arg) {\n return execute(arg, [this._element])\n }\n\n _getPopperConfig(attachment) {\n const defaultBsPopperConfig = {\n placement: attachment,\n modifiers: [\n {\n name: 'flip',\n options: {\n fallbackPlacements: this._config.fallbackPlacements\n }\n },\n {\n name: 'offset',\n options: {\n offset: this._getOffset()\n }\n },\n {\n name: 'preventOverflow',\n options: {\n boundary: this._config.boundary\n }\n },\n {\n name: 'arrow',\n options: {\n element: `.${this.constructor.NAME}-arrow`\n }\n },\n {\n name: 'preSetPlacement',\n enabled: true,\n phase: 'beforeMain',\n fn: data => {\n // Pre-set Popper's placement attribute in order to read the arrow sizes properly.\n // Otherwise, Popper mixes up the width and height dimensions since the initial arrow style is for top placement\n this._getTipElement().setAttribute('data-popper-placement', data.state.placement)\n }\n }\n ]\n }\n\n return {\n ...defaultBsPopperConfig,\n ...execute(this._config.popperConfig, [defaultBsPopperConfig])\n }\n }\n\n _setListeners() {\n const triggers = this._config.trigger.split(' ')\n\n for (const trigger of triggers) {\n if (trigger === 'click') {\n EventHandler.on(this._element, this.constructor.eventName(EVENT_CLICK), this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event)\n context.toggle()\n })\n } else if (trigger !== TRIGGER_MANUAL) {\n const eventIn = trigger === TRIGGER_HOVER ?\n this.constructor.eventName(EVENT_MOUSEENTER) :\n this.constructor.eventName(EVENT_FOCUSIN)\n const eventOut = trigger === TRIGGER_HOVER ?\n this.constructor.eventName(EVENT_MOUSELEAVE) :\n this.constructor.eventName(EVENT_FOCUSOUT)\n\n EventHandler.on(this._element, eventIn, this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event)\n context._activeTrigger[event.type === 'focusin' ? TRIGGER_FOCUS : TRIGGER_HOVER] = true\n context._enter()\n })\n EventHandler.on(this._element, eventOut, this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event)\n context._activeTrigger[event.type === 'focusout' ? TRIGGER_FOCUS : TRIGGER_HOVER] =\n context._element.contains(event.relatedTarget)\n\n context._leave()\n })\n }\n }\n\n this._hideModalHandler = () => {\n if (this._element) {\n this.hide()\n }\n }\n\n EventHandler.on(this._element.closest(SELECTOR_MODAL), EVENT_MODAL_HIDE, this._hideModalHandler)\n }\n\n _fixTitle() {\n const title = this._element.getAttribute('title')\n\n if (!title) {\n return\n }\n\n if (!this._element.getAttribute('aria-label') && !this._element.textContent.trim()) {\n this._element.setAttribute('aria-label', title)\n }\n\n this._element.setAttribute('data-bs-original-title', title) // DO NOT USE IT. Is only for backwards compatibility\n this._element.removeAttribute('title')\n }\n\n _enter() {\n if (this._isShown() || this._isHovered) {\n this._isHovered = true\n return\n }\n\n this._isHovered = true\n\n this._setTimeout(() => {\n if (this._isHovered) {\n this.show()\n }\n }, this._config.delay.show)\n }\n\n _leave() {\n if (this._isWithActiveTrigger()) {\n return\n }\n\n this._isHovered = false\n\n this._setTimeout(() => {\n if (!this._isHovered) {\n this.hide()\n }\n }, this._config.delay.hide)\n }\n\n _setTimeout(handler, timeout) {\n clearTimeout(this._timeout)\n this._timeout = setTimeout(handler, timeout)\n }\n\n _isWithActiveTrigger() {\n return Object.values(this._activeTrigger).includes(true)\n }\n\n _getConfig(config) {\n const dataAttributes = Manipulator.getDataAttributes(this._element)\n\n for (const dataAttribute of Object.keys(dataAttributes)) {\n if (DISALLOWED_ATTRIBUTES.has(dataAttribute)) {\n delete dataAttributes[dataAttribute]\n }\n }\n\n config = {\n ...dataAttributes,\n ...(typeof config === 'object' && config ? config : {})\n }\n config = this._mergeConfigObj(config)\n config = this._configAfterMerge(config)\n this._typeCheckConfig(config)\n return config\n }\n\n _configAfterMerge(config) {\n config.container = config.container === false ? document.body : getElement(config.container)\n\n if (typeof config.delay === 'number') {\n config.delay = {\n show: config.delay,\n hide: config.delay\n }\n }\n\n if (typeof config.title === 'number') {\n config.title = config.title.toString()\n }\n\n if (typeof config.content === 'number') {\n config.content = config.content.toString()\n }\n\n return config\n }\n\n _getDelegateConfig() {\n const config = {}\n\n for (const [key, value] of Object.entries(this._config)) {\n if (this.constructor.Default[key] !== value) {\n config[key] = value\n }\n }\n\n config.selector = false\n config.trigger = 'manual'\n\n // In the future can be replaced with:\n // const keysWithDifferentValues = Object.entries(this._config).filter(entry => this.constructor.Default[entry[0]] !== this._config[entry[0]])\n // `Object.fromEntries(keysWithDifferentValues)`\n return config\n }\n\n _disposePopper() {\n if (this._popper) {\n this._popper.destroy()\n this._popper = null\n }\n\n if (this.tip) {\n this.tip.remove()\n this.tip = null\n }\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Tooltip.getOrCreateInstance(this, config)\n\n if (typeof config !== 'string') {\n return\n }\n\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`)\n }\n\n data[config]()\n })\n }\n}\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Tooltip)\n\nexport default Tooltip\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap popover.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport Tooltip from './tooltip.js'\nimport { defineJQueryPlugin } from './util/index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'popover'\n\nconst SELECTOR_TITLE = '.popover-header'\nconst SELECTOR_CONTENT = '.popover-body'\n\nconst Default = {\n ...Tooltip.Default,\n content: '',\n offset: [0, 8],\n placement: 'right',\n template: '
          ' +\n '
          ' +\n '

          ' +\n '
          ' +\n '
          ',\n trigger: 'click'\n}\n\nconst DefaultType = {\n ...Tooltip.DefaultType,\n content: '(null|string|element|function)'\n}\n\n/**\n * Class definition\n */\n\nclass Popover extends Tooltip {\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Overrides\n _isWithContent() {\n return this._getTitle() || this._getContent()\n }\n\n // Private\n _getContentForTemplate() {\n return {\n [SELECTOR_TITLE]: this._getTitle(),\n [SELECTOR_CONTENT]: this._getContent()\n }\n }\n\n _getContent() {\n return this._resolvePossibleFunction(this._config.content)\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Popover.getOrCreateInstance(this, config)\n\n if (typeof config !== 'string') {\n return\n }\n\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`)\n }\n\n data[config]()\n })\n }\n}\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Popover)\n\nexport default Popover\n","/**\n * --------------------------------------------------------------------------\n * Bootstrap scrollspy.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nimport BaseComponent from './base-component.js'\nimport EventHandler from './dom/event-handler.js'\nimport SelectorEngine from './dom/selector-engine.js'\nimport { defineJQueryPlugin, getElement, isDisabled, isVisible } from './util/index.js'\n\n/**\n * Constants\n */\n\nconst NAME = 'scrollspy'\nconst DATA_KEY = 'bs.scrollspy'\nconst EVENT_KEY = `.${DATA_KEY}`\nconst DATA_API_KEY = '.data-api'\n\nconst EVENT_ACTIVATE = `activate${EVENT_KEY}`\nconst EVENT_CLICK = `click${EVENT_KEY}`\nconst EVENT_LOAD_DATA_API = `load${EVENT_KEY}${DATA_API_KEY}`\n\nconst CLASS_NAME_DROPDOWN_ITEM = 'dropdown-item'\nconst CLASS_NAME_ACTIVE = 'active'\n\nconst SELECTOR_DATA_SPY = '[data-bs-spy=\"scroll\"]'\nconst SELECTOR_TARGET_LINKS = '[href]'\nconst SELECTOR_NAV_LIST_GROUP = '.nav, .list-group'\nconst SELECTOR_NAV_LINKS = '.nav-link'\nconst SELECTOR_NAV_ITEMS = '.nav-item'\nconst SELECTOR_LIST_ITEMS = '.list-group-item'\nconst SELECTOR_LINK_ITEMS = `${SELECTOR_NAV_LINKS}, ${SELECTOR_NAV_ITEMS} > ${SELECTOR_NAV_LINKS}, ${SELECTOR_LIST_ITEMS}`\nconst SELECTOR_DROPDOWN = '.dropdown'\nconst SELECTOR_DROPDOWN_TOGGLE = '.dropdown-toggle'\n\nconst Default = {\n offset: null, // TODO: v6 @deprecated, keep it for backwards compatibility reasons\n rootMargin: '0px 0px -25%',\n smoothScroll: false,\n target: null,\n threshold: [0.1, 0.5, 1]\n}\n\nconst DefaultType = {\n offset: '(number|null)', // TODO v6 @deprecated, keep it for backwards compatibility reasons\n rootMargin: 'string',\n smoothScroll: 'boolean',\n target: 'element',\n threshold: 'array'\n}\n\n/**\n * Class definition\n */\n\nclass ScrollSpy extends BaseComponent {\n constructor(element, config) {\n super(element, config)\n\n // this._element is the observablesContainer and config.target the menu links wrapper\n this._targetLinks = new Map()\n this._observableSections = new Map()\n this._rootElement = getComputedStyle(this._element).overflowY === 'visible' ? null : this._element\n this._activeTarget = null\n this._observer = null\n this._previousScrollData = {\n visibleEntryTop: 0,\n parentScrollTop: 0\n }\n this.refresh() // initialize\n }\n\n // Getters\n static get Default() {\n return Default\n }\n\n static get DefaultType() {\n return DefaultType\n }\n\n static get NAME() {\n return NAME\n }\n\n // Public\n refresh() {\n this._initializeTargetsAndObservables()\n this._maybeEnableSmoothScroll()\n\n if (this._observer) {\n this._observer.disconnect()\n } else {\n this._observer = this._getNewObserver()\n }\n\n for (const section of this._observableSections.values()) {\n this._observer.observe(section)\n }\n }\n\n dispose() {\n this._observer.disconnect()\n super.dispose()\n }\n\n // Private\n _configAfterMerge(config) {\n // TODO: on v6 target should be given explicitly & remove the {target: 'ss-target'} case\n config.target = getElement(config.target) || document.body\n\n // TODO: v6 Only for backwards compatibility reasons. Use rootMargin only\n config.rootMargin = config.offset ? `${config.offset}px 0px -30%` : config.rootMargin\n\n if (typeof config.threshold === 'string') {\n config.threshold = config.threshold.split(',').map(value => Number.parseFloat(value))\n }\n\n return config\n }\n\n _maybeEnableSmoothScroll() {\n if (!this._config.smoothScroll) {\n return\n }\n\n // unregister any previous listeners\n EventHandler.off(this._config.target, EVENT_CLICK)\n\n EventHandler.on(this._config.target, EVENT_CLICK, SELECTOR_TARGET_LINKS, event => {\n const observableSection = this._observableSections.get(event.target.hash)\n if (observableSection) {\n event.preventDefault()\n const root = this._rootElement || window\n const height = observableSection.offsetTop - this._element.offsetTop\n if (root.scrollTo) {\n root.scrollTo({ top: height, behavior: 'smooth' })\n return\n }\n\n // Chrome 60 doesn't support `scrollTo`\n root.scrollTop = height\n }\n })\n }\n\n _getNewObserver() {\n const options = {\n root: this._rootElement,\n threshold: this._config.threshold,\n rootMargin: this._config.rootMargin\n }\n\n return new IntersectionObserver(entries => this._observerCallback(entries), options)\n }\n\n // The logic of selection\n _observerCallback(entries) {\n const targetElement = entry => this._targetLinks.get(`#${entry.target.id}`)\n const activate = entry => {\n this._previousScrollData.visibleEntryTop = entry.target.offsetTop\n this._process(targetElement(entry))\n }\n\n const parentScrollTop = (this._rootElement || document.documentElement).scrollTop\n const userScrollsDown = parentScrollTop >= this._previousScrollData.parentScrollTop\n this._previousScrollData.parentScrollTop = parentScrollTop\n\n for (const entry of entries) {\n if (!entry.isIntersecting) {\n this._activeTarget = null\n this._clearActiveClass(targetElement(entry))\n\n continue\n }\n\n const entryIsLowerThanPrevious = entry.target.offsetTop >= this._previousScrollData.visibleEntryTop\n // if we are scrolling down, pick the bigger offsetTop\n if (userScrollsDown && entryIsLowerThanPrevious) {\n activate(entry)\n // if parent isn't scrolled, let's keep the first visible item, breaking the iteration\n if (!parentScrollTop) {\n return\n }\n\n continue\n }\n\n // if we are scrolling up, pick the smallest offsetTop\n if (!userScrollsDown && !entryIsLowerThanPrevious) {\n activate(entry)\n }\n }\n }\n\n _initializeTargetsAndObservables() {\n this._targetLinks = new Map()\n this._observableSections = new Map()\n\n const targetLinks = SelectorEngine.find(SELECTOR_TARGET_LINKS, this._config.target)\n\n for (const anchor of targetLinks) {\n // ensure that the anchor has an id and is not disabled\n if (!anchor.hash || isDisabled(anchor)) {\n continue\n }\n\n const observableSection = SelectorEngine.findOne(decodeURI(anchor.hash), this._element)\n\n // ensure that the observableSection exists & is visible\n if (isVisible(observableSection)) {\n this._targetLinks.set(decodeURI(anchor.hash), anchor)\n this._observableSections.set(anchor.hash, observableSection)\n }\n }\n }\n\n _process(target) {\n if (this._activeTarget === target) {\n return\n }\n\n this._clearActiveClass(this._config.target)\n this._activeTarget = target\n target.classList.add(CLASS_NAME_ACTIVE)\n this._activateParents(target)\n\n EventHandler.trigger(this._element, EVENT_ACTIVATE, { relatedTarget: target })\n }\n\n _activateParents(target) {\n // Activate dropdown parents\n if (target.classList.contains(CLASS_NAME_DROPDOWN_ITEM)) {\n SelectorEngine.findOne(SELECTOR_DROPDOWN_TOGGLE, target.closest(SELECTOR_DROPDOWN))\n .classList.add(CLASS_NAME_ACTIVE)\n return\n }\n\n for (const listGroup of SelectorEngine.parents(target, SELECTOR_NAV_LIST_GROUP)) {\n // Set triggered links parents as active\n // With both
            and
          ')},createChildNavList:function(e){var t=this.createNavList();return e.append(t),t},generateNavEl:function(e,t){var n=a('          ');n.attr("href","#"+e),n.text(t);var r=a("
        • ");return r.append(n),r},generateNavItem:function(e){var t=this.generateAnchor(e),n=a(e),r=n.data("toc-text")||n.text();return this.generateNavEl(t,r)},getTopLevel:function(e){for(var t=1;t<=6;t++){if(1 - - - - - - - - - - - - diff --git a/docs/deps/font-awesome-6.5.2/css/all.css b/docs/deps/font-awesome-6.5.2/css/all.css deleted file mode 100644 index 151dd57..0000000 --- a/docs/deps/font-awesome-6.5.2/css/all.css +++ /dev/null @@ -1,8028 +0,0 @@ -/*! - * Font Awesome Free 6.5.2 by @fontawesome - https://fontawesome.com - * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) - * Copyright 2024 Fonticons, Inc. - */ -.fa { - font-family: var(--fa-style-family, "Font Awesome 6 Free"); - font-weight: var(--fa-style, 900); } - -.fa, -.fa-classic, -.fa-sharp, -.fas, -.fa-solid, -.far, -.fa-regular, -.fab, -.fa-brands { - -moz-osx-font-smoothing: grayscale; - -webkit-font-smoothing: antialiased; - display: var(--fa-display, inline-block); - font-style: normal; - font-variant: normal; - line-height: 1; - text-rendering: auto; } - -.fas, -.fa-classic, -.fa-solid, -.far, -.fa-regular { - font-family: 'Font Awesome 6 Free'; } - -.fab, -.fa-brands { - font-family: 'Font Awesome 6 Brands'; } - -.fa-1x { - font-size: 1em; } - -.fa-2x { - font-size: 2em; } - -.fa-3x { - font-size: 3em; } - -.fa-4x { - font-size: 4em; } - -.fa-5x { - font-size: 5em; } - -.fa-6x { - font-size: 6em; } - -.fa-7x { - font-size: 7em; } - -.fa-8x { - font-size: 8em; } - -.fa-9x { - font-size: 9em; } - -.fa-10x { - font-size: 10em; } - -.fa-2xs { - font-size: 0.625em; - line-height: 0.1em; - vertical-align: 0.225em; } - -.fa-xs { - font-size: 0.75em; - line-height: 0.08333em; - vertical-align: 0.125em; } - -.fa-sm { - font-size: 0.875em; - line-height: 0.07143em; - vertical-align: 0.05357em; } - -.fa-lg { - font-size: 1.25em; - line-height: 0.05em; - vertical-align: -0.075em; } - -.fa-xl { - font-size: 1.5em; - line-height: 0.04167em; - vertical-align: -0.125em; } - -.fa-2xl { - font-size: 2em; - line-height: 0.03125em; - vertical-align: -0.1875em; } - -.fa-fw { - text-align: center; - width: 1.25em; } - -.fa-ul { - list-style-type: none; - margin-left: var(--fa-li-margin, 2.5em); - padding-left: 0; } - .fa-ul > li { - position: relative; } - -.fa-li { - left: calc(var(--fa-li-width, 2em) * -1); - position: absolute; - text-align: center; - width: var(--fa-li-width, 2em); - line-height: inherit; } - -.fa-border { - border-color: var(--fa-border-color, #eee); - border-radius: var(--fa-border-radius, 0.1em); - border-style: var(--fa-border-style, solid); - border-width: var(--fa-border-width, 0.08em); - padding: var(--fa-border-padding, 0.2em 0.25em 0.15em); } - -.fa-pull-left { - float: left; - margin-right: var(--fa-pull-margin, 0.3em); } - -.fa-pull-right { - float: right; - margin-left: var(--fa-pull-margin, 0.3em); } - -.fa-beat { - -webkit-animation-name: fa-beat; - animation-name: fa-beat; - -webkit-animation-delay: var(--fa-animation-delay, 0s); - animation-delay: var(--fa-animation-delay, 0s); - -webkit-animation-direction: var(--fa-animation-direction, normal); - animation-direction: var(--fa-animation-direction, normal); - -webkit-animation-duration: var(--fa-animation-duration, 1s); - animation-duration: var(--fa-animation-duration, 1s); - -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite); - animation-iteration-count: var(--fa-animation-iteration-count, infinite); - -webkit-animation-timing-function: var(--fa-animation-timing, ease-in-out); - animation-timing-function: var(--fa-animation-timing, ease-in-out); } - -.fa-bounce { - -webkit-animation-name: fa-bounce; - animation-name: fa-bounce; - -webkit-animation-delay: var(--fa-animation-delay, 0s); - animation-delay: var(--fa-animation-delay, 0s); - -webkit-animation-direction: var(--fa-animation-direction, normal); - animation-direction: var(--fa-animation-direction, normal); - -webkit-animation-duration: var(--fa-animation-duration, 1s); - animation-duration: var(--fa-animation-duration, 1s); - -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite); - animation-iteration-count: var(--fa-animation-iteration-count, infinite); - -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.28, 0.84, 0.42, 1)); - animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.28, 0.84, 0.42, 1)); } - -.fa-fade { - -webkit-animation-name: fa-fade; - animation-name: fa-fade; - -webkit-animation-delay: var(--fa-animation-delay, 0s); - animation-delay: var(--fa-animation-delay, 0s); - -webkit-animation-direction: var(--fa-animation-direction, normal); - animation-direction: var(--fa-animation-direction, normal); - -webkit-animation-duration: var(--fa-animation-duration, 1s); - animation-duration: var(--fa-animation-duration, 1s); - -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite); - animation-iteration-count: var(--fa-animation-iteration-count, infinite); - -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1)); - animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1)); } - -.fa-beat-fade { - -webkit-animation-name: fa-beat-fade; - animation-name: fa-beat-fade; - -webkit-animation-delay: var(--fa-animation-delay, 0s); - animation-delay: var(--fa-animation-delay, 0s); - -webkit-animation-direction: var(--fa-animation-direction, normal); - animation-direction: var(--fa-animation-direction, normal); - -webkit-animation-duration: var(--fa-animation-duration, 1s); - animation-duration: var(--fa-animation-duration, 1s); - -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite); - animation-iteration-count: var(--fa-animation-iteration-count, infinite); - -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1)); - animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1)); } - -.fa-flip { - -webkit-animation-name: fa-flip; - animation-name: fa-flip; - -webkit-animation-delay: var(--fa-animation-delay, 0s); - animation-delay: var(--fa-animation-delay, 0s); - -webkit-animation-direction: var(--fa-animation-direction, normal); - animation-direction: var(--fa-animation-direction, normal); - -webkit-animation-duration: var(--fa-animation-duration, 1s); - animation-duration: var(--fa-animation-duration, 1s); - -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite); - animation-iteration-count: var(--fa-animation-iteration-count, infinite); - -webkit-animation-timing-function: var(--fa-animation-timing, ease-in-out); - animation-timing-function: var(--fa-animation-timing, ease-in-out); } - -.fa-shake { - -webkit-animation-name: fa-shake; - animation-name: fa-shake; - -webkit-animation-delay: var(--fa-animation-delay, 0s); - animation-delay: var(--fa-animation-delay, 0s); - -webkit-animation-direction: var(--fa-animation-direction, normal); - animation-direction: var(--fa-animation-direction, normal); - -webkit-animation-duration: var(--fa-animation-duration, 1s); - animation-duration: var(--fa-animation-duration, 1s); - -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite); - animation-iteration-count: var(--fa-animation-iteration-count, infinite); - -webkit-animation-timing-function: var(--fa-animation-timing, linear); - animation-timing-function: var(--fa-animation-timing, linear); } - -.fa-spin { - -webkit-animation-name: fa-spin; - animation-name: fa-spin; - -webkit-animation-delay: var(--fa-animation-delay, 0s); - animation-delay: var(--fa-animation-delay, 0s); - -webkit-animation-direction: var(--fa-animation-direction, normal); - animation-direction: var(--fa-animation-direction, normal); - -webkit-animation-duration: var(--fa-animation-duration, 2s); - animation-duration: var(--fa-animation-duration, 2s); - -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite); - animation-iteration-count: var(--fa-animation-iteration-count, infinite); - -webkit-animation-timing-function: var(--fa-animation-timing, linear); - animation-timing-function: var(--fa-animation-timing, linear); } - -.fa-spin-reverse { - --fa-animation-direction: reverse; } - -.fa-pulse, -.fa-spin-pulse { - -webkit-animation-name: fa-spin; - animation-name: fa-spin; - -webkit-animation-direction: var(--fa-animation-direction, normal); - animation-direction: var(--fa-animation-direction, normal); - -webkit-animation-duration: var(--fa-animation-duration, 1s); - animation-duration: var(--fa-animation-duration, 1s); - -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite); - animation-iteration-count: var(--fa-animation-iteration-count, infinite); - -webkit-animation-timing-function: var(--fa-animation-timing, steps(8)); - animation-timing-function: var(--fa-animation-timing, steps(8)); } - -@media (prefers-reduced-motion: reduce) { - .fa-beat, - .fa-bounce, - .fa-fade, - .fa-beat-fade, - .fa-flip, - .fa-pulse, - .fa-shake, - .fa-spin, - .fa-spin-pulse { - -webkit-animation-delay: -1ms; - animation-delay: -1ms; - -webkit-animation-duration: 1ms; - animation-duration: 1ms; - -webkit-animation-iteration-count: 1; - animation-iteration-count: 1; - -webkit-transition-delay: 0s; - transition-delay: 0s; - -webkit-transition-duration: 0s; - transition-duration: 0s; } } - -@-webkit-keyframes fa-beat { - 0%, 90% { - -webkit-transform: scale(1); - transform: scale(1); } - 45% { - -webkit-transform: scale(var(--fa-beat-scale, 1.25)); - transform: scale(var(--fa-beat-scale, 1.25)); } } - -@keyframes fa-beat { - 0%, 90% { - -webkit-transform: scale(1); - transform: scale(1); } - 45% { - -webkit-transform: scale(var(--fa-beat-scale, 1.25)); - transform: scale(var(--fa-beat-scale, 1.25)); } } - -@-webkit-keyframes fa-bounce { - 0% { - -webkit-transform: scale(1, 1) translateY(0); - transform: scale(1, 1) translateY(0); } - 10% { - -webkit-transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); - transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); } - 30% { - -webkit-transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); - transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); } - 50% { - -webkit-transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); - transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); } - 57% { - -webkit-transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); - transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); } - 64% { - -webkit-transform: scale(1, 1) translateY(0); - transform: scale(1, 1) translateY(0); } - 100% { - -webkit-transform: scale(1, 1) translateY(0); - transform: scale(1, 1) translateY(0); } } - -@keyframes fa-bounce { - 0% { - -webkit-transform: scale(1, 1) translateY(0); - transform: scale(1, 1) translateY(0); } - 10% { - -webkit-transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); - transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); } - 30% { - -webkit-transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); - transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); } - 50% { - -webkit-transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); - transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); } - 57% { - -webkit-transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); - transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); } - 64% { - -webkit-transform: scale(1, 1) translateY(0); - transform: scale(1, 1) translateY(0); } - 100% { - -webkit-transform: scale(1, 1) translateY(0); - transform: scale(1, 1) translateY(0); } } - -@-webkit-keyframes fa-fade { - 50% { - opacity: var(--fa-fade-opacity, 0.4); } } - -@keyframes fa-fade { - 50% { - opacity: var(--fa-fade-opacity, 0.4); } } - -@-webkit-keyframes fa-beat-fade { - 0%, 100% { - opacity: var(--fa-beat-fade-opacity, 0.4); - -webkit-transform: scale(1); - transform: scale(1); } - 50% { - opacity: 1; - -webkit-transform: scale(var(--fa-beat-fade-scale, 1.125)); - transform: scale(var(--fa-beat-fade-scale, 1.125)); } } - -@keyframes fa-beat-fade { - 0%, 100% { - opacity: var(--fa-beat-fade-opacity, 0.4); - -webkit-transform: scale(1); - transform: scale(1); } - 50% { - opacity: 1; - -webkit-transform: scale(var(--fa-beat-fade-scale, 1.125)); - transform: scale(var(--fa-beat-fade-scale, 1.125)); } } - -@-webkit-keyframes fa-flip { - 50% { - -webkit-transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); - transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); } } - -@keyframes fa-flip { - 50% { - -webkit-transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); - transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); } } - -@-webkit-keyframes fa-shake { - 0% { - -webkit-transform: rotate(-15deg); - transform: rotate(-15deg); } - 4% { - -webkit-transform: rotate(15deg); - transform: rotate(15deg); } - 8%, 24% { - -webkit-transform: rotate(-18deg); - transform: rotate(-18deg); } - 12%, 28% { - -webkit-transform: rotate(18deg); - transform: rotate(18deg); } - 16% { - -webkit-transform: rotate(-22deg); - transform: rotate(-22deg); } - 20% { - -webkit-transform: rotate(22deg); - transform: rotate(22deg); } - 32% { - -webkit-transform: rotate(-12deg); - transform: rotate(-12deg); } - 36% { - -webkit-transform: rotate(12deg); - transform: rotate(12deg); } - 40%, 100% { - -webkit-transform: rotate(0deg); - transform: rotate(0deg); } } - -@keyframes fa-shake { - 0% { - -webkit-transform: rotate(-15deg); - transform: rotate(-15deg); } - 4% { - -webkit-transform: rotate(15deg); - transform: rotate(15deg); } - 8%, 24% { - -webkit-transform: rotate(-18deg); - transform: rotate(-18deg); } - 12%, 28% { - -webkit-transform: rotate(18deg); - transform: rotate(18deg); } - 16% { - -webkit-transform: rotate(-22deg); - transform: rotate(-22deg); } - 20% { - -webkit-transform: rotate(22deg); - transform: rotate(22deg); } - 32% { - -webkit-transform: rotate(-12deg); - transform: rotate(-12deg); } - 36% { - -webkit-transform: rotate(12deg); - transform: rotate(12deg); } - 40%, 100% { - -webkit-transform: rotate(0deg); - transform: rotate(0deg); } } - -@-webkit-keyframes fa-spin { - 0% { - -webkit-transform: rotate(0deg); - transform: rotate(0deg); } - 100% { - -webkit-transform: rotate(360deg); - transform: rotate(360deg); } } - -@keyframes fa-spin { - 0% { - -webkit-transform: rotate(0deg); - transform: rotate(0deg); } - 100% { - -webkit-transform: rotate(360deg); - transform: rotate(360deg); } } - -.fa-rotate-90 { - -webkit-transform: rotate(90deg); - transform: rotate(90deg); } - -.fa-rotate-180 { - -webkit-transform: rotate(180deg); - transform: rotate(180deg); } - -.fa-rotate-270 { - -webkit-transform: rotate(270deg); - transform: rotate(270deg); } - -.fa-flip-horizontal { - -webkit-transform: scale(-1, 1); - transform: scale(-1, 1); } - -.fa-flip-vertical { - -webkit-transform: scale(1, -1); - transform: scale(1, -1); } - -.fa-flip-both, -.fa-flip-horizontal.fa-flip-vertical { - -webkit-transform: scale(-1, -1); - transform: scale(-1, -1); } - -.fa-rotate-by { - -webkit-transform: rotate(var(--fa-rotate-angle, 0)); - transform: rotate(var(--fa-rotate-angle, 0)); } - -.fa-stack { - display: inline-block; - height: 2em; - line-height: 2em; - position: relative; - vertical-align: middle; - width: 2.5em; } - -.fa-stack-1x, -.fa-stack-2x { - left: 0; - position: absolute; - text-align: center; - width: 100%; - z-index: var(--fa-stack-z-index, auto); } - -.fa-stack-1x { - line-height: inherit; } - -.fa-stack-2x { - font-size: 2em; } - -.fa-inverse { - color: var(--fa-inverse, #fff); } - -/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen -readers do not read off random characters that represent icons */ - -.fa-0::before { - content: "\30"; } - -.fa-1::before { - content: "\31"; } - -.fa-2::before { - content: "\32"; } - -.fa-3::before { - content: "\33"; } - -.fa-4::before { - content: "\34"; } - -.fa-5::before { - content: "\35"; } - -.fa-6::before { - content: "\36"; } - -.fa-7::before { - content: "\37"; } - -.fa-8::before { - content: "\38"; } - -.fa-9::before { - content: "\39"; } - -.fa-fill-drip::before { - content: "\f576"; } - -.fa-arrows-to-circle::before { - content: "\e4bd"; } - -.fa-circle-chevron-right::before { - content: "\f138"; } - -.fa-chevron-circle-right::before { - content: "\f138"; } - -.fa-at::before { - content: "\40"; } - -.fa-trash-can::before { - content: "\f2ed"; } - -.fa-trash-alt::before { - content: "\f2ed"; } - -.fa-text-height::before { - content: "\f034"; } - -.fa-user-xmark::before { - content: "\f235"; } - -.fa-user-times::before { - content: "\f235"; } - -.fa-stethoscope::before { - content: "\f0f1"; } - -.fa-message::before { - content: "\f27a"; } - -.fa-comment-alt::before { - content: "\f27a"; } - -.fa-info::before { - content: "\f129"; } - -.fa-down-left-and-up-right-to-center::before { - content: "\f422"; } - -.fa-compress-alt::before { - content: "\f422"; } - -.fa-explosion::before { - content: "\e4e9"; } - -.fa-file-lines::before { - content: "\f15c"; } - -.fa-file-alt::before { - content: "\f15c"; } - -.fa-file-text::before { - content: "\f15c"; } - -.fa-wave-square::before { - content: "\f83e"; } - -.fa-ring::before { - content: "\f70b"; } - -.fa-building-un::before { - content: "\e4d9"; } - -.fa-dice-three::before { - content: "\f527"; } - -.fa-calendar-days::before { - content: "\f073"; } - -.fa-calendar-alt::before { - content: "\f073"; } - -.fa-anchor-circle-check::before { - content: "\e4aa"; } - -.fa-building-circle-arrow-right::before { - content: "\e4d1"; } - -.fa-volleyball::before { - content: "\f45f"; } - -.fa-volleyball-ball::before { - content: "\f45f"; } - -.fa-arrows-up-to-line::before { - content: "\e4c2"; } - -.fa-sort-down::before { - content: "\f0dd"; } - -.fa-sort-desc::before { - content: "\f0dd"; } - -.fa-circle-minus::before { - content: "\f056"; } - -.fa-minus-circle::before { - content: "\f056"; } - -.fa-door-open::before { - content: "\f52b"; } - -.fa-right-from-bracket::before { - content: "\f2f5"; } - -.fa-sign-out-alt::before { - content: "\f2f5"; } - -.fa-atom::before { - content: "\f5d2"; } - -.fa-soap::before { - content: "\e06e"; } - -.fa-icons::before { - content: "\f86d"; } - -.fa-heart-music-camera-bolt::before { - content: "\f86d"; } - -.fa-microphone-lines-slash::before { - content: "\f539"; } - -.fa-microphone-alt-slash::before { - content: "\f539"; } - -.fa-bridge-circle-check::before { - content: "\e4c9"; } - -.fa-pump-medical::before { - content: "\e06a"; } - -.fa-fingerprint::before { - content: "\f577"; } - -.fa-hand-point-right::before { - content: "\f0a4"; } - -.fa-magnifying-glass-location::before { - content: "\f689"; } - -.fa-search-location::before { - content: "\f689"; } - -.fa-forward-step::before { - content: "\f051"; } - -.fa-step-forward::before { - content: "\f051"; } - -.fa-face-smile-beam::before { - content: "\f5b8"; } - -.fa-smile-beam::before { - content: "\f5b8"; } - -.fa-flag-checkered::before { - content: "\f11e"; } - -.fa-football::before { - content: "\f44e"; } - -.fa-football-ball::before { - content: "\f44e"; } - -.fa-school-circle-exclamation::before { - content: "\e56c"; } - -.fa-crop::before { - content: "\f125"; } - -.fa-angles-down::before { - content: "\f103"; } - -.fa-angle-double-down::before { - content: "\f103"; } - -.fa-users-rectangle::before { - content: "\e594"; } - -.fa-people-roof::before { - content: "\e537"; } - -.fa-people-line::before { - content: "\e534"; } - -.fa-beer-mug-empty::before { - content: "\f0fc"; } - -.fa-beer::before { - content: "\f0fc"; } - -.fa-diagram-predecessor::before { - content: "\e477"; } - -.fa-arrow-up-long::before { - content: "\f176"; } - -.fa-long-arrow-up::before { - content: "\f176"; } - -.fa-fire-flame-simple::before { - content: "\f46a"; } - -.fa-burn::before { - content: "\f46a"; } - -.fa-person::before { - content: "\f183"; } - -.fa-male::before { - content: "\f183"; } - -.fa-laptop::before { - content: "\f109"; } - -.fa-file-csv::before { - content: "\f6dd"; } - -.fa-menorah::before { - content: "\f676"; } - -.fa-truck-plane::before { - content: "\e58f"; } - -.fa-record-vinyl::before { - content: "\f8d9"; } - -.fa-face-grin-stars::before { - content: "\f587"; } - -.fa-grin-stars::before { - content: "\f587"; } - -.fa-bong::before { - content: "\f55c"; } - -.fa-spaghetti-monster-flying::before { - content: "\f67b"; } - -.fa-pastafarianism::before { - content: "\f67b"; } - -.fa-arrow-down-up-across-line::before { - content: "\e4af"; } - -.fa-spoon::before { - content: "\f2e5"; } - -.fa-utensil-spoon::before { - content: "\f2e5"; } - -.fa-jar-wheat::before { - content: "\e517"; } - -.fa-envelopes-bulk::before { - content: "\f674"; } - -.fa-mail-bulk::before { - content: "\f674"; } - -.fa-file-circle-exclamation::before { - content: "\e4eb"; } - -.fa-circle-h::before { - content: "\f47e"; } - -.fa-hospital-symbol::before { - content: "\f47e"; } - -.fa-pager::before { - content: "\f815"; } - -.fa-address-book::before { - content: "\f2b9"; } - -.fa-contact-book::before { - content: "\f2b9"; } - -.fa-strikethrough::before { - content: "\f0cc"; } - -.fa-k::before { - content: "\4b"; } - -.fa-landmark-flag::before { - content: "\e51c"; } - -.fa-pencil::before { - content: "\f303"; } - -.fa-pencil-alt::before { - content: "\f303"; } - -.fa-backward::before { - content: "\f04a"; } - -.fa-caret-right::before { - content: "\f0da"; } - -.fa-comments::before { - content: "\f086"; } - -.fa-paste::before { - content: "\f0ea"; } - -.fa-file-clipboard::before { - content: "\f0ea"; } - -.fa-code-pull-request::before { - content: "\e13c"; } - -.fa-clipboard-list::before { - content: "\f46d"; } - -.fa-truck-ramp-box::before { - content: "\f4de"; } - -.fa-truck-loading::before { - content: "\f4de"; } - -.fa-user-check::before { - content: "\f4fc"; } - -.fa-vial-virus::before { - content: "\e597"; } - -.fa-sheet-plastic::before { - content: "\e571"; } - -.fa-blog::before { - content: "\f781"; } - -.fa-user-ninja::before { - content: "\f504"; } - -.fa-person-arrow-up-from-line::before { - content: "\e539"; } - -.fa-scroll-torah::before { - content: "\f6a0"; } - -.fa-torah::before { - content: "\f6a0"; } - -.fa-broom-ball::before { - content: "\f458"; } - -.fa-quidditch::before { - content: "\f458"; } - -.fa-quidditch-broom-ball::before { - content: "\f458"; } - -.fa-toggle-off::before { - content: "\f204"; } - -.fa-box-archive::before { - content: "\f187"; } - -.fa-archive::before { - content: "\f187"; } - -.fa-person-drowning::before { - content: "\e545"; } - -.fa-arrow-down-9-1::before { - content: "\f886"; } - -.fa-sort-numeric-desc::before { - content: "\f886"; } - -.fa-sort-numeric-down-alt::before { - content: "\f886"; } - -.fa-face-grin-tongue-squint::before { - content: "\f58a"; } - -.fa-grin-tongue-squint::before { - content: "\f58a"; } - -.fa-spray-can::before { - content: "\f5bd"; } - -.fa-truck-monster::before { - content: "\f63b"; } - -.fa-w::before { - content: "\57"; } - -.fa-earth-africa::before { - content: "\f57c"; } - -.fa-globe-africa::before { - content: "\f57c"; } - -.fa-rainbow::before { - content: "\f75b"; } - -.fa-circle-notch::before { - content: "\f1ce"; } - -.fa-tablet-screen-button::before { - content: "\f3fa"; } - -.fa-tablet-alt::before { - content: "\f3fa"; } - -.fa-paw::before { - content: "\f1b0"; } - -.fa-cloud::before { - content: "\f0c2"; } - -.fa-trowel-bricks::before { - content: "\e58a"; } - -.fa-face-flushed::before { - content: "\f579"; } - -.fa-flushed::before { - content: "\f579"; } - -.fa-hospital-user::before { - content: "\f80d"; } - -.fa-tent-arrow-left-right::before { - content: "\e57f"; } - -.fa-gavel::before { - content: "\f0e3"; } - -.fa-legal::before { - content: "\f0e3"; } - -.fa-binoculars::before { - content: "\f1e5"; } - -.fa-microphone-slash::before { - content: "\f131"; } - -.fa-box-tissue::before { - content: "\e05b"; } - -.fa-motorcycle::before { - content: "\f21c"; } - -.fa-bell-concierge::before { - content: "\f562"; } - -.fa-concierge-bell::before { - content: "\f562"; } - -.fa-pen-ruler::before { - content: "\f5ae"; } - -.fa-pencil-ruler::before { - content: "\f5ae"; } - -.fa-people-arrows::before { - content: "\e068"; } - -.fa-people-arrows-left-right::before { - content: "\e068"; } - -.fa-mars-and-venus-burst::before { - content: "\e523"; } - -.fa-square-caret-right::before { - content: "\f152"; } - -.fa-caret-square-right::before { - content: "\f152"; } - -.fa-scissors::before { - content: "\f0c4"; } - -.fa-cut::before { - content: "\f0c4"; } - -.fa-sun-plant-wilt::before { - content: "\e57a"; } - -.fa-toilets-portable::before { - content: "\e584"; } - -.fa-hockey-puck::before { - content: "\f453"; } - -.fa-table::before { - content: "\f0ce"; } - -.fa-magnifying-glass-arrow-right::before { - content: "\e521"; } - -.fa-tachograph-digital::before { - content: "\f566"; } - -.fa-digital-tachograph::before { - content: "\f566"; } - -.fa-users-slash::before { - content: "\e073"; } - -.fa-clover::before { - content: "\e139"; } - -.fa-reply::before { - content: "\f3e5"; } - -.fa-mail-reply::before { - content: "\f3e5"; } - -.fa-star-and-crescent::before { - content: "\f699"; } - -.fa-house-fire::before { - content: "\e50c"; } - -.fa-square-minus::before { - content: "\f146"; } - -.fa-minus-square::before { - content: "\f146"; } - -.fa-helicopter::before { - content: "\f533"; } - -.fa-compass::before { - content: "\f14e"; } - -.fa-square-caret-down::before { - content: "\f150"; } - -.fa-caret-square-down::before { - content: "\f150"; } - -.fa-file-circle-question::before { - content: "\e4ef"; } - -.fa-laptop-code::before { - content: "\f5fc"; } - -.fa-swatchbook::before { - content: "\f5c3"; } - -.fa-prescription-bottle::before { - content: "\f485"; } - -.fa-bars::before { - content: "\f0c9"; } - -.fa-navicon::before { - content: "\f0c9"; } - -.fa-people-group::before { - content: "\e533"; } - -.fa-hourglass-end::before { - content: "\f253"; } - -.fa-hourglass-3::before { - content: "\f253"; } - -.fa-heart-crack::before { - content: "\f7a9"; } - -.fa-heart-broken::before { - content: "\f7a9"; } - -.fa-square-up-right::before { - content: "\f360"; } - -.fa-external-link-square-alt::before { - content: "\f360"; } - -.fa-face-kiss-beam::before { - content: "\f597"; } - -.fa-kiss-beam::before { - content: "\f597"; } - -.fa-film::before { - content: "\f008"; } - -.fa-ruler-horizontal::before { - content: "\f547"; } - -.fa-people-robbery::before { - content: "\e536"; } - -.fa-lightbulb::before { - content: "\f0eb"; } - -.fa-caret-left::before { - content: "\f0d9"; } - -.fa-circle-exclamation::before { - content: "\f06a"; } - -.fa-exclamation-circle::before { - content: "\f06a"; } - -.fa-school-circle-xmark::before { - content: "\e56d"; } - -.fa-arrow-right-from-bracket::before { - content: "\f08b"; } - -.fa-sign-out::before { - content: "\f08b"; } - -.fa-circle-chevron-down::before { - content: "\f13a"; } - -.fa-chevron-circle-down::before { - content: "\f13a"; } - -.fa-unlock-keyhole::before { - content: "\f13e"; } - -.fa-unlock-alt::before { - content: "\f13e"; } - -.fa-cloud-showers-heavy::before { - content: "\f740"; } - -.fa-headphones-simple::before { - content: "\f58f"; } - -.fa-headphones-alt::before { - content: "\f58f"; } - -.fa-sitemap::before { - content: "\f0e8"; } - -.fa-circle-dollar-to-slot::before { - content: "\f4b9"; } - -.fa-donate::before { - content: "\f4b9"; } - -.fa-memory::before { - content: "\f538"; } - -.fa-road-spikes::before { - content: "\e568"; } - -.fa-fire-burner::before { - content: "\e4f1"; } - -.fa-flag::before { - content: "\f024"; } - -.fa-hanukiah::before { - content: "\f6e6"; } - -.fa-feather::before { - content: "\f52d"; } - -.fa-volume-low::before { - content: "\f027"; } - -.fa-volume-down::before { - content: "\f027"; } - -.fa-comment-slash::before { - content: "\f4b3"; } - -.fa-cloud-sun-rain::before { - content: "\f743"; } - -.fa-compress::before { - content: "\f066"; } - -.fa-wheat-awn::before { - content: "\e2cd"; } - -.fa-wheat-alt::before { - content: "\e2cd"; } - -.fa-ankh::before { - content: "\f644"; } - -.fa-hands-holding-child::before { - content: "\e4fa"; } - -.fa-asterisk::before { - content: "\2a"; } - -.fa-square-check::before { - content: "\f14a"; } - -.fa-check-square::before { - content: "\f14a"; } - -.fa-peseta-sign::before { - content: "\e221"; } - -.fa-heading::before { - content: "\f1dc"; } - -.fa-header::before { - content: "\f1dc"; } - -.fa-ghost::before { - content: "\f6e2"; } - -.fa-list::before { - content: "\f03a"; } - -.fa-list-squares::before { - content: "\f03a"; } - -.fa-square-phone-flip::before { - content: "\f87b"; } - -.fa-phone-square-alt::before { - content: "\f87b"; } - -.fa-cart-plus::before { - content: "\f217"; } - -.fa-gamepad::before { - content: "\f11b"; } - -.fa-circle-dot::before { - content: "\f192"; } - -.fa-dot-circle::before { - content: "\f192"; } - -.fa-face-dizzy::before { - content: "\f567"; } - -.fa-dizzy::before { - content: "\f567"; } - -.fa-egg::before { - content: "\f7fb"; } - -.fa-house-medical-circle-xmark::before { - content: "\e513"; } - -.fa-campground::before { - content: "\f6bb"; } - -.fa-folder-plus::before { - content: "\f65e"; } - -.fa-futbol::before { - content: "\f1e3"; } - -.fa-futbol-ball::before { - content: "\f1e3"; } - -.fa-soccer-ball::before { - content: "\f1e3"; } - -.fa-paintbrush::before { - content: "\f1fc"; } - -.fa-paint-brush::before { - content: "\f1fc"; } - -.fa-lock::before { - content: "\f023"; } - -.fa-gas-pump::before { - content: "\f52f"; } - -.fa-hot-tub-person::before { - content: "\f593"; } - -.fa-hot-tub::before { - content: "\f593"; } - -.fa-map-location::before { - content: "\f59f"; } - -.fa-map-marked::before { - content: "\f59f"; } - -.fa-house-flood-water::before { - content: "\e50e"; } - -.fa-tree::before { - content: "\f1bb"; } - -.fa-bridge-lock::before { - content: "\e4cc"; } - -.fa-sack-dollar::before { - content: "\f81d"; } - -.fa-pen-to-square::before { - content: "\f044"; } - -.fa-edit::before { - content: "\f044"; } - -.fa-car-side::before { - content: "\f5e4"; } - -.fa-share-nodes::before { - content: "\f1e0"; } - -.fa-share-alt::before { - content: "\f1e0"; } - -.fa-heart-circle-minus::before { - content: "\e4ff"; } - -.fa-hourglass-half::before { - content: "\f252"; } - -.fa-hourglass-2::before { - content: "\f252"; } - -.fa-microscope::before { - content: "\f610"; } - -.fa-sink::before { - content: "\e06d"; } - -.fa-bag-shopping::before { - content: "\f290"; } - -.fa-shopping-bag::before { - content: "\f290"; } - -.fa-arrow-down-z-a::before { - content: "\f881"; } - -.fa-sort-alpha-desc::before { - content: "\f881"; } - -.fa-sort-alpha-down-alt::before { - content: "\f881"; } - -.fa-mitten::before { - content: "\f7b5"; } - -.fa-person-rays::before { - content: "\e54d"; } - -.fa-users::before { - content: "\f0c0"; } - -.fa-eye-slash::before { - content: "\f070"; } - -.fa-flask-vial::before { - content: "\e4f3"; } - -.fa-hand::before { - content: "\f256"; } - -.fa-hand-paper::before { - content: "\f256"; } - -.fa-om::before { - content: "\f679"; } - -.fa-worm::before { - content: "\e599"; } - -.fa-house-circle-xmark::before { - content: "\e50b"; } - -.fa-plug::before { - content: "\f1e6"; } - -.fa-chevron-up::before { - content: "\f077"; } - -.fa-hand-spock::before { - content: "\f259"; } - -.fa-stopwatch::before { - content: "\f2f2"; } - -.fa-face-kiss::before { - content: "\f596"; } - -.fa-kiss::before { - content: "\f596"; } - -.fa-bridge-circle-xmark::before { - content: "\e4cb"; } - -.fa-face-grin-tongue::before { - content: "\f589"; } - -.fa-grin-tongue::before { - content: "\f589"; } - -.fa-chess-bishop::before { - content: "\f43a"; } - -.fa-face-grin-wink::before { - content: "\f58c"; } - -.fa-grin-wink::before { - content: "\f58c"; } - -.fa-ear-deaf::before { - content: "\f2a4"; } - -.fa-deaf::before { - content: "\f2a4"; } - -.fa-deafness::before { - content: "\f2a4"; } - -.fa-hard-of-hearing::before { - content: "\f2a4"; } - -.fa-road-circle-check::before { - content: "\e564"; } - -.fa-dice-five::before { - content: "\f523"; } - -.fa-square-rss::before { - content: "\f143"; } - -.fa-rss-square::before { - content: "\f143"; } - -.fa-land-mine-on::before { - content: "\e51b"; } - -.fa-i-cursor::before { - content: "\f246"; } - -.fa-stamp::before { - content: "\f5bf"; } - -.fa-stairs::before { - content: "\e289"; } - -.fa-i::before { - content: "\49"; } - -.fa-hryvnia-sign::before { - content: "\f6f2"; } - -.fa-hryvnia::before { - content: "\f6f2"; } - -.fa-pills::before { - content: "\f484"; } - -.fa-face-grin-wide::before { - content: "\f581"; } - -.fa-grin-alt::before { - content: "\f581"; } - -.fa-tooth::before { - content: "\f5c9"; } - -.fa-v::before { - content: "\56"; } - -.fa-bangladeshi-taka-sign::before { - content: "\e2e6"; } - -.fa-bicycle::before { - content: "\f206"; } - -.fa-staff-snake::before { - content: "\e579"; } - -.fa-rod-asclepius::before { - content: "\e579"; } - -.fa-rod-snake::before { - content: "\e579"; } - -.fa-staff-aesculapius::before { - content: "\e579"; } - -.fa-head-side-cough-slash::before { - content: "\e062"; } - -.fa-truck-medical::before { - content: "\f0f9"; } - -.fa-ambulance::before { - content: "\f0f9"; } - -.fa-wheat-awn-circle-exclamation::before { - content: "\e598"; } - -.fa-snowman::before { - content: "\f7d0"; } - -.fa-mortar-pestle::before { - content: "\f5a7"; } - -.fa-road-barrier::before { - content: "\e562"; } - -.fa-school::before { - content: "\f549"; } - -.fa-igloo::before { - content: "\f7ae"; } - -.fa-joint::before { - content: "\f595"; } - -.fa-angle-right::before { - content: "\f105"; } - -.fa-horse::before { - content: "\f6f0"; } - -.fa-q::before { - content: "\51"; } - -.fa-g::before { - content: "\47"; } - -.fa-notes-medical::before { - content: "\f481"; } - -.fa-temperature-half::before { - content: "\f2c9"; } - -.fa-temperature-2::before { - content: "\f2c9"; } - -.fa-thermometer-2::before { - content: "\f2c9"; } - -.fa-thermometer-half::before { - content: "\f2c9"; } - -.fa-dong-sign::before { - content: "\e169"; } - -.fa-capsules::before { - content: "\f46b"; } - -.fa-poo-storm::before { - content: "\f75a"; } - -.fa-poo-bolt::before { - content: "\f75a"; } - -.fa-face-frown-open::before { - content: "\f57a"; } - -.fa-frown-open::before { - content: "\f57a"; } - -.fa-hand-point-up::before { - content: "\f0a6"; } - -.fa-money-bill::before { - content: "\f0d6"; } - -.fa-bookmark::before { - content: "\f02e"; } - -.fa-align-justify::before { - content: "\f039"; } - -.fa-umbrella-beach::before { - content: "\f5ca"; } - -.fa-helmet-un::before { - content: "\e503"; } - -.fa-bullseye::before { - content: "\f140"; } - -.fa-bacon::before { - content: "\f7e5"; } - -.fa-hand-point-down::before { - content: "\f0a7"; } - -.fa-arrow-up-from-bracket::before { - content: "\e09a"; } - -.fa-folder::before { - content: "\f07b"; } - -.fa-folder-blank::before { - content: "\f07b"; } - -.fa-file-waveform::before { - content: "\f478"; } - -.fa-file-medical-alt::before { - content: "\f478"; } - -.fa-radiation::before { - content: "\f7b9"; } - -.fa-chart-simple::before { - content: "\e473"; } - -.fa-mars-stroke::before { - content: "\f229"; } - -.fa-vial::before { - content: "\f492"; } - -.fa-gauge::before { - content: "\f624"; } - -.fa-dashboard::before { - content: "\f624"; } - -.fa-gauge-med::before { - content: "\f624"; } - -.fa-tachometer-alt-average::before { - content: "\f624"; } - -.fa-wand-magic-sparkles::before { - content: "\e2ca"; } - -.fa-magic-wand-sparkles::before { - content: "\e2ca"; } - -.fa-e::before { - content: "\45"; } - -.fa-pen-clip::before { - content: "\f305"; } - -.fa-pen-alt::before { - content: "\f305"; } - -.fa-bridge-circle-exclamation::before { - content: "\e4ca"; } - -.fa-user::before { - content: "\f007"; } - -.fa-school-circle-check::before { - content: "\e56b"; } - -.fa-dumpster::before { - content: "\f793"; } - -.fa-van-shuttle::before { - content: "\f5b6"; } - -.fa-shuttle-van::before { - content: "\f5b6"; } - -.fa-building-user::before { - content: "\e4da"; } - -.fa-square-caret-left::before { - content: "\f191"; } - -.fa-caret-square-left::before { - content: "\f191"; } - -.fa-highlighter::before { - content: "\f591"; } - -.fa-key::before { - content: "\f084"; } - -.fa-bullhorn::before { - content: "\f0a1"; } - -.fa-globe::before { - content: "\f0ac"; } - -.fa-synagogue::before { - content: "\f69b"; } - -.fa-person-half-dress::before { - content: "\e548"; } - -.fa-road-bridge::before { - content: "\e563"; } - -.fa-location-arrow::before { - content: "\f124"; } - -.fa-c::before { - content: "\43"; } - -.fa-tablet-button::before { - content: "\f10a"; } - -.fa-building-lock::before { - content: "\e4d6"; } - -.fa-pizza-slice::before { - content: "\f818"; } - -.fa-money-bill-wave::before { - content: "\f53a"; } - -.fa-chart-area::before { - content: "\f1fe"; } - -.fa-area-chart::before { - content: "\f1fe"; } - -.fa-house-flag::before { - content: "\e50d"; } - -.fa-person-circle-minus::before { - content: "\e540"; } - -.fa-ban::before { - content: "\f05e"; } - -.fa-cancel::before { - content: "\f05e"; } - -.fa-camera-rotate::before { - content: "\e0d8"; } - -.fa-spray-can-sparkles::before { - content: "\f5d0"; } - -.fa-air-freshener::before { - content: "\f5d0"; } - -.fa-star::before { - content: "\f005"; } - -.fa-repeat::before { - content: "\f363"; } - -.fa-cross::before { - content: "\f654"; } - -.fa-box::before { - content: "\f466"; } - -.fa-venus-mars::before { - content: "\f228"; } - -.fa-arrow-pointer::before { - content: "\f245"; } - -.fa-mouse-pointer::before { - content: "\f245"; } - -.fa-maximize::before { - content: "\f31e"; } - -.fa-expand-arrows-alt::before { - content: "\f31e"; } - -.fa-charging-station::before { - content: "\f5e7"; } - -.fa-shapes::before { - content: "\f61f"; } - -.fa-triangle-circle-square::before { - content: "\f61f"; } - -.fa-shuffle::before { - content: "\f074"; } - -.fa-random::before { - content: "\f074"; } - -.fa-person-running::before { - content: "\f70c"; } - -.fa-running::before { - content: "\f70c"; } - -.fa-mobile-retro::before { - content: "\e527"; } - -.fa-grip-lines-vertical::before { - content: "\f7a5"; } - -.fa-spider::before { - content: "\f717"; } - -.fa-hands-bound::before { - content: "\e4f9"; } - -.fa-file-invoice-dollar::before { - content: "\f571"; } - -.fa-plane-circle-exclamation::before { - content: "\e556"; } - -.fa-x-ray::before { - content: "\f497"; } - -.fa-spell-check::before { - content: "\f891"; } - -.fa-slash::before { - content: "\f715"; } - -.fa-computer-mouse::before { - content: "\f8cc"; } - -.fa-mouse::before { - content: "\f8cc"; } - -.fa-arrow-right-to-bracket::before { - content: "\f090"; } - -.fa-sign-in::before { - content: "\f090"; } - -.fa-shop-slash::before { - content: "\e070"; } - -.fa-store-alt-slash::before { - content: "\e070"; } - -.fa-server::before { - content: "\f233"; } - -.fa-virus-covid-slash::before { - content: "\e4a9"; } - -.fa-shop-lock::before { - content: "\e4a5"; } - -.fa-hourglass-start::before { - content: "\f251"; } - -.fa-hourglass-1::before { - content: "\f251"; } - -.fa-blender-phone::before { - content: "\f6b6"; } - -.fa-building-wheat::before { - content: "\e4db"; } - -.fa-person-breastfeeding::before { - content: "\e53a"; } - -.fa-right-to-bracket::before { - content: "\f2f6"; } - -.fa-sign-in-alt::before { - content: "\f2f6"; } - -.fa-venus::before { - content: "\f221"; } - -.fa-passport::before { - content: "\f5ab"; } - -.fa-heart-pulse::before { - content: "\f21e"; } - -.fa-heartbeat::before { - content: "\f21e"; } - -.fa-people-carry-box::before { - content: "\f4ce"; } - -.fa-people-carry::before { - content: "\f4ce"; } - -.fa-temperature-high::before { - content: "\f769"; } - -.fa-microchip::before { - content: "\f2db"; } - -.fa-crown::before { - content: "\f521"; } - -.fa-weight-hanging::before { - content: "\f5cd"; } - -.fa-xmarks-lines::before { - content: "\e59a"; } - -.fa-file-prescription::before { - content: "\f572"; } - -.fa-weight-scale::before { - content: "\f496"; } - -.fa-weight::before { - content: "\f496"; } - -.fa-user-group::before { - content: "\f500"; } - -.fa-user-friends::before { - content: "\f500"; } - -.fa-arrow-up-a-z::before { - content: "\f15e"; } - -.fa-sort-alpha-up::before { - content: "\f15e"; } - -.fa-chess-knight::before { - content: "\f441"; } - -.fa-face-laugh-squint::before { - content: "\f59b"; } - -.fa-laugh-squint::before { - content: "\f59b"; } - -.fa-wheelchair::before { - content: "\f193"; } - -.fa-circle-arrow-up::before { - content: "\f0aa"; } - -.fa-arrow-circle-up::before { - content: "\f0aa"; } - -.fa-toggle-on::before { - content: "\f205"; } - -.fa-person-walking::before { - content: "\f554"; } - -.fa-walking::before { - content: "\f554"; } - -.fa-l::before { - content: "\4c"; } - -.fa-fire::before { - content: "\f06d"; } - -.fa-bed-pulse::before { - content: "\f487"; } - -.fa-procedures::before { - content: "\f487"; } - -.fa-shuttle-space::before { - content: "\f197"; } - -.fa-space-shuttle::before { - content: "\f197"; } - -.fa-face-laugh::before { - content: "\f599"; } - -.fa-laugh::before { - content: "\f599"; } - -.fa-folder-open::before { - content: "\f07c"; } - -.fa-heart-circle-plus::before { - content: "\e500"; } - -.fa-code-fork::before { - content: "\e13b"; } - -.fa-city::before { - content: "\f64f"; } - -.fa-microphone-lines::before { - content: "\f3c9"; } - -.fa-microphone-alt::before { - content: "\f3c9"; } - -.fa-pepper-hot::before { - content: "\f816"; } - -.fa-unlock::before { - content: "\f09c"; } - -.fa-colon-sign::before { - content: "\e140"; } - -.fa-headset::before { - content: "\f590"; } - -.fa-store-slash::before { - content: "\e071"; } - -.fa-road-circle-xmark::before { - content: "\e566"; } - -.fa-user-minus::before { - content: "\f503"; } - -.fa-mars-stroke-up::before { - content: "\f22a"; } - -.fa-mars-stroke-v::before { - content: "\f22a"; } - -.fa-champagne-glasses::before { - content: "\f79f"; } - -.fa-glass-cheers::before { - content: "\f79f"; } - -.fa-clipboard::before { - content: "\f328"; } - -.fa-house-circle-exclamation::before { - content: "\e50a"; } - -.fa-file-arrow-up::before { - content: "\f574"; } - -.fa-file-upload::before { - content: "\f574"; } - -.fa-wifi::before { - content: "\f1eb"; } - -.fa-wifi-3::before { - content: "\f1eb"; } - -.fa-wifi-strong::before { - content: "\f1eb"; } - -.fa-bath::before { - content: "\f2cd"; } - -.fa-bathtub::before { - content: "\f2cd"; } - -.fa-underline::before { - content: "\f0cd"; } - -.fa-user-pen::before { - content: "\f4ff"; } - -.fa-user-edit::before { - content: "\f4ff"; } - -.fa-signature::before { - content: "\f5b7"; } - -.fa-stroopwafel::before { - content: "\f551"; } - -.fa-bold::before { - content: "\f032"; } - -.fa-anchor-lock::before { - content: "\e4ad"; } - -.fa-building-ngo::before { - content: "\e4d7"; } - -.fa-manat-sign::before { - content: "\e1d5"; } - -.fa-not-equal::before { - content: "\f53e"; } - -.fa-border-top-left::before { - content: "\f853"; } - -.fa-border-style::before { - content: "\f853"; } - -.fa-map-location-dot::before { - content: "\f5a0"; } - -.fa-map-marked-alt::before { - content: "\f5a0"; } - -.fa-jedi::before { - content: "\f669"; } - -.fa-square-poll-vertical::before { - content: "\f681"; } - -.fa-poll::before { - content: "\f681"; } - -.fa-mug-hot::before { - content: "\f7b6"; } - -.fa-car-battery::before { - content: "\f5df"; } - -.fa-battery-car::before { - content: "\f5df"; } - -.fa-gift::before { - content: "\f06b"; } - -.fa-dice-two::before { - content: "\f528"; } - -.fa-chess-queen::before { - content: "\f445"; } - -.fa-glasses::before { - content: "\f530"; } - -.fa-chess-board::before { - content: "\f43c"; } - -.fa-building-circle-check::before { - content: "\e4d2"; } - -.fa-person-chalkboard::before { - content: "\e53d"; } - -.fa-mars-stroke-right::before { - content: "\f22b"; } - -.fa-mars-stroke-h::before { - content: "\f22b"; } - -.fa-hand-back-fist::before { - content: "\f255"; } - -.fa-hand-rock::before { - content: "\f255"; } - -.fa-square-caret-up::before { - content: "\f151"; } - -.fa-caret-square-up::before { - content: "\f151"; } - -.fa-cloud-showers-water::before { - content: "\e4e4"; } - -.fa-chart-bar::before { - content: "\f080"; } - -.fa-bar-chart::before { - content: "\f080"; } - -.fa-hands-bubbles::before { - content: "\e05e"; } - -.fa-hands-wash::before { - content: "\e05e"; } - -.fa-less-than-equal::before { - content: "\f537"; } - -.fa-train::before { - content: "\f238"; } - -.fa-eye-low-vision::before { - content: "\f2a8"; } - -.fa-low-vision::before { - content: "\f2a8"; } - -.fa-crow::before { - content: "\f520"; } - -.fa-sailboat::before { - content: "\e445"; } - -.fa-window-restore::before { - content: "\f2d2"; } - -.fa-square-plus::before { - content: "\f0fe"; } - -.fa-plus-square::before { - content: "\f0fe"; } - -.fa-torii-gate::before { - content: "\f6a1"; } - -.fa-frog::before { - content: "\f52e"; } - -.fa-bucket::before { - content: "\e4cf"; } - -.fa-image::before { - content: "\f03e"; } - -.fa-microphone::before { - content: "\f130"; } - -.fa-cow::before { - content: "\f6c8"; } - -.fa-caret-up::before { - content: "\f0d8"; } - -.fa-screwdriver::before { - content: "\f54a"; } - -.fa-folder-closed::before { - content: "\e185"; } - -.fa-house-tsunami::before { - content: "\e515"; } - -.fa-square-nfi::before { - content: "\e576"; } - -.fa-arrow-up-from-ground-water::before { - content: "\e4b5"; } - -.fa-martini-glass::before { - content: "\f57b"; } - -.fa-glass-martini-alt::before { - content: "\f57b"; } - -.fa-rotate-left::before { - content: "\f2ea"; } - -.fa-rotate-back::before { - content: "\f2ea"; } - -.fa-rotate-backward::before { - content: "\f2ea"; } - -.fa-undo-alt::before { - content: "\f2ea"; } - -.fa-table-columns::before { - content: "\f0db"; } - -.fa-columns::before { - content: "\f0db"; } - -.fa-lemon::before { - content: "\f094"; } - -.fa-head-side-mask::before { - content: "\e063"; } - -.fa-handshake::before { - content: "\f2b5"; } - -.fa-gem::before { - content: "\f3a5"; } - -.fa-dolly::before { - content: "\f472"; } - -.fa-dolly-box::before { - content: "\f472"; } - -.fa-smoking::before { - content: "\f48d"; } - -.fa-minimize::before { - content: "\f78c"; } - -.fa-compress-arrows-alt::before { - content: "\f78c"; } - -.fa-monument::before { - content: "\f5a6"; } - -.fa-snowplow::before { - content: "\f7d2"; } - -.fa-angles-right::before { - content: "\f101"; } - -.fa-angle-double-right::before { - content: "\f101"; } - -.fa-cannabis::before { - content: "\f55f"; } - -.fa-circle-play::before { - content: "\f144"; } - -.fa-play-circle::before { - content: "\f144"; } - -.fa-tablets::before { - content: "\f490"; } - -.fa-ethernet::before { - content: "\f796"; } - -.fa-euro-sign::before { - content: "\f153"; } - -.fa-eur::before { - content: "\f153"; } - -.fa-euro::before { - content: "\f153"; } - -.fa-chair::before { - content: "\f6c0"; } - -.fa-circle-check::before { - content: "\f058"; } - -.fa-check-circle::before { - content: "\f058"; } - -.fa-circle-stop::before { - content: "\f28d"; } - -.fa-stop-circle::before { - content: "\f28d"; } - -.fa-compass-drafting::before { - content: "\f568"; } - -.fa-drafting-compass::before { - content: "\f568"; } - -.fa-plate-wheat::before { - content: "\e55a"; } - -.fa-icicles::before { - content: "\f7ad"; } - -.fa-person-shelter::before { - content: "\e54f"; } - -.fa-neuter::before { - content: "\f22c"; } - -.fa-id-badge::before { - content: "\f2c1"; } - -.fa-marker::before { - content: "\f5a1"; } - -.fa-face-laugh-beam::before { - content: "\f59a"; } - -.fa-laugh-beam::before { - content: "\f59a"; } - -.fa-helicopter-symbol::before { - content: "\e502"; } - -.fa-universal-access::before { - content: "\f29a"; } - -.fa-circle-chevron-up::before { - content: "\f139"; } - -.fa-chevron-circle-up::before { - content: "\f139"; } - -.fa-lari-sign::before { - content: "\e1c8"; } - -.fa-volcano::before { - content: "\f770"; } - -.fa-person-walking-dashed-line-arrow-right::before { - content: "\e553"; } - -.fa-sterling-sign::before { - content: "\f154"; } - -.fa-gbp::before { - content: "\f154"; } - -.fa-pound-sign::before { - content: "\f154"; } - -.fa-viruses::before { - content: "\e076"; } - -.fa-square-person-confined::before { - content: "\e577"; } - -.fa-user-tie::before { - content: "\f508"; } - -.fa-arrow-down-long::before { - content: "\f175"; } - -.fa-long-arrow-down::before { - content: "\f175"; } - -.fa-tent-arrow-down-to-line::before { - content: "\e57e"; } - -.fa-certificate::before { - content: "\f0a3"; } - -.fa-reply-all::before { - content: "\f122"; } - -.fa-mail-reply-all::before { - content: "\f122"; } - -.fa-suitcase::before { - content: "\f0f2"; } - -.fa-person-skating::before { - content: "\f7c5"; } - -.fa-skating::before { - content: "\f7c5"; } - -.fa-filter-circle-dollar::before { - content: "\f662"; } - -.fa-funnel-dollar::before { - content: "\f662"; } - -.fa-camera-retro::before { - content: "\f083"; } - -.fa-circle-arrow-down::before { - content: "\f0ab"; } - -.fa-arrow-circle-down::before { - content: "\f0ab"; } - -.fa-file-import::before { - content: "\f56f"; } - -.fa-arrow-right-to-file::before { - content: "\f56f"; } - -.fa-square-arrow-up-right::before { - content: "\f14c"; } - -.fa-external-link-square::before { - content: "\f14c"; } - -.fa-box-open::before { - content: "\f49e"; } - -.fa-scroll::before { - content: "\f70e"; } - -.fa-spa::before { - content: "\f5bb"; } - -.fa-location-pin-lock::before { - content: "\e51f"; } - -.fa-pause::before { - content: "\f04c"; } - -.fa-hill-avalanche::before { - content: "\e507"; } - -.fa-temperature-empty::before { - content: "\f2cb"; } - -.fa-temperature-0::before { - content: "\f2cb"; } - -.fa-thermometer-0::before { - content: "\f2cb"; } - -.fa-thermometer-empty::before { - content: "\f2cb"; } - -.fa-bomb::before { - content: "\f1e2"; } - -.fa-registered::before { - content: "\f25d"; } - -.fa-address-card::before { - content: "\f2bb"; } - -.fa-contact-card::before { - content: "\f2bb"; } - -.fa-vcard::before { - content: "\f2bb"; } - -.fa-scale-unbalanced-flip::before { - content: "\f516"; } - -.fa-balance-scale-right::before { - content: "\f516"; } - -.fa-subscript::before { - content: "\f12c"; } - -.fa-diamond-turn-right::before { - content: "\f5eb"; } - -.fa-directions::before { - content: "\f5eb"; } - -.fa-burst::before { - content: "\e4dc"; } - -.fa-house-laptop::before { - content: "\e066"; } - -.fa-laptop-house::before { - content: "\e066"; } - -.fa-face-tired::before { - content: "\f5c8"; } - -.fa-tired::before { - content: "\f5c8"; } - -.fa-money-bills::before { - content: "\e1f3"; } - -.fa-smog::before { - content: "\f75f"; } - -.fa-crutch::before { - content: "\f7f7"; } - -.fa-cloud-arrow-up::before { - content: "\f0ee"; } - -.fa-cloud-upload::before { - content: "\f0ee"; } - -.fa-cloud-upload-alt::before { - content: "\f0ee"; } - -.fa-palette::before { - content: "\f53f"; } - -.fa-arrows-turn-right::before { - content: "\e4c0"; } - -.fa-vest::before { - content: "\e085"; } - -.fa-ferry::before { - content: "\e4ea"; } - -.fa-arrows-down-to-people::before { - content: "\e4b9"; } - -.fa-seedling::before { - content: "\f4d8"; } - -.fa-sprout::before { - content: "\f4d8"; } - -.fa-left-right::before { - content: "\f337"; } - -.fa-arrows-alt-h::before { - content: "\f337"; } - -.fa-boxes-packing::before { - content: "\e4c7"; } - -.fa-circle-arrow-left::before { - content: "\f0a8"; } - -.fa-arrow-circle-left::before { - content: "\f0a8"; } - -.fa-group-arrows-rotate::before { - content: "\e4f6"; } - -.fa-bowl-food::before { - content: "\e4c6"; } - -.fa-candy-cane::before { - content: "\f786"; } - -.fa-arrow-down-wide-short::before { - content: "\f160"; } - -.fa-sort-amount-asc::before { - content: "\f160"; } - -.fa-sort-amount-down::before { - content: "\f160"; } - -.fa-cloud-bolt::before { - content: "\f76c"; } - -.fa-thunderstorm::before { - content: "\f76c"; } - -.fa-text-slash::before { - content: "\f87d"; } - -.fa-remove-format::before { - content: "\f87d"; } - -.fa-face-smile-wink::before { - content: "\f4da"; } - -.fa-smile-wink::before { - content: "\f4da"; } - -.fa-file-word::before { - content: "\f1c2"; } - -.fa-file-powerpoint::before { - content: "\f1c4"; } - -.fa-arrows-left-right::before { - content: "\f07e"; } - -.fa-arrows-h::before { - content: "\f07e"; } - -.fa-house-lock::before { - content: "\e510"; } - -.fa-cloud-arrow-down::before { - content: "\f0ed"; } - -.fa-cloud-download::before { - content: "\f0ed"; } - -.fa-cloud-download-alt::before { - content: "\f0ed"; } - -.fa-children::before { - content: "\e4e1"; } - -.fa-chalkboard::before { - content: "\f51b"; } - -.fa-blackboard::before { - content: "\f51b"; } - -.fa-user-large-slash::before { - content: "\f4fa"; } - -.fa-user-alt-slash::before { - content: "\f4fa"; } - -.fa-envelope-open::before { - content: "\f2b6"; } - -.fa-handshake-simple-slash::before { - content: "\e05f"; } - -.fa-handshake-alt-slash::before { - content: "\e05f"; } - -.fa-mattress-pillow::before { - content: "\e525"; } - -.fa-guarani-sign::before { - content: "\e19a"; } - -.fa-arrows-rotate::before { - content: "\f021"; } - -.fa-refresh::before { - content: "\f021"; } - -.fa-sync::before { - content: "\f021"; } - -.fa-fire-extinguisher::before { - content: "\f134"; } - -.fa-cruzeiro-sign::before { - content: "\e152"; } - -.fa-greater-than-equal::before { - content: "\f532"; } - -.fa-shield-halved::before { - content: "\f3ed"; } - -.fa-shield-alt::before { - content: "\f3ed"; } - -.fa-book-atlas::before { - content: "\f558"; } - -.fa-atlas::before { - content: "\f558"; } - -.fa-virus::before { - content: "\e074"; } - -.fa-envelope-circle-check::before { - content: "\e4e8"; } - -.fa-layer-group::before { - content: "\f5fd"; } - -.fa-arrows-to-dot::before { - content: "\e4be"; } - -.fa-archway::before { - content: "\f557"; } - -.fa-heart-circle-check::before { - content: "\e4fd"; } - -.fa-house-chimney-crack::before { - content: "\f6f1"; } - -.fa-house-damage::before { - content: "\f6f1"; } - -.fa-file-zipper::before { - content: "\f1c6"; } - -.fa-file-archive::before { - content: "\f1c6"; } - -.fa-square::before { - content: "\f0c8"; } - -.fa-martini-glass-empty::before { - content: "\f000"; } - -.fa-glass-martini::before { - content: "\f000"; } - -.fa-couch::before { - content: "\f4b8"; } - -.fa-cedi-sign::before { - content: "\e0df"; } - -.fa-italic::before { - content: "\f033"; } - -.fa-table-cells-column-lock::before { - content: "\e678"; } - -.fa-church::before { - content: "\f51d"; } - -.fa-comments-dollar::before { - content: "\f653"; } - -.fa-democrat::before { - content: "\f747"; } - -.fa-z::before { - content: "\5a"; } - -.fa-person-skiing::before { - content: "\f7c9"; } - -.fa-skiing::before { - content: "\f7c9"; } - -.fa-road-lock::before { - content: "\e567"; } - -.fa-a::before { - content: "\41"; } - -.fa-temperature-arrow-down::before { - content: "\e03f"; } - -.fa-temperature-down::before { - content: "\e03f"; } - -.fa-feather-pointed::before { - content: "\f56b"; } - -.fa-feather-alt::before { - content: "\f56b"; } - -.fa-p::before { - content: "\50"; } - -.fa-snowflake::before { - content: "\f2dc"; } - -.fa-newspaper::before { - content: "\f1ea"; } - -.fa-rectangle-ad::before { - content: "\f641"; } - -.fa-ad::before { - content: "\f641"; } - -.fa-circle-arrow-right::before { - content: "\f0a9"; } - -.fa-arrow-circle-right::before { - content: "\f0a9"; } - -.fa-filter-circle-xmark::before { - content: "\e17b"; } - -.fa-locust::before { - content: "\e520"; } - -.fa-sort::before { - content: "\f0dc"; } - -.fa-unsorted::before { - content: "\f0dc"; } - -.fa-list-ol::before { - content: "\f0cb"; } - -.fa-list-1-2::before { - content: "\f0cb"; } - -.fa-list-numeric::before { - content: "\f0cb"; } - -.fa-person-dress-burst::before { - content: "\e544"; } - -.fa-money-check-dollar::before { - content: "\f53d"; } - -.fa-money-check-alt::before { - content: "\f53d"; } - -.fa-vector-square::before { - content: "\f5cb"; } - -.fa-bread-slice::before { - content: "\f7ec"; } - -.fa-language::before { - content: "\f1ab"; } - -.fa-face-kiss-wink-heart::before { - content: "\f598"; } - -.fa-kiss-wink-heart::before { - content: "\f598"; } - -.fa-filter::before { - content: "\f0b0"; } - -.fa-question::before { - content: "\3f"; } - -.fa-file-signature::before { - content: "\f573"; } - -.fa-up-down-left-right::before { - content: "\f0b2"; } - -.fa-arrows-alt::before { - content: "\f0b2"; } - -.fa-house-chimney-user::before { - content: "\e065"; } - -.fa-hand-holding-heart::before { - content: "\f4be"; } - -.fa-puzzle-piece::before { - content: "\f12e"; } - -.fa-money-check::before { - content: "\f53c"; } - -.fa-star-half-stroke::before { - content: "\f5c0"; } - -.fa-star-half-alt::before { - content: "\f5c0"; } - -.fa-code::before { - content: "\f121"; } - -.fa-whiskey-glass::before { - content: "\f7a0"; } - -.fa-glass-whiskey::before { - content: "\f7a0"; } - -.fa-building-circle-exclamation::before { - content: "\e4d3"; } - -.fa-magnifying-glass-chart::before { - content: "\e522"; } - -.fa-arrow-up-right-from-square::before { - content: "\f08e"; } - -.fa-external-link::before { - content: "\f08e"; } - -.fa-cubes-stacked::before { - content: "\e4e6"; } - -.fa-won-sign::before { - content: "\f159"; } - -.fa-krw::before { - content: "\f159"; } - -.fa-won::before { - content: "\f159"; } - -.fa-virus-covid::before { - content: "\e4a8"; } - -.fa-austral-sign::before { - content: "\e0a9"; } - -.fa-f::before { - content: "\46"; } - -.fa-leaf::before { - content: "\f06c"; } - -.fa-road::before { - content: "\f018"; } - -.fa-taxi::before { - content: "\f1ba"; } - -.fa-cab::before { - content: "\f1ba"; } - -.fa-person-circle-plus::before { - content: "\e541"; } - -.fa-chart-pie::before { - content: "\f200"; } - -.fa-pie-chart::before { - content: "\f200"; } - -.fa-bolt-lightning::before { - content: "\e0b7"; } - -.fa-sack-xmark::before { - content: "\e56a"; } - -.fa-file-excel::before { - content: "\f1c3"; } - -.fa-file-contract::before { - content: "\f56c"; } - -.fa-fish-fins::before { - content: "\e4f2"; } - -.fa-building-flag::before { - content: "\e4d5"; } - -.fa-face-grin-beam::before { - content: "\f582"; } - -.fa-grin-beam::before { - content: "\f582"; } - -.fa-object-ungroup::before { - content: "\f248"; } - -.fa-poop::before { - content: "\f619"; } - -.fa-location-pin::before { - content: "\f041"; } - -.fa-map-marker::before { - content: "\f041"; } - -.fa-kaaba::before { - content: "\f66b"; } - -.fa-toilet-paper::before { - content: "\f71e"; } - -.fa-helmet-safety::before { - content: "\f807"; } - -.fa-hard-hat::before { - content: "\f807"; } - -.fa-hat-hard::before { - content: "\f807"; } - -.fa-eject::before { - content: "\f052"; } - -.fa-circle-right::before { - content: "\f35a"; } - -.fa-arrow-alt-circle-right::before { - content: "\f35a"; } - -.fa-plane-circle-check::before { - content: "\e555"; } - -.fa-face-rolling-eyes::before { - content: "\f5a5"; } - -.fa-meh-rolling-eyes::before { - content: "\f5a5"; } - -.fa-object-group::before { - content: "\f247"; } - -.fa-chart-line::before { - content: "\f201"; } - -.fa-line-chart::before { - content: "\f201"; } - -.fa-mask-ventilator::before { - content: "\e524"; } - -.fa-arrow-right::before { - content: "\f061"; } - -.fa-signs-post::before { - content: "\f277"; } - -.fa-map-signs::before { - content: "\f277"; } - -.fa-cash-register::before { - content: "\f788"; } - -.fa-person-circle-question::before { - content: "\e542"; } - -.fa-h::before { - content: "\48"; } - -.fa-tarp::before { - content: "\e57b"; } - -.fa-screwdriver-wrench::before { - content: "\f7d9"; } - -.fa-tools::before { - content: "\f7d9"; } - -.fa-arrows-to-eye::before { - content: "\e4bf"; } - -.fa-plug-circle-bolt::before { - content: "\e55b"; } - -.fa-heart::before { - content: "\f004"; } - -.fa-mars-and-venus::before { - content: "\f224"; } - -.fa-house-user::before { - content: "\e1b0"; } - -.fa-home-user::before { - content: "\e1b0"; } - -.fa-dumpster-fire::before { - content: "\f794"; } - -.fa-house-crack::before { - content: "\e3b1"; } - -.fa-martini-glass-citrus::before { - content: "\f561"; } - -.fa-cocktail::before { - content: "\f561"; } - -.fa-face-surprise::before { - content: "\f5c2"; } - -.fa-surprise::before { - content: "\f5c2"; } - -.fa-bottle-water::before { - content: "\e4c5"; } - -.fa-circle-pause::before { - content: "\f28b"; } - -.fa-pause-circle::before { - content: "\f28b"; } - -.fa-toilet-paper-slash::before { - content: "\e072"; } - -.fa-apple-whole::before { - content: "\f5d1"; } - -.fa-apple-alt::before { - content: "\f5d1"; } - -.fa-kitchen-set::before { - content: "\e51a"; } - -.fa-r::before { - content: "\52"; } - -.fa-temperature-quarter::before { - content: "\f2ca"; } - -.fa-temperature-1::before { - content: "\f2ca"; } - -.fa-thermometer-1::before { - content: "\f2ca"; } - -.fa-thermometer-quarter::before { - content: "\f2ca"; } - -.fa-cube::before { - content: "\f1b2"; } - -.fa-bitcoin-sign::before { - content: "\e0b4"; } - -.fa-shield-dog::before { - content: "\e573"; } - -.fa-solar-panel::before { - content: "\f5ba"; } - -.fa-lock-open::before { - content: "\f3c1"; } - -.fa-elevator::before { - content: "\e16d"; } - -.fa-money-bill-transfer::before { - content: "\e528"; } - -.fa-money-bill-trend-up::before { - content: "\e529"; } - -.fa-house-flood-water-circle-arrow-right::before { - content: "\e50f"; } - -.fa-square-poll-horizontal::before { - content: "\f682"; } - -.fa-poll-h::before { - content: "\f682"; } - -.fa-circle::before { - content: "\f111"; } - -.fa-backward-fast::before { - content: "\f049"; } - -.fa-fast-backward::before { - content: "\f049"; } - -.fa-recycle::before { - content: "\f1b8"; } - -.fa-user-astronaut::before { - content: "\f4fb"; } - -.fa-plane-slash::before { - content: "\e069"; } - -.fa-trademark::before { - content: "\f25c"; } - -.fa-basketball::before { - content: "\f434"; } - -.fa-basketball-ball::before { - content: "\f434"; } - -.fa-satellite-dish::before { - content: "\f7c0"; } - -.fa-circle-up::before { - content: "\f35b"; } - -.fa-arrow-alt-circle-up::before { - content: "\f35b"; } - -.fa-mobile-screen-button::before { - content: "\f3cd"; } - -.fa-mobile-alt::before { - content: "\f3cd"; } - -.fa-volume-high::before { - content: "\f028"; } - -.fa-volume-up::before { - content: "\f028"; } - -.fa-users-rays::before { - content: "\e593"; } - -.fa-wallet::before { - content: "\f555"; } - -.fa-clipboard-check::before { - content: "\f46c"; } - -.fa-file-audio::before { - content: "\f1c7"; } - -.fa-burger::before { - content: "\f805"; } - -.fa-hamburger::before { - content: "\f805"; } - -.fa-wrench::before { - content: "\f0ad"; } - -.fa-bugs::before { - content: "\e4d0"; } - -.fa-rupee-sign::before { - content: "\f156"; } - -.fa-rupee::before { - content: "\f156"; } - -.fa-file-image::before { - content: "\f1c5"; } - -.fa-circle-question::before { - content: "\f059"; } - -.fa-question-circle::before { - content: "\f059"; } - -.fa-plane-departure::before { - content: "\f5b0"; } - -.fa-handshake-slash::before { - content: "\e060"; } - -.fa-book-bookmark::before { - content: "\e0bb"; } - -.fa-code-branch::before { - content: "\f126"; } - -.fa-hat-cowboy::before { - content: "\f8c0"; } - -.fa-bridge::before { - content: "\e4c8"; } - -.fa-phone-flip::before { - content: "\f879"; } - -.fa-phone-alt::before { - content: "\f879"; } - -.fa-truck-front::before { - content: "\e2b7"; } - -.fa-cat::before { - content: "\f6be"; } - -.fa-anchor-circle-exclamation::before { - content: "\e4ab"; } - -.fa-truck-field::before { - content: "\e58d"; } - -.fa-route::before { - content: "\f4d7"; } - -.fa-clipboard-question::before { - content: "\e4e3"; } - -.fa-panorama::before { - content: "\e209"; } - -.fa-comment-medical::before { - content: "\f7f5"; } - -.fa-teeth-open::before { - content: "\f62f"; } - -.fa-file-circle-minus::before { - content: "\e4ed"; } - -.fa-tags::before { - content: "\f02c"; } - -.fa-wine-glass::before { - content: "\f4e3"; } - -.fa-forward-fast::before { - content: "\f050"; } - -.fa-fast-forward::before { - content: "\f050"; } - -.fa-face-meh-blank::before { - content: "\f5a4"; } - -.fa-meh-blank::before { - content: "\f5a4"; } - -.fa-square-parking::before { - content: "\f540"; } - -.fa-parking::before { - content: "\f540"; } - -.fa-house-signal::before { - content: "\e012"; } - -.fa-bars-progress::before { - content: "\f828"; } - -.fa-tasks-alt::before { - content: "\f828"; } - -.fa-faucet-drip::before { - content: "\e006"; } - -.fa-cart-flatbed::before { - content: "\f474"; } - -.fa-dolly-flatbed::before { - content: "\f474"; } - -.fa-ban-smoking::before { - content: "\f54d"; } - -.fa-smoking-ban::before { - content: "\f54d"; } - -.fa-terminal::before { - content: "\f120"; } - -.fa-mobile-button::before { - content: "\f10b"; } - -.fa-house-medical-flag::before { - content: "\e514"; } - -.fa-basket-shopping::before { - content: "\f291"; } - -.fa-shopping-basket::before { - content: "\f291"; } - -.fa-tape::before { - content: "\f4db"; } - -.fa-bus-simple::before { - content: "\f55e"; } - -.fa-bus-alt::before { - content: "\f55e"; } - -.fa-eye::before { - content: "\f06e"; } - -.fa-face-sad-cry::before { - content: "\f5b3"; } - -.fa-sad-cry::before { - content: "\f5b3"; } - -.fa-audio-description::before { - content: "\f29e"; } - -.fa-person-military-to-person::before { - content: "\e54c"; } - -.fa-file-shield::before { - content: "\e4f0"; } - -.fa-user-slash::before { - content: "\f506"; } - -.fa-pen::before { - content: "\f304"; } - -.fa-tower-observation::before { - content: "\e586"; } - -.fa-file-code::before { - content: "\f1c9"; } - -.fa-signal::before { - content: "\f012"; } - -.fa-signal-5::before { - content: "\f012"; } - -.fa-signal-perfect::before { - content: "\f012"; } - -.fa-bus::before { - content: "\f207"; } - -.fa-heart-circle-xmark::before { - content: "\e501"; } - -.fa-house-chimney::before { - content: "\e3af"; } - -.fa-home-lg::before { - content: "\e3af"; } - -.fa-window-maximize::before { - content: "\f2d0"; } - -.fa-face-frown::before { - content: "\f119"; } - -.fa-frown::before { - content: "\f119"; } - -.fa-prescription::before { - content: "\f5b1"; } - -.fa-shop::before { - content: "\f54f"; } - -.fa-store-alt::before { - content: "\f54f"; } - -.fa-floppy-disk::before { - content: "\f0c7"; } - -.fa-save::before { - content: "\f0c7"; } - -.fa-vihara::before { - content: "\f6a7"; } - -.fa-scale-unbalanced::before { - content: "\f515"; } - -.fa-balance-scale-left::before { - content: "\f515"; } - -.fa-sort-up::before { - content: "\f0de"; } - -.fa-sort-asc::before { - content: "\f0de"; } - -.fa-comment-dots::before { - content: "\f4ad"; } - -.fa-commenting::before { - content: "\f4ad"; } - -.fa-plant-wilt::before { - content: "\e5aa"; } - -.fa-diamond::before { - content: "\f219"; } - -.fa-face-grin-squint::before { - content: "\f585"; } - -.fa-grin-squint::before { - content: "\f585"; } - -.fa-hand-holding-dollar::before { - content: "\f4c0"; } - -.fa-hand-holding-usd::before { - content: "\f4c0"; } - -.fa-bacterium::before { - content: "\e05a"; } - -.fa-hand-pointer::before { - content: "\f25a"; } - -.fa-drum-steelpan::before { - content: "\f56a"; } - -.fa-hand-scissors::before { - content: "\f257"; } - -.fa-hands-praying::before { - content: "\f684"; } - -.fa-praying-hands::before { - content: "\f684"; } - -.fa-arrow-rotate-right::before { - content: "\f01e"; } - -.fa-arrow-right-rotate::before { - content: "\f01e"; } - -.fa-arrow-rotate-forward::before { - content: "\f01e"; } - -.fa-redo::before { - content: "\f01e"; } - -.fa-biohazard::before { - content: "\f780"; } - -.fa-location-crosshairs::before { - content: "\f601"; } - -.fa-location::before { - content: "\f601"; } - -.fa-mars-double::before { - content: "\f227"; } - -.fa-child-dress::before { - content: "\e59c"; } - -.fa-users-between-lines::before { - content: "\e591"; } - -.fa-lungs-virus::before { - content: "\e067"; } - -.fa-face-grin-tears::before { - content: "\f588"; } - -.fa-grin-tears::before { - content: "\f588"; } - -.fa-phone::before { - content: "\f095"; } - -.fa-calendar-xmark::before { - content: "\f273"; } - -.fa-calendar-times::before { - content: "\f273"; } - -.fa-child-reaching::before { - content: "\e59d"; } - -.fa-head-side-virus::before { - content: "\e064"; } - -.fa-user-gear::before { - content: "\f4fe"; } - -.fa-user-cog::before { - content: "\f4fe"; } - -.fa-arrow-up-1-9::before { - content: "\f163"; } - -.fa-sort-numeric-up::before { - content: "\f163"; } - -.fa-door-closed::before { - content: "\f52a"; } - -.fa-shield-virus::before { - content: "\e06c"; } - -.fa-dice-six::before { - content: "\f526"; } - -.fa-mosquito-net::before { - content: "\e52c"; } - -.fa-bridge-water::before { - content: "\e4ce"; } - -.fa-person-booth::before { - content: "\f756"; } - -.fa-text-width::before { - content: "\f035"; } - -.fa-hat-wizard::before { - content: "\f6e8"; } - -.fa-pen-fancy::before { - content: "\f5ac"; } - -.fa-person-digging::before { - content: "\f85e"; } - -.fa-digging::before { - content: "\f85e"; } - -.fa-trash::before { - content: "\f1f8"; } - -.fa-gauge-simple::before { - content: "\f629"; } - -.fa-gauge-simple-med::before { - content: "\f629"; } - -.fa-tachometer-average::before { - content: "\f629"; } - -.fa-book-medical::before { - content: "\f7e6"; } - -.fa-poo::before { - content: "\f2fe"; } - -.fa-quote-right::before { - content: "\f10e"; } - -.fa-quote-right-alt::before { - content: "\f10e"; } - -.fa-shirt::before { - content: "\f553"; } - -.fa-t-shirt::before { - content: "\f553"; } - -.fa-tshirt::before { - content: "\f553"; } - -.fa-cubes::before { - content: "\f1b3"; } - -.fa-divide::before { - content: "\f529"; } - -.fa-tenge-sign::before { - content: "\f7d7"; } - -.fa-tenge::before { - content: "\f7d7"; } - -.fa-headphones::before { - content: "\f025"; } - -.fa-hands-holding::before { - content: "\f4c2"; } - -.fa-hands-clapping::before { - content: "\e1a8"; } - -.fa-republican::before { - content: "\f75e"; } - -.fa-arrow-left::before { - content: "\f060"; } - -.fa-person-circle-xmark::before { - content: "\e543"; } - -.fa-ruler::before { - content: "\f545"; } - -.fa-align-left::before { - content: "\f036"; } - -.fa-dice-d6::before { - content: "\f6d1"; } - -.fa-restroom::before { - content: "\f7bd"; } - -.fa-j::before { - content: "\4a"; } - -.fa-users-viewfinder::before { - content: "\e595"; } - -.fa-file-video::before { - content: "\f1c8"; } - -.fa-up-right-from-square::before { - content: "\f35d"; } - -.fa-external-link-alt::before { - content: "\f35d"; } - -.fa-table-cells::before { - content: "\f00a"; } - -.fa-th::before { - content: "\f00a"; } - -.fa-file-pdf::before { - content: "\f1c1"; } - -.fa-book-bible::before { - content: "\f647"; } - -.fa-bible::before { - content: "\f647"; } - -.fa-o::before { - content: "\4f"; } - -.fa-suitcase-medical::before { - content: "\f0fa"; } - -.fa-medkit::before { - content: "\f0fa"; } - -.fa-user-secret::before { - content: "\f21b"; } - -.fa-otter::before { - content: "\f700"; } - -.fa-person-dress::before { - content: "\f182"; } - -.fa-female::before { - content: "\f182"; } - -.fa-comment-dollar::before { - content: "\f651"; } - -.fa-business-time::before { - content: "\f64a"; } - -.fa-briefcase-clock::before { - content: "\f64a"; } - -.fa-table-cells-large::before { - content: "\f009"; } - -.fa-th-large::before { - content: "\f009"; } - -.fa-book-tanakh::before { - content: "\f827"; } - -.fa-tanakh::before { - content: "\f827"; } - -.fa-phone-volume::before { - content: "\f2a0"; } - -.fa-volume-control-phone::before { - content: "\f2a0"; } - -.fa-hat-cowboy-side::before { - content: "\f8c1"; } - -.fa-clipboard-user::before { - content: "\f7f3"; } - -.fa-child::before { - content: "\f1ae"; } - -.fa-lira-sign::before { - content: "\f195"; } - -.fa-satellite::before { - content: "\f7bf"; } - -.fa-plane-lock::before { - content: "\e558"; } - -.fa-tag::before { - content: "\f02b"; } - -.fa-comment::before { - content: "\f075"; } - -.fa-cake-candles::before { - content: "\f1fd"; } - -.fa-birthday-cake::before { - content: "\f1fd"; } - -.fa-cake::before { - content: "\f1fd"; } - -.fa-envelope::before { - content: "\f0e0"; } - -.fa-angles-up::before { - content: "\f102"; } - -.fa-angle-double-up::before { - content: "\f102"; } - -.fa-paperclip::before { - content: "\f0c6"; } - -.fa-arrow-right-to-city::before { - content: "\e4b3"; } - -.fa-ribbon::before { - content: "\f4d6"; } - -.fa-lungs::before { - content: "\f604"; } - -.fa-arrow-up-9-1::before { - content: "\f887"; } - -.fa-sort-numeric-up-alt::before { - content: "\f887"; } - -.fa-litecoin-sign::before { - content: "\e1d3"; } - -.fa-border-none::before { - content: "\f850"; } - -.fa-circle-nodes::before { - content: "\e4e2"; } - -.fa-parachute-box::before { - content: "\f4cd"; } - -.fa-indent::before { - content: "\f03c"; } - -.fa-truck-field-un::before { - content: "\e58e"; } - -.fa-hourglass::before { - content: "\f254"; } - -.fa-hourglass-empty::before { - content: "\f254"; } - -.fa-mountain::before { - content: "\f6fc"; } - -.fa-user-doctor::before { - content: "\f0f0"; } - -.fa-user-md::before { - content: "\f0f0"; } - -.fa-circle-info::before { - content: "\f05a"; } - -.fa-info-circle::before { - content: "\f05a"; } - -.fa-cloud-meatball::before { - content: "\f73b"; } - -.fa-camera::before { - content: "\f030"; } - -.fa-camera-alt::before { - content: "\f030"; } - -.fa-square-virus::before { - content: "\e578"; } - -.fa-meteor::before { - content: "\f753"; } - -.fa-car-on::before { - content: "\e4dd"; } - -.fa-sleigh::before { - content: "\f7cc"; } - -.fa-arrow-down-1-9::before { - content: "\f162"; } - -.fa-sort-numeric-asc::before { - content: "\f162"; } - -.fa-sort-numeric-down::before { - content: "\f162"; } - -.fa-hand-holding-droplet::before { - content: "\f4c1"; } - -.fa-hand-holding-water::before { - content: "\f4c1"; } - -.fa-water::before { - content: "\f773"; } - -.fa-calendar-check::before { - content: "\f274"; } - -.fa-braille::before { - content: "\f2a1"; } - -.fa-prescription-bottle-medical::before { - content: "\f486"; } - -.fa-prescription-bottle-alt::before { - content: "\f486"; } - -.fa-landmark::before { - content: "\f66f"; } - -.fa-truck::before { - content: "\f0d1"; } - -.fa-crosshairs::before { - content: "\f05b"; } - -.fa-person-cane::before { - content: "\e53c"; } - -.fa-tent::before { - content: "\e57d"; } - -.fa-vest-patches::before { - content: "\e086"; } - -.fa-check-double::before { - content: "\f560"; } - -.fa-arrow-down-a-z::before { - content: "\f15d"; } - -.fa-sort-alpha-asc::before { - content: "\f15d"; } - -.fa-sort-alpha-down::before { - content: "\f15d"; } - -.fa-money-bill-wheat::before { - content: "\e52a"; } - -.fa-cookie::before { - content: "\f563"; } - -.fa-arrow-rotate-left::before { - content: "\f0e2"; } - -.fa-arrow-left-rotate::before { - content: "\f0e2"; } - -.fa-arrow-rotate-back::before { - content: "\f0e2"; } - -.fa-arrow-rotate-backward::before { - content: "\f0e2"; } - -.fa-undo::before { - content: "\f0e2"; } - -.fa-hard-drive::before { - content: "\f0a0"; } - -.fa-hdd::before { - content: "\f0a0"; } - -.fa-face-grin-squint-tears::before { - content: "\f586"; } - -.fa-grin-squint-tears::before { - content: "\f586"; } - -.fa-dumbbell::before { - content: "\f44b"; } - -.fa-rectangle-list::before { - content: "\f022"; } - -.fa-list-alt::before { - content: "\f022"; } - -.fa-tarp-droplet::before { - content: "\e57c"; } - -.fa-house-medical-circle-check::before { - content: "\e511"; } - -.fa-person-skiing-nordic::before { - content: "\f7ca"; } - -.fa-skiing-nordic::before { - content: "\f7ca"; } - -.fa-calendar-plus::before { - content: "\f271"; } - -.fa-plane-arrival::before { - content: "\f5af"; } - -.fa-circle-left::before { - content: "\f359"; } - -.fa-arrow-alt-circle-left::before { - content: "\f359"; } - -.fa-train-subway::before { - content: "\f239"; } - -.fa-subway::before { - content: "\f239"; } - -.fa-chart-gantt::before { - content: "\e0e4"; } - -.fa-indian-rupee-sign::before { - content: "\e1bc"; } - -.fa-indian-rupee::before { - content: "\e1bc"; } - -.fa-inr::before { - content: "\e1bc"; } - -.fa-crop-simple::before { - content: "\f565"; } - -.fa-crop-alt::before { - content: "\f565"; } - -.fa-money-bill-1::before { - content: "\f3d1"; } - -.fa-money-bill-alt::before { - content: "\f3d1"; } - -.fa-left-long::before { - content: "\f30a"; } - -.fa-long-arrow-alt-left::before { - content: "\f30a"; } - -.fa-dna::before { - content: "\f471"; } - -.fa-virus-slash::before { - content: "\e075"; } - -.fa-minus::before { - content: "\f068"; } - -.fa-subtract::before { - content: "\f068"; } - -.fa-chess::before { - content: "\f439"; } - -.fa-arrow-left-long::before { - content: "\f177"; } - -.fa-long-arrow-left::before { - content: "\f177"; } - -.fa-plug-circle-check::before { - content: "\e55c"; } - -.fa-street-view::before { - content: "\f21d"; } - -.fa-franc-sign::before { - content: "\e18f"; } - -.fa-volume-off::before { - content: "\f026"; } - -.fa-hands-asl-interpreting::before { - content: "\f2a3"; } - -.fa-american-sign-language-interpreting::before { - content: "\f2a3"; } - -.fa-asl-interpreting::before { - content: "\f2a3"; } - -.fa-hands-american-sign-language-interpreting::before { - content: "\f2a3"; } - -.fa-gear::before { - content: "\f013"; } - -.fa-cog::before { - content: "\f013"; } - -.fa-droplet-slash::before { - content: "\f5c7"; } - -.fa-tint-slash::before { - content: "\f5c7"; } - -.fa-mosque::before { - content: "\f678"; } - -.fa-mosquito::before { - content: "\e52b"; } - -.fa-star-of-david::before { - content: "\f69a"; } - -.fa-person-military-rifle::before { - content: "\e54b"; } - -.fa-cart-shopping::before { - content: "\f07a"; } - -.fa-shopping-cart::before { - content: "\f07a"; } - -.fa-vials::before { - content: "\f493"; } - -.fa-plug-circle-plus::before { - content: "\e55f"; } - -.fa-place-of-worship::before { - content: "\f67f"; } - -.fa-grip-vertical::before { - content: "\f58e"; } - -.fa-arrow-turn-up::before { - content: "\f148"; } - -.fa-level-up::before { - content: "\f148"; } - -.fa-u::before { - content: "\55"; } - -.fa-square-root-variable::before { - content: "\f698"; } - -.fa-square-root-alt::before { - content: "\f698"; } - -.fa-clock::before { - content: "\f017"; } - -.fa-clock-four::before { - content: "\f017"; } - -.fa-backward-step::before { - content: "\f048"; } - -.fa-step-backward::before { - content: "\f048"; } - -.fa-pallet::before { - content: "\f482"; } - -.fa-faucet::before { - content: "\e005"; } - -.fa-baseball-bat-ball::before { - content: "\f432"; } - -.fa-s::before { - content: "\53"; } - -.fa-timeline::before { - content: "\e29c"; } - -.fa-keyboard::before { - content: "\f11c"; } - -.fa-caret-down::before { - content: "\f0d7"; } - -.fa-house-chimney-medical::before { - content: "\f7f2"; } - -.fa-clinic-medical::before { - content: "\f7f2"; } - -.fa-temperature-three-quarters::before { - content: "\f2c8"; } - -.fa-temperature-3::before { - content: "\f2c8"; } - -.fa-thermometer-3::before { - content: "\f2c8"; } - -.fa-thermometer-three-quarters::before { - content: "\f2c8"; } - -.fa-mobile-screen::before { - content: "\f3cf"; } - -.fa-mobile-android-alt::before { - content: "\f3cf"; } - -.fa-plane-up::before { - content: "\e22d"; } - -.fa-piggy-bank::before { - content: "\f4d3"; } - -.fa-battery-half::before { - content: "\f242"; } - -.fa-battery-3::before { - content: "\f242"; } - -.fa-mountain-city::before { - content: "\e52e"; } - -.fa-coins::before { - content: "\f51e"; } - -.fa-khanda::before { - content: "\f66d"; } - -.fa-sliders::before { - content: "\f1de"; } - -.fa-sliders-h::before { - content: "\f1de"; } - -.fa-folder-tree::before { - content: "\f802"; } - -.fa-network-wired::before { - content: "\f6ff"; } - -.fa-map-pin::before { - content: "\f276"; } - -.fa-hamsa::before { - content: "\f665"; } - -.fa-cent-sign::before { - content: "\e3f5"; } - -.fa-flask::before { - content: "\f0c3"; } - -.fa-person-pregnant::before { - content: "\e31e"; } - -.fa-wand-sparkles::before { - content: "\f72b"; } - -.fa-ellipsis-vertical::before { - content: "\f142"; } - -.fa-ellipsis-v::before { - content: "\f142"; } - -.fa-ticket::before { - content: "\f145"; } - -.fa-power-off::before { - content: "\f011"; } - -.fa-right-long::before { - content: "\f30b"; } - -.fa-long-arrow-alt-right::before { - content: "\f30b"; } - -.fa-flag-usa::before { - content: "\f74d"; } - -.fa-laptop-file::before { - content: "\e51d"; } - -.fa-tty::before { - content: "\f1e4"; } - -.fa-teletype::before { - content: "\f1e4"; } - -.fa-diagram-next::before { - content: "\e476"; } - -.fa-person-rifle::before { - content: "\e54e"; } - -.fa-house-medical-circle-exclamation::before { - content: "\e512"; } - -.fa-closed-captioning::before { - content: "\f20a"; } - -.fa-person-hiking::before { - content: "\f6ec"; } - -.fa-hiking::before { - content: "\f6ec"; } - -.fa-venus-double::before { - content: "\f226"; } - -.fa-images::before { - content: "\f302"; } - -.fa-calculator::before { - content: "\f1ec"; } - -.fa-people-pulling::before { - content: "\e535"; } - -.fa-n::before { - content: "\4e"; } - -.fa-cable-car::before { - content: "\f7da"; } - -.fa-tram::before { - content: "\f7da"; } - -.fa-cloud-rain::before { - content: "\f73d"; } - -.fa-building-circle-xmark::before { - content: "\e4d4"; } - -.fa-ship::before { - content: "\f21a"; } - -.fa-arrows-down-to-line::before { - content: "\e4b8"; } - -.fa-download::before { - content: "\f019"; } - -.fa-face-grin::before { - content: "\f580"; } - -.fa-grin::before { - content: "\f580"; } - -.fa-delete-left::before { - content: "\f55a"; } - -.fa-backspace::before { - content: "\f55a"; } - -.fa-eye-dropper::before { - content: "\f1fb"; } - -.fa-eye-dropper-empty::before { - content: "\f1fb"; } - -.fa-eyedropper::before { - content: "\f1fb"; } - -.fa-file-circle-check::before { - content: "\e5a0"; } - -.fa-forward::before { - content: "\f04e"; } - -.fa-mobile::before { - content: "\f3ce"; } - -.fa-mobile-android::before { - content: "\f3ce"; } - -.fa-mobile-phone::before { - content: "\f3ce"; } - -.fa-face-meh::before { - content: "\f11a"; } - -.fa-meh::before { - content: "\f11a"; } - -.fa-align-center::before { - content: "\f037"; } - -.fa-book-skull::before { - content: "\f6b7"; } - -.fa-book-dead::before { - content: "\f6b7"; } - -.fa-id-card::before { - content: "\f2c2"; } - -.fa-drivers-license::before { - content: "\f2c2"; } - -.fa-outdent::before { - content: "\f03b"; } - -.fa-dedent::before { - content: "\f03b"; } - -.fa-heart-circle-exclamation::before { - content: "\e4fe"; } - -.fa-house::before { - content: "\f015"; } - -.fa-home::before { - content: "\f015"; } - -.fa-home-alt::before { - content: "\f015"; } - -.fa-home-lg-alt::before { - content: "\f015"; } - -.fa-calendar-week::before { - content: "\f784"; } - -.fa-laptop-medical::before { - content: "\f812"; } - -.fa-b::before { - content: "\42"; } - -.fa-file-medical::before { - content: "\f477"; } - -.fa-dice-one::before { - content: "\f525"; } - -.fa-kiwi-bird::before { - content: "\f535"; } - -.fa-arrow-right-arrow-left::before { - content: "\f0ec"; } - -.fa-exchange::before { - content: "\f0ec"; } - -.fa-rotate-right::before { - content: "\f2f9"; } - -.fa-redo-alt::before { - content: "\f2f9"; } - -.fa-rotate-forward::before { - content: "\f2f9"; } - -.fa-utensils::before { - content: "\f2e7"; } - -.fa-cutlery::before { - content: "\f2e7"; } - -.fa-arrow-up-wide-short::before { - content: "\f161"; } - -.fa-sort-amount-up::before { - content: "\f161"; } - -.fa-mill-sign::before { - content: "\e1ed"; } - -.fa-bowl-rice::before { - content: "\e2eb"; } - -.fa-skull::before { - content: "\f54c"; } - -.fa-tower-broadcast::before { - content: "\f519"; } - -.fa-broadcast-tower::before { - content: "\f519"; } - -.fa-truck-pickup::before { - content: "\f63c"; } - -.fa-up-long::before { - content: "\f30c"; } - -.fa-long-arrow-alt-up::before { - content: "\f30c"; } - -.fa-stop::before { - content: "\f04d"; } - -.fa-code-merge::before { - content: "\f387"; } - -.fa-upload::before { - content: "\f093"; } - -.fa-hurricane::before { - content: "\f751"; } - -.fa-mound::before { - content: "\e52d"; } - -.fa-toilet-portable::before { - content: "\e583"; } - -.fa-compact-disc::before { - content: "\f51f"; } - -.fa-file-arrow-down::before { - content: "\f56d"; } - -.fa-file-download::before { - content: "\f56d"; } - -.fa-caravan::before { - content: "\f8ff"; } - -.fa-shield-cat::before { - content: "\e572"; } - -.fa-bolt::before { - content: "\f0e7"; } - -.fa-zap::before { - content: "\f0e7"; } - -.fa-glass-water::before { - content: "\e4f4"; } - -.fa-oil-well::before { - content: "\e532"; } - -.fa-vault::before { - content: "\e2c5"; } - -.fa-mars::before { - content: "\f222"; } - -.fa-toilet::before { - content: "\f7d8"; } - -.fa-plane-circle-xmark::before { - content: "\e557"; } - -.fa-yen-sign::before { - content: "\f157"; } - -.fa-cny::before { - content: "\f157"; } - -.fa-jpy::before { - content: "\f157"; } - -.fa-rmb::before { - content: "\f157"; } - -.fa-yen::before { - content: "\f157"; } - -.fa-ruble-sign::before { - content: "\f158"; } - -.fa-rouble::before { - content: "\f158"; } - -.fa-rub::before { - content: "\f158"; } - -.fa-ruble::before { - content: "\f158"; } - -.fa-sun::before { - content: "\f185"; } - -.fa-guitar::before { - content: "\f7a6"; } - -.fa-face-laugh-wink::before { - content: "\f59c"; } - -.fa-laugh-wink::before { - content: "\f59c"; } - -.fa-horse-head::before { - content: "\f7ab"; } - -.fa-bore-hole::before { - content: "\e4c3"; } - -.fa-industry::before { - content: "\f275"; } - -.fa-circle-down::before { - content: "\f358"; } - -.fa-arrow-alt-circle-down::before { - content: "\f358"; } - -.fa-arrows-turn-to-dots::before { - content: "\e4c1"; } - -.fa-florin-sign::before { - content: "\e184"; } - -.fa-arrow-down-short-wide::before { - content: "\f884"; } - -.fa-sort-amount-desc::before { - content: "\f884"; } - -.fa-sort-amount-down-alt::before { - content: "\f884"; } - -.fa-less-than::before { - content: "\3c"; } - -.fa-angle-down::before { - content: "\f107"; } - -.fa-car-tunnel::before { - content: "\e4de"; } - -.fa-head-side-cough::before { - content: "\e061"; } - -.fa-grip-lines::before { - content: "\f7a4"; } - -.fa-thumbs-down::before { - content: "\f165"; } - -.fa-user-lock::before { - content: "\f502"; } - -.fa-arrow-right-long::before { - content: "\f178"; } - -.fa-long-arrow-right::before { - content: "\f178"; } - -.fa-anchor-circle-xmark::before { - content: "\e4ac"; } - -.fa-ellipsis::before { - content: "\f141"; } - -.fa-ellipsis-h::before { - content: "\f141"; } - -.fa-chess-pawn::before { - content: "\f443"; } - -.fa-kit-medical::before { - content: "\f479"; } - -.fa-first-aid::before { - content: "\f479"; } - -.fa-person-through-window::before { - content: "\e5a9"; } - -.fa-toolbox::before { - content: "\f552"; } - -.fa-hands-holding-circle::before { - content: "\e4fb"; } - -.fa-bug::before { - content: "\f188"; } - -.fa-credit-card::before { - content: "\f09d"; } - -.fa-credit-card-alt::before { - content: "\f09d"; } - -.fa-car::before { - content: "\f1b9"; } - -.fa-automobile::before { - content: "\f1b9"; } - -.fa-hand-holding-hand::before { - content: "\e4f7"; } - -.fa-book-open-reader::before { - content: "\f5da"; } - -.fa-book-reader::before { - content: "\f5da"; } - -.fa-mountain-sun::before { - content: "\e52f"; } - -.fa-arrows-left-right-to-line::before { - content: "\e4ba"; } - -.fa-dice-d20::before { - content: "\f6cf"; } - -.fa-truck-droplet::before { - content: "\e58c"; } - -.fa-file-circle-xmark::before { - content: "\e5a1"; } - -.fa-temperature-arrow-up::before { - content: "\e040"; } - -.fa-temperature-up::before { - content: "\e040"; } - -.fa-medal::before { - content: "\f5a2"; } - -.fa-bed::before { - content: "\f236"; } - -.fa-square-h::before { - content: "\f0fd"; } - -.fa-h-square::before { - content: "\f0fd"; } - -.fa-podcast::before { - content: "\f2ce"; } - -.fa-temperature-full::before { - content: "\f2c7"; } - -.fa-temperature-4::before { - content: "\f2c7"; } - -.fa-thermometer-4::before { - content: "\f2c7"; } - -.fa-thermometer-full::before { - content: "\f2c7"; } - -.fa-bell::before { - content: "\f0f3"; } - -.fa-superscript::before { - content: "\f12b"; } - -.fa-plug-circle-xmark::before { - content: "\e560"; } - -.fa-star-of-life::before { - content: "\f621"; } - -.fa-phone-slash::before { - content: "\f3dd"; } - -.fa-paint-roller::before { - content: "\f5aa"; } - -.fa-handshake-angle::before { - content: "\f4c4"; } - -.fa-hands-helping::before { - content: "\f4c4"; } - -.fa-location-dot::before { - content: "\f3c5"; } - -.fa-map-marker-alt::before { - content: "\f3c5"; } - -.fa-file::before { - content: "\f15b"; } - -.fa-greater-than::before { - content: "\3e"; } - -.fa-person-swimming::before { - content: "\f5c4"; } - -.fa-swimmer::before { - content: "\f5c4"; } - -.fa-arrow-down::before { - content: "\f063"; } - -.fa-droplet::before { - content: "\f043"; } - -.fa-tint::before { - content: "\f043"; } - -.fa-eraser::before { - content: "\f12d"; } - -.fa-earth-americas::before { - content: "\f57d"; } - -.fa-earth::before { - content: "\f57d"; } - -.fa-earth-america::before { - content: "\f57d"; } - -.fa-globe-americas::before { - content: "\f57d"; } - -.fa-person-burst::before { - content: "\e53b"; } - -.fa-dove::before { - content: "\f4ba"; } - -.fa-battery-empty::before { - content: "\f244"; } - -.fa-battery-0::before { - content: "\f244"; } - -.fa-socks::before { - content: "\f696"; } - -.fa-inbox::before { - content: "\f01c"; } - -.fa-section::before { - content: "\e447"; } - -.fa-gauge-high::before { - content: "\f625"; } - -.fa-tachometer-alt::before { - content: "\f625"; } - -.fa-tachometer-alt-fast::before { - content: "\f625"; } - -.fa-envelope-open-text::before { - content: "\f658"; } - -.fa-hospital::before { - content: "\f0f8"; } - -.fa-hospital-alt::before { - content: "\f0f8"; } - -.fa-hospital-wide::before { - content: "\f0f8"; } - -.fa-wine-bottle::before { - content: "\f72f"; } - -.fa-chess-rook::before { - content: "\f447"; } - -.fa-bars-staggered::before { - content: "\f550"; } - -.fa-reorder::before { - content: "\f550"; } - -.fa-stream::before { - content: "\f550"; } - -.fa-dharmachakra::before { - content: "\f655"; } - -.fa-hotdog::before { - content: "\f80f"; } - -.fa-person-walking-with-cane::before { - content: "\f29d"; } - -.fa-blind::before { - content: "\f29d"; } - -.fa-drum::before { - content: "\f569"; } - -.fa-ice-cream::before { - content: "\f810"; } - -.fa-heart-circle-bolt::before { - content: "\e4fc"; } - -.fa-fax::before { - content: "\f1ac"; } - -.fa-paragraph::before { - content: "\f1dd"; } - -.fa-check-to-slot::before { - content: "\f772"; } - -.fa-vote-yea::before { - content: "\f772"; } - -.fa-star-half::before { - content: "\f089"; } - -.fa-boxes-stacked::before { - content: "\f468"; } - -.fa-boxes::before { - content: "\f468"; } - -.fa-boxes-alt::before { - content: "\f468"; } - -.fa-link::before { - content: "\f0c1"; } - -.fa-chain::before { - content: "\f0c1"; } - -.fa-ear-listen::before { - content: "\f2a2"; } - -.fa-assistive-listening-systems::before { - content: "\f2a2"; } - -.fa-tree-city::before { - content: "\e587"; } - -.fa-play::before { - content: "\f04b"; } - -.fa-font::before { - content: "\f031"; } - -.fa-table-cells-row-lock::before { - content: "\e67a"; } - -.fa-rupiah-sign::before { - content: "\e23d"; } - -.fa-magnifying-glass::before { - content: "\f002"; } - -.fa-search::before { - content: "\f002"; } - -.fa-table-tennis-paddle-ball::before { - content: "\f45d"; } - -.fa-ping-pong-paddle-ball::before { - content: "\f45d"; } - -.fa-table-tennis::before { - content: "\f45d"; } - -.fa-person-dots-from-line::before { - content: "\f470"; } - -.fa-diagnoses::before { - content: "\f470"; } - -.fa-trash-can-arrow-up::before { - content: "\f82a"; } - -.fa-trash-restore-alt::before { - content: "\f82a"; } - -.fa-naira-sign::before { - content: "\e1f6"; } - -.fa-cart-arrow-down::before { - content: "\f218"; } - -.fa-walkie-talkie::before { - content: "\f8ef"; } - -.fa-file-pen::before { - content: "\f31c"; } - -.fa-file-edit::before { - content: "\f31c"; } - -.fa-receipt::before { - content: "\f543"; } - -.fa-square-pen::before { - content: "\f14b"; } - -.fa-pen-square::before { - content: "\f14b"; } - -.fa-pencil-square::before { - content: "\f14b"; } - -.fa-suitcase-rolling::before { - content: "\f5c1"; } - -.fa-person-circle-exclamation::before { - content: "\e53f"; } - -.fa-chevron-down::before { - content: "\f078"; } - -.fa-battery-full::before { - content: "\f240"; } - -.fa-battery::before { - content: "\f240"; } - -.fa-battery-5::before { - content: "\f240"; } - -.fa-skull-crossbones::before { - content: "\f714"; } - -.fa-code-compare::before { - content: "\e13a"; } - -.fa-list-ul::before { - content: "\f0ca"; } - -.fa-list-dots::before { - content: "\f0ca"; } - -.fa-school-lock::before { - content: "\e56f"; } - -.fa-tower-cell::before { - content: "\e585"; } - -.fa-down-long::before { - content: "\f309"; } - -.fa-long-arrow-alt-down::before { - content: "\f309"; } - -.fa-ranking-star::before { - content: "\e561"; } - -.fa-chess-king::before { - content: "\f43f"; } - -.fa-person-harassing::before { - content: "\e549"; } - -.fa-brazilian-real-sign::before { - content: "\e46c"; } - -.fa-landmark-dome::before { - content: "\f752"; } - -.fa-landmark-alt::before { - content: "\f752"; } - -.fa-arrow-up::before { - content: "\f062"; } - -.fa-tv::before { - content: "\f26c"; } - -.fa-television::before { - content: "\f26c"; } - -.fa-tv-alt::before { - content: "\f26c"; } - -.fa-shrimp::before { - content: "\e448"; } - -.fa-list-check::before { - content: "\f0ae"; } - -.fa-tasks::before { - content: "\f0ae"; } - -.fa-jug-detergent::before { - content: "\e519"; } - -.fa-circle-user::before { - content: "\f2bd"; } - -.fa-user-circle::before { - content: "\f2bd"; } - -.fa-user-shield::before { - content: "\f505"; } - -.fa-wind::before { - content: "\f72e"; } - -.fa-car-burst::before { - content: "\f5e1"; } - -.fa-car-crash::before { - content: "\f5e1"; } - -.fa-y::before { - content: "\59"; } - -.fa-person-snowboarding::before { - content: "\f7ce"; } - -.fa-snowboarding::before { - content: "\f7ce"; } - -.fa-truck-fast::before { - content: "\f48b"; } - -.fa-shipping-fast::before { - content: "\f48b"; } - -.fa-fish::before { - content: "\f578"; } - -.fa-user-graduate::before { - content: "\f501"; } - -.fa-circle-half-stroke::before { - content: "\f042"; } - -.fa-adjust::before { - content: "\f042"; } - -.fa-clapperboard::before { - content: "\e131"; } - -.fa-circle-radiation::before { - content: "\f7ba"; } - -.fa-radiation-alt::before { - content: "\f7ba"; } - -.fa-baseball::before { - content: "\f433"; } - -.fa-baseball-ball::before { - content: "\f433"; } - -.fa-jet-fighter-up::before { - content: "\e518"; } - -.fa-diagram-project::before { - content: "\f542"; } - -.fa-project-diagram::before { - content: "\f542"; } - -.fa-copy::before { - content: "\f0c5"; } - -.fa-volume-xmark::before { - content: "\f6a9"; } - -.fa-volume-mute::before { - content: "\f6a9"; } - -.fa-volume-times::before { - content: "\f6a9"; } - -.fa-hand-sparkles::before { - content: "\e05d"; } - -.fa-grip::before { - content: "\f58d"; } - -.fa-grip-horizontal::before { - content: "\f58d"; } - -.fa-share-from-square::before { - content: "\f14d"; } - -.fa-share-square::before { - content: "\f14d"; } - -.fa-child-combatant::before { - content: "\e4e0"; } - -.fa-child-rifle::before { - content: "\e4e0"; } - -.fa-gun::before { - content: "\e19b"; } - -.fa-square-phone::before { - content: "\f098"; } - -.fa-phone-square::before { - content: "\f098"; } - -.fa-plus::before { - content: "\2b"; } - -.fa-add::before { - content: "\2b"; } - -.fa-expand::before { - content: "\f065"; } - -.fa-computer::before { - content: "\e4e5"; } - -.fa-xmark::before { - content: "\f00d"; } - -.fa-close::before { - content: "\f00d"; } - -.fa-multiply::before { - content: "\f00d"; } - -.fa-remove::before { - content: "\f00d"; } - -.fa-times::before { - content: "\f00d"; } - -.fa-arrows-up-down-left-right::before { - content: "\f047"; } - -.fa-arrows::before { - content: "\f047"; } - -.fa-chalkboard-user::before { - content: "\f51c"; } - -.fa-chalkboard-teacher::before { - content: "\f51c"; } - -.fa-peso-sign::before { - content: "\e222"; } - -.fa-building-shield::before { - content: "\e4d8"; } - -.fa-baby::before { - content: "\f77c"; } - -.fa-users-line::before { - content: "\e592"; } - -.fa-quote-left::before { - content: "\f10d"; } - -.fa-quote-left-alt::before { - content: "\f10d"; } - -.fa-tractor::before { - content: "\f722"; } - -.fa-trash-arrow-up::before { - content: "\f829"; } - -.fa-trash-restore::before { - content: "\f829"; } - -.fa-arrow-down-up-lock::before { - content: "\e4b0"; } - -.fa-lines-leaning::before { - content: "\e51e"; } - -.fa-ruler-combined::before { - content: "\f546"; } - -.fa-copyright::before { - content: "\f1f9"; } - -.fa-equals::before { - content: "\3d"; } - -.fa-blender::before { - content: "\f517"; } - -.fa-teeth::before { - content: "\f62e"; } - -.fa-shekel-sign::before { - content: "\f20b"; } - -.fa-ils::before { - content: "\f20b"; } - -.fa-shekel::before { - content: "\f20b"; } - -.fa-sheqel::before { - content: "\f20b"; } - -.fa-sheqel-sign::before { - content: "\f20b"; } - -.fa-map::before { - content: "\f279"; } - -.fa-rocket::before { - content: "\f135"; } - -.fa-photo-film::before { - content: "\f87c"; } - -.fa-photo-video::before { - content: "\f87c"; } - -.fa-folder-minus::before { - content: "\f65d"; } - -.fa-store::before { - content: "\f54e"; } - -.fa-arrow-trend-up::before { - content: "\e098"; } - -.fa-plug-circle-minus::before { - content: "\e55e"; } - -.fa-sign-hanging::before { - content: "\f4d9"; } - -.fa-sign::before { - content: "\f4d9"; } - -.fa-bezier-curve::before { - content: "\f55b"; } - -.fa-bell-slash::before { - content: "\f1f6"; } - -.fa-tablet::before { - content: "\f3fb"; } - -.fa-tablet-android::before { - content: "\f3fb"; } - -.fa-school-flag::before { - content: "\e56e"; } - -.fa-fill::before { - content: "\f575"; } - -.fa-angle-up::before { - content: "\f106"; } - -.fa-drumstick-bite::before { - content: "\f6d7"; } - -.fa-holly-berry::before { - content: "\f7aa"; } - -.fa-chevron-left::before { - content: "\f053"; } - -.fa-bacteria::before { - content: "\e059"; } - -.fa-hand-lizard::before { - content: "\f258"; } - -.fa-notdef::before { - content: "\e1fe"; } - -.fa-disease::before { - content: "\f7fa"; } - -.fa-briefcase-medical::before { - content: "\f469"; } - -.fa-genderless::before { - content: "\f22d"; } - -.fa-chevron-right::before { - content: "\f054"; } - -.fa-retweet::before { - content: "\f079"; } - -.fa-car-rear::before { - content: "\f5de"; } - -.fa-car-alt::before { - content: "\f5de"; } - -.fa-pump-soap::before { - content: "\e06b"; } - -.fa-video-slash::before { - content: "\f4e2"; } - -.fa-battery-quarter::before { - content: "\f243"; } - -.fa-battery-2::before { - content: "\f243"; } - -.fa-radio::before { - content: "\f8d7"; } - -.fa-baby-carriage::before { - content: "\f77d"; } - -.fa-carriage-baby::before { - content: "\f77d"; } - -.fa-traffic-light::before { - content: "\f637"; } - -.fa-thermometer::before { - content: "\f491"; } - -.fa-vr-cardboard::before { - content: "\f729"; } - -.fa-hand-middle-finger::before { - content: "\f806"; } - -.fa-percent::before { - content: "\25"; } - -.fa-percentage::before { - content: "\25"; } - -.fa-truck-moving::before { - content: "\f4df"; } - -.fa-glass-water-droplet::before { - content: "\e4f5"; } - -.fa-display::before { - content: "\e163"; } - -.fa-face-smile::before { - content: "\f118"; } - -.fa-smile::before { - content: "\f118"; } - -.fa-thumbtack::before { - content: "\f08d"; } - -.fa-thumb-tack::before { - content: "\f08d"; } - -.fa-trophy::before { - content: "\f091"; } - -.fa-person-praying::before { - content: "\f683"; } - -.fa-pray::before { - content: "\f683"; } - -.fa-hammer::before { - content: "\f6e3"; } - -.fa-hand-peace::before { - content: "\f25b"; } - -.fa-rotate::before { - content: "\f2f1"; } - -.fa-sync-alt::before { - content: "\f2f1"; } - -.fa-spinner::before { - content: "\f110"; } - -.fa-robot::before { - content: "\f544"; } - -.fa-peace::before { - content: "\f67c"; } - -.fa-gears::before { - content: "\f085"; } - -.fa-cogs::before { - content: "\f085"; } - -.fa-warehouse::before { - content: "\f494"; } - -.fa-arrow-up-right-dots::before { - content: "\e4b7"; } - -.fa-splotch::before { - content: "\f5bc"; } - -.fa-face-grin-hearts::before { - content: "\f584"; } - -.fa-grin-hearts::before { - content: "\f584"; } - -.fa-dice-four::before { - content: "\f524"; } - -.fa-sim-card::before { - content: "\f7c4"; } - -.fa-transgender::before { - content: "\f225"; } - -.fa-transgender-alt::before { - content: "\f225"; } - -.fa-mercury::before { - content: "\f223"; } - -.fa-arrow-turn-down::before { - content: "\f149"; } - -.fa-level-down::before { - content: "\f149"; } - -.fa-person-falling-burst::before { - content: "\e547"; } - -.fa-award::before { - content: "\f559"; } - -.fa-ticket-simple::before { - content: "\f3ff"; } - -.fa-ticket-alt::before { - content: "\f3ff"; } - -.fa-building::before { - content: "\f1ad"; } - -.fa-angles-left::before { - content: "\f100"; } - -.fa-angle-double-left::before { - content: "\f100"; } - -.fa-qrcode::before { - content: "\f029"; } - -.fa-clock-rotate-left::before { - content: "\f1da"; } - -.fa-history::before { - content: "\f1da"; } - -.fa-face-grin-beam-sweat::before { - content: "\f583"; } - -.fa-grin-beam-sweat::before { - content: "\f583"; } - -.fa-file-export::before { - content: "\f56e"; } - -.fa-arrow-right-from-file::before { - content: "\f56e"; } - -.fa-shield::before { - content: "\f132"; } - -.fa-shield-blank::before { - content: "\f132"; } - -.fa-arrow-up-short-wide::before { - content: "\f885"; } - -.fa-sort-amount-up-alt::before { - content: "\f885"; } - -.fa-house-medical::before { - content: "\e3b2"; } - -.fa-golf-ball-tee::before { - content: "\f450"; } - -.fa-golf-ball::before { - content: "\f450"; } - -.fa-circle-chevron-left::before { - content: "\f137"; } - -.fa-chevron-circle-left::before { - content: "\f137"; } - -.fa-house-chimney-window::before { - content: "\e00d"; } - -.fa-pen-nib::before { - content: "\f5ad"; } - -.fa-tent-arrow-turn-left::before { - content: "\e580"; } - -.fa-tents::before { - content: "\e582"; } - -.fa-wand-magic::before { - content: "\f0d0"; } - -.fa-magic::before { - content: "\f0d0"; } - -.fa-dog::before { - content: "\f6d3"; } - -.fa-carrot::before { - content: "\f787"; } - -.fa-moon::before { - content: "\f186"; } - -.fa-wine-glass-empty::before { - content: "\f5ce"; } - -.fa-wine-glass-alt::before { - content: "\f5ce"; } - -.fa-cheese::before { - content: "\f7ef"; } - -.fa-yin-yang::before { - content: "\f6ad"; } - -.fa-music::before { - content: "\f001"; } - -.fa-code-commit::before { - content: "\f386"; } - -.fa-temperature-low::before { - content: "\f76b"; } - -.fa-person-biking::before { - content: "\f84a"; } - -.fa-biking::before { - content: "\f84a"; } - -.fa-broom::before { - content: "\f51a"; } - -.fa-shield-heart::before { - content: "\e574"; } - -.fa-gopuram::before { - content: "\f664"; } - -.fa-earth-oceania::before { - content: "\e47b"; } - -.fa-globe-oceania::before { - content: "\e47b"; } - -.fa-square-xmark::before { - content: "\f2d3"; } - -.fa-times-square::before { - content: "\f2d3"; } - -.fa-xmark-square::before { - content: "\f2d3"; } - -.fa-hashtag::before { - content: "\23"; } - -.fa-up-right-and-down-left-from-center::before { - content: "\f424"; } - -.fa-expand-alt::before { - content: "\f424"; } - -.fa-oil-can::before { - content: "\f613"; } - -.fa-t::before { - content: "\54"; } - -.fa-hippo::before { - content: "\f6ed"; } - -.fa-chart-column::before { - content: "\e0e3"; } - -.fa-infinity::before { - content: "\f534"; } - -.fa-vial-circle-check::before { - content: "\e596"; } - -.fa-person-arrow-down-to-line::before { - content: "\e538"; } - -.fa-voicemail::before { - content: "\f897"; } - -.fa-fan::before { - content: "\f863"; } - -.fa-person-walking-luggage::before { - content: "\e554"; } - -.fa-up-down::before { - content: "\f338"; } - -.fa-arrows-alt-v::before { - content: "\f338"; } - -.fa-cloud-moon-rain::before { - content: "\f73c"; } - -.fa-calendar::before { - content: "\f133"; } - -.fa-trailer::before { - content: "\e041"; } - -.fa-bahai::before { - content: "\f666"; } - -.fa-haykal::before { - content: "\f666"; } - -.fa-sd-card::before { - content: "\f7c2"; } - -.fa-dragon::before { - content: "\f6d5"; } - -.fa-shoe-prints::before { - content: "\f54b"; } - -.fa-circle-plus::before { - content: "\f055"; } - -.fa-plus-circle::before { - content: "\f055"; } - -.fa-face-grin-tongue-wink::before { - content: "\f58b"; } - -.fa-grin-tongue-wink::before { - content: "\f58b"; } - -.fa-hand-holding::before { - content: "\f4bd"; } - -.fa-plug-circle-exclamation::before { - content: "\e55d"; } - -.fa-link-slash::before { - content: "\f127"; } - -.fa-chain-broken::before { - content: "\f127"; } - -.fa-chain-slash::before { - content: "\f127"; } - -.fa-unlink::before { - content: "\f127"; } - -.fa-clone::before { - content: "\f24d"; } - -.fa-person-walking-arrow-loop-left::before { - content: "\e551"; } - -.fa-arrow-up-z-a::before { - content: "\f882"; } - -.fa-sort-alpha-up-alt::before { - content: "\f882"; } - -.fa-fire-flame-curved::before { - content: "\f7e4"; } - -.fa-fire-alt::before { - content: "\f7e4"; } - -.fa-tornado::before { - content: "\f76f"; } - -.fa-file-circle-plus::before { - content: "\e494"; } - -.fa-book-quran::before { - content: "\f687"; } - -.fa-quran::before { - content: "\f687"; } - -.fa-anchor::before { - content: "\f13d"; } - -.fa-border-all::before { - content: "\f84c"; } - -.fa-face-angry::before { - content: "\f556"; } - -.fa-angry::before { - content: "\f556"; } - -.fa-cookie-bite::before { - content: "\f564"; } - -.fa-arrow-trend-down::before { - content: "\e097"; } - -.fa-rss::before { - content: "\f09e"; } - -.fa-feed::before { - content: "\f09e"; } - -.fa-draw-polygon::before { - content: "\f5ee"; } - -.fa-scale-balanced::before { - content: "\f24e"; } - -.fa-balance-scale::before { - content: "\f24e"; } - -.fa-gauge-simple-high::before { - content: "\f62a"; } - -.fa-tachometer::before { - content: "\f62a"; } - -.fa-tachometer-fast::before { - content: "\f62a"; } - -.fa-shower::before { - content: "\f2cc"; } - -.fa-desktop::before { - content: "\f390"; } - -.fa-desktop-alt::before { - content: "\f390"; } - -.fa-m::before { - content: "\4d"; } - -.fa-table-list::before { - content: "\f00b"; } - -.fa-th-list::before { - content: "\f00b"; } - -.fa-comment-sms::before { - content: "\f7cd"; } - -.fa-sms::before { - content: "\f7cd"; } - -.fa-book::before { - content: "\f02d"; } - -.fa-user-plus::before { - content: "\f234"; } - -.fa-check::before { - content: "\f00c"; } - -.fa-battery-three-quarters::before { - content: "\f241"; } - -.fa-battery-4::before { - content: "\f241"; } - -.fa-house-circle-check::before { - content: "\e509"; } - -.fa-angle-left::before { - content: "\f104"; } - -.fa-diagram-successor::before { - content: "\e47a"; } - -.fa-truck-arrow-right::before { - content: "\e58b"; } - -.fa-arrows-split-up-and-left::before { - content: "\e4bc"; } - -.fa-hand-fist::before { - content: "\f6de"; } - -.fa-fist-raised::before { - content: "\f6de"; } - -.fa-cloud-moon::before { - content: "\f6c3"; } - -.fa-briefcase::before { - content: "\f0b1"; } - -.fa-person-falling::before { - content: "\e546"; } - -.fa-image-portrait::before { - content: "\f3e0"; } - -.fa-portrait::before { - content: "\f3e0"; } - -.fa-user-tag::before { - content: "\f507"; } - -.fa-rug::before { - content: "\e569"; } - -.fa-earth-europe::before { - content: "\f7a2"; } - -.fa-globe-europe::before { - content: "\f7a2"; } - -.fa-cart-flatbed-suitcase::before { - content: "\f59d"; } - -.fa-luggage-cart::before { - content: "\f59d"; } - -.fa-rectangle-xmark::before { - content: "\f410"; } - -.fa-rectangle-times::before { - content: "\f410"; } - -.fa-times-rectangle::before { - content: "\f410"; } - -.fa-window-close::before { - content: "\f410"; } - -.fa-baht-sign::before { - content: "\e0ac"; } - -.fa-book-open::before { - content: "\f518"; } - -.fa-book-journal-whills::before { - content: "\f66a"; } - -.fa-journal-whills::before { - content: "\f66a"; } - -.fa-handcuffs::before { - content: "\e4f8"; } - -.fa-triangle-exclamation::before { - content: "\f071"; } - -.fa-exclamation-triangle::before { - content: "\f071"; } - -.fa-warning::before { - content: "\f071"; } - -.fa-database::before { - content: "\f1c0"; } - -.fa-share::before { - content: "\f064"; } - -.fa-mail-forward::before { - content: "\f064"; } - -.fa-bottle-droplet::before { - content: "\e4c4"; } - -.fa-mask-face::before { - content: "\e1d7"; } - -.fa-hill-rockslide::before { - content: "\e508"; } - -.fa-right-left::before { - content: "\f362"; } - -.fa-exchange-alt::before { - content: "\f362"; } - -.fa-paper-plane::before { - content: "\f1d8"; } - -.fa-road-circle-exclamation::before { - content: "\e565"; } - -.fa-dungeon::before { - content: "\f6d9"; } - -.fa-align-right::before { - content: "\f038"; } - -.fa-money-bill-1-wave::before { - content: "\f53b"; } - -.fa-money-bill-wave-alt::before { - content: "\f53b"; } - -.fa-life-ring::before { - content: "\f1cd"; } - -.fa-hands::before { - content: "\f2a7"; } - -.fa-sign-language::before { - content: "\f2a7"; } - -.fa-signing::before { - content: "\f2a7"; } - -.fa-calendar-day::before { - content: "\f783"; } - -.fa-water-ladder::before { - content: "\f5c5"; } - -.fa-ladder-water::before { - content: "\f5c5"; } - -.fa-swimming-pool::before { - content: "\f5c5"; } - -.fa-arrows-up-down::before { - content: "\f07d"; } - -.fa-arrows-v::before { - content: "\f07d"; } - -.fa-face-grimace::before { - content: "\f57f"; } - -.fa-grimace::before { - content: "\f57f"; } - -.fa-wheelchair-move::before { - content: "\e2ce"; } - -.fa-wheelchair-alt::before { - content: "\e2ce"; } - -.fa-turn-down::before { - content: "\f3be"; } - -.fa-level-down-alt::before { - content: "\f3be"; } - -.fa-person-walking-arrow-right::before { - content: "\e552"; } - -.fa-square-envelope::before { - content: "\f199"; } - -.fa-envelope-square::before { - content: "\f199"; } - -.fa-dice::before { - content: "\f522"; } - -.fa-bowling-ball::before { - content: "\f436"; } - -.fa-brain::before { - content: "\f5dc"; } - -.fa-bandage::before { - content: "\f462"; } - -.fa-band-aid::before { - content: "\f462"; } - -.fa-calendar-minus::before { - content: "\f272"; } - -.fa-circle-xmark::before { - content: "\f057"; } - -.fa-times-circle::before { - content: "\f057"; } - -.fa-xmark-circle::before { - content: "\f057"; } - -.fa-gifts::before { - content: "\f79c"; } - -.fa-hotel::before { - content: "\f594"; } - -.fa-earth-asia::before { - content: "\f57e"; } - -.fa-globe-asia::before { - content: "\f57e"; } - -.fa-id-card-clip::before { - content: "\f47f"; } - -.fa-id-card-alt::before { - content: "\f47f"; } - -.fa-magnifying-glass-plus::before { - content: "\f00e"; } - -.fa-search-plus::before { - content: "\f00e"; } - -.fa-thumbs-up::before { - content: "\f164"; } - -.fa-user-clock::before { - content: "\f4fd"; } - -.fa-hand-dots::before { - content: "\f461"; } - -.fa-allergies::before { - content: "\f461"; } - -.fa-file-invoice::before { - content: "\f570"; } - -.fa-window-minimize::before { - content: "\f2d1"; } - -.fa-mug-saucer::before { - content: "\f0f4"; } - -.fa-coffee::before { - content: "\f0f4"; } - -.fa-brush::before { - content: "\f55d"; } - -.fa-mask::before { - content: "\f6fa"; } - -.fa-magnifying-glass-minus::before { - content: "\f010"; } - -.fa-search-minus::before { - content: "\f010"; } - -.fa-ruler-vertical::before { - content: "\f548"; } - -.fa-user-large::before { - content: "\f406"; } - -.fa-user-alt::before { - content: "\f406"; } - -.fa-train-tram::before { - content: "\e5b4"; } - -.fa-user-nurse::before { - content: "\f82f"; } - -.fa-syringe::before { - content: "\f48e"; } - -.fa-cloud-sun::before { - content: "\f6c4"; } - -.fa-stopwatch-20::before { - content: "\e06f"; } - -.fa-square-full::before { - content: "\f45c"; } - -.fa-magnet::before { - content: "\f076"; } - -.fa-jar::before { - content: "\e516"; } - -.fa-note-sticky::before { - content: "\f249"; } - -.fa-sticky-note::before { - content: "\f249"; } - -.fa-bug-slash::before { - content: "\e490"; } - -.fa-arrow-up-from-water-pump::before { - content: "\e4b6"; } - -.fa-bone::before { - content: "\f5d7"; } - -.fa-user-injured::before { - content: "\f728"; } - -.fa-face-sad-tear::before { - content: "\f5b4"; } - -.fa-sad-tear::before { - content: "\f5b4"; } - -.fa-plane::before { - content: "\f072"; } - -.fa-tent-arrows-down::before { - content: "\e581"; } - -.fa-exclamation::before { - content: "\21"; } - -.fa-arrows-spin::before { - content: "\e4bb"; } - -.fa-print::before { - content: "\f02f"; } - -.fa-turkish-lira-sign::before { - content: "\e2bb"; } - -.fa-try::before { - content: "\e2bb"; } - -.fa-turkish-lira::before { - content: "\e2bb"; } - -.fa-dollar-sign::before { - content: "\24"; } - -.fa-dollar::before { - content: "\24"; } - -.fa-usd::before { - content: "\24"; } - -.fa-x::before { - content: "\58"; } - -.fa-magnifying-glass-dollar::before { - content: "\f688"; } - -.fa-search-dollar::before { - content: "\f688"; } - -.fa-users-gear::before { - content: "\f509"; } - -.fa-users-cog::before { - content: "\f509"; } - -.fa-person-military-pointing::before { - content: "\e54a"; } - -.fa-building-columns::before { - content: "\f19c"; } - -.fa-bank::before { - content: "\f19c"; } - -.fa-institution::before { - content: "\f19c"; } - -.fa-museum::before { - content: "\f19c"; } - -.fa-university::before { - content: "\f19c"; } - -.fa-umbrella::before { - content: "\f0e9"; } - -.fa-trowel::before { - content: "\e589"; } - -.fa-d::before { - content: "\44"; } - -.fa-stapler::before { - content: "\e5af"; } - -.fa-masks-theater::before { - content: "\f630"; } - -.fa-theater-masks::before { - content: "\f630"; } - -.fa-kip-sign::before { - content: "\e1c4"; } - -.fa-hand-point-left::before { - content: "\f0a5"; } - -.fa-handshake-simple::before { - content: "\f4c6"; } - -.fa-handshake-alt::before { - content: "\f4c6"; } - -.fa-jet-fighter::before { - content: "\f0fb"; } - -.fa-fighter-jet::before { - content: "\f0fb"; } - -.fa-square-share-nodes::before { - content: "\f1e1"; } - -.fa-share-alt-square::before { - content: "\f1e1"; } - -.fa-barcode::before { - content: "\f02a"; } - -.fa-plus-minus::before { - content: "\e43c"; } - -.fa-video::before { - content: "\f03d"; } - -.fa-video-camera::before { - content: "\f03d"; } - -.fa-graduation-cap::before { - content: "\f19d"; } - -.fa-mortar-board::before { - content: "\f19d"; } - -.fa-hand-holding-medical::before { - content: "\e05c"; } - -.fa-person-circle-check::before { - content: "\e53e"; } - -.fa-turn-up::before { - content: "\f3bf"; } - -.fa-level-up-alt::before { - content: "\f3bf"; } - -.sr-only, -.fa-sr-only { - position: absolute; - width: 1px; - height: 1px; - padding: 0; - margin: -1px; - overflow: hidden; - clip: rect(0, 0, 0, 0); - white-space: nowrap; - border-width: 0; } - -.sr-only-focusable:not(:focus), -.fa-sr-only-focusable:not(:focus) { - position: absolute; - width: 1px; - height: 1px; - padding: 0; - margin: -1px; - overflow: hidden; - clip: rect(0, 0, 0, 0); - white-space: nowrap; - border-width: 0; } -:root, :host { - --fa-style-family-brands: 'Font Awesome 6 Brands'; - --fa-font-brands: normal 400 1em/1 'Font Awesome 6 Brands'; } - -@font-face { - font-family: 'Font Awesome 6 Brands'; - font-style: normal; - font-weight: 400; - font-display: block; - src: url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.ttf") format("truetype"); } - -.fab, -.fa-brands { - font-weight: 400; } - -.fa-monero:before { - content: "\f3d0"; } - -.fa-hooli:before { - content: "\f427"; } - -.fa-yelp:before { - content: "\f1e9"; } - -.fa-cc-visa:before { - content: "\f1f0"; } - -.fa-lastfm:before { - content: "\f202"; } - -.fa-shopware:before { - content: "\f5b5"; } - -.fa-creative-commons-nc:before { - content: "\f4e8"; } - -.fa-aws:before { - content: "\f375"; } - -.fa-redhat:before { - content: "\f7bc"; } - -.fa-yoast:before { - content: "\f2b1"; } - -.fa-cloudflare:before { - content: "\e07d"; } - -.fa-ups:before { - content: "\f7e0"; } - -.fa-pixiv:before { - content: "\e640"; } - -.fa-wpexplorer:before { - content: "\f2de"; } - -.fa-dyalog:before { - content: "\f399"; } - -.fa-bity:before { - content: "\f37a"; } - -.fa-stackpath:before { - content: "\f842"; } - -.fa-buysellads:before { - content: "\f20d"; } - -.fa-first-order:before { - content: "\f2b0"; } - -.fa-modx:before { - content: "\f285"; } - -.fa-guilded:before { - content: "\e07e"; } - -.fa-vnv:before { - content: "\f40b"; } - -.fa-square-js:before { - content: "\f3b9"; } - -.fa-js-square:before { - content: "\f3b9"; } - -.fa-microsoft:before { - content: "\f3ca"; } - -.fa-qq:before { - content: "\f1d6"; } - -.fa-orcid:before { - content: "\f8d2"; } - -.fa-java:before { - content: "\f4e4"; } - -.fa-invision:before { - content: "\f7b0"; } - -.fa-creative-commons-pd-alt:before { - content: "\f4ed"; } - -.fa-centercode:before { - content: "\f380"; } - -.fa-glide-g:before { - content: "\f2a6"; } - -.fa-drupal:before { - content: "\f1a9"; } - -.fa-jxl:before { - content: "\e67b"; } - -.fa-hire-a-helper:before { - content: "\f3b0"; } - -.fa-creative-commons-by:before { - content: "\f4e7"; } - -.fa-unity:before { - content: "\e049"; } - -.fa-whmcs:before { - content: "\f40d"; } - -.fa-rocketchat:before { - content: "\f3e8"; } - -.fa-vk:before { - content: "\f189"; } - -.fa-untappd:before { - content: "\f405"; } - -.fa-mailchimp:before { - content: "\f59e"; } - -.fa-css3-alt:before { - content: "\f38b"; } - -.fa-square-reddit:before { - content: "\f1a2"; } - -.fa-reddit-square:before { - content: "\f1a2"; } - -.fa-vimeo-v:before { - content: "\f27d"; } - -.fa-contao:before { - content: "\f26d"; } - -.fa-square-font-awesome:before { - content: "\e5ad"; } - -.fa-deskpro:before { - content: "\f38f"; } - -.fa-brave:before { - content: "\e63c"; } - -.fa-sistrix:before { - content: "\f3ee"; } - -.fa-square-instagram:before { - content: "\e055"; } - -.fa-instagram-square:before { - content: "\e055"; } - -.fa-battle-net:before { - content: "\f835"; } - -.fa-the-red-yeti:before { - content: "\f69d"; } - -.fa-square-hacker-news:before { - content: "\f3af"; } - -.fa-hacker-news-square:before { - content: "\f3af"; } - -.fa-edge:before { - content: "\f282"; } - -.fa-threads:before { - content: "\e618"; } - -.fa-napster:before { - content: "\f3d2"; } - -.fa-square-snapchat:before { - content: "\f2ad"; } - -.fa-snapchat-square:before { - content: "\f2ad"; } - -.fa-google-plus-g:before { - content: "\f0d5"; } - -.fa-artstation:before { - content: "\f77a"; } - -.fa-markdown:before { - content: "\f60f"; } - -.fa-sourcetree:before { - content: "\f7d3"; } - -.fa-google-plus:before { - content: "\f2b3"; } - -.fa-diaspora:before { - content: "\f791"; } - -.fa-foursquare:before { - content: "\f180"; } - -.fa-stack-overflow:before { - content: "\f16c"; } - -.fa-github-alt:before { - content: "\f113"; } - -.fa-phoenix-squadron:before { - content: "\f511"; } - -.fa-pagelines:before { - content: "\f18c"; } - -.fa-algolia:before { - content: "\f36c"; } - -.fa-red-river:before { - content: "\f3e3"; } - -.fa-creative-commons-sa:before { - content: "\f4ef"; } - -.fa-safari:before { - content: "\f267"; } - -.fa-google:before { - content: "\f1a0"; } - -.fa-square-font-awesome-stroke:before { - content: "\f35c"; } - -.fa-font-awesome-alt:before { - content: "\f35c"; } - -.fa-atlassian:before { - content: "\f77b"; } - -.fa-linkedin-in:before { - content: "\f0e1"; } - -.fa-digital-ocean:before { - content: "\f391"; } - -.fa-nimblr:before { - content: "\f5a8"; } - -.fa-chromecast:before { - content: "\f838"; } - -.fa-evernote:before { - content: "\f839"; } - -.fa-hacker-news:before { - content: "\f1d4"; } - -.fa-creative-commons-sampling:before { - content: "\f4f0"; } - -.fa-adversal:before { - content: "\f36a"; } - -.fa-creative-commons:before { - content: "\f25e"; } - -.fa-watchman-monitoring:before { - content: "\e087"; } - -.fa-fonticons:before { - content: "\f280"; } - -.fa-weixin:before { - content: "\f1d7"; } - -.fa-shirtsinbulk:before { - content: "\f214"; } - -.fa-codepen:before { - content: "\f1cb"; } - -.fa-git-alt:before { - content: "\f841"; } - -.fa-lyft:before { - content: "\f3c3"; } - -.fa-rev:before { - content: "\f5b2"; } - -.fa-windows:before { - content: "\f17a"; } - -.fa-wizards-of-the-coast:before { - content: "\f730"; } - -.fa-square-viadeo:before { - content: "\f2aa"; } - -.fa-viadeo-square:before { - content: "\f2aa"; } - -.fa-meetup:before { - content: "\f2e0"; } - -.fa-centos:before { - content: "\f789"; } - -.fa-adn:before { - content: "\f170"; } - -.fa-cloudsmith:before { - content: "\f384"; } - -.fa-opensuse:before { - content: "\e62b"; } - -.fa-pied-piper-alt:before { - content: "\f1a8"; } - -.fa-square-dribbble:before { - content: "\f397"; } - -.fa-dribbble-square:before { - content: "\f397"; } - -.fa-codiepie:before { - content: "\f284"; } - -.fa-node:before { - content: "\f419"; } - -.fa-mix:before { - content: "\f3cb"; } - -.fa-steam:before { - content: "\f1b6"; } - -.fa-cc-apple-pay:before { - content: "\f416"; } - -.fa-scribd:before { - content: "\f28a"; } - -.fa-debian:before { - content: "\e60b"; } - -.fa-openid:before { - content: "\f19b"; } - -.fa-instalod:before { - content: "\e081"; } - -.fa-expeditedssl:before { - content: "\f23e"; } - -.fa-sellcast:before { - content: "\f2da"; } - -.fa-square-twitter:before { - content: "\f081"; } - -.fa-twitter-square:before { - content: "\f081"; } - -.fa-r-project:before { - content: "\f4f7"; } - -.fa-delicious:before { - content: "\f1a5"; } - -.fa-freebsd:before { - content: "\f3a4"; } - -.fa-vuejs:before { - content: "\f41f"; } - -.fa-accusoft:before { - content: "\f369"; } - -.fa-ioxhost:before { - content: "\f208"; } - -.fa-fonticons-fi:before { - content: "\f3a2"; } - -.fa-app-store:before { - content: "\f36f"; } - -.fa-cc-mastercard:before { - content: "\f1f1"; } - -.fa-itunes-note:before { - content: "\f3b5"; } - -.fa-golang:before { - content: "\e40f"; } - -.fa-kickstarter:before { - content: "\f3bb"; } - -.fa-square-kickstarter:before { - content: "\f3bb"; } - -.fa-grav:before { - content: "\f2d6"; } - -.fa-weibo:before { - content: "\f18a"; } - -.fa-uncharted:before { - content: "\e084"; } - -.fa-firstdraft:before { - content: "\f3a1"; } - -.fa-square-youtube:before { - content: "\f431"; } - -.fa-youtube-square:before { - content: "\f431"; } - -.fa-wikipedia-w:before { - content: "\f266"; } - -.fa-wpressr:before { - content: "\f3e4"; } - -.fa-rendact:before { - content: "\f3e4"; } - -.fa-angellist:before { - content: "\f209"; } - -.fa-galactic-republic:before { - content: "\f50c"; } - -.fa-nfc-directional:before { - content: "\e530"; } - -.fa-skype:before { - content: "\f17e"; } - -.fa-joget:before { - content: "\f3b7"; } - -.fa-fedora:before { - content: "\f798"; } - -.fa-stripe-s:before { - content: "\f42a"; } - -.fa-meta:before { - content: "\e49b"; } - -.fa-laravel:before { - content: "\f3bd"; } - -.fa-hotjar:before { - content: "\f3b1"; } - -.fa-bluetooth-b:before { - content: "\f294"; } - -.fa-square-letterboxd:before { - content: "\e62e"; } - -.fa-sticker-mule:before { - content: "\f3f7"; } - -.fa-creative-commons-zero:before { - content: "\f4f3"; } - -.fa-hips:before { - content: "\f452"; } - -.fa-behance:before { - content: "\f1b4"; } - -.fa-reddit:before { - content: "\f1a1"; } - -.fa-discord:before { - content: "\f392"; } - -.fa-chrome:before { - content: "\f268"; } - -.fa-app-store-ios:before { - content: "\f370"; } - -.fa-cc-discover:before { - content: "\f1f2"; } - -.fa-wpbeginner:before { - content: "\f297"; } - -.fa-confluence:before { - content: "\f78d"; } - -.fa-shoelace:before { - content: "\e60c"; } - -.fa-mdb:before { - content: "\f8ca"; } - -.fa-dochub:before { - content: "\f394"; } - -.fa-accessible-icon:before { - content: "\f368"; } - -.fa-ebay:before { - content: "\f4f4"; } - -.fa-amazon:before { - content: "\f270"; } - -.fa-unsplash:before { - content: "\e07c"; } - -.fa-yarn:before { - content: "\f7e3"; } - -.fa-square-steam:before { - content: "\f1b7"; } - -.fa-steam-square:before { - content: "\f1b7"; } - -.fa-500px:before { - content: "\f26e"; } - 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(gh-4756) - return typeof obj === "function" && typeof obj.nodeType !== "number" && - typeof obj.item !== "function"; - }; - - -var isWindow = function isWindow( obj ) { - return obj != null && obj === obj.window; - }; - - -var document = window.document; - - - - var preservedScriptAttributes = { - type: true, - src: true, - nonce: true, - noModule: true - }; - - function DOMEval( code, node, doc ) { - doc = doc || document; - - var i, val, - script = doc.createElement( "script" ); - - script.text = code; - if ( node ) { - for ( i in preservedScriptAttributes ) { - - // Support: Firefox 64+, Edge 18+ - // Some browsers don't support the "nonce" property on scripts. - // On the other hand, just using `getAttribute` is not enough as - // the `nonce` attribute is reset to an empty string whenever it - // becomes browsing-context connected. - // See https://github.com/whatwg/html/issues/2369 - // See https://html.spec.whatwg.org/#nonce-attributes - // The `node.getAttribute` check was added for the sake of - // `jQuery.globalEval` so that it can fake a nonce-containing node - // via an object. - val = node[ i ] || node.getAttribute && node.getAttribute( i ); - if ( val ) { - script.setAttribute( i, val ); - } - } - } - doc.head.appendChild( script ).parentNode.removeChild( script ); - } - - -function toType( obj ) { - if ( obj == null ) { - return obj + ""; - } - - // Support: Android <=2.3 only (functionish RegExp) - return typeof obj === "object" || typeof obj === "function" ? - class2type[ toString.call( obj ) ] || "object" : - typeof obj; -} -/* global Symbol */ -// Defining this global in .eslintrc.json would create a danger of using the global -// unguarded in another place, it seems safer to define global only for this module - - - -var - version = "3.6.0", - - // Define a local copy of jQuery - jQuery = function( selector, context ) { - - // The jQuery object is actually just the init constructor 'enhanced' - // Need init if jQuery is called (just allow error to be thrown if not included) - return new jQuery.fn.init( selector, context ); - }; - -jQuery.fn = jQuery.prototype = { - - // The current version of jQuery being used - jquery: version, - - constructor: jQuery, - - // The default length of a jQuery object is 0 - length: 0, - - toArray: function() { - return slice.call( this ); - }, - - // Get the Nth element in the matched element set OR - // Get the whole matched element set as a clean array - get: function( num ) { - - // Return all the elements in a clean array - if ( num == null ) { - return slice.call( this ); - } - - // Return just the one element from the set - return num < 0 ? this[ num + this.length ] : this[ num ]; - }, - - // Take an array of elements and push it onto the stack - // (returning the new matched element set) - pushStack: function( elems ) { - - // Build a new jQuery matched element set - var ret = jQuery.merge( this.constructor(), elems ); - - // Add the old object onto the stack (as a reference) - ret.prevObject = this; - - // Return the newly-formed element set - return ret; - }, - - // Execute a callback for every element in the matched set. - each: function( callback ) { - return jQuery.each( this, callback ); - }, - - map: function( callback ) { - return this.pushStack( jQuery.map( this, function( elem, i ) { - return callback.call( elem, i, elem ); - } ) ); - }, - - slice: function() { - return this.pushStack( slice.apply( this, arguments ) ); - }, - - first: function() { - return this.eq( 0 ); - }, - - last: function() { - return this.eq( -1 ); - }, - - even: function() { - return this.pushStack( jQuery.grep( this, function( _elem, i ) { - return ( i + 1 ) % 2; - } ) ); - }, - - odd: function() { - return this.pushStack( jQuery.grep( this, function( _elem, i ) { - return i % 2; - } ) ); - }, - - eq: function( i ) { - var len = this.length, - j = +i + ( i < 0 ? len : 0 ); - return this.pushStack( j >= 0 && j < len ? [ this[ j ] ] : [] ); - }, - - end: function() { - return this.prevObject || this.constructor(); - }, - - // For internal use only. - // Behaves like an Array's method, not like a jQuery method. - push: push, - sort: arr.sort, - splice: arr.splice -}; - -jQuery.extend = jQuery.fn.extend = function() { - var options, name, src, copy, copyIsArray, clone, - target = arguments[ 0 ] || {}, - i = 1, - length = arguments.length, - deep = false; - - // Handle a deep copy situation - if ( typeof target === "boolean" ) { - deep = target; - - // Skip the boolean and the target - target = arguments[ i ] || {}; - i++; - } - - // Handle case when target is a string or something (possible in deep copy) - if ( typeof target !== "object" && !isFunction( target ) ) { - target = {}; - } - - // Extend jQuery itself if only one argument is passed - if ( i === length ) { - target = this; - i--; - } - - for ( ; i < length; i++ ) { - - // Only deal with non-null/undefined values - if ( ( options = arguments[ i ] ) != null ) { - - // Extend the base object - for ( name in options ) { - copy = options[ name ]; - - // Prevent Object.prototype pollution - // Prevent never-ending loop - if ( name === "__proto__" || target === copy ) { - continue; - } - - // Recurse if we're merging plain objects or arrays - if ( deep && copy && ( jQuery.isPlainObject( copy ) || - ( copyIsArray = Array.isArray( copy ) ) ) ) { - src = target[ name ]; - - // Ensure proper type for the source value - if ( copyIsArray && !Array.isArray( src ) ) { - clone = []; - } else if ( !copyIsArray && !jQuery.isPlainObject( src ) ) { - clone = {}; - } else { - clone = src; - } - copyIsArray = false; - - // Never move original objects, clone them - target[ name ] = jQuery.extend( deep, clone, copy ); - - // Don't bring in undefined values - } else if ( copy !== undefined ) { - target[ name ] = copy; - } - } - } - } - - // Return the modified object - return target; -}; - -jQuery.extend( { - - // Unique for each copy of jQuery on the page - expando: "jQuery" + ( version + Math.random() ).replace( /\D/g, "" ), - - // Assume jQuery is ready without the ready module - isReady: true, - - error: function( msg ) { - throw new Error( msg ); - }, - - noop: function() {}, - - isPlainObject: function( obj ) { - var proto, Ctor; - - // Detect obvious negatives - // Use toString instead of jQuery.type to catch host objects - if ( !obj || toString.call( obj ) !== "[object Object]" ) { - return false; - } - - proto = getProto( obj ); - - // Objects with no prototype (e.g., `Object.create( null )`) are plain - if ( !proto ) { - return true; - } - - // Objects with prototype are plain iff they were constructed by a global Object function - Ctor = hasOwn.call( proto, "constructor" ) && proto.constructor; - return typeof Ctor === "function" && fnToString.call( Ctor ) === ObjectFunctionString; - }, - - isEmptyObject: function( obj ) { - var name; - - for ( name in obj ) { - return false; - } - return true; - }, - - // Evaluates a script in a provided context; falls back to the global one - // if not specified. - globalEval: function( code, options, doc ) { - DOMEval( code, { nonce: options && options.nonce }, doc ); - }, - - each: function( obj, callback ) { - var length, i = 0; - - if ( isArrayLike( obj ) ) { - length = obj.length; - for ( ; i < length; i++ ) { - if ( callback.call( obj[ i ], i, obj[ i ] ) === false ) { - break; - } - } - } else { - for ( i in obj ) { - if ( callback.call( obj[ i ], i, obj[ i ] ) === false ) { - break; - } - } - } - - return obj; - }, - - // results is for internal usage only - makeArray: function( arr, results ) { - var ret = results || []; - - if ( arr != null ) { - if ( isArrayLike( Object( arr ) ) ) { - jQuery.merge( ret, - typeof arr === "string" ? - [ arr ] : arr - ); - } else { - push.call( ret, arr ); - } - } - - return ret; - }, - - inArray: function( elem, arr, i ) { - return arr == null ? -1 : indexOf.call( arr, elem, i ); - }, - - // Support: Android <=4.0 only, PhantomJS 1 only - // push.apply(_, arraylike) throws on ancient WebKit - merge: function( first, second ) { - var len = +second.length, - j = 0, - i = first.length; - - for ( ; j < len; j++ ) { - first[ i++ ] = second[ j ]; - } - - first.length = i; - - return first; - }, - - grep: function( elems, callback, invert ) { - var callbackInverse, - matches = [], - i = 0, - length = elems.length, - callbackExpect = !invert; - - // Go through the array, only saving the items - // that pass the validator function - for ( ; i < length; i++ ) { - callbackInverse = !callback( elems[ i ], i ); - if ( callbackInverse !== callbackExpect ) { - matches.push( elems[ i ] ); - } - } - - return matches; - }, - - // arg is for internal usage only - map: function( elems, callback, arg ) { - var length, value, - i = 0, - ret = []; - - // Go through the array, translating each of the items to their new values - if ( isArrayLike( elems ) ) { - length = elems.length; - for ( ; i < length; i++ ) { - value = callback( elems[ i ], i, arg ); - - if ( value != null ) { - ret.push( value ); - } - } - - // Go through every key on the object, - } else { - for ( i in elems ) { - value = callback( elems[ i ], i, arg ); - - if ( value != null ) { - ret.push( value ); - } - } - } - - // Flatten any nested arrays - return flat( ret ); - }, - - // A global GUID counter for objects - guid: 1, - - // jQuery.support is not used in Core but other projects attach their - // properties to it so it needs to exist. - support: support -} ); - -if ( typeof Symbol === "function" ) { - jQuery.fn[ Symbol.iterator ] = arr[ Symbol.iterator ]; -} - -// Populate the class2type map -jQuery.each( "Boolean Number String Function Array Date RegExp Object Error Symbol".split( " " ), - function( _i, name ) { - class2type[ "[object " + name + "]" ] = name.toLowerCase(); - } ); - -function isArrayLike( obj ) { - - // Support: real iOS 8.2 only (not reproducible in simulator) - // `in` check used to prevent JIT error (gh-2145) - // hasOwn isn't used here due to false negatives - // regarding Nodelist length in IE - var length = !!obj && "length" in obj && obj.length, - type = toType( obj ); - - if ( isFunction( obj ) || isWindow( obj ) ) { - return false; - } - - return type === "array" || length === 0 || - typeof length === "number" && length > 0 && ( length - 1 ) in obj; -} -var Sizzle = -/*! - * Sizzle CSS Selector Engine v2.3.6 - * https://sizzlejs.com/ - * - * Copyright JS Foundation and other contributors - * Released under the MIT license - * https://js.foundation/ - * - * Date: 2021-02-16 - */ -( function( window ) { -var i, - support, - Expr, - getText, - isXML, - tokenize, - compile, - select, - outermostContext, - sortInput, - hasDuplicate, - - // Local document vars - setDocument, - document, - docElem, - documentIsHTML, - rbuggyQSA, - rbuggyMatches, - matches, - contains, - - // Instance-specific data - expando = "sizzle" + 1 * new Date(), - preferredDoc = window.document, - dirruns = 0, - done = 0, - classCache = createCache(), - tokenCache = createCache(), - compilerCache = createCache(), - nonnativeSelectorCache = createCache(), - sortOrder = function( a, b ) { - if ( a === b ) { - hasDuplicate = true; - } - return 0; - }, - - // Instance methods - hasOwn = ( {} ).hasOwnProperty, - arr = [], - pop = arr.pop, - pushNative = arr.push, - push = arr.push, - slice = arr.slice, - - // Use a stripped-down indexOf as it's faster than native - // https://jsperf.com/thor-indexof-vs-for/5 - indexOf = function( list, elem ) { - var i = 0, - len = list.length; - for ( ; i < len; i++ ) { - if ( list[ i ] === elem ) { - return i; - } - } - return -1; - }, - - booleans = "checked|selected|async|autofocus|autoplay|controls|defer|disabled|hidden|" + - "ismap|loop|multiple|open|readonly|required|scoped", - - // Regular expressions - - // http://www.w3.org/TR/css3-selectors/#whitespace - whitespace = "[\\x20\\t\\r\\n\\f]", - - // https://www.w3.org/TR/css-syntax-3/#ident-token-diagram - identifier = "(?:\\\\[\\da-fA-F]{1,6}" + whitespace + - "?|\\\\[^\\r\\n\\f]|[\\w-]|[^\0-\\x7f])+", - - // Attribute selectors: http://www.w3.org/TR/selectors/#attribute-selectors - attributes = "\\[" + whitespace + "*(" + identifier + ")(?:" + whitespace + - - // Operator (capture 2) - "*([*^$|!~]?=)" + whitespace + - - // "Attribute values must be CSS identifiers [capture 5] - // or strings [capture 3 or capture 4]" - "*(?:'((?:\\\\.|[^\\\\'])*)'|\"((?:\\\\.|[^\\\\\"])*)\"|(" + identifier + "))|)" + - whitespace + "*\\]", - - pseudos = ":(" + identifier + ")(?:\\((" + - - // To reduce the number of selectors needing tokenize in the preFilter, prefer arguments: - // 1. quoted (capture 3; capture 4 or capture 5) - "('((?:\\\\.|[^\\\\'])*)'|\"((?:\\\\.|[^\\\\\"])*)\")|" + - - // 2. simple (capture 6) - "((?:\\\\.|[^\\\\()[\\]]|" + attributes + ")*)|" + - - // 3. anything else (capture 2) - ".*" + - ")\\)|)", - - // Leading and non-escaped trailing whitespace, capturing some non-whitespace characters preceding the latter - rwhitespace = new RegExp( whitespace + "+", "g" ), - rtrim = new RegExp( "^" + whitespace + "+|((?:^|[^\\\\])(?:\\\\.)*)" + - whitespace + "+$", "g" ), - - rcomma = new RegExp( "^" + whitespace + "*," + whitespace + "*" ), - rcombinators = new RegExp( "^" + whitespace + "*([>+~]|" + whitespace + ")" + whitespace + - "*" ), - rdescend = new RegExp( whitespace + "|>" ), - - rpseudo = new RegExp( pseudos ), - ridentifier = new RegExp( "^" + identifier + "$" ), - - matchExpr = { - "ID": new RegExp( "^#(" + identifier + ")" ), - "CLASS": new RegExp( "^\\.(" + identifier + ")" ), - "TAG": new RegExp( "^(" + identifier + "|[*])" ), - "ATTR": new RegExp( "^" + attributes ), - "PSEUDO": new RegExp( "^" + pseudos ), - "CHILD": new RegExp( "^:(only|first|last|nth|nth-last)-(child|of-type)(?:\\(" + - whitespace + "*(even|odd|(([+-]|)(\\d*)n|)" + whitespace + "*(?:([+-]|)" + - whitespace + "*(\\d+)|))" + whitespace + "*\\)|)", "i" ), - "bool": new RegExp( "^(?:" + booleans + ")$", "i" ), - - // For use in libraries implementing .is() - // We use this for POS matching in `select` - "needsContext": new RegExp( "^" + whitespace + - "*[>+~]|:(even|odd|eq|gt|lt|nth|first|last)(?:\\(" + whitespace + - "*((?:-\\d)?\\d*)" + whitespace + "*\\)|)(?=[^-]|$)", "i" ) - }, - - rhtml = /HTML$/i, - rinputs = /^(?:input|select|textarea|button)$/i, - rheader = /^h\d$/i, - - rnative = /^[^{]+\{\s*\[native \w/, - - // Easily-parseable/retrievable ID or TAG or CLASS selectors - rquickExpr = /^(?:#([\w-]+)|(\w+)|\.([\w-]+))$/, - - rsibling = /[+~]/, - - // CSS escapes - // http://www.w3.org/TR/CSS21/syndata.html#escaped-characters - runescape = new RegExp( "\\\\[\\da-fA-F]{1,6}" + whitespace + "?|\\\\([^\\r\\n\\f])", "g" ), - funescape = function( escape, nonHex ) { - var high = "0x" + escape.slice( 1 ) - 0x10000; - - return nonHex ? - - // Strip the backslash prefix from a non-hex escape sequence - nonHex : - - // Replace a hexadecimal escape sequence with the encoded Unicode code point - // Support: IE <=11+ - // For values outside the Basic Multilingual Plane (BMP), manually construct a - // surrogate pair - high < 0 ? - String.fromCharCode( high + 0x10000 ) : - String.fromCharCode( high >> 10 | 0xD800, high & 0x3FF | 0xDC00 ); - }, - - // CSS string/identifier serialization - // https://drafts.csswg.org/cssom/#common-serializing-idioms - rcssescape = /([\0-\x1f\x7f]|^-?\d)|^-$|[^\0-\x1f\x7f-\uFFFF\w-]/g, - fcssescape = function( ch, asCodePoint ) { - if ( asCodePoint ) { - - // U+0000 NULL becomes U+FFFD REPLACEMENT CHARACTER - if ( ch === "\0" ) { - return "\uFFFD"; - } - - // Control characters and (dependent upon position) numbers get escaped as code points - return ch.slice( 0, -1 ) + "\\" + - ch.charCodeAt( ch.length - 1 ).toString( 16 ) + " "; - } - - // Other potentially-special ASCII characters get backslash-escaped - return "\\" + ch; - }, - - // Used for iframes - // See setDocument() - // Removing the function wrapper causes a "Permission Denied" - // error in IE - unloadHandler = function() { - setDocument(); - }, - - inDisabledFieldset = addCombinator( - function( elem ) { - return elem.disabled === true && elem.nodeName.toLowerCase() === "fieldset"; - }, - { dir: "parentNode", next: "legend" } - ); - -// Optimize for push.apply( _, NodeList ) -try { - push.apply( - ( arr = slice.call( preferredDoc.childNodes ) ), - preferredDoc.childNodes - ); - - // Support: Android<4.0 - // Detect silently failing push.apply - // eslint-disable-next-line no-unused-expressions - arr[ preferredDoc.childNodes.length ].nodeType; -} catch ( e ) { - push = { apply: arr.length ? - - // Leverage slice if possible - function( target, els ) { - pushNative.apply( target, slice.call( els ) ); - } : - - // Support: IE<9 - // Otherwise append directly - function( target, els ) { - var j = target.length, - i = 0; - - // Can't trust NodeList.length - while ( ( target[ j++ ] = els[ i++ ] ) ) {} - target.length = j - 1; - } - }; -} - -function Sizzle( selector, context, results, seed ) { - var m, i, elem, nid, match, groups, newSelector, - newContext = context && context.ownerDocument, - - // nodeType defaults to 9, since context defaults to document - nodeType = context ? context.nodeType : 9; - - results = results || []; - - // Return early from calls with invalid selector or context - if ( typeof selector !== "string" || !selector || - nodeType !== 1 && nodeType !== 9 && nodeType !== 11 ) { - - return results; - } - - // Try to shortcut find operations (as opposed to filters) in HTML documents - if ( !seed ) { - setDocument( context ); - context = context || document; - - if ( documentIsHTML ) { - - // If the selector is sufficiently simple, try using a "get*By*" DOM method - // (excepting DocumentFragment context, where the methods don't exist) - if ( nodeType !== 11 && ( match = rquickExpr.exec( selector ) ) ) { - - // ID selector - if ( ( m = match[ 1 ] ) ) { - - // Document context - if ( nodeType === 9 ) { - if ( ( elem = context.getElementById( m ) ) ) { - - // Support: IE, Opera, Webkit - // TODO: identify versions - // getElementById can match elements by name instead of ID - if ( elem.id === m ) { - results.push( elem ); - return results; - } - } else { - return results; - } - - // Element context - } else { - - // Support: IE, Opera, Webkit - // TODO: identify versions - // getElementById can match elements by name instead of ID - if ( newContext && ( elem = newContext.getElementById( m ) ) && - contains( context, elem ) && - elem.id === m ) { - - results.push( elem ); - return results; - } - } - - // Type selector - } else if ( match[ 2 ] ) { - push.apply( results, context.getElementsByTagName( selector ) ); - return results; - - // Class selector - } else if ( ( m = match[ 3 ] ) && support.getElementsByClassName && - context.getElementsByClassName ) { - - push.apply( results, context.getElementsByClassName( m ) ); - return results; - } - } - - // Take advantage of querySelectorAll - if ( support.qsa && - !nonnativeSelectorCache[ selector + " " ] && - ( !rbuggyQSA || !rbuggyQSA.test( selector ) ) && - - // Support: IE 8 only - // Exclude object elements - ( nodeType !== 1 || context.nodeName.toLowerCase() !== "object" ) ) { - - newSelector = selector; - newContext = context; - - // qSA considers elements outside a scoping root when evaluating child or - // descendant combinators, which is not what we want. - // In such cases, we work around the behavior by prefixing every selector in the - // list with an ID selector referencing the scope context. - // The technique has to be used as well when a leading combinator is used - // as such selectors are not recognized by querySelectorAll. - // Thanks to Andrew Dupont for this technique. - if ( nodeType === 1 && - ( rdescend.test( selector ) || rcombinators.test( selector ) ) ) { - - // Expand context for sibling selectors - newContext = rsibling.test( selector ) && testContext( context.parentNode ) || - context; - - // We can use :scope instead of the ID hack if the browser - // supports it & if we're not changing the context. - if ( newContext !== context || !support.scope ) { - - // Capture the context ID, setting it first if necessary - if ( ( nid = context.getAttribute( "id" ) ) ) { - nid = nid.replace( rcssescape, fcssescape ); - } else { - context.setAttribute( "id", ( nid = expando ) ); - } - } - - // Prefix every selector in the list - groups = tokenize( selector ); - i = groups.length; - while ( i-- ) { - groups[ i ] = ( nid ? "#" + nid : ":scope" ) + " " + - toSelector( groups[ i ] ); - } - newSelector = groups.join( "," ); - } - - try { - push.apply( results, - newContext.querySelectorAll( newSelector ) - ); - return results; - } catch ( qsaError ) { - nonnativeSelectorCache( selector, true ); - } finally { - if ( nid === expando ) { - context.removeAttribute( "id" ); - } - } - } - } - } - - // All others - return select( selector.replace( rtrim, "$1" ), context, results, seed ); -} - -/** - * Create key-value caches of limited size - * @returns {function(string, object)} Returns the Object data after storing it on itself with - * property name the (space-suffixed) string and (if the cache is larger than Expr.cacheLength) - * deleting the oldest entry - */ -function createCache() { - var keys = []; - - function cache( key, value ) { - - // Use (key + " ") to avoid collision with native prototype properties (see Issue #157) - if ( keys.push( key + " " ) > Expr.cacheLength ) { - - // Only keep the most recent entries - delete cache[ keys.shift() ]; - } - return ( cache[ key + " " ] = value ); - } - return cache; -} - -/** - * Mark a function for special use by Sizzle - * @param {Function} fn The function to mark - */ -function markFunction( fn ) { - fn[ expando ] = true; - return fn; -} - -/** - * Support testing using an element - * @param {Function} fn Passed the created element and returns a boolean result - */ -function assert( fn ) { - var el = document.createElement( "fieldset" ); - - try { - return !!fn( el ); - } catch ( e ) { - return false; - } finally { - - // Remove from its parent by default - if ( el.parentNode ) { - el.parentNode.removeChild( el ); - } - - // release memory in IE - el = null; - } -} - -/** - * Adds the same handler for all of the specified attrs - * @param {String} attrs Pipe-separated list of attributes - * @param {Function} handler The method that will be applied - */ -function addHandle( attrs, handler ) { - var arr = attrs.split( "|" ), - i = arr.length; - - while ( i-- ) { - Expr.attrHandle[ arr[ i ] ] = handler; - } -} - -/** - * Checks document order of two siblings - * @param {Element} a - * @param {Element} b - * @returns {Number} Returns less than 0 if a precedes b, greater than 0 if a follows b - */ -function siblingCheck( a, b ) { - var cur = b && a, - diff = cur && a.nodeType === 1 && b.nodeType === 1 && - a.sourceIndex - b.sourceIndex; - - // Use IE sourceIndex if available on both nodes - if ( diff ) { - return diff; - } - - // Check if b follows a - if ( cur ) { - while ( ( cur = cur.nextSibling ) ) { - if ( cur === b ) { - return -1; - } - } - } - - return a ? 1 : -1; -} - -/** - * Returns a function to use in pseudos for input types - * @param {String} type - */ -function createInputPseudo( type ) { - return function( elem ) { - var name = elem.nodeName.toLowerCase(); - return name === "input" && elem.type === type; - }; -} - -/** - * Returns a function to use in pseudos for buttons - * @param {String} type - */ -function createButtonPseudo( type ) { - return function( elem ) { - var name = elem.nodeName.toLowerCase(); - return ( name === "input" || name === "button" ) && elem.type === type; - }; -} - -/** - * Returns a function to use in pseudos for :enabled/:disabled - * @param {Boolean} disabled true for :disabled; false for :enabled - */ -function createDisabledPseudo( disabled ) { - - // Known :disabled false positives: fieldset[disabled] > legend:nth-of-type(n+2) :can-disable - return function( elem ) { - - // Only certain elements can match :enabled or :disabled - // https://html.spec.whatwg.org/multipage/scripting.html#selector-enabled - // https://html.spec.whatwg.org/multipage/scripting.html#selector-disabled - if ( "form" in elem ) { - - // Check for inherited disabledness on relevant non-disabled elements: - // * listed form-associated elements in a disabled fieldset - // https://html.spec.whatwg.org/multipage/forms.html#category-listed - // https://html.spec.whatwg.org/multipage/forms.html#concept-fe-disabled - // * option elements in a disabled optgroup - // https://html.spec.whatwg.org/multipage/forms.html#concept-option-disabled - // All such elements have a "form" property. - if ( elem.parentNode && elem.disabled === false ) { - - // Option elements defer to a parent optgroup if present - if ( "label" in elem ) { - if ( "label" in elem.parentNode ) { - return elem.parentNode.disabled === disabled; - } else { - return elem.disabled === disabled; - } - } - - // Support: IE 6 - 11 - // Use the isDisabled shortcut property to check for disabled fieldset ancestors - return elem.isDisabled === disabled || - - // Where there is no isDisabled, check manually - /* jshint -W018 */ - elem.isDisabled !== !disabled && - inDisabledFieldset( elem ) === disabled; - } - - return elem.disabled === disabled; - - // Try to winnow out elements that can't be disabled before trusting the disabled property. - // Some victims get caught in our net (label, legend, menu, track), but it shouldn't - // even exist on them, let alone have a boolean value. - } else if ( "label" in elem ) { - return elem.disabled === disabled; - } - - // Remaining elements are neither :enabled nor :disabled - return false; - }; -} - -/** - * Returns a function to use in pseudos for positionals - * @param {Function} fn - */ -function createPositionalPseudo( fn ) { - return markFunction( function( argument ) { - argument = +argument; - return markFunction( function( seed, matches ) { - var j, - matchIndexes = fn( [], seed.length, argument ), - i = matchIndexes.length; - - // Match elements found at the specified indexes - while ( i-- ) { - if ( seed[ ( j = matchIndexes[ i ] ) ] ) { - seed[ j ] = !( matches[ j ] = seed[ j ] ); - } - } - } ); - } ); -} - -/** - * Checks a node for validity as a Sizzle context - * @param {Element|Object=} context - * @returns {Element|Object|Boolean} The input node if acceptable, otherwise a falsy value - */ -function testContext( context ) { - return context && typeof context.getElementsByTagName !== "undefined" && context; -} - -// Expose support vars for convenience -support = Sizzle.support = {}; - -/** - * Detects XML nodes - * @param {Element|Object} elem An element or a document - * @returns {Boolean} True iff elem is a non-HTML XML node - */ -isXML = Sizzle.isXML = function( elem ) { - var namespace = elem && elem.namespaceURI, - docElem = elem && ( elem.ownerDocument || elem ).documentElement; - - // Support: IE <=8 - // Assume HTML when documentElement doesn't yet exist, such as inside loading iframes - // https://bugs.jquery.com/ticket/4833 - return !rhtml.test( namespace || docElem && docElem.nodeName || "HTML" ); -}; - -/** - * Sets document-related variables once based on the current document - * @param {Element|Object} [doc] An element or document object to use to set the document - * @returns {Object} Returns the current document - */ -setDocument = Sizzle.setDocument = function( node ) { - var hasCompare, subWindow, - doc = node ? node.ownerDocument || node : preferredDoc; - - // Return early if doc is invalid or already selected - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - if ( doc == document || doc.nodeType !== 9 || !doc.documentElement ) { - return document; - } - - // Update global variables - document = doc; - docElem = document.documentElement; - documentIsHTML = !isXML( document ); - - // Support: IE 9 - 11+, Edge 12 - 18+ - // Accessing iframe documents after unload throws "permission denied" errors (jQuery #13936) - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - if ( preferredDoc != document && - ( subWindow = document.defaultView ) && subWindow.top !== subWindow ) { - - // Support: IE 11, Edge - if ( subWindow.addEventListener ) { - subWindow.addEventListener( "unload", unloadHandler, false ); - - // Support: IE 9 - 10 only - } else if ( subWindow.attachEvent ) { - subWindow.attachEvent( "onunload", unloadHandler ); - } - } - - // Support: IE 8 - 11+, Edge 12 - 18+, Chrome <=16 - 25 only, Firefox <=3.6 - 31 only, - // Safari 4 - 5 only, Opera <=11.6 - 12.x only - // IE/Edge & older browsers don't support the :scope pseudo-class. - // Support: Safari 6.0 only - // Safari 6.0 supports :scope but it's an alias of :root there. - support.scope = assert( function( el ) { - docElem.appendChild( el ).appendChild( document.createElement( "div" ) ); - return typeof el.querySelectorAll !== "undefined" && - !el.querySelectorAll( ":scope fieldset div" ).length; - } ); - - /* Attributes - ---------------------------------------------------------------------- */ - - // Support: IE<8 - // Verify that getAttribute really returns attributes and not properties - // (excepting IE8 booleans) - support.attributes = assert( function( el ) { - el.className = "i"; - return !el.getAttribute( "className" ); - } ); - - /* getElement(s)By* - ---------------------------------------------------------------------- */ - - // Check if getElementsByTagName("*") returns only elements - support.getElementsByTagName = assert( function( el ) { - el.appendChild( document.createComment( "" ) ); - return !el.getElementsByTagName( "*" ).length; - } ); - - // Support: IE<9 - support.getElementsByClassName = rnative.test( document.getElementsByClassName ); - - // Support: IE<10 - // Check if getElementById returns elements by name - // The broken getElementById methods don't pick up programmatically-set names, - // so use a roundabout getElementsByName test - support.getById = assert( function( el ) { - docElem.appendChild( el ).id = expando; - return !document.getElementsByName || !document.getElementsByName( expando ).length; - } ); - - // ID filter and find - if ( support.getById ) { - Expr.filter[ "ID" ] = function( id ) { - var attrId = id.replace( runescape, funescape ); - return function( elem ) { - return elem.getAttribute( "id" ) === attrId; - }; - }; - Expr.find[ "ID" ] = function( id, context ) { - if ( typeof context.getElementById !== "undefined" && documentIsHTML ) { - var elem = context.getElementById( id ); - return elem ? [ elem ] : []; - } - }; - } else { - Expr.filter[ "ID" ] = function( id ) { - var attrId = id.replace( runescape, funescape ); - return function( elem ) { - var node = typeof elem.getAttributeNode !== "undefined" && - elem.getAttributeNode( "id" ); - return node && node.value === attrId; - }; - }; - - // Support: IE 6 - 7 only - // getElementById is not reliable as a find shortcut - Expr.find[ "ID" ] = function( id, context ) { - if ( typeof context.getElementById !== "undefined" && documentIsHTML ) { - var node, i, elems, - elem = context.getElementById( id ); - - if ( elem ) { - - // Verify the id attribute - node = elem.getAttributeNode( "id" ); - if ( node && node.value === id ) { - return [ elem ]; - } - - // Fall back on getElementsByName - elems = context.getElementsByName( id ); - i = 0; - while ( ( elem = elems[ i++ ] ) ) { - node = elem.getAttributeNode( "id" ); - if ( node && node.value === id ) { - return [ elem ]; - } - } - } - - return []; - } - }; - } - - // Tag - Expr.find[ "TAG" ] = support.getElementsByTagName ? - function( tag, context ) { - if ( typeof context.getElementsByTagName !== "undefined" ) { - return context.getElementsByTagName( tag ); - - // DocumentFragment nodes don't have gEBTN - } else if ( support.qsa ) { - return context.querySelectorAll( tag ); - } - } : - - function( tag, context ) { - var elem, - tmp = [], - i = 0, - - // By happy coincidence, a (broken) gEBTN appears on DocumentFragment nodes too - results = context.getElementsByTagName( tag ); - - // Filter out possible comments - if ( tag === "*" ) { - while ( ( elem = results[ i++ ] ) ) { - if ( elem.nodeType === 1 ) { - tmp.push( elem ); - } - } - - return tmp; - } - return results; - }; - - // Class - Expr.find[ "CLASS" ] = support.getElementsByClassName && function( className, context ) { - if ( typeof context.getElementsByClassName !== "undefined" && documentIsHTML ) { - return context.getElementsByClassName( className ); - } - }; - - /* QSA/matchesSelector - ---------------------------------------------------------------------- */ - - // QSA and matchesSelector support - - // matchesSelector(:active) reports false when true (IE9/Opera 11.5) - rbuggyMatches = []; - - // qSa(:focus) reports false when true (Chrome 21) - // We allow this because of a bug in IE8/9 that throws an error - // whenever `document.activeElement` is accessed on an iframe - // So, we allow :focus to pass through QSA all the time to avoid the IE error - // See https://bugs.jquery.com/ticket/13378 - rbuggyQSA = []; - - if ( ( support.qsa = rnative.test( document.querySelectorAll ) ) ) { - - // Build QSA regex - // Regex strategy adopted from Diego Perini - assert( function( el ) { - - var input; - - // Select is set to empty string on purpose - // This is to test IE's treatment of not explicitly - // setting a boolean content attribute, - // since its presence should be enough - // https://bugs.jquery.com/ticket/12359 - docElem.appendChild( el ).innerHTML = "" + - ""; - - // Support: IE8, Opera 11-12.16 - // Nothing should be selected when empty strings follow ^= or $= or *= - // The test attribute must be unknown in Opera but "safe" for WinRT - // https://msdn.microsoft.com/en-us/library/ie/hh465388.aspx#attribute_section - if ( el.querySelectorAll( "[msallowcapture^='']" ).length ) { - rbuggyQSA.push( "[*^$]=" + whitespace + "*(?:''|\"\")" ); - } - - // Support: IE8 - // Boolean attributes and "value" are not treated correctly - if ( !el.querySelectorAll( "[selected]" ).length ) { - rbuggyQSA.push( "\\[" + whitespace + "*(?:value|" + booleans + ")" ); - } - - // Support: Chrome<29, Android<4.4, Safari<7.0+, iOS<7.0+, PhantomJS<1.9.8+ - if ( !el.querySelectorAll( "[id~=" + expando + "-]" ).length ) { - rbuggyQSA.push( "~=" ); - } - - // Support: IE 11+, Edge 15 - 18+ - // IE 11/Edge don't find elements on a `[name='']` query in some cases. - // Adding a temporary attribute to the document before the selection works - // around the issue. - // Interestingly, IE 10 & older don't seem to have the issue. - input = document.createElement( "input" ); - input.setAttribute( "name", "" ); - el.appendChild( input ); - if ( !el.querySelectorAll( "[name='']" ).length ) { - rbuggyQSA.push( "\\[" + whitespace + "*name" + whitespace + "*=" + - whitespace + "*(?:''|\"\")" ); - } - - // Webkit/Opera - :checked should return selected option elements - // http://www.w3.org/TR/2011/REC-css3-selectors-20110929/#checked - // IE8 throws error here and will not see later tests - if ( !el.querySelectorAll( ":checked" ).length ) { - rbuggyQSA.push( ":checked" ); - } - - // Support: Safari 8+, iOS 8+ - // https://bugs.webkit.org/show_bug.cgi?id=136851 - // In-page `selector#id sibling-combinator selector` fails - if ( !el.querySelectorAll( "a#" + expando + "+*" ).length ) { - rbuggyQSA.push( ".#.+[+~]" ); - } - - // Support: Firefox <=3.6 - 5 only - // Old Firefox doesn't throw on a badly-escaped identifier. - el.querySelectorAll( "\\\f" ); - rbuggyQSA.push( "[\\r\\n\\f]" ); - } ); - - assert( function( el ) { - el.innerHTML = "" + - ""; - - // Support: Windows 8 Native Apps - // The type and name attributes are restricted during .innerHTML assignment - var input = document.createElement( "input" ); - input.setAttribute( "type", "hidden" ); - el.appendChild( input ).setAttribute( "name", "D" ); - - // Support: IE8 - // Enforce case-sensitivity of name attribute - if ( el.querySelectorAll( "[name=d]" ).length ) { - rbuggyQSA.push( "name" + whitespace + "*[*^$|!~]?=" ); - } - - // FF 3.5 - :enabled/:disabled and hidden elements (hidden elements are still enabled) - // IE8 throws error here and will not see later tests - if ( el.querySelectorAll( ":enabled" ).length !== 2 ) { - rbuggyQSA.push( ":enabled", ":disabled" ); - } - - // Support: IE9-11+ - // IE's :disabled selector does not pick up the children of disabled fieldsets - docElem.appendChild( el ).disabled = true; - if ( el.querySelectorAll( ":disabled" ).length !== 2 ) { - rbuggyQSA.push( ":enabled", ":disabled" ); - } - - // Support: Opera 10 - 11 only - // Opera 10-11 does not throw on post-comma invalid pseudos - el.querySelectorAll( "*,:x" ); - rbuggyQSA.push( ",.*:" ); - } ); - } - - if ( ( support.matchesSelector = rnative.test( ( matches = docElem.matches || - docElem.webkitMatchesSelector || - docElem.mozMatchesSelector || - docElem.oMatchesSelector || - docElem.msMatchesSelector ) ) ) ) { - - assert( function( el ) { - - // Check to see if it's possible to do matchesSelector - // on a disconnected node (IE 9) - support.disconnectedMatch = matches.call( el, "*" ); - - // This should fail with an exception - // Gecko does not error, returns false instead - matches.call( el, "[s!='']:x" ); - rbuggyMatches.push( "!=", pseudos ); - } ); - } - - rbuggyQSA = rbuggyQSA.length && new RegExp( rbuggyQSA.join( "|" ) ); - rbuggyMatches = rbuggyMatches.length && new RegExp( rbuggyMatches.join( "|" ) ); - - /* Contains - ---------------------------------------------------------------------- */ - hasCompare = rnative.test( docElem.compareDocumentPosition ); - - // Element contains another - // Purposefully self-exclusive - // As in, an element does not contain itself - contains = hasCompare || rnative.test( docElem.contains ) ? - function( a, b ) { - var adown = a.nodeType === 9 ? a.documentElement : a, - bup = b && b.parentNode; - return a === bup || !!( bup && bup.nodeType === 1 && ( - adown.contains ? - adown.contains( bup ) : - a.compareDocumentPosition && a.compareDocumentPosition( bup ) & 16 - ) ); - } : - function( a, b ) { - if ( b ) { - while ( ( b = b.parentNode ) ) { - if ( b === a ) { - return true; - } - } - } - return false; - }; - - /* Sorting - ---------------------------------------------------------------------- */ - - // Document order sorting - sortOrder = hasCompare ? - function( a, b ) { - - // Flag for duplicate removal - if ( a === b ) { - hasDuplicate = true; - return 0; - } - - // Sort on method existence if only one input has compareDocumentPosition - var compare = !a.compareDocumentPosition - !b.compareDocumentPosition; - if ( compare ) { - return compare; - } - - // Calculate position if both inputs belong to the same document - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - compare = ( a.ownerDocument || a ) == ( b.ownerDocument || b ) ? - a.compareDocumentPosition( b ) : - - // Otherwise we know they are disconnected - 1; - - // Disconnected nodes - if ( compare & 1 || - ( !support.sortDetached && b.compareDocumentPosition( a ) === compare ) ) { - - // Choose the first element that is related to our preferred document - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - if ( a == document || a.ownerDocument == preferredDoc && - contains( preferredDoc, a ) ) { - return -1; - } - - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - if ( b == document || b.ownerDocument == preferredDoc && - contains( preferredDoc, b ) ) { - return 1; - } - - // Maintain original order - return sortInput ? - ( indexOf( sortInput, a ) - indexOf( sortInput, b ) ) : - 0; - } - - return compare & 4 ? -1 : 1; - } : - function( a, b ) { - - // Exit early if the nodes are identical - if ( a === b ) { - hasDuplicate = true; - return 0; - } - - var cur, - i = 0, - aup = a.parentNode, - bup = b.parentNode, - ap = [ a ], - bp = [ b ]; - - // Parentless nodes are either documents or disconnected - if ( !aup || !bup ) { - - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - /* eslint-disable eqeqeq */ - return a == document ? -1 : - b == document ? 1 : - /* eslint-enable eqeqeq */ - aup ? -1 : - bup ? 1 : - sortInput ? - ( indexOf( sortInput, a ) - indexOf( sortInput, b ) ) : - 0; - - // If the nodes are siblings, we can do a quick check - } else if ( aup === bup ) { - return siblingCheck( a, b ); - } - - // Otherwise we need full lists of their ancestors for comparison - cur = a; - while ( ( cur = cur.parentNode ) ) { - ap.unshift( cur ); - } - cur = b; - while ( ( cur = cur.parentNode ) ) { - bp.unshift( cur ); - } - - // Walk down the tree looking for a discrepancy - while ( ap[ i ] === bp[ i ] ) { - i++; - } - - return i ? - - // Do a sibling check if the nodes have a common ancestor - siblingCheck( ap[ i ], bp[ i ] ) : - - // Otherwise nodes in our document sort first - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - /* eslint-disable eqeqeq */ - ap[ i ] == preferredDoc ? -1 : - bp[ i ] == preferredDoc ? 1 : - /* eslint-enable eqeqeq */ - 0; - }; - - return document; -}; - -Sizzle.matches = function( expr, elements ) { - return Sizzle( expr, null, null, elements ); -}; - -Sizzle.matchesSelector = function( elem, expr ) { - setDocument( elem ); - - if ( support.matchesSelector && documentIsHTML && - !nonnativeSelectorCache[ expr + " " ] && - ( !rbuggyMatches || !rbuggyMatches.test( expr ) ) && - ( !rbuggyQSA || !rbuggyQSA.test( expr ) ) ) { - - try { - var ret = matches.call( elem, expr ); - - // IE 9's matchesSelector returns false on disconnected nodes - if ( ret || support.disconnectedMatch || - - // As well, disconnected nodes are said to be in a document - // fragment in IE 9 - elem.document && elem.document.nodeType !== 11 ) { - return ret; - } - } catch ( e ) { - nonnativeSelectorCache( expr, true ); - } - } - - return Sizzle( expr, document, null, [ elem ] ).length > 0; -}; - -Sizzle.contains = function( context, elem ) { - - // Set document vars if needed - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - if ( ( context.ownerDocument || context ) != document ) { - setDocument( context ); - } - return contains( context, elem ); -}; - -Sizzle.attr = function( elem, name ) { - - // Set document vars if needed - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - if ( ( elem.ownerDocument || elem ) != document ) { - setDocument( elem ); - } - - var fn = Expr.attrHandle[ name.toLowerCase() ], - - // Don't get fooled by Object.prototype properties (jQuery #13807) - val = fn && hasOwn.call( Expr.attrHandle, name.toLowerCase() ) ? - fn( elem, name, !documentIsHTML ) : - undefined; - - return val !== undefined ? - val : - support.attributes || !documentIsHTML ? - elem.getAttribute( name ) : - ( val = elem.getAttributeNode( name ) ) && val.specified ? - val.value : - null; -}; - -Sizzle.escape = function( sel ) { - return ( sel + "" ).replace( rcssescape, fcssescape ); -}; - -Sizzle.error = function( msg ) { - throw new Error( "Syntax error, unrecognized expression: " + msg ); -}; - -/** - * Document sorting and removing duplicates - * @param {ArrayLike} results - */ -Sizzle.uniqueSort = function( results ) { - var elem, - duplicates = [], - j = 0, - i = 0; - - // Unless we *know* we can detect duplicates, assume their presence - hasDuplicate = !support.detectDuplicates; - sortInput = !support.sortStable && results.slice( 0 ); - results.sort( sortOrder ); - - if ( hasDuplicate ) { - while ( ( elem = results[ i++ ] ) ) { - if ( elem === results[ i ] ) { - j = duplicates.push( i ); - } - } - while ( j-- ) { - results.splice( duplicates[ j ], 1 ); - } - } - - // Clear input after sorting to release objects - // See https://github.com/jquery/sizzle/pull/225 - sortInput = null; - - return results; -}; - -/** - * Utility function for retrieving the text value of an array of DOM nodes - * @param {Array|Element} elem - */ -getText = Sizzle.getText = function( elem ) { - var node, - ret = "", - i = 0, - nodeType = elem.nodeType; - - if ( !nodeType ) { - - // If no nodeType, this is expected to be an array - while ( ( node = elem[ i++ ] ) ) { - - // Do not traverse comment nodes - ret += getText( node ); - } - } else if ( nodeType === 1 || nodeType === 9 || nodeType === 11 ) { - - // Use textContent for elements - // innerText usage removed for consistency of new lines (jQuery #11153) - if ( typeof elem.textContent === "string" ) { - return elem.textContent; - } else { - - // Traverse its children - for ( elem = elem.firstChild; elem; elem = elem.nextSibling ) { - ret += getText( elem ); - } - } - } else if ( nodeType === 3 || nodeType === 4 ) { - return elem.nodeValue; - } - - // Do not include comment or processing instruction nodes - - return ret; -}; - -Expr = Sizzle.selectors = { - - // Can be adjusted by the user - cacheLength: 50, - - createPseudo: markFunction, - - match: matchExpr, - - attrHandle: {}, - - find: {}, - - relative: { - ">": { dir: "parentNode", first: true }, - " ": { dir: "parentNode" }, - "+": { dir: "previousSibling", first: true }, - "~": { dir: "previousSibling" } - }, - - preFilter: { - "ATTR": function( match ) { - match[ 1 ] = match[ 1 ].replace( runescape, funescape ); - - // Move the given value to match[3] whether quoted or unquoted - match[ 3 ] = ( match[ 3 ] || match[ 4 ] || - match[ 5 ] || "" ).replace( runescape, funescape ); - - if ( match[ 2 ] === "~=" ) { - match[ 3 ] = " " + match[ 3 ] + " "; - } - - return match.slice( 0, 4 ); - }, - - "CHILD": function( match ) { - - /* matches from matchExpr["CHILD"] - 1 type (only|nth|...) - 2 what (child|of-type) - 3 argument (even|odd|\d*|\d*n([+-]\d+)?|...) - 4 xn-component of xn+y argument ([+-]?\d*n|) - 5 sign of xn-component - 6 x of xn-component - 7 sign of y-component - 8 y of y-component - */ - match[ 1 ] = match[ 1 ].toLowerCase(); - - if ( match[ 1 ].slice( 0, 3 ) === "nth" ) { - - // nth-* requires argument - if ( !match[ 3 ] ) { - Sizzle.error( match[ 0 ] ); - } - - // numeric x and y parameters for Expr.filter.CHILD - // remember that false/true cast respectively to 0/1 - match[ 4 ] = +( match[ 4 ] ? - match[ 5 ] + ( match[ 6 ] || 1 ) : - 2 * ( match[ 3 ] === "even" || match[ 3 ] === "odd" ) ); - match[ 5 ] = +( ( match[ 7 ] + match[ 8 ] ) || match[ 3 ] === "odd" ); - - // other types prohibit arguments - } else if ( match[ 3 ] ) { - Sizzle.error( match[ 0 ] ); - } - - return match; - }, - - "PSEUDO": function( match ) { - var excess, - unquoted = !match[ 6 ] && match[ 2 ]; - - if ( matchExpr[ "CHILD" ].test( match[ 0 ] ) ) { - return null; - } - - // Accept quoted arguments as-is - if ( match[ 3 ] ) { - match[ 2 ] = match[ 4 ] || match[ 5 ] || ""; - - // Strip excess characters from unquoted arguments - } else if ( unquoted && rpseudo.test( unquoted ) && - - // Get excess from tokenize (recursively) - ( excess = tokenize( unquoted, true ) ) && - - // advance to the next closing parenthesis - ( excess = unquoted.indexOf( ")", unquoted.length - excess ) - unquoted.length ) ) { - - // excess is a negative index - match[ 0 ] = match[ 0 ].slice( 0, excess ); - match[ 2 ] = unquoted.slice( 0, excess ); - } - - // Return only captures needed by the pseudo filter method (type and argument) - return match.slice( 0, 3 ); - } - }, - - filter: { - - "TAG": function( nodeNameSelector ) { - var nodeName = nodeNameSelector.replace( runescape, funescape ).toLowerCase(); - return nodeNameSelector === "*" ? - function() { - return true; - } : - function( elem ) { - return elem.nodeName && elem.nodeName.toLowerCase() === nodeName; - }; - }, - - "CLASS": function( className ) { - var pattern = classCache[ className + " " ]; - - return pattern || - ( pattern = new RegExp( "(^|" + whitespace + - ")" + className + "(" + whitespace + "|$)" ) ) && classCache( - className, function( elem ) { - return pattern.test( - typeof elem.className === "string" && elem.className || - typeof elem.getAttribute !== "undefined" && - elem.getAttribute( "class" ) || - "" - ); - } ); - }, - - "ATTR": function( name, operator, check ) { - return function( elem ) { - var result = Sizzle.attr( elem, name ); - - if ( result == null ) { - return operator === "!="; - } - if ( !operator ) { - return true; - } - - result += ""; - - /* eslint-disable max-len */ - - return operator === "=" ? result === check : - operator === "!=" ? result !== check : - operator === "^=" ? check && result.indexOf( check ) === 0 : - operator === "*=" ? check && result.indexOf( check ) > -1 : - operator === "$=" ? check && result.slice( -check.length ) === check : - operator === "~=" ? ( " " + result.replace( rwhitespace, " " ) + " " ).indexOf( check ) > -1 : - operator === "|=" ? result === check || result.slice( 0, check.length + 1 ) === check + "-" : - false; - /* eslint-enable max-len */ - - }; - }, - - "CHILD": function( type, what, _argument, first, last ) { - var simple = type.slice( 0, 3 ) !== "nth", - forward = type.slice( -4 ) !== "last", - ofType = what === "of-type"; - - return first === 1 && last === 0 ? - - // Shortcut for :nth-*(n) - function( elem ) { - return !!elem.parentNode; - } : - - function( elem, _context, xml ) { - var cache, uniqueCache, outerCache, node, nodeIndex, start, - dir = simple !== forward ? "nextSibling" : "previousSibling", - parent = elem.parentNode, - name = ofType && elem.nodeName.toLowerCase(), - useCache = !xml && !ofType, - diff = false; - - if ( parent ) { - - // :(first|last|only)-(child|of-type) - if ( simple ) { - while ( dir ) { - node = elem; - while ( ( node = node[ dir ] ) ) { - if ( ofType ? - node.nodeName.toLowerCase() === name : - node.nodeType === 1 ) { - - return false; - } - } - - // Reverse direction for :only-* (if we haven't yet done so) - start = dir = type === "only" && !start && "nextSibling"; - } - return true; - } - - start = [ forward ? parent.firstChild : parent.lastChild ]; - - // non-xml :nth-child(...) stores cache data on `parent` - if ( forward && useCache ) { - - // Seek `elem` from a previously-cached index - - // ...in a gzip-friendly way - node = parent; - outerCache = node[ expando ] || ( node[ expando ] = {} ); - - // Support: IE <9 only - // Defend against cloned attroperties (jQuery gh-1709) - uniqueCache = outerCache[ node.uniqueID ] || - ( outerCache[ node.uniqueID ] = {} ); - - cache = uniqueCache[ type ] || []; - nodeIndex = cache[ 0 ] === dirruns && cache[ 1 ]; - diff = nodeIndex && cache[ 2 ]; - node = nodeIndex && parent.childNodes[ nodeIndex ]; - - while ( ( node = ++nodeIndex && node && node[ dir ] || - - // Fallback to seeking `elem` from the start - ( diff = nodeIndex = 0 ) || start.pop() ) ) { - - // When found, cache indexes on `parent` and break - if ( node.nodeType === 1 && ++diff && node === elem ) { - uniqueCache[ type ] = [ dirruns, nodeIndex, diff ]; - break; - } - } - - } else { - - // Use previously-cached element index if available - if ( useCache ) { - - // ...in a gzip-friendly way - node = elem; - outerCache = node[ expando ] || ( node[ expando ] = {} ); - - // Support: IE <9 only - // Defend against cloned attroperties (jQuery gh-1709) - uniqueCache = outerCache[ node.uniqueID ] || - ( outerCache[ node.uniqueID ] = {} ); - - cache = uniqueCache[ type ] || []; - nodeIndex = cache[ 0 ] === dirruns && cache[ 1 ]; - diff = nodeIndex; - } - - // xml :nth-child(...) - // or :nth-last-child(...) or :nth(-last)?-of-type(...) - if ( diff === false ) { - - // Use the same loop as above to seek `elem` from the start - while ( ( node = ++nodeIndex && node && node[ dir ] || - ( diff = nodeIndex = 0 ) || start.pop() ) ) { - - if ( ( ofType ? - node.nodeName.toLowerCase() === name : - node.nodeType === 1 ) && - ++diff ) { - - // Cache the index of each encountered element - if ( useCache ) { - outerCache = node[ expando ] || - ( node[ expando ] = {} ); - - // Support: IE <9 only - // Defend against cloned attroperties (jQuery gh-1709) - uniqueCache = outerCache[ node.uniqueID ] || - ( outerCache[ node.uniqueID ] = {} ); - - uniqueCache[ type ] = [ dirruns, diff ]; - } - - if ( node === elem ) { - break; - } - } - } - } - } - - // Incorporate the offset, then check against cycle size - diff -= last; - return diff === first || ( diff % first === 0 && diff / first >= 0 ); - } - }; - }, - - "PSEUDO": function( pseudo, argument ) { - - // pseudo-class names are case-insensitive - // http://www.w3.org/TR/selectors/#pseudo-classes - // Prioritize by case sensitivity in case custom pseudos are added with uppercase letters - // Remember that setFilters inherits from pseudos - var args, - fn = Expr.pseudos[ pseudo ] || Expr.setFilters[ pseudo.toLowerCase() ] || - Sizzle.error( "unsupported pseudo: " + pseudo ); - - // The user may use createPseudo to indicate that - // arguments are needed to create the filter function - // just as Sizzle does - if ( fn[ expando ] ) { - return fn( argument ); - } - - // But maintain support for old signatures - if ( fn.length > 1 ) { - args = [ pseudo, pseudo, "", argument ]; - return Expr.setFilters.hasOwnProperty( pseudo.toLowerCase() ) ? - markFunction( function( seed, matches ) { - var idx, - matched = fn( seed, argument ), - i = matched.length; - while ( i-- ) { - idx = indexOf( seed, matched[ i ] ); - seed[ idx ] = !( matches[ idx ] = matched[ i ] ); - } - } ) : - function( elem ) { - return fn( elem, 0, args ); - }; - } - - return fn; - } - }, - - pseudos: { - - // Potentially complex pseudos - "not": markFunction( function( selector ) { - - // Trim the selector passed to compile - // to avoid treating leading and trailing - // spaces as combinators - var input = [], - results = [], - matcher = compile( selector.replace( rtrim, "$1" ) ); - - return matcher[ expando ] ? - markFunction( function( seed, matches, _context, xml ) { - var elem, - unmatched = matcher( seed, null, xml, [] ), - i = seed.length; - - // Match elements unmatched by `matcher` - while ( i-- ) { - if ( ( elem = unmatched[ i ] ) ) { - seed[ i ] = !( matches[ i ] = elem ); - } - } - } ) : - function( elem, _context, xml ) { - input[ 0 ] = elem; - matcher( input, null, xml, results ); - - // Don't keep the element (issue #299) - input[ 0 ] = null; - return !results.pop(); - }; - } ), - - "has": markFunction( function( selector ) { - return function( elem ) { - return Sizzle( selector, elem ).length > 0; - }; - } ), - - "contains": markFunction( function( text ) { - text = text.replace( runescape, funescape ); - return function( elem ) { - return ( elem.textContent || getText( elem ) ).indexOf( text ) > -1; - }; - } ), - - // "Whether an element is represented by a :lang() selector - // is based solely on the element's language value - // being equal to the identifier C, - // or beginning with the identifier C immediately followed by "-". - // The matching of C against the element's language value is performed case-insensitively. - // The identifier C does not have to be a valid language name." - // http://www.w3.org/TR/selectors/#lang-pseudo - "lang": markFunction( function( lang ) { - - // lang value must be a valid identifier - if ( !ridentifier.test( lang || "" ) ) { - Sizzle.error( "unsupported lang: " + lang ); - } - lang = lang.replace( runescape, funescape ).toLowerCase(); - return function( elem ) { - var elemLang; - do { - if ( ( elemLang = documentIsHTML ? - elem.lang : - elem.getAttribute( "xml:lang" ) || elem.getAttribute( "lang" ) ) ) { - - elemLang = elemLang.toLowerCase(); - return elemLang === lang || elemLang.indexOf( lang + "-" ) === 0; - } - } while ( ( elem = elem.parentNode ) && elem.nodeType === 1 ); - return false; - }; - } ), - - // Miscellaneous - "target": function( elem ) { - var hash = window.location && window.location.hash; - return hash && hash.slice( 1 ) === elem.id; - }, - - "root": function( elem ) { - return elem === docElem; - }, - - "focus": function( elem ) { - return elem === document.activeElement && - ( !document.hasFocus || document.hasFocus() ) && - !!( elem.type || elem.href || ~elem.tabIndex ); - }, - - // Boolean properties - "enabled": createDisabledPseudo( false ), - "disabled": createDisabledPseudo( true ), - - "checked": function( elem ) { - - // In CSS3, :checked should return both checked and selected elements - // http://www.w3.org/TR/2011/REC-css3-selectors-20110929/#checked - var nodeName = elem.nodeName.toLowerCase(); - return ( nodeName === "input" && !!elem.checked ) || - ( nodeName === "option" && !!elem.selected ); - }, - - "selected": function( elem ) { - - // Accessing this property makes selected-by-default - // options in Safari work properly - if ( elem.parentNode ) { - // eslint-disable-next-line no-unused-expressions - elem.parentNode.selectedIndex; - } - - return elem.selected === true; - }, - - // Contents - "empty": function( elem ) { - - // http://www.w3.org/TR/selectors/#empty-pseudo - // :empty is negated by element (1) or content nodes (text: 3; cdata: 4; entity ref: 5), - // but not by others (comment: 8; processing instruction: 7; etc.) - // nodeType < 6 works because attributes (2) do not appear as children - for ( elem = elem.firstChild; elem; elem = elem.nextSibling ) { - if ( elem.nodeType < 6 ) { - return false; - } - } - return true; - }, - - "parent": function( elem ) { - return !Expr.pseudos[ "empty" ]( elem ); - }, - - // Element/input types - "header": function( elem ) { - return rheader.test( elem.nodeName ); - }, - - "input": function( elem ) { - return rinputs.test( elem.nodeName ); - }, - - "button": function( elem ) { - var name = elem.nodeName.toLowerCase(); - return name === "input" && elem.type === "button" || name === "button"; - }, - - "text": function( elem ) { - var attr; - return elem.nodeName.toLowerCase() === "input" && - elem.type === "text" && - - // Support: IE<8 - // New HTML5 attribute values (e.g., "search") appear with elem.type === "text" - ( ( attr = elem.getAttribute( "type" ) ) == null || - attr.toLowerCase() === "text" ); - }, - - // Position-in-collection - "first": createPositionalPseudo( function() { - return [ 0 ]; - } ), - - "last": createPositionalPseudo( function( _matchIndexes, length ) { - return [ length - 1 ]; - } ), - - "eq": createPositionalPseudo( function( _matchIndexes, length, argument ) { - return [ argument < 0 ? argument + length : argument ]; - } ), - - "even": createPositionalPseudo( function( matchIndexes, length ) { - var i = 0; - for ( ; i < length; i += 2 ) { - matchIndexes.push( i ); - } - return matchIndexes; - } ), - - "odd": createPositionalPseudo( function( matchIndexes, length ) { - var i = 1; - for ( ; i < length; i += 2 ) { - matchIndexes.push( i ); - } - return matchIndexes; - } ), - - "lt": createPositionalPseudo( function( matchIndexes, length, argument ) { - var i = argument < 0 ? - argument + length : - argument > length ? - length : - argument; - for ( ; --i >= 0; ) { - matchIndexes.push( i ); - } - return matchIndexes; - } ), - - "gt": createPositionalPseudo( function( matchIndexes, length, argument ) { - var i = argument < 0 ? argument + length : argument; - for ( ; ++i < length; ) { - matchIndexes.push( i ); - } - return matchIndexes; - } ) - } -}; - -Expr.pseudos[ "nth" ] = Expr.pseudos[ "eq" ]; - -// Add button/input type pseudos -for ( i in { radio: true, checkbox: true, file: true, password: true, image: true } ) { - Expr.pseudos[ i ] = createInputPseudo( i ); -} -for ( i in { submit: true, reset: true } ) { - Expr.pseudos[ i ] = createButtonPseudo( i ); -} - -// Easy API for creating new setFilters -function setFilters() {} -setFilters.prototype = Expr.filters = Expr.pseudos; -Expr.setFilters = new setFilters(); - -tokenize = Sizzle.tokenize = function( selector, parseOnly ) { - var matched, match, tokens, type, - soFar, groups, preFilters, - cached = tokenCache[ selector + " " ]; - - if ( cached ) { - return parseOnly ? 0 : cached.slice( 0 ); - } - - soFar = selector; - groups = []; - preFilters = Expr.preFilter; - - while ( soFar ) { - - // Comma and first run - if ( !matched || ( match = rcomma.exec( soFar ) ) ) { - if ( match ) { - - // Don't consume trailing commas as valid - soFar = soFar.slice( match[ 0 ].length ) || soFar; - } - groups.push( ( tokens = [] ) ); - } - - matched = false; - - // Combinators - if ( ( match = rcombinators.exec( soFar ) ) ) { - matched = match.shift(); - tokens.push( { - value: matched, - - // Cast descendant combinators to space - type: match[ 0 ].replace( rtrim, " " ) - } ); - soFar = soFar.slice( matched.length ); - } - - // Filters - for ( type in Expr.filter ) { - if ( ( match = matchExpr[ type ].exec( soFar ) ) && ( !preFilters[ type ] || - ( match = preFilters[ type ]( match ) ) ) ) { - matched = match.shift(); - tokens.push( { - value: matched, - type: type, - matches: match - } ); - soFar = soFar.slice( matched.length ); - } - } - - if ( !matched ) { - break; - } - } - - // Return the length of the invalid excess - // if we're just parsing - // Otherwise, throw an error or return tokens - return parseOnly ? - soFar.length : - soFar ? - Sizzle.error( selector ) : - - // Cache the tokens - tokenCache( selector, groups ).slice( 0 ); -}; - -function toSelector( tokens ) { - var i = 0, - len = tokens.length, - selector = ""; - for ( ; i < len; i++ ) { - selector += tokens[ i ].value; - } - return selector; -} - -function addCombinator( matcher, combinator, base ) { - var dir = combinator.dir, - skip = combinator.next, - key = skip || dir, - checkNonElements = base && key === "parentNode", - doneName = done++; - - return combinator.first ? - - // Check against closest ancestor/preceding element - function( elem, context, xml ) { - while ( ( elem = elem[ dir ] ) ) { - if ( elem.nodeType === 1 || checkNonElements ) { - return matcher( elem, context, xml ); - } - } - return false; - } : - - // Check against all ancestor/preceding elements - function( elem, context, xml ) { - var oldCache, uniqueCache, outerCache, - newCache = [ dirruns, doneName ]; - - // We can't set arbitrary data on XML nodes, so they don't benefit from combinator caching - if ( xml ) { - while ( ( elem = elem[ dir ] ) ) { - if ( elem.nodeType === 1 || checkNonElements ) { - if ( matcher( elem, context, xml ) ) { - return true; - } - } - } - } else { - while ( ( elem = elem[ dir ] ) ) { - if ( elem.nodeType === 1 || checkNonElements ) { - outerCache = elem[ expando ] || ( elem[ expando ] = {} ); - - // Support: IE <9 only - // Defend against cloned attroperties (jQuery gh-1709) - uniqueCache = outerCache[ elem.uniqueID ] || - ( outerCache[ elem.uniqueID ] = {} ); - - if ( skip && skip === elem.nodeName.toLowerCase() ) { - elem = elem[ dir ] || elem; - } else if ( ( oldCache = uniqueCache[ key ] ) && - oldCache[ 0 ] === dirruns && oldCache[ 1 ] === doneName ) { - - // Assign to newCache so results back-propagate to previous elements - return ( newCache[ 2 ] = oldCache[ 2 ] ); - } else { - - // Reuse newcache so results back-propagate to previous elements - uniqueCache[ key ] = newCache; - - // A match means we're done; a fail means we have to keep checking - if ( ( newCache[ 2 ] = matcher( elem, context, xml ) ) ) { - return true; - } - } - } - } - } - return false; - }; -} - -function elementMatcher( matchers ) { - return matchers.length > 1 ? - function( elem, context, xml ) { - var i = matchers.length; - while ( i-- ) { - if ( !matchers[ i ]( elem, context, xml ) ) { - return false; - } - } - return true; - } : - matchers[ 0 ]; -} - -function multipleContexts( selector, contexts, results ) { - var i = 0, - len = contexts.length; - for ( ; i < len; i++ ) { - Sizzle( selector, contexts[ i ], results ); - } - return results; -} - -function condense( unmatched, map, filter, context, xml ) { - var elem, - newUnmatched = [], - i = 0, - len = unmatched.length, - mapped = map != null; - - for ( ; i < len; i++ ) { - if ( ( elem = unmatched[ i ] ) ) { - if ( !filter || filter( elem, context, xml ) ) { - newUnmatched.push( elem ); - if ( mapped ) { - map.push( i ); - } - } - } - } - - return newUnmatched; -} - -function setMatcher( preFilter, selector, matcher, postFilter, postFinder, postSelector ) { - if ( postFilter && !postFilter[ expando ] ) { - postFilter = setMatcher( postFilter ); - } - if ( postFinder && !postFinder[ expando ] ) { - postFinder = setMatcher( postFinder, postSelector ); - } - return markFunction( function( seed, results, context, xml ) { - var temp, i, elem, - preMap = [], - postMap = [], - preexisting = results.length, - - // Get initial elements from seed or context - elems = seed || multipleContexts( - selector || "*", - context.nodeType ? [ context ] : context, - [] - ), - - // Prefilter to get matcher input, preserving a map for seed-results synchronization - matcherIn = preFilter && ( seed || !selector ) ? - condense( elems, preMap, preFilter, context, xml ) : - elems, - - matcherOut = matcher ? - - // If we have a postFinder, or filtered seed, or non-seed postFilter or preexisting results, - postFinder || ( seed ? preFilter : preexisting || postFilter ) ? - - // ...intermediate processing is necessary - [] : - - // ...otherwise use results directly - results : - matcherIn; - - // Find primary matches - if ( matcher ) { - matcher( matcherIn, matcherOut, context, xml ); - } - - // Apply postFilter - if ( postFilter ) { - temp = condense( matcherOut, postMap ); - postFilter( temp, [], context, xml ); - - // Un-match failing elements by moving them back to matcherIn - i = temp.length; - while ( i-- ) { - if ( ( elem = temp[ i ] ) ) { - matcherOut[ postMap[ i ] ] = !( matcherIn[ postMap[ i ] ] = elem ); - } - } - } - - if ( seed ) { - if ( postFinder || preFilter ) { - if ( postFinder ) { - - // Get the final matcherOut by condensing this intermediate into postFinder contexts - temp = []; - i = matcherOut.length; - while ( i-- ) { - if ( ( elem = matcherOut[ i ] ) ) { - - // Restore matcherIn since elem is not yet a final match - temp.push( ( matcherIn[ i ] = elem ) ); - } - } - postFinder( null, ( matcherOut = [] ), temp, xml ); - } - - // Move matched elements from seed to results to keep them synchronized - i = matcherOut.length; - while ( i-- ) { - if ( ( elem = matcherOut[ i ] ) && - ( temp = postFinder ? indexOf( seed, elem ) : preMap[ i ] ) > -1 ) { - - seed[ temp ] = !( results[ temp ] = elem ); - } - } - } - - // Add elements to results, through postFinder if defined - } else { - matcherOut = condense( - matcherOut === results ? - matcherOut.splice( preexisting, matcherOut.length ) : - matcherOut - ); - if ( postFinder ) { - postFinder( null, results, matcherOut, xml ); - } else { - push.apply( results, matcherOut ); - } - } - } ); -} - -function matcherFromTokens( tokens ) { - var checkContext, matcher, j, - len = tokens.length, - leadingRelative = Expr.relative[ tokens[ 0 ].type ], - implicitRelative = leadingRelative || Expr.relative[ " " ], - i = leadingRelative ? 1 : 0, - - // The foundational matcher ensures that elements are reachable from top-level context(s) - matchContext = addCombinator( function( elem ) { - return elem === checkContext; - }, implicitRelative, true ), - matchAnyContext = addCombinator( function( elem ) { - return indexOf( checkContext, elem ) > -1; - }, implicitRelative, true ), - matchers = [ function( elem, context, xml ) { - var ret = ( !leadingRelative && ( xml || context !== outermostContext ) ) || ( - ( checkContext = context ).nodeType ? - matchContext( elem, context, xml ) : - matchAnyContext( elem, context, xml ) ); - - // Avoid hanging onto element (issue #299) - checkContext = null; - return ret; - } ]; - - for ( ; i < len; i++ ) { - if ( ( matcher = Expr.relative[ tokens[ i ].type ] ) ) { - matchers = [ addCombinator( elementMatcher( matchers ), matcher ) ]; - } else { - matcher = Expr.filter[ tokens[ i ].type ].apply( null, tokens[ i ].matches ); - - // Return special upon seeing a positional matcher - if ( matcher[ expando ] ) { - - // Find the next relative operator (if any) for proper handling - j = ++i; - for ( ; j < len; j++ ) { - if ( Expr.relative[ tokens[ j ].type ] ) { - break; - } - } - return setMatcher( - i > 1 && elementMatcher( matchers ), - i > 1 && toSelector( - - // If the preceding token was a descendant combinator, insert an implicit any-element `*` - tokens - .slice( 0, i - 1 ) - .concat( { value: tokens[ i - 2 ].type === " " ? "*" : "" } ) - ).replace( rtrim, "$1" ), - matcher, - i < j && matcherFromTokens( tokens.slice( i, j ) ), - j < len && matcherFromTokens( ( tokens = tokens.slice( j ) ) ), - j < len && toSelector( tokens ) - ); - } - matchers.push( matcher ); - } - } - - return elementMatcher( matchers ); -} - -function matcherFromGroupMatchers( elementMatchers, setMatchers ) { - var bySet = setMatchers.length > 0, - byElement = elementMatchers.length > 0, - superMatcher = function( seed, context, xml, results, outermost ) { - var elem, j, matcher, - matchedCount = 0, - i = "0", - unmatched = seed && [], - setMatched = [], - contextBackup = outermostContext, - - // We must always have either seed elements or outermost context - elems = seed || byElement && Expr.find[ "TAG" ]( "*", outermost ), - - // Use integer dirruns iff this is the outermost matcher - dirrunsUnique = ( dirruns += contextBackup == null ? 1 : Math.random() || 0.1 ), - len = elems.length; - - if ( outermost ) { - - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - outermostContext = context == document || context || outermost; - } - - // Add elements passing elementMatchers directly to results - // Support: IE<9, Safari - // Tolerate NodeList properties (IE: "length"; Safari: ) matching elements by id - for ( ; i !== len && ( elem = elems[ i ] ) != null; i++ ) { - if ( byElement && elem ) { - j = 0; - - // Support: IE 11+, Edge 17 - 18+ - // IE/Edge sometimes throw a "Permission denied" error when strict-comparing - // two documents; shallow comparisons work. - // eslint-disable-next-line eqeqeq - if ( !context && elem.ownerDocument != document ) { - setDocument( elem ); - xml = !documentIsHTML; - } - while ( ( matcher = elementMatchers[ j++ ] ) ) { - if ( matcher( elem, context || document, xml ) ) { - results.push( elem ); - break; - } - } - if ( outermost ) { - dirruns = dirrunsUnique; - } - } - - // Track unmatched elements for set filters - if ( bySet ) { - - // They will have gone through all possible matchers - if ( ( elem = !matcher && elem ) ) { - matchedCount--; - } - - // Lengthen the array for every element, matched or not - if ( seed ) { - unmatched.push( elem ); - } - } - } - - // `i` is now the count of elements visited above, and adding it to `matchedCount` - // makes the latter nonnegative. - matchedCount += i; - - // Apply set filters to unmatched elements - // NOTE: This can be skipped if there are no unmatched elements (i.e., `matchedCount` - // equals `i`), unless we didn't visit _any_ elements in the above loop because we have - // no element matchers and no seed. - // Incrementing an initially-string "0" `i` allows `i` to remain a string only in that - // case, which will result in a "00" `matchedCount` that differs from `i` but is also - // numerically zero. - if ( bySet && i !== matchedCount ) { - j = 0; - while ( ( matcher = setMatchers[ j++ ] ) ) { - matcher( unmatched, setMatched, context, xml ); - } - - if ( seed ) { - - // Reintegrate element matches to eliminate the need for sorting - if ( matchedCount > 0 ) { - while ( i-- ) { - if ( !( unmatched[ i ] || setMatched[ i ] ) ) { - setMatched[ i ] = pop.call( results ); - } - } - } - - // Discard index placeholder values to get only actual matches - setMatched = condense( setMatched ); - } - - // Add matches to results - push.apply( results, setMatched ); - - // Seedless set matches succeeding multiple successful matchers stipulate sorting - if ( outermost && !seed && setMatched.length > 0 && - ( matchedCount + setMatchers.length ) > 1 ) { - - Sizzle.uniqueSort( results ); - } - } - - // Override manipulation of globals by nested matchers - if ( outermost ) { - dirruns = dirrunsUnique; - outermostContext = contextBackup; - } - - return unmatched; - }; - - return bySet ? - markFunction( superMatcher ) : - superMatcher; -} - -compile = Sizzle.compile = function( selector, match /* Internal Use Only */ ) { - var i, - setMatchers = [], - elementMatchers = [], - cached = compilerCache[ selector + " " ]; - - if ( !cached ) { - - // Generate a function of recursive functions that can be used to check each element - if ( !match ) { - match = tokenize( selector ); - } - i = match.length; - while ( i-- ) { - cached = matcherFromTokens( match[ i ] ); - if ( cached[ expando ] ) { - setMatchers.push( cached ); - } else { - elementMatchers.push( cached ); - } - } - - // Cache the compiled function - cached = compilerCache( - selector, - matcherFromGroupMatchers( elementMatchers, setMatchers ) - ); - - // Save selector and tokenization - cached.selector = selector; - } - return cached; -}; - -/** - * A low-level selection function that works with Sizzle's compiled - * selector functions - * @param {String|Function} selector A selector or a pre-compiled - * selector function built with Sizzle.compile - * @param {Element} context - * @param {Array} [results] - * @param {Array} [seed] A set of elements to match against - */ -select = Sizzle.select = function( selector, context, results, seed ) { - var i, tokens, token, type, find, - compiled = typeof selector === "function" && selector, - match = !seed && tokenize( ( selector = compiled.selector || selector ) ); - - results = results || []; - - // Try to minimize operations if there is only one selector in the list and no seed - // (the latter of which guarantees us context) - if ( match.length === 1 ) { - - // Reduce context if the leading compound selector is an ID - tokens = match[ 0 ] = match[ 0 ].slice( 0 ); - if ( tokens.length > 2 && ( token = tokens[ 0 ] ).type === "ID" && - context.nodeType === 9 && documentIsHTML && Expr.relative[ tokens[ 1 ].type ] ) { - - context = ( Expr.find[ "ID" ]( token.matches[ 0 ] - .replace( runescape, funescape ), context ) || [] )[ 0 ]; - if ( !context ) { - return results; - - // Precompiled matchers will still verify ancestry, so step up a level - } else if ( compiled ) { - context = context.parentNode; - } - - selector = selector.slice( tokens.shift().value.length ); - } - - // Fetch a seed set for right-to-left matching - i = matchExpr[ "needsContext" ].test( selector ) ? 0 : tokens.length; - while ( i-- ) { - token = tokens[ i ]; - - // Abort if we hit a combinator - if ( Expr.relative[ ( type = token.type ) ] ) { - break; - } - if ( ( find = Expr.find[ type ] ) ) { - - // Search, expanding context for leading sibling combinators - if ( ( seed = find( - token.matches[ 0 ].replace( runescape, funescape ), - rsibling.test( tokens[ 0 ].type ) && testContext( context.parentNode ) || - context - ) ) ) { - - // If seed is empty or no tokens remain, we can return early - tokens.splice( i, 1 ); - selector = seed.length && toSelector( tokens ); - if ( !selector ) { - push.apply( results, seed ); - return results; - } - - break; - } - } - } - } - - // Compile and execute a filtering function if one is not provided - // Provide `match` to avoid retokenization if we modified the selector above - ( compiled || compile( selector, match ) )( - seed, - context, - !documentIsHTML, - results, - !context || rsibling.test( selector ) && testContext( context.parentNode ) || context - ); - return results; -}; - -// One-time assignments - -// Sort stability -support.sortStable = expando.split( "" ).sort( sortOrder ).join( "" ) === expando; - -// Support: Chrome 14-35+ -// Always assume duplicates if they aren't passed to the comparison function -support.detectDuplicates = !!hasDuplicate; - -// Initialize against the default document -setDocument(); - -// Support: Webkit<537.32 - Safari 6.0.3/Chrome 25 (fixed in Chrome 27) -// Detached nodes confoundingly follow *each other* -support.sortDetached = assert( function( el ) { - - // Should return 1, but returns 4 (following) - return el.compareDocumentPosition( document.createElement( "fieldset" ) ) & 1; -} ); - -// Support: IE<8 -// Prevent attribute/property "interpolation" -// https://msdn.microsoft.com/en-us/library/ms536429%28VS.85%29.aspx -if ( !assert( function( el ) { - el.innerHTML = ""; - return el.firstChild.getAttribute( "href" ) === "#"; -} ) ) { - addHandle( "type|href|height|width", function( elem, name, isXML ) { - if ( !isXML ) { - return elem.getAttribute( name, name.toLowerCase() === "type" ? 1 : 2 ); - } - } ); -} - -// Support: IE<9 -// Use defaultValue in place of getAttribute("value") -if ( !support.attributes || !assert( function( el ) { - el.innerHTML = ""; - el.firstChild.setAttribute( "value", "" ); - return el.firstChild.getAttribute( "value" ) === ""; -} ) ) { - addHandle( "value", function( elem, _name, isXML ) { - if ( !isXML && elem.nodeName.toLowerCase() === "input" ) { - return elem.defaultValue; - } - } ); -} - -// Support: IE<9 -// Use getAttributeNode to fetch booleans when getAttribute lies -if ( !assert( function( el ) { - return el.getAttribute( "disabled" ) == null; -} ) ) { - addHandle( booleans, function( elem, name, isXML ) { - var val; - if ( !isXML ) { - return elem[ name ] === true ? name.toLowerCase() : - ( val = elem.getAttributeNode( name ) ) && val.specified ? - val.value : - null; - } - } ); -} - -return Sizzle; - -} )( window ); - - - -jQuery.find = Sizzle; -jQuery.expr = Sizzle.selectors; - -// Deprecated -jQuery.expr[ ":" ] = jQuery.expr.pseudos; -jQuery.uniqueSort = jQuery.unique = Sizzle.uniqueSort; -jQuery.text = Sizzle.getText; -jQuery.isXMLDoc = Sizzle.isXML; -jQuery.contains = Sizzle.contains; -jQuery.escapeSelector = Sizzle.escape; - - - - -var dir = function( elem, dir, until ) { - var matched = [], - truncate = until !== undefined; - - while ( ( elem = elem[ dir ] ) && elem.nodeType !== 9 ) { - if ( elem.nodeType === 1 ) { - if ( truncate && jQuery( elem ).is( until ) ) { - break; - } - matched.push( elem ); - } - } - return matched; -}; - - -var siblings = function( n, elem ) { - var matched = []; - - for ( ; n; n = n.nextSibling ) { - if ( n.nodeType === 1 && n !== elem ) { - matched.push( n ); - } - } - - return matched; -}; - - -var rneedsContext = jQuery.expr.match.needsContext; - - - -function nodeName( elem, name ) { - - return elem.nodeName && elem.nodeName.toLowerCase() === name.toLowerCase(); - -} -var rsingleTag = ( /^<([a-z][^\/\0>:\x20\t\r\n\f]*)[\x20\t\r\n\f]*\/?>(?:<\/\1>|)$/i ); - - - -// Implement the identical functionality for filter and not -function winnow( elements, qualifier, not ) { - if ( isFunction( qualifier ) ) { - return jQuery.grep( elements, function( elem, i ) { - return !!qualifier.call( elem, i, elem ) !== not; - } ); - } - - // Single element - if ( qualifier.nodeType ) { - return jQuery.grep( elements, function( elem ) { - return ( elem === qualifier ) !== not; - } ); - } - - // Arraylike of elements (jQuery, arguments, Array) - if ( typeof qualifier !== "string" ) { - return jQuery.grep( elements, function( elem ) { - return ( indexOf.call( qualifier, elem ) > -1 ) !== not; - } ); - } - - // Filtered directly for both simple and complex selectors - return jQuery.filter( qualifier, elements, not ); -} - -jQuery.filter = function( expr, elems, not ) { - var elem = elems[ 0 ]; - - if ( not ) { - expr = ":not(" + expr + ")"; - } - - if ( elems.length === 1 && elem.nodeType === 1 ) { - return jQuery.find.matchesSelector( elem, expr ) ? [ elem ] : []; - } - - return jQuery.find.matches( expr, jQuery.grep( elems, function( elem ) { - return elem.nodeType === 1; - } ) ); -}; - -jQuery.fn.extend( { - find: function( selector ) { - var i, ret, - len = this.length, - self = this; - - if ( typeof selector !== "string" ) { - return this.pushStack( jQuery( selector ).filter( function() { - for ( i = 0; i < len; i++ ) { - if ( jQuery.contains( self[ i ], this ) ) { - return true; - } - } - } ) ); - } - - ret = this.pushStack( [] ); - - for ( i = 0; i < len; i++ ) { - jQuery.find( selector, self[ i ], ret ); - } - - return len > 1 ? jQuery.uniqueSort( ret ) : ret; - }, - filter: function( selector ) { - return this.pushStack( winnow( this, selector || [], false ) ); - }, - not: function( selector ) { - return this.pushStack( winnow( this, selector || [], true ) ); - }, - is: function( selector ) { - return !!winnow( - this, - - // If this is a positional/relative selector, check membership in the returned set - // so $("p:first").is("p:last") won't return true for a doc with two "p". - typeof selector === "string" && rneedsContext.test( selector ) ? - jQuery( selector ) : - selector || [], - false - ).length; - } -} ); - - -// Initialize a jQuery object - - -// A central reference to the root jQuery(document) -var rootjQuery, - - // A simple way to check for HTML strings - // Prioritize #id over to avoid XSS via location.hash (#9521) - // Strict HTML recognition (#11290: must start with <) - // Shortcut simple #id case for speed - rquickExpr = /^(?:\s*(<[\w\W]+>)[^>]*|#([\w-]+))$/, - - init = jQuery.fn.init = function( selector, context, root ) { - var match, elem; - - // HANDLE: $(""), $(null), $(undefined), $(false) - if ( !selector ) { - return this; - } - - // Method init() accepts an alternate rootjQuery - // so migrate can support jQuery.sub (gh-2101) - root = root || rootjQuery; - - // Handle HTML strings - if ( typeof selector === "string" ) { - if ( selector[ 0 ] === "<" && - selector[ selector.length - 1 ] === ">" && - selector.length >= 3 ) { - - // Assume that strings that start and end with <> are HTML and skip the regex check - match = [ null, selector, null ]; - - } else { - match = rquickExpr.exec( selector ); - } - - // Match html or make sure no context is specified for #id - if ( match && ( match[ 1 ] || !context ) ) { - - // HANDLE: $(html) -> $(array) - if ( match[ 1 ] ) { - context = context instanceof jQuery ? context[ 0 ] : context; - - // Option to run scripts is true for back-compat - // Intentionally let the error be thrown if parseHTML is not present - jQuery.merge( this, jQuery.parseHTML( - match[ 1 ], - context && context.nodeType ? context.ownerDocument || context : document, - true - ) ); - - // HANDLE: $(html, props) - if ( rsingleTag.test( match[ 1 ] ) && jQuery.isPlainObject( context ) ) { - for ( match in context ) { - - // Properties of context are called as methods if possible - if ( isFunction( this[ match ] ) ) { - this[ match ]( context[ match ] ); - - // ...and otherwise set as attributes - } else { - this.attr( match, context[ match ] ); - } - } - } - - return this; - - // HANDLE: $(#id) - } else { - elem = document.getElementById( match[ 2 ] ); - - if ( elem ) { - - // Inject the element directly into the jQuery object - this[ 0 ] = elem; - this.length = 1; - } - return this; - } - - // HANDLE: $(expr, $(...)) - } else if ( !context || context.jquery ) { - return ( context || root ).find( selector ); - - // HANDLE: $(expr, context) - // (which is just equivalent to: $(context).find(expr) - } else { - return this.constructor( context ).find( selector ); - } - - // HANDLE: $(DOMElement) - } else if ( selector.nodeType ) { - this[ 0 ] = selector; - this.length = 1; - return this; - - // HANDLE: $(function) - // Shortcut for document ready - } else if ( isFunction( selector ) ) { - return root.ready !== undefined ? - root.ready( selector ) : - - // Execute immediately if ready is not present - selector( jQuery ); - } - - return jQuery.makeArray( selector, this ); - }; - -// Give the init function the jQuery prototype for later instantiation -init.prototype = jQuery.fn; - -// Initialize central reference -rootjQuery = jQuery( document ); - - -var rparentsprev = /^(?:parents|prev(?:Until|All))/, - - // Methods guaranteed to produce a unique set when starting from a unique set - guaranteedUnique = { - children: true, - contents: true, - next: true, - prev: true - }; - -jQuery.fn.extend( { - has: function( target ) { - var targets = jQuery( target, this ), - l = targets.length; - - return this.filter( function() { - var i = 0; - for ( ; i < l; i++ ) { - if ( jQuery.contains( this, targets[ i ] ) ) { - return true; - } - } - } ); - }, - - closest: function( selectors, context ) { - var cur, - i = 0, - l = this.length, - matched = [], - targets = typeof selectors !== "string" && jQuery( selectors ); - - // Positional selectors never match, since there's no _selection_ context - if ( !rneedsContext.test( selectors ) ) { - for ( ; i < l; i++ ) { - for ( cur = this[ i ]; cur && cur !== context; cur = cur.parentNode ) { - - // Always skip document fragments - if ( cur.nodeType < 11 && ( targets ? - targets.index( cur ) > -1 : - - // Don't pass non-elements to Sizzle - cur.nodeType === 1 && - jQuery.find.matchesSelector( cur, selectors ) ) ) { - - matched.push( cur ); - break; - } - } - } - } - - return this.pushStack( matched.length > 1 ? jQuery.uniqueSort( matched ) : matched ); - }, - - // Determine the position of an element within the set - index: function( elem ) { - - // No argument, return index in parent - if ( !elem ) { - return ( this[ 0 ] && this[ 0 ].parentNode ) ? this.first().prevAll().length : -1; - } - - // Index in selector - if ( typeof elem === "string" ) { - return indexOf.call( jQuery( elem ), this[ 0 ] ); - } - - // Locate the position of the desired element - return indexOf.call( this, - - // If it receives a jQuery object, the first element is used - elem.jquery ? elem[ 0 ] : elem - ); - }, - - add: function( selector, context ) { - return this.pushStack( - jQuery.uniqueSort( - jQuery.merge( this.get(), jQuery( selector, context ) ) - ) - ); - }, - - addBack: function( selector ) { - return this.add( selector == null ? - this.prevObject : this.prevObject.filter( selector ) - ); - } -} ); - -function sibling( cur, dir ) { - while ( ( cur = cur[ dir ] ) && cur.nodeType !== 1 ) {} - return cur; -} - -jQuery.each( { - parent: function( elem ) { - var parent = elem.parentNode; - return parent && parent.nodeType !== 11 ? parent : null; - }, - parents: function( elem ) { - return dir( elem, "parentNode" ); - }, - parentsUntil: function( elem, _i, until ) { - return dir( elem, "parentNode", until ); - }, - next: function( elem ) { - return sibling( elem, "nextSibling" ); - }, - prev: function( elem ) { - return sibling( elem, "previousSibling" ); - }, - nextAll: function( elem ) { - return dir( elem, "nextSibling" ); - }, - prevAll: function( elem ) { - return dir( elem, "previousSibling" ); - }, - nextUntil: function( elem, _i, until ) { - return dir( elem, "nextSibling", until ); - }, - prevUntil: function( elem, _i, until ) { - return dir( elem, "previousSibling", until ); - }, - siblings: function( elem ) { - return siblings( ( elem.parentNode || {} ).firstChild, elem ); - }, - children: function( elem ) { - return siblings( elem.firstChild ); - }, - contents: function( elem ) { - if ( elem.contentDocument != null && - - // Support: IE 11+ - // elements with no `data` attribute has an object - // `contentDocument` with a `null` prototype. - getProto( elem.contentDocument ) ) { - - return elem.contentDocument; - } - - // Support: IE 9 - 11 only, iOS 7 only, Android Browser <=4.3 only - // Treat the template element as a regular one in browsers that - // don't support it. - if ( nodeName( elem, "template" ) ) { - elem = elem.content || elem; - } - - return jQuery.merge( [], elem.childNodes ); - } -}, function( name, fn ) { - jQuery.fn[ name ] = function( until, selector ) { - var matched = jQuery.map( this, fn, until ); - - if ( name.slice( -5 ) !== "Until" ) { - selector = until; - } - - if ( selector && typeof selector === "string" ) { - matched = jQuery.filter( selector, matched ); - } - - if ( this.length > 1 ) { - - // Remove duplicates - if ( !guaranteedUnique[ name ] ) { - jQuery.uniqueSort( matched ); - } - - // Reverse order for parents* and prev-derivatives - if ( rparentsprev.test( name ) ) { - matched.reverse(); - } - } - - return this.pushStack( matched ); - }; -} ); -var rnothtmlwhite = ( /[^\x20\t\r\n\f]+/g ); - - - -// Convert String-formatted options into Object-formatted ones -function createOptions( options ) { - var object = {}; - jQuery.each( options.match( rnothtmlwhite ) || [], function( _, flag ) { - object[ flag ] = true; - } ); - return object; -} - -/* - * Create a callback list using the following parameters: - * - * options: an optional list of space-separated options that will change how - * the callback list behaves or a more traditional option object - * - * By default a callback list will act like an event callback list and can be - * "fired" multiple times. - * - * Possible options: - * - * once: will ensure the callback list can only be fired once (like a Deferred) - * - * memory: will keep track of previous values and will call any callback added - * after the list has been fired right away with the latest "memorized" - * values (like a Deferred) - * - * unique: will ensure a callback can only be added once (no duplicate in the list) - * - * stopOnFalse: interrupt callings when a callback returns false - * - */ -jQuery.Callbacks = function( options ) { - - // Convert options from String-formatted to Object-formatted if needed - // (we check in cache first) - options = typeof options === "string" ? - createOptions( options ) : - jQuery.extend( {}, options ); - - var // Flag to know if list is currently firing - firing, - - // Last fire value for non-forgettable lists - memory, - - // Flag to know if list was already fired - fired, - - // Flag to prevent firing - locked, - - // Actual callback list - list = [], - - // Queue of execution data for repeatable lists - queue = [], - - // Index of currently firing callback (modified by add/remove as needed) - firingIndex = -1, - - // Fire callbacks - fire = function() { - - // Enforce single-firing - locked = locked || options.once; - - // Execute callbacks for all pending executions, - // respecting firingIndex overrides and runtime changes - fired = firing = true; - for ( ; queue.length; firingIndex = -1 ) { - memory = queue.shift(); - while ( ++firingIndex < list.length ) { - - // Run callback and check for early termination - if ( list[ firingIndex ].apply( memory[ 0 ], memory[ 1 ] ) === false && - options.stopOnFalse ) { - - // Jump to end and forget the data so .add doesn't re-fire - firingIndex = list.length; - memory = false; - } - } - } - - // Forget the data if we're done with it - if ( !options.memory ) { - memory = false; - } - - firing = false; - - // Clean up if we're done firing for good - if ( locked ) { - - // Keep an empty list if we have data for future add calls - if ( memory ) { - list = []; - - // Otherwise, this object is spent - } else { - list = ""; - } - } - }, - - // Actual Callbacks object - self = { - - // Add a callback or a collection of callbacks to the list - add: function() { - if ( list ) { - - // If we have memory from a past run, we should fire after adding - if ( memory && !firing ) { - firingIndex = list.length - 1; - queue.push( memory ); - } - - ( function add( args ) { - jQuery.each( args, function( _, arg ) { - if ( isFunction( arg ) ) { - if ( !options.unique || !self.has( arg ) ) { - list.push( arg ); - } - } else if ( arg && arg.length && toType( arg ) !== "string" ) { - - // Inspect recursively - add( arg ); - } - } ); - } )( arguments ); - - if ( memory && !firing ) { - fire(); - } - } - return this; - }, - - // Remove a callback from the list - remove: function() { - jQuery.each( arguments, function( _, arg ) { - var index; - while ( ( index = jQuery.inArray( arg, list, index ) ) > -1 ) { - list.splice( index, 1 ); - - // Handle firing indexes - if ( index <= firingIndex ) { - firingIndex--; - } - } - } ); - return this; - }, - - // Check if a given callback is in the list. - // If no argument is given, return whether or not list has callbacks attached. - has: function( fn ) { - return fn ? - jQuery.inArray( fn, list ) > -1 : - list.length > 0; - }, - - // Remove all callbacks from the list - empty: function() { - if ( list ) { - list = []; - } - return this; - }, - - // Disable .fire and .add - // Abort any current/pending executions - // Clear all callbacks and values - disable: function() { - locked = queue = []; - list = memory = ""; - return this; - }, - disabled: function() { - return !list; - }, - - // Disable .fire - // Also disable .add unless we have memory (since it would have no effect) - // Abort any pending executions - lock: function() { - locked = queue = []; - if ( !memory && !firing ) { - list = memory = ""; - } - return this; - }, - locked: function() { - return !!locked; - }, - - // Call all callbacks with the given context and arguments - fireWith: function( context, args ) { - if ( !locked ) { - args = args || []; - args = [ context, args.slice ? args.slice() : args ]; - queue.push( args ); - if ( !firing ) { - fire(); - } - } - return this; - }, - - // Call all the callbacks with the given arguments - fire: function() { - self.fireWith( this, arguments ); - return this; - }, - - // To know if the callbacks have already been called at least once - fired: function() { - return !!fired; - } - }; - - return self; -}; - - -function Identity( v ) { - return v; -} -function Thrower( ex ) { - throw ex; -} - -function adoptValue( value, resolve, reject, noValue ) { - var method; - - try { - - // Check for promise aspect first to privilege synchronous behavior - if ( value && isFunction( ( method = value.promise ) ) ) { - method.call( value ).done( resolve ).fail( reject ); - - // Other thenables - } else if ( value && isFunction( ( method = value.then ) ) ) { - method.call( value, resolve, reject ); - - // Other non-thenables - } else { - - // Control `resolve` arguments by letting Array#slice cast boolean `noValue` to integer: - // * false: [ value ].slice( 0 ) => resolve( value ) - // * true: [ value ].slice( 1 ) => resolve() - resolve.apply( undefined, [ value ].slice( noValue ) ); - } - - // For Promises/A+, convert exceptions into rejections - // Since jQuery.when doesn't unwrap thenables, we can skip the extra checks appearing in - // Deferred#then to conditionally suppress rejection. - } catch ( value ) { - - // Support: Android 4.0 only - // Strict mode functions invoked without .call/.apply get global-object context - reject.apply( undefined, [ value ] ); - } -} - -jQuery.extend( { - - Deferred: function( func ) { - var tuples = [ - - // action, add listener, callbacks, - // ... .then handlers, argument index, [final state] - [ "notify", "progress", jQuery.Callbacks( "memory" ), - jQuery.Callbacks( "memory" ), 2 ], - [ "resolve", "done", jQuery.Callbacks( "once memory" ), - jQuery.Callbacks( "once memory" ), 0, "resolved" ], - [ "reject", "fail", jQuery.Callbacks( "once memory" ), - jQuery.Callbacks( "once memory" ), 1, "rejected" ] - ], - state = "pending", - promise = { - state: function() { - return state; - }, - always: function() { - deferred.done( arguments ).fail( arguments ); - return this; - }, - "catch": function( fn ) { - return promise.then( null, fn ); - }, - - // Keep pipe for back-compat - pipe: function( /* fnDone, fnFail, fnProgress */ ) { - var fns = arguments; - - return jQuery.Deferred( function( newDefer ) { - jQuery.each( tuples, function( _i, tuple ) { - - // Map tuples (progress, done, fail) to arguments (done, fail, progress) - var fn = isFunction( fns[ tuple[ 4 ] ] ) && fns[ tuple[ 4 ] ]; - - // deferred.progress(function() { bind to newDefer or newDefer.notify }) - // deferred.done(function() { bind to newDefer or newDefer.resolve }) - // deferred.fail(function() { bind to newDefer or newDefer.reject }) - deferred[ tuple[ 1 ] ]( function() { - var returned = fn && fn.apply( this, arguments ); - if ( returned && isFunction( returned.promise ) ) { - returned.promise() - .progress( newDefer.notify ) - .done( newDefer.resolve ) - .fail( newDefer.reject ); - } else { - newDefer[ tuple[ 0 ] + "With" ]( - this, - fn ? [ returned ] : arguments - ); - } - } ); - } ); - fns = null; - } ).promise(); - }, - then: function( onFulfilled, onRejected, onProgress ) { - var maxDepth = 0; - function resolve( depth, deferred, handler, special ) { - return function() { - var that = this, - args = arguments, - mightThrow = function() { - var returned, then; - - // Support: Promises/A+ section 2.3.3.3.3 - // https://promisesaplus.com/#point-59 - // Ignore double-resolution attempts - if ( depth < maxDepth ) { - return; - } - - returned = handler.apply( that, args ); - - // Support: Promises/A+ section 2.3.1 - // https://promisesaplus.com/#point-48 - if ( returned === deferred.promise() ) { - throw new TypeError( "Thenable self-resolution" ); - } - - // Support: Promises/A+ sections 2.3.3.1, 3.5 - // https://promisesaplus.com/#point-54 - // https://promisesaplus.com/#point-75 - // Retrieve `then` only once - then = returned && - - // Support: Promises/A+ section 2.3.4 - // https://promisesaplus.com/#point-64 - // Only check objects and functions for thenability - ( typeof returned === "object" || - typeof returned === "function" ) && - returned.then; - - // Handle a returned thenable - if ( isFunction( then ) ) { - - // Special processors (notify) just wait for resolution - if ( special ) { - then.call( - returned, - resolve( maxDepth, deferred, Identity, special ), - resolve( maxDepth, deferred, Thrower, special ) - ); - - // Normal processors (resolve) also hook into progress - } else { - - // ...and disregard older resolution values - maxDepth++; - - then.call( - returned, - resolve( maxDepth, deferred, Identity, special ), - resolve( maxDepth, deferred, Thrower, special ), - resolve( maxDepth, deferred, Identity, - deferred.notifyWith ) - ); - } - - // Handle all other returned values - } else { - - // Only substitute handlers pass on context - // and multiple values (non-spec behavior) - if ( handler !== Identity ) { - that = undefined; - args = [ returned ]; - } - - // Process the value(s) - // Default process is resolve - ( special || deferred.resolveWith )( that, args ); - } - }, - - // Only normal processors (resolve) catch and reject exceptions - process = special ? - mightThrow : - function() { - try { - mightThrow(); - } catch ( e ) { - - if ( jQuery.Deferred.exceptionHook ) { - jQuery.Deferred.exceptionHook( e, - process.stackTrace ); - } - - // Support: Promises/A+ section 2.3.3.3.4.1 - // https://promisesaplus.com/#point-61 - // Ignore post-resolution exceptions - if ( depth + 1 >= maxDepth ) { - - // Only substitute handlers pass on context - // and multiple values (non-spec behavior) - if ( handler !== Thrower ) { - that = undefined; - args = [ e ]; - } - - deferred.rejectWith( that, args ); - } - } - }; - - // Support: Promises/A+ section 2.3.3.3.1 - // https://promisesaplus.com/#point-57 - // Re-resolve promises immediately to dodge false rejection from - // subsequent errors - if ( depth ) { - process(); - } else { - - // Call an optional hook to record the stack, in case of exception - // since it's otherwise lost when execution goes async - if ( jQuery.Deferred.getStackHook ) { - process.stackTrace = jQuery.Deferred.getStackHook(); - } - window.setTimeout( process ); - } - }; - } - - return jQuery.Deferred( function( newDefer ) { - - // progress_handlers.add( ... ) - tuples[ 0 ][ 3 ].add( - resolve( - 0, - newDefer, - isFunction( onProgress ) ? - onProgress : - Identity, - newDefer.notifyWith - ) - ); - - // fulfilled_handlers.add( ... ) - tuples[ 1 ][ 3 ].add( - resolve( - 0, - newDefer, - isFunction( onFulfilled ) ? - onFulfilled : - Identity - ) - ); - - // rejected_handlers.add( ... ) - tuples[ 2 ][ 3 ].add( - resolve( - 0, - newDefer, - isFunction( onRejected ) ? - onRejected : - Thrower - ) - ); - } ).promise(); - }, - - // Get a promise for this deferred - // If obj is provided, the promise aspect is added to the object - promise: function( obj ) { - return obj != null ? jQuery.extend( obj, promise ) : promise; - } - }, - deferred = {}; - - // Add list-specific methods - jQuery.each( tuples, function( i, tuple ) { - var list = tuple[ 2 ], - stateString = tuple[ 5 ]; - - // promise.progress = list.add - // promise.done = list.add - // promise.fail = list.add - promise[ tuple[ 1 ] ] = list.add; - - // Handle state - if ( stateString ) { - list.add( - function() { - - // state = "resolved" (i.e., fulfilled) - // state = "rejected" - state = stateString; - }, - - // rejected_callbacks.disable - // fulfilled_callbacks.disable - tuples[ 3 - i ][ 2 ].disable, - - // rejected_handlers.disable - // fulfilled_handlers.disable - tuples[ 3 - i ][ 3 ].disable, - - // progress_callbacks.lock - tuples[ 0 ][ 2 ].lock, - - // progress_handlers.lock - tuples[ 0 ][ 3 ].lock - ); - } - - // progress_handlers.fire - // fulfilled_handlers.fire - // rejected_handlers.fire - list.add( tuple[ 3 ].fire ); - - // deferred.notify = function() { deferred.notifyWith(...) } - // deferred.resolve = function() { deferred.resolveWith(...) } - // deferred.reject = function() { deferred.rejectWith(...) } - deferred[ tuple[ 0 ] ] = function() { - deferred[ tuple[ 0 ] + "With" ]( this === deferred ? undefined : this, arguments ); - return this; - }; - - // deferred.notifyWith = list.fireWith - // deferred.resolveWith = list.fireWith - // deferred.rejectWith = list.fireWith - deferred[ tuple[ 0 ] + "With" ] = list.fireWith; - } ); - - // Make the deferred a promise - promise.promise( deferred ); - - // Call given func if any - if ( func ) { - func.call( deferred, deferred ); - } - - // All done! - return deferred; - }, - - // Deferred helper - when: function( singleValue ) { - var - - // count of uncompleted subordinates - remaining = arguments.length, - - // count of unprocessed arguments - i = remaining, - - // subordinate fulfillment data - resolveContexts = Array( i ), - resolveValues = slice.call( arguments ), - - // the primary Deferred - primary = jQuery.Deferred(), - - // subordinate callback factory - updateFunc = function( i ) { - return function( value ) { - resolveContexts[ i ] = this; - resolveValues[ i ] = arguments.length > 1 ? slice.call( arguments ) : value; - if ( !( --remaining ) ) { - primary.resolveWith( resolveContexts, resolveValues ); - } - }; - }; - - // Single- and empty arguments are adopted like Promise.resolve - if ( remaining <= 1 ) { - adoptValue( singleValue, primary.done( updateFunc( i ) ).resolve, primary.reject, - !remaining ); - - // Use .then() to unwrap secondary thenables (cf. gh-3000) - if ( primary.state() === "pending" || - isFunction( resolveValues[ i ] && resolveValues[ i ].then ) ) { - - return primary.then(); - } - } - - // Multiple arguments are aggregated like Promise.all array elements - while ( i-- ) { - adoptValue( resolveValues[ i ], updateFunc( i ), primary.reject ); - } - - return primary.promise(); - } -} ); - - -// These usually indicate a programmer mistake during development, -// warn about them ASAP rather than swallowing them by default. -var rerrorNames = /^(Eval|Internal|Range|Reference|Syntax|Type|URI)Error$/; - -jQuery.Deferred.exceptionHook = function( error, stack ) { - - // Support: IE 8 - 9 only - // Console exists when dev tools are open, which can happen at any time - if ( window.console && window.console.warn && error && rerrorNames.test( error.name ) ) { - window.console.warn( "jQuery.Deferred exception: " + error.message, error.stack, stack ); - } -}; - - - - -jQuery.readyException = function( error ) { - window.setTimeout( function() { - throw error; - } ); -}; - - - - -// The deferred used on DOM ready -var readyList = jQuery.Deferred(); - -jQuery.fn.ready = function( fn ) { - - readyList - .then( fn ) - - // Wrap jQuery.readyException in a function so that the lookup - // happens at the time of error handling instead of callback - // registration. - .catch( function( error ) { - jQuery.readyException( error ); - } ); - - return this; -}; - -jQuery.extend( { - - // Is the DOM ready to be used? Set to true once it occurs. - isReady: false, - - // A counter to track how many items to wait for before - // the ready event fires. See #6781 - readyWait: 1, - - // Handle when the DOM is ready - ready: function( wait ) { - - // Abort if there are pending holds or we're already ready - if ( wait === true ? --jQuery.readyWait : jQuery.isReady ) { - return; - } - - // Remember that the DOM is ready - jQuery.isReady = true; - - // If a normal DOM Ready event fired, decrement, and wait if need be - if ( wait !== true && --jQuery.readyWait > 0 ) { - return; - } - - // If there are functions bound, to execute - readyList.resolveWith( document, [ jQuery ] ); - } -} ); - -jQuery.ready.then = readyList.then; - -// The ready event handler and self cleanup method -function completed() { - document.removeEventListener( "DOMContentLoaded", completed ); - window.removeEventListener( "load", completed ); - jQuery.ready(); -} - -// Catch cases where $(document).ready() is called -// after the browser event has already occurred. -// Support: IE <=9 - 10 only -// Older IE sometimes signals "interactive" too soon -if ( document.readyState === "complete" || - ( document.readyState !== "loading" && !document.documentElement.doScroll ) ) { - - // Handle it asynchronously to allow scripts the opportunity to delay ready - window.setTimeout( jQuery.ready ); - -} else { - - // Use the handy event callback - document.addEventListener( "DOMContentLoaded", completed ); - - // A fallback to window.onload, that will always work - window.addEventListener( "load", completed ); -} - - - - -// Multifunctional method to get and set values of a collection -// The value/s can optionally be executed if it's a function -var access = function( elems, fn, key, value, chainable, emptyGet, raw ) { - var i = 0, - len = elems.length, - bulk = key == null; - - // Sets many values - if ( toType( key ) === "object" ) { - chainable = true; - for ( i in key ) { - access( elems, fn, i, key[ i ], true, emptyGet, raw ); - } - - // Sets one value - } else if ( value !== undefined ) { - chainable = true; - - if ( !isFunction( value ) ) { - raw = true; - } - - if ( bulk ) { - - // Bulk operations run against the entire set - if ( raw ) { - fn.call( elems, value ); - fn = null; - - // ...except when executing function values - } else { - bulk = fn; - fn = function( elem, _key, value ) { - return bulk.call( jQuery( elem ), value ); - }; - } - } - - if ( fn ) { - for ( ; i < len; i++ ) { - fn( - elems[ i ], key, raw ? - value : - value.call( elems[ i ], i, fn( elems[ i ], key ) ) - ); - } - } - } - - if ( chainable ) { - return elems; - } - - // Gets - if ( bulk ) { - return fn.call( elems ); - } - - return len ? fn( elems[ 0 ], key ) : emptyGet; -}; - - -// Matches dashed string for camelizing -var rmsPrefix = /^-ms-/, - rdashAlpha = /-([a-z])/g; - -// Used by camelCase as callback to replace() -function fcamelCase( _all, letter ) { - return letter.toUpperCase(); -} - -// Convert dashed to camelCase; used by the css and data modules -// Support: IE <=9 - 11, Edge 12 - 15 -// Microsoft forgot to hump their vendor prefix (#9572) -function camelCase( string ) { - return string.replace( rmsPrefix, "ms-" ).replace( rdashAlpha, fcamelCase ); -} -var acceptData = function( owner ) { - - // Accepts only: - // - Node - // - Node.ELEMENT_NODE - // - Node.DOCUMENT_NODE - // - Object - // - Any - return owner.nodeType === 1 || owner.nodeType === 9 || !( +owner.nodeType ); -}; - - - - -function Data() { - this.expando = jQuery.expando + Data.uid++; -} - -Data.uid = 1; - -Data.prototype = { - - cache: function( owner ) { - - // Check if the owner object already has a cache - var value = owner[ this.expando ]; - - // If not, create one - if ( !value ) { - value = {}; - - // We can accept data for non-element nodes in modern browsers, - // but we should not, see #8335. - // Always return an empty object. - if ( acceptData( owner ) ) { - - // If it is a node unlikely to be stringify-ed or looped over - // use plain assignment - if ( owner.nodeType ) { - owner[ this.expando ] = value; - - // Otherwise secure it in a non-enumerable property - // configurable must be true to allow the property to be - // deleted when data is removed - } else { - Object.defineProperty( owner, this.expando, { - value: value, - configurable: true - } ); - } - } - } - - return value; - }, - set: function( owner, data, value ) { - var prop, - cache = this.cache( owner ); - - // Handle: [ owner, key, value ] args - // Always use camelCase key (gh-2257) - if ( typeof data === "string" ) { - cache[ camelCase( data ) ] = value; - - // Handle: [ owner, { properties } ] args - } else { - - // Copy the properties one-by-one to the cache object - for ( prop in data ) { - cache[ camelCase( prop ) ] = data[ prop ]; - } - } - return cache; - }, - get: function( owner, key ) { - return key === undefined ? - this.cache( owner ) : - - // Always use camelCase key (gh-2257) - owner[ this.expando ] && owner[ this.expando ][ camelCase( key ) ]; - }, - access: function( owner, key, value ) { - - // In cases where either: - // - // 1. No key was specified - // 2. A string key was specified, but no value provided - // - // Take the "read" path and allow the get method to determine - // which value to return, respectively either: - // - // 1. The entire cache object - // 2. The data stored at the key - // - if ( key === undefined || - ( ( key && typeof key === "string" ) && value === undefined ) ) { - - return this.get( owner, key ); - } - - // When the key is not a string, or both a key and value - // are specified, set or extend (existing objects) with either: - // - // 1. An object of properties - // 2. A key and value - // - this.set( owner, key, value ); - - // Since the "set" path can have two possible entry points - // return the expected data based on which path was taken[*] - return value !== undefined ? value : key; - }, - remove: function( owner, key ) { - var i, - cache = owner[ this.expando ]; - - if ( cache === undefined ) { - return; - } - - if ( key !== undefined ) { - - // Support array or space separated string of keys - if ( Array.isArray( key ) ) { - - // If key is an array of keys... - // We always set camelCase keys, so remove that. - key = key.map( camelCase ); - } else { - key = camelCase( key ); - - // If a key with the spaces exists, use it. - // Otherwise, create an array by matching non-whitespace - key = key in cache ? - [ key ] : - ( key.match( rnothtmlwhite ) || [] ); - } - - i = key.length; - - while ( i-- ) { - delete cache[ key[ i ] ]; - } - } - - // Remove the expando if there's no more data - if ( key === undefined || jQuery.isEmptyObject( cache ) ) { - - // Support: Chrome <=35 - 45 - // Webkit & Blink performance suffers when deleting properties - // from DOM nodes, so set to undefined instead - // https://bugs.chromium.org/p/chromium/issues/detail?id=378607 (bug restricted) - if ( owner.nodeType ) { - owner[ this.expando ] = undefined; - } else { - delete owner[ this.expando ]; - } - } - }, - hasData: function( owner ) { - var cache = owner[ this.expando ]; - return cache !== undefined && !jQuery.isEmptyObject( cache ); - } -}; -var dataPriv = new Data(); - -var dataUser = new Data(); - - - -// Implementation Summary -// -// 1. Enforce API surface and semantic compatibility with 1.9.x branch -// 2. Improve the module's maintainability by reducing the storage -// paths to a single mechanism. -// 3. Use the same single mechanism to support "private" and "user" data. -// 4. _Never_ expose "private" data to user code (TODO: Drop _data, _removeData) -// 5. Avoid exposing implementation details on user objects (eg. expando properties) -// 6. Provide a clear path for implementation upgrade to WeakMap in 2014 - -var rbrace = /^(?:\{[\w\W]*\}|\[[\w\W]*\])$/, - rmultiDash = /[A-Z]/g; - -function getData( data ) { - if ( data === "true" ) { - return true; - } - - if ( data === "false" ) { - return false; - } - - if ( data === "null" ) { - return null; - } - - // Only convert to a number if it doesn't change the string - if ( data === +data + "" ) { - return +data; - } - - if ( rbrace.test( data ) ) { - return JSON.parse( data ); - } - - return data; -} - -function dataAttr( elem, key, data ) { - var name; - - // If nothing was found internally, try to fetch any - // data from the HTML5 data-* attribute - if ( data === undefined && elem.nodeType === 1 ) { - name = "data-" + key.replace( rmultiDash, "-$&" ).toLowerCase(); - data = elem.getAttribute( name ); - - if ( typeof data === "string" ) { - try { - data = getData( data ); - } catch ( e ) {} - - // Make sure we set the data so it isn't changed later - dataUser.set( elem, key, data ); - } else { - data = undefined; - } - } - return data; -} - -jQuery.extend( { - hasData: function( elem ) { - return dataUser.hasData( elem ) || dataPriv.hasData( elem ); - }, - - data: function( elem, name, data ) { - return dataUser.access( elem, name, data ); - }, - - removeData: function( elem, name ) { - dataUser.remove( elem, name ); - }, - - // TODO: Now that all calls to _data and _removeData have been replaced - // with direct calls to dataPriv methods, these can be deprecated. - _data: function( elem, name, data ) { - return dataPriv.access( elem, name, data ); - }, - - _removeData: function( elem, name ) { - dataPriv.remove( elem, name ); - } -} ); - -jQuery.fn.extend( { - data: function( key, value ) { - var i, name, data, - elem = this[ 0 ], - attrs = elem && elem.attributes; - - // Gets all values - if ( key === undefined ) { - if ( this.length ) { - data = dataUser.get( elem ); - - if ( elem.nodeType === 1 && !dataPriv.get( elem, "hasDataAttrs" ) ) { - i = attrs.length; - while ( i-- ) { - - // Support: IE 11 only - // The attrs elements can be null (#14894) - if ( attrs[ i ] ) { - name = attrs[ i ].name; - if ( name.indexOf( "data-" ) === 0 ) { - name = camelCase( name.slice( 5 ) ); - dataAttr( elem, name, data[ name ] ); - } - } - } - dataPriv.set( elem, "hasDataAttrs", true ); - } - } - - return data; - } - - // Sets multiple values - if ( typeof key === "object" ) { - return this.each( function() { - dataUser.set( this, key ); - } ); - } - - return access( this, function( value ) { - var data; - - // The calling jQuery object (element matches) is not empty - // (and therefore has an element appears at this[ 0 ]) and the - // `value` parameter was not undefined. An empty jQuery object - // will result in `undefined` for elem = this[ 0 ] which will - // throw an exception if an attempt to read a data cache is made. - if ( elem && value === undefined ) { - - // Attempt to get data from the cache - // The key will always be camelCased in Data - data = dataUser.get( elem, key ); - if ( data !== undefined ) { - return data; - } - - // Attempt to "discover" the data in - // HTML5 custom data-* attrs - data = dataAttr( elem, key ); - if ( data !== undefined ) { - return data; - } - - // We tried really hard, but the data doesn't exist. - return; - } - - // Set the data... - this.each( function() { - - // We always store the camelCased key - dataUser.set( this, key, value ); - } ); - }, null, value, arguments.length > 1, null, true ); - }, - - removeData: function( key ) { - return this.each( function() { - dataUser.remove( this, key ); - } ); - } -} ); - - -jQuery.extend( { - queue: function( elem, type, data ) { - var queue; - - if ( elem ) { - type = ( type || "fx" ) + "queue"; - queue = dataPriv.get( elem, type ); - - // Speed up dequeue by getting out quickly if this is just a lookup - if ( data ) { - if ( !queue || Array.isArray( data ) ) { - queue = dataPriv.access( elem, type, jQuery.makeArray( data ) ); - } else { - queue.push( data ); - } - } - return queue || []; - } - }, - - dequeue: function( elem, type ) { - type = type || "fx"; - - var queue = jQuery.queue( elem, type ), - startLength = queue.length, - fn = queue.shift(), - hooks = jQuery._queueHooks( elem, type ), - next = function() { - jQuery.dequeue( elem, type ); - }; - - // If the fx queue is dequeued, always remove the progress sentinel - if ( fn === "inprogress" ) { - fn = queue.shift(); - startLength--; - } - - if ( fn ) { - - // Add a progress sentinel to prevent the fx queue from being - // automatically dequeued - if ( type === "fx" ) { - queue.unshift( "inprogress" ); - } - - // Clear up the last queue stop function - delete hooks.stop; - fn.call( elem, next, hooks ); - } - - if ( !startLength && hooks ) { - hooks.empty.fire(); - } - }, - - // Not public - generate a queueHooks object, or return the current one - _queueHooks: function( elem, type ) { - var key = type + "queueHooks"; - return dataPriv.get( elem, key ) || dataPriv.access( elem, key, { - empty: jQuery.Callbacks( "once memory" ).add( function() { - dataPriv.remove( elem, [ type + "queue", key ] ); - } ) - } ); - } -} ); - -jQuery.fn.extend( { - queue: function( type, data ) { - var setter = 2; - - if ( typeof type !== "string" ) { - data = type; - type = "fx"; - setter--; - } - - if ( arguments.length < setter ) { - return jQuery.queue( this[ 0 ], type ); - } - - return data === undefined ? - this : - this.each( function() { - var queue = jQuery.queue( this, type, data ); - - // Ensure a hooks for this queue - jQuery._queueHooks( this, type ); - - if ( type === "fx" && queue[ 0 ] !== "inprogress" ) { - jQuery.dequeue( this, type ); - } - } ); - }, - dequeue: function( type ) { - return this.each( function() { - jQuery.dequeue( this, type ); - } ); - }, - clearQueue: function( type ) { - return this.queue( type || "fx", [] ); - }, - - // Get a promise resolved when queues of a certain type - // are emptied (fx is the type by default) - promise: function( type, obj ) { - var tmp, - count = 1, - defer = jQuery.Deferred(), - elements = this, - i = this.length, - resolve = function() { - if ( !( --count ) ) { - defer.resolveWith( elements, [ elements ] ); - } - }; - - if ( typeof type !== "string" ) { - obj = type; - type = undefined; - } - type = type || "fx"; - - while ( i-- ) { - tmp = dataPriv.get( elements[ i ], type + "queueHooks" ); - if ( tmp && tmp.empty ) { - count++; - tmp.empty.add( resolve ); - } - } - resolve(); - return defer.promise( obj ); - } -} ); -var pnum = ( /[+-]?(?:\d*\.|)\d+(?:[eE][+-]?\d+|)/ ).source; - -var rcssNum = new RegExp( "^(?:([+-])=|)(" + pnum + ")([a-z%]*)$", "i" ); - - -var cssExpand = [ "Top", "Right", "Bottom", "Left" ]; - -var documentElement = document.documentElement; - - - - var isAttached = function( elem ) { - return jQuery.contains( elem.ownerDocument, elem ); - }, - composed = { composed: true }; - - // Support: IE 9 - 11+, Edge 12 - 18+, iOS 10.0 - 10.2 only - // Check attachment across shadow DOM boundaries when possible (gh-3504) - // Support: iOS 10.0-10.2 only - // Early iOS 10 versions support `attachShadow` but not `getRootNode`, - // leading to errors. We need to check for `getRootNode`. - if ( documentElement.getRootNode ) { - isAttached = function( elem ) { - return jQuery.contains( elem.ownerDocument, elem ) || - elem.getRootNode( composed ) === elem.ownerDocument; - }; - } -var isHiddenWithinTree = function( elem, el ) { - - // isHiddenWithinTree might be called from jQuery#filter function; - // in that case, element will be second argument - elem = el || elem; - - // Inline style trumps all - return elem.style.display === "none" || - elem.style.display === "" && - - // Otherwise, check computed style - // Support: Firefox <=43 - 45 - // Disconnected elements can have computed display: none, so first confirm that elem is - // in the document. - isAttached( elem ) && - - jQuery.css( elem, "display" ) === "none"; - }; - - - -function adjustCSS( elem, prop, valueParts, tween ) { - var adjusted, scale, - maxIterations = 20, - currentValue = tween ? - function() { - return tween.cur(); - } : - function() { - return jQuery.css( elem, prop, "" ); - }, - initial = currentValue(), - unit = valueParts && valueParts[ 3 ] || ( jQuery.cssNumber[ prop ] ? "" : "px" ), - - // Starting value computation is required for potential unit mismatches - initialInUnit = elem.nodeType && - ( jQuery.cssNumber[ prop ] || unit !== "px" && +initial ) && - rcssNum.exec( jQuery.css( elem, prop ) ); - - if ( initialInUnit && initialInUnit[ 3 ] !== unit ) { - - // Support: Firefox <=54 - // Halve the iteration target value to prevent interference from CSS upper bounds (gh-2144) - initial = initial / 2; - - // Trust units reported by jQuery.css - unit = unit || initialInUnit[ 3 ]; - - // Iteratively approximate from a nonzero starting point - initialInUnit = +initial || 1; - - while ( maxIterations-- ) { - - // Evaluate and update our best guess (doubling guesses that zero out). - // Finish if the scale equals or crosses 1 (making the old*new product non-positive). - jQuery.style( elem, prop, initialInUnit + unit ); - if ( ( 1 - scale ) * ( 1 - ( scale = currentValue() / initial || 0.5 ) ) <= 0 ) { - maxIterations = 0; - } - initialInUnit = initialInUnit / scale; - - } - - initialInUnit = initialInUnit * 2; - jQuery.style( elem, prop, initialInUnit + unit ); - - // Make sure we update the tween properties later on - valueParts = valueParts || []; - } - - if ( valueParts ) { - initialInUnit = +initialInUnit || +initial || 0; - - // Apply relative offset (+=/-=) if specified - adjusted = valueParts[ 1 ] ? - initialInUnit + ( valueParts[ 1 ] + 1 ) * valueParts[ 2 ] : - +valueParts[ 2 ]; - if ( tween ) { - tween.unit = unit; - tween.start = initialInUnit; - tween.end = adjusted; - } - } - return adjusted; -} - - -var defaultDisplayMap = {}; - -function getDefaultDisplay( elem ) { - var temp, - doc = elem.ownerDocument, - nodeName = elem.nodeName, - display = defaultDisplayMap[ nodeName ]; - - if ( display ) { - return display; - } - - temp = doc.body.appendChild( doc.createElement( nodeName ) ); - display = jQuery.css( temp, "display" ); - - temp.parentNode.removeChild( temp ); - - if ( display === "none" ) { - display = "block"; - } - defaultDisplayMap[ nodeName ] = display; - - return display; -} - -function showHide( elements, show ) { - var display, elem, - values = [], - index = 0, - length = elements.length; - - // Determine new display value for elements that need to change - for ( ; index < length; index++ ) { - elem = elements[ index ]; - if ( !elem.style ) { - continue; - } - - display = elem.style.display; - if ( show ) { - - // Since we force visibility upon cascade-hidden elements, an immediate (and slow) - // check is required in this first loop unless we have a nonempty display value (either - // inline or about-to-be-restored) - if ( display === "none" ) { - values[ index ] = dataPriv.get( elem, "display" ) || null; - if ( !values[ index ] ) { - elem.style.display = ""; - } - } - if ( elem.style.display === "" && isHiddenWithinTree( elem ) ) { - values[ index ] = getDefaultDisplay( elem ); - } - } else { - if ( display !== "none" ) { - values[ index ] = "none"; - - // Remember what we're overwriting - dataPriv.set( elem, "display", display ); - } - } - } - - // Set the display of the elements in a second loop to avoid constant reflow - for ( index = 0; index < length; index++ ) { - if ( values[ index ] != null ) { - elements[ index ].style.display = values[ index ]; - } - } - - return elements; -} - -jQuery.fn.extend( { - show: function() { - return showHide( this, true ); - }, - hide: function() { - return showHide( this ); - }, - toggle: function( state ) { - if ( typeof state === "boolean" ) { - return state ? this.show() : this.hide(); - } - - return this.each( function() { - if ( isHiddenWithinTree( this ) ) { - jQuery( this ).show(); - } else { - jQuery( this ).hide(); - } - } ); - } -} ); -var rcheckableType = ( /^(?:checkbox|radio)$/i ); - -var rtagName = ( /<([a-z][^\/\0>\x20\t\r\n\f]*)/i ); - -var rscriptType = ( /^$|^module$|\/(?:java|ecma)script/i ); - - - -( function() { - var fragment = document.createDocumentFragment(), - div = fragment.appendChild( document.createElement( "div" ) ), - input = document.createElement( "input" ); - - // Support: Android 4.0 - 4.3 only - // Check state lost if the name is set (#11217) - // Support: Windows Web Apps (WWA) - // `name` and `type` must use .setAttribute for WWA (#14901) - input.setAttribute( "type", "radio" ); - input.setAttribute( "checked", "checked" ); - input.setAttribute( "name", "t" ); - - div.appendChild( input ); - - // Support: Android <=4.1 only - // Older WebKit doesn't clone checked state correctly in fragments - support.checkClone = div.cloneNode( true ).cloneNode( true ).lastChild.checked; - - // Support: IE <=11 only - // Make sure textarea (and checkbox) defaultValue is properly cloned - div.innerHTML = ""; - support.noCloneChecked = !!div.cloneNode( true ).lastChild.defaultValue; - - // Support: IE <=9 only - // IE <=9 replaces "; - support.option = !!div.lastChild; -} )(); - - -// We have to close these tags to support XHTML (#13200) -var wrapMap = { - - // XHTML parsers do not magically insert elements in the - // same way that tag soup parsers do. So we cannot shorten - // this by omitting or other required elements. - thead: [ 1, "", "
          " ], - col: [ 2, "", "
          " ], - tr: [ 2, "", "
          " ], - td: [ 3, "", "
          " ], - - _default: [ 0, "", "" ] -}; - -wrapMap.tbody = wrapMap.tfoot = wrapMap.colgroup = wrapMap.caption = wrapMap.thead; -wrapMap.th = wrapMap.td; - -// Support: IE <=9 only -if ( !support.option ) { - wrapMap.optgroup = wrapMap.option = [ 1, "" ]; -} - - -function getAll( context, tag ) { - - // Support: IE <=9 - 11 only - // Use typeof to avoid zero-argument method invocation on host objects (#15151) - var ret; - - if ( typeof context.getElementsByTagName !== "undefined" ) { - ret = context.getElementsByTagName( tag || "*" ); - - } else if ( typeof context.querySelectorAll !== "undefined" ) { - ret = context.querySelectorAll( tag || "*" ); - - } else { - ret = []; - } - - if ( tag === undefined || tag && nodeName( context, tag ) ) { - return jQuery.merge( [ context ], ret ); - } - - return ret; -} - - -// Mark scripts as having already been evaluated -function setGlobalEval( elems, refElements ) { - var i = 0, - l = elems.length; - - for ( ; i < l; i++ ) { - dataPriv.set( - elems[ i ], - "globalEval", - !refElements || dataPriv.get( refElements[ i ], "globalEval" ) - ); - } -} - - -var rhtml = /<|&#?\w+;/; - -function buildFragment( elems, context, scripts, selection, ignored ) { - var elem, tmp, tag, wrap, attached, j, - fragment = context.createDocumentFragment(), - nodes = [], - i = 0, - l = elems.length; - - for ( ; i < l; i++ ) { - elem = elems[ i ]; - - if ( elem || elem === 0 ) { - - // Add nodes directly - if ( toType( elem ) === "object" ) { - - // Support: Android <=4.0 only, PhantomJS 1 only - // push.apply(_, arraylike) throws on ancient WebKit - jQuery.merge( nodes, elem.nodeType ? [ elem ] : elem ); - - // Convert non-html into a text node - } else if ( !rhtml.test( elem ) ) { - nodes.push( context.createTextNode( elem ) ); - - // Convert html into DOM nodes - } else { - tmp = tmp || fragment.appendChild( context.createElement( "div" ) ); - - // Deserialize a standard representation - tag = ( rtagName.exec( elem ) || [ "", "" ] )[ 1 ].toLowerCase(); - wrap = wrapMap[ tag ] || wrapMap._default; - tmp.innerHTML = wrap[ 1 ] + jQuery.htmlPrefilter( elem ) + wrap[ 2 ]; - - // Descend through wrappers to the right content - j = wrap[ 0 ]; - while ( j-- ) { - tmp = tmp.lastChild; - } - - // Support: Android <=4.0 only, PhantomJS 1 only - // push.apply(_, arraylike) throws on ancient WebKit - jQuery.merge( nodes, tmp.childNodes ); - - // Remember the top-level container - tmp = fragment.firstChild; - - // Ensure the created nodes are orphaned (#12392) - tmp.textContent = ""; - } - } - } - - // Remove wrapper from fragment - fragment.textContent = ""; - - i = 0; - while ( ( elem = nodes[ i++ ] ) ) { - - // Skip elements already in the context collection (trac-4087) - if ( selection && jQuery.inArray( elem, selection ) > -1 ) { - if ( ignored ) { - ignored.push( elem ); - } - continue; - } - - attached = isAttached( elem ); - - // Append to fragment - tmp = getAll( fragment.appendChild( elem ), "script" ); - - // Preserve script evaluation history - if ( attached ) { - setGlobalEval( tmp ); - } - - // Capture executables - if ( scripts ) { - j = 0; - while ( ( elem = tmp[ j++ ] ) ) { - if ( rscriptType.test( elem.type || "" ) ) { - scripts.push( elem ); - } - } - } - } - - return fragment; -} - - -var rtypenamespace = /^([^.]*)(?:\.(.+)|)/; - -function returnTrue() { - return true; -} - -function returnFalse() { - return false; -} - -// Support: IE <=9 - 11+ -// focus() and blur() are asynchronous, except when they are no-op. -// So expect focus to be synchronous when the element is already active, -// and blur to be synchronous when the element is not already active. -// (focus and blur are always synchronous in other supported browsers, -// this just defines when we can count on it). -function expectSync( elem, type ) { - return ( elem === safeActiveElement() ) === ( type === "focus" ); -} - -// Support: IE <=9 only -// Accessing document.activeElement can throw unexpectedly -// https://bugs.jquery.com/ticket/13393 -function safeActiveElement() { - try { - return document.activeElement; - } catch ( err ) { } -} - -function on( elem, types, selector, data, fn, one ) { - var origFn, type; - - // Types can be a map of types/handlers - if ( typeof types === "object" ) { - - // ( types-Object, selector, data ) - if ( typeof selector !== "string" ) { - - // ( types-Object, data ) - data = data || selector; - selector = undefined; - } - for ( type in types ) { - on( elem, type, selector, data, types[ type ], one ); - } - return elem; - } - - if ( data == null && fn == null ) { - - // ( types, fn ) - fn = selector; - data = selector = undefined; - } else if ( fn == null ) { - if ( typeof selector === "string" ) { - - // ( types, selector, fn ) - fn = data; - data = undefined; - } else { - - // ( types, data, fn ) - fn = data; - data = selector; - selector = undefined; - } - } - if ( fn === false ) { - fn = returnFalse; - } else if ( !fn ) { - return elem; - } - - if ( one === 1 ) { - origFn = fn; - fn = function( event ) { - - // Can use an empty set, since event contains the info - jQuery().off( event ); - return origFn.apply( this, arguments ); - }; - - // Use same guid so caller can remove using origFn - fn.guid = origFn.guid || ( origFn.guid = jQuery.guid++ ); - } - return elem.each( function() { - jQuery.event.add( this, types, fn, data, selector ); - } ); -} - -/* - * Helper functions for managing events -- not part of the public interface. - * Props to Dean Edwards' addEvent library for many of the ideas. - */ -jQuery.event = { - - global: {}, - - add: function( elem, types, handler, data, selector ) { - - var handleObjIn, eventHandle, tmp, - events, t, handleObj, - special, handlers, type, namespaces, origType, - elemData = dataPriv.get( elem ); - - // Only attach events to objects that accept data - if ( !acceptData( elem ) ) { - return; - } - - // Caller can pass in an object of custom data in lieu of the handler - if ( handler.handler ) { - handleObjIn = handler; - handler = handleObjIn.handler; - selector = handleObjIn.selector; - } - - // Ensure that invalid selectors throw exceptions at attach time - // Evaluate against documentElement in case elem is a non-element node (e.g., document) - if ( selector ) { - jQuery.find.matchesSelector( documentElement, selector ); - } - - // Make sure that the handler has a unique ID, used to find/remove it later - if ( !handler.guid ) { - handler.guid = jQuery.guid++; - } - - // Init the element's event structure and main handler, if this is the first - if ( !( events = elemData.events ) ) { - events = elemData.events = Object.create( null ); - } - if ( !( eventHandle = elemData.handle ) ) { - eventHandle = elemData.handle = function( e ) { - - // Discard the second event of a jQuery.event.trigger() and - // when an event is called after a page has unloaded - return typeof jQuery !== "undefined" && jQuery.event.triggered !== e.type ? - jQuery.event.dispatch.apply( elem, arguments ) : undefined; - }; - } - - // Handle multiple events separated by a space - types = ( types || "" ).match( rnothtmlwhite ) || [ "" ]; - t = types.length; - while ( t-- ) { - tmp = rtypenamespace.exec( types[ t ] ) || []; - type = origType = tmp[ 1 ]; - namespaces = ( tmp[ 2 ] || "" ).split( "." ).sort(); - - // There *must* be a type, no attaching namespace-only handlers - if ( !type ) { - continue; - } - - // If event changes its type, use the special event handlers for the changed type - special = jQuery.event.special[ type ] || {}; - - // If selector defined, determine special event api type, otherwise given type - type = ( selector ? special.delegateType : special.bindType ) || type; - - // Update special based on newly reset type - special = jQuery.event.special[ type ] || {}; - - // handleObj is passed to all event handlers - handleObj = jQuery.extend( { - type: type, - origType: origType, - data: data, - handler: handler, - guid: handler.guid, - selector: selector, - needsContext: selector && jQuery.expr.match.needsContext.test( selector ), - namespace: namespaces.join( "." ) - }, handleObjIn ); - - // Init the event handler queue if we're the first - if ( !( handlers = events[ type ] ) ) { - handlers = events[ type ] = []; - handlers.delegateCount = 0; - - // Only use addEventListener if the special events handler returns false - if ( !special.setup || - special.setup.call( elem, data, namespaces, eventHandle ) === false ) { - - if ( elem.addEventListener ) { - elem.addEventListener( type, eventHandle ); - } - } - } - - if ( special.add ) { - special.add.call( elem, handleObj ); - - if ( !handleObj.handler.guid ) { - handleObj.handler.guid = handler.guid; - } - } - - // Add to the element's handler list, delegates in front - if ( selector ) { - handlers.splice( handlers.delegateCount++, 0, handleObj ); - } else { - handlers.push( handleObj ); - } - - // Keep track of which events have ever been used, for event optimization - jQuery.event.global[ type ] = true; - } - - }, - - // Detach an event or set of events from an element - remove: function( elem, types, handler, selector, mappedTypes ) { - - var j, origCount, tmp, - events, t, handleObj, - special, handlers, type, namespaces, origType, - elemData = dataPriv.hasData( elem ) && dataPriv.get( elem ); - - if ( !elemData || !( events = elemData.events ) ) { - return; - } - - // Once for each type.namespace in types; type may be omitted - types = ( types || "" ).match( rnothtmlwhite ) || [ "" ]; - t = types.length; - while ( t-- ) { - tmp = rtypenamespace.exec( types[ t ] ) || []; - type = origType = tmp[ 1 ]; - namespaces = ( tmp[ 2 ] || "" ).split( "." ).sort(); - - // Unbind all events (on this namespace, if provided) for the element - if ( !type ) { - for ( type in events ) { - jQuery.event.remove( elem, type + types[ t ], handler, selector, true ); - } - continue; - } - - special = jQuery.event.special[ type ] || {}; - type = ( selector ? special.delegateType : special.bindType ) || type; - handlers = events[ type ] || []; - tmp = tmp[ 2 ] && - new RegExp( "(^|\\.)" + namespaces.join( "\\.(?:.*\\.|)" ) + "(\\.|$)" ); - - // Remove matching events - origCount = j = handlers.length; - while ( j-- ) { - handleObj = handlers[ j ]; - - if ( ( mappedTypes || origType === handleObj.origType ) && - ( !handler || handler.guid === handleObj.guid ) && - ( !tmp || tmp.test( handleObj.namespace ) ) && - ( !selector || selector === handleObj.selector || - selector === "**" && handleObj.selector ) ) { - handlers.splice( j, 1 ); - - if ( handleObj.selector ) { - handlers.delegateCount--; - } - if ( special.remove ) { - special.remove.call( elem, handleObj ); - } - } - } - - // Remove generic event handler if we removed something and no more handlers exist - // (avoids potential for endless recursion during removal of special event handlers) - if ( origCount && !handlers.length ) { - if ( !special.teardown || - special.teardown.call( elem, namespaces, elemData.handle ) === false ) { - - jQuery.removeEvent( elem, type, elemData.handle ); - } - - delete events[ type ]; - } - } - - // Remove data and the expando if it's no longer used - if ( jQuery.isEmptyObject( events ) ) { - dataPriv.remove( elem, "handle events" ); - } - }, - - dispatch: function( nativeEvent ) { - - var i, j, ret, matched, handleObj, handlerQueue, - args = new Array( arguments.length ), - - // Make a writable jQuery.Event from the native event object - event = jQuery.event.fix( nativeEvent ), - - handlers = ( - dataPriv.get( this, "events" ) || Object.create( null ) - )[ event.type ] || [], - special = jQuery.event.special[ event.type ] || {}; - - // Use the fix-ed jQuery.Event rather than the (read-only) native event - args[ 0 ] = event; - - for ( i = 1; i < arguments.length; i++ ) { - args[ i ] = arguments[ i ]; - } - - event.delegateTarget = this; - - // Call the preDispatch hook for the mapped type, and let it bail if desired - if ( special.preDispatch && special.preDispatch.call( this, event ) === false ) { - return; - } - - // Determine handlers - handlerQueue = jQuery.event.handlers.call( this, event, handlers ); - - // Run delegates first; they may want to stop propagation beneath us - i = 0; - while ( ( matched = handlerQueue[ i++ ] ) && !event.isPropagationStopped() ) { - event.currentTarget = matched.elem; - - j = 0; - while ( ( handleObj = matched.handlers[ j++ ] ) && - !event.isImmediatePropagationStopped() ) { - - // If the event is namespaced, then each handler is only invoked if it is - // specially universal or its namespaces are a superset of the event's. - if ( !event.rnamespace || handleObj.namespace === false || - event.rnamespace.test( handleObj.namespace ) ) { - - event.handleObj = handleObj; - event.data = handleObj.data; - - ret = ( ( jQuery.event.special[ handleObj.origType ] || {} ).handle || - handleObj.handler ).apply( matched.elem, args ); - - if ( ret !== undefined ) { - if ( ( event.result = ret ) === false ) { - event.preventDefault(); - event.stopPropagation(); - } - } - } - } - } - - // Call the postDispatch hook for the mapped type - if ( special.postDispatch ) { - special.postDispatch.call( this, event ); - } - - return event.result; - }, - - handlers: function( event, handlers ) { - var i, handleObj, sel, matchedHandlers, matchedSelectors, - handlerQueue = [], - delegateCount = handlers.delegateCount, - cur = event.target; - - // Find delegate handlers - if ( delegateCount && - - // Support: IE <=9 - // Black-hole SVG instance trees (trac-13180) - cur.nodeType && - - // Support: Firefox <=42 - // Suppress spec-violating clicks indicating a non-primary pointer button (trac-3861) - // https://www.w3.org/TR/DOM-Level-3-Events/#event-type-click - // Support: IE 11 only - // ...but not arrow key "clicks" of radio inputs, which can have `button` -1 (gh-2343) - !( event.type === "click" && event.button >= 1 ) ) { - - for ( ; cur !== this; cur = cur.parentNode || this ) { - - // Don't check non-elements (#13208) - // Don't process clicks on disabled elements (#6911, #8165, #11382, #11764) - if ( cur.nodeType === 1 && !( event.type === "click" && cur.disabled === true ) ) { - matchedHandlers = []; - matchedSelectors = {}; - for ( i = 0; i < delegateCount; i++ ) { - handleObj = handlers[ i ]; - - // Don't conflict with Object.prototype properties (#13203) - sel = handleObj.selector + " "; - - if ( matchedSelectors[ sel ] === undefined ) { - matchedSelectors[ sel ] = handleObj.needsContext ? - jQuery( sel, this ).index( cur ) > -1 : - jQuery.find( sel, this, null, [ cur ] ).length; - } - if ( matchedSelectors[ sel ] ) { - matchedHandlers.push( handleObj ); - } - } - if ( matchedHandlers.length ) { - handlerQueue.push( { elem: cur, handlers: matchedHandlers } ); - } - } - } - } - - // Add the remaining (directly-bound) handlers - cur = this; - if ( delegateCount < handlers.length ) { - handlerQueue.push( { elem: cur, handlers: handlers.slice( delegateCount ) } ); - } - - return handlerQueue; - }, - - addProp: function( name, hook ) { - Object.defineProperty( jQuery.Event.prototype, name, { - enumerable: true, - configurable: true, - - get: isFunction( hook ) ? - function() { - if ( this.originalEvent ) { - return hook( this.originalEvent ); - } - } : - function() { - if ( this.originalEvent ) { - return this.originalEvent[ name ]; - } - }, - - set: function( value ) { - Object.defineProperty( this, name, { - enumerable: true, - configurable: true, - writable: true, - value: value - } ); - } - } ); - }, - - fix: function( originalEvent ) { - return originalEvent[ jQuery.expando ] ? - originalEvent : - new jQuery.Event( originalEvent ); - }, - - special: { - load: { - - // Prevent triggered image.load events from bubbling to window.load - noBubble: true - }, - click: { - - // Utilize native event to ensure correct state for checkable inputs - setup: function( data ) { - - // For mutual compressibility with _default, replace `this` access with a local var. - // `|| data` is dead code meant only to preserve the variable through minification. - var el = this || data; - - // Claim the first handler - if ( rcheckableType.test( el.type ) && - el.click && nodeName( el, "input" ) ) { - - // dataPriv.set( el, "click", ... ) - leverageNative( el, "click", returnTrue ); - } - - // Return false to allow normal processing in the caller - return false; - }, - trigger: function( data ) { - - // For mutual compressibility with _default, replace `this` access with a local var. - // `|| data` is dead code meant only to preserve the variable through minification. - var el = this || data; - - // Force setup before triggering a click - if ( rcheckableType.test( el.type ) && - el.click && nodeName( el, "input" ) ) { - - leverageNative( el, "click" ); - } - - // Return non-false to allow normal event-path propagation - return true; - }, - - // For cross-browser consistency, suppress native .click() on links - // Also prevent it if we're currently inside a leveraged native-event stack - _default: function( event ) { - var target = event.target; - return rcheckableType.test( target.type ) && - target.click && nodeName( target, "input" ) && - dataPriv.get( target, "click" ) || - nodeName( target, "a" ); - } - }, - - beforeunload: { - postDispatch: function( event ) { - - // Support: Firefox 20+ - // Firefox doesn't alert if the returnValue field is not set. - if ( event.result !== undefined && event.originalEvent ) { - event.originalEvent.returnValue = event.result; - } - } - } - } -}; - -// Ensure the presence of an event listener that handles manually-triggered -// synthetic events by interrupting progress until reinvoked in response to -// *native* events that it fires directly, ensuring that state changes have -// already occurred before other listeners are invoked. -function leverageNative( el, type, expectSync ) { - - // Missing expectSync indicates a trigger call, which must force setup through jQuery.event.add - if ( !expectSync ) { - if ( dataPriv.get( el, type ) === undefined ) { - jQuery.event.add( el, type, returnTrue ); - } - return; - } - - // Register the controller as a special universal handler for all event namespaces - dataPriv.set( el, type, false ); - jQuery.event.add( el, type, { - namespace: false, - handler: function( event ) { - var notAsync, result, - saved = dataPriv.get( this, type ); - - if ( ( event.isTrigger & 1 ) && this[ type ] ) { - - // Interrupt processing of the outer synthetic .trigger()ed event - // Saved data should be false in such cases, but might be a leftover capture object - // from an async native handler (gh-4350) - if ( !saved.length ) { - - // Store arguments for use when handling the inner native event - // There will always be at least one argument (an event object), so this array - // will not be confused with a leftover capture object. - saved = slice.call( arguments ); - dataPriv.set( this, type, saved ); - - // Trigger the native event and capture its result - // Support: IE <=9 - 11+ - // focus() and blur() are asynchronous - notAsync = expectSync( this, type ); - this[ type ](); - result = dataPriv.get( this, type ); - if ( saved !== result || notAsync ) { - dataPriv.set( this, type, false ); - } else { - result = {}; - } - if ( saved !== result ) { - - // Cancel the outer synthetic event - event.stopImmediatePropagation(); - event.preventDefault(); - - // Support: Chrome 86+ - // In Chrome, if an element having a focusout handler is blurred by - // clicking outside of it, it invokes the handler synchronously. If - // that handler calls `.remove()` on the element, the data is cleared, - // leaving `result` undefined. We need to guard against this. - return result && result.value; - } - - // If this is an inner synthetic event for an event with a bubbling surrogate - // (focus or blur), assume that the surrogate already propagated from triggering the - // native event and prevent that from happening again here. - // This technically gets the ordering wrong w.r.t. to `.trigger()` (in which the - // bubbling surrogate propagates *after* the non-bubbling base), but that seems - // less bad than duplication. - } else if ( ( jQuery.event.special[ type ] || {} ).delegateType ) { - event.stopPropagation(); - } - - // If this is a native event triggered above, everything is now in order - // Fire an inner synthetic event with the original arguments - } else if ( saved.length ) { - - // ...and capture the result - dataPriv.set( this, type, { - value: jQuery.event.trigger( - - // Support: IE <=9 - 11+ - // Extend with the prototype to reset the above stopImmediatePropagation() - jQuery.extend( saved[ 0 ], jQuery.Event.prototype ), - saved.slice( 1 ), - this - ) - } ); - - // Abort handling of the native event - event.stopImmediatePropagation(); - } - } - } ); -} - -jQuery.removeEvent = function( elem, type, handle ) { - - // This "if" is needed for plain objects - if ( elem.removeEventListener ) { - elem.removeEventListener( type, handle ); - } -}; - -jQuery.Event = function( src, props ) { - - // Allow instantiation without the 'new' keyword - if ( !( this instanceof jQuery.Event ) ) { - return new jQuery.Event( src, props ); - } - - // Event object - if ( src && src.type ) { - this.originalEvent = src; - this.type = src.type; - - // Events bubbling up the document may have been marked as prevented - // by a handler lower down the tree; reflect the correct value. - this.isDefaultPrevented = src.defaultPrevented || - src.defaultPrevented === undefined && - - // Support: Android <=2.3 only - src.returnValue === false ? - returnTrue : - returnFalse; - - // Create target properties - // Support: Safari <=6 - 7 only - // Target should not be a text node (#504, #13143) - this.target = ( src.target && src.target.nodeType === 3 ) ? - src.target.parentNode : - src.target; - - this.currentTarget = src.currentTarget; - this.relatedTarget = src.relatedTarget; - - // Event type - } else { - this.type = src; - } - - // Put explicitly provided properties onto the event object - if ( props ) { - jQuery.extend( this, props ); - } - - // Create a timestamp if incoming event doesn't have one - this.timeStamp = src && src.timeStamp || Date.now(); - - // Mark it as fixed - this[ jQuery.expando ] = true; -}; - -// jQuery.Event is based on DOM3 Events as specified by the ECMAScript Language Binding -// https://www.w3.org/TR/2003/WD-DOM-Level-3-Events-20030331/ecma-script-binding.html -jQuery.Event.prototype = { - constructor: jQuery.Event, - isDefaultPrevented: returnFalse, - isPropagationStopped: returnFalse, - isImmediatePropagationStopped: returnFalse, - isSimulated: false, - - preventDefault: function() { - var e = this.originalEvent; - - this.isDefaultPrevented = returnTrue; - - if ( e && !this.isSimulated ) { - e.preventDefault(); - } - }, - stopPropagation: function() { - var e = this.originalEvent; - - this.isPropagationStopped = returnTrue; - - if ( e && !this.isSimulated ) { - e.stopPropagation(); - } - }, - stopImmediatePropagation: function() { - var e = this.originalEvent; - - this.isImmediatePropagationStopped = returnTrue; - - if ( e && !this.isSimulated ) { - e.stopImmediatePropagation(); - } - - this.stopPropagation(); - } -}; - -// Includes all common event props including KeyEvent and MouseEvent specific props -jQuery.each( { - altKey: true, - bubbles: true, - cancelable: true, - changedTouches: true, - ctrlKey: true, - detail: true, - eventPhase: true, - metaKey: true, - pageX: true, - pageY: true, - shiftKey: true, - view: true, - "char": true, - code: true, - charCode: true, - key: true, - keyCode: true, - button: true, - buttons: true, - clientX: true, - clientY: true, - offsetX: true, - offsetY: true, - pointerId: true, - pointerType: true, - screenX: true, - screenY: true, - targetTouches: true, - toElement: true, - touches: true, - which: true -}, jQuery.event.addProp ); - -jQuery.each( { focus: "focusin", blur: "focusout" }, function( type, delegateType ) { - jQuery.event.special[ type ] = { - - // Utilize native event if possible so blur/focus sequence is correct - setup: function() { - - // Claim the first handler - // dataPriv.set( this, "focus", ... ) - // dataPriv.set( this, "blur", ... ) - leverageNative( this, type, expectSync ); - - // Return false to allow normal processing in the caller - return false; - }, - trigger: function() { - - // Force setup before trigger - leverageNative( this, type ); - - // Return non-false to allow normal event-path propagation - return true; - }, - - // Suppress native focus or blur as it's already being fired - // in leverageNative. - _default: function() { - return true; - }, - - delegateType: delegateType - }; -} ); - -// Create mouseenter/leave events using mouseover/out and event-time checks -// so that event delegation works in jQuery. -// Do the same for pointerenter/pointerleave and pointerover/pointerout -// -// Support: Safari 7 only -// Safari sends mouseenter too often; see: -// https://bugs.chromium.org/p/chromium/issues/detail?id=470258 -// for the description of the bug (it existed in older Chrome versions as well). -jQuery.each( { - mouseenter: "mouseover", - mouseleave: "mouseout", - pointerenter: "pointerover", - pointerleave: "pointerout" -}, function( orig, fix ) { - jQuery.event.special[ orig ] = { - delegateType: fix, - bindType: fix, - - handle: function( event ) { - var ret, - target = this, - related = event.relatedTarget, - handleObj = event.handleObj; - - // For mouseenter/leave call the handler if related is outside the target. - // NB: No relatedTarget if the mouse left/entered the browser window - if ( !related || ( related !== target && !jQuery.contains( target, related ) ) ) { - event.type = handleObj.origType; - ret = handleObj.handler.apply( this, arguments ); - event.type = fix; - } - return ret; - } - }; -} ); - -jQuery.fn.extend( { - - on: function( types, selector, data, fn ) { - return on( this, types, selector, data, fn ); - }, - one: function( types, selector, data, fn ) { - return on( this, types, selector, data, fn, 1 ); - }, - off: function( types, selector, fn ) { - var handleObj, type; - if ( types && types.preventDefault && types.handleObj ) { - - // ( event ) dispatched jQuery.Event - handleObj = types.handleObj; - jQuery( types.delegateTarget ).off( - handleObj.namespace ? - handleObj.origType + "." + handleObj.namespace : - handleObj.origType, - handleObj.selector, - handleObj.handler - ); - return this; - } - if ( typeof types === "object" ) { - - // ( types-object [, selector] ) - for ( type in types ) { - this.off( type, selector, types[ type ] ); - } - return this; - } - if ( selector === false || typeof selector === "function" ) { - - // ( types [, fn] ) - fn = selector; - selector = undefined; - } - if ( fn === false ) { - fn = returnFalse; - } - return this.each( function() { - jQuery.event.remove( this, types, fn, selector ); - } ); - } -} ); - - -var - - // Support: IE <=10 - 11, Edge 12 - 13 only - // In IE/Edge using regex groups here causes severe slowdowns. - // See https://connect.microsoft.com/IE/feedback/details/1736512/ - rnoInnerhtml = /\s*$/g; - -// Prefer a tbody over its parent table for containing new rows -function manipulationTarget( elem, content ) { - if ( nodeName( elem, "table" ) && - nodeName( content.nodeType !== 11 ? content : content.firstChild, "tr" ) ) { - - return jQuery( elem ).children( "tbody" )[ 0 ] || elem; - } - - return elem; -} - -// Replace/restore the type attribute of script elements for safe DOM manipulation -function disableScript( elem ) { - elem.type = ( elem.getAttribute( "type" ) !== null ) + "/" + elem.type; - return elem; -} -function restoreScript( elem ) { - if ( ( elem.type || "" ).slice( 0, 5 ) === "true/" ) { - elem.type = elem.type.slice( 5 ); - } else { - elem.removeAttribute( "type" ); - } - - return elem; -} - -function cloneCopyEvent( src, dest ) { - var i, l, type, pdataOld, udataOld, udataCur, events; - - if ( dest.nodeType !== 1 ) { - return; - } - - // 1. Copy private data: events, handlers, etc. - if ( dataPriv.hasData( src ) ) { - pdataOld = dataPriv.get( src ); - events = pdataOld.events; - - if ( events ) { - dataPriv.remove( dest, "handle events" ); - - for ( type in events ) { - for ( i = 0, l = events[ type ].length; i < l; i++ ) { - jQuery.event.add( dest, type, events[ type ][ i ] ); - } - } - } - } - - // 2. Copy user data - if ( dataUser.hasData( src ) ) { - udataOld = dataUser.access( src ); - udataCur = jQuery.extend( {}, udataOld ); - - dataUser.set( dest, udataCur ); - } -} - -// Fix IE bugs, see support tests -function fixInput( src, dest ) { - var nodeName = dest.nodeName.toLowerCase(); - - // Fails to persist the checked state of a cloned checkbox or radio button. - if ( nodeName === "input" && rcheckableType.test( src.type ) ) { - dest.checked = src.checked; - - // Fails to return the selected option to the default selected state when cloning options - } else if ( nodeName === "input" || nodeName === "textarea" ) { - dest.defaultValue = src.defaultValue; - } -} - -function domManip( collection, args, callback, ignored ) { - - // Flatten any nested arrays - args = flat( args ); - - var fragment, first, scripts, hasScripts, node, doc, - i = 0, - l = collection.length, - iNoClone = l - 1, - value = args[ 0 ], - valueIsFunction = isFunction( value ); - - // We can't cloneNode fragments that contain checked, in WebKit - if ( valueIsFunction || - ( l > 1 && typeof value === "string" && - !support.checkClone && rchecked.test( value ) ) ) { - return collection.each( function( index ) { - var self = collection.eq( index ); - if ( valueIsFunction ) { - args[ 0 ] = value.call( this, index, self.html() ); - } - domManip( self, args, callback, ignored ); - } ); - } - - if ( l ) { - fragment = buildFragment( args, collection[ 0 ].ownerDocument, false, collection, ignored ); - first = fragment.firstChild; - - if ( fragment.childNodes.length === 1 ) { - fragment = first; - } - - // Require either new content or an interest in ignored elements to invoke the callback - if ( first || ignored ) { - scripts = jQuery.map( getAll( fragment, "script" ), disableScript ); - hasScripts = scripts.length; - - // Use the original fragment for the last item - // instead of the first because it can end up - // being emptied incorrectly in certain situations (#8070). - for ( ; i < l; i++ ) { - node = fragment; - - if ( i !== iNoClone ) { - node = jQuery.clone( node, true, true ); - - // Keep references to cloned scripts for later restoration - if ( hasScripts ) { - - // Support: Android <=4.0 only, PhantomJS 1 only - // push.apply(_, arraylike) throws on ancient WebKit - jQuery.merge( scripts, getAll( node, "script" ) ); - } - } - - callback.call( collection[ i ], node, i ); - } - - if ( hasScripts ) { - doc = scripts[ scripts.length - 1 ].ownerDocument; - - // Reenable scripts - jQuery.map( scripts, restoreScript ); - - // Evaluate executable scripts on first document insertion - for ( i = 0; i < hasScripts; i++ ) { - node = scripts[ i ]; - if ( rscriptType.test( node.type || "" ) && - !dataPriv.access( node, "globalEval" ) && - jQuery.contains( doc, node ) ) { - - if ( node.src && ( node.type || "" ).toLowerCase() !== "module" ) { - - // Optional AJAX dependency, but won't run scripts if not present - if ( jQuery._evalUrl && !node.noModule ) { - jQuery._evalUrl( node.src, { - nonce: node.nonce || node.getAttribute( "nonce" ) - }, doc ); - } - } else { - DOMEval( node.textContent.replace( rcleanScript, "" ), node, doc ); - } - } - } - } - } - } - - return collection; -} - -function remove( elem, selector, keepData ) { - var node, - nodes = selector ? jQuery.filter( selector, elem ) : elem, - i = 0; - - for ( ; ( node = nodes[ i ] ) != null; i++ ) { - if ( !keepData && node.nodeType === 1 ) { - jQuery.cleanData( getAll( node ) ); - } - - if ( node.parentNode ) { - if ( keepData && isAttached( node ) ) { - setGlobalEval( getAll( node, "script" ) ); - } - node.parentNode.removeChild( node ); - } - } - - return elem; -} - -jQuery.extend( { - htmlPrefilter: function( html ) { - return html; - }, - - clone: function( elem, dataAndEvents, deepDataAndEvents ) { - var i, l, srcElements, destElements, - clone = elem.cloneNode( true ), - inPage = isAttached( elem ); - - // Fix IE cloning issues - if ( !support.noCloneChecked && ( elem.nodeType === 1 || elem.nodeType === 11 ) && - !jQuery.isXMLDoc( elem ) ) { - - // We eschew Sizzle here for performance reasons: https://jsperf.com/getall-vs-sizzle/2 - destElements = getAll( clone ); - srcElements = getAll( elem ); - - for ( i = 0, l = srcElements.length; i < l; i++ ) { - fixInput( srcElements[ i ], destElements[ i ] ); - } - } - - // Copy the events from the original to the clone - if ( dataAndEvents ) { - if ( deepDataAndEvents ) { - srcElements = srcElements || getAll( elem ); - destElements = destElements || getAll( clone ); - - for ( i = 0, l = srcElements.length; i < l; i++ ) { - cloneCopyEvent( srcElements[ i ], destElements[ i ] ); - } - } else { - cloneCopyEvent( elem, clone ); - } - } - - // Preserve script evaluation history - destElements = getAll( clone, "script" ); - if ( destElements.length > 0 ) { - setGlobalEval( destElements, !inPage && getAll( elem, "script" ) ); - } - - // Return the cloned set - return clone; - }, - - cleanData: function( elems ) { - var data, elem, type, - special = jQuery.event.special, - i = 0; - - for ( ; ( elem = elems[ i ] ) !== undefined; i++ ) { - if ( acceptData( elem ) ) { - if ( ( data = elem[ dataPriv.expando ] ) ) { - if ( data.events ) { - for ( type in data.events ) { - if ( special[ type ] ) { - jQuery.event.remove( elem, type ); - - // This is a shortcut to avoid jQuery.event.remove's overhead - } else { - jQuery.removeEvent( elem, type, data.handle ); - } - } - } - - // Support: Chrome <=35 - 45+ - // Assign undefined instead of using delete, see Data#remove - elem[ dataPriv.expando ] = undefined; - } - if ( elem[ dataUser.expando ] ) { - - // Support: Chrome <=35 - 45+ - // Assign undefined instead of using delete, see Data#remove - elem[ dataUser.expando ] = undefined; - } - } - } - } -} ); - -jQuery.fn.extend( { - detach: function( selector ) { - return remove( this, selector, true ); - }, - - remove: function( selector ) { - return remove( this, selector ); - }, - - text: function( value ) { - return access( this, function( value ) { - return value === undefined ? - jQuery.text( this ) : - this.empty().each( function() { - if ( this.nodeType === 1 || this.nodeType === 11 || this.nodeType === 9 ) { - this.textContent = value; - } - } ); - }, null, value, arguments.length ); - }, - - append: function() { - return domManip( this, arguments, function( elem ) { - if ( this.nodeType === 1 || this.nodeType === 11 || this.nodeType === 9 ) { - var target = manipulationTarget( this, elem ); - target.appendChild( elem ); - } - } ); - }, - - prepend: function() { - return domManip( this, arguments, function( elem ) { - if ( this.nodeType === 1 || this.nodeType === 11 || this.nodeType === 9 ) { - var target = manipulationTarget( this, elem ); - target.insertBefore( elem, target.firstChild ); - } - } ); - }, - - before: function() { - return domManip( this, arguments, function( elem ) { - if ( this.parentNode ) { - this.parentNode.insertBefore( elem, this ); - } - } ); - }, - - after: function() { - return domManip( this, arguments, function( elem ) { - if ( this.parentNode ) { - this.parentNode.insertBefore( elem, this.nextSibling ); - } - } ); - }, - - empty: function() { - var elem, - i = 0; - - for ( ; ( elem = this[ i ] ) != null; i++ ) { - if ( elem.nodeType === 1 ) { - - // Prevent memory leaks - jQuery.cleanData( getAll( elem, false ) ); - - // Remove any remaining nodes - elem.textContent = ""; - } - } - - return this; - }, - - clone: function( dataAndEvents, deepDataAndEvents ) { - dataAndEvents = dataAndEvents == null ? false : dataAndEvents; - deepDataAndEvents = deepDataAndEvents == null ? dataAndEvents : deepDataAndEvents; - - return this.map( function() { - return jQuery.clone( this, dataAndEvents, deepDataAndEvents ); - } ); - }, - - html: function( value ) { - return access( this, function( value ) { - var elem = this[ 0 ] || {}, - i = 0, - l = this.length; - - if ( value === undefined && elem.nodeType === 1 ) { - return elem.innerHTML; - } - - // See if we can take a shortcut and just use innerHTML - if ( typeof value === "string" && !rnoInnerhtml.test( value ) && - !wrapMap[ ( rtagName.exec( value ) || [ "", "" ] )[ 1 ].toLowerCase() ] ) { - - value = jQuery.htmlPrefilter( value ); - - try { - for ( ; i < l; i++ ) { - elem = this[ i ] || {}; - - // Remove element nodes and prevent memory leaks - if ( elem.nodeType === 1 ) { - jQuery.cleanData( getAll( elem, false ) ); - elem.innerHTML = value; - } - } - - elem = 0; - - // If using innerHTML throws an exception, use the fallback method - } catch ( e ) {} - } - - if ( elem ) { - this.empty().append( value ); - } - }, null, value, arguments.length ); - }, - - replaceWith: function() { - var ignored = []; - - // Make the changes, replacing each non-ignored context element with the new content - return domManip( this, arguments, function( elem ) { - var parent = this.parentNode; - - if ( jQuery.inArray( this, ignored ) < 0 ) { - jQuery.cleanData( getAll( this ) ); - if ( parent ) { - parent.replaceChild( elem, this ); - } - } - - // Force callback invocation - }, ignored ); - } -} ); - -jQuery.each( { - appendTo: "append", - prependTo: "prepend", - insertBefore: "before", - insertAfter: "after", - replaceAll: "replaceWith" -}, function( name, original ) { - jQuery.fn[ name ] = function( selector ) { - var elems, - ret = [], - insert = jQuery( selector ), - last = insert.length - 1, - i = 0; - - for ( ; i <= last; i++ ) { - elems = i === last ? this : this.clone( true ); - jQuery( insert[ i ] )[ original ]( elems ); - - // Support: Android <=4.0 only, PhantomJS 1 only - // .get() because push.apply(_, arraylike) throws on ancient WebKit - push.apply( ret, elems.get() ); - } - - return this.pushStack( ret ); - }; -} ); -var rnumnonpx = new RegExp( "^(" + pnum + ")(?!px)[a-z%]+$", "i" ); - -var getStyles = function( elem ) { - - // Support: IE <=11 only, Firefox <=30 (#15098, #14150) - // IE throws on elements created in popups - // FF meanwhile throws on frame elements through "defaultView.getComputedStyle" - var view = elem.ownerDocument.defaultView; - - if ( !view || !view.opener ) { - view = window; - } - - return view.getComputedStyle( elem ); - }; - -var swap = function( elem, options, callback ) { - var ret, name, - old = {}; - - // Remember the old values, and insert the new ones - for ( name in options ) { - old[ name ] = elem.style[ name ]; - elem.style[ name ] = options[ name ]; - } - - ret = callback.call( elem ); - - // Revert the old values - for ( name in options ) { - elem.style[ name ] = old[ name ]; - } - - return ret; -}; - - -var rboxStyle = new RegExp( cssExpand.join( "|" ), "i" ); - - - -( function() { - - // Executing both pixelPosition & boxSizingReliable tests require only one layout - // so they're executed at the same time to save the second computation. - function computeStyleTests() { - - // This is a singleton, we need to execute it only once - if ( !div ) { - return; - } - - container.style.cssText = "position:absolute;left:-11111px;width:60px;" + - "margin-top:1px;padding:0;border:0"; - div.style.cssText = - "position:relative;display:block;box-sizing:border-box;overflow:scroll;" + - "margin:auto;border:1px;padding:1px;" + - "width:60%;top:1%"; - documentElement.appendChild( container ).appendChild( div ); - - var divStyle = window.getComputedStyle( div ); - pixelPositionVal = divStyle.top !== "1%"; - - // Support: Android 4.0 - 4.3 only, Firefox <=3 - 44 - reliableMarginLeftVal = roundPixelMeasures( divStyle.marginLeft ) === 12; - - // Support: Android 4.0 - 4.3 only, Safari <=9.1 - 10.1, iOS <=7.0 - 9.3 - // Some styles come back with percentage values, even though they shouldn't - div.style.right = "60%"; - pixelBoxStylesVal = roundPixelMeasures( divStyle.right ) === 36; - - // Support: IE 9 - 11 only - // Detect misreporting of content dimensions for box-sizing:border-box elements - boxSizingReliableVal = roundPixelMeasures( divStyle.width ) === 36; - - // Support: IE 9 only - // Detect overflow:scroll screwiness (gh-3699) - // Support: Chrome <=64 - // Don't get tricked when zoom affects offsetWidth (gh-4029) - div.style.position = "absolute"; - scrollboxSizeVal = roundPixelMeasures( div.offsetWidth / 3 ) === 12; - - documentElement.removeChild( container ); - - // Nullify the div so it wouldn't be stored in the memory and - // it will also be a sign that checks already performed - div = null; - } - - function roundPixelMeasures( measure ) { - return Math.round( parseFloat( measure ) ); - } - - var pixelPositionVal, boxSizingReliableVal, scrollboxSizeVal, pixelBoxStylesVal, - reliableTrDimensionsVal, reliableMarginLeftVal, - container = document.createElement( "div" ), - div = document.createElement( "div" ); - - // Finish early in limited (non-browser) environments - if ( !div.style ) { - return; - } - - // Support: IE <=9 - 11 only - // Style of cloned element affects source element cloned (#8908) - div.style.backgroundClip = "content-box"; - div.cloneNode( true ).style.backgroundClip = ""; - support.clearCloneStyle = div.style.backgroundClip === "content-box"; - - jQuery.extend( support, { - boxSizingReliable: function() { - computeStyleTests(); - return boxSizingReliableVal; - }, - pixelBoxStyles: function() { - computeStyleTests(); - return pixelBoxStylesVal; - }, - pixelPosition: function() { - computeStyleTests(); - return pixelPositionVal; - }, - reliableMarginLeft: function() { - computeStyleTests(); - return reliableMarginLeftVal; - }, - scrollboxSize: function() { - computeStyleTests(); - return scrollboxSizeVal; - }, - - // Support: IE 9 - 11+, Edge 15 - 18+ - // IE/Edge misreport `getComputedStyle` of table rows with width/height - // set in CSS while `offset*` properties report correct values. - // Behavior in IE 9 is more subtle than in newer versions & it passes - // some versions of this test; make sure not to make it pass there! - // - // Support: Firefox 70+ - // Only Firefox includes border widths - // in computed dimensions. (gh-4529) - reliableTrDimensions: function() { - var table, tr, trChild, trStyle; - if ( reliableTrDimensionsVal == null ) { - table = document.createElement( "table" ); - tr = document.createElement( "tr" ); - trChild = document.createElement( "div" ); - - table.style.cssText = "position:absolute;left:-11111px;border-collapse:separate"; - tr.style.cssText = "border:1px solid"; - - // Support: Chrome 86+ - // Height set through cssText does not get applied. - // Computed height then comes back as 0. - tr.style.height = "1px"; - trChild.style.height = "9px"; - - // Support: Android 8 Chrome 86+ - // In our bodyBackground.html iframe, - // display for all div elements is set to "inline", - // which causes a problem only in Android 8 Chrome 86. - // Ensuring the div is display: block - // gets around this issue. - trChild.style.display = "block"; - - documentElement - .appendChild( table ) - .appendChild( tr ) - .appendChild( trChild ); - - trStyle = window.getComputedStyle( tr ); - reliableTrDimensionsVal = ( parseInt( trStyle.height, 10 ) + - parseInt( trStyle.borderTopWidth, 10 ) + - parseInt( trStyle.borderBottomWidth, 10 ) ) === tr.offsetHeight; - - documentElement.removeChild( table ); - } - return reliableTrDimensionsVal; - } - } ); -} )(); - - -function curCSS( elem, name, computed ) { - var width, minWidth, maxWidth, ret, - - // Support: Firefox 51+ - // Retrieving style before computed somehow - // fixes an issue with getting wrong values - // on detached elements - style = elem.style; - - computed = computed || getStyles( elem ); - - // getPropertyValue is needed for: - // .css('filter') (IE 9 only, #12537) - // .css('--customProperty) (#3144) - if ( computed ) { - ret = computed.getPropertyValue( name ) || computed[ name ]; - - if ( ret === "" && !isAttached( elem ) ) { - ret = jQuery.style( elem, name ); - } - - // A tribute to the "awesome hack by Dean Edwards" - // Android Browser returns percentage for some values, - // but width seems to be reliably pixels. - // This is against the CSSOM draft spec: - // https://drafts.csswg.org/cssom/#resolved-values - if ( !support.pixelBoxStyles() && rnumnonpx.test( ret ) && rboxStyle.test( name ) ) { - - // Remember the original values - width = style.width; - minWidth = style.minWidth; - maxWidth = style.maxWidth; - - // Put in the new values to get a computed value out - style.minWidth = style.maxWidth = style.width = ret; - ret = computed.width; - - // Revert the changed values - style.width = width; - style.minWidth = minWidth; - style.maxWidth = maxWidth; - } - } - - return ret !== undefined ? - - // Support: IE <=9 - 11 only - // IE returns zIndex value as an integer. - ret + "" : - ret; -} - - -function addGetHookIf( conditionFn, hookFn ) { - - // Define the hook, we'll check on the first run if it's really needed. - return { - get: function() { - if ( conditionFn() ) { - - // Hook not needed (or it's not possible to use it due - // to missing dependency), remove it. - delete this.get; - return; - } - - // Hook needed; redefine it so that the support test is not executed again. - return ( this.get = hookFn ).apply( this, arguments ); - } - }; -} - - -var cssPrefixes = [ "Webkit", "Moz", "ms" ], - emptyStyle = document.createElement( "div" ).style, - vendorProps = {}; - -// Return a vendor-prefixed property or undefined -function vendorPropName( name ) { - - // Check for vendor prefixed names - var capName = name[ 0 ].toUpperCase() + name.slice( 1 ), - i = cssPrefixes.length; - - while ( i-- ) { - name = cssPrefixes[ i ] + capName; - if ( name in emptyStyle ) { - return name; - } - } -} - -// Return a potentially-mapped jQuery.cssProps or vendor prefixed property -function finalPropName( name ) { - var final = jQuery.cssProps[ name ] || vendorProps[ name ]; - - if ( final ) { - return final; - } - if ( name in emptyStyle ) { - return name; - } - return vendorProps[ name ] = vendorPropName( name ) || name; -} - - -var - - // Swappable if display is none or starts with table - // except "table", "table-cell", or "table-caption" - // See here for display values: https://developer.mozilla.org/en-US/docs/CSS/display - rdisplayswap = /^(none|table(?!-c[ea]).+)/, - rcustomProp = /^--/, - cssShow = { position: "absolute", visibility: "hidden", display: "block" }, - cssNormalTransform = { - letterSpacing: "0", - fontWeight: "400" - }; - -function setPositiveNumber( _elem, value, subtract ) { - - // Any relative (+/-) values have already been - // normalized at this point - var matches = rcssNum.exec( value ); - return matches ? - - // Guard against undefined "subtract", e.g., when used as in cssHooks - Math.max( 0, matches[ 2 ] - ( subtract || 0 ) ) + ( matches[ 3 ] || "px" ) : - value; -} - -function boxModelAdjustment( elem, dimension, box, isBorderBox, styles, computedVal ) { - var i = dimension === "width" ? 1 : 0, - extra = 0, - delta = 0; - - // Adjustment may not be necessary - if ( box === ( isBorderBox ? "border" : "content" ) ) { - return 0; - } - - for ( ; i < 4; i += 2 ) { - - // Both box models exclude margin - if ( box === "margin" ) { - delta += jQuery.css( elem, box + cssExpand[ i ], true, styles ); - } - - // If we get here with a content-box, we're seeking "padding" or "border" or "margin" - if ( !isBorderBox ) { - - // Add padding - delta += jQuery.css( elem, "padding" + cssExpand[ i ], true, styles ); - - // For "border" or "margin", add border - if ( box !== "padding" ) { - delta += jQuery.css( elem, "border" + cssExpand[ i ] + "Width", true, styles ); - - // But still keep track of it otherwise - } else { - extra += jQuery.css( elem, "border" + cssExpand[ i ] + "Width", true, styles ); - } - - // If we get here with a border-box (content + padding + border), we're seeking "content" or - // "padding" or "margin" - } else { - - // For "content", subtract padding - if ( box === "content" ) { - delta -= jQuery.css( elem, "padding" + cssExpand[ i ], true, styles ); - } - - // For "content" or "padding", subtract border - if ( box !== "margin" ) { - delta -= jQuery.css( elem, "border" + cssExpand[ i ] + "Width", true, styles ); - } - } - } - - // Account for positive content-box scroll gutter when requested by providing computedVal - if ( !isBorderBox && computedVal >= 0 ) { - - // offsetWidth/offsetHeight is a rounded sum of content, padding, scroll gutter, and border - // Assuming integer scroll gutter, subtract the rest and round down - delta += Math.max( 0, Math.ceil( - elem[ "offset" + dimension[ 0 ].toUpperCase() + dimension.slice( 1 ) ] - - computedVal - - delta - - extra - - 0.5 - - // If offsetWidth/offsetHeight is unknown, then we can't determine content-box scroll gutter - // Use an explicit zero to avoid NaN (gh-3964) - ) ) || 0; - } - - return delta; -} - -function getWidthOrHeight( elem, dimension, extra ) { - - // Start with computed style - var styles = getStyles( elem ), - - // To avoid forcing a reflow, only fetch boxSizing if we need it (gh-4322). - // Fake content-box until we know it's needed to know the true value. - boxSizingNeeded = !support.boxSizingReliable() || extra, - isBorderBox = boxSizingNeeded && - jQuery.css( elem, "boxSizing", false, styles ) === "border-box", - valueIsBorderBox = isBorderBox, - - val = curCSS( elem, dimension, styles ), - offsetProp = "offset" + dimension[ 0 ].toUpperCase() + dimension.slice( 1 ); - - // Support: Firefox <=54 - // Return a confounding non-pixel value or feign ignorance, as appropriate. - if ( rnumnonpx.test( val ) ) { - if ( !extra ) { - return val; - } - val = "auto"; - } - - - // Support: IE 9 - 11 only - // Use offsetWidth/offsetHeight for when box sizing is unreliable. - // In those cases, the computed value can be trusted to be border-box. - if ( ( !support.boxSizingReliable() && isBorderBox || - - // Support: IE 10 - 11+, Edge 15 - 18+ - // IE/Edge misreport `getComputedStyle` of table rows with width/height - // set in CSS while `offset*` properties report correct values. - // Interestingly, in some cases IE 9 doesn't suffer from this issue. - !support.reliableTrDimensions() && nodeName( elem, "tr" ) || - - // Fall back to offsetWidth/offsetHeight when value is "auto" - // This happens for inline elements with no explicit setting (gh-3571) - val === "auto" || - - // Support: Android <=4.1 - 4.3 only - // Also use offsetWidth/offsetHeight for misreported inline dimensions (gh-3602) - !parseFloat( val ) && jQuery.css( elem, "display", false, styles ) === "inline" ) && - - // Make sure the element is visible & connected - elem.getClientRects().length ) { - - isBorderBox = jQuery.css( elem, "boxSizing", false, styles ) === "border-box"; - - // Where available, offsetWidth/offsetHeight approximate border box dimensions. - // Where not available (e.g., SVG), assume unreliable box-sizing and interpret the - // retrieved value as a content box dimension. - valueIsBorderBox = offsetProp in elem; - if ( valueIsBorderBox ) { - val = elem[ offsetProp ]; - } - } - - // Normalize "" and auto - val = parseFloat( val ) || 0; - - // Adjust for the element's box model - return ( val + - boxModelAdjustment( - elem, - dimension, - extra || ( isBorderBox ? "border" : "content" ), - valueIsBorderBox, - styles, - - // Provide the current computed size to request scroll gutter calculation (gh-3589) - val - ) - ) + "px"; -} - -jQuery.extend( { - - // Add in style property hooks for overriding the default - // behavior of getting and setting a style property - cssHooks: { - opacity: { - get: function( elem, computed ) { - if ( computed ) { - - // We should always get a number back from opacity - var ret = curCSS( elem, "opacity" ); - return ret === "" ? "1" : ret; - } - } - } - }, - - // Don't automatically add "px" to these possibly-unitless properties - cssNumber: { - "animationIterationCount": true, - "columnCount": true, - "fillOpacity": true, - "flexGrow": true, - "flexShrink": true, - "fontWeight": true, - "gridArea": true, - "gridColumn": true, - "gridColumnEnd": true, - "gridColumnStart": true, - "gridRow": true, - "gridRowEnd": true, - "gridRowStart": true, - "lineHeight": true, - "opacity": true, - "order": true, - "orphans": true, - "widows": true, - "zIndex": true, - "zoom": true - }, - - // Add in properties whose names you wish to fix before - // setting or getting the value - cssProps: {}, - - // Get and set the style property on a DOM Node - style: function( elem, name, value, extra ) { - - // Don't set styles on text and comment nodes - if ( !elem || elem.nodeType === 3 || elem.nodeType === 8 || !elem.style ) { - return; - } - - // Make sure that we're working with the right name - var ret, type, hooks, - origName = camelCase( name ), - isCustomProp = rcustomProp.test( name ), - style = elem.style; - - // Make sure that we're working with the right name. We don't - // want to query the value if it is a CSS custom property - // since they are user-defined. - if ( !isCustomProp ) { - name = finalPropName( origName ); - } - - // Gets hook for the prefixed version, then unprefixed version - hooks = jQuery.cssHooks[ name ] || jQuery.cssHooks[ origName ]; - - // Check if we're setting a value - if ( value !== undefined ) { - type = typeof value; - - // Convert "+=" or "-=" to relative numbers (#7345) - if ( type === "string" && ( ret = rcssNum.exec( value ) ) && ret[ 1 ] ) { - value = adjustCSS( elem, name, ret ); - - // Fixes bug #9237 - type = "number"; - } - - // Make sure that null and NaN values aren't set (#7116) - if ( value == null || value !== value ) { - return; - } - - // If a number was passed in, add the unit (except for certain CSS properties) - // The isCustomProp check can be removed in jQuery 4.0 when we only auto-append - // "px" to a few hardcoded values. - if ( type === "number" && !isCustomProp ) { - value += ret && ret[ 3 ] || ( jQuery.cssNumber[ origName ] ? "" : "px" ); - } - - // background-* props affect original clone's values - if ( !support.clearCloneStyle && value === "" && name.indexOf( "background" ) === 0 ) { - style[ name ] = "inherit"; - } - - // If a hook was provided, use that value, otherwise just set the specified value - if ( !hooks || !( "set" in hooks ) || - ( value = hooks.set( elem, value, extra ) ) !== undefined ) { - - if ( isCustomProp ) { - style.setProperty( name, value ); - } else { - style[ name ] = value; - } - } - - } else { - - // If a hook was provided get the non-computed value from there - if ( hooks && "get" in hooks && - ( ret = hooks.get( elem, false, extra ) ) !== undefined ) { - - return ret; - } - - // Otherwise just get the value from the style object - return style[ name ]; - } - }, - - css: function( elem, name, extra, styles ) { - var val, num, hooks, - origName = camelCase( name ), - isCustomProp = rcustomProp.test( name ); - - // Make sure that we're working with the right name. We don't - // want to modify the value if it is a CSS custom property - // since they are user-defined. - if ( !isCustomProp ) { - name = finalPropName( origName ); - } - - // Try prefixed name followed by the unprefixed name - hooks = jQuery.cssHooks[ name ] || jQuery.cssHooks[ origName ]; - - // If a hook was provided get the computed value from there - if ( hooks && "get" in hooks ) { - val = hooks.get( elem, true, extra ); - } - - // Otherwise, if a way to get the computed value exists, use that - if ( val === undefined ) { - val = curCSS( elem, name, styles ); - } - - // Convert "normal" to computed value - if ( val === "normal" && name in cssNormalTransform ) { - val = cssNormalTransform[ name ]; - } - - // Make numeric if forced or a qualifier was provided and val looks numeric - if ( extra === "" || extra ) { - num = parseFloat( val ); - return extra === true || isFinite( num ) ? num || 0 : val; - } - - return val; - } -} ); - -jQuery.each( [ "height", "width" ], function( _i, dimension ) { - jQuery.cssHooks[ dimension ] = { - get: function( elem, computed, extra ) { - if ( computed ) { - - // Certain elements can have dimension info if we invisibly show them - // but it must have a current display style that would benefit - return rdisplayswap.test( jQuery.css( elem, "display" ) ) && - - // Support: Safari 8+ - // Table columns in Safari have non-zero offsetWidth & zero - // getBoundingClientRect().width unless display is changed. - // Support: IE <=11 only - // Running getBoundingClientRect on a disconnected node - // in IE throws an error. - ( !elem.getClientRects().length || !elem.getBoundingClientRect().width ) ? - swap( elem, cssShow, function() { - return getWidthOrHeight( elem, dimension, extra ); - } ) : - getWidthOrHeight( elem, dimension, extra ); - } - }, - - set: function( elem, value, extra ) { - var matches, - styles = getStyles( elem ), - - // Only read styles.position if the test has a chance to fail - // to avoid forcing a reflow. - scrollboxSizeBuggy = !support.scrollboxSize() && - styles.position === "absolute", - - // To avoid forcing a reflow, only fetch boxSizing if we need it (gh-3991) - boxSizingNeeded = scrollboxSizeBuggy || extra, - isBorderBox = boxSizingNeeded && - jQuery.css( elem, "boxSizing", false, styles ) === "border-box", - subtract = extra ? - boxModelAdjustment( - elem, - dimension, - extra, - isBorderBox, - styles - ) : - 0; - - // Account for unreliable border-box dimensions by comparing offset* to computed and - // faking a content-box to get border and padding (gh-3699) - if ( isBorderBox && scrollboxSizeBuggy ) { - subtract -= Math.ceil( - elem[ "offset" + dimension[ 0 ].toUpperCase() + dimension.slice( 1 ) ] - - parseFloat( styles[ dimension ] ) - - boxModelAdjustment( elem, dimension, "border", false, styles ) - - 0.5 - ); - } - - // Convert to pixels if value adjustment is needed - if ( subtract && ( matches = rcssNum.exec( value ) ) && - ( matches[ 3 ] || "px" ) !== "px" ) { - - elem.style[ dimension ] = value; - value = jQuery.css( elem, dimension ); - } - - return setPositiveNumber( elem, value, subtract ); - } - }; -} ); - -jQuery.cssHooks.marginLeft = addGetHookIf( support.reliableMarginLeft, - function( elem, computed ) { - if ( computed ) { - return ( parseFloat( curCSS( elem, "marginLeft" ) ) || - elem.getBoundingClientRect().left - - swap( elem, { marginLeft: 0 }, function() { - return elem.getBoundingClientRect().left; - } ) - ) + "px"; - } - } -); - -// These hooks are used by animate to expand properties -jQuery.each( { - margin: "", - padding: "", - border: "Width" -}, function( prefix, suffix ) { - jQuery.cssHooks[ prefix + suffix ] = { - expand: function( value ) { - var i = 0, - expanded = {}, - - // Assumes a single number if not a string - parts = typeof value === "string" ? value.split( " " ) : [ value ]; - - for ( ; i < 4; i++ ) { - expanded[ prefix + cssExpand[ i ] + suffix ] = - parts[ i ] || parts[ i - 2 ] || parts[ 0 ]; - } - - return expanded; - } - }; - - if ( prefix !== "margin" ) { - jQuery.cssHooks[ prefix + suffix ].set = setPositiveNumber; - } -} ); - -jQuery.fn.extend( { - css: function( name, value ) { - return access( this, function( elem, name, value ) { - var styles, len, - map = {}, - i = 0; - - if ( Array.isArray( name ) ) { - styles = getStyles( elem ); - len = name.length; - - for ( ; i < len; i++ ) { - map[ name[ i ] ] = jQuery.css( elem, name[ i ], false, styles ); - } - - return map; - } - - return value !== undefined ? - jQuery.style( elem, name, value ) : - jQuery.css( elem, name ); - }, name, value, arguments.length > 1 ); - } -} ); - - -function Tween( elem, options, prop, end, easing ) { - return new Tween.prototype.init( elem, options, prop, end, easing ); -} -jQuery.Tween = Tween; - -Tween.prototype = { - constructor: Tween, - init: function( elem, options, prop, end, easing, unit ) { - this.elem = elem; - this.prop = prop; - this.easing = easing || jQuery.easing._default; - this.options = options; - this.start = this.now = this.cur(); - this.end = end; - this.unit = unit || ( jQuery.cssNumber[ prop ] ? "" : "px" ); - }, - cur: function() { - var hooks = Tween.propHooks[ this.prop ]; - - return hooks && hooks.get ? - hooks.get( this ) : - Tween.propHooks._default.get( this ); - }, - run: function( percent ) { - var eased, - hooks = Tween.propHooks[ this.prop ]; - - if ( this.options.duration ) { - this.pos = eased = jQuery.easing[ this.easing ]( - percent, this.options.duration * percent, 0, 1, this.options.duration - ); - } else { - this.pos = eased = percent; - } - this.now = ( this.end - this.start ) * eased + this.start; - - if ( this.options.step ) { - this.options.step.call( this.elem, this.now, this ); - } - - if ( hooks && hooks.set ) { - hooks.set( this ); - } else { - Tween.propHooks._default.set( this ); - } - return this; - } -}; - -Tween.prototype.init.prototype = Tween.prototype; - -Tween.propHooks = { - _default: { - get: function( tween ) { - var result; - - // Use a property on the element directly when it is not a DOM element, - // or when there is no matching style property that exists. - if ( tween.elem.nodeType !== 1 || - tween.elem[ tween.prop ] != null && tween.elem.style[ tween.prop ] == null ) { - return tween.elem[ tween.prop ]; - } - - // Passing an empty string as a 3rd parameter to .css will automatically - // attempt a parseFloat and fallback to a string if the parse fails. - // Simple values such as "10px" are parsed to Float; - // complex values such as "rotate(1rad)" are returned as-is. - result = jQuery.css( tween.elem, tween.prop, "" ); - - // Empty strings, null, undefined and "auto" are converted to 0. - return !result || result === "auto" ? 0 : result; - }, - set: function( tween ) { - - // Use step hook for back compat. - // Use cssHook if its there. - // Use .style if available and use plain properties where available. - if ( jQuery.fx.step[ tween.prop ] ) { - jQuery.fx.step[ tween.prop ]( tween ); - } else if ( tween.elem.nodeType === 1 && ( - jQuery.cssHooks[ tween.prop ] || - tween.elem.style[ finalPropName( tween.prop ) ] != null ) ) { - jQuery.style( tween.elem, tween.prop, tween.now + tween.unit ); - } else { - tween.elem[ tween.prop ] = tween.now; - } - } - } -}; - -// Support: IE <=9 only -// Panic based approach to setting things on disconnected nodes -Tween.propHooks.scrollTop = Tween.propHooks.scrollLeft = { - set: function( tween ) { - if ( tween.elem.nodeType && tween.elem.parentNode ) { - tween.elem[ tween.prop ] = tween.now; - } - } -}; - -jQuery.easing = { - linear: function( p ) { - return p; - }, - swing: function( p ) { - return 0.5 - Math.cos( p * Math.PI ) / 2; - }, - _default: "swing" -}; - -jQuery.fx = Tween.prototype.init; - -// Back compat <1.8 extension point -jQuery.fx.step = {}; - - - - -var - fxNow, inProgress, - rfxtypes = /^(?:toggle|show|hide)$/, - rrun = /queueHooks$/; - -function schedule() { - if ( inProgress ) { - if ( document.hidden === false && window.requestAnimationFrame ) { - window.requestAnimationFrame( schedule ); - } else { - window.setTimeout( schedule, jQuery.fx.interval ); - } - - jQuery.fx.tick(); - } -} - -// Animations created synchronously will run synchronously -function createFxNow() { - window.setTimeout( function() { - fxNow = undefined; - } ); - return ( fxNow = Date.now() ); -} - -// Generate parameters to create a standard animation -function genFx( type, includeWidth ) { - var which, - i = 0, - attrs = { height: type }; - - // If we include width, step value is 1 to do all cssExpand values, - // otherwise step value is 2 to skip over Left and Right - includeWidth = includeWidth ? 1 : 0; - for ( ; i < 4; i += 2 - includeWidth ) { - which = cssExpand[ i ]; - attrs[ "margin" + which ] = attrs[ "padding" + which ] = type; - } - - if ( includeWidth ) { - attrs.opacity = attrs.width = type; - } - - return attrs; -} - -function createTween( value, prop, animation ) { - var tween, - collection = ( Animation.tweeners[ prop ] || [] ).concat( Animation.tweeners[ "*" ] ), - index = 0, - length = collection.length; - for ( ; index < length; index++ ) { - if ( ( tween = collection[ index ].call( animation, prop, value ) ) ) { - - // We're done with this property - return tween; - } - } -} - -function defaultPrefilter( elem, props, opts ) { - var prop, value, toggle, hooks, oldfire, propTween, restoreDisplay, display, - isBox = "width" in props || "height" in props, - anim = this, - orig = {}, - style = elem.style, - hidden = elem.nodeType && isHiddenWithinTree( elem ), - dataShow = dataPriv.get( elem, "fxshow" ); - - // Queue-skipping animations hijack the fx hooks - if ( !opts.queue ) { - hooks = jQuery._queueHooks( elem, "fx" ); - if ( hooks.unqueued == null ) { - hooks.unqueued = 0; - oldfire = hooks.empty.fire; - hooks.empty.fire = function() { - if ( !hooks.unqueued ) { - oldfire(); - } - }; - } - hooks.unqueued++; - - anim.always( function() { - - // Ensure the complete handler is called before this completes - anim.always( function() { - hooks.unqueued--; - if ( !jQuery.queue( elem, "fx" ).length ) { - hooks.empty.fire(); - } - } ); - } ); - } - - // Detect show/hide animations - for ( prop in props ) { - value = props[ prop ]; - if ( rfxtypes.test( value ) ) { - delete props[ prop ]; - toggle = toggle || value === "toggle"; - if ( value === ( hidden ? "hide" : "show" ) ) { - - // Pretend to be hidden if this is a "show" and - // there is still data from a stopped show/hide - if ( value === "show" && dataShow && dataShow[ prop ] !== undefined ) { - hidden = true; - - // Ignore all other no-op show/hide data - } else { - continue; - } - } - orig[ prop ] = dataShow && dataShow[ prop ] || jQuery.style( elem, prop ); - } - } - - // Bail out if this is a no-op like .hide().hide() - propTween = !jQuery.isEmptyObject( props ); - if ( !propTween && jQuery.isEmptyObject( orig ) ) { - return; - } - - // Restrict "overflow" and "display" styles during box animations - if ( isBox && elem.nodeType === 1 ) { - - // Support: IE <=9 - 11, Edge 12 - 15 - // Record all 3 overflow attributes because IE does not infer the shorthand - // from identically-valued overflowX and overflowY and Edge just mirrors - // the overflowX value there. - opts.overflow = [ style.overflow, style.overflowX, style.overflowY ]; - - // Identify a display type, preferring old show/hide data over the CSS cascade - restoreDisplay = dataShow && dataShow.display; - if ( restoreDisplay == null ) { - restoreDisplay = dataPriv.get( elem, "display" ); - } - display = jQuery.css( elem, "display" ); - if ( display === "none" ) { - if ( restoreDisplay ) { - display = restoreDisplay; - } else { - - // Get nonempty value(s) by temporarily forcing visibility - showHide( [ elem ], true ); - restoreDisplay = elem.style.display || restoreDisplay; - display = jQuery.css( elem, "display" ); - showHide( [ elem ] ); - } - } - - // Animate inline elements as inline-block - if ( display === "inline" || display === "inline-block" && restoreDisplay != null ) { - if ( jQuery.css( elem, "float" ) === "none" ) { - - // Restore the original display value at the end of pure show/hide animations - if ( !propTween ) { - anim.done( function() { - style.display = restoreDisplay; - } ); - if ( restoreDisplay == null ) { - display = style.display; - restoreDisplay = display === "none" ? "" : display; - } - } - style.display = "inline-block"; - } - } - } - - if ( opts.overflow ) { - style.overflow = "hidden"; - anim.always( function() { - style.overflow = opts.overflow[ 0 ]; - style.overflowX = opts.overflow[ 1 ]; - style.overflowY = opts.overflow[ 2 ]; - } ); - } - - // Implement show/hide animations - propTween = false; - for ( prop in orig ) { - - // General show/hide setup for this element animation - if ( !propTween ) { - if ( dataShow ) { - if ( "hidden" in dataShow ) { - hidden = dataShow.hidden; - } - } else { - dataShow = dataPriv.access( elem, "fxshow", { display: restoreDisplay } ); - } - - // Store hidden/visible for toggle so `.stop().toggle()` "reverses" - if ( toggle ) { - dataShow.hidden = !hidden; - } - - // Show elements before animating them - if ( hidden ) { - showHide( [ elem ], true ); - } - - /* eslint-disable no-loop-func */ - - anim.done( function() { - - /* eslint-enable no-loop-func */ - - // The final step of a "hide" animation is actually hiding the element - if ( !hidden ) { - showHide( [ elem ] ); - } - dataPriv.remove( elem, "fxshow" ); - for ( prop in orig ) { - jQuery.style( elem, prop, orig[ prop ] ); - } - } ); - } - - // Per-property setup - propTween = createTween( hidden ? dataShow[ prop ] : 0, prop, anim ); - if ( !( prop in dataShow ) ) { - dataShow[ prop ] = propTween.start; - if ( hidden ) { - propTween.end = propTween.start; - propTween.start = 0; - } - } - } -} - -function propFilter( props, specialEasing ) { - var index, name, easing, value, hooks; - - // camelCase, specialEasing and expand cssHook pass - for ( index in props ) { - name = camelCase( index ); - easing = specialEasing[ name ]; - value = props[ index ]; - if ( Array.isArray( value ) ) { - easing = value[ 1 ]; - value = props[ index ] = value[ 0 ]; - } - - if ( index !== name ) { - props[ name ] = value; - delete props[ index ]; - } - - hooks = jQuery.cssHooks[ name ]; - if ( hooks && "expand" in hooks ) { - value = hooks.expand( value ); - delete props[ name ]; - - // Not quite $.extend, this won't overwrite existing keys. - // Reusing 'index' because we have the correct "name" - for ( index in value ) { - if ( !( index in props ) ) { - props[ index ] = value[ index ]; - specialEasing[ index ] = easing; - } - } - } else { - specialEasing[ name ] = easing; - } - } -} - -function Animation( elem, properties, options ) { - var result, - stopped, - index = 0, - length = Animation.prefilters.length, - deferred = jQuery.Deferred().always( function() { - - // Don't match elem in the :animated selector - delete tick.elem; - } ), - tick = function() { - if ( stopped ) { - return false; - } - var currentTime = fxNow || createFxNow(), - remaining = Math.max( 0, animation.startTime + animation.duration - currentTime ), - - // Support: Android 2.3 only - // Archaic crash bug won't allow us to use `1 - ( 0.5 || 0 )` (#12497) - temp = remaining / animation.duration || 0, - percent = 1 - temp, - index = 0, - length = animation.tweens.length; - - for ( ; index < length; index++ ) { - animation.tweens[ index ].run( percent ); - } - - deferred.notifyWith( elem, [ animation, percent, remaining ] ); - - // If there's more to do, yield - if ( percent < 1 && length ) { - return remaining; - } - - // If this was an empty animation, synthesize a final progress notification - if ( !length ) { - deferred.notifyWith( elem, [ animation, 1, 0 ] ); - } - - // Resolve the animation and report its conclusion - deferred.resolveWith( elem, [ animation ] ); - return false; - }, - animation = deferred.promise( { - elem: elem, - props: jQuery.extend( {}, properties ), - opts: jQuery.extend( true, { - specialEasing: {}, - easing: jQuery.easing._default - }, options ), - originalProperties: properties, - originalOptions: options, - startTime: fxNow || createFxNow(), - duration: options.duration, - tweens: [], - createTween: function( prop, end ) { - var tween = jQuery.Tween( elem, animation.opts, prop, end, - animation.opts.specialEasing[ prop ] || animation.opts.easing ); - animation.tweens.push( tween ); - return tween; - }, - stop: function( gotoEnd ) { - var index = 0, - - // If we are going to the end, we want to run all the tweens - // otherwise we skip this part - length = gotoEnd ? animation.tweens.length : 0; - if ( stopped ) { - return this; - } - stopped = true; - for ( ; index < length; index++ ) { - animation.tweens[ index ].run( 1 ); - } - - // Resolve when we played the last frame; otherwise, reject - if ( gotoEnd ) { - deferred.notifyWith( elem, [ animation, 1, 0 ] ); - deferred.resolveWith( elem, [ animation, gotoEnd ] ); - } else { - deferred.rejectWith( elem, [ animation, gotoEnd ] ); - } - return this; - } - } ), - props = animation.props; - - propFilter( props, animation.opts.specialEasing ); - - for ( ; index < length; index++ ) { - result = Animation.prefilters[ index ].call( animation, elem, props, animation.opts ); - if ( result ) { - if ( isFunction( result.stop ) ) { - jQuery._queueHooks( animation.elem, animation.opts.queue ).stop = - result.stop.bind( result ); - } - return result; - } - } - - jQuery.map( props, createTween, animation ); - - if ( isFunction( animation.opts.start ) ) { - animation.opts.start.call( elem, animation ); - } - - // Attach callbacks from options - animation - .progress( animation.opts.progress ) - .done( animation.opts.done, animation.opts.complete ) - .fail( animation.opts.fail ) - .always( animation.opts.always ); - - jQuery.fx.timer( - jQuery.extend( tick, { - elem: elem, - anim: animation, - queue: animation.opts.queue - } ) - ); - - return animation; -} - -jQuery.Animation = jQuery.extend( Animation, { - - tweeners: { - "*": [ function( prop, value ) { - var tween = this.createTween( prop, value ); - adjustCSS( tween.elem, prop, rcssNum.exec( value ), tween ); - return tween; - } ] - }, - - tweener: function( props, callback ) { - if ( isFunction( props ) ) { - callback = props; - props = [ "*" ]; - } else { - props = props.match( rnothtmlwhite ); - } - - var prop, - index = 0, - length = props.length; - - for ( ; index < length; index++ ) { - prop = props[ index ]; - Animation.tweeners[ prop ] = Animation.tweeners[ prop ] || []; - Animation.tweeners[ prop ].unshift( callback ); - } - }, - - prefilters: [ defaultPrefilter ], - - prefilter: function( callback, prepend ) { - if ( prepend ) { - Animation.prefilters.unshift( callback ); - } else { - Animation.prefilters.push( callback ); - } - } -} ); - -jQuery.speed = function( speed, easing, fn ) { - var opt = speed && typeof speed === "object" ? jQuery.extend( {}, speed ) : { - complete: fn || !fn && easing || - isFunction( speed ) && speed, - duration: speed, - easing: fn && easing || easing && !isFunction( easing ) && easing - }; - - // Go to the end state if fx are off - if ( jQuery.fx.off ) { - opt.duration = 0; - - } else { - if ( typeof opt.duration !== "number" ) { - if ( opt.duration in jQuery.fx.speeds ) { - opt.duration = jQuery.fx.speeds[ opt.duration ]; - - } else { - opt.duration = jQuery.fx.speeds._default; - } - } - } - - // Normalize opt.queue - true/undefined/null -> "fx" - if ( opt.queue == null || opt.queue === true ) { - opt.queue = "fx"; - } - - // Queueing - opt.old = opt.complete; - - opt.complete = function() { - if ( isFunction( opt.old ) ) { - opt.old.call( this ); - } - - if ( opt.queue ) { - jQuery.dequeue( this, opt.queue ); - } - }; - - return opt; -}; - -jQuery.fn.extend( { - fadeTo: function( speed, to, easing, callback ) { - - // Show any hidden elements after setting opacity to 0 - return this.filter( isHiddenWithinTree ).css( "opacity", 0 ).show() - - // Animate to the value specified - .end().animate( { opacity: to }, speed, easing, callback ); - }, - animate: function( prop, speed, easing, callback ) { - var empty = jQuery.isEmptyObject( prop ), - optall = jQuery.speed( speed, easing, callback ), - doAnimation = function() { - - // Operate on a copy of prop so per-property easing won't be lost - var anim = Animation( this, jQuery.extend( {}, prop ), optall ); - - // Empty animations, or finishing resolves immediately - if ( empty || dataPriv.get( this, "finish" ) ) { - anim.stop( true ); - } - }; - - doAnimation.finish = doAnimation; - - return empty || optall.queue === false ? - this.each( doAnimation ) : - this.queue( optall.queue, doAnimation ); - }, - stop: function( type, clearQueue, gotoEnd ) { - var stopQueue = function( hooks ) { - var stop = hooks.stop; - delete hooks.stop; - stop( gotoEnd ); - }; - - if ( typeof type !== "string" ) { - gotoEnd = clearQueue; - clearQueue = type; - type = undefined; - } - if ( clearQueue ) { - this.queue( type || "fx", [] ); - } - - return this.each( function() { - var dequeue = true, - index = type != null && type + "queueHooks", - timers = jQuery.timers, - data = dataPriv.get( this ); - - if ( index ) { - if ( data[ index ] && data[ index ].stop ) { - stopQueue( data[ index ] ); - } - } else { - for ( index in data ) { - if ( data[ index ] && data[ index ].stop && rrun.test( index ) ) { - stopQueue( data[ index ] ); - } - } - } - - for ( index = timers.length; index--; ) { - if ( timers[ index ].elem === this && - ( type == null || timers[ index ].queue === type ) ) { - - timers[ index ].anim.stop( gotoEnd ); - dequeue = false; - timers.splice( index, 1 ); - } - } - - // Start the next in the queue if the last step wasn't forced. - // Timers currently will call their complete callbacks, which - // will dequeue but only if they were gotoEnd. - if ( dequeue || !gotoEnd ) { - jQuery.dequeue( this, type ); - } - } ); - }, - finish: function( type ) { - if ( type !== false ) { - type = type || "fx"; - } - return this.each( function() { - var index, - data = dataPriv.get( this ), - queue = data[ type + "queue" ], - hooks = data[ type + "queueHooks" ], - timers = jQuery.timers, - length = queue ? queue.length : 0; - - // Enable finishing flag on private data - data.finish = true; - - // Empty the queue first - jQuery.queue( this, type, [] ); - - if ( hooks && hooks.stop ) { - hooks.stop.call( this, true ); - } - - // Look for any active animations, and finish them - for ( index = timers.length; index--; ) { - if ( timers[ index ].elem === this && timers[ index ].queue === type ) { - timers[ index ].anim.stop( true ); - timers.splice( index, 1 ); - } - } - - // Look for any animations in the old queue and finish them - for ( index = 0; index < length; index++ ) { - if ( queue[ index ] && queue[ index ].finish ) { - queue[ index ].finish.call( this ); - } - } - - // Turn off finishing flag - delete data.finish; - } ); - } -} ); - -jQuery.each( [ "toggle", "show", "hide" ], function( _i, name ) { - var cssFn = jQuery.fn[ name ]; - jQuery.fn[ name ] = function( speed, easing, callback ) { - return speed == null || typeof speed === "boolean" ? - cssFn.apply( this, arguments ) : - this.animate( genFx( name, true ), speed, easing, callback ); - }; -} ); - -// Generate shortcuts for custom animations -jQuery.each( { - slideDown: genFx( "show" ), - slideUp: genFx( "hide" ), - slideToggle: genFx( "toggle" ), - fadeIn: { opacity: "show" }, - fadeOut: { opacity: "hide" }, - fadeToggle: { opacity: "toggle" } -}, function( name, props ) { - jQuery.fn[ name ] = function( speed, easing, callback ) { - return this.animate( props, speed, easing, callback ); - }; -} ); - -jQuery.timers = []; -jQuery.fx.tick = function() { - var timer, - i = 0, - timers = jQuery.timers; - - fxNow = Date.now(); - - for ( ; i < timers.length; i++ ) { - timer = timers[ i ]; - - // Run the timer and safely remove it when done (allowing for external removal) - if ( !timer() && timers[ i ] === timer ) { - timers.splice( i--, 1 ); - } - } - - if ( !timers.length ) { - jQuery.fx.stop(); - } - fxNow = undefined; -}; - -jQuery.fx.timer = function( timer ) { - jQuery.timers.push( timer ); - jQuery.fx.start(); -}; - -jQuery.fx.interval = 13; -jQuery.fx.start = function() { - if ( inProgress ) { - return; - } - - inProgress = true; - schedule(); -}; - -jQuery.fx.stop = function() { - inProgress = null; -}; - -jQuery.fx.speeds = { - slow: 600, - fast: 200, - - // Default speed - _default: 400 -}; - - -// Based off of the plugin by Clint Helfers, with permission. -// https://web.archive.org/web/20100324014747/http://blindsignals.com/index.php/2009/07/jquery-delay/ -jQuery.fn.delay = function( time, type ) { - time = jQuery.fx ? jQuery.fx.speeds[ time ] || time : time; - type = type || "fx"; - - return this.queue( type, function( next, hooks ) { - var timeout = window.setTimeout( next, time ); - hooks.stop = function() { - window.clearTimeout( timeout ); - }; - } ); -}; - - -( function() { - var input = document.createElement( "input" ), - select = document.createElement( "select" ), - opt = select.appendChild( document.createElement( "option" ) ); - - input.type = "checkbox"; - - // Support: Android <=4.3 only - // Default value for a checkbox should be "on" - support.checkOn = input.value !== ""; - - // Support: IE <=11 only - // Must access selectedIndex to make default options select - support.optSelected = opt.selected; - - // Support: IE <=11 only - // An input loses its value after becoming a radio - input = document.createElement( "input" ); - input.value = "t"; - input.type = "radio"; - support.radioValue = input.value === "t"; -} )(); - - -var boolHook, - attrHandle = jQuery.expr.attrHandle; - -jQuery.fn.extend( { - attr: function( name, value ) { - return access( this, jQuery.attr, name, value, arguments.length > 1 ); - }, - - removeAttr: function( name ) { - return this.each( function() { - jQuery.removeAttr( this, name ); - } ); - } -} ); - -jQuery.extend( { - attr: function( elem, name, value ) { - var ret, hooks, - nType = elem.nodeType; - - // Don't get/set attributes on text, comment and attribute nodes - if ( nType === 3 || nType === 8 || nType === 2 ) { - return; - } - - // Fallback to prop when attributes are not supported - if ( typeof elem.getAttribute === "undefined" ) { - return jQuery.prop( elem, name, value ); - } - - // Attribute hooks are determined by the lowercase version - // Grab necessary hook if one is defined - if ( nType !== 1 || !jQuery.isXMLDoc( elem ) ) { - hooks = jQuery.attrHooks[ name.toLowerCase() ] || - ( jQuery.expr.match.bool.test( name ) ? boolHook : undefined ); - } - - if ( value !== undefined ) { - if ( value === null ) { - jQuery.removeAttr( elem, name ); - return; - } - - if ( hooks && "set" in hooks && - ( ret = hooks.set( elem, value, name ) ) !== undefined ) { - return ret; - } - - elem.setAttribute( name, value + "" ); - return value; - } - - if ( hooks && "get" in hooks && ( ret = hooks.get( elem, name ) ) !== null ) { - return ret; - } - - ret = jQuery.find.attr( elem, name ); - - // Non-existent attributes return null, we normalize to undefined - return ret == null ? undefined : ret; - }, - - attrHooks: { - type: { - set: function( elem, value ) { - if ( !support.radioValue && value === "radio" && - nodeName( elem, "input" ) ) { - var val = elem.value; - elem.setAttribute( "type", value ); - if ( val ) { - elem.value = val; - } - return value; - } - } - } - }, - - removeAttr: function( elem, value ) { - var name, - i = 0, - - // Attribute names can contain non-HTML whitespace characters - // https://html.spec.whatwg.org/multipage/syntax.html#attributes-2 - attrNames = value && value.match( rnothtmlwhite ); - - if ( attrNames && elem.nodeType === 1 ) { - while ( ( name = attrNames[ i++ ] ) ) { - elem.removeAttribute( name ); - } - } - } -} ); - -// Hooks for boolean attributes -boolHook = { - set: function( elem, value, name ) { - if ( value === false ) { - - // Remove boolean attributes when set to false - jQuery.removeAttr( elem, name ); - } else { - elem.setAttribute( name, name ); - } - return name; - } -}; - -jQuery.each( jQuery.expr.match.bool.source.match( /\w+/g ), function( _i, name ) { - var getter = attrHandle[ name ] || jQuery.find.attr; - - attrHandle[ name ] = function( elem, name, isXML ) { - var ret, handle, - lowercaseName = name.toLowerCase(); - - if ( !isXML ) { - - // Avoid an infinite loop by temporarily removing this function from the getter - handle = attrHandle[ lowercaseName ]; - attrHandle[ lowercaseName ] = ret; - ret = getter( elem, name, isXML ) != null ? - lowercaseName : - null; - attrHandle[ lowercaseName ] = handle; - } - return ret; - }; -} ); - - - - -var rfocusable = /^(?:input|select|textarea|button)$/i, - rclickable = /^(?:a|area)$/i; - -jQuery.fn.extend( { - prop: function( name, value ) { - return access( this, jQuery.prop, name, value, arguments.length > 1 ); - }, - - removeProp: function( name ) { - return this.each( function() { - delete this[ jQuery.propFix[ name ] || name ]; - } ); - } -} ); - -jQuery.extend( { - prop: function( elem, name, value ) { - var ret, hooks, - nType = elem.nodeType; - - // Don't get/set properties on text, comment and attribute nodes - if ( nType === 3 || nType === 8 || nType === 2 ) { - return; - } - - if ( nType !== 1 || !jQuery.isXMLDoc( elem ) ) { - - // Fix name and attach hooks - name = jQuery.propFix[ name ] || name; - hooks = jQuery.propHooks[ name ]; - } - - if ( value !== undefined ) { - if ( hooks && "set" in hooks && - ( ret = hooks.set( elem, value, name ) ) !== undefined ) { - return ret; - } - - return ( elem[ name ] = value ); - } - - if ( hooks && "get" in hooks && ( ret = hooks.get( elem, name ) ) !== null ) { - return ret; - } - - return elem[ name ]; - }, - - propHooks: { - tabIndex: { - get: function( elem ) { - - // Support: IE <=9 - 11 only - // elem.tabIndex doesn't always return the - // correct value when it hasn't been explicitly set - // https://web.archive.org/web/20141116233347/http://fluidproject.org/blog/2008/01/09/getting-setting-and-removing-tabindex-values-with-javascript/ - // Use proper attribute retrieval(#12072) - var tabindex = jQuery.find.attr( elem, "tabindex" ); - - if ( tabindex ) { - return parseInt( tabindex, 10 ); - } - - if ( - rfocusable.test( elem.nodeName ) || - rclickable.test( elem.nodeName ) && - elem.href - ) { - return 0; - } - - return -1; - } - } - }, - - propFix: { - "for": "htmlFor", - "class": "className" - } -} ); - -// Support: IE <=11 only -// Accessing the selectedIndex property -// forces the browser to respect setting selected -// on the option -// The getter ensures a default option is selected -// when in an optgroup -// eslint rule "no-unused-expressions" is disabled for this code -// since it considers such accessions noop -if ( !support.optSelected ) { - jQuery.propHooks.selected = { - get: function( elem ) { - - /* eslint no-unused-expressions: "off" */ - - var parent = elem.parentNode; - if ( parent && parent.parentNode ) { - parent.parentNode.selectedIndex; - } - return null; - }, - set: function( elem ) { - - /* eslint no-unused-expressions: "off" */ - - var parent = elem.parentNode; - if ( parent ) { - parent.selectedIndex; - - if ( parent.parentNode ) { - parent.parentNode.selectedIndex; - } - } - } - }; -} - -jQuery.each( [ - "tabIndex", - "readOnly", - "maxLength", - "cellSpacing", - "cellPadding", - "rowSpan", - "colSpan", - "useMap", - "frameBorder", - "contentEditable" -], function() { - jQuery.propFix[ this.toLowerCase() ] = this; -} ); - - - - - // Strip and collapse whitespace according to HTML spec - // https://infra.spec.whatwg.org/#strip-and-collapse-ascii-whitespace - function stripAndCollapse( value ) { - var tokens = value.match( rnothtmlwhite ) || []; - return tokens.join( " " ); - } - - -function getClass( elem ) { - return elem.getAttribute && elem.getAttribute( "class" ) || ""; -} - -function classesToArray( value ) { - if ( Array.isArray( value ) ) { - return value; - } - if ( typeof value === "string" ) { - return value.match( rnothtmlwhite ) || []; - } - return []; -} - -jQuery.fn.extend( { - addClass: function( value ) { - var classes, elem, cur, curValue, clazz, j, finalValue, - i = 0; - - if ( isFunction( value ) ) { - return this.each( function( j ) { - jQuery( this ).addClass( value.call( this, j, getClass( this ) ) ); - } ); - } - - classes = classesToArray( value ); - - if ( classes.length ) { - while ( ( elem = this[ i++ ] ) ) { - curValue = getClass( elem ); - cur = elem.nodeType === 1 && ( " " + stripAndCollapse( curValue ) + " " ); - - if ( cur ) { - j = 0; - while ( ( clazz = classes[ j++ ] ) ) { - if ( cur.indexOf( " " + clazz + " " ) < 0 ) { - cur += clazz + " "; - } - } - - // Only assign if different to avoid unneeded rendering. - finalValue = stripAndCollapse( cur ); - if ( curValue !== finalValue ) { - elem.setAttribute( "class", finalValue ); - } - } - } - } - - return this; - }, - - removeClass: function( value ) { - var classes, elem, cur, curValue, clazz, j, finalValue, - i = 0; - - if ( isFunction( value ) ) { - return this.each( function( j ) { - jQuery( this ).removeClass( value.call( this, j, getClass( this ) ) ); - } ); - } - - if ( !arguments.length ) { - return this.attr( "class", "" ); - } - - classes = classesToArray( value ); - - if ( classes.length ) { - while ( ( elem = this[ i++ ] ) ) { - curValue = getClass( elem ); - - // This expression is here for better compressibility (see addClass) - cur = elem.nodeType === 1 && ( " " + stripAndCollapse( curValue ) + " " ); - - if ( cur ) { - j = 0; - while ( ( clazz = classes[ j++ ] ) ) { - - // Remove *all* instances - while ( cur.indexOf( " " + clazz + " " ) > -1 ) { - cur = cur.replace( " " + clazz + " ", " " ); - } - } - - // Only assign if different to avoid unneeded rendering. - finalValue = stripAndCollapse( cur ); - if ( curValue !== finalValue ) { - elem.setAttribute( "class", finalValue ); - } - } - } - } - - return this; - }, - - toggleClass: function( value, stateVal ) { - var type = typeof value, - isValidValue = type === "string" || Array.isArray( value ); - - if ( typeof stateVal === "boolean" && isValidValue ) { - return stateVal ? this.addClass( value ) : this.removeClass( value ); - } - - if ( isFunction( value ) ) { - return this.each( function( i ) { - jQuery( this ).toggleClass( - value.call( this, i, getClass( this ), stateVal ), - stateVal - ); - } ); - } - - return this.each( function() { - var className, i, self, classNames; - - if ( isValidValue ) { - - // Toggle individual class names - i = 0; - self = jQuery( this ); - classNames = classesToArray( value ); - - while ( ( className = classNames[ i++ ] ) ) { - - // Check each className given, space separated list - if ( self.hasClass( className ) ) { - self.removeClass( className ); - } else { - self.addClass( className ); - } - } - - // Toggle whole class name - } else if ( value === undefined || type === "boolean" ) { - className = getClass( this ); - if ( className ) { - - // Store className if set - dataPriv.set( this, "__className__", className ); - } - - // If the element has a class name or if we're passed `false`, - // then remove the whole classname (if there was one, the above saved it). - // Otherwise bring back whatever was previously saved (if anything), - // falling back to the empty string if nothing was stored. - if ( this.setAttribute ) { - this.setAttribute( "class", - className || value === false ? - "" : - dataPriv.get( this, "__className__" ) || "" - ); - } - } - } ); - }, - - hasClass: function( selector ) { - var className, elem, - i = 0; - - className = " " + selector + " "; - while ( ( elem = this[ i++ ] ) ) { - if ( elem.nodeType === 1 && - ( " " + stripAndCollapse( getClass( elem ) ) + " " ).indexOf( className ) > -1 ) { - return true; - } - } - - return false; - } -} ); - - - - -var rreturn = /\r/g; - -jQuery.fn.extend( { - val: function( value ) { - var hooks, ret, valueIsFunction, - elem = this[ 0 ]; - - if ( !arguments.length ) { - if ( elem ) { - hooks = jQuery.valHooks[ elem.type ] || - jQuery.valHooks[ elem.nodeName.toLowerCase() ]; - - if ( hooks && - "get" in hooks && - ( ret = hooks.get( elem, "value" ) ) !== undefined - ) { - return ret; - } - - ret = elem.value; - - // Handle most common string cases - if ( typeof ret === "string" ) { - return ret.replace( rreturn, "" ); - } - - // Handle cases where value is null/undef or number - return ret == null ? "" : ret; - } - - return; - } - - valueIsFunction = isFunction( value ); - - return this.each( function( i ) { - var val; - - if ( this.nodeType !== 1 ) { - return; - } - - if ( valueIsFunction ) { - val = value.call( this, i, jQuery( this ).val() ); - } else { - val = value; - } - - // Treat null/undefined as ""; convert numbers to string - if ( val == null ) { - val = ""; - - } else if ( typeof val === "number" ) { - val += ""; - - } else if ( Array.isArray( val ) ) { - val = jQuery.map( val, function( value ) { - return value == null ? "" : value + ""; - } ); - } - - hooks = jQuery.valHooks[ this.type ] || jQuery.valHooks[ this.nodeName.toLowerCase() ]; - - // If set returns undefined, fall back to normal setting - if ( !hooks || !( "set" in hooks ) || hooks.set( this, val, "value" ) === undefined ) { - this.value = val; - } - } ); - } -} ); - -jQuery.extend( { - valHooks: { - option: { - get: function( elem ) { - - var val = jQuery.find.attr( elem, "value" ); - return val != null ? - val : - - // Support: IE <=10 - 11 only - // option.text throws exceptions (#14686, #14858) - // Strip and collapse whitespace - // https://html.spec.whatwg.org/#strip-and-collapse-whitespace - stripAndCollapse( jQuery.text( elem ) ); - } - }, - select: { - get: function( elem ) { - var value, option, i, - options = elem.options, - index = elem.selectedIndex, - one = elem.type === "select-one", - values = one ? null : [], - max = one ? index + 1 : options.length; - - if ( index < 0 ) { - i = max; - - } else { - i = one ? index : 0; - } - - // Loop through all the selected options - for ( ; i < max; i++ ) { - option = options[ i ]; - - // Support: IE <=9 only - // IE8-9 doesn't update selected after form reset (#2551) - if ( ( option.selected || i === index ) && - - // Don't return options that are disabled or in a disabled optgroup - !option.disabled && - ( !option.parentNode.disabled || - !nodeName( option.parentNode, "optgroup" ) ) ) { - - // Get the specific value for the option - value = jQuery( option ).val(); - - // We don't need an array for one selects - if ( one ) { - return value; - } - - // Multi-Selects return an array - values.push( value ); - } - } - - return values; - }, - - set: function( elem, value ) { - var optionSet, option, - options = elem.options, - values = jQuery.makeArray( value ), - i = options.length; - - while ( i-- ) { - option = options[ i ]; - - /* eslint-disable no-cond-assign */ - - if ( option.selected = - jQuery.inArray( jQuery.valHooks.option.get( option ), values ) > -1 - ) { - optionSet = true; - } - - /* eslint-enable no-cond-assign */ - } - - // Force browsers to behave consistently when non-matching value is set - if ( !optionSet ) { - elem.selectedIndex = -1; - } - return values; - } - } - } -} ); - -// Radios and checkboxes getter/setter -jQuery.each( [ "radio", "checkbox" ], function() { - jQuery.valHooks[ this ] = { - set: function( elem, value ) { - if ( Array.isArray( value ) ) { - return ( elem.checked = jQuery.inArray( jQuery( elem ).val(), value ) > -1 ); - } - } - }; - if ( !support.checkOn ) { - jQuery.valHooks[ this ].get = function( elem ) { - return elem.getAttribute( "value" ) === null ? "on" : elem.value; - }; - } -} ); - - - - -// Return jQuery for attributes-only inclusion - - -support.focusin = "onfocusin" in window; - - -var rfocusMorph = /^(?:focusinfocus|focusoutblur)$/, - stopPropagationCallback = function( e ) { - e.stopPropagation(); - }; - -jQuery.extend( jQuery.event, { - - trigger: function( event, data, elem, onlyHandlers ) { - - var i, cur, tmp, bubbleType, ontype, handle, special, lastElement, - eventPath = [ elem || document ], - type = hasOwn.call( event, "type" ) ? event.type : event, - namespaces = hasOwn.call( event, "namespace" ) ? event.namespace.split( "." ) : []; - - cur = lastElement = tmp = elem = elem || document; - - // Don't do events on text and comment nodes - if ( elem.nodeType === 3 || elem.nodeType === 8 ) { - return; - } - - // focus/blur morphs to focusin/out; ensure we're not firing them right now - if ( rfocusMorph.test( type + jQuery.event.triggered ) ) { - return; - } - - if ( type.indexOf( "." ) > -1 ) { - - // Namespaced trigger; create a regexp to match event type in handle() - namespaces = type.split( "." ); - type = namespaces.shift(); - namespaces.sort(); - } - ontype = type.indexOf( ":" ) < 0 && "on" + type; - - // Caller can pass in a jQuery.Event object, Object, or just an event type string - event = event[ jQuery.expando ] ? - event : - new jQuery.Event( type, typeof event === "object" && event ); - - // Trigger bitmask: & 1 for native handlers; & 2 for jQuery (always true) - event.isTrigger = onlyHandlers ? 2 : 3; - event.namespace = namespaces.join( "." ); - event.rnamespace = event.namespace ? - new RegExp( "(^|\\.)" + namespaces.join( "\\.(?:.*\\.|)" ) + "(\\.|$)" ) : - null; - - // Clean up the event in case it is being reused - event.result = undefined; - if ( !event.target ) { - event.target = elem; - } - - // Clone any incoming data and prepend the event, creating the handler arg list - data = data == null ? - [ event ] : - jQuery.makeArray( data, [ event ] ); - - // Allow special events to draw outside the lines - special = jQuery.event.special[ type ] || {}; - if ( !onlyHandlers && special.trigger && special.trigger.apply( elem, data ) === false ) { - return; - } - - // Determine event propagation path in advance, per W3C events spec (#9951) - // Bubble up to document, then to window; watch for a global ownerDocument var (#9724) - if ( !onlyHandlers && !special.noBubble && !isWindow( elem ) ) { - - bubbleType = special.delegateType || type; - if ( !rfocusMorph.test( bubbleType + type ) ) { - cur = cur.parentNode; - } - for ( ; cur; cur = cur.parentNode ) { - eventPath.push( cur ); - tmp = cur; - } - - // Only add window if we got to document (e.g., not plain obj or detached DOM) - if ( tmp === ( elem.ownerDocument || document ) ) { - eventPath.push( tmp.defaultView || tmp.parentWindow || window ); - } - } - - // Fire handlers on the event path - i = 0; - while ( ( cur = eventPath[ i++ ] ) && !event.isPropagationStopped() ) { - lastElement = cur; - event.type = i > 1 ? - bubbleType : - special.bindType || type; - - // jQuery handler - handle = ( dataPriv.get( cur, "events" ) || Object.create( null ) )[ event.type ] && - dataPriv.get( cur, "handle" ); - if ( handle ) { - handle.apply( cur, data ); - } - - // Native handler - handle = ontype && cur[ ontype ]; - if ( handle && handle.apply && acceptData( cur ) ) { - event.result = handle.apply( cur, data ); - if ( event.result === false ) { - event.preventDefault(); - } - } - } - event.type = type; - - // If nobody prevented the default action, do it now - if ( !onlyHandlers && !event.isDefaultPrevented() ) { - - if ( ( !special._default || - special._default.apply( eventPath.pop(), data ) === false ) && - acceptData( elem ) ) { - - // Call a native DOM method on the target with the same name as the event. - // Don't do default actions on window, that's where global variables be (#6170) - if ( ontype && isFunction( elem[ type ] ) && !isWindow( elem ) ) { - - // Don't re-trigger an onFOO event when we call its FOO() method - tmp = elem[ ontype ]; - - if ( tmp ) { - elem[ ontype ] = null; - } - - // Prevent re-triggering of the same event, since we already bubbled it above - jQuery.event.triggered = type; - - if ( event.isPropagationStopped() ) { - lastElement.addEventListener( type, stopPropagationCallback ); - } - - elem[ type ](); - - if ( event.isPropagationStopped() ) { - lastElement.removeEventListener( type, stopPropagationCallback ); - } - - jQuery.event.triggered = undefined; - - if ( tmp ) { - elem[ ontype ] = tmp; - } - } - } - } - - return event.result; - }, - - // Piggyback on a donor event to simulate a different one - // Used only for `focus(in | out)` events - simulate: function( type, elem, event ) { - var e = jQuery.extend( - new jQuery.Event(), - event, - { - type: type, - isSimulated: true - } - ); - - jQuery.event.trigger( e, null, elem ); - } - -} ); - -jQuery.fn.extend( { - - trigger: function( type, data ) { - return this.each( function() { - jQuery.event.trigger( type, data, this ); - } ); - }, - triggerHandler: function( type, data ) { - var elem = this[ 0 ]; - if ( elem ) { - return jQuery.event.trigger( type, data, elem, true ); - } - } -} ); - - -// Support: Firefox <=44 -// Firefox doesn't have focus(in | out) events -// Related ticket - https://bugzilla.mozilla.org/show_bug.cgi?id=687787 -// -// Support: Chrome <=48 - 49, Safari <=9.0 - 9.1 -// focus(in | out) events fire after focus & blur events, -// which is spec violation - http://www.w3.org/TR/DOM-Level-3-Events/#events-focusevent-event-order -// Related ticket - https://bugs.chromium.org/p/chromium/issues/detail?id=449857 -if ( !support.focusin ) { - jQuery.each( { focus: "focusin", blur: "focusout" }, function( orig, fix ) { - - // Attach a single capturing handler on the document while someone wants focusin/focusout - var handler = function( event ) { - jQuery.event.simulate( fix, event.target, jQuery.event.fix( event ) ); - }; - - jQuery.event.special[ fix ] = { - setup: function() { - - // Handle: regular nodes (via `this.ownerDocument`), window - // (via `this.document`) & document (via `this`). - var doc = this.ownerDocument || this.document || this, - attaches = dataPriv.access( doc, fix ); - - if ( !attaches ) { - doc.addEventListener( orig, handler, true ); - } - dataPriv.access( doc, fix, ( attaches || 0 ) + 1 ); - }, - teardown: function() { - var doc = this.ownerDocument || this.document || this, - attaches = dataPriv.access( doc, fix ) - 1; - - if ( !attaches ) { - doc.removeEventListener( orig, handler, true ); - dataPriv.remove( doc, fix ); - - } else { - dataPriv.access( doc, fix, attaches ); - } - } - }; - } ); -} -var location = window.location; - -var nonce = { guid: Date.now() }; - -var rquery = ( /\?/ ); - - - -// Cross-browser xml parsing -jQuery.parseXML = function( data ) { - var xml, parserErrorElem; - if ( !data || typeof data !== "string" ) { - return null; - } - - // Support: IE 9 - 11 only - // IE throws on parseFromString with invalid input. - try { - xml = ( new window.DOMParser() ).parseFromString( data, "text/xml" ); - } catch ( e ) {} - - parserErrorElem = xml && xml.getElementsByTagName( "parsererror" )[ 0 ]; - if ( !xml || parserErrorElem ) { - jQuery.error( "Invalid XML: " + ( - parserErrorElem ? - jQuery.map( parserErrorElem.childNodes, function( el ) { - return el.textContent; - } ).join( "\n" ) : - data - ) ); - } - return xml; -}; - - -var - rbracket = /\[\]$/, - rCRLF = /\r?\n/g, - rsubmitterTypes = /^(?:submit|button|image|reset|file)$/i, - rsubmittable = /^(?:input|select|textarea|keygen)/i; - -function buildParams( prefix, obj, traditional, add ) { - var name; - - if ( Array.isArray( obj ) ) { - - // Serialize array item. - jQuery.each( obj, function( i, v ) { - if ( traditional || rbracket.test( prefix ) ) { - - // Treat each array item as a scalar. - add( prefix, v ); - - } else { - - // Item is non-scalar (array or object), encode its numeric index. - buildParams( - prefix + "[" + ( typeof v === "object" && v != null ? i : "" ) + "]", - v, - traditional, - add - ); - } - } ); - - } else if ( !traditional && toType( obj ) === "object" ) { - - // Serialize object item. - for ( name in obj ) { - buildParams( prefix + "[" + name + "]", obj[ name ], traditional, add ); - } - - } else { - - // Serialize scalar item. - add( prefix, obj ); - } -} - -// Serialize an array of form elements or a set of -// key/values into a query string -jQuery.param = function( a, traditional ) { - var prefix, - s = [], - add = function( key, valueOrFunction ) { - - // If value is a function, invoke it and use its return value - var value = isFunction( valueOrFunction ) ? - valueOrFunction() : - valueOrFunction; - - s[ s.length ] = encodeURIComponent( key ) + "=" + - encodeURIComponent( value == null ? "" : value ); - }; - - if ( a == null ) { - return ""; - } - - // If an array was passed in, assume that it is an array of form elements. - if ( Array.isArray( a ) || ( a.jquery && !jQuery.isPlainObject( a ) ) ) { - - // Serialize the form elements - jQuery.each( a, function() { - add( this.name, this.value ); - } ); - - } else { - - // If traditional, encode the "old" way (the way 1.3.2 or older - // did it), otherwise encode params recursively. - for ( prefix in a ) { - buildParams( prefix, a[ prefix ], traditional, add ); - } - } - - // Return the resulting serialization - return s.join( "&" ); -}; - -jQuery.fn.extend( { - serialize: function() { - return jQuery.param( this.serializeArray() ); - }, - serializeArray: function() { - return this.map( function() { - - // Can add propHook for "elements" to filter or add form elements - var elements = jQuery.prop( this, "elements" ); - return elements ? jQuery.makeArray( elements ) : this; - } ).filter( function() { - var type = this.type; - - // Use .is( ":disabled" ) so that fieldset[disabled] works - return this.name && !jQuery( this ).is( ":disabled" ) && - rsubmittable.test( this.nodeName ) && !rsubmitterTypes.test( type ) && - ( this.checked || !rcheckableType.test( type ) ); - } ).map( function( _i, elem ) { - var val = jQuery( this ).val(); - - if ( val == null ) { - return null; - } - - if ( Array.isArray( val ) ) { - return jQuery.map( val, function( val ) { - return { name: elem.name, value: val.replace( rCRLF, "\r\n" ) }; - } ); - } - - return { name: elem.name, value: val.replace( rCRLF, "\r\n" ) }; - } ).get(); - } -} ); - - -var - r20 = /%20/g, - rhash = /#.*$/, - rantiCache = /([?&])_=[^&]*/, - rheaders = /^(.*?):[ \t]*([^\r\n]*)$/mg, - - // #7653, #8125, #8152: local protocol detection - rlocalProtocol = /^(?:about|app|app-storage|.+-extension|file|res|widget):$/, - rnoContent = /^(?:GET|HEAD)$/, - rprotocol = /^\/\//, - - /* Prefilters - * 1) They are useful to introduce custom dataTypes (see ajax/jsonp.js for an example) - * 2) These are called: - * - BEFORE asking for a transport - * - AFTER param serialization (s.data is a string if s.processData is true) - * 3) key is the dataType - * 4) the catchall symbol "*" can be used - * 5) execution will start with transport dataType and THEN continue down to "*" if needed - */ - prefilters = {}, - - /* Transports bindings - * 1) key is the dataType - * 2) the catchall symbol "*" can be used - * 3) selection will start with transport dataType and THEN go to "*" if needed - */ - transports = {}, - - // Avoid comment-prolog char sequence (#10098); must appease lint and evade compression - allTypes = "*/".concat( "*" ), - - // Anchor tag for parsing the document origin - originAnchor = document.createElement( "a" ); - -originAnchor.href = location.href; - -// Base "constructor" for jQuery.ajaxPrefilter and jQuery.ajaxTransport -function addToPrefiltersOrTransports( structure ) { - - // dataTypeExpression is optional and defaults to "*" - return function( dataTypeExpression, func ) { - - if ( typeof dataTypeExpression !== "string" ) { - func = dataTypeExpression; - dataTypeExpression = "*"; - } - - var dataType, - i = 0, - dataTypes = dataTypeExpression.toLowerCase().match( rnothtmlwhite ) || []; - - if ( isFunction( func ) ) { - - // For each dataType in the dataTypeExpression - while ( ( dataType = dataTypes[ i++ ] ) ) { - - // Prepend if requested - if ( dataType[ 0 ] === "+" ) { - dataType = dataType.slice( 1 ) || "*"; - ( structure[ dataType ] = structure[ dataType ] || [] ).unshift( func ); - - // Otherwise append - } else { - ( structure[ dataType ] = structure[ dataType ] || [] ).push( func ); - } - } - } - }; -} - -// Base inspection function for prefilters and transports -function inspectPrefiltersOrTransports( structure, options, originalOptions, jqXHR ) { - - var inspected = {}, - seekingTransport = ( structure === transports ); - - function inspect( dataType ) { - var selected; - inspected[ dataType ] = true; - jQuery.each( structure[ dataType ] || [], function( _, prefilterOrFactory ) { - var dataTypeOrTransport = prefilterOrFactory( options, originalOptions, jqXHR ); - if ( typeof dataTypeOrTransport === "string" && - !seekingTransport && !inspected[ dataTypeOrTransport ] ) { - - options.dataTypes.unshift( dataTypeOrTransport ); - inspect( dataTypeOrTransport ); - return false; - } else if ( seekingTransport ) { - return !( selected = dataTypeOrTransport ); - } - } ); - return selected; - } - - return inspect( options.dataTypes[ 0 ] ) || !inspected[ "*" ] && inspect( "*" ); -} - -// A special extend for ajax options -// that takes "flat" options (not to be deep extended) -// Fixes #9887 -function ajaxExtend( target, src ) { - var key, deep, - flatOptions = jQuery.ajaxSettings.flatOptions || {}; - - for ( key in src ) { - if ( src[ key ] !== undefined ) { - ( flatOptions[ key ] ? target : ( deep || ( deep = {} ) ) )[ key ] = src[ key ]; - } - } - if ( deep ) { - jQuery.extend( true, target, deep ); - } - - return target; -} - -/* Handles responses to an ajax request: - * - finds the right dataType (mediates between content-type and expected dataType) - * - returns the corresponding response - */ -function ajaxHandleResponses( s, jqXHR, responses ) { - - var ct, type, finalDataType, firstDataType, - contents = s.contents, - dataTypes = s.dataTypes; - - // Remove auto dataType and get content-type in the process - while ( dataTypes[ 0 ] === "*" ) { - dataTypes.shift(); - if ( ct === undefined ) { - ct = s.mimeType || jqXHR.getResponseHeader( "Content-Type" ); - } - } - - // Check if we're dealing with a known content-type - if ( ct ) { - for ( type in contents ) { - if ( contents[ type ] && contents[ type ].test( ct ) ) { - dataTypes.unshift( type ); - break; - } - } - } - - // Check to see if we have a response for the expected dataType - if ( dataTypes[ 0 ] in responses ) { - finalDataType = dataTypes[ 0 ]; - } else { - - // Try convertible dataTypes - for ( type in responses ) { - if ( !dataTypes[ 0 ] || s.converters[ type + " " + dataTypes[ 0 ] ] ) { - finalDataType = type; - break; - } - if ( !firstDataType ) { - firstDataType = type; - } - } - - // Or just use first one - finalDataType = finalDataType || firstDataType; - } - - // If we found a dataType - // We add the dataType to the list if needed - // and return the corresponding response - if ( finalDataType ) { - if ( finalDataType !== dataTypes[ 0 ] ) { - dataTypes.unshift( finalDataType ); - } - return responses[ finalDataType ]; - } -} - -/* Chain conversions given the request and the original response - * Also sets the responseXXX fields on the jqXHR instance - */ -function ajaxConvert( s, response, jqXHR, isSuccess ) { - var conv2, current, conv, tmp, prev, - converters = {}, - - // Work with a copy of dataTypes in case we need to modify it for conversion - dataTypes = s.dataTypes.slice(); - - // Create converters map with lowercased keys - if ( dataTypes[ 1 ] ) { - for ( conv in s.converters ) { - converters[ conv.toLowerCase() ] = s.converters[ conv ]; - } - } - - current = dataTypes.shift(); - - // Convert to each sequential dataType - while ( current ) { - - if ( s.responseFields[ current ] ) { - jqXHR[ s.responseFields[ current ] ] = response; - } - - // Apply the dataFilter if provided - if ( !prev && isSuccess && s.dataFilter ) { - response = s.dataFilter( response, s.dataType ); - } - - prev = current; - current = dataTypes.shift(); - - if ( current ) { - - // There's only work to do if current dataType is non-auto - if ( current === "*" ) { - - current = prev; - - // Convert response if prev dataType is non-auto and differs from current - } else if ( prev !== "*" && prev !== current ) { - - // Seek a direct converter - conv = converters[ prev + " " + current ] || converters[ "* " + current ]; - - // If none found, seek a pair - if ( !conv ) { - for ( conv2 in converters ) { - - // If conv2 outputs current - tmp = conv2.split( " " ); - if ( tmp[ 1 ] === current ) { - - // If prev can be converted to accepted input - conv = converters[ prev + " " + tmp[ 0 ] ] || - converters[ "* " + tmp[ 0 ] ]; - if ( conv ) { - - // Condense equivalence converters - if ( conv === true ) { - conv = converters[ conv2 ]; - - // Otherwise, insert the intermediate dataType - } else if ( converters[ conv2 ] !== true ) { - current = tmp[ 0 ]; - dataTypes.unshift( tmp[ 1 ] ); - } - break; - } - } - } - } - - // Apply converter (if not an equivalence) - if ( conv !== true ) { - - // Unless errors are allowed to bubble, catch and return them - if ( conv && s.throws ) { - response = conv( response ); - } else { - try { - response = conv( response ); - } catch ( e ) { - return { - state: "parsererror", - error: conv ? e : "No conversion from " + prev + " to " + current - }; - } - } - } - } - } - } - - return { state: "success", data: response }; -} - -jQuery.extend( { - - // Counter for holding the number of active queries - active: 0, - - // Last-Modified header cache for next request - lastModified: {}, - etag: {}, - - ajaxSettings: { - url: location.href, - type: "GET", - isLocal: rlocalProtocol.test( location.protocol ), - global: true, - processData: true, - async: true, - contentType: "application/x-www-form-urlencoded; charset=UTF-8", - - /* - timeout: 0, - data: null, - dataType: null, - username: null, - password: null, - cache: null, - throws: false, - traditional: false, - headers: {}, - */ - - accepts: { - "*": allTypes, - text: "text/plain", - html: "text/html", - xml: "application/xml, text/xml", - json: "application/json, text/javascript" - }, - - contents: { - xml: /\bxml\b/, - html: /\bhtml/, - json: /\bjson\b/ - }, - - responseFields: { - xml: "responseXML", - text: "responseText", - json: "responseJSON" - }, - - // Data converters - // Keys separate source (or catchall "*") and destination types with a single space - converters: { - - // Convert anything to text - "* text": String, - - // Text to html (true = no transformation) - "text html": true, - - // Evaluate text as a json expression - "text json": JSON.parse, - - // Parse text as xml - "text xml": jQuery.parseXML - }, - - // For options that shouldn't be deep extended: - // you can add your own custom options here if - // and when you create one that shouldn't be - // deep extended (see ajaxExtend) - flatOptions: { - url: true, - context: true - } - }, - - // Creates a full fledged settings object into target - // with both ajaxSettings and settings fields. - // If target is omitted, writes into ajaxSettings. - ajaxSetup: function( target, settings ) { - return settings ? - - // Building a settings object - ajaxExtend( ajaxExtend( target, jQuery.ajaxSettings ), settings ) : - - // Extending ajaxSettings - ajaxExtend( jQuery.ajaxSettings, target ); - }, - - ajaxPrefilter: addToPrefiltersOrTransports( prefilters ), - ajaxTransport: addToPrefiltersOrTransports( transports ), - - // Main method - ajax: function( url, options ) { - - // If url is an object, simulate pre-1.5 signature - if ( typeof url === "object" ) { - options = url; - url = undefined; - } - - // Force options to be an object - options = options || {}; - - var transport, - - // URL without anti-cache param - cacheURL, - - // Response headers - responseHeadersString, - responseHeaders, - - // timeout handle - timeoutTimer, - - // Url cleanup var - urlAnchor, - - // Request state (becomes false upon send and true upon completion) - completed, - - // To know if global events are to be dispatched - fireGlobals, - - // Loop variable - i, - - // uncached part of the url - uncached, - - // Create the final options object - s = jQuery.ajaxSetup( {}, options ), - - // Callbacks context - callbackContext = s.context || s, - - // Context for global events is callbackContext if it is a DOM node or jQuery collection - globalEventContext = s.context && - ( callbackContext.nodeType || callbackContext.jquery ) ? - jQuery( callbackContext ) : - jQuery.event, - - // Deferreds - deferred = jQuery.Deferred(), - completeDeferred = jQuery.Callbacks( "once memory" ), - - // Status-dependent callbacks - statusCode = s.statusCode || {}, - - // Headers (they are sent all at once) - requestHeaders = {}, - requestHeadersNames = {}, - - // Default abort message - strAbort = "canceled", - - // Fake xhr - jqXHR = { - readyState: 0, - - // Builds headers hashtable if needed - getResponseHeader: function( key ) { - var match; - if ( completed ) { - if ( !responseHeaders ) { - responseHeaders = {}; - while ( ( match = rheaders.exec( responseHeadersString ) ) ) { - responseHeaders[ match[ 1 ].toLowerCase() + " " ] = - ( responseHeaders[ match[ 1 ].toLowerCase() + " " ] || [] ) - .concat( match[ 2 ] ); - } - } - match = responseHeaders[ key.toLowerCase() + " " ]; - } - return match == null ? null : match.join( ", " ); - }, - - // Raw string - getAllResponseHeaders: function() { - return completed ? responseHeadersString : null; - }, - - // Caches the header - setRequestHeader: function( name, value ) { - if ( completed == null ) { - name = requestHeadersNames[ name.toLowerCase() ] = - requestHeadersNames[ name.toLowerCase() ] || name; - requestHeaders[ name ] = value; - } - return this; - }, - - // Overrides response content-type header - overrideMimeType: function( type ) { - if ( completed == null ) { - s.mimeType = type; - } - return this; - }, - - // Status-dependent callbacks - statusCode: function( map ) { - var code; - if ( map ) { - if ( completed ) { - - // Execute the appropriate callbacks - jqXHR.always( map[ jqXHR.status ] ); - } else { - - // Lazy-add the new callbacks in a way that preserves old ones - for ( code in map ) { - statusCode[ code ] = [ statusCode[ code ], map[ code ] ]; - } - } - } - return this; - }, - - // Cancel the request - abort: function( statusText ) { - var finalText = statusText || strAbort; - if ( transport ) { - transport.abort( finalText ); - } - done( 0, finalText ); - return this; - } - }; - - // Attach deferreds - deferred.promise( jqXHR ); - - // Add protocol if not provided (prefilters might expect it) - // Handle falsy url in the settings object (#10093: consistency with old signature) - // We also use the url parameter if available - s.url = ( ( url || s.url || location.href ) + "" ) - .replace( rprotocol, location.protocol + "//" ); - - // Alias method option to type as per ticket #12004 - s.type = options.method || options.type || s.method || s.type; - - // Extract dataTypes list - s.dataTypes = ( s.dataType || "*" ).toLowerCase().match( rnothtmlwhite ) || [ "" ]; - - // A cross-domain request is in order when the origin doesn't match the current origin. - if ( s.crossDomain == null ) { - urlAnchor = document.createElement( "a" ); - - // Support: IE <=8 - 11, Edge 12 - 15 - // IE throws exception on accessing the href property if url is malformed, - // e.g. http://example.com:80x/ - try { - urlAnchor.href = s.url; - - // Support: IE <=8 - 11 only - // Anchor's host property isn't correctly set when s.url is relative - urlAnchor.href = urlAnchor.href; - s.crossDomain = originAnchor.protocol + "//" + originAnchor.host !== - urlAnchor.protocol + "//" + urlAnchor.host; - } catch ( e ) { - - // If there is an error parsing the URL, assume it is crossDomain, - // it can be rejected by the transport if it is invalid - s.crossDomain = true; - } - } - - // Convert data if not already a string - if ( s.data && s.processData && typeof s.data !== "string" ) { - s.data = jQuery.param( s.data, s.traditional ); - } - - // Apply prefilters - inspectPrefiltersOrTransports( prefilters, s, options, jqXHR ); - - // If request was aborted inside a prefilter, stop there - if ( completed ) { - return jqXHR; - } - - // We can fire global events as of now if asked to - // Don't fire events if jQuery.event is undefined in an AMD-usage scenario (#15118) - fireGlobals = jQuery.event && s.global; - - // Watch for a new set of requests - if ( fireGlobals && jQuery.active++ === 0 ) { - jQuery.event.trigger( "ajaxStart" ); - } - - // Uppercase the type - s.type = s.type.toUpperCase(); - - // Determine if request has content - s.hasContent = !rnoContent.test( s.type ); - - // Save the URL in case we're toying with the If-Modified-Since - // and/or If-None-Match header later on - // Remove hash to simplify url manipulation - cacheURL = s.url.replace( rhash, "" ); - - // More options handling for requests with no content - if ( !s.hasContent ) { - - // Remember the hash so we can put it back - uncached = s.url.slice( cacheURL.length ); - - // If data is available and should be processed, append data to url - if ( s.data && ( s.processData || typeof s.data === "string" ) ) { - cacheURL += ( rquery.test( cacheURL ) ? "&" : "?" ) + s.data; - - // #9682: remove data so that it's not used in an eventual retry - delete s.data; - } - - // Add or update anti-cache param if needed - if ( s.cache === false ) { - cacheURL = cacheURL.replace( rantiCache, "$1" ); - uncached = ( rquery.test( cacheURL ) ? "&" : "?" ) + "_=" + ( nonce.guid++ ) + - uncached; - } - - // Put hash and anti-cache on the URL that will be requested (gh-1732) - s.url = cacheURL + uncached; - - // Change '%20' to '+' if this is encoded form body content (gh-2658) - } else if ( s.data && s.processData && - ( s.contentType || "" ).indexOf( "application/x-www-form-urlencoded" ) === 0 ) { - s.data = s.data.replace( r20, "+" ); - } - - // Set the If-Modified-Since and/or If-None-Match header, if in ifModified mode. - if ( s.ifModified ) { - if ( jQuery.lastModified[ cacheURL ] ) { - jqXHR.setRequestHeader( "If-Modified-Since", jQuery.lastModified[ cacheURL ] ); - } - if ( jQuery.etag[ cacheURL ] ) { - jqXHR.setRequestHeader( "If-None-Match", jQuery.etag[ cacheURL ] ); - } - } - - // Set the correct header, if data is being sent - if ( s.data && s.hasContent && s.contentType !== false || options.contentType ) { - jqXHR.setRequestHeader( "Content-Type", s.contentType ); - } - - // Set the Accepts header for the server, depending on the dataType - jqXHR.setRequestHeader( - "Accept", - s.dataTypes[ 0 ] && s.accepts[ s.dataTypes[ 0 ] ] ? - s.accepts[ s.dataTypes[ 0 ] ] + - ( s.dataTypes[ 0 ] !== "*" ? ", " + allTypes + "; q=0.01" : "" ) : - s.accepts[ "*" ] - ); - - // Check for headers option - for ( i in s.headers ) { - jqXHR.setRequestHeader( i, s.headers[ i ] ); - } - - // Allow custom headers/mimetypes and early abort - if ( s.beforeSend && - ( s.beforeSend.call( callbackContext, jqXHR, s ) === false || completed ) ) { - - // Abort if not done already and return - return jqXHR.abort(); - } - - // Aborting is no longer a cancellation - strAbort = "abort"; - - // Install callbacks on deferreds - completeDeferred.add( s.complete ); - jqXHR.done( s.success ); - jqXHR.fail( s.error ); - - // Get transport - transport = inspectPrefiltersOrTransports( transports, s, options, jqXHR ); - - // If no transport, we auto-abort - if ( !transport ) { - done( -1, "No Transport" ); - } else { - jqXHR.readyState = 1; - - // Send global event - if ( fireGlobals ) { - globalEventContext.trigger( "ajaxSend", [ jqXHR, s ] ); - } - - // If request was aborted inside ajaxSend, stop there - if ( completed ) { - return jqXHR; - } - - // Timeout - if ( s.async && s.timeout > 0 ) { - timeoutTimer = window.setTimeout( function() { - jqXHR.abort( "timeout" ); - }, s.timeout ); - } - - try { - completed = false; - transport.send( requestHeaders, done ); - } catch ( e ) { - - // Rethrow post-completion exceptions - if ( completed ) { - throw e; - } - - // Propagate others as results - done( -1, e ); - } - } - - // Callback for when everything is done - function done( status, nativeStatusText, responses, headers ) { - var isSuccess, success, error, response, modified, - statusText = nativeStatusText; - - // Ignore repeat invocations - if ( completed ) { - return; - } - - completed = true; - - // Clear timeout if it exists - if ( timeoutTimer ) { - window.clearTimeout( timeoutTimer ); - } - - // Dereference transport for early garbage collection - // (no matter how long the jqXHR object will be used) - transport = undefined; - - // Cache response headers - responseHeadersString = headers || ""; - - // Set readyState - jqXHR.readyState = status > 0 ? 4 : 0; - - // Determine if successful - isSuccess = status >= 200 && status < 300 || status === 304; - - // Get response data - if ( responses ) { - response = ajaxHandleResponses( s, jqXHR, responses ); - } - - // Use a noop converter for missing script but not if jsonp - if ( !isSuccess && - jQuery.inArray( "script", s.dataTypes ) > -1 && - jQuery.inArray( "json", s.dataTypes ) < 0 ) { - s.converters[ "text script" ] = function() {}; - } - - // Convert no matter what (that way responseXXX fields are always set) - response = ajaxConvert( s, response, jqXHR, isSuccess ); - - // If successful, handle type chaining - if ( isSuccess ) { - - // Set the If-Modified-Since and/or If-None-Match header, if in ifModified mode. - if ( s.ifModified ) { - modified = jqXHR.getResponseHeader( "Last-Modified" ); - if ( modified ) { - jQuery.lastModified[ cacheURL ] = modified; - } - modified = jqXHR.getResponseHeader( "etag" ); - if ( modified ) { - jQuery.etag[ cacheURL ] = modified; - } - } - - // if no content - if ( status === 204 || s.type === "HEAD" ) { - statusText = "nocontent"; - - // if not modified - } else if ( status === 304 ) { - statusText = "notmodified"; - - // If we have data, let's convert it - } else { - statusText = response.state; - success = response.data; - error = response.error; - isSuccess = !error; - } - } else { - - // Extract error from statusText and normalize for non-aborts - error = statusText; - if ( status || !statusText ) { - statusText = "error"; - if ( status < 0 ) { - status = 0; - } - } - } - - // Set data for the fake xhr object - jqXHR.status = status; - jqXHR.statusText = ( nativeStatusText || statusText ) + ""; - - // Success/Error - if ( isSuccess ) { - deferred.resolveWith( callbackContext, [ success, statusText, jqXHR ] ); - } else { - deferred.rejectWith( callbackContext, [ jqXHR, statusText, error ] ); - } - - // Status-dependent callbacks - jqXHR.statusCode( statusCode ); - statusCode = undefined; - - if ( fireGlobals ) { - globalEventContext.trigger( isSuccess ? "ajaxSuccess" : "ajaxError", - [ jqXHR, s, isSuccess ? success : error ] ); - } - - // Complete - completeDeferred.fireWith( callbackContext, [ jqXHR, statusText ] ); - - if ( fireGlobals ) { - globalEventContext.trigger( "ajaxComplete", [ jqXHR, s ] ); - - // Handle the global AJAX counter - if ( !( --jQuery.active ) ) { - jQuery.event.trigger( "ajaxStop" ); - } - } - } - - return jqXHR; - }, - - getJSON: function( url, data, callback ) { - return jQuery.get( url, data, callback, "json" ); - }, - - getScript: function( url, callback ) { - return jQuery.get( url, undefined, callback, "script" ); - } -} ); - -jQuery.each( [ "get", "post" ], function( _i, method ) { - jQuery[ method ] = function( url, data, callback, type ) { - - // Shift arguments if data argument was omitted - if ( isFunction( data ) ) { - type = type || callback; - callback = data; - data = undefined; - } - - // The url can be an options object (which then must have .url) - return jQuery.ajax( jQuery.extend( { - url: url, - type: method, - dataType: type, - data: data, - success: callback - }, jQuery.isPlainObject( url ) && url ) ); - }; -} ); - -jQuery.ajaxPrefilter( function( s ) { - var i; - for ( i in s.headers ) { - if ( i.toLowerCase() === "content-type" ) { - s.contentType = s.headers[ i ] || ""; - } - } -} ); - - -jQuery._evalUrl = function( url, options, doc ) { - return jQuery.ajax( { - url: url, - - // Make this explicit, since user can override this through ajaxSetup (#11264) - type: "GET", - dataType: "script", - cache: true, - async: false, - global: false, - - // Only evaluate the response if it is successful (gh-4126) - // dataFilter is not invoked for failure responses, so using it instead - // of the default converter is kludgy but it works. - converters: { - "text script": function() {} - }, - dataFilter: function( response ) { - jQuery.globalEval( response, options, doc ); - } - } ); -}; - - -jQuery.fn.extend( { - wrapAll: function( html ) { - var wrap; - - if ( this[ 0 ] ) { - if ( isFunction( html ) ) { - html = html.call( this[ 0 ] ); - } - - // The elements to wrap the target around - wrap = jQuery( html, this[ 0 ].ownerDocument ).eq( 0 ).clone( true ); - - if ( this[ 0 ].parentNode ) { - wrap.insertBefore( this[ 0 ] ); - } - - wrap.map( function() { - var elem = this; - - while ( elem.firstElementChild ) { - elem = elem.firstElementChild; - } - - return elem; - } ).append( this ); - } - - return this; - }, - - wrapInner: function( html ) { - if ( isFunction( html ) ) { - return this.each( function( i ) { - jQuery( this ).wrapInner( html.call( this, i ) ); - } ); - } - - return this.each( function() { - var self = jQuery( this ), - contents = self.contents(); - - if ( contents.length ) { - contents.wrapAll( html ); - - } else { - self.append( html ); - } - } ); - }, - - wrap: function( html ) { - var htmlIsFunction = isFunction( html ); - - return this.each( function( i ) { - jQuery( this ).wrapAll( htmlIsFunction ? 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          -
          -
          -

          CLAMP -

          - -
          -

          Bioconductor release status -

          - - - - - - - - - - - - - - - - - - -
          BranchR CMD checkLast updated
          develBioconductor-devel Build Status
          releaseBioconductor-release Build Status
          -

          The goal of CLAMP (Curated Latent-variable Analysis with Molecular Priors) is to provide an easy-to-use package to extract interpretable latent variables from large transcriptomic datasets using biological priors.

          -
          -
          -

          Local development via Conda -

          -

          We keep a fully specified environment file at envs/clamp.yaml. From your package root, create and activate it like so:

          -
          # Create and activate the environment
-conda env create -f envs/clamp.yaml
-conda activate clamp
-
-# Define the repository path (adjust as needed)
-REPO_PATH=~/path/to/CLAMP
-
-# Install and check CLAMP using devtools
-Rscript -e "devtools::install_local('$REPO_PATH', force=TRUE, dependencies=FALSE)"
-Rscript -e "library(CLAMP); cat('CLAMP version:', as.character(packageVersion('CLAMP')), '\n')"
          -
          -
          -

          Installation -

          -

          You can install the latest release of CLAMP from Bioconductor:

          -
          -if (!requireNamespace("BiocManager", quietly = TRUE)) {
-    install.packages("BiocManager")
-}
-
-BiocManager::install("CLAMP")
          -

          If you want to test the development version, you can install it from the github repository:

          -
          -BiocManager::install("mchikina/CLAMP")
          -

          Now you can load the package using:

          - -
          -
          -

          Basic usage -

          -

          For detailed instructions on how to use CLAMP, please see the vignette.

          -
          -library(CLAMP)
-#some example
          -
          -
          -

          Code of Conduct -

          -

          Please note that the CLAMP project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

          -
          -
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          -
          - - - - - - - diff --git a/docs/katex-auto.js b/docs/katex-auto.js deleted file mode 100644 index 2adab3a..0000000 --- a/docs/katex-auto.js +++ /dev/null @@ -1,16 +0,0 @@ -// https://github.com/jgm/pandoc/blob/29fa97ab96b8e2d62d48326e1b949a71dc41f47a/src/Text/Pandoc/Writers/HTML.hs#L332-L345 -document.addEventListener("DOMContentLoaded", function () { - var mathElements = document.getElementsByClassName("math"); - var macros = []; - for (var i = 0; i < mathElements.length; i++) { - var texText = mathElements[i].firstChild; - if (mathElements[i].tagName == "SPAN") { - katex.render(texText.data, mathElements[i], { - displayMode: mathElements[i].classList.contains("display"), - throwOnError: false, - macros: macros, - fleqn: false - }); - } - } -}); diff --git a/docs/lightswitch.js b/docs/lightswitch.js deleted file mode 100644 index 3808ca1..0000000 --- a/docs/lightswitch.js +++ /dev/null @@ -1,85 +0,0 @@ - -/*! - * Color mode toggler for Bootstrap's docs (https://getbootstrap.com/) - * Copyright 2011-2023 The Bootstrap Authors - * Licensed under the Creative Commons Attribution 3.0 Unported License. - * Updates for {pkgdown} by the {bslib} authors, also licensed under CC-BY-3.0. - */ - -const getStoredTheme = () => localStorage.getItem('theme') -const setStoredTheme = theme => localStorage.setItem('theme', theme) - -const getPreferredTheme = () => { - const storedTheme = getStoredTheme() - if (storedTheme) { - return storedTheme - } - - return window.matchMedia('(prefers-color-scheme: dark)').matches ? 'dark' : 'light' -} - -const setTheme = theme => { - if (theme === 'auto') { - document.documentElement.setAttribute('data-bs-theme', (window.matchMedia('(prefers-color-scheme: dark)').matches ? 'dark' : 'light')) - } else { - document.documentElement.setAttribute('data-bs-theme', theme) - } -} - -function bsSetupThemeToggle() { - 'use strict' - - const showActiveTheme = (theme, focus = false) => { - var activeLabel, activeIcon; - - document.querySelectorAll('[data-bs-theme-value]').forEach(element => { - const buttonTheme = element.getAttribute('data-bs-theme-value') - const isActive = buttonTheme == theme - - element.classList.toggle('active', isActive) - element.setAttribute('aria-pressed', isActive) - - if (isActive) { - activeLabel = element.textContent; - activeIcon = element.querySelector('span').classList.value; - } - }) - - const themeSwitcher = document.querySelector('#dropdown-lightswitch') - if (!themeSwitcher) { - return - } - - themeSwitcher.setAttribute('aria-label', activeLabel) - themeSwitcher.querySelector('span').classList.value = activeIcon; - - if (focus) { - themeSwitcher.focus() - } - } - - window.matchMedia('(prefers-color-scheme: dark)').addEventListener('change', () => { - const storedTheme = getStoredTheme() - if (storedTheme !== 'light' && storedTheme !== 'dark') { - setTheme(getPreferredTheme()) - } - }) - - window.addEventListener('DOMContentLoaded', () => { - showActiveTheme(getPreferredTheme()) - - document - .querySelectorAll('[data-bs-theme-value]') - .forEach(toggle => { - toggle.addEventListener('click', () => { - const theme = toggle.getAttribute('data-bs-theme-value') - setTheme(theme) - setStoredTheme(theme) - showActiveTheme(theme, true) - }) - }) - }) -} - -setTheme(getPreferredTheme()); -bsSetupThemeToggle(); diff --git a/docs/link.svg b/docs/link.svg deleted file mode 100644 index 88ad827..0000000 --- a/docs/link.svg +++ /dev/null @@ -1,12 +0,0 @@ - - - - - - diff --git a/docs/news/index.html b/docs/news/index.html deleted file mode 100644 index 1fac14c..0000000 --- a/docs/news/index.html +++ /dev/null @@ -1,82 +0,0 @@ - -Changelog • CLAMP - Skip to contents - - -
          -
          -
          - -

          Changelog

          - Source: NEWS.md -
          - -
          -

          CLAMP 0.99.0

          -
          -

          New features

          -
          • Initial Bioconductor submission.
            • -
          • Implements prior-informed latent variable decomposition for gene expression.
            • -
          • Supports file-backed matrices (bigstatsr::FBM) for large datasets.
            • -
          • Added CPM, z-score, and filtering functions for preprocessing.
            • -
          • Projection of new datasets into pre-trained models.
            • -
          • Vignettes with example workflows and detailed documentation.
            • -
          -
          -

          Improvements

          -
          • Optimized in-place operations for large matrices.
            • -
          • Added cross-validation utilities and adaptive sparsity support.
            • -
          • Roxygen2 documentation for all exported functions.
            • -
          -
          -

          Bug fixes

          -
          • Fixed edge case in CPM normalization for zero-count columns.
            • -
          • Corrected NA handling in preprocessing.
            • -
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
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- element.setAttribute('data-bs-original-title', msg); - $(element).tooltip('show'); - element.setAttribute('data-bs-original-title', tooltipOriginalTitle); - } - - if (ClipboardJS.isSupported()) { - $(document).ready(function () { - var copyButton = ""; - - $("div.sourceCode").addClass("hasCopyButton"); - - // Insert copy buttons: - $(copyButton).prependTo(".hasCopyButton"); - - // Initialize tooltips: - $('.btn-copy-ex').tooltip({ container: 'body' }); - - // Initialize clipboard: - var clipboard = new ClipboardJS('[data-clipboard-copy]', { - text: function (trigger) { - return trigger.parentNode.textContent.replace(/\n#>[^\n]*/g, ""); - } - }); - - clipboard.on('success', function (e) { - changeTooltipMessage(e.trigger, 'Copied!'); - e.clearSelection(); - }); - - clipboard.on('error', function (e) { - changeTooltipMessage(e.trigger, 'Press Ctrl+C or Command+C to copy'); - }); - - }); - } - - /* Search marking --------------------------*/ - var url = new URL(window.location.href); - var toMark = url.searchParams.get("q"); - var mark = new Mark("main#main"); - if (toMark) { - mark.mark(toMark, { - accuracy: { - value: "complementary", - limiters: [",", ".", ":", "/"], - } - }); - } - - /* Search --------------------------*/ - /* Adapted from https://github.com/rstudio/bookdown/blob/2d692ba4b61f1e466c92e78fd712b0ab08c11d31/inst/resources/bs4_book/bs4_book.js#L25 */ - // Initialise search index on focus - var fuse; - $("#search-input").focus(async function (e) { - if (fuse) { - return; - } - - $(e.target).addClass("loading"); - var response = await fetch($("#search-input").data("search-index")); - var data = await response.json(); - - var options = { - keys: ["what", "text", "code"], - ignoreLocation: true, - threshold: 0.1, - includeMatches: true, - includeScore: true, - }; - fuse = new Fuse(data, options); - - $(e.target).removeClass("loading"); - }); - - // Use algolia autocomplete - var options = { - autoselect: true, - debug: true, - hint: false, - minLength: 2, - }; - var q; - async function searchFuse(query, callback) { - await fuse; - - var items; - if (!fuse) { - items = []; - } else { - q = query; - var results = fuse.search(query, { limit: 20 }); - items = results - .filter((x) => x.score <= 0.75) - .map((x) => x.item); - if (items.length === 0) { - items = [{ dir: "Sorry 😿", previous_headings: "", title: "No results found.", what: "No results found.", path: window.location.href }]; - } - } - callback(items); - } - $("#search-input").autocomplete(options, [ - { - name: "content", - source: searchFuse, - templates: { - suggestion: (s) => { - if (s.title == s.what) { - return `${s.dir} >
          ${s.title}
          `; - } else if (s.previous_headings == "") { - return `${s.dir} >
          ${s.title}
          > ${s.what}`; - } else { - return `${s.dir} >
          ${s.title}
          > ${s.previous_headings} > ${s.what}`; - } - }, - }, - }, - ]).on('autocomplete:selected', function (event, s) { - window.location.href = s.path + "?q=" + q + "#" + s.id; - }); - }); -})(window.jQuery || window.$) - -document.addEventListener('keydown', function (event) { - // Check if the pressed key is '/' - if (event.key === '/') { - event.preventDefault(); // Prevent any default action associated with the '/' key - document.getElementById('search-input').focus(); // Set focus to the search input - } -}); diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml deleted file mode 100644 index 35dba8e..0000000 --- a/docs/pkgdown.yml +++ /dev/null @@ -1,10 +0,0 @@ -pandoc: 2.9.2.1 -pkgdown: 2.2.0 -pkgdown_sha: ~ -articles: - comparing_clampbase_clampfull: comparing_clampbase_clampfull.html - get_started: get_started.html -last_built: 2026-05-05T22:21Z -urls: - reference: https://mchikina.github.io/CLAMP/reference - article: https://mchikina.github.io/CLAMP/articles diff --git a/docs/reference/AUC.html b/docs/reference/AUC.html deleted file mode 100644 index fea6ac6..0000000 --- a/docs/reference/AUC.html +++ /dev/null @@ -1,98 +0,0 @@ - -Compute AUC using Wilcoxon rank-sum test — AUC • CLAMP - Skip to contents - - -
          -
          -
          - -

          Compute AUC using Wilcoxon rank-sum test

          - Source: R/solvers.R -
          AUC.Rd
          -
          - -
          -

          Computes the area under the ROC curve (AUC) by applying a Wilcoxon rank-sum test -between predicted values for positive and negative labels. This is equivalent to -computing the Mann-Whitney U statistic.

          -
          - -
          -

          Usage

          - 
          AUC(labels, values)
          -
          - -
          -

          Arguments

          - - -
          labels
          -

          A numeric or logical vector indicating class labels. Values > 0 are treated as positive.

          - - -
          values
          -

          A numeric vector of prediction scores corresponding to labels.

          - -
          -
          -

          Value

          -

          A list with:

          auc
          -

          Estimated AUC, or 0.5 if one class is missing

          - -
          pval
          -

          Wilcoxon test p-value, or NA if one class is missing

          - - -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/BH.html b/docs/reference/BH.html deleted file mode 100644 index cd4a6b8..0000000 --- a/docs/reference/BH.html +++ /dev/null @@ -1,85 +0,0 @@ - -Adjust p-values using Benjamini-Hochberg method — BH • CLAMP - Skip to contents - - -
          -
          -
          - -

          Adjust p-values using Benjamini-Hochberg method

          - Source: R/solvers.R -
          BH.Rd
          -
          - -
          -

          Applies the BH (Benjamini-Hochberg) correction for -multiple hypothesis testing.

          -
          - -
          -

          Usage

          - 
          BH(p)
          -
          - -
          -

          Arguments

          - - -
          p
          -

          Numeric vector of p-values.

          - -
          -
          -

          Value

          -

          Adjusted p-values.

          -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/CLAMPbase.html b/docs/reference/CLAMPbase.html deleted file mode 100644 index 5cef9c1..0000000 --- a/docs/reference/CLAMPbase.html +++ /dev/null @@ -1,232 +0,0 @@ - -CLAMP base matrix factorization — CLAMPbase • CLAMP - Skip to contents - - -
          -
          -
          - -

          CLAMP base matrix factorization

          - Source: R/solvers.R -
          CLAMPbase.Rd
          -
          - -
          -

          Runs the core matrix factorization procedure of CLAMP, -decomposing the gene expression matrix Y into latent variables Z and loadings B. -It supports sparse, dense, and Filebacked Big Matrices (FBM) as input and includes options for -adaptive sparsity, positive constraints, and regularization.

          -
          - -
          -

          Usage

          - 
          CLAMPbase(
-  Y,
-  clamp_k = NULL,
-  svd_k = NULL,
-  svdres = NULL,
-  L1 = NULL,
-  L2 = NULL,
-  Zpos = TRUE,
-  max.iter = 200,
-  tol = 5e-04,
-  trace = FALSE,
-  rseed = NULL,
-  B = NULL,
-  scale = 1,
-  pos.adj = 3,
-  adaptive.p = 0.05,
-  adaptive.iter = 20,
-  cutoff = 0,
-  ncores = 1,
-  clamp_k_method = "elbow"
-)
          -
          - -
          -

          Arguments

          - - -
          Y
          -

          Input gene expression matrix (genes x samples). Can be dense, sparse (dgCMatrix), or FBM.

          - - -
          clamp_k
          -

          Number of latent variables for CLAMP (final model rank). -If NULL, it is chosen automatically via select_clamp_k().

          - - -
          svd_k
          -

          Number of singular values/components to compute in the SVD. -If NULL, defaults to max(2, min(n_genes, n_samples) - 1).

          - - -
          svdres
          -

          Optional precomputed SVD result. If not supplied, it is computed internally.

          - - -
          L1
          -

          L1 regularization strength for Z. Defaults to scaled singular value.

          - - -
          L2
          -

          L2 regularization strength for B. Defaults to scaled singular value.

          - - -
          Zpos
          -

          Logical; if TRUE, negative entries in Z are zeroed. Default is TRUE.

          - - -
          max.iter
          -

          Maximum number of optimization iterations. Default is 200.

          - - -
          tol
          -

          Convergence tolerance for B update. Default is 5e-4.

          - - -
          trace
          -

          Logical; if TRUE, prints progress. Default is FALSE.

          - - -
          rseed
          -

          Optional integer for reproducible random initialization of B.

          - - -
          B
          -

          Optional initial matrix for B. If not provided, initialized from SVD.

          - - -
          scale
          -

          Scaling factor for L1 and L2 when not provided. Default is 1.

          - - -
          pos.adj
          -

          Positive constraint adjustment divisor for L1. Default is 3.

          - - -
          adaptive.p
          -

          Controls adaptive sparsity in Z. After each ALS update, -negative entries in Z are assumed to reflect noise. -The cutoff for thresholding is set according to the probability of positive values under -a reflected negative distribution—effectively zeroing out small positive entries likely to be noise. -Smaller values lead to more sparsity. Default is 0.05.

          - - -
          adaptive.iter
          -

          Number of iterations before adaptive sparsity is applied. Default is 20.

          - - -
          cutoff
          -

          Scalar threshold to zero Z values when Zpos = TRUE and adaptive thresholding -is not used. Default is 0.

          - - -
          ncores
          -

          Number of cores to use for parallel computation (only used if Y is an FBM). Default is 1.

          - - -
          clamp_k_method
          -

          Method for selecting clamp_k when not provided. -One of "elbow" (default), "permutation", "gavish_donoho", or -"scaleSVs". Passed to select_clamp_k().

          - -
          -
          -

          Value

          -

          A list with components:

          B
          -

          Latent variable loadings (LVs x genes)

          - -
          Z
          -

          Latent variable scores (LVs x samples)

          - -
          Zraw
          -

          Raw Z matrix before thresholding

          - -
          L1
          -

          Final value of L1 used

          - -
          L2
          -

          Final value of L2 used

          - - -
          -
          -

          Details

          -

          This function is the low-level implementation of CLAMP. It alternates between solving for Z -given B and solving for B given Z, with optional sparsity and non-negativity -constraints on Z. Convergence is assessed via relative change in B.

          -
          - -
          -

          Examples

          - 
          # small toy dataset: 5 genes x 4 samples
-Y <- matrix(rnorm(5 * 4), nrow = 5, ncol = 4)
-# run a single iteration for speed
-res <- CLAMPbase(Y, clamp_k = 2, max.iter = 1, trace = FALSE)
-#> ****
-#> Computing SVD
-#> CLAMP k is set to 2
-#> L1 is set to 0.734790510178155
-#> L2 is set to 2.20437153053447
-# inspect dimensions of B and Z
-dim(res$B)
-#> [1] 2 4
-dim(res$Z)
-#> [1] 5 2
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
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          -
          -
          - -

          Dot plot of top pathways for a single latent variable

          - Source: R/plots.R -
          CLAMPdotplot.Rd
          -
          - -
          -

          Lollipop-style dot plot showing the top pathways associated with one -selected LV. Dot size encodes AUC; dot colour encodes -log10(FDR). -The x-axis and pathway ordering can use either AUC or -log10(FDR).

          -
          - -
          -

          Usage

          - 
          CLAMPdotplot(
-  clampRes,
-  lv = 1,
-  top = 20,
-  auc.cutoff = 0.6,
-  fdr.cutoff = 0.05,
-  max.name.len = 50,
-  x.axis = c("AUC", "-log10(FDR)", "log10FDR"),
-  order.by = x.axis
-)
          -
          - -
          -

          Arguments

          - - -
          clampRes
          -

          A CLAMP result list containing a summary data frame, or -the summary data frame itself.

          - - -
          lv
          -

          LV to plot: either a numeric index (e.g. 1 -> "LV1") or a -character name (e.g. "LV3"). Default 1.

          - - -
          top
          -

          Maximum number of pathways to display, chosen by order.by. -Default 20.

          - - -
          auc.cutoff
          -

          Minimum AUC to display. Default 0.6.

          - - -
          fdr.cutoff
          -

          Maximum FDR to display. Default 0.05.

          - - -
          max.name.len
          -

          Maximum characters for pathway label trimming. -Default 50.

          - - -
          x.axis
          -

          Metric to place on the x-axis. Use "AUC" or -"-log10(FDR)". "log10FDR" is also accepted. Default "AUC".

          - - -
          order.by
          -

          Metric used to choose the top pathways and order the y-axis. -Use "AUC" or "-log10(FDR)". "log10FDR" is also accepted. Defaults -to x.axis.

          - -
          -
          -

          Value

          -

          Invisibly returns a ggplot2::ggplot() object.

          -
          - -
          -

          Examples

          - 
          set.seed(9)
-pathways <- paste0("Pathway_", 1:20)
-lvs      <- paste0("LV", 1:5)
-nr       <- length(pathways) * length(lvs)
-
-summ <- data.frame(
-  pathway = rep(pathways, length(lvs)),
-  LV      = rep(lvs, each = length(pathways)),
-  AUC     = runif(nr, 0.5, 1.0),
-  FDR     = runif(nr, 0, 0.05),
-  stringsAsFactors = FALSE
-)
-
-CLAMPdotplot(list(summary = summ), lv = 1, top = 10)
-
-CLAMPdotplot(list(summary = summ), lv = "LV2", x.axis = "-log10(FDR)",
-             order.by = "-log10(FDR)")
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
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          -
          -
          - -

          Dot plot of pathway-LV associations across all latent variables

          - Source: R/plots.R -
          CLAMPdotplotAll.Rd
          -
          - -
          -

          Produces a dot plot where each point represents one pathway × LV pair. -Dot size encodes the AUC value and dot colour encodes -log10(FDR). Only -associations passing auc.cutoff and fdr.cutoff are shown.

          -
          - -
          -

          Usage

          - 
          CLAMPdotplotAll(
-  clampRes,
-  auc.cutoff = 0.6,
-  fdr.cutoff = 0.05,
-  top.per.lv = NULL,
-  max.name.len = 40
-)
          -
          - -
          -

          Arguments

          - - -
          clampRes
          -

          A CLAMP result list containing a summary data frame with -columns pathway, LV, AUC, and FDR. Alternatively, clampRes -may be the summary data frame itself.

          - - -
          auc.cutoff
          -

          Minimum AUC to display. Default 0.6.

          - - -
          fdr.cutoff
          -

          Maximum FDR to display. Default 0.05.

          - - -
          top.per.lv
          -

          Maximum number of pathways to display per LV, chosen by -highest AUC. NULL shows all. Default NULL.

          - - -
          max.name.len
          -

          Maximum characters for pathway label trimming. -Default 40.

          - -
          -
          -

          Value

          -

          Invisibly returns a ggplot2::ggplot() object.

          -
          - -
          -

          Examples

          - 
          set.seed(9)
-pathways <- paste0("Pathway_", 1:20)
-lvs      <- paste0("LV", 1:5)
-nr       <- length(pathways) * length(lvs)
-
-summ <- data.frame(
-  pathway = rep(pathways, length(lvs)),
-  LV      = rep(lvs, each = length(pathways)),
-  AUC     = runif(nr, 0.5, 1.0),
-  FDR     = runif(nr, 0, 0.2),
-  stringsAsFactors = FALSE
-)
-
-CLAMPdotplotAll(list(summary = summ), auc.cutoff = 0.6, fdr.cutoff = 0.15)
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/CLAMPfull.html b/docs/reference/CLAMPfull.html deleted file mode 100644 index 523cc5d..0000000 --- a/docs/reference/CLAMPfull.html +++ /dev/null @@ -1,331 +0,0 @@ - -Runs the streamlined full CLAMP model. — CLAMPfull • CLAMP - Skip to contents - - -
          -
          -
          - -

          Runs the streamlined full CLAMP model.

          - Source: R/solvers.R -
          CLAMPfull.Rd
          -
          - -
          -

          This version performs latent-variable decomposition of a gene expression matrix Y -guided by prior pathway annotations priorMat, with simplified and lighter regularization -compared to the original extended CLAMP variant. The algorithm alternates updates of Z, -B, and U, where U captures pathway–latent variable associations inferred -directly from the data without ridge-regularized projections (Chat is not used).

          -
          - -
          -

          Usage

          - 
          CLAMPfull(
-  Y,
-  priorMat,
-  Chat = NULL,
-  svdres = NULL,
-  clamp.base.result = NULL,
-  clamp_k = NULL,
-  svd_k = NULL,
-  L1 = NULL,
-  L2 = NULL,
-  cvn = 5,
-  max.iter = 30,
-  trace = TRUE,
-  maxPath = 10,
-  doCrossval = TRUE,
-  penalty.factor = rep(1, ncol(priorMat)),
-  glm_alpha = 0.9,
-  minGenes = 0,
-  tol = 5e-04,
-  seed = 123456,
-  allGenes = FALSE,
-  rseed = NULL,
-  max.U.updates = Inf,
-  pathwaySelection = c("fast", "complete"),
-  multiplier = 5,
-  adaptive.p = 0.05,
-  useNNLS = TRUE,
-  useRaw = TRUE,
-  refitEvery = 3,
-  useSE = FALSE,
-  var.prior = TRUE,
-  Uscale = FALSE,
-  robust.vp = TRUE,
-  use_cpp = FALSE,
-  clamp_k_method = "elbow"
-)
          -
          - -
          -

          Arguments

          - - -
          Y
          -

          Gene expression matrix (genes × samples). Can be dense, sparse (dgCMatrix), or FBM.

          - - -
          priorMat
          -

          Binary or weighted prior matrix (genes × pathways) linking genes to pathways.

          - - -
          Chat
          -

          Ignored in this version (kept for interface compatibility).

          - - -
          svdres
          -

          Optional precomputed SVD result for initialization.

          - - -
          clamp.base.result
          -

          Optional result from CLAMPbase() providing initial values.

          - - -
          clamp_k
          -

          Number of latent variables for CLAMP (final model rank). -If NULL, it is chosen automatically via select_clamp_k().

          - - -
          svd_k
          -

          Number of singular values/components to compute in the SVD. -If NULL, defaults to max(2, min(n_genes, n_samples) - 1).

          - - -
          L1, L2
          -

          Regularization parameters for Z and B. Defaults use values from -clamp.base.result.

          - - -
          cvn
          -

          Number of folds for pathway-level cross-validation. Default: 5.

          - - -
          max.iter
          -

          Maximum number of outer iterations. Default: 30.

          - - -
          trace
          -

          Logical; print iteration progress. Default: TRUE.

          - - -
          maxPath
          -

          Maximum number of pathways per LV during U-fitting. Default: 10.

          - - -
          doCrossval
          -

          Whether to mask prior entries for CV evaluation. Default: TRUE.

          - - -
          penalty.factor
          -

          Optional vector of per-pathway penalties for glmnet. Default: 1.

          - - -
          glm_alpha
          -

          Elastic net mixing parameter for U estimation. Default: 0.9.

          - - -
          minGenes
          -

          Minimum number of genes per pathway. Default: 0.

          - - -
          tol
          -

          Convergence tolerance for B updates. Default: 5e-4.

          - - -
          seed
          -

          Random seed for CV masking. Default: 123456.

          - - -
          allGenes
          -

          If TRUE, adds zero-filled rows for missing genes. Default: FALSE.

          - - -
          rseed
          -

          Reproducibility, coordinate descent updates are done in random order.

          - - -
          max.U.updates
          -

          Maximum number of U updates (capped by max.iter).

          - - -
          pathwaySelection
          -

          Pathway selection mode for U fitting ("fast" or "complete").

          - - -
          multiplier
          -

          Variance-prior scaling factor. Default: 5.

          - - -
          adaptive.p
          -

          Quantile of negative Z values used to define adaptive thresholding. Default: 0.05.

          - - -
          useNNLS
          -

          Whether to use non-negative least squares for U estimation. Default: TRUE.

          - - -
          useRaw
          -

          If TRUE, uses unthresholded Z in U updates. Default: TRUE.

          - - -
          refitEvery
          -

          Frequency (in U updates) of full refits. Default: 3.

          - - -
          useSE
          -

          Logical; whether to use the 1-standard-error rule for internal glmnet fitting. Default is FALSE.

          - - -
          var.prior
          -

          Logical; if TRUE, enables adaptive variance prior updates for Z. -Default: TRUE.

          - - -
          Uscale
          -

          Logical; whether to scale U columns. Default: FALSE.

          - - -
          robust.vp
          -

          Logical; winsorize prior-predicted Z2 values to reduce outlier effects. Default: TRUE.

          - - -
          use_cpp
          -

          Logical; if TRUE, use C++ implementation for Z updates. Default is FALSE.

          - - -
          clamp_k_method
          -

          Method for selecting clamp_k when not provided. -One of "elbow" (default), "permutation", "gavish_donoho", or -"scaleSVs". Passed to select_clamp_k().

          - -
          -
          -

          Value

          -

          A list with elements:

          B
          -

          LV loadings on samples (k × samples)

          - -
          Z
          -

          Gene loadings (genes × k)

          - -
          U
          -

          Pathway loadings (pathways × k)

          - -
          C
          -

          Prior matrix used during training (masked if CV)

          - -
          Z2
          -

          Predicted Z from pathway priors

          - -
          heldOutGenes
          -

          Held-out gene lists per pathway (CV mode)

          - -
          Uauc, Up, summary
          -

          CV evaluation metrics if CV is enabled

          - -
          priorMat, priorMatCV
          -

          Final and masked prior matrices

          - -
          call
          -

          Function call

          - - -
          -
          -

          Details

          -

          Cross-validation can be used to evaluate pathway–LV specificity, and a variance-based prior -(var.prior = TRUE) introduces adaptive shrinkage of Z based on how strongly -each latent component aligns with prior pathways. The scaling factor multiplier (default 5) -controls the strength of this adaptive shrinkage.

          -

          This implementation omits ridge-projected priors (Chat) and uses a lighter variance prior -with a lower default multiplier = 5, allowing more flexible latent representations. -Setting var.prior = FALSE reproduces standard CLAMP-like updates. Cross-validation, if -enabled, masks 20% of gene–pathway associations per column to estimate pathway–LV specificity -(reported via AUC and p-values).

          -
          - -
          -

          Examples

          - 
          set.seed(1)
-mat <- matrix(rnorm(100), nrow = 10, ncol = 10)
-base <- CLAMPbase(mat, clamp_k = 5, trace = FALSE, max.iter = 5)
-#> ****
-#> Computing SVD
-#> CLAMP k is set to 5
-#> L1 is set to 0.736045659723087
-#> L2 is set to 2.20813697916926
-prior <- matrix(sample(0:1, 10 * 6, TRUE, prob = c(0.9, 0.1)),
-                nrow = 10, ncol = 6)
-fit <- CLAMPfull(
-  Y = mat,
-  priorMat = prior,
-  clamp.base.result = base,
-  doCrossval = FALSE,
-  adaptive.p = 0,
-  max.U.updates = 0,
-  max.iter = 1,
-  trace = FALSE
-)
-#> ** CLAMPfull **
-#> using provided CLAMPbase result
-#> CLAMP k is set to 5
-#> L1=0.736045659723087; L2=2.20813697916926
-#> Not using cross-validation. No AUCs or p-values
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/CLAMPfullnVP.html b/docs/reference/CLAMPfullnVP.html deleted file mode 100644 index 7d77e13..0000000 --- a/docs/reference/CLAMPfullnVP.html +++ /dev/null @@ -1,321 +0,0 @@ - -Full CLAMP model with prior information and cross-validation — CLAMPfullnVP • CLAMP - Skip to contents - - -
          -
          -
          - -

          Full CLAMP model with prior information and cross-validation

          - Source: R/solvers.R -
          CLAMPfullnVP.Rd
          -
          - -
          -

          Runs the full CLAMP model using a gene expression matrix -and prior pathway annotation matrix. This function performs latent variable decomposition -guided by prior knowledge and includes optional cross-validation to evaluate pathway associations.

          -
          - -
          -

          Usage

          - 
          CLAMPfullnVP(
-  Y,
-  priorMat,
-  svdres = NULL,
-  clamp.base.result = NULL,
-  clamp_k = NULL,
-  svd_k = NULL,
-  L1 = NULL,
-  L2 = NULL,
-  top = NULL,
-  cvn = 5,
-  max.iter = 350,
-  trace = FALSE,
-  Chat = NULL,
-  maxPath = 10,
-  doCrossval = TRUE,
-  penalty.factor = rep(1, ncol(priorMat)),
-  glm_alpha = 0.9,
-  minGenes = 10,
-  tol = 5e-04,
-  seed = 123456,
-  allGenes = FALSE,
-  rseed = NULL,
-  max.U.updates = 5,
-  pathwaySelection = c("fast"),
-  multiplier = 1,
-  adaptive.p = 0.05,
-  useNNLS = TRUE,
-  useRaw = TRUE,
-  refitAll = FALSE,
-  useSE = FALSE,
-  ncores = 1,
-  clamp_k_method = "elbow"
-)
          -
          - -
          -

          Arguments

          - - -
          Y
          -

          Gene expression matrix (genes x samples). Can be dense, sparse (dgCMatrix), or FBM.

          - - -
          priorMat
          -

          Binary matrix (genes x pathways) representing prior annotations.

          - - -
          svdres
          -

          Optional SVD result used for initialization.

          - - -
          clamp.base.result
          -

          Optional result from CLAMPbase() to initialize B.

          - - -
          clamp_k
          -

          Number of latent variables for CLAMP (final model rank). -If NULL, it is chosen automatically via select_clamp_k().

          - - -
          svd_k
          -

          Number of singular values/components to compute in the SVD. -If NULL, defaults to max(2, min(n_genes, n_samples) - 1).

          - - -
          L1
          -

          Regularization strength for Z. If NULL, initialized from SVD or clamp.base.result.

          - - -
          L2
          -

          Regularization strength for B. If NULL, initialized from SVD or clamp.base.result.

          - - -
          top
          -

          If set, keeps only top-n values per column in Z during U updates.

          - - -
          cvn
          -

          Number of folds for cross-validation in U updates. Default is 5.

          - - -
          max.iter
          -

          Maximum number of iterations. Default is 350.

          - - -
          trace
          -

          Logical; if TRUE, prints iteration progress.

          - - -
          Chat
          -

          Optional precomputed matrix for solving U.

          - - -
          maxPath
          -

          Maximum number of pathways/features selected per LV. Default is 10.

          - - -
          doCrossval
          -

          Whether to perform pathway-level cross-validation. Default is TRUE.

          - - -
          penalty.factor
          -

          Vector of feature-specific penalties for glmnet. Default: all ones.

          - - -
          glm_alpha
          -

          Elastic net mixing parameter for glmnet. Default is 0.9.

          - - -
          minGenes
          -

          Minimum number of genes per pathway to retain. Default is 10.

          - - -
          tol
          -

          Convergence tolerance on relative change in B. Default is 5e-4.

          - - -
          seed
          -

          Seed for reproducibility of cross-validation masking. Default is 123456.

          - - -
          allGenes
          -

          If TRUE, zero-fills priorMat for genes not present. Default is FALSE.

          - - -
          rseed
          -

          Optional seed for randomly reinitializing B and Z.

          - - -
          max.U.updates
          -

          Maximum number of U updates. Default is 5.

          - - -
          pathwaySelection
          -

          Pathway selection mode: "fast" or "complete".

          - - -
          multiplier
          -

          Scaling factor for adjusting L1 and L2.

          - - -
          adaptive.p
          -

          Quantile threshold for adaptively zeroing small Z values. After each update, -the adaptive.p-quantile of negative entries in Z is used (flipped positive) to threshold -small positive values, assuming they reflect noise. Default is 0.05.

          - - -
          useNNLS
          -

          If TRUE, uses non-negative least squares in U estimation. Default is TRUE.

          - - -
          useRaw
          -

          If TRUE, uses unthresholded Z for solving U. Default is TRUE.

          - - -
          refitAll
          -

          If TRUE, refits all U columns every update. Default is FALSE.

          - - -
          useSE
          -

          Logical; passed to the internal solveU() call. If TRUE, -enables standard-error–aware selection when fitting U (pathway coefficients). Default is FALSE.

          - - -
          ncores
          -

          Number of cores to use for parallel computation (only used if Y is an FBM). Default is 1.

          - - -
          clamp_k_method
          -

          Method for selecting clamp_k when not provided. -One of "elbow" (default), "permutation", "gavish_donoho", or -"scaleSVs". Passed to select_clamp_k().

          - -
          -
          -

          Value

          -

          A list with the following components:

          B
          -

          Latent variable loadings (LVs x genes)

          - -
          Z
          -

          Latent variable matrix (LVs x samples)

          - -
          U
          -

          Pathway loadings matrix (pathways x LVs)

          - -
          C
          -

          Masked prior matrix used for training

          - -
          L1, L2
          -

          Regularization parameters

          - -
          heldOutGenes
          -

          List of held-out genes per pathway (if CV is enabled)

          - -
          Uauc
          -

          AUC matrix from CV evaluation (if enabled)

          - -
          Up
          -

          -log10(p) values from CV evaluation (if enabled)

          - -
          summary
          -

          Data frame of AUC, p-values, and FDR per pathway x LV (if enabled)

          - -
          priorMatCV
          -

          Masked prior matrix used during CV

          - -
          priorMat
          -

          Final filtered prior matrix

          - -
          withPrior
          -

          Indices of LVs with non-zero pathway loadings

          - -
          call
          -

          Function call

          - - -
          -
          -

          Details

          -

          The model alternates between solving Z, B, and U. Adaptive sparsity is applied -to Z using a dynamic threshold based on the negative tail of its distribution. Cross-validation -is used to hold out gene annotations in priorMat and evaluate latent variable specificity.

          -
          - -
          -

          Examples

          - 
          mat <- matrix(rnorm(100), 10, 10)
-svdres <- rsvd::rsvd(mat, k = 5)
-base <- CLAMPbase(Y = mat, clamp_k = 5, svdres = svdres, trace = FALSE)
-#> ****
-#> CLAMP k is set to 5
-#> L1 is set to 0.901075915083534
-#> L2 is set to 2.7032277452506
-#> Converged at iteration= 31 | Bdiff=0.000000,  tol=0.000500     
-priorMat <- matrix(1, nrow(mat), 5)
-full <- CLAMPfullnVP(
-    Y = mat, priorMat = priorMat, svdres = svdres,
-    clamp.base.result = base, clamp_k = 5,
-    doCrossval = FALSE, trace = FALSE, max.U.updates = 0
-)
-#> **CLAMPfullnVP v2 **
-#> using provided CLAMPbase result
-#> CLAMP k is set to 5
-#> L1=0.901075915083534; L2=2.7032277452506
-#> 
Converged at 8 / 350 | Bdiff=0.000000, minCor=1.000000
-#> Not using cross-validation. No AUCs or p-values
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
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          -
          -
          - -

          Plot top genes per LV by Z loading

          - Source: R/plots.R -
          CLAMPplotTopZ.Rd
          -
          - -
          -

          For each selected latent variable, ranks genes by their Z loading and plots -the top genes as a loading-versus-rank scatter plot. The highest ranking -genes are labelled with ggrepel.

          -
          - -
          -

          Usage

          - 
          CLAMPplotTopZ(
-  clampRes,
-  data = NULL,
-  priorMat = NULL,
-  top = 50,
-  index = NULL,
-  allLVs = FALSE,
-  label.top = min(10, top),
-  max.name.len = 50
-)
          -
          - -
          -

          Arguments

          - - -
          clampRes
          -

          A CLAMP result list containing at least Z, and optionally -U for selecting LVs with pathway support.

          - - -
          data
          -

          Deprecated; retained for backward compatibility and ignored.

          - - -
          priorMat
          -

          Deprecated; retained for backward compatibility and ignored.

          - - -
          top
          -

          Number of top genes to plot per LV. Default 50.

          - - -
          index
          -

          Integer or character vector of LV columns to include. NULL -keeps LVs with non-zero U entries when U is present.

          - - -
          allLVs
          -

          Logical; if TRUE, all LVs are eligible when index = NULL. -Default FALSE.

          - - -
          label.top
          -

          Number of top genes to label per LV. Default min(10, top).

          - - -
          max.name.len
          -

          Maximum characters for displayed gene labels.

          - -
          -
          -

          Value

          -

          A ggplot2::ggplot() object for one LV, or a patchwork object for -multiple LVs.

          -
          - -
          -

          Examples

          - 
          set.seed(1)
-genes <- paste0("Gene", 1:80)
-lvs   <- paste0("LV", 1:4)
-paths <- paste0("Path", 1:10)
-Z     <- matrix(abs(rnorm(80 * 4)), nrow = 80,
-                dimnames = list(genes, lvs))
-U     <- matrix(abs(rnorm(10 * 4)), nrow = 10,
-                dimnames = list(paths, lvs))
-clampRes <- list(Z = Z, U = U)
-CLAMPplotTopZ(clampRes, top = 20, index = 1:2)
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
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zobo%$tEw7-plNJtlkb+Je*NCT@we2#ildvm@jE$E95Bf@fdZViF8HzQ+)w|0e`I6w YGMaX>M7Ko2n_#e~wEjr@{nE|<0_VE7`~Uy| diff --git a/docs/reference/CLAMPplotU.html b/docs/reference/CLAMPplotU.html deleted file mode 100644 index e40ba38..0000000 --- a/docs/reference/CLAMPplotU.html +++ /dev/null @@ -1,158 +0,0 @@ - -Plot the U matrix (pathway-LV associations) as a heatmap — CLAMPplotU • CLAMP - Skip to contents - - -
          -
          -
          - -

          Plot the U matrix (pathway-LV associations) as a heatmap

          - Source: R/plots.R -
          CLAMPplotU.Rd
          -
          - -
          -

          Displays the pathway loading matrix U after filtering by AUC and FDR -thresholds. Only the top-top pathways per LV are shown.

          -
          - -
          -

          Usage

          - 
          CLAMPplotU(
-  clampRes,
-  auc.cutoff = 0.6,
-  fdr.cutoff = 0.05,
-  indexCol = NULL,
-  indexRow = NULL,
-  top = 3,
-  sort.row = FALSE,
-  cluster.rows = TRUE
-)
          -
          - -
          -

          Arguments

          - - -
          clampRes
          -

          A CLAMP result list containing at least U, Uauc, Up, -and summary.

          - - -
          auc.cutoff
          -

          Minimum AUC threshold; entries below this are set to zero. -Default 0.6.

          - - -
          fdr.cutoff
          -

          Maximum FDR threshold for pathway significance filtering. -Default 0.05.

          - - -
          indexCol
          -

          Integer vector of LV column indices to include. NULL uses -all LVs.

          - - -
          indexRow
          -

          Integer vector of pathway row indices to include. NULL uses -all pathways.

          - - -
          top
          -

          Number of top pathways to retain per LV. Default 3.

          - - -
          sort.row
          -

          Logical; if TRUE, rows are sorted by the dominant LV. -Default FALSE.

          - - -
          cluster.rows
          -

          Logical; if TRUE (default), rows are reordered by -hierarchical clustering (overridden when sort.row = TRUE).

          - -
          -
          -

          Value

          -

          Invisibly returns a ggplot2::ggplot() object.

          -
          - -
          -

          Examples

          - 
          set.seed(42)
-pathways <- paste0("Path", 1:30)
-lvs      <- paste0("LV",   1:5)
-
-U    <- matrix(abs(rnorm(30 * 5)), nrow = 30,
-               dimnames = list(pathways, lvs))
-Uauc <- matrix(runif(30 * 5, 0.5, 1.0), nrow = 30,
-               dimnames = list(pathways, lvs))
-Up   <- matrix(runif(30 * 5, 0, 3), nrow = 30,
-               dimnames = list(pathways, lvs))
-
-# Build a minimal summary table
-nr <- 30 * 5
-summ <- data.frame(
-  pathway = rep(pathways, 5),
-  LV      = rep(lvs, each = 30),
-  AUC     = as.vector(Uauc),
-  p_value = runif(nr, 0, 0.1),
-  FDR     = runif(nr, 0, 0.1),
-  stringsAsFactors = FALSE
-)
-
-clampRes <- list(U = U, Uauc = Uauc, Up = Up, summary = summ)
-CLAMPplotU(clampRes, auc.cutoff = 0.6, fdr.cutoff = 0.1, top = 3)
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/PLIERbase.html b/docs/reference/PLIERbase.html deleted file mode 100644 index 9a3ac46..0000000 --- a/docs/reference/PLIERbase.html +++ /dev/null @@ -1,203 +0,0 @@ - -PLIER base matrix factorization — PLIERbase • PLIER2 - Skip to contents - - -
          -
          -
          - -

          PLIER base matrix factorization

          - Source: R/solvers.R -
          PLIERbase.Rd
          -
          - -
          -

          Runs the core matrix factorization procedure of PLIER (Pathway-Level Information ExtractoR), -decomposing the gene expression matrix Y into latent variables Z and loadings B. -It supports sparse, dense, and Filebacked Big Matrices (FBM) as input and includes options for -adaptive sparsity, positive constraints, and regularization.

          -
          - -
          -

          Usage

          - 
          PLIERbase(
-  Y,
-  k,
-  svdres = NULL,
-  L1 = NULL,
-  L2 = NULL,
-  Zpos = T,
-  max.iter = 200,
-  tol = 5e-04,
-  trace = F,
-  rseed = NULL,
-  B = NULL,
-  scale = 1,
-  pos.adj = 3,
-  adaptive.p = 0.05,
-  adaptive.iter = 20,
-  cutoff = 0
-)
          -
          - -
          -

          Arguments

          - - -
          Y
          -

          Input gene expression matrix (genes x samples). Can be dense, sparse (dgCMatrix), or FBM.

          - - -
          k
          -

          Number of latent variables.

          - - -
          svdres
          -

          Optional precomputed SVD result. If not supplied, it is computed internally.

          - - -
          L1
          -

          L1 regularization strength for Z. Defaults to scaled singular value.

          - - -
          L2
          -

          L2 regularization strength for B. Defaults to scaled singular value.

          - - -
          Zpos
          -

          Logical; if TRUE, negative entries in Z are zeroed. Default is TRUE.

          - - -
          max.iter
          -

          Maximum number of optimization iterations. Default is 200.

          - - -
          tol
          -

          Convergence tolerance for B update. Default is 5e-4.

          - - -
          trace
          -

          Logical; if TRUE, prints progress. Default is FALSE.

          - - -
          rseed
          -

          Optional integer for reproducible random initialization of B.

          - - -
          B
          -

          Optional initial matrix for B. If not provided, initialized from SVD.

          - - -
          scale
          -

          Scaling factor for L1 and L2 when not provided. Default is 1.

          - - -
          pos.adj
          -

          Positive constraint adjustment divisor for L1. Default is 3.

          - - -
          adaptive.p
          -

          Controls adaptive sparsity in Z. After each ALS update, negative entries in Z are assumed to reflect noise. The cutoff for thresholding is set according to the probability of positive values under a reflected negative distribution—effectively zeroing out small positive entries likely to be noise. Smaller values lead to more sparsity. Default is 0.05.

          - - -
          adaptive.iter
          -

          Number of iterations before adaptive sparsity is applied. Default is 20.

          - - -
          cutoff
          -

          Scalar threshold to zero Z values when Zpos = TRUE and adaptive thresholding is not used. Default is 0.

          - -
          -
          -

          Value

          -

          A list with components:

          B
          -

          Latent variable loadings (LVs x genes)

          - -
          Z
          -

          Latent variable scores (LVs x samples)

          - -
          Zraw
          -

          Raw Z matrix before thresholding

          - -
          L1
          -

          Final value of L1 used

          - -
          L2
          -

          Final value of L2 used

          - - -
          -
          -

          Details

          -

          This function is the low-level implementation of PLIER. It alternates between solving for Z -given B and solving for B given Z, with optional sparsity and non-negativity -constraints on Z. Convergence is assessed via relative change in B.

          -
          - -
          -

          Examples

          - 
          # small toy dataset: 5 genes x 4 samples
-Y <- matrix(rnorm(5 * 4), nrow = 5, ncol = 4)
-# run a single iteration for speed
-res <- PLIERbase(Y, k = 2, max.iter = 1, trace = FALSE)
-#> ****
-#> Computing SVD
-#> [1] "L1 is set to 0.926903271141505"
-#> [1] "L2 is set to 2.78070981342451"
-# inspect dimensions of B and Z
-dim(res$B)
-#> [1] 2 4
-dim(res$Z)
-#> [1] 5 2
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.1.3.

          -
          - -
          - - - - - - - diff --git a/docs/reference/PLIERfull.html b/docs/reference/PLIERfull.html deleted file mode 100644 index df54a84..0000000 --- a/docs/reference/PLIERfull.html +++ /dev/null @@ -1,293 +0,0 @@ - -Full PLIER model with prior information and cross-validation — PLIERfull • PLIER2 - Skip to contents - - -
          -
          -
          - -

          Full PLIER model with prior information and cross-validation

          - Source: R/solvers.R -
          PLIERfull.Rd
          -
          - -
          -

          Runs the full PLIER (Pathway-Level Information ExtractoR) model using a gene expression matrix -and prior pathway annotation matrix. This function performs latent variable decomposition -guided by prior knowledge and includes optional cross-validation to evaluate pathway associations.

          -
          - -
          -

          Usage

          - 
          PLIERfull(
-  Y,
-  priorMat,
-  svdres = NULL,
-  plier.base.result = NULL,
-  k = NULL,
-  L1 = NULL,
-  L2 = NULL,
-  top = NULL,
-  cvn = 5,
-  max.iter = 350,
-  trace = F,
-  Chat = NULL,
-  maxPath = 10,
-  doCrossval = T,
-  penalty.factor = rep(1, ncol(priorMat)),
-  glm_alpha = 0.9,
-  minGenes = 10,
-  tol = 5e-04,
-  seed = 123456,
-  allGenes = F,
-  rseed = NULL,
-  max.U.updates = 5,
-  pathwaySelection = c("fast"),
-  multiplier = 1,
-  adaptive.p = 0.05,
-  useNNLS = T,
-  useRaw = T,
-  refitAll = F,
-  useSE = F
-)
          -
          - -
          -

          Arguments

          - - -
          Y
          -

          Gene expression matrix (genes x samples). Can be dense, sparse (dgCMatrix), or FBM.

          - - -
          priorMat
          -

          Binary matrix (genes x pathways) representing prior annotations.

          - - -
          svdres
          -

          Optional SVD result used for initialization.

          - - -
          plier.base.result
          -

          Optional result from PLIERbase() to initialize B.

          - - -
          k
          -

          Number of latent variables. If NULL, estimated from SVD.

          - - -
          L1
          -

          Regularization strength for Z. If NULL, initialized from SVD or plier.base.result.

          - - -
          L2
          -

          Regularization strength for B. If NULL, initialized from SVD or plier.base.result.

          - - -
          top
          -

          If set, keeps only top-n values per column in Z during U updates.

          - - -
          cvn
          -

          Number of folds for cross-validation in U updates. Default is 5.

          - - -
          max.iter
          -

          Maximum number of iterations. Default is 350.

          - - -
          trace
          -

          Logical; if TRUE, prints iteration progress.

          - - -
          Chat
          -

          Optional precomputed matrix for solving U.

          - - -
          maxPath
          -

          Maximum number of pathways/features selected per LV. Default is 10.

          - - -
          doCrossval
          -

          Whether to perform pathway-level cross-validation. Default is TRUE.

          - - -
          penalty.factor
          -

          Vector of feature-specific penalties for glmnet. Default: all ones.

          - - -
          glm_alpha
          -

          Elastic net mixing parameter for glmnet. Default is 0.9.

          - - -
          minGenes
          -

          Minimum number of genes per pathway to retain. Default is 10.

          - - -
          tol
          -

          Convergence tolerance on relative change in B. Default is 5e-4.

          - - -
          seed
          -

          Seed for reproducibility of cross-validation masking. Default is 123456.

          - - -
          allGenes
          -

          If TRUE, zero-fills priorMat for genes not present. Default is FALSE.

          - - -
          rseed
          -

          Optional seed for randomly reinitializing B and Z.

          - - -
          max.U.updates
          -

          Maximum number of U updates. Default is 5.

          - - -
          pathwaySelection
          -

          Pathway selection mode: "fast" or "complete".

          - - -
          multiplier
          -

          Scaling factor for adjusting L1 and L2.

          - - -
          adaptive.p
          -

          Quantile threshold for adaptively zeroing small Z values. After each update, -the adaptive.p-quantile of negative entries in Z is used (flipped positive) to threshold -small positive values, assuming they reflect noise. Default is 0.05.

          - - -
          useNNLS
          -

          If TRUE, uses non-negative least squares in U estimation. Default is TRUE.

          - - -
          useRaw
          -

          If TRUE, uses unthresholded Z for solving U. Default is TRUE.

          - - -
          refitAll
          -

          If TRUE, refits all U columns every update. Default is FALSE.

          - - -
          useSE
          -

          Logical; passed to the internal solveU() call. If TRUE, enables standard-error–aware selection when fitting U (pathway coefficients). Default is FALSE.

          - -
          -
          -

          Value

          -

          A list with the following components:

          B
          -

          Latent variable loadings (LVs x genes)

          - -
          Z
          -

          Latent variable matrix (LVs x samples)

          - -
          U
          -

          Pathway loadings matrix (pathways x LVs)

          - -
          C
          -

          Masked prior matrix used for training

          - -
          L1, L2
          -

          Regularization parameters

          - -
          heldOutGenes
          -

          List of held-out genes per pathway (if CV is enabled)

          - -
          Uauc
          -

          AUC matrix from CV evaluation (if enabled)

          - -
          Up
          -

          -log10(p) values from CV evaluation (if enabled)

          - -
          summary
          -

          Data frame of AUC, p-values, and FDR per pathway x LV (if enabled)

          - -
          priorMatCV
          -

          Masked prior matrix used during CV

          - -
          priorMat
          -

          Final filtered prior matrix

          - -
          withPrior
          -

          Indices of LVs with non-zero pathway loadings

          - -
          call
          -

          Function call

          - - -
          -
          -

          Details

          -

          The model alternates between solving Z, B, and U. Adaptive sparsity is applied -to Z using a dynamic threshold based on the negative tail of its distribution. Cross-validation -is used to hold out gene annotations in priorMat and evaluate latent variable specificity.

          -
          - -
          -

          Examples

          - 
          mat <- matrix(rnorm(100), 10, 10)
-svdres <- rsvd::rsvd(mat, k = 5)
-base <- PLIERbase(Y = mat, k = 5, svdres = svdres, trace = FALSE)
-#> ****
-#> [1] "L1 is set to 0.971985706716372"
-#> [1] "L2 is set to 2.91595712014912"
-#> Converged at iteration= 31 | Bdiff=0.000003,  tol=0.000500     
-priorMat <- matrix(1, nrow(mat), 5)
-full <- PLIERfull(Y = mat, priorMat = priorMat, svdres = svdres,
-                  plier.base.result = base, k = 5,
-                  doCrossval = FALSE, trace = FALSE, max.U.updates = 0)
-#> **PLIER v2 **
-#> using provided PLIERbase result
-#> L1=0.971985706716372; L2=2.91595712014912
-#> 
Converged at 8 / 350 | Bdiff=0.000000, minCor=1.000000
-#> Not using cross-validation. No AUCs or p-values
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.1.3.

          -
          - -
          - - - - - - - diff --git a/docs/reference/allAgainstAllAUCs.html b/docs/reference/allAgainstAllAUCs.html deleted file mode 100644 index 5ace975..0000000 --- a/docs/reference/allAgainstAllAUCs.html +++ /dev/null @@ -1,111 +0,0 @@ - -Compute all-vs-all AUC matrix — allAgainstAllAUCs • CLAMP - Skip to contents - - -
          -
          -
          - -

          Compute all-vs-all AUC matrix

          - Source: R/utils.R -
          allAgainstAllAUCs.Rd
          -
          - -
          -

          Calculates the area under the ROC curve (AUC) for all pairs of columns -between a prediction matrix B and binary targets in target. -Each column of B is ranked, and AUC is computed based on how well -the ranks separate positive vs. negative samples in each target column.

          -
          - -
          -

          Usage

          - 
          allAgainstAllAUCs(B, target)
          -
          - -
          -

          Arguments

          - - -
          B
          -

          A numeric matrix of predictions (samples × features).

          - - -
          target
          -

          A binary matrix of the same number of rows as B -(samples × targets), where 1 indicates positive and 0 indicates negative.

          - -
          -
          -

          Value

          -

          A numeric matrix of AUC values (features × targets).

          -
          - -
          -

          Examples

          - 
          set.seed(1)
-B <- matrix(rnorm(100), nrow = 20)
-target <- matrix(sample(0:1, 40, replace = TRUE), nrow = 20)
-allAgainstAllAUCs(B, target)
-#>           [,1]      [,2]
-#> [1,] 0.4848485 0.4895833
-#> [2,] 0.5959596 0.6354167
-#> [3,] 0.1919192 0.5520833
-#> [4,] 0.4545455 0.5000000
-#> [5,] 0.2929293 0.2500000
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/binarizeTop.html b/docs/reference/binarizeTop.html deleted file mode 100644 index 3261617..0000000 --- a/docs/reference/binarizeTop.html +++ /dev/null @@ -1,90 +0,0 @@ - -Binarize matrix by top-k values per column — binarizeTop • CLAMP - Skip to contents - - -
          -
          -
          - -

          Binarize matrix by top-k values per column

          - Source: R/solvers.R -
          binarizeTop.Rd
          -
          - -
          -

          Keeps only the top top values in each column of a matrix, setting others to 0.

          -
          - -
          -

          Usage

          - 
          binarizeTop(Z, top, keepVals = TRUE)
          -
          - -
          -

          Arguments

          - - -
          Z
          -

          A numeric matrix.

          - - -
          top
          -

          Number of top entries to keep in each column.

          - - -
          keepVals
          -

          If TRUE, retains original values above the cutoff; otherwise, sets them to 1.

          - -
          -
          -

          Value

          -

          A modified matrix with only top entries retained per column.

          -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/celltypeTargets.html b/docs/reference/celltypeTargets.html deleted file mode 100644 index 2b41916..0000000 --- a/docs/reference/celltypeTargets.html +++ /dev/null @@ -1,90 +0,0 @@ - -Cell-type deconvolution matrix — celltypeTargets • CLAMP - Skip to contents - - -
          -
          -
          - -

          Cell-type deconvolution matrix

          - Source: R/celltypeTargets.R -
          celltypeTargets.Rd
          -
          - -
          -

          A numeric matrix of estimated cell-type proportions for whole-blood samples. -Rows correspond to sample IDs and columns to major immune cell types. This dataset -can be used for validation or illustrative purposes in CLAMP analyses.

          -
          - -
          -

          Usage

          - 
          data(celltypeTargets)
          -
          - -
          -

          Format

          -

          A numeric matrix with samples as rows and cell types as columns. -Row names are sample identifiers.

          -
          -
          -

          Value

          -

          A numeric matrix of cell-type proportions.

          -
          - -
          -

          Examples

          - 
          data(celltypeTargets)
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/cleanFBM.html b/docs/reference/cleanFBM.html deleted file mode 100644 index cf3a8ec..0000000 --- a/docs/reference/cleanFBM.html +++ /dev/null @@ -1,120 +0,0 @@ - -Clean a Filebacked Big Matrix (FBM) by log-transforming and handling NAs — cleanFBM • CLAMP - Skip to contents - - -
          -
          -
          - -

          Clean a Filebacked Big Matrix (FBM) by log-transforming and handling NAs

          - Source: R/utils.R -
          cleanFBM.Rd
          -
          - -
          -

          This function inspects an FBM to determine if log-transformation is needed (based on value range) -and whether NA values are present. If the maximum value is >= 100, it applies a log2(x + 1) -transformation in-place. If any NA values are detected, they are replaced with 0.

          -
          - -
          -

          Usage

          - 
          cleanFBM(fbm, ncores = 1)
          -
          - -
          -

          Arguments

          - - -
          fbm
          -

          A bigmemory::FBM or bigstatsr::FBM object.

          - - -
          ncores
          -

          Integer; number of cores to use for parallel operations (default 1).

          - -
          -
          -

          Value

          -

          A list with:

          max_value
          -

          The maximum value encountered in the FBM (after log transformation if applied).

          - -
          had_na
          -

          Logical indicating whether any NA values were found and filled.

          - - -
          -
          -

          Details

          -

          Modifies the FBM in place. Uses bigstatsr::big_apply() to process in parallel-safe chunks.

          -
          - -
          -

          Examples

          - 
          # \donttest{
-library(bigstatsr)
-fbm <- FBM(3, 4, init = matrix(c(0, 1, 2, NA, 100, 200, 300, 400, 5, 6, 7, 8), nrow = 3))
-cleanFBM(fbm, ncores = 1)
-#> Applying log2 transformation
-#> Filling NAs with 0
-#> $max_value
-#> [1] 400
-#> 
-#> $had_na
-#> [1] TRUE
-#> 
-# }
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/commonRows.html b/docs/reference/commonRows.html deleted file mode 100644 index e1c635a..0000000 --- a/docs/reference/commonRows.html +++ /dev/null @@ -1,86 +0,0 @@ - -Find common row names between two matrices or data frames — commonRows • CLAMP - Skip to contents - - -
          -
          -
          - -

          Find common row names between two matrices or data frames

          - Source: R/utils.R -
          commonRows.Rd
          -
          - -
          -

          Returns the intersection of row names shared by two input objects.

          -
          - -
          -

          Usage

          - 
          commonRows(data1, data2)
          -
          - -
          -

          Arguments

          - - -
          data1
          -

          A matrix, data frame, or similar object with row names.

          - - -
          data2
          -

          A matrix, data frame, or similar object with row names.

          - -
          -
          -

          Value

          -

          A character vector of row names common to both inputs.

          -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/compareBs.html b/docs/reference/compareBs.html deleted file mode 100644 index 39010a9..0000000 --- a/docs/reference/compareBs.html +++ /dev/null @@ -1,153 +0,0 @@ - -Compare two sets of factor loadings or embeddings — compareBs • CLAMP - Skip to contents - - -
          -
          -
          - -

          Compare two sets of factor loadings or embeddings

          - Source: R/plots.R -
          compareBs.Rd
          -
          - -
          -

          Compares correspondence between two result matrices (e.g., factor loadings) -across multiple targets using correlation, AUC, or t-statistics. -Produces a paired comparison plot and summary statistics.

          -
          - -
          -

          Usage

          - 
          compareBs(
-  res1,
-  res2,
-  target,
-  method = "p",
-  xlab = "1",
-  ylab = "2",
-  stat.method = "t",
-  oneToOne = TRUE
-)
          -
          - -
          -

          Arguments

          - - -
          res1,
          -

          res2 Result objects or matrices containing factor loadings. -If a list, must contain element B; if of class "rsvd", t(res$v) is used.

          - - -
          res2
          -

          Second result object or matrix to compare against.

          - - -
          target
          -

          Numeric matrix of target variables (samples × targets).

          - - -
          method
          -

          Character, one of "p", "s", "a", or "t", indicating -Pearson, Spearman, AUC, or t-statistic comparison.

          - - -
          xlab,
          -

          ylab Labels for x and y axes in the plot.

          - - -
          ylab
          -

          Label for y-axis (used in plot).

          - - -
          stat.method
          -

          Statistical test to compare correlations ("t" or "wilcox").

          - - -
          oneToOne
          -

          Logical, whether to apply one-to-one masking of associations.

          - -
          -
          -

          Value

          -

          A list with:

          plot
          -

          A ggplot object comparing maximal correlations across targets.

          - -
          df
          -

          A data.frame with per-target metrics and (if available) top genes.

          - - -
          - -
          -

          Examples

          - 
          set.seed(123)
-# Simulated example with 50 genes × 20 samples
-Y <- matrix(rnorm(50 * 20), nrow = 50, ncol = 20)
-
-# Run two CLAMP-like decompositions (here using simple SVD)
-svd1 <- rsvd::rsvd(Y, k = 5)
-svd2 <- rsvd::rsvd(Y + matrix(rnorm(50 * 20, 0, 0.1), 50, 20), k = 5)
-
-# Define a target variable (e.g., binary or continuous trait)
-target <- matrix(rnorm(20 * 3), ncol = 3)
-colnames(target) <- c("Trait1", "Trait2", "Trait3")
-
-# Compare the two sets of embeddings
-res <- compareBs(svd1, svd2, target, method = "p", xlab = "SVD1", ylab = "SVD2")
-#> [1]  5 20
-#> [1]  5 20
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/computeRowStatsFBM.html b/docs/reference/computeRowStatsFBM.html deleted file mode 100644 index 1063ec8..0000000 --- a/docs/reference/computeRowStatsFBM.html +++ /dev/null @@ -1,95 +0,0 @@ - -Compute row-wise sum and sum of squares for a Filebacked Big Matrix — computeRowStatsFBM • CLAMP - Skip to contents - - -
          -
          -
          - -

          Compute row-wise sum and sum of squares for a Filebacked Big Matrix

          - Source: R/utils.R -
          computeRowStatsFBM.Rd
          -
          - -
          -

          Efficiently computes row sums and row sum-of-squares for a bigstatsr::FBM using -column-wise chunking, suitable for large datasets that cannot be loaded fully into memory.

          -
          - -
          -

          Usage

          - 
          computeRowStatsFBM(fbm, ncores = 1)
          -
          - -
          -

          Arguments

          - - -
          fbm
          -

          A bigstatsr::FBM object.

          - - -
          ncores
          -

          Integer; number of cores to use for parallel operations (default 1).

          - -
          -
          -

          Value

          -

          A list with two numeric vectors:

          row_sums
          -

          Sum of each row.

          - -
          row_sums_sq
          -

          Sum of squares of each row.

          - - -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/compute_svd.html b/docs/reference/compute_svd.html deleted file mode 100644 index ccf8723..0000000 --- a/docs/reference/compute_svd.html +++ /dev/null @@ -1,107 +0,0 @@ - -Compute a truncated SVD for a CLAMP input matrix — compute_svd • CLAMP - Skip to contents - - -
          -
          -
          - -

          Compute a truncated SVD for a CLAMP input matrix

          - Source: R/utils.R -
          compute_svd.Rd
          -
          - -
          -

          Dispatches to the appropriate SVD backend based on the class of Y: -bigstatsr::big_SVD for FBM objects, irlba::irlba for sparse -dgCMatrix objects, and rsvd::rsvd otherwise. Used by the CLAMP -solvers so that the SVD step is handled in one place.

          -
          - -
          -

          Usage

          - 
          compute_svd(Y, k = NULL)
          -
          - -
          -

          Arguments

          - - -
          Y
          -

          A matrix-like object (dense matrix, dgCMatrix, or FBM).

          - - -
          k
          -

          Integer number of components to compute. If NULL (the -default), select_svd_k(Y) is used.

          - -
          -
          -

          Value

          -

          A list with d, u, v components (structure depends on the -backend but these three fields are always present).

          -
          - -
          -

          Examples

          - 
          set.seed(1)
-Y <- matrix(rnorm(100), nrow = 20, ncol = 5)
-res <- compute_svd(Y, k = 3)
-length(res$d)
-#> [1] 3
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/cpmCLAMP.html b/docs/reference/cpmCLAMP.html deleted file mode 100644 index b99c657..0000000 --- a/docs/reference/cpmCLAMP.html +++ /dev/null @@ -1,92 +0,0 @@ - -Compute counts-per-million (CPM) for CLAMP pipelines — cpmCLAMP • CLAMP - Skip to contents - - -
          -
          -
          - -

          Compute counts-per-million (CPM) for CLAMP pipelines

          - Source: R/utils.R -
          cpmCLAMP.Rd
          -
          - -
          -

          Compute counts-per-million (CPM) for CLAMP pipelines

          -
          - -
          -

          Usage

          - 
          cpmCLAMP(counts)
          -
          - -
          -

          Arguments

          - - -
          counts
          -

          A numeric matrix or data.frame of raw counts (genes x samples).

          - -
          -
          -

          Value

          -

          A numeric matrix of CPM values (same dimensions), ready for CLAMP input.

          -
          - -
          -

          Examples

          - 
          mat <- matrix(seq_len(12), nrow = 3)
-cpmCLAMP(mat)
-#>          [,1]     [,2]     [,3]     [,4]
-#> [1,] 166666.7 266666.7 291666.7 303030.3
-#> [2,] 333333.3 333333.3 333333.3 333333.3
-#> [3,] 500000.0 400000.0 375000.0 363636.4
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/cpmCLAMPFBM.html b/docs/reference/cpmCLAMPFBM.html deleted file mode 100644 index 0a6c646..0000000 --- a/docs/reference/cpmCLAMPFBM.html +++ /dev/null @@ -1,101 +0,0 @@ - -Compute CPM on a file-backed matrix for CLAMP (in-place) — cpmCLAMPFBM • CLAMP - Skip to contents - - -
          -
          -
          - -

          Compute CPM on a file-backed matrix for CLAMP (in-place)

          - Source: R/utils.R -
          cpmCLAMPFBM.Rd
          -
          - -
          -

          Compute CPM on a file-backed matrix for CLAMP (in-place)

          -
          - -
          -

          Usage

          - 
          cpmCLAMPFBM(fbm_counts, block_size = 1000, ncores = 1)
          -
          - -
          -

          Arguments

          - - -
          fbm_counts
          -

          A bigstatsr::FBM of raw counts (genes x samples).

          - - -
          block_size
          -

          Integer; columns per block (default 1000).

          - - -
          ncores
          -

          Integer; number of cores to use for parallel operations (default 1).

          - -
          -
          -

          Value

          -

          Invisibly returns the modified FBM (now holding CPM values).

          -
          - -
          -

          Examples

          - 
          library(bigstatsr)
-mat <- matrix(c(10, 20, 30, 40, 50, 60),
-    nrow = 2,
-    dimnames = list(c('gene1', 'gene2'), paste0('sample', seq_len(3)))
-)
-fbm <- FBM(nrow(mat), ncol(mat), init = mat)
-cpmCLAMPFBM(fbm, block_size = 1)
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/cpmPLIER2.html b/docs/reference/cpmPLIER2.html deleted file mode 100644 index 0873a27..0000000 --- a/docs/reference/cpmPLIER2.html +++ /dev/null @@ -1,88 +0,0 @@ - -Compute counts-per-million (CPM) for PLIER2 pipelines — cpmPLIER2 • PLIER2 - Skip to contents - - -
          -
          -
          - -

          Compute counts-per-million (CPM) for PLIER2 pipelines

          - Source: R/utils.R -
          cpmPLIER2.Rd
          -
          - -
          -

          Compute counts-per-million (CPM) for PLIER2 pipelines

          -
          - -
          -

          Usage

          - 
          cpmPLIER2(counts)
          -
          - -
          -

          Arguments

          - - -
          counts
          -

          A numeric matrix or data.frame of raw counts (genes x samples).

          - -
          -
          -

          Value

          -

          A numeric matrix of CPM values (same dimensions), ready for PLIER2 input.

          -
          - -
          -

          Examples

          - 
          mat <- matrix(1:12, nrow = 3)
-cpmPLIER2(mat)
-#>          [,1]     [,2]     [,3]     [,4]
-#> [1,] 166666.7 266666.7 291666.7 303030.3
-#> [2,] 333333.3 333333.3 333333.3 333333.3
-#> [3,] 500000.0 400000.0 375000.0 363636.4
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.1.3.

          -
          - -
          - - - - - - - diff --git a/docs/reference/cpmPLIER2FBM.html b/docs/reference/cpmPLIER2FBM.html deleted file mode 100644 index b8709ee..0000000 --- a/docs/reference/cpmPLIER2FBM.html +++ /dev/null @@ -1,101 +0,0 @@ - -Compute CPM on a file-backed matrix for PLIER2 (in-place) — cpmPLIER2FBM • PLIER2 - Skip to contents - - -
          -
          -
          - -

          Compute CPM on a file-backed matrix for PLIER2 (in-place)

          - Source: R/utils.R -
          cpmPLIER2FBM.Rd
          -
          - -
          -

          Compute CPM on a file-backed matrix for PLIER2 (in-place)

          -
          - -
          -

          Usage

          - 
          cpmPLIER2FBM(fbm_counts, block_size = 1000)
          -
          - -
          -

          Arguments

          - - -
          fbm_counts
          -

          A bigstatsr::FBM of raw counts (genes x samples).

          - - -
          block_size
          -

          Numeric; rows per block (default 1000).

          - -
          -
          -

          Value

          -

          Invisibly returns the modified FBM (now holding CPM values).

          -
          - -
          -

          Examples

          - 
          library(bigstatsr)
-
-# small 2 genes x 3 samples count matrix
-mat <- matrix(
-  c(10, 20, 30,
-    40, 50, 60),
-  nrow = 2, byrow = FALSE,
-  dimnames = list(c("gene1", "gene2"), paste0("sample", 1:3))
-)
-
-# create an FBM initialized with counts
-fbm <- FBM(nrow(mat), ncol(mat), init = mat)
-
-# convert counts to CPM in-place
-cpmPLIER2FBM(fbm, block_size = 1)
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.1.3.

          -
          - -
          - - - - - - - diff --git a/docs/reference/crossVal.html b/docs/reference/crossVal.html deleted file mode 100644 index 3d01e86..0000000 --- a/docs/reference/crossVal.html +++ /dev/null @@ -1,105 +0,0 @@ - -Cross-validation AUC for CLAMP latent variables and pathways — crossVal • CLAMP - Skip to contents - - -
          -
          -
          - -

          Cross-validation AUC for CLAMP latent variables and pathways

          - Source: R/solvers.R -
          crossVal.Rd
          -
          - -
          -

          Evaluates how well each latent variable in a CLAMP model captures held-out pathway annotations, -using cross-validation over the prior matrix. For each latent variable and associated pathway, -held-out genes are selected and the AUC is computed using their scores in clampRes$Z.

          -
          - -
          -

          Usage

          - 
          crossVal(clampRes, priorMat, priorMatcv)
          -
          - -
          -

          Arguments

          - - -
          clampRes
          -

          A list containing U (loadings) and Z (scores) from a CLAMP model.

          - - -
          priorMat
          -

          A binary matrix (genes x pathways) indicating original pathway annotations.

          - - -
          priorMatcv
          -

          A version of priorMat used to mask held-out annotations for cross-validation.

          - -
          -
          -

          Value

          -

          A list with:

          Uauc
          -

          Matrix of AUC values (pathways x LVs)

          - -
          Upval
          -

          Matrix of -log10(p) values (pathways x LVs)

          - -
          summary
          -

          Data frame with pathway, LV index, AUC, p-value, and FDR

          - - -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/cross_ZY.html b/docs/reference/cross_ZY.html deleted file mode 100644 index be93430..0000000 --- a/docs/reference/cross_ZY.html +++ /dev/null @@ -1,106 +0,0 @@ - -Cross-product Z^T Y with FBM or dense matrices — cross_ZY • CLAMP - Skip to contents - - -
          -
          -
          - -

          Cross-product Z^T Y with FBM or dense matrices

          - Source: R/solvers.R -
          cross_ZY.Rd
          -
          - -
          -

          Computes \(Z^T Y\), handling FBM objects from bigstatsr -as well as base R matrices.

          -
          - -
          -

          Usage

          - 
          cross_ZY(Y, Z)
          -
          - -
          -

          Arguments

          - - -
          Y
          -

          Gene expression matrix (genes x samples), dense or FBM.

          - - -
          Z
          -

          Latent variable matrix (genes x k).

          - -
          -
          -

          Value

          -

          A numeric matrix giving Z^T Y.

          -
          - -
          -

          Examples

          - 
          set.seed(123)
-
-genes <- 40
-samples <- 10
-k <- 4
-
-Y <- matrix(rnorm(genes * samples), nrow = genes)
-Z <- matrix(rnorm(genes * k), nrow = genes)
-
-# Compute Z^T Y
-res1 <- cross_ZY(Y, Z)
-dim(res1)   # k × samples
-#> [1]  4 10
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/dataWholeBlood.html b/docs/reference/dataWholeBlood.html deleted file mode 100644 index 4fe5762..0000000 --- a/docs/reference/dataWholeBlood.html +++ /dev/null @@ -1,87 +0,0 @@ - -Whole-blood reference expression matrix — dataWholeBlood • CLAMP - Skip to contents - - -
          -
          -
          - -

          Whole-blood reference expression matrix

          - Source: R/dataWholeBlood.R -
          dataWholeBlood.Rd
          -
          - -
          -

          A numeric matrix of whole-blood gene expression -where rows correspond to genes and columns to samples.

          -
          - -
          -

          Usage

          - 
          data(dataWholeBlood)
          -
          - -
          -

          Format

          -

          A numeric matrix with G genes (rows) and N samples (columns). -Row names are gene symbols, and column names are sample IDs.

          -
          -
          -

          Value

          -

          A numeric matrix of expression values.

          -
          - -
          -

          Examples

          - 
          data(dataWholeBlood)
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
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zWF#J4z7mpjP8DUdAH)~{tojN8qSn~^V&v4h=;i2p?#go53nBzY6pH7OTL5VP3*sBS vbIZ2dHtSVRW`Wxsl(5T-bKgL|CpdAcpcYu?T{ZBzr5B(tvSOv8IzRpg9Q*%k diff --git a/docs/reference/figures/plier2.svg b/docs/reference/figures/plier2.svg deleted file mode 100644 index 1f7e828..0000000 --- a/docs/reference/figures/plier2.svg +++ /dev/null @@ -1,277 +0,0 @@ - - - -image/svg+xml -PLIER2 diff --git a/docs/reference/filterFBM.html b/docs/reference/filterFBM.html deleted file mode 100644 index 06c07ec..0000000 --- a/docs/reference/filterFBM.html +++ /dev/null @@ -1,134 +0,0 @@ - -Filter rows of a Filebacked Big Matrix based on mean and variance — filterFBM • CLAMP - Skip to contents - - -

          -
          -
          - -

          Filter rows of a Filebacked Big Matrix based on mean and variance

          - Source: R/utils.R -
          filterFBM.Rd
          -
          - -
          -

          Filters an FBM based on row-level mean and variance thresholds, returning a new FBM -with only the selected rows.

          -
          - -
          -

          Usage

          - 
          filterFBM(
-  fbm,
-  rowStats,
-  keep_samples_idx = NULL,
-  mean_cutoff = NULL,
-  var_cutoff = NULL,
-  backingfile = "filtered_fbm"
-)
          -
          - -
          -

          Arguments

          - - -
          fbm
          -

          A bigstatsr::FBM object.

          - - -
          rowStats
          -

          A list with numeric vectors row_means and row_variances.

          - - -
          keep_samples_idx
          -

          Optional integer vector of column indices to retain. -Default is filtered_fbm.

          - - -
          mean_cutoff
          -

          Optional minimum mean threshold; rows with means below this are removed.

          - - -
          var_cutoff
          -

          Optional minimum variance threshold; rows with variances below this are removed.

          - - -
          backingfile
          -

          A character string specifying the filename (without extension) for the new FBM.

          - -
          -
          -

          Value

          -

          A list with:

          fbm_filtered
          -

          A new FBM object containing only filtered rows.

          - -
          kept_rows
          -

          Indices of rows retained in the filtering step.

          - - -
          -
          -

          Details

          -

          This function creates a new FBM and copies over only the rows that pass the filtering criteria. -The original FBM is unchanged.

          -
          - -
          -

          Examples

          - 
          # \donttest{
-library(bigstatsr)
-fbm <- FBM(5, 3, init = matrix(rnorm(15), nrow = 5))
-rs <- list(row_means = rowMeans(fbm[]), row_variances = apply(fbm[], 1, var))
-out <- filterFBM(fbm, rs, mean_cutoff = -0.2, var_cutoff = 0.5, backingfile = tempfile())
-# }
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/findSplineMax.html b/docs/reference/findSplineMax.html deleted file mode 100644 index 2b9acab..0000000 --- a/docs/reference/findSplineMax.html +++ /dev/null @@ -1,114 +0,0 @@ - -Find the location of the maximum of a smoothing spline — findSplineMax • CLAMP - Skip to contents - - -
          -
          -
          - -

          Find the location of the maximum of a smoothing spline

          - Source: R/utils.R -
          findSplineMax.Rd
          -
          - -
          -

          Find the location of the maximum of a smoothing spline

          -
          - -
          -

          Usage

          - 
          findSplineMax(x, y, n = 1000, spar = NULL)
          -
          - -
          -

          Arguments

          - - -
          x
          -

          Numeric vector of x values.

          - - -
          y
          -

          Numeric vector of y values (same length as x).

          - - -
          n
          -

          Integer, number of grid points to evaluate (default 1000).

          - - -
          spar
          -

          Smoothing parameter passed to stats::smooth.spline.

          - -
          -
          -

          Value

          -

          A named list with components:

          x
          -

          The x coordinate at which the spline reaches its maximum.

          - -
          y
          -

          The corresponding maximum fitted y value.

          - - -
          - -
          -

          Examples

          - 
          x <- seq_len(10)
-y <- sin(x) + rnorm(10, 0, 0.1)
-findSplineMax(x, y)
-#> $x
-#> [1] 7.981982
-#> 
-#> $y
-#> [1] 0.9668493
-#> 
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/getAUCstats.html b/docs/reference/getAUCstats.html deleted file mode 100644 index e57d93b..0000000 --- a/docs/reference/getAUCstats.html +++ /dev/null @@ -1,85 +0,0 @@ - -Count number of latent variables exceeding AUC thresholds — getAUCstats • CLAMP - Skip to contents - - -
          -
          -
          - -

          Count number of latent variables exceeding AUC thresholds

          - Source: R/utils.R -
          getAUCstats.Rd
          -
          - -
          -

          Given a summary data frame from cross-validation, reports the number of latent variables -with maximum AUC exceeding 0.7, 0.8, and 0.9.

          -
          - -
          -

          Usage

          - 
          getAUCstats(summary)
          -
          - -
          -

          Arguments

          - - -
          summary
          -

          A data frame with LV index and AUC columns.

          - -
          -
          -

          Value

          -

          A named numeric vector with counts for thresholds 0.7, 0.8, and 0.9.

          -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/getChat.html b/docs/reference/getChat.html deleted file mode 100644 index 91a8679..0000000 --- a/docs/reference/getChat.html +++ /dev/null @@ -1,113 +0,0 @@ - -Compute Chat matrix from prior annotation — getChat • CLAMP - Skip to contents - - -
          -
          -
          - -

          Compute Chat matrix from prior annotation

          - Source: R/solvers.R -
          getChat.Rd
          -
          - -
          -

          Computes the transformation matrix Chat used to map from observed data to latent space, -based on a pseudo-inverse of the prior annotation matrix. Optionally standardizes the columns -of priorMat before computing.

          -
          - -
          -

          Usage

          - 
          getChat(priorMat, scale = TRUE)
          -
          - -
          -

          Arguments

          - - -
          priorMat
          -

          A numeric or sparse matrix (features x pathways) containing prior annotations.

          - - -
          scale
          -

          Logical; if TRUE (default), standardizes the columns of priorMat -before computing Chat.

          - -
          -
          -

          Value

          -

          A numeric matrix Chat of dimensions (pathways x features).

          -
          - -
          -

          Examples

          - 
          # simple toy prior: 3 features x 2 pathways
-priorMat <- matrix(
-    c(
-        1, 0, 1,
-        0, 1, 0
-    ),
-    nrow = 3, ncol = 2,
-    dimnames = list(
-        paste0("gene", seq_len(3)),
-        paste0("path", seq_len(2))
-    )
-)
-# compute Chat (2 pathways x 3 features)
-Chat <- getChat(priorMat)
-#> Inverting...
-#> done
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/getGMT.html b/docs/reference/getGMT.html deleted file mode 100644 index 4cc6e63..0000000 --- a/docs/reference/getGMT.html +++ /dev/null @@ -1,418 +0,0 @@ - -Download and read a GMT file from a URL — getGMT • CLAMP - Skip to contents - - -
          -
          -
          - -

          Download and read a GMT file from a URL

          - Source: R/utils.R -
          getGMT.Rd
          -
          - -
          -

          Downloads a Gene Matrix Transposed (GMT) file from a specified URL, reads it into R as a list, -and removes the temporary file afterward.

          -
          - -
          -

          Usage

          - 
          getGMT(url, name = NULL, cache_dir = NULL, redownload = FALSE)
          -
          - -
          -

          Arguments

          - - -
          url
          -

          A character string specifying the URL to a GMT file.

          - - -
          name
          -

          Optional name for the GMT file (defaults to the portion after the last '=' in the URL).

          - - -
          cache_dir
          -

          Optional directory in which to cache/download the GMT file.

          - - -
          redownload
          -

          Logical; if TRUE, forces re-download even if cached.

          - -
          -
          -

          Value

          -

          A named list where each element is a character vector of gene names for a given gene set.

          -
          - -
          -

          Examples

          - 
          url <- 'https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=KEGG_2019_Human'
-gmt_list <- getGMT(url)
-#> Auto-detected name: KEGG_2019_Human
-#> Using cached file for KEGG_2019_Human
-# list available gene sets
-names(gmt_list)
-#>   [1] "ABC transporters"                                          
-#>   [2] "AGE-RAGE signaling pathway in diabetic complications"      
-#>   [3] "AMPK signaling pathway"                                    
-#>   [4] "Acute myeloid leukemia"                                    
-#>   [5] "Adherens junction"                                         
-#>   [6] "Adipocytokine signaling pathway"                           
-#>   [7] "Adrenergic signaling in cardiomyocytes"                    
-#>   [8] "African trypanosomiasis"                                   
-#>   [9] "Alanine, aspartate and glutamate metabolism"               
-#>  [10] "Alcoholism"                                                
-#>  [11] "Aldosterone synthesis and secretion"                       
-#>  [12] "Aldosterone-regulated sodium reabsorption"                 
-#>  [13] "Allograft rejection"                                       
-#>  [14] "Alzheimer disease"                                         
-#>  [15] "Amino sugar and nucleotide sugar metabolism"               
-#>  [16] "Aminoacyl-tRNA biosynthesis"                               
-#>  [17] "Amoebiasis"                                                
-#>  [18] "Amphetamine addiction"                                     
-#>  [19] "Amyotrophic lateral sclerosis (ALS)"                       
-#>  [20] "Antigen processing and presentation"                       
-#>  [21] "Apelin signaling pathway"                                  
-#>  [22] "Apoptosis"                                                 
-#>  [23] "Arachidonic acid metabolism"                               
-#>  [24] "Arginine and proline metabolism"                           
-#>  [25] "Arginine biosynthesis"                                     
-#>  [26] "Arrhythmogenic right ventricular cardiomyopathy (ARVC)"    
-#>  [27] "Ascorbate and aldarate metabolism"                         
-#>  [28] "Asthma"                                                    
-#>  [29] "Autoimmune thyroid disease"                                
-#>  [30] "Autophagy"                                                 
-#>  [31] "Axon guidance"                                             
-#>  [32] "B cell receptor signaling pathway"                         
-#>  [33] "Bacterial invasion of epithelial cells"                    
-#>  [34] "Basal cell carcinoma"                                      
-#>  [35] "Basal transcription factors"                               
-#>  [36] "Base excision repair"                                      
-#>  [37] "Bile secretion"                                            
-#>  [38] "Biosynthesis of unsaturated fatty acids"                   
-#>  [39] "Bladder cancer"                                            
-#>  [40] "Breast cancer"                                             
-#>  [41] "Butanoate metabolism"                                      
-#>  [42] "C-type lectin receptor signaling pathway"                  
-#>  [43] "Caffeine metabolism"                                       
-#>  [44] "Calcium signaling pathway"                                 
-#>  [45] "Carbohydrate digestion and absorption"                     
-#>  [46] "Cardiac muscle contraction"                                
-#>  [47] "Cell adhesion molecules (CAMs)"                            
-#>  [48] "Cell cycle"                                                
-#>  [49] "Cellular senescence"                                       
-#>  [50] "Central carbon metabolism in cancer"                       
-#>  [51] "Chagas disease (American trypanosomiasis)"                 
-#>  [52] "Chemical carcinogenesis"                                   
-#>  [53] "Chemokine signaling pathway"                               
-#>  [54] "Cholesterol metabolism"                                    
-#>  [55] "Choline metabolism in cancer"                              
-#>  [56] "Cholinergic synapse"                                       
-#>  [57] "Chronic myeloid leukemia"                                  
-#>  [58] "Circadian entrainment"                                     
-#>  [59] "Circadian rhythm"                                          
-#>  [60] "Citrate cycle (TCA cycle)"                                 
-#>  [61] "Cocaine addiction"                                         
-#>  [62] "Collecting duct acid secretion"                            
-#>  [63] "Colorectal cancer"                                         
-#>  [64] "Complement and coagulation cascades"                       
-#>  [65] "Cortisol synthesis and secretion"                          
-#>  [66] "Cushing syndrome"                                          
-#>  [67] "Cysteine and methionine metabolism"                        
-#>  [68] "Cytokine-cytokine receptor interaction"                    
-#>  [69] "Cytosolic DNA-sensing pathway"                             
-#>  [70] "D-Glutamine and D-glutamate metabolism"                    
-#>  [71] "DNA replication"                                           
-#>  [72] "Dilated cardiomyopathy (DCM)"                              
-#>  [73] "Dopaminergic synapse"                                      
-#>  [74] "Drug metabolism"                                           
-#>  [75] "ECM-receptor interaction"                                  
-#>  [76] "Endocrine and other factor-regulated calcium reabsorption" 
-#>  [77] "Endocytosis"                                               
-#>  [78] "Endometrial cancer"                                        
-#>  [79] "Epithelial cell signaling in Helicobacter pylori infection"
-#>  [80] "Epstein-Barr virus infection"                              
-#>  [81] "ErbB signaling pathway"                                    
-#>  [82] "Estrogen signaling pathway"                                
-#>  [83] "Ether lipid metabolism"                                    
-#>  [84] "Fanconi anemia pathway"                                    
-#>  [85] "Fat digestion and absorption"                              
-#>  [86] "Fatty acid biosynthesis"                                   
-#>  [87] "Fatty acid degradation"                                    
-#>  [88] "Fatty acid elongation"                                     
-#>  [89] "Fc epsilon RI signaling pathway"                           
-#>  [90] "Fc gamma R-mediated phagocytosis"                          
-#>  [91] "Ferroptosis"                                               
-#>  [92] "Fluid shear stress and atherosclerosis"                    
-#>  [93] "Focal adhesion"                                            
-#>  [94] "Folate biosynthesis"                                       
-#>  [95] "FoxO signaling pathway"                                    
-#>  [96] "Fructose and mannose metabolism"                           
-#>  [97] "GABAergic synapse"                                         
-#>  [98] "Galactose metabolism"                                      
-#>  [99] "Gap junction"                                              
-#> [100] "Gastric acid secretion"                                    
-#> [101] "Gastric cancer"                                            
-#> [102] "Glioma"                                                    
-#> [103] "Glucagon signaling pathway"                                
-#> [104] "Glutamatergic synapse"                                     
-#> [105] "Glutathione metabolism"                                    
-#> [106] "Glycerolipid metabolism"                                   
-#> [107] "Glycerophospholipid metabolism"                            
-#> [108] "Glycine, serine and threonine metabolism"                  
-#> [109] "Glycolysis / Gluconeogenesis"                              
-#> [110] "Glycosaminoglycan biosynthesis"                            
-#> [111] "Glycosaminoglycan degradation"                             
-#> [112] "Glycosphingolipid biosynthesis"                            
-#> [113] "Glycosylphosphatidylinositol (GPI)-anchor biosynthesis"    
-#> [114] "Glyoxylate and dicarboxylate metabolism"                   
-#> [115] "GnRH signaling pathway"                                    
-#> [116] "Graft-versus-host disease"                                 
-#> [117] "HIF-1 signaling pathway"                                   
-#> [118] "Hedgehog signaling pathway"                                
-#> [119] "Hematopoietic cell lineage"                                
-#> [120] "Hepatitis B"                                               
-#> [121] "Hepatitis C"                                               
-#> [122] "Hepatocellular carcinoma"                                  
-#> [123] "Herpes simplex virus 1 infection"                          
-#> [124] "Hippo signaling pathway"                                   
-#> [125] "Histidine metabolism"                                      
-#> [126] "Homologous recombination"                                  
-#> [127] "Human T-cell leukemia virus 1 infection"                   
-#> [128] "Human cytomegalovirus infection"                           
-#> [129] "Human immunodeficiency virus 1 infection"                  
-#> [130] "Human papillomavirus infection"                            
-#> [131] "Huntington disease"                                        
-#> [132] "Hypertrophic cardiomyopathy (HCM)"                         
-#> [133] "IL-17 signaling pathway"                                   
-#> [134] "Inflammatory bowel disease (IBD)"                          
-#> [135] "Inflammatory mediator regulation of TRP channels"          
-#> [136] "Influenza A"                                               
-#> [137] "Inositol phosphate metabolism"                             
-#> [138] "Insulin resistance"                                        
-#> [139] "Insulin secretion"                                         
-#> [140] "Insulin signaling pathway"                                 
-#> [141] "Intestinal immune network for IgA production"              
-#> [142] "JAK-STAT signaling pathway"                                
-#> [143] "Kaposi sarcoma-associated herpesvirus infection"           
-#> [144] "Legionellosis"                                             
-#> [145] "Leishmaniasis"                                             
-#> [146] "Leukocyte transendothelial migration"                      
-#> [147] "Linoleic acid metabolism"                                  
-#> [148] "Long-term depression"                                      
-#> [149] "Long-term potentiation"                                    
-#> [150] "Longevity regulating pathway"                              
-#> [151] "Lysine degradation"                                        
-#> [152] "Lysosome"                                                  
-#> [153] "MAPK signaling pathway"                                    
-#> [154] "Malaria"                                                   
-#> [155] "Mannose type O-glycan biosynthesis"                        
-#> [156] "Maturity onset diabetes of the young"                      
-#> [157] "Measles"                                                   
-#> [158] "Melanogenesis"                                             
-#> [159] "Melanoma"                                                  
-#> [160] "Metabolism of xenobiotics by cytochrome P450"              
-#> [161] "MicroRNAs in cancer"                                       
-#> [162] "Mineral absorption"                                        
-#> [163] "Mismatch repair"                                           
-#> [164] "Mitophagy"                                                 
-#> [165] "Morphine addiction"                                        
-#> [166] "Mucin type O-glycan biosynthesis"                          
-#> [167] "N-Glycan biosynthesis"                                     
-#> [168] "NF-kappa B signaling pathway"                              
-#> [169] "NOD-like receptor signaling pathway"                       
-#> [170] "Natural killer cell mediated cytotoxicity"                 
-#> [171] "Necroptosis"                                               
-#> [172] "Neomycin, kanamycin and gentamicin biosynthesis"           
-#> [173] "Neuroactive ligand-receptor interaction"                   
-#> [174] "Neurotrophin signaling pathway"                            
-#> [175] "Nicotinate and nicotinamide metabolism"                    
-#> [176] "Nicotine addiction"                                        
-#> [177] "Nitrogen metabolism"                                       
-#> [178] "Non-alcoholic fatty liver disease (NAFLD)"                 
-#> [179] "Non-homologous end-joining"                                
-#> [180] "Non-small cell lung cancer"                                
-#> [181] "Notch signaling pathway"                                   
-#> [182] "Nucleotide excision repair"                                
-#> [183] "Olfactory transduction"                                    
-#> [184] "One carbon pool by folate"                                 
-#> [185] "Oocyte meiosis"                                            
-#> [186] "Osteoclast differentiation"                                
-#> [187] "Other glycan degradation"                                  
-#> [188] "Other types of O-glycan biosynthesis"                      
-#> [189] "Ovarian steroidogenesis"                                   
-#> [190] "Oxidative phosphorylation"                                 
-#> [191] "Oxytocin signaling pathway"                                
-#> [192] "PI3K-Akt signaling pathway"                                
-#> [193] "PPAR signaling pathway"                                    
-#> [194] "Pancreatic cancer"                                         
-#> [195] "Pancreatic secretion"                                      
-#> [196] "Pantothenate and CoA biosynthesis"                         
-#> [197] "Parathyroid hormone synthesis, secretion and action"       
-#> [198] "Parkinson disease"                                         
-#> [199] "Pathogenic Escherichia coli infection"                     
-#> [200] "Pathways in cancer"                                        
-#> [201] "Pentose and glucuronate interconversions"                  
-#> [202] "Pentose phosphate pathway"                                 
-#> [203] "Peroxisome"                                                
-#> [204] "Pertussis"                                                 
-#> [205] "Phagosome"                                                 
-#> [206] "Phenylalanine metabolism"                                  
-#> [207] "Phenylalanine, tyrosine and tryptophan biosynthesis"       
-#> [208] "Phosphatidylinositol signaling system"                     
-#> [209] "Phospholipase D signaling pathway"                         
-#> [210] "Phosphonate and phosphinate metabolism"                    
-#> [211] "Phototransduction"                                         
-#> [212] "Platelet activation"                                       
-#> [213] "Porphyrin and chlorophyll metabolism"                      
-#> [214] "Primary bile acid biosynthesis"                            
-#> [215] "Primary immunodeficiency"                                  
-#> [216] "Prion diseases"                                            
-#> [217] "Progesterone-mediated oocyte maturation"                   
-#> [218] "Prolactin signaling pathway"                               
-#> [219] "Propanoate metabolism"                                     
-#> [220] "Prostate cancer"                                           
-#> [221] "Proteasome"                                                
-#> [222] "Protein digestion and absorption"                          
-#> [223] "Protein export"                                            
-#> [224] "Protein processing in endoplasmic reticulum"               
-#> [225] "Proteoglycans in cancer"                                   
-#> [226] "Proximal tubule bicarbonate reclamation"                   
-#> [227] "Purine metabolism"                                         
-#> [228] "Pyrimidine metabolism"                                     
-#> [229] "Pyruvate metabolism"                                       
-#> [230] "RIG-I-like receptor signaling pathway"                     
-#> [231] "RNA degradation"                                           
-#> [232] "RNA polymerase"                                            
-#> [233] "RNA transport"                                             
-#> [234] "Rap1 signaling pathway"                                    
-#> [235] "Ras signaling pathway"                                     
-#> [236] "Regulation of actin cytoskeleton"                          
-#> [237] "Regulation of lipolysis in adipocytes"                     
-#> [238] "Relaxin signaling pathway"                                 
-#> [239] "Renal cell carcinoma"                                      
-#> [240] "Renin secretion"                                           
-#> [241] "Renin-angiotensin system"                                  
-#> [242] "Retinol metabolism"                                        
-#> [243] "Retrograde endocannabinoid signaling"                      
-#> [244] "Rheumatoid arthritis"                                      
-#> [245] "Riboflavin metabolism"                                     
-#> [246] "Ribosome"                                                  
-#> [247] "Ribosome biogenesis in eukaryotes"                         
-#> [248] "SNARE interactions in vesicular transport"                 
-#> [249] "Salivary secretion"                                        
-#> [250] "Salmonella infection"                                      
-#> [251] "Selenocompound metabolism"                                 
-#> [252] "Serotonergic synapse"                                      
-#> [253] "Shigellosis"                                               
-#> [254] "Signaling pathways regulating pluripotency of stem cells"  
-#> [255] "Small cell lung cancer"                                    
-#> [256] "Sphingolipid metabolism"                                   
-#> [257] "Sphingolipid signaling pathway"                            
-#> [258] "Spliceosome"                                               
-#> [259] "Staphylococcus aureus infection"                           
-#> [260] "Starch and sucrose metabolism"                             
-#> [261] "Steroid biosynthesis"                                      
-#> [262] "Steroid hormone biosynthesis"                              
-#> [263] "Sulfur metabolism"                                         
-#> [264] "Sulfur relay system"                                       
-#> [265] "Synaptic vesicle cycle"                                    
-#> [266] "Synthesis and degradation of ketone bodies"                
-#> [267] "Systemic lupus erythematosus"                              
-#> [268] "T cell receptor signaling pathway"                         
-#> [269] "TGF-beta signaling pathway"                                
-#> [270] "TNF signaling pathway"                                     
-#> [271] "Taste transduction"                                        
-#> [272] "Taurine and hypotaurine metabolism"                        
-#> [273] "Terpenoid backbone biosynthesis"                           
-#> [274] "Th1 and Th2 cell differentiation"                          
-#> [275] "Th17 cell differentiation"                                 
-#> [276] "Thermogenesis"                                             
-#> [277] "Thiamine metabolism"                                       
-#> [278] "Thyroid cancer"                                            
-#> [279] "Thyroid hormone signaling pathway"                         
-#> [280] "Thyroid hormone synthesis"                                 
-#> [281] "Tight junction"                                            
-#> [282] "Toll-like receptor signaling pathway"                      
-#> [283] "Toxoplasmosis"                                             
-#> [284] "Transcriptional misregulation in cancer"                   
-#> [285] "Tryptophan metabolism"                                     
-#> [286] "Tuberculosis"                                              
-#> [287] "Type I diabetes mellitus"                                  
-#> [288] "Type II diabetes mellitus"                                 
-#> [289] "Tyrosine metabolism"                                       
-#> [290] "Ubiquinone and other terpenoid-quinone biosynthesis"       
-#> [291] "Ubiquitin mediated proteolysis"                            
-#> [292] "VEGF signaling pathway"                                    
-#> [293] "Valine, leucine and isoleucine degradation"                
-#> [294] "Vascular smooth muscle contraction"                        
-#> [295] "Vasopressin-regulated water reabsorption"                  
-#> [296] "Vibrio cholerae infection"                                 
-#> [297] "Viral carcinogenesis"                                      
-#> [298] "Viral myocarditis"                                         
-#> [299] "Vitamin B6 metabolism"                                     
-#> [300] "Vitamin digestion and absorption"                          
-#> [301] "Wnt signaling pathway"                                     
-#> [302] "alpha-Linolenic acid metabolism"                           
-#> [303] "beta-Alanine metabolism"                                   
-#> [304] "cAMP signaling pathway"                                    
-#> [305] "cGMP-PKG signaling pathway"                                
-#> [306] "mRNA surveillance pathway"                                 
-#> [307] "mTOR signaling pathway"                                    
-#> [308] "p53 signaling pathway"                                     
-# inspect the first few genes in the first gene set
-head(gmt_list[[1]])
-#> [1] "ABCA1"  "ABCA10" "ABCA12" "ABCA13" "ABCA2"  "ABCA3" 
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/getMatchedPathwayMat.html b/docs/reference/getMatchedPathwayMat.html deleted file mode 100644 index c7b474d..0000000 --- a/docs/reference/getMatchedPathwayMat.html +++ /dev/null @@ -1,118 +0,0 @@ - -Subset and filter pathway matrix to match target genes — getMatchedPathwayMat • CLAMP - Skip to contents - - -
          -
          -
          - -

          Subset and filter pathway matrix to match target genes

          - Source: R/solvers.R -
          getMatchedPathwayMat.Rd
          -
          - -
          -

          Filters a gene-by-pathway annotation matrix to retain only pathways -with sufficient overlap with a given gene set. The result is a sparse matrix -aligned to new.genes, with columns (pathways) retained only if they -have at least min.genes matched genes.

          -
          - -
          -

          Usage

          - 
          getMatchedPathwayMat(pathMat, new.genes, min.genes = 10)
          -
          - -
          -

          Arguments

          - - -
          pathMat
          -

          A sparse binary matrix of genes (rows) x pathways (columns).

          - - -
          new.genes
          -

          Character vector of gene names to match.

          - - -
          min.genes
          -

          Minimum number of overlapping genes required to keep a pathway.

          - -
          -
          -

          Value

          -

          A sparse matrix of dimensions length(new.genes) x filtered pathways.

          -
          - -
          -

          Examples

          - 
          library(Matrix)
-# create a toy gene-by-pathway sparse matrix
-genes <- paste0("g", seq_len(6))
-pathways <- c("Path1", "Path2", "Path3")
-# Path1: g1, g2; Path2: g2, g3, g4; Path3: g5
-pathMat <- sparseMatrix(
-    i = c(1, 2, 2, 3, 4, 5),
-    j = c(1, 1, 2, 2, 2, 3),
-    dims = c(length(genes), length(pathways)),
-    dimnames = list(genes, pathways)
-)
-new.genes <- genes
-filtered <- getMatchedPathwayMat(pathMat, new.genes, min.genes = 2)
-#> There are 6 genes in the intersection between data and prior
-#> Removing 1 pathways
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/getMatchedPathwayMat2.html b/docs/reference/getMatchedPathwayMat2.html deleted file mode 100644 index 83c956c..0000000 --- a/docs/reference/getMatchedPathwayMat2.html +++ /dev/null @@ -1,96 +0,0 @@ - -Subset and filter multiple pathway matrices to match target genes — getMatchedPathwayMat2 • CLAMP - Skip to contents - - -
          -
          -
          - -

          Subset and filter multiple pathway matrices to match target genes

          - Source: R/solvers.R -
          getMatchedPathwayMat2.Rd
          -
          - -
          -

          Filters gene-by-pathway annotation matrices to retain only pathways -with sufficient overlap with a given gene set. The result is a sparse matrix -aligned to new.genes, combining all inputs column-wise.

          -
          - -
          -

          Usage

          - 
          getMatchedPathwayMat2(..., new.genes, min.genes = 10)
          -
          - -
          -

          Arguments

          - - -
          ...
          -

          One or more sparse binary matrices (genes x pathways).

          - - -
          new.genes
          -

          Character vector of gene names to match.

          - - -
          min.genes
          -

          Minimum number of overlapping genes required to keep a pathway.

          - -
          -
          -

          Value

          -

          A sparse matrix with rows = new.genes and columns = filtered pathways from all inputs.

          -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/getMatchedPathwayMatList.html b/docs/reference/getMatchedPathwayMatList.html deleted file mode 100644 index beb2ea5..0000000 --- a/docs/reference/getMatchedPathwayMatList.html +++ /dev/null @@ -1,133 +0,0 @@ - -Subset and filter multiple pathway matrices to match target genes — getMatchedPathwayMatList • CLAMP - Skip to contents - - -
          -
          -
          - -

          Subset and filter multiple pathway matrices to match target genes

          - Source: R/solvers.R -
          getMatchedPathwayMatList.Rd
          -
          - -
          -

          Filters one or more gene-by-pathway annotation matrices to retain only pathways -with sufficient overlap with a given target gene set. Each input matrix is -restricted to new.genes, and pathways with fewer than min.genes -overlapping genes are removed. The resulting matrices are column-bound into a -single sparse matrix aligned to new.genes.

          -
          - -
          -

          Usage

          - 
          getMatchedPathwayMatList(..., new.genes, min.genes = 10)
          -
          - -
          -

          Arguments

          - - -
          ...
          -

          One or more binary matrices (genes × pathways), either base matrix -or sparse Matrix objects. Row names must be gene identifiers.

          - - -
          new.genes
          -

          Character vector of gene names to align all pathway matrices to.

          - - -
          min.genes
          -

          Integer; minimum number of overlapping genes required for a pathway -to be retained. Default is 10.

          - -
          -
          -

          Value

          -

          A sparse binary matrix with rows equal to new.genes and columns equal to -the union of filtered pathways from all input matrices.

          -
          - -
          -

          Examples

          - 
          set.seed(123)
-library(Matrix)
-
-# Simulate two small pathway matrices (genes × pathways)
-genes <- paste0("Gene", 1:100)
-pathways1 <- paste0("Path", 1:5)
-pathways2 <- paste0("Path", 6:10)
-
-mat1 <- matrix(sample(c(0, 1), 100 * 5, replace = TRUE, prob = c(0.9, 0.1)),
-               nrow = 100, ncol = 5,
-               dimnames = list(genes, pathways1))
-mat2 <- matrix(sample(c(0, 1), 100 * 5, replace = TRUE, prob = c(0.9, 0.1)),
-               nrow = 100, ncol = 5,
-               dimnames = list(genes, pathways2))
-
-# Define target genes (subset of total)
-new.genes <- sample(genes, 50)
-
-# Match and filter pathways with at least 5 genes
-matched <- getMatchedPathwayMatList(mat1, mat2, new.genes = new.genes, min.genes = 5)
-#> There are 50 genes in the intersection between data and prior
-#> Removing 4 pathways
-#> There are 50 genes in the intersection between data and prior
-#> Removing 4 pathways
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/getMatchedPathwayMatOld.html b/docs/reference/getMatchedPathwayMatOld.html deleted file mode 100644 index dcb07e1..0000000 --- a/docs/reference/getMatchedPathwayMatOld.html +++ /dev/null @@ -1,99 +0,0 @@ - -Subset and filter pathway matrix to match target genes — getMatchedPathwayMatOld • CLAMP - Skip to contents - - -
          -
          -
          - -

          Subset and filter pathway matrix to match target genes

          - Source: R/solvers.R -
          getMatchedPathwayMatOld.Rd
          -
          - -
          -

          Filters a gene-by-pathway annotation matrix to retain only pathways -with sufficient overlap with a given gene set. The result is a sparse matrix -aligned to new.genes, with columns (pathways) retained only if they -have at least min.genes matched genes.

          -
          - -
          -

          Usage

          - 
          getMatchedPathwayMatOld(pathMat, new.genes, min.genes = 10)
          -
          - -
          -

          Arguments

          - - -
          pathMat
          -

          A sparse binary matrix of genes (rows) x pathways (columns).

          - - -
          new.genes
          -

          Character vector of gene names to match.

          - - -
          min.genes
          -

          Minimum number of overlapping genes required to keep a pathway.

          - -
          -
          -

          Value

          -

          A sparse matrix of dimensions length(new.genes) x filtered pathways.

          -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/getMaxAUC.html b/docs/reference/getMaxAUC.html deleted file mode 100644 index da10c82..0000000 --- a/docs/reference/getMaxAUC.html +++ /dev/null @@ -1,89 +0,0 @@ - -Get maximum AUC per latent variable — getMaxAUC • CLAMP - Skip to contents - - -
          -
          -
          - -

          Get maximum AUC per latent variable

          - Source: R/utils.R -
          getMaxAUC.Rd
          -
          - -
          -

          Summarizes a cross-validation results data frame to extract the highest AUC value -associated with each latent variable (LV).

          -
          - -
          -

          Usage

          - 
          getMaxAUC(summary, verbose = FALSE)
          -
          - -
          -

          Arguments

          - - -
          summary
          -

          A data frame (e.g., from crossVal()) .

          - - -
          verbose
          -

          Logical; if TRUE, prints counts of LVs exceeding AUC thresholds. Default is FALSE.

          - -
          -
          -

          Value

          -

          A data frame with columns LV index and max_AUC.

          -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/getScaleFromSVs.html b/docs/reference/getScaleFromSVs.html deleted file mode 100644 index bb0dff6..0000000 --- a/docs/reference/getScaleFromSVs.html +++ /dev/null @@ -1,117 +0,0 @@ - -Estimate noise scale from singular values with linear tail extrapolation — getScaleFromSVs • CLAMP - Skip to contents - - -
          -
          -
          - -

          Estimate noise scale from singular values with linear tail extrapolation

          - Source: R/utils.R -
          getScaleFromSVs.Rd
          -
          - -
          -

          This function estimates a characteristic scale from a vector of singular values -by fitting a linear model to the tail and extrapolating to length n. -The median of the extrapolated values is returned as the estimate. -If no sufficiently linear tail is detected (based on min_r2) or -the extrapolation produces negative values, a fallback estimate is returned -using the 75\

          -
          - -
          -

          Usage

          - 
          getScaleFromSVs(sv, n, min_r2 = 0.95)
          -
          - -
          -

          Arguments

          - - -
          sv
          -

          Numeric vector of singular values sorted in decreasing order.

          - - -
          n
          -

          Integer, total length to which the linear tail is extrapolated.

          - - -
          min_r2
          -

          Numeric, minimum R-squared value required for accepting -the linear tail fit. Defaults to 0.95.

          - -
          -
          -

          Value

          -

          A numeric scalar giving the estimated scale. If linear extrapolation -is unreliable, returns sv[ceiling(0.75 * length(sv))].

          -
          - -
          -

          Examples

          - 
          sv <- exp(-seq(0, 5, length.out = 50)) + rnorm(50, 0, 0.01)
-getScaleFromSVs(sv, n = 100)
-#> $scale
-#> [1] 0.02612941
-#> 
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/gmtListToSparseMat.html b/docs/reference/gmtListToSparseMat.html deleted file mode 100644 index ca69595..0000000 --- a/docs/reference/gmtListToSparseMat.html +++ /dev/null @@ -1,103 +0,0 @@ - -Convert a list of GMT gene sets to a sparse matrix — gmtListToSparseMat • CLAMP - Skip to contents - - -
          -
          -
          - -

          Convert a list of GMT gene sets to a sparse matrix

          - Source: R/utils.R -
          gmtListToSparseMat.Rd
          -
          - -
          -

          Converts a list of named gene sets (e.g., from getGMT()) into a sparse binary matrix -where rows are genes, columns are gene sets, and entries are 1 if the gene is in the set.

          -
          - -
          -

          Usage

          - 
          gmtListToSparseMat(gmtList)
          -
          - -
          -

          Arguments

          - - -
          gmtList
          -

          A nested list of gene sets. Outer names are gene set names; each entry is a character -vector of gene names.

          - -
          -
          -

          Value

          -

          A sparse binary matrix with genes as rows and gene sets as columns.

          -
          - -
          -

          Examples

          - 
          # define a simple nested GMT list
-gmt1 <- list(
-    PathwayA = c('Gene1', 'Gene2', 'Gene3'),
-    PathwayB = c('Gene2', 'Gene4')
-)
-gmt2 <- list(
-    PathwayC = c('Gene1', 'Gene4'),
-    PathwayD = c('Gene3', 'Gene5')
-)
-# combine into a nested list
-nestedList <- list(gmt1 = gmt1, gmt2 = gmt2)
-# convert to sparse matrix
-sparseMat <- gmtListToSparseMat(nestedList)
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/index.html b/docs/reference/index.html deleted file mode 100644 index 7608ca3..0000000 --- a/docs/reference/index.html +++ /dev/null @@ -1,439 +0,0 @@ - -Package index • CLAMP - Skip to contents - - -
          -
          -
          - -

          Package index

          -
          - -
          -

          Main CLAMP functions

          - - - -
          - - - - -
          - - CLAMPbase() - -
          -
          CLAMP base matrix factorization
          - -
          - - CLAMPfull() - -
          -
          Runs the streamlined full CLAMP model.
          - -
          - - CLAMPfullnVP() - -
          -
          Full CLAMP model with prior information and cross-validation
          - -
          - - projectCLAMP() - -
          -
          Project new data into CLAMP latent space
          -
          -

          SVD and rank selection

          - - - -
          - - - - -
          - - select_svd_k() - -
          -
          Select default number of components for a CLAMP solver SVD
          - -
          - - compute_svd() - -
          -
          Compute a truncated SVD for a CLAMP input matrix
          - -
          - - select_clamp_k() - -
          -
          Select default number of CLAMP latent variables from an SVD
          - -
          - - num.pc() - -
          -
          Estimate number of principal components via elbow or permutation method
          - -
          - - getScaleFromSVs() - -
          -
          Estimate noise scale from singular values with linear tail extrapolation
          -
          -

          Preprocessing

          - - - -
          - - - - -
          - - cpmCLAMP() - -
          -
          Compute counts-per-million (CPM) for CLAMP pipelines
          - -
          - - cpmCLAMPFBM() - -
          -
          Compute CPM on a file-backed matrix for CLAMP (in-place)
          - -
          - - preprocessCLAMP() - -
          -
          Preprocess an expression matrix for CLAMP
          - -
          - - preprocessCLAMPFBM() - -
          -
          Preprocess a bigstatsr FBM for CLAMP
          - -
          - - zscoreCLAMP() - -
          -
          Z-score a filtered expression matrix for CLAMP
          - -
          - - zscoreCLAMPFBM() - -
          -
          Z-score a filtered FBM in-place
          - -
          - - tscale() - -
          -
          Row-wise scaling (mean 0, sd 1)
          -
          -

          Prior knowledge

          - - - -
          - - - - -
          - - getGMT() - -
          -
          Download and read a GMT file from a URL
          - -
          - - read_gmt() - -
          -
          Read a GMT file into a list
          - -
          - - gmtListToSparseMat() - -
          -
          Convert a list of GMT gene sets to a sparse matrix
          - -
          - - getMatchedPathwayMat() - -
          -
          Subset and filter pathway matrix to match target genes
          - -
          - - getMatchedPathwayMatList() - -
          -
          Subset and filter multiple pathway matrices to match target genes
          - -
          - - getChat() - -
          -
          Compute Chat matrix from prior annotation
          -
          -

          Evaluation and visualization

          - - - -
          - - - - -
          - - compareBs() - -
          -
          Compare two sets of factor loadings or embeddings
          - -
          - - allAgainstAllAUCs() - -
          -
          Compute all-vs-all AUC matrix
          - -
          - - CLAMPplotU() - -
          -
          Plot the U matrix (pathway-LV associations) as a heatmap
          - -
          - - CLAMPplotTopZ() - -
          -
          Plot top genes per LV by Z loading
          - -
          - - CLAMPdotplot() - -
          -
          Dot plot of top pathways for a single latent variable
          - -
          - - CLAMPdotplotAll() - -
          -
          Dot plot of pathway-LV associations across all latent variables
          - -
          - - plotTopZ_Complex() - -
          -
          ComplexHeatmap visualization of top genes by latent variable
          -
          -

          FBM utilities

          - - - -
          - - - - -
          - - cleanFBM() - -
          -
          Clean a Filebacked Big Matrix (FBM) by log-transforming and handling NAs
          - -
          - - filterFBM() - -
          -
          Filter rows of a Filebacked Big Matrix based on mean and variance
          -
          -

          Solvers and helpers

          - - - -
          - - - - -
          - - cross_ZY() - -
          -
          Cross-product Z^T Y with FBM or dense matrices
          - -
          - - ridge_B() - -
          -
          Ridge regression update for B
          - -
          - - solveU() - -
          -
          Fit the loading matrix Z using sparse regression of prior information U
          - -
          - - mat_mult() - -
          -
          Matrix multiplication with support for FBM objects
          - -
          - - findSplineMax() - -
          -
          Find the location of the maximum of a smoothing spline
          - -
          - - oneToOneMask() - -
          -
          One-to-one masking of maximum associations
          - -
          - - squashZscore() - -
          -
          Squash extreme z-scores
          - -
          - - winsor_topk() - -
          -
          Winsorize matrix columns by capping the top-k values
          -
          -

          Datasets

          - - - -
          - - - - -
          - - dataWholeBlood - -
          -
          Whole-blood reference expression matrix
          - -
          - - celltypeTargets - -
          -
          Cell-type deconvolution matrix
          - -
          - - majorCellTypes - -
          -
          Major cell-type annotations
          - -
          - - panDB - -
          -
          panDB gene-set database
          - -
          - - xCell - -
          -
          xCell cell-signature matrix
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/majorCellTypes.html b/docs/reference/majorCellTypes.html deleted file mode 100644 index 9633840..0000000 --- a/docs/reference/majorCellTypes.html +++ /dev/null @@ -1,90 +0,0 @@ - -Major cell-type annotations — majorCellTypes • CLAMP - Skip to contents - - -
          -
          -
          - -

          Major cell-type annotations

          - Source: R/majorCellTypes.R -
          majorCellTypes.Rd
          -
          - -
          -

          A factor vector annotating samples by major cell type. -This dataset provides cell-type labels corresponding to each sample -in the reference expression matrix.

          -
          - -
          -

          Usage

          - 
          data(majorCellTypes)
          -
          - -
          -

          Format

          -

          A factor (or character) vector of length N, -where each element corresponds to a sample and indicates its major cell type.

          -
          -
          -

          Value

          -

          A factor (or character) vector of major cell-type labels.

          -
          - -
          -

          Examples

          - 
          data(majorCellTypes)
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/mat_mult.html b/docs/reference/mat_mult.html deleted file mode 100644 index 4e74b13..0000000 --- a/docs/reference/mat_mult.html +++ /dev/null @@ -1,108 +0,0 @@ - -Matrix multiplication with support for FBM objects — mat_mult • CLAMP - Skip to contents - - -
          -
          -
          - -

          Matrix multiplication with support for FBM objects

          - Source: R/solvers.R -
          mat_mult.Rd
          -
          - -
          -

          Multiplies two matrices, using optimized multiplication if the first -is a Filebacked Big Matrix (FBM).

          -
          - -
          -

          Usage

          - 
          mat_mult(mat1, mat2, ncores = 1)
          -
          - -
          -

          Arguments

          - - -
          mat1
          -

          A matrix or an object of class FBM.

          - - -
          mat2
          -

          A numeric matrix.

          - - -
          ncores
          -

          Number of cores to use for parallel computation -(only used if mat1 is an FBM). Default is 1.

          - -
          -
          -

          Value

          -

          Matrix product of mat1 and mat2.

          -
          - -
          -

          Examples

          - 
          set.seed(123)
-mat1 <- matrix(rnorm(20), nrow = 4)
-mat2 <- matrix(rnorm(15), nrow = 5)
-res1 <- mat_mult(mat1, mat2)
-res1
-#>            [,1]       [,2]       [,3]
-#> [1,]  0.6717269  1.1164009 -0.1310362
-#> [2,]  1.4777363 -0.8350005 -2.5216939
-#> [3,] -3.0540345 -0.5431782  1.7125552
-#> [4,] -1.1756616 -3.7501369  1.9061432
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/max_correspondence_greedy.html b/docs/reference/max_correspondence_greedy.html deleted file mode 100644 index d972570..0000000 --- a/docs/reference/max_correspondence_greedy.html +++ /dev/null @@ -1,85 +0,0 @@ - -Greedy maximum correspondence from correlation matrix — max_correspondence_greedy • CLAMP - Skip to contents - - -
          -
          -
          - -

          Greedy maximum correspondence from correlation matrix

          - Source: R/utils.R -
          max_correspondence_greedy.Rd
          -
          - -
          -

          Finds a one-to-one assignment (permutation) between rows and columns of a square correlation matrix -that maximizes the total correlation score, using a greedy algorithm.

          -
          - -
          -

          Usage

          - 
          max_correspondence_greedy(cor_mat)
          -
          - -
          -

          Arguments

          - - -
          cor_mat
          -

          A square numeric matrix of pairwise correlations (rows = items, cols = items).

          - -
          -
          -

          Value

          -

          A vector of assignments (integer indices).

          -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/mymessage.html b/docs/reference/mymessage.html deleted file mode 100644 index 7656bcb..0000000 --- a/docs/reference/mymessage.html +++ /dev/null @@ -1,82 +0,0 @@ - -Print a concatenated message — mymessage • CLAMP - Skip to contents - - -
          -
          -
          - -

          Print a concatenated message

          - Source: R/utils.R -
          mymessage.Rd
          -
          - -
          -

          Wrapper around message() that pastes arguments together into a single string.

          -
          - -
          -

          Usage

          - 
          mymessage(...)
          -
          - -
          -

          Arguments

          - - -
          ...
          -

          Character strings to concatenate and print.

          - -
          -
          -

          Value

          -

          Invisibly returns NULL. Called for side effects (messages).

          -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/num.pc.html b/docs/reference/num.pc.html deleted file mode 100644 index 217a3e7..0000000 --- a/docs/reference/num.pc.html +++ /dev/null @@ -1,108 +0,0 @@ - -Estimate number of principal components via elbow or permutation method — num.pc • CLAMP - Skip to contents - - -
          -
          -
          - -

          Estimate number of principal components via elbow or permutation method

          - Source: R/solvers.R -
          num.pc.Rd
          -
          - -
          -

          Estimate number of principal components via elbow or permutation method

          -
          - -
          -

          Usage

          - 
          num.pc(data, method = c("elbow", "permutation"), B = 20, seed = NULL)
          -
          - -
          -

          Arguments

          - - -
          data
          -

          Either a matrix (e.g. z-scored data) or an SVD result (list with $d).

          - - -
          method
          -

          One of "elbow" (fast) or "permutation" (slower).

          - - -
          B
          -

          Number of permutations (for method = "permutation").

          - - -
          seed
          -

          Seed for reproducibility.

          - -
          -
          -

          Value

          - 

             Estimated number of PCs.

          -
          - -
          -

          Examples

          - 
          # generate a small random matrix: 5 features x 10 samples
-mat <- matrix(rnorm(5 * 10), nrow = 5)
-# fast elbow estimate
-num.pc(mat, method = "elbow")
-#> Computing SVD
-#> [1] 2
-# slower permutation estimate (use fewer perms for example speed)
-num.pc(mat, method = "permutation", B = 5)
-#> Computing SVD
-#> [1] 0
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/oneToOneMask.html b/docs/reference/oneToOneMask.html deleted file mode 100644 index 60fab56..0000000 --- a/docs/reference/oneToOneMask.html +++ /dev/null @@ -1,103 +0,0 @@ - -One-to-one masking of maximum associations — oneToOneMask • CLAMP - Skip to contents - - -
          -
          -
          - -

          One-to-one masking of maximum associations

          - Source: R/utils.R -
          oneToOneMask.Rd
          -
          - -
          -

          Selects the highest-scoring one-to-one pairs between rows and columns -of a matrix, similar to a greedy bipartite matching. All other entries -are set to a sentinel value (default -100).

          -
          - -
          -

          Usage

          - 
          oneToOneMask(cc)
          -
          - -
          -

          Arguments

          - - -
          cc
          -

          A numeric matrix of association scores.

          - -
          -
          -

          Value

          -

          A numeric matrix of the same dimensions as cc, -where only the selected one-to-one maxima are retained -and all other entries are set to -100.

          -
          - -
          -

          Examples

          - 
          set.seed(1)
-m <- matrix(runif(16), 4, 4)
-oneToOneMask(m)
-#>              [,1]         [,2]          [,3]         [,4]
-#> [1,] -100.0000000 -100.0000000 -100.00000000    0.6870228
-#> [2,] -100.0000000 -100.0000000    0.06178627 -100.0000000
-#> [3,] -100.0000000    0.9446753 -100.00000000 -100.0000000
-#> [4,]    0.9082078 -100.0000000 -100.00000000 -100.0000000
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/panDB.html b/docs/reference/panDB.html deleted file mode 100644 index eac503b..0000000 --- a/docs/reference/panDB.html +++ /dev/null @@ -1,91 +0,0 @@ - -panDB gene-set database — panDB • CLAMP - Skip to contents - - -
          -
          -
          - -

          panDB gene-set database

          - Source: R/panDB.R -
          panDB.Rd
          -
          - -
          -

          A list of curated pathway and biological process gene sets used as prior knowledge -for CLAMP and other latent-variable models.

          -
          - -
          -

          Usage

          - 
          data(panDB)
          -
          - -
          -

          Format

          -

          A named list of length M, where each element is a gene-set collection.

          -
          -
          -

          Value

          -

          A list of gene-set collections used as priors for pathway-informed modeling.

          -
          -
          -

          Details

          -

          Each element corresponds to a functional collection (e.g., KEGG, Reactome, GO), -where each entry contains a character vector of gene symbols.

          -
          - -
          -

          Examples

          - 
          data(panDB)
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/pinv.ridge.html b/docs/reference/pinv.ridge.html deleted file mode 100644 index 7f138e5..0000000 --- a/docs/reference/pinv.ridge.html +++ /dev/null @@ -1,94 +0,0 @@ - -Ridge-regularized pseudoinverse via SVD — pinv.ridge • CLAMP - Skip to contents - - -
          -
          -
          - -

          Ridge-regularized pseudoinverse via SVD

          - Source: R/solvers.R -
          pinv.ridge.Rd
          -
          - -
          -

          Computes a stable pseudoinverse of a symmetric positive semi-definite matrix -using singular value decomposition (SVD) and ridge regularization. This is -useful when the matrix is ill-conditioned or rank-deficient.

          -
          - -
          -

          Usage

          - 
          pinv.ridge(m, alpha = 0)
          -
          - -
          -

          Arguments

          - - -
          m
          -

          A symmetric numeric matrix (e.g., from crossprod()).

          - - -
          alpha
          -

          Non-negative scalar specifying the ridge penalty. -A small positive value stabilizes the inversion by shrinking large singular values.

          - -
          -
          -

          Value

          -

          A numeric matrix representing the ridge-regularized -pseudoinverse of m.

          -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
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z3<}2K(F!oFtgnyYh(5ythZ$+jhX$wNQ_`Pum&BC{4_6RIt^wtL-$&tQ&za<)pXAL9`1Me}oy~MZdmh+#^iUcIy>979&qu_R^k-Bs9DZ3;|5JTjn z!dVcfCt1xUB9*?Hu=w43nfgwHzNak+kdM;JURAw$(?#NkjCn*G+i=m#g_Ix+my#qj zD*Rx_oSWQ(rVX6_=Pva+%rN>OwSv7IBUwp!j5xS9(T^WIfWwp%b`~ou1z}hNw^WLZ zf~fNQVM!z9bzC+RKFp9(vAB9nSyd>&xi__`-ySpbmg0ce(Lc-)xjiiYBjcrK`~1iR z$zvHPJGni50Eg_`upC*>$z%eIkBIf8@2lWxg2_(r?>tFN@iMGCn*toOn>|S;JR)KW z*&BhUlW-A1|A@;MlKN)Olk)Nyp-kyz*3ytCJ}E-9`40qT_f=h}U7dc~oC`xqgFeYd*M^^!m6m!WgXv5yUS|Zy6(uDhgpc}huSEw+Z(25F|lLwT1 zu!nVi(3S!qtB2bogg~vaKJ(! z^qFn9U3|io-apLTeK+woguj+xErke62=&JZR||PsqBrJAoJ29`HeQ(KLzy>-AR}@ z0u?d*5T=FmS(!TnVJAQg7nk~32L>!_{rAh|^M#zI__KxD%95M;wz=86aLEk==j4#1 zM|*D;o!Nbr{_jWkAl)DnU5hE(Ha*#4!=OOC -ComplexHeatmap visualization of top genes by latent variable — plotTopZ_Complex • CLAMP - Skip to contents - - -

          -
          -
          - -

          ComplexHeatmap visualization of top genes by latent variable

          - Source: R/plots.R -
          plotTopZ_Complex.Rd
          -
          - -
          -

          Produces a combined heatmap showing expression, pathway membership, -and optionally Z-loadings for top genes per LV using ComplexHeatmap.

          -
          - -
          -

          Usage

          - 
          plotTopZ_Complex(
-  clampRes,
-  data,
-  priorMat,
-  top = 10,
-  top.pathway = 5,
-  index = NULL,
-  allLVs = FALSE,
-  Zheat = FALSE,
-  LV.names = NULL,
-  max.genes = 100,
-  max.col = 50,
-  seed = 1234
-)
          -
          - -
          -

          Arguments

          - - -
          clampRes
          -

          A CLAMP result list containing matrices Z, U, etc.

          - - -
          data
          -

          Expression matrix with genes as rows.

          - - -
          priorMat
          -

          Binary gene × pathway matrix.

          - - -
          top
          -

          Integer, number of top genes per LV.

          - - -
          top.pathway
          -

          Integer, number of top pathways per LV to annotate.

          - - -
          index
          -

          Optional vector of LVs to include.

          - - -
          allLVs
          -

          Logical; include all LVs.

          - - -
          Zheat
          -

          Logical; whether to include the Z matrix as an additional heatmap.

          - - -
          LV.names
          -

          Optional character vector for LV names.

          - - -
          max.genes
          -

          Maximum number of genes allowed in the plot.

          - - -
          max.col
          -

          Maximum number of columns (samples).

          - - -
          seed
          -

          Random seed for column subsampling.

          - -
          -
          -

          Value

          -

          Invisibly returns the drawn ComplexHeatmap object.

          -
          - -
          -

          Examples

          - 
          library(ComplexHeatmap)
-#> Loading required package: grid
-#> ========================================
-#> ComplexHeatmap version 2.27.1
-#> Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
-#> Github page: https://github.com/jokergoo/ComplexHeatmap
-#> Documentation: http://jokergoo.github.io/ComplexHeatmap-reference
-#> 
-#> If you use it in published research, please cite either one:
-#> - Gu, Z. Complex Heatmap Visualization. iMeta 2022.
-#> - Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
-#>     genomic data. Bioinformatics 2016.
-#> 
-#> 
-#> The new InteractiveComplexHeatmap package can directly export static 
-#> complex heatmaps into an interactive Shiny app with zero effort. Have a try!
-#> 
-#> This message can be suppressed by:
-#>   suppressPackageStartupMessages(library(ComplexHeatmap))
-#> ========================================
-library(Matrix)
-
-# Simulate small CLAMP-like results
-set.seed(123)
-genes <- paste0("Gene", 1:100)
-samples <- paste0("S", 1:20)
-lvs <- paste0("LV", 1:3)
-
-# Simulated Z (gene loadings) and U (pathway loadings)
-Z <- matrix(rnorm(100 * 3), nrow = 100, dimnames = list(genes, lvs))
-U <- matrix(abs(rnorm(50 * 3)), nrow = 50,
-            dimnames = list(paste0("Path", 1:50), lvs))
-
-# Expression data
-expr_data <- matrix(rnorm(100 * 20), nrow = 100,
-                    dimnames = list(genes, samples))
-
-# Binary gene × pathway matrix
-priorMat <- matrix(sample(0:1, 100 * 50, replace = TRUE, prob = c(0.9, 0.1)),
-                   nrow = 100, ncol = 50,
-                   dimnames = list(genes, paste0("Path", 1:50)))
-
-# Create a CLAMP-like result list
-clampRes <- list(Z = Z, U = U)
-
-# Plot top genes and pathway memberships
-plotTopZ_Complex(clampRes, expr_data, priorMat,
-                 top = 5, top.pathway = 3, index = 1:2, Zheat = TRUE)
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/preprocessCLAMP.html b/docs/reference/preprocessCLAMP.html deleted file mode 100644 index d5e0433..0000000 --- a/docs/reference/preprocessCLAMP.html +++ /dev/null @@ -1,113 +0,0 @@ - -Preprocess an expression matrix for CLAMP — preprocessCLAMP • CLAMP - Skip to contents - - -
          -
          -
          - -

          Preprocess an expression matrix for CLAMP

          - Source: R/utils.R -
          preprocessCLAMP.Rd
          -
          - -
          -

          Filters genes by mean expression and variance, returning the filtered matrix -and per-gene statistics.

          -
          - -
          -

          Usage

          - 
          preprocessCLAMP(Y, mean_cutoff = 0, var_cutoff = 0)
          -
          - -
          -

          Arguments

          - - -
          Y
          -

          Numeric matrix of gene expression (rows = genes, cols = samples)

          - - -
          mean_cutoff
          -

          Numeric. Minimum row-mean required to keep a gene (default 0).

          - - -
          var_cutoff
          -

          Numeric. Minimum row-variance required to keep a gene (default 0).

          - -
          -
          -

          Value

          -

          A list with components:

          • Y_filtered: filtered matrix (genes x samples)

            • -

          • rowStats: data.frame with columns mean and variance for each kept gene

            • -

          • kept_rows: integer vector of the original row indices that were kept

            • -
          - -
          -

          Examples

          - 
          # construct a small example matrix
-mat <- matrix(
-    c(
-        1, 5, 10,
-        2, 6, 11,
-        3, 7, 12,
-        4, 8, 13
-    ),
-    nrow = 4, byrow = FALSE,
-    dimnames = list(paste0('gene', seq_len(4)), paste0('sample', seq_len(3)))
-)
-
-# keep genes with mean >= 6 and variance >= 2
-res <- preprocessCLAMP(mat, mean_cutoff = 6, var_cutoff = 2)
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/preprocessCLAMPFBM.html b/docs/reference/preprocessCLAMPFBM.html deleted file mode 100644 index ab549af..0000000 --- a/docs/reference/preprocessCLAMPFBM.html +++ /dev/null @@ -1,143 +0,0 @@ - -Preprocess a bigstatsr FBM for CLAMP — preprocessCLAMPFBM • CLAMP - Skip to contents - - -
          -
          -
          - -

          Preprocess a bigstatsr FBM for CLAMP

          - Source: R/utils.R -
          preprocessCLAMPFBM.Rd
          -
          - -
          -

          Makes a writable copy of the input FBM, cleans it (log2 transform if needed, fill NAs), -filters rows by mean/variance, and returns the filtered FBM plus stats and indices.

          -
          - -
          -

          Usage

          - 
          preprocessCLAMPFBM(
-  fbm,
-  mean_cutoff = NULL,
-  var_cutoff = NULL,
-  backingfile = NULL,
-  block_size = 1000,
-  ncores = 1
-)
          -
          - -
          -

          Arguments

          - - -
          fbm
          -

          A bigstatsr::FBM (genes x samples), possibly read-only.

          - - -
          mean_cutoff
          -

          Numeric or NULL. Minimum row mean to keep (NULL = no mean filter).

          - - -
          var_cutoff
          -

          Numeric or NULL. Minimum row variance to keep (NULL = no var filter).

          - - -
          backingfile
          -

          Character or NULL. Base name for the copy FBM and filtered FBM on disk. -If NULL, defaults to paste0(fbm$backingfile, '_preproc') and '_filtered'.

          - - -
          block_size
          -

          Number of rows to process at a time when copying data. Default is 1000.

          - - -
          ncores
          -

          Integer; number of cores to use for parallel operations (default 1).

          - -
          -
          -

          Value

          -

          A list with:

          -
          fbm_filtered
          -

          The filtered FBM (writable).

          - -
          rowStats
          -

          List with row_means & row_variances for fbm_filtered.

          - -
          kept_rows
          -

          Integer vector of original row indices that were retained.

          - -
          - -
          -

          Examples

          - 
          library(bigstatsr)
-# create a toy matrix and back it with an FBM
-mat <- matrix(
-    c(
-        1, 2, 3, # geneA
-        10, 20, 30, # geneB
-        100, 200, 300 # geneC
-    ),
-    nrow = 3, byrow = TRUE,
-    dimnames = list(c('geneA', 'geneB', 'geneC'), paste0('s', seq_len(3)))
-)
-fbm <- FBM(nrow(mat), ncol(mat), init = mat)
-
-# preprocess without filtering (all genes kept)
-res_all <- preprocessCLAMPFBM(fbm)
-#> Applying log2 transformation
-#> No NA values found
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/preprocessPLIER2.html b/docs/reference/preprocessPLIER2.html deleted file mode 100644 index 79c958e..0000000 --- a/docs/reference/preprocessPLIER2.html +++ /dev/null @@ -1,107 +0,0 @@ - -Preprocess an expression matrix for PLIER2 — preprocessPLIER2 • PLIER2 - Skip to contents - - -
          -
          -
          - -

          Preprocess an expression matrix for PLIER2

          - Source: R/utils.R -
          preprocessPLIER2.Rd
          -
          - -
          -

          Filters genes by mean expression and variance, returning the filtered matrix -and per-gene statistics.

          -
          - -
          -

          Usage

          - 
          preprocessPLIER2(Y, mean_cutoff = 0, var_cutoff = 0)
          -
          - -
          -

          Arguments

          - - -
          Y
          -

          Numeric matrix of gene expression (rows = genes, cols = samples)

          - - -
          mean_cutoff
          -

          Numeric. Minimum row-mean required to keep a gene (default 0).

          - - -
          var_cutoff
          -

          Numeric. Minimum row-variance required to keep a gene (default 0).

          - -
          -
          -

          Value

          -

          A list with components:

          • Y_filtered: filtered matrix (genes x samples)

            • -

          • rowStats: data.frame with columns mean and variance for each kept gene

            • -

          • kept_rows: integer vector of the original row indices that were kept

            • -
          - -
          -

          Examples

          - 
          # construct a small example matrix
-mat <- matrix(
-  c(1, 5, 10,
-    2, 6, 11,
-    3, 7, 12,
-    4, 8, 13),
-  nrow = 4, byrow = FALSE,
-  dimnames = list(paste0("gene", 1:4), paste0("sample", 1:3))
-)
-
-# keep genes with mean >= 6 and variance >= 2
-res <- preprocessPLIER2(mat, mean_cutoff = 6, var_cutoff = 2)
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.1.3.

          -
          - -
          - - - - - - - diff --git a/docs/reference/preprocessPLIER2FBM.html b/docs/reference/preprocessPLIER2FBM.html deleted file mode 100644 index 15f5fd3..0000000 --- a/docs/reference/preprocessPLIER2FBM.html +++ /dev/null @@ -1,126 +0,0 @@ - -Preprocess a bigstatsr FBM for PLIER2 — preprocessPLIER2FBM • PLIER2 - Skip to contents - - -
          -
          -
          - -

          Preprocess a bigstatsr FBM for PLIER2

          - Source: R/utils.R -
          preprocessPLIER2FBM.Rd
          -
          - -
          -

          Makes a writable copy of the input FBM, cleans it (log2 transform if needed, fill NAs), -filters rows by mean/variance, and returns the filtered FBM plus stats and indices.

          -
          - -
          -

          Usage

          - 
          preprocessPLIER2FBM(
-  fbm,
-  mean_cutoff = NULL,
-  var_cutoff = NULL,
-  backingfile = NULL
-)
          -
          - -
          -

          Arguments

          - - -
          fbm
          -

          A bigstatsr::FBM (genes x samples), possibly read-only.

          - - -
          mean_cutoff
          -

          Numeric or NULL. Minimum row mean to keep (NULL = no mean filter).

          - - -
          var_cutoff
          -

          Numeric or NULL. Minimum row variance to keep (NULL = no var filter).

          - - -
          backingfile
          -

          Character or NULL. Base name for the copy FBM and filtered FBM on disk. -If NULL, defaults to paste0(fbm$backingfile, "_preproc") and "_filtered".

          - -
          -
          -

          Value

          -

          A list with:

          -
          fbm_filtered
          -

          The filtered FBM (writable).

          - -
          rowStats
          -

          List with row_means & row_variances for fbm_filtered.

          - -
          kept_rows
          -

          Integer vector of original row indices that were retained.

          - -
          - -
          -

          Examples

          - 
          library(bigstatsr)
-# create a toy matrix and back it with an FBM
-mat <- matrix(c(
-  1,   2,   3,    # geneA
-  10, 20,  30,    # geneB
-  100,200,300     # geneC
-), nrow = 3, byrow = TRUE,
-dimnames = list(c("geneA","geneB","geneC"), paste0("s", 1:3)))
-fbm <- FBM(nrow(mat), ncol(mat), init = mat)
-
-# preprocess without filtering (all genes kept)
-res_all <- preprocessPLIER2FBM(fbm)
-#> Applying log2 transformation
-#> No NA values found
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.1.3.

          -
          - -
          - - - - - - - diff --git a/docs/reference/projectCLAMP.html b/docs/reference/projectCLAMP.html deleted file mode 100644 index d03271d..0000000 --- a/docs/reference/projectCLAMP.html +++ /dev/null @@ -1,153 +0,0 @@ - -Project new data into CLAMP latent space — projectCLAMP • CLAMP - Skip to contents - - -
          -
          -
          - -

          Project new data into CLAMP latent space

          - Source: R/solvers.R -
          projectCLAMP.Rd
          -
          - -
          -

          Computes the latent loadings B for new gene expression data using -the latent variables Z from a fitted CLAMP model. This allows -transfer of the learned latent structure to new datasets with matched genes.

          -
          - -
          -

          Usage

          - 
          projectCLAMP(
-  CLAMPres,
-  newdata,
-  scale = 1,
-  ncores = 1,
-  align = TRUE,
-  verbose = TRUE
-)
          -
          - -
          -

          Arguments

          - - -
          CLAMPres
          -

          A result object from CLAMPfull() or -CLAMPbase(), containing at least Z and L2.

          - - -
          newdata
          -

          A gene expression matrix (genes x samples) to be projected. -Can be a standard matrix, sparse matrix, or FBM/big.matrix.

          - - -
          scale
          -

          Optional numeric multiplier for the L2 regularization terms. Default is 1.

          - - -
          ncores
          -

          Number of cores to use for parallel computation (only used if newdata is an FBM). -Default is 1.

          - - -
          align
          -

          Logical; if TRUE (default), row names shared by -CLAMPres$Z and newdata are used to align both matrices to -the same genes in the same order before projection. If row names are not -available, dimensions must already match.

          - - -
          verbose
          -

          Logical; if TRUE (default), report how many common -rows are used for projection.

          - -
          -
          -

          Value

          -

          A matrix B of projected latent loadings (LVs x samples) for the new dataset.

          -
          -
          -

          Details

          -

          This function uses ridge-regularized least squares to compute -B = solve(Z'Z + L2 * I) * Z'Y, where Z is the latent matrix -from the trained CLAMP model and Y is the new dataset. If -newdata is a Filebacked Big Matrix (FBM) and does not need row-name -subsetting, the computation is optimized using -bigstatsr::big_cprodMat().

          -
          - -
          -

          Examples

          - 
          # fit a tiny CLAMP model for projection
-Y0 <- matrix(rnorm(5 * 3), nrow = 5,
-             dimnames = list(paste0("Gene", 1:5), paste0("S", 1:3)))
-base <- CLAMPbase(Y0, clamp_k = 2, max.iter = 1, trace = FALSE)
-#> ****
-#> Computing SVD
-#> CLAMP k is set to 2
-#> L1 is set to 0.607987142025783
-#> L2 is set to 1.82396142607735
-# new data can be provided in a different row order
-newY <- matrix(rnorm(5 * 2), nrow = 5,
-               dimnames = list(rev(rownames(Y0)), paste0("N", 1:2)))
-projB <- projectCLAMP(base, newdata = newY)
-#> 5 common rows found
-# check dimensions: 2 latent vars x 2 samples
-dim(projB)
-#> [1] 2 2
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/projectPLIER.html b/docs/reference/projectPLIER.html deleted file mode 100644 index 64dafa4..0000000 --- a/docs/reference/projectPLIER.html +++ /dev/null @@ -1,117 +0,0 @@ - -Project new data into PLIER latent space — projectPLIER • PLIER2 - Skip to contents - - -
          -
          -
          - -

          Project new data into PLIER latent space

          - Source: R/solvers.R -
          projectPLIER.Rd
          -
          - -
          -

          Computes the latent loadings B for new gene expression data using the latent variables -Z from a fitted PLIER model. This allows transfer of the learned latent structure to -new datasets with matched genes.

          -
          - -
          -

          Usage

          - 
          projectPLIER(PLIERres, newdata, scale = 1)
          -
          - -
          -

          Arguments

          - - -
          PLIERres
          -

          A result object from PLIERfull() or PLIERbase(), containing at least Z and L2.

          - - -
          newdata
          -

          A gene expression matrix (genes x samples) to be projected. Must have the same genes (rows) as PLIERres$Z. -Can be a standard matrix, sparse matrix, or FBM/big.matrix.

          - - -
          scale
          -

          Optional numeric multiplier for the L2 regularization terms. Default is 1.

          - -
          -
          -

          Value

          -

          A matrix B of projected latent loadings (LVs x samples) for the new dataset.

          -
          -
          -

          Details

          -

          This function uses ridge-regularized least squares to compute B = solve(ZᵗZ + L2·I) · ZᵗY, where -Z is the latent matrix from the trained PLIER model and Y is the new dataset. -If newdata is a Filebacked Big Matrix (FBM), the computation is optimized using bigstatsr::big_cprodMat().

          -
          - -
          -

          Examples

          - 
          # fit a tiny PLIER model for projection
-Y0 <- matrix(rnorm(5*3), nrow = 5)
-base <- PLIERbase(Y0, k = 2, max.iter = 1, trace = FALSE)
-#> ****
-#> Computing SVD
-#> [1] "L1 is set to 0.840633045609829"
-#> [1] "L2 is set to 2.52189913682949"
-# new data with same 5 genes
-newY <- matrix(rnorm(5*2), nrow = 5)
-projB <- projectPLIER(base, newdata = newY)
-# check dimensions: 2 latent vars x 2 samples
-dim(projB)
-#> [1] 2 2
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.1.3.

          -
          - -
          - - - - - - - diff --git a/docs/reference/read_gmt.html b/docs/reference/read_gmt.html deleted file mode 100644 index 7f6b0bc..0000000 --- a/docs/reference/read_gmt.html +++ /dev/null @@ -1,109 +0,0 @@ - -Read a GMT file into a list — read_gmt • CLAMP - Skip to contents - - -
          -
          -
          - -

          Read a GMT file into a list

          - Source: R/utils.R -
          read_gmt.Rd
          -
          - -
          -

          Parses a local GMT file and returns a list of gene sets. Each gene -set is represented as a character vector of unique gene names.

          -
          - -
          -

          Usage

          - 
          read_gmt(filename)
          -
          - -
          -

          Arguments

          - - -
          filename
          -

          A character(1) string giving the path to a .gmt file.

          - -
          -
          -

          Value

          -

          A list where each element is a character vector of gene names, -named by the gene set ID.

          -
          - -
          -

          Examples

          - 
          # Bioconductor requires runnable examples. 
-# We create a dummy GMT file for this example:
-gmt_file <- tempfile(fileext = ".gmt")
-writeLines(
-    c("PATHWAY_A\thttp://link.com\tGENE1\tGENE2\tGENE3",
-      "PATHWAY_B\thttp://link.com\tGENE2\tGENE4"),
-    con = gmt_file
-)
-
-# Run the function
-gs <- read_gmt(gmt_file)
-
-# Inspect results
-length(gs)
-#> [1] 2
-names(gs)
-#> [1] "PATHWAY_A" "PATHWAY_B"
-gs[["PATHWAY_A"]]
-#> [1] "GENE1" "GENE2" "GENE3"
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/ridge_B.html b/docs/reference/ridge_B.html deleted file mode 100644 index 9a0be02..0000000 --- a/docs/reference/ridge_B.html +++ /dev/null @@ -1,108 +0,0 @@ - -Ridge regression update for B — ridge_B • CLAMP - Skip to contents - - -
          -
          -
          - -

          Ridge regression update for B

          - Source: R/solvers.R -
          ridge_B.Rd
          -
          - -
          -

          Solves \(B = (Z^T Z + L2)^{-1} Z^T Y\) with ridge penalty matrix L2.

          -
          - -
          -

          Usage

          - 
          ridge_B(Y, Z, L2k)
          -
          - -
          -

          Arguments

          - - -
          Y
          -

          Gene expression matrix (genes x samples), dense or FBM.

          - - -
          Z
          -

          Latent variable matrix (genes x k).

          - - -
          L2k
          -

          Ridge penalty matrix (k x k).

          - -
          -
          -

          Value

          -

          A numeric matrix of size k x samples.

          -
          - -
          -

          Examples

          - 
          set.seed(123)
-
-genes <- paste0("Gene", 1:50)
-samples <- paste0("S", 1:20)
-k <- 5
-
-Y <- matrix(rnorm(50 * 20), nrow = 50, dimnames = list(genes, samples))
-Z <- matrix(rnorm(50 * k),  nrow = 50, dimnames = list(genes, paste0("LV", 1:k)))
-
-lambda <- 0.1
-L2k <- diag(lambda, k)
-
-# Solve for B = (Z'Z + L2)^(-1) Z'Y
-B <- ridge_B(Y, Z, L2k)
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/rotateSVD.html b/docs/reference/rotateSVD.html deleted file mode 100644 index 895b963..0000000 --- a/docs/reference/rotateSVD.html +++ /dev/null @@ -1,86 +0,0 @@ - -Rotate SVD components to make dominant directions positive — rotateSVD • CLAMP - Skip to contents - - -
          -
          -
          - -

          Rotate SVD components to make dominant directions positive

          - Source: R/solvers.R -
          rotateSVD.Rd
          -
          - -
          -

          Ensures consistency in SVD output by flipping signs so that each left singular vector -has a majority of positive entries.

          -
          - -
          -

          Usage

          - 
          rotateSVD(svdres)
          -
          - -
          -

          Arguments

          - - -
          svdres
          -

          A list as returned by svd(), with components u, d, and v.

          - -
          -
          -

          Value

          -

          A modified svd‐result list where each column of $u has been sign‐flipped -so that its entries sum to a nonnegative value; $v is flipped correspondingly.

          -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/row_cor.html b/docs/reference/row_cor.html deleted file mode 100644 index f685218..0000000 --- a/docs/reference/row_cor.html +++ /dev/null @@ -1,89 +0,0 @@ - -Row-wise correlation between two matrices — row_cor • CLAMP - Skip to contents - - -
          -
          -
          - -

          Row-wise correlation between two matrices

          - Source: R/solvers.R -
          row_cor.Rd
          -
          - -
          -

          Computes the Pearson correlation for each row between matrices -A and B.

          -
          - -
          -

          Usage

          - 
          row_cor(A, B)
          -
          - -
          -

          Arguments

          - - -
          A
          -

          A numeric matrix.

          - - -
          B
          -

          A numeric matrix of the same dimensions as A.

          - -
          -
          -

          Value

          -

          A numeric vector of correlations, one per row.

          -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/run_elbow.html b/docs/reference/run_elbow.html deleted file mode 100644 index 6054173..0000000 --- a/docs/reference/run_elbow.html +++ /dev/null @@ -1,82 +0,0 @@ - -Run elbow method to estimate number of PCs — run_elbow • CLAMP - Skip to contents - - -
          -
          -
          - -

          Run elbow method to estimate number of PCs

          - Source: R/solvers.R -
          run_elbow.Rd
          -
          - -
          -

          Run elbow method to estimate number of PCs

          -
          - -
          -

          Usage

          - 
          run_elbow(d)
          -
          - -
          -

          Arguments

          - - -
          d
          -

          Vector of singular values

          - -
          -
          -

          Value

          -

          Estimated number of PCs via elbow

          -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/run_permutation.html b/docs/reference/run_permutation.html deleted file mode 100644 index e5ddf99..0000000 --- a/docs/reference/run_permutation.html +++ /dev/null @@ -1,90 +0,0 @@ - -Run permutation method to estimate number of PCs — run_permutation • CLAMP - Skip to contents - - -
          -
          -
          - -

          Run permutation method to estimate number of PCs

          - Source: R/solvers.R -
          run_permutation.Rd
          -
          - -
          -

          Run permutation method to estimate number of PCs

          -
          - -
          -

          Usage

          - 
          run_permutation(data, d, B = 20)
          -
          - -
          -

          Arguments

          - - -
          data
          -

          Raw data matrix (row-normalized)

          - - -
          d
          -

          Vector of singular values

          - - -
          B
          -

          Number of permutations

          - -
          -
          -

          Value

          -

          Estimated number of PCs via permutation test

          -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/select_clamp_k.html b/docs/reference/select_clamp_k.html deleted file mode 100644 index 836a7cf..0000000 --- a/docs/reference/select_clamp_k.html +++ /dev/null @@ -1,141 +0,0 @@ - -Select default number of CLAMP latent variables from an SVD — select_clamp_k • CLAMP - Skip to contents - - -
          -
          -
          - -

          Select default number of CLAMP latent variables from an SVD

          - Source: R/utils.R -
          select_clamp_k.Rd
          -
          - -
          -

          Chooses the default clamp_k used by the CLAMP solvers when the user -does not provide one, and returns the scale used for downstream L1/L2 -regularization. Multiple methods are available via method:

          -
          - -
          -

          Usage

          - 
          select_clamp_k(
-  svdres,
-  n_samples,
-  svd_k,
-  method = c("elbow", "permutation", "gavish_donoho", "scaleSVs"),
-  data = NULL,
-  B = 20
-)
          -
          - -
          -

          Arguments

          - - -
          svdres
          -

          An SVD result with a d component (output of compute_svd).

          - - -
          n_samples
          -

          Integer number of samples in the original matrix -(i.e. ncol(Y)). Used by "scaleSVs" and "gavish_donoho".

          - - -
          svd_k
          -

          Integer upper bound on clamp_k (number of components -actually computed in the SVD).

          - - -
          method
          -

          One of "elbow", "permutation", "gavish_donoho", -"scaleSVs". Defaults to "elbow".

          - - -
          data
          -

          Raw data matrix. Required for "permutation" (row-normalized -internally) and "gavish_donoho" (used for n_genes).

          - - -
          B
          -

          Number of permutations for "permutation".

          - -
          -
          -

          Value

          -

          An integer: the selected number of latent variables.

          -
          -
          -

          Details

          - -
          "elbow" (default)
          -

          Elbow heuristic on the singular-value spectrum -via num.pc(svdres, method = "elbow"). scale = svdres$d[clamp_k].

          - -
          "permutation"
          -

          Permutation test via num.pc(data, method = "permutation", B = B). Requires the raw row-normalized data matrix. -scale = svdres$d[clamp_k].

          - -
          "gavish_donoho"
          -

          Gavish-Donoho optimal singular-value threshold -via PCAtools::chooseGavishDonoho(). Requires the raw data matrix -(used for n_genes). scale = svdres$d[clamp_k].

          - -
          "scaleSVs"
          -

          Previous behavior: getScaleFromSVs() linear-tail fit, -clamp_k <- min(floor(k * 1.5), svd_k), scale from the fit.

          - - -
          - -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/select_svd_k.html b/docs/reference/select_svd_k.html deleted file mode 100644 index 6fad621..0000000 --- a/docs/reference/select_svd_k.html +++ /dev/null @@ -1,95 +0,0 @@ - -Select default number of components for a CLAMP solver SVD — select_svd_k • CLAMP - Skip to contents - - -
          -
          -
          - -

          Select default number of components for a CLAMP solver SVD

          - Source: R/utils.R -
          select_svd_k.Rd
          -
          - -
          -

          Returns the default number of components to compute in a truncated SVD -for the given input matrix. Used by the CLAMP solvers when svd_k is -not provided explicitly. Other SVD contexts use their own heuristics.

          -
          - -
          -

          Usage

          - 
          select_svd_k(Y)
          -
          - -
          -

          Arguments

          - - -
          Y
          -

          A matrix-like object (dense matrix, dgCMatrix, or FBM).

          - -
          -
          -

          Value

          -

          An integer: max(2, floor((min(nrow(Y), ncol(Y)) - 1) / 4)).

          -
          - -
          -

          Examples

          - 
          select_svd_k(matrix(0, nrow = 100, ncol = 20))
-#> [1] 4
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/solveU.html b/docs/reference/solveU.html deleted file mode 100644 index fb8eda6..0000000 --- a/docs/reference/solveU.html +++ /dev/null @@ -1,209 +0,0 @@ - -Fit the loading matrix Z using sparse regression of prior information U — solveU • CLAMP - Skip to contents - - -
          -
          -
          - -

          Fit the loading matrix Z using sparse regression of prior information U

          - Source: R/solvers.R -
          solveU.Rd
          -
          - -
          -

          For each column of a target matrix Z using pathway or prior annotation priorMat. -It performs regularization selection using cross-validation and can apply either -Supports continuous or binary response models. Relaxed refitting is supported for final -coefficient estimation.

          -
          - -
          -

          Usage

          - 
          solveU(
-  Z,
-  Chat = NULL,
-  priorMat,
-  penalty.factor,
-  pathwaySelection = "fast",
-  alpha = 0.9,
-  maxPath = 10,
-  nfolds = 5,
-  useSE = FALSE,
-  top = NULL,
-  binary = FALSE,
-  nlambda = 20,
-  scale = TRUE,
-  refit = TRUE,
-  Uprev = NULL,
-  useAUC = TRUE,
-  intercept = TRUE,
-  ...
-)
          -
          - -
          -

          Arguments

          - - -
          Z
          -

          A numeric matrix with features (rows) and samples (columns).

          - - -
          Chat
          -

          (Optional) Precomputed pseudo-inverse of priorMat; if NULL, -it is calculated using ridge regularization.

          - - -
          priorMat
          -

          A numeric matrix with prior information (features x pathways).

          - - -
          penalty.factor
          -

          Optional penalty weights for features in priorMat.

          - - -
          pathwaySelection
          -

          Method to select candidate pathways: "fast" (default) or "complete".

          - - -
          alpha
          -

          Elastic net mixing parameter (0 = ridge, 1 = lasso). Default is 0.9.

          - - -
          maxPath
          -

          Maximum number of pathways/features selected per column. Default is 10.

          - - -
          nfolds
          -

          Number of cross-validation folds. Default is 5.

          - - -
          useSE
          -

          Whether to use the 1-standard-error rule for lambda selection. Default is FALSE.

          - - -
          top
          -

          If set, sets to 0 all but the top entries of Z per column before fitting.

          - - -
          binary
          -

          If TRUE, fits a binomial model (e.g., classification) to Z>0. -Can be used incombination with top. Default is FALSE.

          - - -
          nlambda
          -

          Number of lambda values for glmnet. Default is 20.

          - - -
          scale
          -

          Whether to standardize predictors in glmnet. Default is TRUE.

          - - -
          refit
          -

          Whether to perform relaxed refitting using selected predictors. Default is TRUE.

          - - -
          Uprev
          -

          (Optional) Previous U matrix to reuse. In this mode only the columns of U -that are all zero are estimated. Used internally in CLAMP.

          - - -
          useAUC
          -

          Logical; whether to compute pathway–LV associations using AUC (default TRUE) instead of OLS.

          - - -
          intercept
          -

          Logical; whether to include an intercept term in glmnet models. Default is TRUE.

          - - -
          ...
          -

          Additional arguments passed to glmnet() or cv.glmnet().

          - -
          -
          -

          Value

          -

          A list with one element:

          U
          -

          A matrix of loadings (features x components). -Columns are named LV1, LV2, ...

          - - -
          - -
          -

          Examples

          - 
          set.seed(123)
-genes <- paste0("G", 1:200)
-lvs   <- paste0("LV", 1:4)
-paths <- paste0("Path", 1:60)
-
-Z <- matrix(rnorm(200 * 4), nrow = 200, dimnames = list(genes, lvs))
-
-priorMat <- matrix(rbinom(200 * 60, 1, 0.07),
-                   nrow = 200, dimnames = list(genes, paths))
-
-fit1 <- solveU(
-  Z = Z,
-  priorMat = priorMat,
-  pathwaySelection = "fast",
-  alpha = 0.9,
-  maxPath = 10,
-  nfolds = 5,
-  binary = FALSE,
-  refit = TRUE
-)
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/squashZscore.html b/docs/reference/squashZscore.html deleted file mode 100644 index f5a03c0..0000000 --- a/docs/reference/squashZscore.html +++ /dev/null @@ -1,96 +0,0 @@ - -Squash extreme z-scores — squashZscore • CLAMP - Skip to contents - - -
          -
          -
          - -

          Squash extreme z-scores

          - Source: R/utils.R -
          squashZscore.Rd
          -
          - -
          -

          Squash extreme z-scores

          -
          - -
          -

          Usage

          - 
          squashZscore(zdata, maxScore = 2)
          -
          - -
          -

          Arguments

          - - -
          zdata
          -

          Numeric vector or matrix of z-scores.

          - - -
          maxScore
          -

          Numeric scalar, maximum absolute score (default 2).

          - -
          -
          -

          Value

          -

          A numeric object of same dimensions as zdata, with values -shrunk by a hyperbolic tangent transformation.

          -
          - -
          -

          Examples

          - 
          z <- rnorm(10, 0, 5)
-squashZscore(z)
-#>  [1] -1.9666024  0.1065201 -1.9890084 -1.9821643  1.9995401  1.9182935
-#>  [7] -1.9985126 -1.0657078  0.6332484 -1.2923063
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/tscale.html b/docs/reference/tscale.html deleted file mode 100644 index 87d0486..0000000 --- a/docs/reference/tscale.html +++ /dev/null @@ -1,105 +0,0 @@ - -Row-wise scaling (mean 0, sd 1) — tscale • CLAMP - Skip to contents - - -
          -
          -
          - -

          Row-wise scaling (mean 0, sd 1)

          - Source: R/utils.R -
          tscale.Rd
          -
          - -
          -

          Standardizes each row of a numeric matrix to have mean 0 and -standard deviation 1. Missing values are ignored in the computation -of the mean and standard deviation.

          -
          - -
          -

          Usage

          - 
          tscale(x)
          -
          - -
          -

          Arguments

          - - -
          x
          -

          A numeric matrix. Each row will be scaled independently.

          - -
          -
          -

          Value

          -

          A numeric matrix of the same dimensions as x, where each row -has mean 0 and standard deviation 1 (ignoring NAs). If a row -has zero variance, it is returned unchanged.

          -
          -
          -

          See also

          -

          base::scale()

          -
          - -
          -

          Examples

          - 
          mat <- matrix(seq_len(9), nrow = 3)
-tscale(mat)
-#>           [,1] [,2]     [,3]
-#> [1,] -1.224745    0 1.224745
-#> [2,] -1.224745    0 1.224745
-#> [3,] -1.224745    0 1.224745
-
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/winsor_topk.html b/docs/reference/winsor_topk.html deleted file mode 100644 index dceb703..0000000 --- a/docs/reference/winsor_topk.html +++ /dev/null @@ -1,104 +0,0 @@ - -Winsorize matrix columns by capping the top-k values — winsor_topk • CLAMP - Skip to contents - - -
          -
          -
          - -

          Winsorize matrix columns by capping the top-k values

          - Source: R/solvers.R -
          winsor_topk.Rd
          -
          - -
          -

          For each column, replaces values greater than the k-th largest -entry with that threshold.

          -
          - -
          -

          Usage

          - 
          winsor_topk(M, k)
          -
          - -
          -

          Arguments

          - - -
          M
          -

          A numeric matrix.

          - - -
          k
          -

          Integer; number of top elements to cap. Must be >= 1 and <= nrow(M).

          - -
          -
          -

          Value

          -

          A numeric matrix of the same dimensions as M, winsorized per column.

          -
          - -
          -

          Examples

          - 
          set.seed(123)
-M <- matrix(rnorm(20 * 5, mean = 0, sd = 2), nrow = 20,
-            dimnames = list(paste0("Gene", 1:20), paste0("S", 1:5)))
-
-# Display column maxima before winsorization
-apply(M, 2, max)
-#>       S1       S2       S3       S4       S5 
-#> 3.573826 2.507630 4.337912 4.100169 4.374666 
-
-# Winsorize each column by capping top 3 values
-M_winsor <- winsor_topk(M, k = 3)
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/xCell.html b/docs/reference/xCell.html deleted file mode 100644 index 064807d..0000000 --- a/docs/reference/xCell.html +++ /dev/null @@ -1,90 +0,0 @@ - -xCell cell-signature matrix — xCell • CLAMP - Skip to contents - - -
          -
          -
          - -

          xCell cell-signature matrix

          - Source: R/xCell.R -
          xCell.Rd
          -
          - -
          -

          A numeric matrix of cell-type signatures derived from xCell, -used to represent the transcriptional profiles of distinct immune -and stromal cell populations.

          -
          - -
          -

          Usage

          - 
          data(xCell)
          -
          - -
          -

          Format

          -

          A numeric matrix with G genes (rows) and C cell types (columns). -Row names are gene symbols; column names are xCell cell-type labels.

          -
          -
          -

          Value

          -

          A matrix of xCell-derived reference expression signatures.

          -
          - -
          -

          Examples

          - 
          data(xCell)
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/zscoreCLAMP.html b/docs/reference/zscoreCLAMP.html deleted file mode 100644 index e188722..0000000 --- a/docs/reference/zscoreCLAMP.html +++ /dev/null @@ -1,110 +0,0 @@ - -Z-score a filtered expression matrix for CLAMP — zscoreCLAMP • CLAMP - Skip to contents - - -
          -
          -
          - -

          Z-score a filtered expression matrix for CLAMP

          - Source: R/utils.R -
          zscoreCLAMP.Rd
          -
          - -
          -

          Centers each gene to mean 0 and scales to unit variance.

          -
          - -
          -

          Usage

          - 
          zscoreCLAMP(Y_filtered, rowStats)
          -
          - -
          -

          Arguments

          - - -
          Y_filtered
          -

          Numeric matrix (genes x samples) returned by preprocessCLAMP

          - - -
          rowStats
          -

          Data frame with numeric columns mean and variance, -row-named to match rownames(Y_filtered)

          - -
          -
          -

          Value

          -

          Numeric matrix of the same dimensions as Y_filtered, with each row centered and scaled.

          -
          - -
          -

          Examples

          - 
          # simple 2 genes x 3 samples matrix
-Y <- matrix(
-    c(
-        2, 4, 6, # gene1 counts
-        8, 10, 12 # gene2 counts
-    ),
-    nrow = 2, byrow = TRUE,
-    dimnames = list(c('gene1', 'gene2'), paste0('sample', seq_len(3)))
-)
-
-# compute per‐gene mean and variance
-rowStats <- data.frame(
-    mean = rowMeans(Y),
-    variance = apply(Y, 1, var),
-    row.names = rownames(Y)
-)
-
-# z‐score each row
-Y_z <- zscoreCLAMP(Y, rowStats)
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/zscoreCLAMPFBM.html b/docs/reference/zscoreCLAMPFBM.html deleted file mode 100644 index 127e1b8..0000000 --- a/docs/reference/zscoreCLAMPFBM.html +++ /dev/null @@ -1,109 +0,0 @@ - -Z-score a filtered FBM in-place — zscoreCLAMPFBM • CLAMP - Skip to contents - - -
          -
          -
          - -

          Z-score a filtered FBM in-place

          - Source: R/utils.R -
          zscoreCLAMPFBM.Rd
          -
          - -
          -

          Standardizes each row of an FBM using provided row means and variances.

          -
          - -
          -

          Usage

          - 
          zscoreCLAMPFBM(fbm_filtered, rowStats, chunk_size = 1000, ncores = 1)
          -
          - -
          -

          Arguments

          - - -
          fbm_filtered
          -

          A bigstatsr::FBM produced by preprocessCLAMPFBM().

          - - -
          rowStats
          -

          A list with row_means and row_variances from that FBM.

          - - -
          chunk_size
          -

          Columns per block (default 1000).

          - - -
          ncores
          -

          Integer; number of cores to use for parallel operations (default 1).

          - -
          -
          -

          Value

          -

          A normalized FBM with z-scored rows.

          -
          - -
          -

          Examples

          - 
          library(bigstatsr)
-fbm <- FBM(
-    nrow = 2, ncol = 4,
-    init = matrix(seq_len(8), nrow = 2)
-)
-stats <- list(
-    row_means     = rowMeans(fbm[]),
-    row_variances = apply(fbm[], 1, var)
-)
-zscoreCLAMPFBM(fbm, stats, chunk_size = 2)
-#> Applying Z-score transformation
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.2.0.

          -
          - -
          - - - - - - - diff --git a/docs/reference/zscorePLIER2.html b/docs/reference/zscorePLIER2.html deleted file mode 100644 index 087d2ad..0000000 --- a/docs/reference/zscorePLIER2.html +++ /dev/null @@ -1,103 +0,0 @@ - -Z-score a filtered expression matrix for PLIER2 — zscorePLIER2 • PLIER2 - Skip to contents - - -
          -
          -
          - -

          Z-score a filtered expression matrix for PLIER2

          - Source: R/utils.R -
          zscorePLIER2.Rd
          -
          - -
          -

          Centers each gene to mean 0 and scales to unit variance.

          -
          - -
          -

          Usage

          - 
          zscorePLIER2(Y_filtered, rowStats)
          -
          - -
          -

          Arguments

          - - -
          Y_filtered
          -

          Numeric matrix (genes x samples) returned by preprocessPLIER2

          - - -
          rowStats
          -

          Data frame with numeric columns mean and variance, -row-named to match rownames(Y_filtered)

          - -
          -
          -

          Value

          -

          Numeric matrix of the same dimensions as Y_filtered, with each row centered and scaled.

          -
          - -
          -

          Examples

          - 
          # simple 2 genes x 3 samples matrix
-Y <- matrix(c(
-  2, 4, 6,    # gene1 counts
-  8,10,12     # gene2 counts
-), nrow = 2, byrow = TRUE,
-dimnames = list(c("gene1","gene2"), paste0("sample",1:3)))
-
-# compute per‐gene mean and variance
-rowStats <- data.frame(
-  mean     = rowMeans(Y),
-  variance = apply(Y, 1, var),
-  row.names = rownames(Y)
-)
-
-# z‐score each row
-Y_z <- zscorePLIER2(Y, rowStats)
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.1.3.

          -
          - -
          - - - - - - - diff --git a/docs/reference/zscorePLIER2FBM.html b/docs/reference/zscorePLIER2FBM.html deleted file mode 100644 index 81e9f86..0000000 --- a/docs/reference/zscorePLIER2FBM.html +++ /dev/null @@ -1,95 +0,0 @@ - -Z-score a filtered FBM in-place — zscorePLIER2FBM • PLIER2 - Skip to contents - - -
          -
          -
          - -

          Z-score a filtered FBM in-place

          - Source: R/utils.R -
          zscorePLIER2FBM.Rd
          -
          - -
          -

          Standardizes each row of an FBM using provided row means and variances.

          -
          - -
          -

          Usage

          - 
          zscorePLIER2FBM(fbm_filtered, rowStats, chunk_size = 1000)
          -
          - -
          -

          Arguments

          - - -
          fbm_filtered
          -

          A bigstatsr::FBM produced by preprocessPLIER2FBM().

          - - -
          rowStats
          -

          A list with row_means and row_variances from that FBM.

          - - -
          chunk_size
          -

          Columns per block (default 1000).

          - -
          - -
          -

          Examples

          - 
          library(bigstatsr)
-fbm <- FBM(nrow = 2, ncol = 4,
-           init = matrix(1:8, nrow = 2))
-stats <- list(
-  row_means     = rowMeans(fbm[]),
-  row_variances = apply(fbm[], 1, var)
-)
-zscorePLIER2FBM(fbm, stats, chunk_size = 2)
-#> Applying Z-score transformation
-
          -
          -
          - - -
          -

          Developed by Marc Subirana-Granes, Maria Chikina.

          -
          - -
          -

          Site built with pkgdown 2.1.3.

          -
          - -
          - - - - - - - diff --git a/docs/search.json b/docs/search.json deleted file mode 100644 index 4259cc4..0000000 --- a/docs/search.json +++ /dev/null @@ -1 +0,0 @@ -[{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"PLIER2 package provides two-stage framework extract interpretable latent variables high-dimensional transcriptomic data. combines standard matrix decomposition (PLIERbase) pathway-guided factor refinement (PLIERfull), enabling: Dimensionality reduction gene expression matrices Incorporation prior knowledge (e.g., Gene Ontology MSigDB) Cross-validation select robust latent variables","code":""},{"path":[]},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"quick-start","dir":"Articles","previous_headings":"","what":"Quick Start","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"provide three self-contained examples: Data-frame example (whole blood): small dataset loaded entirely memory. Shows basic preprocessing, z-scoring, running PLIER2 without -disk storage. HDF5 example (Alzheimer’s brain): Demonstrates import expression HDF5 file, create file-backed FBM object, process larger datasets using FBM interface. Table example (pancreatic islets): Illustrates reading tab-delimited count file comparing conditions via B matrix. example follows steps: Load & preprocess data (filter mean/variance, z-score) Prepare pathway annotations via getGMT() construct prior matrix Compute SVD (-memory file-backed) infer model dimension k Run PLIERbase initialize latent variables Run PLIERfull refine pathway priors obtain summary statistics","code":""},{"path":[]},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"load-example-data","dir":"Articles","previous_headings":"Example 1: In-memory data.frame (Whole Blood)","what":"1. Load example data","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"chunk, load whole-blood expression matrix.","code":"data(\"dataWholeBlood\") # expression matrix dim(dataWholeBlood) # genes x samples #> [1] 11530 36 head(dataWholeBlood) # genes x samples #> BD8001 BD8002 BD8003 BD8004 BD8005 BD8006 BD8007 #> GAS6 7.123563 7.846633 8.356313 7.387916 7.859675 7.057541 8.960098 #> MMP14 6.636157 7.523565 7.033673 6.895476 6.860524 7.268107 7.121380 #> MARCKSL1 10.632837 11.208832 10.519870 10.804867 10.940891 10.984602 11.258157 #> SPARC 12.206811 11.462327 12.391210 12.457026 12.036049 12.010138 11.342475 #> CTSD 13.147963 13.218464 12.574546 12.710222 13.151780 13.131948 13.466095 #> EPAS1 7.011590 6.196898 6.621782 7.251964 6.792337 6.813567 6.785256 #> BD8008 BD8009 BD8010 BD8011 BD8012 BD8013 BD8015 #> GAS6 8.120199 7.061915 7.467680 7.593766 7.980510 7.608529 7.524665 #> MMP14 7.196859 6.764261 7.788809 6.925929 6.658480 7.035367 7.105207 #> MARCKSL1 10.943532 11.242130 11.001261 11.094241 10.827391 10.850013 11.201983 #> SPARC 10.979392 12.464739 11.297043 11.613255 12.116145 12.598474 12.364565 #> CTSD 13.326034 12.885950 13.818859 13.065856 12.869455 12.964527 13.407112 #> EPAS1 6.434220 6.310941 5.269084 6.223021 6.383971 5.728530 6.633363 #> BD8017 BD8018 BD8019 BD8020 BD8021 BD8024 BD8025 #> GAS6 7.939325 8.391950 7.950956 7.560154 7.852542 8.388111 8.465422 #> MMP14 6.905814 7.408872 6.958392 7.166190 6.294972 7.360992 7.649716 #> MARCKSL1 11.088379 11.074874 10.699760 10.778236 11.107787 11.249868 11.004432 #> SPARC 11.935750 12.469152 11.950393 11.285404 12.836662 12.553092 11.980064 #> CTSD 13.669278 13.345946 13.097458 12.637596 13.481647 13.920715 13.477684 #> EPAS1 7.215680 6.401987 6.834593 6.820674 6.909808 6.242905 6.770166 #> BD8026 BD8027 BD8028 BD8029 BD8030 BD8031 BD8032 #> GAS6 7.924237 7.438211 7.562134 7.941111 7.476552 7.837566 7.576831 #> MMP14 7.265736 6.875840 7.166484 7.365906 7.163581 7.026309 6.822608 #> MARCKSL1 10.861711 10.859864 10.908438 10.817281 10.879364 10.540350 11.192079 #> SPARC 11.762774 11.171782 12.461855 11.742365 13.040843 10.445423 11.940918 #> CTSD 13.034718 12.819660 12.713603 12.618206 12.903100 12.837019 13.388076 #> EPAS1 6.792149 6.321837 7.195378 6.219153 6.971319 7.149990 6.572446 #> BD8033 BD8034 BD8038 BD8041 BD8042 BD8043 BD8044 #> GAS6 7.589572 7.751689 7.764586 7.526250 7.144113 7.874906 7.362536 #> MMP14 7.197420 7.060375 6.712708 6.758632 6.506008 7.371407 7.299790 #> MARCKSL1 10.913452 10.910316 10.731734 10.960063 10.852984 10.863946 11.093211 #> SPARC 12.454682 11.457722 11.688371 11.563955 12.331355 11.409792 11.690587 #> CTSD 12.851351 12.840063 12.448499 13.271724 12.993058 13.506943 13.312904 #> EPAS1 6.573068 5.614770 7.084063 5.418134 6.325518 6.446405 6.739370 #> BD8045 #> GAS6 8.315021 #> MMP14 7.354577 #> MARCKSL1 11.404975 #> SPARC 12.448106 #> CTSD 14.070121 #> EPAS1 6.382976"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"preprocess-and-z-score","dir":"Articles","previous_headings":"Example 1: In-memory data.frame (Whole Blood)","what":"2. Preprocess and z-score","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"first CPM-normalize data (needed), filter genes mean expression ≥ 0.5 variance ≥ 0.1, apply z-score normalization.","code":"# CPM normalization dataWholeBlood_cpm <- cpmPLIER2(dataWholeBlood) # Filter and compute row statistics prep_wb <- preprocessPLIER2( Y = dataWholeBlood_cpm, mean_cutoff = 0.5, var_cutoff = 0.1 ) # Extract filtered matrix and rowStats wb_Y_filtered <- prep_wb$Y_filtered wb_rowStats <- prep_wb$rowStats # Z-score normalization wb_Y_z <- zscorePLIER2( Y_filtered = wb_Y_filtered, rowStats = wb_rowStats )"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"svd-computation-and-svd-k-estimation","dir":"Articles","previous_headings":"Example 1: In-memory data.frame (Whole Blood)","what":"3. SVD computation and SVD K estimation","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"Compute robust SVD normalized matrix infer optimal number latent variables K.","code":"# Determine SVD k n_genes <- nrow(wb_Y_z) n_samples <- ncol(wb_Y_z) SVD_K_wd <- min(n_genes, n_samples) - 1 message(\"Using SVD K = \", SVD_K_wd) #> Using SVD K = 35 # Compute full SVD set.seed(1) dataWholeBlood.svd <- rsvd(dataWholeBlood, k = SVD_K_wd) wb_svdRes <- rsvd( wb_Y_z, k = SVD_K_wd )"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"estimate-k-for-plier","dir":"Articles","previous_headings":"Example 1: In-memory data.frame (Whole Blood)","what":"4. Estimate K for PLIER","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"Estimate k via permutation/elbow method","code":"PLIER_K_wb <- num.pc(data = wb_Y_z) #> Computing SVD message(\"Inferred PLIER K = \", PLIER_K_wb) #> Inferred PLIER K = 7"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"plierbase-initialization","dir":"Articles","previous_headings":"Example 1: In-memory data.frame (Whole Blood)","what":"5. PLIERbase initialization","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"First, initialize latent variables using PLIERbase, performs matrix factorization without priors.","code":"wb_baseRes <- PLIERbase( Y = wb_Y_z, k = PLIER_K_wb, svdres = wb_svdRes, trace = TRUE ) #> [1] \"L1 is set to 35.1850960521726\" #> [1] \"L2 is set to 105.555288156518\" #> Progress 1 / 200 | Bdiff=0.989469, minCor=0.836236Progress 2 / 200 | Bdiff=0.052510, minCor=0.879655Progress 3 / 200 | Bdiff=0.034136, minCor=0.965308Progress 4 / 200 | Bdiff=0.012213, minCor=0.983941Progress 5 / 200 | Bdiff=0.008224, minCor=0.986452Progress 6 / 200 | Bdiff=0.006309, minCor=0.991228Progress 7 / 200 | Bdiff=0.005007, minCor=0.995006Progress 8 / 200 | Bdiff=0.003955, minCor=0.995989Progress 9 / 200 | Bdiff=0.003114, minCor=0.996716Progress 10 / 200 | Bdiff=0.002442, minCor=0.997527Progress 11 / 200 | Bdiff=0.001926, minCor=0.998223Progress 12 / 200 | Bdiff=0.001540, minCor=0.998621Progress 13 / 200 | Bdiff=0.001235, minCor=0.998694Progress 14 / 200 | Bdiff=0.001003, minCor=0.998740Progress 15 / 200 | Bdiff=0.000830, minCor=0.998774Progress 16 / 200 | Bdiff=0.000696, minCor=0.998815Progress 17 / 200 | Bdiff=0.000592, minCor=0.998878Progress 18 / 200 | Bdiff=0.000507, minCor=0.998969Progress 19 / 200 | Bdiff=0.000437, minCor=0.999068Progress 20 / 200 | Bdiff=0.424997, minCor=0.977772Progress 21 / 200 | Bdiff=0.016381, minCor=0.985713Progress 22 / 200 | Bdiff=0.000696, minCor=0.998830Progress 23 / 200 | Bdiff=0.000304, minCor=0.999697Progress 24 / 200 | Bdiff=0.000166, minCor=0.999519Progress 25 / 200 | Bdiff=0.000101, minCor=0.999750Progress 26 / 200 | Bdiff=0.000042, minCor=0.999888Progress 27 / 200 | Bdiff=0.000029, minCor=0.999900Progress 28 / 200 | Bdiff=0.000035, minCor=0.999915Progress 29 / 200 | Bdiff=0.000034, minCor=0.999852Progress 30 / 200 | Bdiff=0.000048, minCor=0.999806Progress 31 / 200 | Bdiff=0.000060, minCor=0.999723Converged at iteration= 31 | Bdiff=0.000060, tol=0.000500"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"prepare-pathway-priors","dir":"Articles","previous_headings":"Example 1: In-memory data.frame (Whole Blood)","what":"6. Prepare pathway priors","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"Next, build prior matrix curated gene sets compute Chat object PLIERfull.","code":"wb_gmtList <- list( GTEx_Tissues = getGMT(\"https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=GTEx_Tissues_V8_2023\"), BP = getGMT(\"https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=GO_Biological_Process_2025\"), MSigDB = getGMT(\"https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=MSigDB_Hallmark_2020\") ) wb_pathMat <- gmtListToSparseMat(wb_gmtList) wb_matched <- getMatchedPathwayMat(wb_pathMat, rownames(wb_Y_z)) wb_chatObj <- getChat(wb_matched)"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"plierfull","dir":"Articles","previous_headings":"Example 1: In-memory data.frame (Whole Blood)","what":"7. PLIERfull","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"Finally, refine base model integrating pathway priors using PLIERfull, applies cross-validation.","code":"wb_fullRes <- PLIERfull( Y = wb_Y_z, priorMat = as.matrix(wb_matched), svdres = wb_svdRes, plier.base.result = wb_baseRes, Chat = wb_chatObj, k = wb_k_pl, doCrossval = TRUE, trace = TRUE, max.U.updates = 50 ) #> Progress 1 / 350 | Bdiff=0.000122Progress 2 / 350 | Bdiff=0.000124, Number of annotated columns is 5Progress 3 / 350 | Bdiff=0.000215Progress 4 / 350 | Bdiff=0.000451, Number of annotated columns is 5Progress 5 / 350 | Bdiff=0.001116Progress 6 / 350 | Bdiff=0.001548, Number of annotated columns is 5Progress 7 / 350 | Bdiff=0.001944Progress 8 / 350 | Bdiff=0.001782, Number of annotated columns is 5Progress 9 / 350 | Bdiff=0.001599Progress 10 / 350 | Bdiff=0.000867, Number of annotated columns is 5Progress 11 / 350 | Bdiff=0.000513Progress 12 / 350 | Bdiff=0.000284, Number of annotated columns 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minCor=1.000000"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"display-significant-latent-variables","dir":"Articles","previous_headings":"Example 1: In-memory data.frame (Whole Blood)","what":"8. Display significant latent variables","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"whole-blood RNA-Seq, PLIER2 latent variables recapitulate heme metabolism, mitochondrial ATP synthesis coupled electron transport (GO:0042775) oxidative phosphorylation (GO:0006119), pathways essential oxygen delivery energy generation blood. Heme metabolism reflects erythroid lineage activity hemoglobin production red blood cell precursors, mitochondrial ATP synthesis oxidative phosphorylation components capture bioenergetic demands leukocytes platelets immune activation hemostatic processes. “Whole Blood Male 70–79 ” gene set captures transcriptional signatures peripheral blood.","code":"# Display significant latent variables wb_summary_df <- as.data.frame(wb_fullRes$summary) %>% dplyr::filter(FDR < 0.05 & AUC > 0.7) %>% dplyr::arrange(FDR) %>% dplyr::rename(LV='LV index') %>% dplyr::mutate(LV=paste0('LV', LV)) %>% dplyr::select(LV, pathway, FDR, AUC) datatable( wb_summary_df, filter = \"top\", options = list( pageLength = 10, autoWidth = TRUE), rownames = FALSE, class = \"stripe hover compact\") %>% formatSignif(c(\"AUC\", \"FDR\"), 3)"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"example-2-file-backed-matrix-alzheimers-brain","dir":"Articles","previous_headings":"","what":"Example 2: File-Backed Matrix (Alzheimer’s Brain)","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"example uses HDF5 data ARCHS4 resource (Lachmann et al., 2018; DOI: https://doi.org/10.1038/s41467-018-03751-6) focused Alzheimer’s brain samples Neurobiology Disease study (Hoogland et al., 2017; DOI: https://doi.org/10.1016/j.nbd.2017.06.008). demonstrates ‑disk workflow file‑backed FBM handle large‑scale transcriptomic datasets.","code":""},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"cleanup-old-fbm-files","dir":"Articles","previous_headings":"Example 2: File-Backed Matrix (Alzheimer’s Brain)","what":"1. Cleanup old FBM files","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"output_dir <- here(\"output\", \"alzFBM\") fbm_base <- file.path(output_dir, \"FBMalz\") bk_paths <- paste0(fbm_base, c(\".bk\", \".bk_preproc.bk\", \".bk_preproc_filtered.bk\")) file.remove(bk_paths[file.exists(bk_paths)]) #> [1] TRUE TRUE TRUE"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"computing-cpm-on-a-file-backed-matrix-fbm","dir":"Articles","previous_headings":"Example 2: File-Backed Matrix (Alzheimer’s Brain) > 1. Cleanup old FBM files","what":"Computing CPM on a File-Backed Matrix (FBM)","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"file-backed matrices (FBMs), can compute counts-per-million (CPM) -place—without loading entire dataset RAM—using cpmPLIER2FBM() function PLIER2:","code":""},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"load-hdf5-expression","dir":"Articles","previous_headings":"Example 2: File-Backed Matrix (Alzheimer’s Brain)","what":"2. Load HDF5 expression","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"alz_path <- file.path(ext, 'get_started', \"human_gene_v2.5_alz.h5\") h5 <- H5File$new(alz_path, mode = \"r\") expr_mat <- t(h5[[\"data/expression\"]]$read()) genes <- h5[[\"meta/genes/symbol\"]]$read() samples <- h5[[\"meta/samples/geo_accession\"]]$read() h5$close_all() colnames(expr_mat) <- samples rownames(expr_mat) <- genes"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"construct-filebacked-fbm","dir":"Articles","previous_headings":"Example 2: File-Backed Matrix (Alzheimer’s Brain)","what":"3. Construct file‑backed FBM","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"dir.create(output_dir, recursive = TRUE, showWarnings = FALSE) alzFBM <- FBM(nrow = nrow(expr_mat), ncol = ncol(expr_mat), backingfile = fbm_base) blk <- 1000 for(i in seq_len(ceiling(nrow(expr_mat)/blk))){ rows <- ((i-1)*blk+1):min(i*blk, nrow(expr_mat)) alzFBM[rows, ] <- expr_mat[rows, , drop = FALSE] }"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"cpm-preprocess-and-zscore-fbm","dir":"Articles","previous_headings":"Example 2: File-Backed Matrix (Alzheimer’s Brain)","what":"4. CPM, preprocess and z‑score FBM","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"prep_alz <- preprocessPLIER2FBM( fbm = alzFBM, mean_cutoff= 0.5, var_cutoff = 0.1 ) alz_fbm_filt <- prep_alz$fbm_filtered alz_rowStats <- prep_alz$rowStats zscorePLIER2FBM(alz_fbm_filt, alz_rowStats) alz_genes <- genes[prep_alz$kept_rows]"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"svd-computation-and-svd-k-estimation-1","dir":"Articles","previous_headings":"Example 2: File-Backed Matrix (Alzheimer’s Brain)","what":"5. SVD computation and SVD K estimation","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"g_fb <- nrow(alz_fbm_filt) samples_fb <- ncol(alz_fbm_filt) SVD_K_alz <- min(g_fb, samples_fb) - 1 message(\"Using SVD K = \", SVD_K_alz) #> Using SVD K = 53 set.seed(1) alz_svdRes <- big_randomSVD(alz_fbm_filt, k = SVD_K_alz)"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"estimate-k-for-plier-1","dir":"Articles","previous_headings":"Example 2: File-Backed Matrix (Alzheimer’s Brain)","what":"6. Estimate K for PLIER","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"PLIER_K_alz <- num.pc(list(d = alz_svdRes$d)) message(\"Inferred PLIER K = \", PLIER_K_alz) #> Inferred PLIER K = 17"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"plierbase-initialization-1","dir":"Articles","previous_headings":"Example 2: File-Backed Matrix (Alzheimer’s Brain)","what":"7. PLIERbase initialization","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"alz_baseRes <- PLIERbase( Y = alz_fbm_filt, k = PLIER_K_alz, svdres = alz_svdRes, trace = TRUE ) #> [1] \"L1 is set to 44.9829536996458\" #> [1] \"L2 is set to 134.948861098937\" #> Progress 1 / 200 | Bdiff=1.826270, minCor=0.856822Progress 2 / 200 | Bdiff=0.038443, minCor=0.965096Progress 3 / 200 | Bdiff=0.006582, minCor=0.964510Progress 4 / 200 | Bdiff=0.002720, minCor=0.973542Progress 5 / 200 | Bdiff=0.001726, minCor=0.985099Progress 6 / 200 | Bdiff=0.001193, minCor=0.992761Progress 7 / 200 | Bdiff=0.000901, minCor=0.996114Progress 8 / 200 | Bdiff=0.000737, minCor=0.997516Progress 9 / 200 | Bdiff=0.000625, minCor=0.998218Progress 10 / 200 | Bdiff=0.000539, minCor=0.998625Progress 11 / 200 | Bdiff=0.000467, minCor=0.998893Progress 12 / 200 | Bdiff=0.000407, minCor=0.999096Progress 13 / 200 | Bdiff=0.000356, minCor=0.999256Progress 14 / 200 | Bdiff=0.000312, minCor=0.999381Progress 15 / 200 | Bdiff=0.000276, minCor=0.999484Progress 16 / 200 | Bdiff=0.000246, minCor=0.999568Progress 17 / 200 | Bdiff=0.000221, minCor=0.999636Progress 18 / 200 | Bdiff=0.000201, minCor=0.999690Progress 19 / 200 | Bdiff=0.000184, minCor=0.999734Progress 20 / 200 | Bdiff=0.148207, minCor=0.934848Progress 21 / 200 | Bdiff=0.007964, minCor=0.987206Progress 22 / 200 | Bdiff=0.003631, minCor=0.995188Progress 23 / 200 | Bdiff=0.002611, minCor=0.997771Progress 24 / 200 | Bdiff=0.002079, minCor=0.997901Progress 25 / 200 | Bdiff=0.001680, minCor=0.998049Progress 26 / 200 | Bdiff=0.001419, minCor=0.997742Progress 27 / 200 | Bdiff=0.001278, minCor=0.997647Progress 28 / 200 | Bdiff=0.001115, minCor=0.997839Progress 29 / 200 | Bdiff=0.000974, minCor=0.998061Progress 30 / 200 | Bdiff=0.000871, minCor=0.997577Progress 31 / 200 | Bdiff=0.000803, minCor=0.997071Progress 32 / 200 | Bdiff=0.000731, minCor=0.996936Progress 33 / 200 | Bdiff=0.000651, minCor=0.997612Progress 34 / 200 | Bdiff=0.000594, minCor=0.997835Progress 35 / 200 | Bdiff=0.000535, minCor=0.998174Progress 36 / 200 | Bdiff=0.000515, minCor=0.998605Progress 37 / 200 | Bdiff=0.000462, minCor=0.998919Converged at iteration= 37 | Bdiff=0.000462, tol=0.000500"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"prepare-pathway-priors-1","dir":"Articles","previous_headings":"Example 2: File-Backed Matrix (Alzheimer’s Brain)","what":"8. Prepare pathway priors","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"alz_gmtList <- list( GTEx_Tissues = getGMT(\"https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=GTEx_Tissues_V8_2023\"), BP = getGMT(\"https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=GO_Biological_Process_2025\"), MSigDB = getGMT(\"https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=MSigDB_Hallmark_2020\") ) alz_pathMat <- gmtListToSparseMat(alz_gmtList) alz_matched <- getMatchedPathwayMat(alz_pathMat, alz_genes) alz_chatObj <- getChat(alz_matched)"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"plierfull-1","dir":"Articles","previous_headings":"Example 2: File-Backed Matrix (Alzheimer’s Brain)","what":"9. PLIERfull","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"alz_fullRes <- PLIERfull( Y = alz_fbm_filt, priorMat = as.matrix(alz_matched), svdres = alz_svdRes, plier.base.result = alz_baseRes, Chat = alz_chatObj, k = PLIER_K_alz, doCrossval = TRUE, trace = TRUE, max.U.updates = 50 ) #> Progress 1 / 350 | Bdiff=0.000404Progress 2 / 350 | Bdiff=0.000370, Number of annotated columns is 7Progress 3 / 350 | Bdiff=0.000330Progress 4 / 350 | Bdiff=0.000316, Number of annotated columns is 8Progress 5 / 350 | Bdiff=0.000266Progress 6 / 350 | Bdiff=0.000203, Number of annotated columns is 8Progress 7 / 350 | Bdiff=0.000174Progress 8 / 350 | Bdiff=0.000176, Number of annotated columns is 9Progress 9 / 350 | Bdiff=0.000156Progress 10 / 350 | Bdiff=0.000130, Number of annotated columns is 9Progress 11 / 350 | Bdiff=0.000113Progress 12 / 350 | Bdiff=0.000103, Number of annotated columns is 9Progress 13 / 350 | Bdiff=0.000091Progress 14 / 350 | Bdiff=0.000094, Number of annotated columns is 9Progress 15 / 350 | Bdiff=0.000093Progress 16 / 350 | Bdiff=0.000081, Number of annotated columns is 9Progress 17 / 350 | Bdiff=0.000062Progress 18 / 350 | Bdiff=0.000063, Number of annotated columns is 9Progress 19 / 350 | Bdiff=0.000057Progress 20 / 350 | Bdiff=0.000051, Number of annotated columns is 9Progress 21 / 350 | Bdiff=0.000049Progress 22 / 350 | Bdiff=0.000049, Number of annotated columns is 9Progress 23 / 350 | Bdiff=0.000046Progress 24 / 350 | Bdiff=0.000044, Number of annotated columns is 9Progress 25 / 350 | Bdiff=0.000044Progress 26 / 350 | Bdiff=0.000044, Number of annotated columns is 9Progress 27 / 350 | Bdiff=0.000051Progress 28 / 350 | Bdiff=0.000047, Number of annotated columns is 9Progress 29 / 350 | Bdiff=0.000059Progress 30 / 350 | Bdiff=0.000049, Number of annotated columns is 9Progress 31 / 350 | Bdiff=0.000039Progress 32 / 350 | Bdiff=0.000031, Number of annotated columns is 7Progress 33 / 350 | Bdiff=0.000032Progress 34 / 350 | Bdiff=0.000027, Number of annotated columns is 7Progress 35 / 350 | Bdiff=0.000030Progress 36 / 350 | Bdiff=0.000026, Number of annotated columns is 7Progress 37 / 350 | Bdiff=0.000028Progress 38 / 350 | Bdiff=0.000022, Number of annotated columns is 7Progress 39 / 350 | Bdiff=0.000023Progress 40 / 350 | Bdiff=0.000020, Number of annotated columns is 7Progress 41 / 350 | Bdiff=0.000020Progress 42 / 350 | Bdiff=0.000022, Number of annotated columns is 7Progress 43 / 350 | Bdiff=0.000023Progress 44 / 350 | Bdiff=0.000020, Number of annotated columns is 7Progress 45 / 350 | Bdiff=0.000024Progress 46 / 350 | Bdiff=0.000024, Number of annotated columns is 7Progress 47 / 350 | Bdiff=0.000025Progress 48 / 350 | Bdiff=0.000022, Number of annotated columns is 7Progress 49 / 350 | Bdiff=0.000023Progress 50 / 350 | Bdiff=0.000021, Number of annotated columns is 7Progress 51 / 350 | Bdiff=0.000021Progress 52 / 350 | Bdiff=0.000023, Number of annotated columns is 7Progress 53 / 350 | Bdiff=0.000022Progress 54 / 350 | Bdiff=0.000019, Number of annotated columns is 7Progress 55 / 350 | Bdiff=0.000019Progress 56 / 350 | Bdiff=0.000020, Number of annotated columns is 7Progress 57 / 350 | Bdiff=0.000020Progress 58 / 350 | Bdiff=0.000023, Number of annotated columns is 7Progress 59 / 350 | Bdiff=0.000019Progress 60 / 350 | Bdiff=0.000019, Number of annotated columns is 7Progress 61 / 350 | Bdiff=0.000020Progress 62 / 350 | Bdiff=0.000029, Number of annotated columns is 7Progress 63 / 350 | Bdiff=0.000031Progress 64 / 350 | Bdiff=0.000036, Number of annotated columns is 7Progress 65 / 350 | Bdiff=0.000040Progress 66 / 350 | Bdiff=0.000042, Number of annotated columns is 8Progress 67 / 350 | Bdiff=0.000051Progress 68 / 350 | Bdiff=0.000057, Number of annotated columns is 8Progress 69 / 350 | Bdiff=0.000054Progress 70 / 350 | Bdiff=0.000076, Number of annotated columns is 8Progress 71 / 350 | Bdiff=0.000076Progress 72 / 350 | Bdiff=0.000070, Number of annotated columns is 8Progress 73 / 350 | Bdiff=0.000069Progress 74 / 350 | Bdiff=0.000058, Number of annotated columns is 8Progress 75 / 350 | Bdiff=0.000060"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"display-significant-latent-variables-1","dir":"Articles","previous_headings":"Example 2: File-Backed Matrix (Alzheimer’s Brain)","what":"10. Display significant latent variables","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"Alzheimer’s brain dataset, leading latent variable matches GTEx tissue signature “Brain - Spinal Cord (Cervical C-1) Male 50-59 ” confirming tissue specificity neuroanatomical context. Additional enriched processes include: Potassium Ion Transmembrane Transport, emphasizes neuronal excitability ion homeostasis; Aerobic Electron Transport Chain, reflecting mitochondrial function bioenergetics; Regulation Dendrite Development, highlighting synaptic remodeling neural connectivity; Ubiquitin‑Dependent Proteolysis, indicating protein quality control mechanisms relevant neurodegeneration.","code":"alz_summary_df <- as.data.frame(alz_fullRes$summary) %>% filter(FDR < 0.1 & AUC > 0.6) %>% arrange(FDR) %>% dplyr::rename(LV='LV index') %>% dplyr::mutate(LV=paste0('LV', LV)) %>% dplyr::select(LV, pathway, FDR, AUC) datatable( alz_summary_df, filter = \"top\", options = list( pageLength = 10, autoWidth = TRUE), rownames = FALSE, class = \"stripe hover compact\") %>% formatSignif(c(\"AUC\", \"FDR\"), 3)"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"example-3-tab-delimited-count-file-pancreatic-islets","dir":"Articles","previous_headings":"","what":"Example 3: Tab-Delimited Count File (Pancreatic Islets)","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"example, apply ‑memory PLIER2 workflow RNA‑Seq count data GEO accession GSE164416 (Wigger et al. 2021; “Multi‑omics profiling living human pancreatic islet donors reveals heterogeneous beta cell trajectories towards type 2 diabetes”, DOI: 10.1038/s42255-021-00420-9). preprocessing raw counts fitting PLIER2 model, perform differential analysis latent‑variable activities compare non‑diabetic (ND) type 2 diabetic (T2D) samples.","code":""},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"load-count-data-and-map-gene-symbols","dir":"Articles","previous_headings":"Example 3: Tab-Delimited Count File (Pancreatic Islets)","what":"1. Load count data and map gene symbols","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"islet_file <- file.path(ext, 'get_started', \"GSE164416_DP_htseq_counts.txt\") islet_df <- read.table( islet_file, header = TRUE, stringsAsFactors = FALSE ) islet_df$symbol <- mapIds( org.Hs.eg.db, keys = islet_df$ensembl, column = \"SYMBOL\", keytype = \"ENSEMBL\", multiVals = \"first\" ) islet_df <- islet_df[!is.na(islet_df$symbol), ]"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"aggregate-counts-by-gene-symbol","dir":"Articles","previous_headings":"Example 3: Tab-Delimited Count File (Pancreatic Islets)","what":"2. Aggregate counts by gene symbol","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"# Sum counts per symbol setDT(islet_df) num_cols <- names(islet_df)[sapply(islet_df, is.numeric)] expr <- islet_df[, lapply(.SD, sum), by = symbol, .SDcols = num_cols] expr <- as.data.frame(expr) rownames(expr) <- expr$symbol expr$symbol <- NULL expr <- as.matrix(expr)"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"cpm-preprocess-and-z-score","dir":"Articles","previous_headings":"Example 3: Tab-Delimited Count File (Pancreatic Islets)","what":"3. CPM, preprocess and z-score","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"prep_is <- preprocessPLIER2( Y = expr, mean_cutoff = 0.5, var_cutoff = 0.1 ) iso_Yf <- prep_is$Y_filtered iso_rowS <- prep_is$rowStats iso_Yz <- zscorePLIER2(Y_filtered = iso_Yf, rowStats = iso_rowS)"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"svd-computation-and-svd-k-estimation-2","dir":"Articles","previous_headings":"Example 3: Tab-Delimited Count File (Pancreatic Islets)","what":"4. SVD computation and SVD K estimation","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"# Determine SVD k for islet data n_genes_is <- nrow(iso_Yz) n_samples_is <- ncol(iso_Yz) SVD_K_is <- min(n_genes_is, n_samples_is) - 1 message(\"Using SVD K = \", SVD_K_is) #> Using SVD K = 132 # Compute SVD with determined k set.seed(1) islet_svdRes <- rsvd( iso_Yz, k = SVD_K_is )"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"estimate-k-for-plier-2","dir":"Articles","previous_headings":"Example 3: Tab-Delimited Count File (Pancreatic Islets)","what":"5. Estimate K for PLIER","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"PLIER_K_is <- num.pc(data = iso_Yz) #> Computing SVD message(\"Inferred PLIER k = \", PLIER_K_is) #> Inferred PLIER k = 12"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"plierbase-initialization-2","dir":"Articles","previous_headings":"Example 3: Tab-Delimited Count File (Pancreatic Islets)","what":"6. PLIERbase initialization","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"islet_baseRes <- PLIERbase( Y = iso_Yz, k = PLIER_K_is, svdres = islet_svdRes, trace = TRUE ) #> [1] \"L1 is set to 59.5202833395131\" #> [1] \"L2 is set to 178.560850018539\" #> Progress 1 / 200 | Bdiff=0.899016, minCor=0.827195Progress 2 / 200 | Bdiff=0.054323, minCor=0.950241Progress 3 / 200 | Bdiff=0.013808, minCor=0.980810Progress 4 / 200 | Bdiff=0.005630, minCor=0.992471Progress 5 / 200 | Bdiff=0.003207, minCor=0.995029Progress 6 / 200 | Bdiff=0.002163, minCor=0.996054Progress 7 / 200 | Bdiff=0.001561, minCor=0.997162Progress 8 / 200 | Bdiff=0.001162, minCor=0.998162Progress 9 / 200 | Bdiff=0.000888, minCor=0.998926Progress 10 / 200 | Bdiff=0.000700, minCor=0.999246Progress 11 / 200 | Bdiff=0.000574, minCor=0.999388Progress 12 / 200 | Bdiff=0.000489, minCor=0.999497Progress 13 / 200 | Bdiff=0.000432, minCor=0.999538Progress 14 / 200 | Bdiff=0.000395, minCor=0.999534Progress 15 / 200 | Bdiff=0.000371, minCor=0.999526Progress 16 / 200 | Bdiff=0.000356, minCor=0.999520Progress 17 / 200 | Bdiff=0.000349, minCor=0.999517Progress 18 / 200 | Bdiff=0.000347, minCor=0.999519Progress 19 / 200 | Bdiff=0.000350, minCor=0.999524Progress 20 / 200 | Bdiff=0.023290, minCor=0.984520Progress 21 / 200 | Bdiff=0.005433, minCor=0.992481Progress 22 / 200 | Bdiff=0.003885, minCor=0.989163Progress 23 / 200 | Bdiff=0.004085, minCor=0.986165Progress 24 / 200 | Bdiff=0.004972, minCor=0.982060Progress 25 / 200 | Bdiff=0.005411, minCor=0.978378Progress 26 / 200 | Bdiff=0.004556, minCor=0.988480Progress 27 / 200 | Bdiff=0.003856, minCor=0.994907Progress 28 / 200 | Bdiff=0.003511, minCor=0.994765Progress 29 / 200 | Bdiff=0.003294, minCor=0.994680Progress 30 / 200 | Bdiff=0.002810, minCor=0.994038Progress 31 / 200 | Bdiff=0.002291, minCor=0.993874Progress 32 / 200 | Bdiff=0.001891, minCor=0.993646Progress 33 / 200 | Bdiff=0.001652, minCor=0.993160Progress 34 / 200 | Bdiff=0.001433, minCor=0.991323Progress 35 / 200 | Bdiff=0.001351, minCor=0.990080Progress 36 / 200 | Bdiff=0.001303, minCor=0.987850Progress 37 / 200 | Bdiff=0.001350, minCor=0.988624Progress 38 / 200 | Bdiff=0.001393, minCor=0.992852Progress 39 / 200 | Bdiff=0.001368, minCor=0.996214Progress 40 / 200 | Bdiff=0.001418, minCor=0.994712Progress 41 / 200 | Bdiff=0.001334, minCor=0.992123Progress 42 / 200 | Bdiff=0.001271, minCor=0.989840Progress 43 / 200 | Bdiff=0.000984, minCor=0.990648Progress 44 / 200 | Bdiff=0.000737, minCor=0.991786Progress 45 / 200 | Bdiff=0.000556, minCor=0.993191Progress 46 / 200 | Bdiff=0.000401, minCor=0.995026Converged at iteration= 46 | Bdiff=0.000401, tol=0.000500"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"prepare-pathway-priors-2","dir":"Articles","previous_headings":"Example 3: Tab-Delimited Count File (Pancreatic Islets)","what":"7. Prepare pathway priors","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"islet_gmtList <- list( GTEx_Tissues = getGMT('https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=GTEx_Tissues_V8_2023'), Diabetes_Perturbations = getGMT('https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=Diabetes_Perturbations_GEO_2022'), MSigDB_Hallmark = getGMT('https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=MSigDB_Hallmark_2020') ) islet_pathMat <- gmtListToSparseMat(islet_gmtList) islet_matched <- getMatchedPathwayMat(islet_pathMat, rownames(iso_Yz)) islet_chatObj <- getChat(islet_matched)"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"plierfull-2","dir":"Articles","previous_headings":"Example 3: Tab-Delimited Count File (Pancreatic Islets)","what":"8. PLIERfull","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"islet_fullRes <- PLIERfull( Y = iso_Yz, priorMat = as.matrix(islet_matched), svdres = islet_svdRes, plier.base.result = islet_baseRes, Chat = islet_chatObj, k = PLIER_K_is, doCrossval = TRUE, trace = TRUE, max.U.updates = 50 ) #> Progress 1 / 350 | Bdiff=0.000287Progress 2 / 350 | Bdiff=0.000216, Number of annotated columns is 11Progress 3 / 350 | Bdiff=0.000195Progress 4 / 350 | Bdiff=0.000190, Number of annotated columns is 11Progress 5 / 350 | Bdiff=0.000215Progress 6 / 350 | Bdiff=0.000236, Number of annotated columns is 11Progress 7 / 350 | Bdiff=0.000262Progress 8 / 350 | Bdiff=0.000301, Number of annotated columns is 11Progress 9 / 350 | Bdiff=0.000303Progress 10 / 350 | Bdiff=0.000329, Number of annotated columns is 11Progress 11 / 350 | Bdiff=0.000343Progress 12 / 350 | Bdiff=0.000364, Number of annotated columns is 10Progress 13 / 350 | Bdiff=0.000346Progress 14 / 350 | Bdiff=0.000339, Number of annotated columns is 10Progress 15 / 350 | Bdiff=0.000325Progress 16 / 350 | Bdiff=0.000296, Number of annotated columns is 11Progress 17 / 350 | Bdiff=0.000255Progress 18 / 350 | Bdiff=0.000227, Number of annotated columns is 11Progress 19 / 350 | Bdiff=0.000205Progress 20 / 350 | Bdiff=0.000202, Number of annotated columns is 11Progress 21 / 350 | Bdiff=0.000210Progress 22 / 350 | Bdiff=0.000228, Number of annotated columns is 11Progress 23 / 350 | Bdiff=0.000238Progress 24 / 350 | Bdiff=0.000257, Number of annotated columns is 11Progress 25 / 350 | Bdiff=0.000295Progress 26 / 350 | Bdiff=0.000355, Number of annotated columns is 11Progress 27 / 350 | Bdiff=0.000378Progress 28 / 350 | Bdiff=0.000484, Number of annotated columns is 11Progress 29 / 350 | Bdiff=0.000939Progress 30 / 350 | Bdiff=0.002325, Number of annotated columns is 11Progress 31 / 350 | Bdiff=0.003087Progress 32 / 350 | Bdiff=0.001321, Number of annotated columns is 11Progress 33 / 350 | Bdiff=0.000632Progress 34 / 350 | Bdiff=0.000423, Number of annotated columns is 11Progress 35 / 350 | Bdiff=0.000294Progress 36 / 350 | Bdiff=0.000201, Number of annotated columns is 11Progress 37 / 350 | Bdiff=0.000141Progress 38 / 350 | Bdiff=0.000094, Number of annotated columns is 11Progress 39 / 350 | Bdiff=0.000070Progress 40 / 350 | Bdiff=0.000047, Number of annotated columns is 12Progress 41 / 350 | Bdiff=0.000037Progress 42 / 350 | Bdiff=0.000027, Number of annotated columns is 12Progress 43 / 350 | Bdiff=0.000021Progress 44 / 350 | Bdiff=0.000015, Number of annotated columns is 12Progress 45 / 350 | Bdiff=0.000012Progress 46 / 350 | Bdiff=0.000009, Number of annotated columns is 12Progress 47 / 350 | Bdiff=0.000007Progress 48 / 350 | Bdiff=0.000006, Number of annotated columns is 12Progress 49 / 350 | Bdiff=0.000005Progress 50 / 350 | Bdiff=0.000004, Number of annotated columns is 12Progress 51 / 350 | Bdiff=0.000004Progress 52 / 350 | Bdiff=0.000003, Number of annotated columns is 12Progress 53 / 350 | Bdiff=0.000003Progress 54 / 350 | Bdiff=0.000003, Number of annotated columns is 12Progress 55 / 350 | Bdiff=0.000002Progress 56 / 350 | Bdiff=0.000002, Number of annotated columns is 12Progress 57 / 350 | Bdiff=0.000002Progress 58 / 350 | Bdiff=0.000002, Number of annotated columns is 12Progress 59 / 350 | Bdiff=0.000001Progress 60 / 350 | Bdiff=0.000001, Number of annotated columns is 12Progress 61 / 350 | Bdiff=0.000001Progress 62 / 350 | Bdiff=0.000001, Number of annotated columns is 12Progress 63 / 350 | Bdiff=0.000001Progress 64 / 350 | Bdiff=0.000001, Number of annotated columns is 12Progress 65 / 350 | Bdiff=0.000001Progress 66 / 350 | Bdiff=0.000001, Number of annotated columns is 12Progress 67 / 350 | Bdiff=0.000001Progress 68 / 350 | Bdiff=0.000000, Number of annotated columns is 12Progress 69 / 350 | Bdiff=0.000001Progress 70 / 350 | Bdiff=0.000000, Number of annotated columns is 12Progress 71 / 350 | Bdiff=0.000001Progress 72 / 350 | Bdiff=0.000000, Number of annotated columns is 12Progress 73 / 350 | Bdiff=0.000001Progress 74 / 350 | Bdiff=0.000001, Number of annotated columns is 12Progress 75 / 350 | Bdiff=0.000000Progress 76 / 350 | Bdiff=0.000000, Number of annotated columns is 12Progress 77 / 350 | Bdiff=0.000000Progress 78 / 350 | Bdiff=0.000000, Number of annotated columns is 12Progress 79 / 350 | Bdiff=0.000000Progress 80 / 350 | Bdiff=0.000000, Number of annotated columns is 12Progress 81 / 350 | Bdiff=0.000000Progress 82 / 350 | Bdiff=0.000000, Number of annotated columns is 12Progress 83 / 350 | Bdiff=0.000000Progress 84 / 350 | Bdiff=0.000000, Number of annotated columns is 12Progress 85 / 350 | Bdiff=0.000000Progress 86 / 350 | Bdiff=0.000000, Number of annotated columns is 12Progress 87 / 350 | Bdiff=0.000000Progress 88 / 350 | Bdiff=0.000000, Number of annotated columns is 12Progress 89 / 350 | Bdiff=0.000000Progress 90 / 350 | Bdiff=0.000000, Number of annotated columns is 12Progress 91 / 350 | Bdiff=0.000000Progress 92 / 350 | Bdiff=0.000000, Number of annotated columns is 12Progress 93 / 350 | Bdiff=0.000000Progress 94 / 350 | Bdiff=0.000000, Number of annotated columns is 12Progress 95 / 350 | Bdiff=0.000000Progress 96 / 350 | Bdiff=0.000000, Number of annotated columns is 12Progress 97 / 350 | Bdiff=0.000000Progress 98 / 350 | Bdiff=0.000000, Number of annotated columns is 12Progress 99 / 350 | Bdiff=0.000000Progress 100 / 350 | Bdiff=0.000000, Number of annotated columns is 12Progress 101 / 350 | Bdiff=0.000000Progress 102 / 350 | Bdiff=0.000000Progress 103 / 350 | Bdiff=0.000000Progress 104 / 350 | Bdiff=0.000000Progress 105 / 350 | Bdiff=0.000000Progress 106 / 350 | Bdiff=0.000000Progress 107 / 350 | Bdiff=0.000000Progress 108 / 350 | Bdiff=0.000000Converged at 108 / 350 | Bdiff=0.000000, minCor=0.999997"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"display-significant-latent-variables-2","dir":"Articles","previous_headings":"Example 3: Tab-Delimited Count File (Pancreatic Islets)","what":"9. Display significant latent variables","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"pancreatic islet RNA‑Seq, PLIER2 latent variables robustly capture islet-specific endocrine metabolic programs. top latent variable aligns GTEx “Pancreas Female 30-39 ” signature, confirming tissue specificity. Enrichment Myc Targets V1 TNF‑α Signaling via NF‑κB reflects proliferative inflammatory pathways active islets. Protein Secretion Oxidative Phosphorylation underline secretory mitochondrial metabolic functions. diabetic islet gene sets (GSE41203 NonObeseDiab Islets DN, GSE94846 PAX8-Overexpression Islet ) highlight pathological developmental perturbations associated diabetes.","code":"islet_summary_df <- as.data.frame(islet_fullRes$summary) %>% filter(FDR < 0.05 & AUC > 0.7) %>% arrange(FDR) %>% dplyr::rename(LV='LV index') %>% dplyr::mutate(LV=paste0('LV', LV)) %>% dplyr::select(LV, pathway, FDR, AUC) datatable( islet_summary_df, filter = \"top\", options = list( pageLength = 10, autoWidth = TRUE), rownames = FALSE, class = \"stripe hover compact\") %>% formatSignif(c(\"AUC\", \"FDR\"), 3)"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"differential-latent-variable-expression-between-conditions","dir":"Articles","previous_headings":"Example 3: Tab-Delimited Count File (Pancreatic Islets)","what":"10. Differential latent-variable expression between conditions","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"Rows B matrix correspond LVs columns samples. grouping samples condition (ND vs T2D), compute average LV expression per group identify LVs differ healthy diabetic islets Differential latent-variable expression highlights diabetes-related inflammation pancreatic specificity. LV8 enriched TNF‑α signaling via NF‑κB cytokine-response pathways, reflecting inflammatory β‑cell stress. LV3, associated adipose CBP‑KO islet gene sets, suggests metabolic adaptation disease. LV2 captures changes α‑ versus β‑cell composition. Enrichment pancreas-specific GTEx signatures (e.g., “Pancreas Female 30–39 ”) confirms tissue relevance latent variables.","code":"B_df <- as.data.frame(as.matrix(islet_fullRes$B)) %>% dplyr::mutate(LV = rownames(.)) islet_meta <- file.path(ext, 'get_started', \"islets_metadata.csv\") iselt_metadata <- read.csv(islet_meta, header = TRUE) sample_types <- iselt_metadata %>% dplyr::mutate( id = as.character(id), type = as.character(type) ) sample_cols <- setdiff(colnames(B_df), \"LV\") nd_cols <- intersect(sample_cols, sample_types$id[sample_types$type == \"ND\"]) other_cols <- intersect(sample_cols, sample_types$id[sample_types$type != \"ND\"]) if (length(nd_cols) == 0 || length(other_cols) == 0) { stop(\"No matching ND or non-ND sample columns found\") } lv_stats_all_vs_nd <- B_df %>% dplyr::rowwise() %>% dplyr::mutate( Mean_ND = mean(dplyr::c_across(dplyr::all_of(nd_cols))), Mean_All = mean(dplyr::c_across(dplyr::all_of(other_cols))), Mean_Diff = Mean_All - Mean_ND, P_Value = stats::wilcox.test( dplyr::c_across(dplyr::all_of(nd_cols)), dplyr::c_across(dplyr::all_of(other_cols)) )$p.value ) %>% dplyr::ungroup() %>% dplyr::mutate(FDR = stats::p.adjust(P_Value, method = \"fdr\")) %>% dplyr::select(LV, Mean_ND, Mean_All, Mean_Diff, P_Value, FDR) %>% dplyr::arrange(FDR) sig_lv_all_vs_nd <- lv_stats_all_vs_nd %>% dplyr::filter(FDR < 0.05) sig_pathway <- islet_summary_df %>% dplyr::filter(FDR<0.05 & AUC > 0.7) %>% dplyr::filter(LV %in% sig_lv_all_vs_nd$LV) %>% dplyr::arrange(FDR) %>% dplyr::select(LV, pathway, FDR, AUC) datatable( sig_pathway, filter = \"top\", options = list( pageLength = 10, autoWidth = TRUE), rownames = FALSE, class = \"stripe hover compact\" ) %>% formatSignif(c(\"AUC\", \"FDR\"), 3)"},{"path":"https://mchikina.github.io/PLIER2/articles/get_started.html","id":"session-information","dir":"Articles","previous_headings":"","what":"Session Information","title":"Analyzing human whole blood RNA-Seq data with PLIER2","text":"","code":"sessionInfo() #> R version 4.3.3 (2024-02-29) #> Platform: x86_64-conda-linux-gnu (64-bit) #> Running under: Pop!_OS 22.04 LTS #> #> Matrix products: default #> BLAS/LAPACK: /home/msubirana/miniconda3/envs/plier2/lib/libopenblasp-r0.3.29.so; LAPACK version 3.12.0 #> #> locale: #> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C #> [3] LC_TIME=es_ES.UTF-8 LC_COLLATE=en_US.UTF-8 #> [5] LC_MONETARY=es_ES.UTF-8 LC_MESSAGES=en_US.UTF-8 #> [7] LC_PAPER=es_ES.UTF-8 LC_NAME=C #> [9] LC_ADDRESS=C LC_TELEPHONE=C #> [11] LC_MEASUREMENT=es_ES.UTF-8 LC_IDENTIFICATION=C #> #> time zone: America/Denver #> tzcode source: system (glibc) #> #> attached base packages: #> [1] stats4 stats graphics grDevices utils datasets methods #> [8] base #> #> other attached packages: #> [1] DiagrammeR_1.0.11 DT_0.33 org.Hs.eg.db_3.18.0 #> [4] AnnotationDbi_1.64.1 IRanges_2.36.0 S4Vectors_0.40.2 #> [7] Biobase_2.62.0 BiocGenerics_0.48.1 here_1.0.1 #> [10] bigstatsr_1.6.1 data.table_1.17.8 hdf5r_1.3.12 #> [13] glmnet_4.1-10 Matrix_1.6-5 rsvd_1.0.5 #> [16] PLIER2_0.0.0.9000 dplyr_1.1.4 BiocStyle_2.30.0 #> #> loaded via a namespace (and not attached): #> [1] DBI_1.2.3 bitops_1.0-9 rlang_1.1.6 #> [4] magrittr_2.0.3 compiler_4.3.3 RSQLite_2.3.9 #> [7] png_0.1-8 systemfonts_1.2.1 vctrs_0.6.5 #> [10] pkgconfig_2.0.3 shape_1.4.6.1 crayon_1.5.3 #> [13] fastmap_1.2.0 XVector_0.42.0 rmarkdown_2.29 #> [16] ps_1.9.1 ragg_1.4.0 bit_4.6.0 #> [19] xfun_0.52 zlibbioc_1.48.0 cachem_1.1.0 #> [22] rmio_0.4.0 GenomeInfoDb_1.38.1 jsonlite_2.0.0 #> [25] blob_1.2.4 irlba_2.3.5.1 parallel_4.3.3 #> [28] R6_2.6.1 bslib_0.9.0 RColorBrewer_1.1-3 #> [31] jquerylib_0.1.4 Rcpp_1.0.14 bookdown_0.36 #> [34] iterators_1.0.14 knitr_1.50 splines_4.3.3 #> [37] tidyselect_1.2.1 rstudioapi_0.17.1 yaml_2.3.10 #> [40] doParallel_1.0.17 codetools_0.2-20 lattice_0.22-7 #> [43] tibble_3.3.0 withr_3.0.2 KEGGREST_1.42.0 #> [46] evaluate_1.0.3 desc_1.4.3 survival_3.8-3 #> [49] Biostrings_2.70.1 pillar_1.10.2 BiocManager_1.30.22 #> [52] foreach_1.5.2 bigassertr_0.1.6 generics_0.1.4 #> [55] rprojroot_2.0.4 RCurl_1.98-1.16 ggplot2_3.4.4 #> [58] scales_1.4.0 ff_4.5.2 glue_1.8.0 #> [61] tools_4.3.3 RSpectra_0.16-2 fs_1.6.6 #> [64] visNetwork_2.1.2 cowplot_1.1.3 grid_4.3.3 #> [67] crosstalk_1.2.1 colorspace_2.1-1 GenomeInfoDbData_1.2.11 #> [70] flock_0.7 cli_3.6.5 rappdirs_0.3.3 #> [73] textshaping_1.0.1 bigparallelr_0.3.2 gtable_0.3.6 #> [76] sass_0.4.10 digest_0.6.37 ggrepel_0.9.6 #> [79] htmlwidgets_1.6.4 farver_2.1.2 memoise_2.0.1 #> [82] htmltools_0.5.8.1 pkgdown_2.1.3 lifecycle_1.0.4 #> [85] httr_1.4.7 bit64_4.6.0-1"},{"path":"https://mchikina.github.io/PLIER2/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Marc Subirana-Granes. Author, maintainer. Maria Chikina. Author.","code":""},{"path":"https://mchikina.github.io/PLIER2/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Subirana-Granes M, Chikina M (2025). PLIER2: Pathway-Level Information ExtractoR Version 2 Gene Expression Analysis. R package version 0.0.0.9000, https://github.com/mchikina/PLIER2, https://mchikina.github.io/PLIER2/.","code":"@Manual{, title = {PLIER2: Pathway-Level Information ExtractoR Version 2 for Gene Expression Analysis}, author = {Marc Subirana-Granes and Maria Chikina}, year = {2025}, note = {R package version 0.0.0.9000, https://github.com/mchikina/PLIER2}, url = {https://mchikina.github.io/PLIER2/}, }"},{"path":[]},{"path":"https://mchikina.github.io/PLIER2/index.html","id":"bioconductor-release-status","dir":"","previous_headings":"","what":"Bioconductor release status","title":"Pathway-Level Information ExtractoR Version 2 for Gene Expression Analysis","text":"goal PLIER2 provide easy--use package extract interpretable latent variables large transcriptomic datasets using biological priors.","code":""},{"path":"https://mchikina.github.io/PLIER2/index.html","id":"local-development-via-conda","dir":"","previous_headings":"","what":"Local development via Conda","title":"Pathway-Level Information ExtractoR Version 2 for Gene Expression Analysis","text":"keep fully specified environment file envs/plier2.yaml. package root, create activate like :","code":"conda env create -f envs/plier2.yaml conda activate plier2 library(remotes) REPO_PATH <- \"~/path/to/PLIER2\" # adjust remotes::install_local( REPO_PATH, force = TRUE, dependencies = FALSE ) library(PLIER2) packageVersion(\"PLIER2\")"},{"path":"https://mchikina.github.io/PLIER2/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Pathway-Level Information ExtractoR Version 2 for Gene Expression Analysis","text":"can install latest release PLIER2 Bioconductor: want test development version, can install github repository: Now can load package using:","code":"if (!requireNamespace(\"BiocManager\", quietly = TRUE)) { install.packages(\"BiocManager\") } BiocManager::install(\"PLIER2\") BiocManager::install(\"mchikina/PLIER2\") library(PLIER2)"},{"path":"https://mchikina.github.io/PLIER2/index.html","id":"basic-usage","dir":"","previous_headings":"","what":"Basic usage","title":"Pathway-Level Information ExtractoR Version 2 for Gene Expression Analysis","text":"detailed instructions use PLIER2, please see vignette.","code":"library(PLIER2) #some example"},{"path":"https://mchikina.github.io/PLIER2/index.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Pathway-Level Information ExtractoR Version 2 for Gene Expression Analysis","text":"Please note PLIER2 project released Contributor Code Conduct. contributing project, agree abide terms.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/AUC.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute AUC using Wilcoxon rank-sum test — AUC","title":"Compute AUC using Wilcoxon rank-sum test — AUC","text":"Computes area ROC curve (AUC) applying Wilcoxon rank-sum test predicted values positive negative labels. equivalent computing Mann-Whitney U statistic.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/AUC.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute AUC using Wilcoxon rank-sum test — AUC","text":"","code":"AUC(labels, values)"},{"path":"https://mchikina.github.io/PLIER2/reference/AUC.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute AUC using Wilcoxon rank-sum test — AUC","text":"labels numeric logical vector indicating class labels. Values > 0 treated positive. values numeric vector prediction scores corresponding labels.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/AUC.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute AUC using Wilcoxon rank-sum test — AUC","text":"list : auc Estimated AUC, 0.5 one class missing pval Wilcoxon test p-value, NA one class missing","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/BH.html","id":null,"dir":"Reference","previous_headings":"","what":"Adjust p-values using Benjamini-Hochberg method — BH","title":"Adjust p-values using Benjamini-Hochberg method — BH","text":"Applies BH (Benjamini-Hochberg) correction multiple hypothesis testing.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/BH.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Adjust p-values using Benjamini-Hochberg method — BH","text":"","code":"BH(p)"},{"path":"https://mchikina.github.io/PLIER2/reference/BH.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Adjust p-values using Benjamini-Hochberg method — BH","text":"p Numeric vector p-values.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/BH.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Adjust p-values using Benjamini-Hochberg method — BH","text":"Adjusted p-values.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/PLIERbase.html","id":null,"dir":"Reference","previous_headings":"","what":"PLIER base matrix factorization — PLIERbase","title":"PLIER base matrix factorization — PLIERbase","text":"Runs core matrix factorization procedure PLIER (Pathway-Level Information ExtractoR), decomposing gene expression matrix Y latent variables Z loadings B. supports sparse, dense, Filebacked Big Matrices (FBM) input includes options adaptive sparsity, positive constraints, regularization.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/PLIERbase.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"PLIER base matrix factorization — PLIERbase","text":"","code":"PLIERbase( Y, k, svdres = NULL, L1 = NULL, L2 = NULL, Zpos = T, max.iter = 200, tol = 5e-04, trace = F, rseed = NULL, B = NULL, scale = 1, pos.adj = 3, adaptive.p = 0.05, adaptive.iter = 20, cutoff = 0 )"},{"path":"https://mchikina.github.io/PLIER2/reference/PLIERbase.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"PLIER base matrix factorization — PLIERbase","text":"Y Input gene expression matrix (genes x samples). Can dense, sparse (dgCMatrix), FBM. k Number latent variables. svdres Optional precomputed SVD result. supplied, computed internally. L1 L1 regularization strength Z. Defaults scaled singular value. L2 L2 regularization strength B. Defaults scaled singular value. Zpos Logical; TRUE, negative entries Z zeroed. Default TRUE. max.iter Maximum number optimization iterations. Default 200. tol Convergence tolerance B update. Default 5e-4. trace Logical; TRUE, prints progress. Default FALSE. rseed Optional integer reproducible random initialization B. B Optional initial matrix B. provided, initialized SVD. scale Scaling factor L1 L2 provided. Default 1. pos.adj Positive constraint adjustment divisor L1. Default 3. adaptive.p Controls adaptive sparsity Z. ALS update, negative entries Z assumed reflect noise. cutoff thresholding set according probability positive values reflected negative distribution—effectively zeroing small positive entries likely noise. Smaller values lead sparsity. Default 0.05. adaptive.iter Number iterations adaptive sparsity applied. Default 20. cutoff Scalar threshold zero Z values Zpos = TRUE adaptive thresholding used. Default 0.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/PLIERbase.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"PLIER base matrix factorization — PLIERbase","text":"list components: B Latent variable loadings (LVs x genes) Z Latent variable scores (LVs x samples) Zraw Raw Z matrix thresholding L1 Final value L1 used L2 Final value L2 used","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/PLIERbase.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"PLIER base matrix factorization — PLIERbase","text":"function low-level implementation PLIER. alternates solving Z given B solving B given Z, optional sparsity non-negativity constraints Z. Convergence assessed via relative change B.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/PLIERbase.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"PLIER base matrix factorization — PLIERbase","text":"","code":"# small toy dataset: 5 genes x 4 samples Y <- matrix(rnorm(5 * 4), nrow = 5, ncol = 4) # run a single iteration for speed res <- PLIERbase(Y, k = 2, max.iter = 1, trace = FALSE) #> **** #> Computing SVD #> [1] \"L1 is set to 0.926903271141505\" #> [1] \"L2 is set to 2.78070981342451\" # inspect dimensions of B and Z dim(res$B) #> [1] 2 4 dim(res$Z) #> [1] 5 2"},{"path":"https://mchikina.github.io/PLIER2/reference/PLIERfull.html","id":null,"dir":"Reference","previous_headings":"","what":"Full PLIER model with prior information and cross-validation — PLIERfull","title":"Full PLIER model with prior information and cross-validation — PLIERfull","text":"Runs full PLIER (Pathway-Level Information ExtractoR) model using gene expression matrix prior pathway annotation matrix. function performs latent variable decomposition guided prior knowledge includes optional cross-validation evaluate pathway associations.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/PLIERfull.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Full PLIER model with prior information and cross-validation — PLIERfull","text":"","code":"PLIERfull( Y, priorMat, svdres = NULL, plier.base.result = NULL, k = NULL, L1 = NULL, L2 = NULL, top = NULL, cvn = 5, max.iter = 350, trace = F, Chat = NULL, maxPath = 10, doCrossval = T, penalty.factor = rep(1, ncol(priorMat)), glm_alpha = 0.9, minGenes = 10, tol = 5e-04, seed = 123456, allGenes = F, rseed = NULL, max.U.updates = 5, pathwaySelection = c(\"fast\"), multiplier = 1, adaptive.p = 0.05, useNNLS = T, useRaw = T, refitAll = F, useSE = F )"},{"path":"https://mchikina.github.io/PLIER2/reference/PLIERfull.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Full PLIER model with prior information and cross-validation — PLIERfull","text":"Y Gene expression matrix (genes x samples). Can dense, sparse (dgCMatrix), FBM. priorMat Binary matrix (genes x pathways) representing prior annotations. svdres Optional SVD result used initialization. plier.base.result Optional result PLIERbase() initialize B. k Number latent variables. NULL, estimated SVD. L1 Regularization strength Z. NULL, initialized SVD plier.base.result. L2 Regularization strength B. NULL, initialized SVD plier.base.result. top set, keeps top-n values per column Z U updates. cvn Number folds cross-validation U updates. Default 5. max.iter Maximum number iterations. Default 350. trace Logical; TRUE, prints iteration progress. Chat Optional precomputed matrix solving U. maxPath Maximum number pathways/features selected per LV. Default 10. doCrossval Whether perform pathway-level cross-validation. Default TRUE. penalty.factor Vector feature-specific penalties glmnet. Default: ones. glm_alpha Elastic net mixing parameter glmnet. Default 0.9. minGenes Minimum number genes per pathway retain. Default 10. tol Convergence tolerance relative change B. Default 5e-4. seed Seed reproducibility cross-validation masking. Default 123456. allGenes TRUE, zero-fills priorMat genes present. Default FALSE. rseed Optional seed randomly reinitializing B Z. max.U.updates Maximum number U updates. Default 5. pathwaySelection Pathway selection mode: \"fast\" \"complete\". multiplier Scaling factor adjusting L1 L2. adaptive.p Quantile threshold adaptively zeroing small Z values. update, adaptive.p-quantile negative entries Z used (flipped positive) threshold small positive values, assuming reflect noise. Default 0.05. useNNLS TRUE, uses non-negative least squares U estimation. Default TRUE. useRaw TRUE, uses unthresholded Z solving U. Default TRUE. refitAll TRUE, refits U columns every update. Default FALSE. useSE Logical; passed internal solveU() call. TRUE, enables standard-error–aware selection fitting U (pathway coefficients). Default FALSE.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/PLIERfull.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Full PLIER model with prior information and cross-validation — PLIERfull","text":"list following components: B Latent variable loadings (LVs x genes) Z Latent variable matrix (LVs x samples) U Pathway loadings matrix (pathways x LVs) C Masked prior matrix used training L1, L2 Regularization parameters heldOutGenes List held-genes per pathway (CV enabled) Uauc AUC matrix CV evaluation (enabled) -log10(p) values CV evaluation (enabled) summary Data frame AUC, p-values, FDR per pathway x LV (enabled) priorMatCV Masked prior matrix used CV priorMat Final filtered prior matrix withPrior Indices LVs non-zero pathway loadings call Function call","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/PLIERfull.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Full PLIER model with prior information and cross-validation — PLIERfull","text":"model alternates solving Z, B, U. Adaptive sparsity applied Z using dynamic threshold based negative tail distribution. Cross-validation used hold gene annotations priorMat evaluate latent variable specificity.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/PLIERfull.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Full PLIER model with prior information and cross-validation — PLIERfull","text":"","code":"mat <- matrix(rnorm(100), 10, 10) svdres <- rsvd::rsvd(mat, k = 5) base <- PLIERbase(Y = mat, k = 5, svdres = svdres, trace = FALSE) #> **** #> [1] \"L1 is set to 0.971985706716372\" #> [1] \"L2 is set to 2.91595712014912\" #> Converged at iteration= 31 | Bdiff=0.000003, tol=0.000500 priorMat <- matrix(1, nrow(mat), 5) full <- PLIERfull(Y = mat, priorMat = priorMat, svdres = svdres, plier.base.result = base, k = 5, doCrossval = FALSE, trace = FALSE, max.U.updates = 0) #> **PLIER v2 ** #> using provided PLIERbase result #> L1=0.971985706716372; L2=2.91595712014912 #> Converged at 8 / 350 | Bdiff=0.000000, minCor=1.000000 #> Not using cross-validation. No AUCs or p-values"},{"path":"https://mchikina.github.io/PLIER2/reference/binarizeTop.html","id":null,"dir":"Reference","previous_headings":"","what":"Binarize matrix by top-k values per column — binarizeTop","title":"Binarize matrix by top-k values per column — binarizeTop","text":"Keeps top top values column matrix, setting others 0.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/binarizeTop.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Binarize matrix by top-k values per column — binarizeTop","text":"","code":"binarizeTop(Z, top, keepVals = T)"},{"path":"https://mchikina.github.io/PLIER2/reference/binarizeTop.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Binarize matrix by top-k values per column — binarizeTop","text":"Z numeric matrix. top Number top entries keep column. keepVals TRUE, retains original values cutoff; otherwise, sets 1.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/binarizeTop.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Binarize matrix by top-k values per column — binarizeTop","text":"modified matrix top entries retained per column.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/cleanFBM.html","id":null,"dir":"Reference","previous_headings":"","what":"Clean a Filebacked Big Matrix (FBM) by log-transforming and handling NAs — cleanFBM","title":"Clean a Filebacked Big Matrix (FBM) by log-transforming and handling NAs — cleanFBM","text":"function inspects FBM determine log-transformation needed (based value range) whether NA values present. maximum value >= 100, applies log2(x + 1) transformation -place. NA values detected, replaced 0.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/cleanFBM.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Clean a Filebacked Big Matrix (FBM) by log-transforming and handling NAs — cleanFBM","text":"","code":"cleanFBM(fbm)"},{"path":"https://mchikina.github.io/PLIER2/reference/cleanFBM.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Clean a Filebacked Big Matrix (FBM) by log-transforming and handling NAs — cleanFBM","text":"fbm bigmemory::FBM bigstatsr::FBM object.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/cleanFBM.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Clean a Filebacked Big Matrix (FBM) by log-transforming and handling NAs — cleanFBM","text":"list : max_value maximum value encountered FBM (log transformation applied). had_na Logical indicating whether NA values found filled.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/cleanFBM.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Clean a Filebacked Big Matrix (FBM) by log-transforming and handling NAs — cleanFBM","text":"Modifies FBM place. Uses bigstatsr::big_apply() process parallel-safe chunks.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/commonRows.html","id":null,"dir":"Reference","previous_headings":"","what":"Find common row names between two matrices or data frames — commonRows","title":"Find common row names between two matrices or data frames — commonRows","text":"Returns intersection row names shared two input objects.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/commonRows.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Find common row names between two matrices or data frames — commonRows","text":"","code":"commonRows(data1, data2)"},{"path":"https://mchikina.github.io/PLIER2/reference/commonRows.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Find common row names between two matrices or data frames — commonRows","text":"data1 matrix, data frame, similar object row names. data2 matrix, data frame, similar object row names.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/commonRows.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Find common row names between two matrices or data frames — commonRows","text":"character vector row names common inputs.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/compareBs.html","id":null,"dir":"Reference","previous_headings":"","what":"Compare latent variable loadings against a target using correlation or other statistics — compareBs","title":"Compare latent variable loadings against a target using correlation or other statistics — compareBs","text":"function compares two sets latent variable loadings (res1, res2) respect binary continuous target matrix. computes maximal association (e.g., correlation, t-statistic, AUC) latent variable column target, returns paired comparison plot summary.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/compareBs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compare latent variable loadings against a target using correlation or other statistics — compareBs","text":"","code":"compareBs( res1, res2, target, method = \"p\", xlab = \"1\", ylab = \"2\", stat.method = \"t\" )"},{"path":"https://mchikina.github.io/PLIER2/reference/computeRowStatsFBM.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute row-wise sum and sum of squares for a Filebacked Big Matrix — computeRowStatsFBM","title":"Compute row-wise sum and sum of squares for a Filebacked Big Matrix — computeRowStatsFBM","text":"Efficiently computes row sums row sum--squares bigstatsr::FBM using column-wise chunking, suitable large datasets loaded fully memory.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/computeRowStatsFBM.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute row-wise sum and sum of squares for a Filebacked Big Matrix — computeRowStatsFBM","text":"","code":"computeRowStatsFBM(fbm, chunk_size = 1000)"},{"path":"https://mchikina.github.io/PLIER2/reference/computeRowStatsFBM.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute row-wise sum and sum of squares for a Filebacked Big Matrix — computeRowStatsFBM","text":"fbm bigstatsr::FBM object. chunk_size Number columns process time. Default 1000.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/computeRowStatsFBM.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute row-wise sum and sum of squares for a Filebacked Big Matrix — computeRowStatsFBM","text":"list two numeric vectors: row_sums Sum row. row_sums_sq Sum squares row.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/cpmPLIER2.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute counts-per-million (CPM) for PLIER2 pipelines — cpmPLIER2","title":"Compute counts-per-million (CPM) for PLIER2 pipelines — cpmPLIER2","text":"Compute counts-per-million (CPM) PLIER2 pipelines","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/cpmPLIER2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute counts-per-million (CPM) for PLIER2 pipelines — cpmPLIER2","text":"","code":"cpmPLIER2(counts)"},{"path":"https://mchikina.github.io/PLIER2/reference/cpmPLIER2.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute counts-per-million (CPM) for PLIER2 pipelines — cpmPLIER2","text":"counts numeric matrix data.frame raw counts (genes x samples).","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/cpmPLIER2.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute counts-per-million (CPM) for PLIER2 pipelines — cpmPLIER2","text":"numeric matrix CPM values (dimensions), ready PLIER2 input.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/cpmPLIER2.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute counts-per-million (CPM) for PLIER2 pipelines — cpmPLIER2","text":"","code":"mat <- matrix(1:12, nrow = 3) cpmPLIER2(mat) #> [,1] [,2] [,3] [,4] #> [1,] 166666.7 266666.7 291666.7 303030.3 #> [2,] 333333.3 333333.3 333333.3 333333.3 #> [3,] 500000.0 400000.0 375000.0 363636.4"},{"path":"https://mchikina.github.io/PLIER2/reference/cpmPLIER2FBM.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute CPM on a file-backed matrix for PLIER2 (in-place) — cpmPLIER2FBM","title":"Compute CPM on a file-backed matrix for PLIER2 (in-place) — cpmPLIER2FBM","text":"Compute CPM file-backed matrix PLIER2 (-place)","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/cpmPLIER2FBM.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute CPM on a file-backed matrix for PLIER2 (in-place) — cpmPLIER2FBM","text":"","code":"cpmPLIER2FBM(fbm_counts, block_size = 1000)"},{"path":"https://mchikina.github.io/PLIER2/reference/cpmPLIER2FBM.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute CPM on a file-backed matrix for PLIER2 (in-place) — cpmPLIER2FBM","text":"fbm_counts bigstatsr::FBM raw counts (genes x samples). block_size Numeric; rows per block (default 1000).","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/cpmPLIER2FBM.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute CPM on a file-backed matrix for PLIER2 (in-place) — cpmPLIER2FBM","text":"Invisibly returns modified FBM (now holding CPM values).","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/cpmPLIER2FBM.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute CPM on a file-backed matrix for PLIER2 (in-place) — cpmPLIER2FBM","text":"","code":"library(bigstatsr) # small 2 genes x 3 samples count matrix mat <- matrix( c(10, 20, 30, 40, 50, 60), nrow = 2, byrow = FALSE, dimnames = list(c(\"gene1\", \"gene2\"), paste0(\"sample\", 1:3)) ) # create an FBM initialized with counts fbm <- FBM(nrow(mat), ncol(mat), init = mat) # convert counts to CPM in-place cpmPLIER2FBM(fbm, block_size = 1)"},{"path":"https://mchikina.github.io/PLIER2/reference/crossVal.html","id":null,"dir":"Reference","previous_headings":"","what":"Cross-validation AUC for PLIER latent variables and pathways — crossVal","title":"Cross-validation AUC for PLIER latent variables and pathways — crossVal","text":"Evaluates well latent variable PLIER model captures held-pathway annotations, using cross-validation prior matrix. latent variable associated pathway, held-genes selected AUC computed using scores plierRes$Z.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/crossVal.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cross-validation AUC for PLIER latent variables and pathways — crossVal","text":"","code":"crossVal(plierRes, priorMat, priorMatcv)"},{"path":"https://mchikina.github.io/PLIER2/reference/crossVal.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cross-validation AUC for PLIER latent variables and pathways — crossVal","text":"plierRes list containing U (loadings) Z (scores) PLIER model. priorMat binary matrix (genes x pathways) indicating original pathway annotations. priorMatcv version priorMat used mask held-annotations cross-validation.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/crossVal.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cross-validation AUC for PLIER latent variables and pathways — crossVal","text":"list : Uauc Matrix AUC values (pathways x LVs) Upval Matrix -log10(p) values (pathways x LVs) summary Data frame pathway, LV index, AUC, p-value, FDR","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/dataWholeBlood.html","id":null,"dir":"Reference","previous_headings":"","what":"Whole-blood reference expression matrix — dataWholeBlood","title":"Whole-blood reference expression matrix — dataWholeBlood","text":"numeric matrix whole-blood gene expression (rows = genes, cols = samples).","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/dataWholeBlood.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Whole-blood reference expression matrix — dataWholeBlood","text":"","code":"data(dataWholeBlood)"},{"path":"https://mchikina.github.io/PLIER2/reference/dataWholeBlood.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Whole-blood reference expression matrix — dataWholeBlood","text":"numeric matrix G genes N samples. Row names gene symbols; column names sample IDs.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/dataWholeBlood.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Whole-blood reference expression matrix — dataWholeBlood","text":"","code":"data(dataWholeBlood) dim(dataWholeBlood) #> [1] 11530 36"},{"path":"https://mchikina.github.io/PLIER2/reference/filterFBM.html","id":null,"dir":"Reference","previous_headings":"","what":"Filter rows of a Filebacked Big Matrix based on mean and variance — filterFBM","title":"Filter rows of a Filebacked Big Matrix based on mean and variance — filterFBM","text":"Filters FBM based row-level mean variance thresholds, returning new FBM selected rows.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/filterFBM.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filter rows of a Filebacked Big Matrix based on mean and variance — filterFBM","text":"","code":"filterFBM( fbm, rowStats, mean_cutoff = NULL, var_cutoff = NULL, backingfile = \"filtered_fbm\" )"},{"path":"https://mchikina.github.io/PLIER2/reference/filterFBM.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filter rows of a Filebacked Big Matrix based on mean and variance — filterFBM","text":"fbm bigstatsr::FBM object. rowStats list numeric vectors row_means row_variances. mean_cutoff Optional minimum mean threshold; rows means removed. var_cutoff Optional minimum variance threshold; rows variances removed. backingfile character string specifying filename (without extension) new FBM. Default filtered_fbm.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/filterFBM.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filter rows of a Filebacked Big Matrix based on mean and variance — filterFBM","text":"list : fbm_filtered new FBM object containing filtered rows. kept_rows Indices rows retained filtering step.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/filterFBM.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Filter rows of a Filebacked Big Matrix based on mean and variance — filterFBM","text":"function creates new FBM copies rows pass filtering criteria. original FBM unchanged.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getAUCstats.html","id":null,"dir":"Reference","previous_headings":"","what":"Count number of latent variables exceeding AUC thresholds — getAUCstats","title":"Count number of latent variables exceeding AUC thresholds — getAUCstats","text":"Given summary data frame cross-validation, reports number latent variables maximum AUC exceeding 0.7, 0.8, 0.9.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getAUCstats.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Count number of latent variables exceeding AUC thresholds — getAUCstats","text":"","code":"getAUCstats(summary)"},{"path":"https://mchikina.github.io/PLIER2/reference/getAUCstats.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Count number of latent variables exceeding AUC thresholds — getAUCstats","text":"summary data frame LV index AUC columns.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getAUCstats.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Count number of latent variables exceeding AUC thresholds — getAUCstats","text":"named numeric vector counts thresholds 0.7, 0.8, 0.9.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getChat.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute Chat matrix from prior annotation — getChat","title":"Compute Chat matrix from prior annotation — getChat","text":"Computes transformation matrix Chat used map observed data latent space, based pseudo-inverse prior annotation matrix. Optionally standardizes columns priorMat computing.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getChat.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute Chat matrix from prior annotation — getChat","text":"","code":"getChat(priorMat, scale = TRUE)"},{"path":"https://mchikina.github.io/PLIER2/reference/getChat.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute Chat matrix from prior annotation — getChat","text":"priorMat numeric sparse matrix (features x pathways) containing prior annotations. scale Logical; TRUE (default), standardizes columns priorMat computing Chat.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getChat.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute Chat matrix from prior annotation — getChat","text":"numeric matrix Chat dimensions (pathways x features).","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getChat.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute Chat matrix from prior annotation — getChat","text":"","code":"# simple toy prior: 3 features x 2 pathways priorMat <- matrix(c(1, 0, 1, 0, 1, 0), nrow = 3, ncol = 2, dimnames = list(paste0(\"gene\", 1:3), paste0(\"path\", 1:2))) # compute Chat (2 pathways x 3 features) Chat <- getChat(priorMat) #> Inverting... #> done"},{"path":"https://mchikina.github.io/PLIER2/reference/getGMT.html","id":null,"dir":"Reference","previous_headings":"","what":"Download and read a GMT file from a URL — getGMT","title":"Download and read a GMT file from a URL — getGMT","text":"Downloads Gene Matrix Transposed (GMT) file specified URL, reads R list, removes temporary file afterward.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getGMT.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Download and read a GMT file from a URL — getGMT","text":"","code":"getGMT(url, name = NULL, cache_dir = NULL, redownload = FALSE)"},{"path":"https://mchikina.github.io/PLIER2/reference/getGMT.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Download and read a GMT file from a URL — getGMT","text":"url character string specifying URL GMT file. name Optional name GMT file (defaults portion last \"=\" URL). cache_dir Optional directory cache/download GMT file. redownload Logical; TRUE, forces re-download even cached.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getGMT.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Download and read a GMT file from a URL — getGMT","text":"named list element character vector gene names given gene set.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getGMT.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Download and read a GMT file from a URL — getGMT","text":"","code":"url <- \"https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=KEGG_2019_Human\" gmt_list <- getGMT(url) #> Auto-detected name: KEGG_2019_Human #> Downloading KEGG_2019_Human from Enrichr... # list available gene sets names(gmt_list) #> [1] \"ABC transporters\" #> [2] \"AGE-RAGE signaling pathway in diabetic complications\" #> [3] \"AMPK signaling pathway\" #> [4] \"Acute myeloid leukemia\" #> [5] \"Adherens junction\" #> [6] \"Adipocytokine signaling pathway\" #> [7] \"Adrenergic signaling in cardiomyocytes\" #> [8] \"African trypanosomiasis\" #> [9] \"Alanine, aspartate and glutamate metabolism\" #> [10] \"Alcoholism\" #> [11] \"Aldosterone synthesis and secretion\" #> [12] \"Aldosterone-regulated sodium reabsorption\" #> [13] \"Allograft rejection\" #> [14] \"Alzheimer disease\" #> [15] \"Amino sugar and nucleotide sugar metabolism\" #> [16] \"Aminoacyl-tRNA biosynthesis\" #> [17] \"Amoebiasis\" #> [18] \"Amphetamine addiction\" #> [19] \"Amyotrophic lateral sclerosis (ALS)\" #> [20] \"Antigen processing and presentation\" #> [21] \"Apelin signaling pathway\" #> [22] \"Apoptosis\" #> [23] \"Arachidonic acid metabolism\" #> [24] \"Arginine and proline metabolism\" #> [25] \"Arginine biosynthesis\" #> [26] \"Arrhythmogenic right ventricular cardiomyopathy (ARVC)\" #> [27] \"Ascorbate and aldarate metabolism\" #> [28] \"Asthma\" #> [29] \"Autoimmune thyroid disease\" #> [30] \"Autophagy\" #> [31] \"Axon guidance\" #> [32] \"B cell receptor signaling pathway\" #> [33] \"Bacterial invasion of epithelial cells\" #> [34] \"Basal cell carcinoma\" #> [35] \"Basal transcription factors\" #> [36] \"Base excision repair\" #> [37] \"Bile secretion\" #> [38] \"Biosynthesis of unsaturated fatty acids\" #> [39] \"Bladder cancer\" #> [40] \"Breast cancer\" #> [41] \"Butanoate metabolism\" #> [42] \"C-type lectin receptor signaling pathway\" #> [43] \"Caffeine metabolism\" #> [44] \"Calcium signaling pathway\" #> [45] \"Carbohydrate digestion and absorption\" #> [46] \"Cardiac muscle contraction\" #> [47] \"Cell adhesion molecules (CAMs)\" #> [48] \"Cell cycle\" #> [49] \"Cellular senescence\" #> [50] \"Central carbon metabolism in cancer\" #> [51] \"Chagas disease (American trypanosomiasis)\" #> [52] \"Chemical carcinogenesis\" #> [53] \"Chemokine signaling pathway\" #> [54] \"Cholesterol metabolism\" #> [55] \"Choline metabolism in cancer\" #> [56] \"Cholinergic synapse\" #> [57] \"Chronic myeloid leukemia\" #> [58] \"Circadian entrainment\" #> [59] \"Circadian rhythm\" #> [60] \"Citrate cycle (TCA cycle)\" #> [61] \"Cocaine addiction\" #> [62] \"Collecting duct acid secretion\" #> [63] \"Colorectal cancer\" #> [64] \"Complement and coagulation cascades\" #> [65] \"Cortisol synthesis and secretion\" #> [66] \"Cushing syndrome\" #> [67] \"Cysteine and methionine metabolism\" #> [68] \"Cytokine-cytokine receptor interaction\" #> [69] \"Cytosolic DNA-sensing pathway\" #> [70] \"D-Glutamine and D-glutamate metabolism\" #> [71] \"DNA replication\" #> [72] \"Dilated cardiomyopathy (DCM)\" #> [73] \"Dopaminergic synapse\" #> [74] \"Drug metabolism\" #> [75] \"ECM-receptor interaction\" #> [76] \"Endocrine and other factor-regulated calcium reabsorption\" #> [77] \"Endocytosis\" #> [78] \"Endometrial cancer\" #> [79] \"Epithelial cell signaling in Helicobacter pylori infection\" #> [80] \"Epstein-Barr virus infection\" #> [81] \"ErbB signaling pathway\" #> [82] \"Estrogen signaling pathway\" #> [83] \"Ether lipid metabolism\" #> [84] \"Fanconi anemia pathway\" #> [85] \"Fat digestion and absorption\" #> [86] \"Fatty acid biosynthesis\" #> [87] \"Fatty acid degradation\" #> [88] \"Fatty acid elongation\" #> [89] \"Fc epsilon RI signaling pathway\" #> [90] \"Fc gamma R-mediated phagocytosis\" #> [91] \"Ferroptosis\" #> [92] \"Fluid shear stress and atherosclerosis\" #> [93] \"Focal adhesion\" #> [94] \"Folate biosynthesis\" #> [95] \"FoxO signaling pathway\" #> [96] \"Fructose and mannose metabolism\" #> [97] \"GABAergic synapse\" #> [98] \"Galactose metabolism\" #> [99] \"Gap junction\" #> [100] \"Gastric acid secretion\" #> [101] \"Gastric cancer\" #> [102] \"Glioma\" #> [103] \"Glucagon signaling pathway\" #> [104] \"Glutamatergic synapse\" #> [105] \"Glutathione metabolism\" #> [106] \"Glycerolipid metabolism\" #> [107] \"Glycerophospholipid metabolism\" #> [108] \"Glycine, serine and threonine metabolism\" #> [109] \"Glycolysis / Gluconeogenesis\" #> [110] \"Glycosaminoglycan biosynthesis\" #> [111] \"Glycosaminoglycan degradation\" #> [112] \"Glycosphingolipid biosynthesis\" #> [113] \"Glycosylphosphatidylinositol (GPI)-anchor biosynthesis\" #> [114] \"Glyoxylate and dicarboxylate metabolism\" #> [115] \"GnRH signaling pathway\" #> [116] \"Graft-versus-host disease\" #> [117] \"HIF-1 signaling pathway\" #> [118] \"Hedgehog signaling pathway\" #> [119] \"Hematopoietic cell lineage\" #> [120] \"Hepatitis B\" #> [121] \"Hepatitis C\" #> [122] \"Hepatocellular carcinoma\" #> [123] \"Herpes simplex virus 1 infection\" #> [124] \"Hippo signaling pathway\" #> [125] \"Histidine metabolism\" #> [126] \"Homologous recombination\" #> [127] \"Human T-cell leukemia virus 1 infection\" #> [128] \"Human cytomegalovirus infection\" #> [129] \"Human immunodeficiency virus 1 infection\" #> [130] \"Human papillomavirus infection\" #> [131] \"Huntington disease\" #> [132] \"Hypertrophic cardiomyopathy (HCM)\" #> [133] \"IL-17 signaling pathway\" #> [134] \"Inflammatory bowel disease (IBD)\" #> [135] \"Inflammatory mediator regulation of TRP channels\" #> [136] \"Influenza A\" #> [137] \"Inositol phosphate metabolism\" #> [138] \"Insulin resistance\" #> [139] \"Insulin secretion\" #> [140] \"Insulin signaling pathway\" #> [141] \"Intestinal immune network for IgA production\" #> [142] \"JAK-STAT signaling pathway\" #> [143] \"Kaposi sarcoma-associated herpesvirus infection\" #> [144] \"Legionellosis\" #> [145] \"Leishmaniasis\" #> [146] \"Leukocyte transendothelial migration\" #> [147] \"Linoleic acid metabolism\" #> [148] \"Long-term depression\" #> [149] \"Long-term potentiation\" #> [150] \"Longevity regulating pathway\" #> [151] \"Lysine degradation\" #> [152] \"Lysosome\" #> [153] \"MAPK signaling pathway\" #> [154] \"Malaria\" #> [155] \"Mannose type O-glycan biosynthesis\" #> [156] \"Maturity onset diabetes of the young\" #> [157] \"Measles\" #> [158] \"Melanogenesis\" #> [159] \"Melanoma\" #> [160] \"Metabolism of xenobiotics by cytochrome P450\" #> [161] \"MicroRNAs in cancer\" #> [162] \"Mineral absorption\" #> [163] \"Mismatch repair\" #> [164] \"Mitophagy\" #> [165] \"Morphine addiction\" #> [166] \"Mucin type O-glycan biosynthesis\" #> [167] \"N-Glycan biosynthesis\" #> [168] \"NF-kappa B signaling pathway\" #> [169] \"NOD-like receptor signaling pathway\" #> [170] \"Natural killer cell mediated cytotoxicity\" #> [171] \"Necroptosis\" #> [172] \"Neomycin, kanamycin and gentamicin biosynthesis\" #> [173] \"Neuroactive ligand-receptor interaction\" #> [174] \"Neurotrophin signaling pathway\" #> [175] \"Nicotinate and nicotinamide metabolism\" #> [176] \"Nicotine addiction\" #> [177] \"Nitrogen metabolism\" #> [178] \"Non-alcoholic fatty liver disease (NAFLD)\" #> [179] \"Non-homologous end-joining\" #> [180] \"Non-small cell lung cancer\" #> [181] \"Notch signaling pathway\" #> [182] \"Nucleotide excision repair\" #> [183] \"Olfactory transduction\" #> [184] \"One carbon pool by folate\" #> [185] \"Oocyte meiosis\" #> [186] \"Osteoclast differentiation\" #> [187] \"Other glycan degradation\" #> [188] \"Other types of O-glycan biosynthesis\" #> [189] \"Ovarian steroidogenesis\" #> [190] \"Oxidative phosphorylation\" #> [191] \"Oxytocin signaling pathway\" #> [192] \"PI3K-Akt signaling pathway\" #> [193] \"PPAR signaling pathway\" #> [194] \"Pancreatic cancer\" #> [195] \"Pancreatic secretion\" #> [196] \"Pantothenate and CoA biosynthesis\" #> [197] \"Parathyroid hormone synthesis, secretion and action\" #> [198] \"Parkinson disease\" #> [199] \"Pathogenic Escherichia coli infection\" #> [200] \"Pathways in cancer\" #> [201] \"Pentose and glucuronate interconversions\" #> [202] \"Pentose phosphate pathway\" #> [203] \"Peroxisome\" #> [204] \"Pertussis\" #> [205] \"Phagosome\" #> [206] \"Phenylalanine metabolism\" #> [207] \"Phenylalanine, tyrosine and tryptophan biosynthesis\" #> [208] \"Phosphatidylinositol signaling system\" #> [209] \"Phospholipase D signaling pathway\" #> [210] \"Phosphonate and phosphinate metabolism\" #> [211] \"Phototransduction\" #> [212] \"Platelet activation\" #> [213] \"Porphyrin and chlorophyll metabolism\" #> [214] \"Primary bile acid biosynthesis\" #> [215] \"Primary immunodeficiency\" #> [216] \"Prion diseases\" #> [217] \"Progesterone-mediated oocyte maturation\" #> [218] \"Prolactin signaling pathway\" #> [219] \"Propanoate metabolism\" #> [220] \"Prostate cancer\" #> [221] \"Proteasome\" #> [222] \"Protein digestion and absorption\" #> [223] \"Protein export\" #> [224] \"Protein processing in endoplasmic reticulum\" #> [225] \"Proteoglycans in cancer\" #> [226] \"Proximal tubule bicarbonate reclamation\" #> [227] \"Purine metabolism\" #> [228] \"Pyrimidine metabolism\" #> [229] \"Pyruvate metabolism\" #> [230] \"RIG-I-like receptor signaling pathway\" #> [231] \"RNA degradation\" #> [232] \"RNA polymerase\" #> [233] \"RNA transport\" #> [234] \"Rap1 signaling pathway\" #> [235] \"Ras signaling pathway\" #> [236] \"Regulation of actin cytoskeleton\" #> [237] \"Regulation of lipolysis in adipocytes\" #> [238] \"Relaxin signaling pathway\" #> [239] \"Renal cell carcinoma\" #> [240] \"Renin secretion\" #> [241] \"Renin-angiotensin system\" #> [242] \"Retinol metabolism\" #> [243] \"Retrograde endocannabinoid signaling\" #> [244] \"Rheumatoid arthritis\" #> [245] \"Riboflavin metabolism\" #> [246] \"Ribosome\" #> [247] \"Ribosome biogenesis in eukaryotes\" #> [248] \"SNARE interactions in vesicular transport\" #> [249] \"Salivary secretion\" #> [250] \"Salmonella infection\" #> [251] \"Selenocompound metabolism\" #> [252] \"Serotonergic synapse\" #> [253] \"Shigellosis\" #> [254] \"Signaling pathways regulating pluripotency of stem cells\" #> [255] \"Small cell lung cancer\" #> [256] \"Sphingolipid metabolism\" #> [257] \"Sphingolipid signaling pathway\" #> [258] \"Spliceosome\" #> [259] \"Staphylococcus aureus infection\" #> [260] \"Starch and sucrose metabolism\" #> [261] \"Steroid biosynthesis\" #> [262] \"Steroid hormone biosynthesis\" #> [263] \"Sulfur metabolism\" #> [264] \"Sulfur relay system\" #> [265] \"Synaptic vesicle cycle\" #> [266] \"Synthesis and degradation of ketone bodies\" #> [267] \"Systemic lupus erythematosus\" #> [268] \"T cell receptor signaling pathway\" #> [269] \"TGF-beta signaling pathway\" #> [270] \"TNF signaling pathway\" #> [271] \"Taste transduction\" #> [272] \"Taurine and hypotaurine metabolism\" #> [273] \"Terpenoid backbone biosynthesis\" #> [274] \"Th1 and Th2 cell differentiation\" #> [275] \"Th17 cell differentiation\" #> [276] \"Thermogenesis\" #> [277] \"Thiamine metabolism\" #> [278] \"Thyroid cancer\" #> [279] \"Thyroid hormone signaling pathway\" #> [280] \"Thyroid hormone synthesis\" #> [281] \"Tight junction\" #> [282] \"Toll-like receptor signaling pathway\" #> [283] \"Toxoplasmosis\" #> [284] \"Transcriptional misregulation in cancer\" #> [285] \"Tryptophan metabolism\" #> [286] \"Tuberculosis\" #> [287] \"Type I diabetes mellitus\" #> [288] \"Type II diabetes mellitus\" #> [289] \"Tyrosine metabolism\" #> [290] \"Ubiquinone and other terpenoid-quinone biosynthesis\" #> [291] \"Ubiquitin mediated proteolysis\" #> [292] \"VEGF signaling pathway\" #> [293] \"Valine, leucine and isoleucine degradation\" #> [294] \"Vascular smooth muscle contraction\" #> [295] \"Vasopressin-regulated water reabsorption\" #> [296] \"Vibrio cholerae infection\" #> [297] \"Viral carcinogenesis\" #> [298] \"Viral myocarditis\" #> [299] \"Vitamin B6 metabolism\" #> [300] \"Vitamin digestion and absorption\" #> [301] \"Wnt signaling pathway\" #> [302] \"alpha-Linolenic acid metabolism\" #> [303] \"beta-Alanine metabolism\" #> [304] \"cAMP signaling pathway\" #> [305] \"cGMP-PKG signaling pathway\" #> [306] \"mRNA surveillance pathway\" #> [307] \"mTOR signaling pathway\" #> [308] \"p53 signaling pathway\" # inspect the first few genes in the first gene set head(gmt_list[[1]]) #> [1] \"ABCA1\" \"ABCA10\" \"ABCA12\" \"ABCA13\" \"ABCA2\" \"ABCA3\""},{"path":"https://mchikina.github.io/PLIER2/reference/getMatchedPathwayMat.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset and filter pathway matrix to match target genes — getMatchedPathwayMat","title":"Subset and filter pathway matrix to match target genes — getMatchedPathwayMat","text":"Filters gene--pathway annotation matrix retain pathways sufficient overlap given gene set. result sparse matrix aligned new.genes, columns (pathways) retained least min.genes matched genes.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getMatchedPathwayMat.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Subset and filter pathway matrix to match target genes — getMatchedPathwayMat","text":"","code":"getMatchedPathwayMat(pathMat, new.genes, min.genes = 10)"},{"path":"https://mchikina.github.io/PLIER2/reference/getMatchedPathwayMat.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Subset and filter pathway matrix to match target genes — getMatchedPathwayMat","text":"pathMat sparse binary matrix genes (rows) x pathways (columns). new.genes Character vector gene names match. min.genes Minimum number overlapping genes required keep pathway.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getMatchedPathwayMat.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Subset and filter pathway matrix to match target genes — getMatchedPathwayMat","text":"sparse matrix dimensions length(new.genes) x filtered pathways.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getMatchedPathwayMat.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Subset and filter pathway matrix to match target genes — getMatchedPathwayMat","text":"","code":"library(Matrix) # create a toy gene-by-pathway sparse matrix genes <- paste0(\"g\", 1:6) pathways <- c(\"Path1\", \"Path2\", \"Path3\") # Path1: g1, g2; Path2: g2, g3, g4; Path3: g5 pathMat <- sparseMatrix( i = c(1, 2, 2, 3, 4, 5), j = c(1, 1, 2, 2, 2, 3), dims = c(length(genes), length(pathways)), dimnames = list(genes, pathways) ) new.genes <- genes filtered <- getMatchedPathwayMat(pathMat, new.genes, min.genes = 2) #> there are 6 genes in the intersection between data and prior #> Removing 1 pathways"},{"path":"https://mchikina.github.io/PLIER2/reference/getMatchedPathwayMat2.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset and filter multiple pathway matrices to match target genes — getMatchedPathwayMat2","title":"Subset and filter multiple pathway matrices to match target genes — getMatchedPathwayMat2","text":"Filters gene--pathway annotation matrices retain pathways sufficient overlap given gene set. result sparse matrix aligned new.genes, combining inputs column-wise.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getMatchedPathwayMat2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Subset and filter multiple pathway matrices to match target genes — getMatchedPathwayMat2","text":"","code":"getMatchedPathwayMat2(..., new.genes, min.genes = 10)"},{"path":"https://mchikina.github.io/PLIER2/reference/getMatchedPathwayMat2.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Subset and filter multiple pathway matrices to match target genes — getMatchedPathwayMat2","text":"... One sparse binary matrices (genes x pathways). new.genes Character vector gene names match. min.genes Minimum number overlapping genes required keep pathway.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getMatchedPathwayMat2.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Subset and filter multiple pathway matrices to match target genes — getMatchedPathwayMat2","text":"sparse matrix rows = new.genes columns = filtered pathways inputs.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getMatchedPathwayMatOld.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset and filter pathway matrix to match target genes — getMatchedPathwayMatOld","title":"Subset and filter pathway matrix to match target genes — getMatchedPathwayMatOld","text":"Filters gene--pathway annotation matrix retain pathways sufficient overlap given gene set. result sparse matrix aligned new.genes, columns (pathways) retained least min.genes matched genes.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getMatchedPathwayMatOld.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Subset and filter pathway matrix to match target genes — getMatchedPathwayMatOld","text":"","code":"getMatchedPathwayMatOld(pathMat, new.genes, min.genes = 10)"},{"path":"https://mchikina.github.io/PLIER2/reference/getMatchedPathwayMatOld.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Subset and filter pathway matrix to match target genes — getMatchedPathwayMatOld","text":"pathMat sparse binary matrix genes (rows) x pathways (columns). new.genes Character vector gene names match. min.genes Minimum number overlapping genes required keep pathway.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getMatchedPathwayMatOld.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Subset and filter pathway matrix to match target genes — getMatchedPathwayMatOld","text":"sparse matrix dimensions length(new.genes) x filtered pathways.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getMaxAUC.html","id":null,"dir":"Reference","previous_headings":"","what":"Get maximum AUC per latent variable — getMaxAUC","title":"Get maximum AUC per latent variable — getMaxAUC","text":"Summarizes cross-validation results data frame extract highest AUC value associated latent variable (LV).","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getMaxAUC.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get maximum AUC per latent variable — getMaxAUC","text":"","code":"getMaxAUC(summary, verbose = F)"},{"path":"https://mchikina.github.io/PLIER2/reference/getMaxAUC.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get maximum AUC per latent variable — getMaxAUC","text":"summary data frame (e.g., crossVal()) . verbose Logical; TRUE, prints counts LVs exceeding AUC thresholds. Default FALSE.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/getMaxAUC.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get maximum AUC per latent variable — getMaxAUC","text":"data frame columns LV index max_AUC.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/gmtListToSparseMat.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert a list of GMT gene sets to a sparse matrix — gmtListToSparseMat","title":"Convert a list of GMT gene sets to a sparse matrix — gmtListToSparseMat","text":"Converts list named gene sets (e.g., getGMT()) sparse binary matrix rows genes, columns gene sets, entries 1 gene set.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/gmtListToSparseMat.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert a list of GMT gene sets to a sparse matrix — gmtListToSparseMat","text":"","code":"gmtListToSparseMat(gmtList)"},{"path":"https://mchikina.github.io/PLIER2/reference/gmtListToSparseMat.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert a list of GMT gene sets to a sparse matrix — gmtListToSparseMat","text":"gmtList nested list gene sets. Outer names gene set names; entry character vector gene names.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/gmtListToSparseMat.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert a list of GMT gene sets to a sparse matrix — gmtListToSparseMat","text":"sparse binary matrix genes rows gene sets columns.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/gmtListToSparseMat.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert a list of GMT gene sets to a sparse matrix — gmtListToSparseMat","text":"","code":"# define a simple nested GMT list gmt1 <- list( PathwayA = c(\"Gene1\", \"Gene2\", \"Gene3\"), PathwayB = c(\"Gene2\", \"Gene4\") ) gmt2 <- list( PathwayC = c(\"Gene1\", \"Gene4\"), PathwayD = c(\"Gene3\", \"Gene5\") ) # combine into a nested list nestedList <- list(gmt1 = gmt1, gmt2 = gmt2) # convert to sparse matrix sparseMat <- gmtListToSparseMat(nestedList)"},{"path":"https://mchikina.github.io/PLIER2/reference/majorCellTypes.html","id":null,"dir":"Reference","previous_headings":"","what":"Major cell-type annotations — majorCellTypes","title":"Major cell-type annotations — majorCellTypes","text":"factor (character) vector annotating samples major cell type.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/majorCellTypes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Major cell-type annotations — majorCellTypes","text":"","code":"data(majorCellTypes)"},{"path":"https://mchikina.github.io/PLIER2/reference/majorCellTypes.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Major cell-type annotations — majorCellTypes","text":"vector length N levels major cell types.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/majorCellTypes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Major cell-type annotations — majorCellTypes","text":"","code":"data(majorCellTypes) table(majorCellTypes) #> majorCellTypes #> 0 0.000105765369795621 0.000122612899191439 #> 4 1 1 #> 0.00012985853973272 0.000177659484016916 0.000238332197541257 #> 1 1 1 #> 0.000376471138793427 0.000494862832122158 0.000494864927428137 #> 1 1 1 #> 0.000502291903643954 0.00054069245039974 0.000545886085765001 #> 1 1 1 #> 0.000549971548662921 0.000641449879422342 0.000675953152668738 #> 1 1 1 #> 0.000702262078040315 0.000741326846197314 0.000746375881741824 #> 1 1 1 #> 0.000773306714491231 0.000870586326880219 0.000917052556589807 #> 1 1 1 #> 0.00095480893553724 0.000957818885441608 0.000985882093160198 #> 1 1 1 #> 0.00102743000560496 0.00105492278812236 0.00112263219468082 #> 1 1 1 #> 0.00114342925983075 0.00115254895545522 0.00117692039388605 #> 1 1 1 #> 0.0012120944305135 0.00124243019446861 0.00130990714043388 #> 1 1 1 #> 0.00131894985940902 0.00132717714829129 0.00133793179188627 #> 1 1 1 #> 0.00136655073781011 0.00137318995192884 0.00151206936867062 #> 1 1 1 #> 0.00151762560809736 0.00154955821539954 0.00155691987673111 #> 1 1 1 #> 0.00157067363635394 0.00157411768848213 0.00159862337652369 #> 1 1 1 #> 0.00170819280307912 0.00172994765429745 0.00173214707373052 #> 1 1 1 #> 0.00179536425158469 0.00202780130848743 0.00203488657340437 #> 1 1 1 #> 0.00212552758209046 0.00214416843009114 0.00215151497545269 #> 1 1 1 #> 0.00221580348569829 0.00226818320428344 0.00230307095705207 #> 1 1 1 #> 0.00235983228798272 0.00240073647306138 0.00246326750895677 #> 1 1 1 #> 0.00249322943931585 0.00322852954573713 0.00324250034642334 #> 1 1 1 #> 0.00325364324887692 0.00333059900003553 0.00396362673722992 #> 1 1 1 #> 0.00410684511622942 0.00462662358940394 0.00503892671962541 #> 1 1 1 #> 0.00660716702079511 0.00678126544352017 0.00705135553756952 #> 1 1 1 #> 0.00746444193317067 0.00790887856008828 0.007951354217682 #> 1 1 1 #> 0.0089679112322994 0.0111325882641665 0.0120130452260658 #> 1 1 1 #> 0.0122026745305073 0.0122708872455085 0.0147574669166135 #> 1 1 1 #> 0.0151460100774276 0.0159351043029258 0.0164852261104477 #> 1 1 1 #> 0.0165292145867056 0.0166458054292616 0.0174432130679779 #> 1 1 1 #> 0.0182705128595183 0.0187046977540723 0.0188454773851996 #> 1 1 1 #> 0.0201652328522884 0.0209924590558711 0.020995521777894 #> 1 1 1 #> 0.0211087347032033 0.0217562719361399 0.0222223654412495 #> 1 1 1 #> 0.0222376510502952 0.022771147375855 0.0236609195724835 #> 1 1 1 #> 0.0237856693512395 0.0253333017918847 0.0254073723639836 #> 1 1 1 #> 0.0258548079219002 0.0265372099844563 0.0276838304781127 #> 1 1 1 #> 0.028788430472311 0.0291309733848241 0.0300228325941474 #> 1 1 1 #> 0.0300470924909941 0.0308959963488399 0.0309058100083575 #> 1 1 1 #> 0.0314266432489231 0.0318832388247426 0.0320806158047142 #> 1 1 1 #> 0.0321847528842324 0.0328858268199437 0.0329988549826105 #> 1 1 1 #> 0.0336048764978144 0.0346496504262183 0.0351746621162736 #> 1 1 1 #> 0.0356612928894657 0.0356791631109175 0.0363269442867693 #> 1 1 1 #> 0.0366893771535486 0.0367083925145423 0.0367791345614977 #> 1 1 1 #> 0.0368067511377948 0.0376767095226475 0.0386166865486607 #> 1 1 1 #> 0.0396696860747854 0.0396712080346672 0.0418863814822862 #> 1 1 1 #> 0.0426614504539814 0.0432595544131667 0.0433170166126472 #> 1 1 1 #> 0.0435568027567474 0.0440185112196576 0.0455665556754027 #> 1 1 1 #> 0.0456493957627785 0.0460083315442969 0.0464233450496097 #> 1 1 1 #> 0.0467292706153105 0.0473824924712588 0.0475426526955602 #> 1 1 1 #> 0.0483728347331001 0.0486153187602815 0.0494971557768832 #> 1 1 1 #> 0.0497445010461789 0.0497652729249145 0.0498822766174345 #> 1 1 1 #> 0.0500532307065373 0.0500777169141008 0.0502458762422268 #> 1 1 1 #> 0.0502978588058034 0.0504339209306009 0.0509804739640531 #> 1 1 1 #> 0.0511875023663284 0.051638825752118 0.0520802298473184 #> 1 1 1 #> 0.0537316758453728 0.0550331804259891 0.0557096541146123 #> 1 1 1 #> 0.055853575396581 0.0560238992004396 0.0566198846740586 #> 1 1 1 #> 0.0566322926643152 0.0569270657786518 0.0571038012211861 #> 1 1 1 #> 0.0572477238496887 0.0572683420923991 0.057536694521674 #> 1 1 1 #> 0.0582176221958244 0.0585384233199263 0.0587219183412854 #> 1 1 1 #> 0.0593080347782031 0.0594551225756461 0.0596412778559891 #> 1 1 1 #> 0.0607141706283606 0.0614276049138102 0.0614957168130644 #> 1 1 1 #> 0.0625691999589033 0.064553864355651 0.0655627038939825 #> 1 1 1 #> 0.0656846230440185 0.0660378681397264 0.0669050313408773 #> 1 1 1 #> 0.0675885264534802 0.06764207751483 0.068302256387837 #> 1 1 1 #> 0.06859084464565 0.0700732088396099 0.0710275186592567 #> 1 1 1 #> 0.0726743927352641 0.0745981933822591 0.0770206944769879 #> 1 1 1 #> 0.0773738446989104 0.0777125576287493 0.0779673446530722 #> 1 1 1 #> 0.0789582584261322 0.0795115834195003 0.0798916855334835 #> 1 1 1 #> 0.0805373707742339 0.0807206986722998 0.0808078448550903 #> 1 1 1 #> 0.0817780402902866 0.0818040679908286 0.0834309978777565 #> 1 1 1 #> 0.0843324039023492 0.0848050519229798 0.0851840565630884 #> 1 1 1 #> 0.0852710703952974 0.0854826054071966 0.0861151237585534 #> 1 1 1 #> 0.086693034239642 0.0867346785649447 0.0878858629185002 #> 1 1 1 #> 0.0890008337061549 0.0921067673636057 0.0960413733216776 #> 1 1 1 #> 0.0984049671520659 0.0998149440280789 0.0999488598980401 #> 1 1 1 #> 0.107312531493488 0.107582383991542 0.109617073955872 #> 1 1 1 #> 0.110834104845153 0.115392142834792 0.117591512638955 #> 1 1 1 #> 0.119201250527891 0.119574463264972 0.123093445451578 #> 1 1 1 #> 0.123130554013802 0.124023246751607 0.132958517836899 #> 1 1 1 #> 0.133452013110658 0.135854672473379 0.136553339787683 #> 1 1 1 #> 0.136873430549405 0.139974585652908 0.141118438179306 #> 1 1 1 #> 0.145561451955543 0.159871036522642 0.347611469753354 #> 1 1 1 #> 0.370001748058735 0.377305658302583 0.383517208929934 #> 1 1 1 #> 0.452374750197911 0.4617595610605 0.472197014117784 #> 1 1 1 #> 0.475628719864581 0.504558277961077 0.514875407324254 #> 1 1 1 #> 0.519170810517727 0.532037210276647 0.532841856975974 #> 1 1 1 #> 0.535906941144982 0.53888103244888 0.542252589317719 #> 1 1 1 #> 0.552598857778372 0.556314561907189 0.564030785542027 #> 1 1 1 #> 0.564041398766562 0.566000358538538 0.590885600588469 #> 1 1 1 #> 0.606618608103979 0.609232216265904 0.612057012547294 #> 1 1 1 #> 0.616762138783159 0.620402553226405 0.633526212120543 #> 1 1 1 #> 0.639956077995846 0.649337545766585 0.657520834580215 #> 1 1 1 #> 0.667431562524401 0.669850627046396 0.716702720203359 #> 1 1 1 #> 0.760443249908856 #> 1"},{"path":"https://mchikina.github.io/PLIER2/reference/mat_mult.html","id":null,"dir":"Reference","previous_headings":"","what":"Matrix multiplication with support for FBM objects — mat_mult","title":"Matrix multiplication with support for FBM objects — mat_mult","text":"Multiplies two matrices, using optimized multiplication first Filebacked Big Matrix (FBM).","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/mat_mult.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Matrix multiplication with support for FBM objects — mat_mult","text":"","code":"mat_mult(mat1, mat2)"},{"path":"https://mchikina.github.io/PLIER2/reference/mat_mult.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Matrix multiplication with support for FBM objects — mat_mult","text":"mat1 matrix object class FBM. mat2 numeric matrix.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/mat_mult.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Matrix multiplication with support for FBM objects — mat_mult","text":"Matrix product mat1 mat2.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/max_correspondence_greedy.html","id":null,"dir":"Reference","previous_headings":"","what":"Greedy maximum correspondence from correlation matrix — max_correspondence_greedy","title":"Greedy maximum correspondence from correlation matrix — max_correspondence_greedy","text":"Finds one--one assignment (permutation) rows columns square correlation matrix maximizes total correlation score, using greedy algorithm.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/max_correspondence_greedy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Greedy maximum correspondence from correlation matrix — max_correspondence_greedy","text":"","code":"max_correspondence_greedy(cor_mat)"},{"path":"https://mchikina.github.io/PLIER2/reference/max_correspondence_greedy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Greedy maximum correspondence from correlation matrix — max_correspondence_greedy","text":"cor_mat square numeric matrix pairwise correlations (rows = items, cols = items).","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/mymessage.html","id":null,"dir":"Reference","previous_headings":"","what":"Print a concatenated message — mymessage","title":"Print a concatenated message — mymessage","text":"Wrapper around message() pastes arguments together single string.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/mymessage.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print a concatenated message — mymessage","text":"","code":"mymessage(...)"},{"path":"https://mchikina.github.io/PLIER2/reference/mymessage.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print a concatenated message — mymessage","text":"... Character strings concatenate print.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/num.pc.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimate number of principal components via elbow or permutation method — num.pc","title":"Estimate number of principal components via elbow or permutation method — num.pc","text":"Estimate number principal components via elbow permutation method","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/num.pc.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimate number of principal components via elbow or permutation method — num.pc","text":"","code":"num.pc(data, method = c(\"elbow\", \"permutation\"), B = 20, seed = NULL)"},{"path":"https://mchikina.github.io/PLIER2/reference/num.pc.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimate number of principal components via elbow or permutation method — num.pc","text":"data Either matrix (e.g. z-scored data) SVD result (list $d). method One \"elbow\" (fast) \"permutation\" (slower). B Number permutations (method = \"permutation\"). seed Seed reproducibility.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/num.pc.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Estimate number of principal components via elbow or permutation method — num.pc","text":"","code":"Estimated number of PCs."},{"path":"https://mchikina.github.io/PLIER2/reference/num.pc.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimate number of principal components via elbow or permutation method — num.pc","text":"","code":"# generate a small random matrix: 5 features x 10 samples mat <- matrix(rnorm(5 * 10), nrow = 5) # fast elbow estimate num.pc(mat, method = \"elbow\") #> Computing SVD #> [1] 2 # slower permutation estimate (use fewer perms for example speed) num.pc(mat, method = \"permutation\", B = 5) #> Computing SVD #> [1] 0"},{"path":"https://mchikina.github.io/PLIER2/reference/pinv.ridge.html","id":null,"dir":"Reference","previous_headings":"","what":"Ridge-regularized pseudoinverse via SVD — pinv.ridge","title":"Ridge-regularized pseudoinverse via SVD — pinv.ridge","text":"Computes stable pseudoinverse symmetric positive semi-definite matrix using singular value decomposition (SVD) ridge regularization. useful matrix ill-conditioned rank-deficient.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/pinv.ridge.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Ridge-regularized pseudoinverse via SVD — pinv.ridge","text":"","code":"pinv.ridge(m, alpha = 0)"},{"path":"https://mchikina.github.io/PLIER2/reference/pinv.ridge.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Ridge-regularized pseudoinverse via SVD — pinv.ridge","text":"m symmetric numeric matrix (e.g., crossprod()). alpha Non-negative scalar specifying ridge penalty. small positive value stabilizes inversion shrinking large singular values.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/pinv.ridge.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Ridge-regularized pseudoinverse via SVD — pinv.ridge","text":"numeric matrix representing ridge-regularized pseudoinverse m.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/preprocessPLIER2.html","id":null,"dir":"Reference","previous_headings":"","what":"Preprocess an expression matrix for PLIER2 — preprocessPLIER2","title":"Preprocess an expression matrix for PLIER2 — preprocessPLIER2","text":"Filters genes mean expression variance, returning filtered matrix per-gene statistics.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/preprocessPLIER2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Preprocess an expression matrix for PLIER2 — preprocessPLIER2","text":"","code":"preprocessPLIER2(Y, mean_cutoff = 0, var_cutoff = 0)"},{"path":"https://mchikina.github.io/PLIER2/reference/preprocessPLIER2.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Preprocess an expression matrix for PLIER2 — preprocessPLIER2","text":"Y Numeric matrix gene expression (rows = genes, cols = samples) mean_cutoff Numeric. Minimum row-mean required keep gene (default 0). var_cutoff Numeric. Minimum row-variance required keep gene (default 0).","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/preprocessPLIER2.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Preprocess an expression matrix for PLIER2 — preprocessPLIER2","text":"list components: Y_filtered: filtered matrix (genes x samples) rowStats: data.frame columns mean variance kept gene kept_rows: integer vector original row indices kept","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/preprocessPLIER2.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Preprocess an expression matrix for PLIER2 — preprocessPLIER2","text":"","code":"# construct a small example matrix mat <- matrix( c(1, 5, 10, 2, 6, 11, 3, 7, 12, 4, 8, 13), nrow = 4, byrow = FALSE, dimnames = list(paste0(\"gene\", 1:4), paste0(\"sample\", 1:3)) ) # keep genes with mean >= 6 and variance >= 2 res <- preprocessPLIER2(mat, mean_cutoff = 6, var_cutoff = 2)"},{"path":"https://mchikina.github.io/PLIER2/reference/preprocessPLIER2FBM.html","id":null,"dir":"Reference","previous_headings":"","what":"Preprocess a bigstatsr FBM for PLIER2 — preprocessPLIER2FBM","title":"Preprocess a bigstatsr FBM for PLIER2 — preprocessPLIER2FBM","text":"Makes writable copy input FBM, cleans (log2 transform needed, fill NAs), filters rows mean/variance, returns filtered FBM plus stats indices.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/preprocessPLIER2FBM.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Preprocess a bigstatsr FBM for PLIER2 — preprocessPLIER2FBM","text":"","code":"preprocessPLIER2FBM( fbm, mean_cutoff = NULL, var_cutoff = NULL, backingfile = NULL )"},{"path":"https://mchikina.github.io/PLIER2/reference/preprocessPLIER2FBM.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Preprocess a bigstatsr FBM for PLIER2 — preprocessPLIER2FBM","text":"fbm bigstatsr::FBM (genes x samples), possibly read-. mean_cutoff Numeric NULL. Minimum row mean keep (NULL = mean filter). var_cutoff Numeric NULL. Minimum row variance keep (NULL = var filter). backingfile Character NULL. Base name copy FBM filtered FBM disk. NULL, defaults paste0(fbm$backingfile, \"_preproc\") \"_filtered\".","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/preprocessPLIER2FBM.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Preprocess a bigstatsr FBM for PLIER2 — preprocessPLIER2FBM","text":"list : fbm_filtered filtered FBM (writable). rowStats List row_means & row_variances fbm_filtered. kept_rows Integer vector original row indices retained.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/preprocessPLIER2FBM.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Preprocess a bigstatsr FBM for PLIER2 — preprocessPLIER2FBM","text":"","code":"library(bigstatsr) # create a toy matrix and back it with an FBM mat <- matrix(c( 1, 2, 3, # geneA 10, 20, 30, # geneB 100,200,300 # geneC ), nrow = 3, byrow = TRUE, dimnames = list(c(\"geneA\",\"geneB\",\"geneC\"), paste0(\"s\", 1:3))) fbm <- FBM(nrow(mat), ncol(mat), init = mat) # preprocess without filtering (all genes kept) res_all <- preprocessPLIER2FBM(fbm) #> Applying log2 transformation #> No NA values found"},{"path":"https://mchikina.github.io/PLIER2/reference/projectPLIER.html","id":null,"dir":"Reference","previous_headings":"","what":"Project new data into PLIER latent space — projectPLIER","title":"Project new data into PLIER latent space — projectPLIER","text":"Computes latent loadings B new gene expression data using latent variables Z fitted PLIER model. allows transfer learned latent structure new datasets matched genes.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/projectPLIER.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Project new data into PLIER latent space — projectPLIER","text":"","code":"projectPLIER(PLIERres, newdata, scale = 1)"},{"path":"https://mchikina.github.io/PLIER2/reference/projectPLIER.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Project new data into PLIER latent space — projectPLIER","text":"PLIERres result object PLIERfull() PLIERbase(), containing least Z L2. newdata gene expression matrix (genes x samples) projected. Must genes (rows) PLIERres$Z. Can standard matrix, sparse matrix, FBM/big.matrix. scale Optional numeric multiplier L2 regularization terms. Default 1.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/projectPLIER.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Project new data into PLIER latent space — projectPLIER","text":"matrix B projected latent loadings (LVs x samples) new dataset.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/projectPLIER.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Project new data into PLIER latent space — projectPLIER","text":"function uses ridge-regularized least squares compute B = solve(ZᵗZ + L2·) · ZᵗY, Z latent matrix trained PLIER model Y new dataset. newdata Filebacked Big Matrix (FBM), computation optimized using bigstatsr::big_cprodMat().","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/projectPLIER.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Project new data into PLIER latent space — projectPLIER","text":"","code":"# fit a tiny PLIER model for projection Y0 <- matrix(rnorm(5*3), nrow = 5) base <- PLIERbase(Y0, k = 2, max.iter = 1, trace = FALSE) #> **** #> Computing SVD #> [1] \"L1 is set to 0.840633045609829\" #> [1] \"L2 is set to 2.52189913682949\" # new data with same 5 genes newY <- matrix(rnorm(5*2), nrow = 5) projB <- projectPLIER(base, newdata = newY) # check dimensions: 2 latent vars x 2 samples dim(projB) #> [1] 2 2"},{"path":"https://mchikina.github.io/PLIER2/reference/read_gmt.html","id":null,"dir":"Reference","previous_headings":"","what":"Read a GMT file into a list — read_gmt","title":"Read a GMT file into a list — read_gmt","text":"Parses local GMT file returns list gene sets, gene set represented character vector unique gene names.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/read_gmt.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read a GMT file into a list — read_gmt","text":"","code":"read_gmt(filename)"},{"path":"https://mchikina.github.io/PLIER2/reference/read_gmt.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read a GMT file into a list — read_gmt","text":"filename character string giving path .gmt file.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/read_gmt.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read a GMT file into a list — read_gmt","text":"named list element character vector gene names.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/rotateSVD.html","id":null,"dir":"Reference","previous_headings":"","what":"Rotate SVD components to make dominant directions positive — rotateSVD","title":"Rotate SVD components to make dominant directions positive — rotateSVD","text":"Ensures consistency SVD output flipping signs left singular vector majority positive entries.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/rotateSVD.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Rotate SVD components to make dominant directions positive — rotateSVD","text":"","code":"rotateSVD(svdres)"},{"path":"https://mchikina.github.io/PLIER2/reference/rotateSVD.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Rotate SVD components to make dominant directions positive — rotateSVD","text":"svdres list returned svd(), components u, d, v.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/rotateSVD.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Rotate SVD components to make dominant directions positive — rotateSVD","text":"modified svd‐result list column $u sign‐flipped entries sum nonnegative value; $v flipped correspondingly.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/row_cor.html","id":null,"dir":"Reference","previous_headings":"","what":"Row-wise correlation between two matrices — row_cor","title":"Row-wise correlation between two matrices — row_cor","text":"Computes Pearson correlation row matrices B.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/row_cor.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Row-wise correlation between two matrices — row_cor","text":"","code":"row_cor(A, B)"},{"path":"https://mchikina.github.io/PLIER2/reference/row_cor.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Row-wise correlation between two matrices — row_cor","text":"numeric matrix. B numeric matrix dimensions .","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/row_cor.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Row-wise correlation between two matrices — row_cor","text":"numeric vector correlations, one per row.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/run_elbow.html","id":null,"dir":"Reference","previous_headings":"","what":"Run elbow method to estimate number of PCs — run_elbow","title":"Run elbow method to estimate number of PCs — run_elbow","text":"Run elbow method estimate number PCs","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/run_elbow.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Run elbow method to estimate number of PCs — run_elbow","text":"","code":"run_elbow(d)"},{"path":"https://mchikina.github.io/PLIER2/reference/run_elbow.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Run elbow method to estimate number of PCs — run_elbow","text":"d Vector singular values","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/run_elbow.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Run elbow method to estimate number of PCs — run_elbow","text":"Estimated number PCs via elbow","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/run_permutation.html","id":null,"dir":"Reference","previous_headings":"","what":"Run permutation method to estimate number of PCs — run_permutation","title":"Run permutation method to estimate number of PCs — run_permutation","text":"Run permutation method estimate number PCs","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/run_permutation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Run permutation method to estimate number of PCs — run_permutation","text":"","code":"run_permutation(data, d, B = 20)"},{"path":"https://mchikina.github.io/PLIER2/reference/run_permutation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Run permutation method to estimate number of PCs — run_permutation","text":"data Raw data matrix (row-normalized) d Vector singular values B Number permutations","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/run_permutation.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Run permutation method to estimate number of PCs — run_permutation","text":"Estimated number PCs via permutation test","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/solveU.html","id":null,"dir":"Reference","previous_headings":"","what":"Fit the loading matrix Z using sparse regression of prior information U — solveU","title":"Fit the loading matrix Z using sparse regression of prior information U — solveU","text":"column target matrix Z using pathway prior annotation priorMat. performs regularization selection using cross-validation can apply either Supports continuous binary response models. Relaxed refitting supported final coefficient estimation.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/solveU.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fit the loading matrix Z using sparse regression of prior information U — solveU","text":"","code":"solveU( Z, Chat = NULL, priorMat, penalty.factor, pathwaySelection = \"fast\", alpha = 0.9, maxPath = 10, nfolds = 5, useSE = F, top = NULL, binary = F, nlambda = 20, scale = T, refit = T, Uprev = NULL, ... )"},{"path":"https://mchikina.github.io/PLIER2/reference/solveU.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fit the loading matrix Z using sparse regression of prior information U — solveU","text":"Z numeric matrix features (rows) samples (columns). Chat (Optional) Precomputed pseudo-inverse priorMat; NULL, calculated using ridge regularization. priorMat numeric matrix prior information (features x pathways). penalty.factor Optional penalty weights features priorMat. pathwaySelection Method select candidate pathways: \"fast\" (default) \"complete\". alpha Elastic net mixing parameter (0 = ridge, 1 = lasso). Default 0.9. maxPath Maximum number pathways/features selected per column. Default 10. nfolds Number cross-validation folds. Default 5. useSE Whether use 1-standard-error rule lambda selection. Default FALSE. top set, sets 0 top entries Z per column fitting. binary TRUE, fits binomial model (e.g., classification) Z>0. Can used incombination top. Default FALSE. nlambda Number lambda values glmnet. Default 20. scale Whether standardize predictors glmnet. Default TRUE. refit Whether perform relaxed refitting using selected predictors. Default TRUE. Uprev (Optional) Previous U matrix reuse. mode columns U zero estimated. Used internally PLIER2. ... Additional arguments passed glmnet() cv.glmnet().","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/solveU.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fit the loading matrix Z using sparse regression of prior information U — solveU","text":"list one element: U matrix loadings (features x components). Columns named LV1, LV2, ...","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/tscale.html","id":null,"dir":"Reference","previous_headings":"","what":"Row-wise scaling (mean 0, sd 1) — tscale","title":"Row-wise scaling (mean 0, sd 1) — tscale","text":"Standardize row numeric matrix mean 0 standard deviation 1.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/tscale.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Row-wise scaling (mean 0, sd 1) — tscale","text":"","code":"tscale(x)"},{"path":"https://mchikina.github.io/PLIER2/reference/tscale.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Row-wise scaling (mean 0, sd 1) — tscale","text":"x numeric matrix.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/tscale.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Row-wise scaling (mean 0, sd 1) — tscale","text":"matrix shape, row scaled independently.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/zscorePLIER2.html","id":null,"dir":"Reference","previous_headings":"","what":"Z-score a filtered expression matrix for PLIER2 — zscorePLIER2","title":"Z-score a filtered expression matrix for PLIER2 — zscorePLIER2","text":"Centers gene mean 0 scales unit variance.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/zscorePLIER2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Z-score a filtered expression matrix for PLIER2 — zscorePLIER2","text":"","code":"zscorePLIER2(Y_filtered, rowStats)"},{"path":"https://mchikina.github.io/PLIER2/reference/zscorePLIER2.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Z-score a filtered expression matrix for PLIER2 — zscorePLIER2","text":"Y_filtered Numeric matrix (genes x samples) returned preprocessPLIER2 rowStats Data frame numeric columns mean variance, row-named match rownames(Y_filtered)","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/zscorePLIER2.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Z-score a filtered expression matrix for PLIER2 — zscorePLIER2","text":"Numeric matrix dimensions Y_filtered, row centered scaled.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/zscorePLIER2.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Z-score a filtered expression matrix for PLIER2 — zscorePLIER2","text":"","code":"# simple 2 genes x 3 samples matrix Y <- matrix(c( 2, 4, 6, # gene1 counts 8,10,12 # gene2 counts ), nrow = 2, byrow = TRUE, dimnames = list(c(\"gene1\",\"gene2\"), paste0(\"sample\",1:3))) # compute per‐gene mean and variance rowStats <- data.frame( mean = rowMeans(Y), variance = apply(Y, 1, var), row.names = rownames(Y) ) # z‐score each row Y_z <- zscorePLIER2(Y, rowStats)"},{"path":"https://mchikina.github.io/PLIER2/reference/zscorePLIER2FBM.html","id":null,"dir":"Reference","previous_headings":"","what":"Z-score a filtered FBM in-place — zscorePLIER2FBM","title":"Z-score a filtered FBM in-place — zscorePLIER2FBM","text":"Standardizes row FBM using provided row means variances.","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/zscorePLIER2FBM.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Z-score a filtered FBM in-place — zscorePLIER2FBM","text":"","code":"zscorePLIER2FBM(fbm_filtered, rowStats, chunk_size = 1000)"},{"path":"https://mchikina.github.io/PLIER2/reference/zscorePLIER2FBM.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Z-score a filtered FBM in-place — zscorePLIER2FBM","text":"fbm_filtered bigstatsr::FBM produced preprocessPLIER2FBM(). rowStats list row_means row_variances FBM. chunk_size Columns per block (default 1000).","code":""},{"path":"https://mchikina.github.io/PLIER2/reference/zscorePLIER2FBM.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Z-score a filtered FBM in-place — zscorePLIER2FBM","text":"","code":"library(bigstatsr) fbm <- FBM(nrow = 2, ncol = 4, init = matrix(1:8, nrow = 2)) stats <- list( row_means = rowMeans(fbm[]), row_variances = apply(fbm[], 1, var) ) zscorePLIER2FBM(fbm, stats, chunk_size = 2) #> Applying Z-score transformation"}] diff --git a/docs/sitemap.xml b/docs/sitemap.xml deleted file mode 100644 index 84db795..0000000 --- a/docs/sitemap.xml +++ /dev/null @@ -1,81 +0,0 @@ - -https://mchikina.github.io/CLAMP/404.html -https://mchikina.github.io/CLAMP/articles/comparing_clampbase_clampfull.html -https://mchikina.github.io/CLAMP/articles/get_started.html -https://mchikina.github.io/CLAMP/articles/index.html -https://mchikina.github.io/CLAMP/authors.html -https://mchikina.github.io/CLAMP/index.html -https://mchikina.github.io/CLAMP/news/index.html -https://mchikina.github.io/CLAMP/reference/AUC.html -https://mchikina.github.io/CLAMP/reference/BH.html -https://mchikina.github.io/CLAMP/reference/CLAMPbase.html -https://mchikina.github.io/CLAMP/reference/CLAMPdotplot.html -https://mchikina.github.io/CLAMP/reference/CLAMPdotplotAll.html -https://mchikina.github.io/CLAMP/reference/CLAMPfull.html -https://mchikina.github.io/CLAMP/reference/CLAMPfullnVP.html -https://mchikina.github.io/CLAMP/reference/CLAMPplotTopZ.html -https://mchikina.github.io/CLAMP/reference/CLAMPplotU.html -https://mchikina.github.io/CLAMP/reference/PLIERbase.html -https://mchikina.github.io/CLAMP/reference/PLIERfull.html -https://mchikina.github.io/CLAMP/reference/allAgainstAllAUCs.html -https://mchikina.github.io/CLAMP/reference/binarizeTop.html -https://mchikina.github.io/CLAMP/reference/celltypeTargets.html -https://mchikina.github.io/CLAMP/reference/cleanFBM.html -https://mchikina.github.io/CLAMP/reference/commonRows.html -https://mchikina.github.io/CLAMP/reference/compareBs.html -https://mchikina.github.io/CLAMP/reference/computeRowStatsFBM.html -https://mchikina.github.io/CLAMP/reference/compute_svd.html -https://mchikina.github.io/CLAMP/reference/cpmCLAMP.html -https://mchikina.github.io/CLAMP/reference/cpmCLAMPFBM.html -https://mchikina.github.io/CLAMP/reference/cpmPLIER2.html -https://mchikina.github.io/CLAMP/reference/cpmPLIER2FBM.html -https://mchikina.github.io/CLAMP/reference/crossVal.html -https://mchikina.github.io/CLAMP/reference/cross_ZY.html -https://mchikina.github.io/CLAMP/reference/dataWholeBlood.html -https://mchikina.github.io/CLAMP/reference/filterFBM.html -https://mchikina.github.io/CLAMP/reference/findSplineMax.html -https://mchikina.github.io/CLAMP/reference/getAUCstats.html -https://mchikina.github.io/CLAMP/reference/getChat.html -https://mchikina.github.io/CLAMP/reference/getGMT.html -https://mchikina.github.io/CLAMP/reference/getMatchedPathwayMat.html -https://mchikina.github.io/CLAMP/reference/getMatchedPathwayMat2.html -https://mchikina.github.io/CLAMP/reference/getMatchedPathwayMatList.html -https://mchikina.github.io/CLAMP/reference/getMatchedPathwayMatOld.html -https://mchikina.github.io/CLAMP/reference/getMaxAUC.html -https://mchikina.github.io/CLAMP/reference/getScaleFromSVs.html -https://mchikina.github.io/CLAMP/reference/gmtListToSparseMat.html -https://mchikina.github.io/CLAMP/reference/index.html -https://mchikina.github.io/CLAMP/reference/majorCellTypes.html -https://mchikina.github.io/CLAMP/reference/mat_mult.html -https://mchikina.github.io/CLAMP/reference/max_correspondence_greedy.html -https://mchikina.github.io/CLAMP/reference/mymessage.html -https://mchikina.github.io/CLAMP/reference/num.pc.html -https://mchikina.github.io/CLAMP/reference/oneToOneMask.html -https://mchikina.github.io/CLAMP/reference/panDB.html -https://mchikina.github.io/CLAMP/reference/pinv.ridge.html -https://mchikina.github.io/CLAMP/reference/plotTopZ_Complex.html -https://mchikina.github.io/CLAMP/reference/preprocessCLAMP.html -https://mchikina.github.io/CLAMP/reference/preprocessCLAMPFBM.html -https://mchikina.github.io/CLAMP/reference/preprocessPLIER2.html -https://mchikina.github.io/CLAMP/reference/preprocessPLIER2FBM.html -https://mchikina.github.io/CLAMP/reference/projectCLAMP.html -https://mchikina.github.io/CLAMP/reference/projectPLIER.html -https://mchikina.github.io/CLAMP/reference/read_gmt.html -https://mchikina.github.io/CLAMP/reference/ridge_B.html -https://mchikina.github.io/CLAMP/reference/rotateSVD.html -https://mchikina.github.io/CLAMP/reference/row_cor.html -https://mchikina.github.io/CLAMP/reference/run_elbow.html -https://mchikina.github.io/CLAMP/reference/run_permutation.html -https://mchikina.github.io/CLAMP/reference/select_clamp_k.html -https://mchikina.github.io/CLAMP/reference/select_svd_k.html -https://mchikina.github.io/CLAMP/reference/solveU.html -https://mchikina.github.io/CLAMP/reference/squashZscore.html -https://mchikina.github.io/CLAMP/reference/tscale.html -https://mchikina.github.io/CLAMP/reference/winsor_topk.html -https://mchikina.github.io/CLAMP/reference/xCell.html -https://mchikina.github.io/CLAMP/reference/zscoreCLAMP.html -https://mchikina.github.io/CLAMP/reference/zscoreCLAMPFBM.html -https://mchikina.github.io/CLAMP/reference/zscorePLIER2.html -https://mchikina.github.io/CLAMP/reference/zscorePLIER2FBM.html - - diff --git a/envs/clamp.yaml b/envs/clamp.yaml deleted file mode 100644 index ae4f17d..0000000 --- a/envs/clamp.yaml +++ /dev/null @@ -1,63 +0,0 @@ -name: clamp -channels: - - conda-forge - - bioconda - - defaults -dependencies: - - r-base=4.6.* #Must eventuallly be 4.6.0 due to CLAMPData requring 4.6.0, when it comes out 4-24-26 - - hdf5 - - r-hdf5r - - bioconductor-rhdf5 - - # Core R packages - - r-bigstatsr - - r-data.table - - r-dplyr - - r-rsvd - - r-glmnet - - r-matrix - - r-knitr - - r-here - - r-tibble - - r-tidyr - - r-devtools - - r-irkernel - - r-knitr - - r-pkgdown - - # Jupyter support - - jupyterlab - - notebook - - nb_conda_kernels - - # Bioconductor and bioinformatics - - bioconductor-qvalue - - bioconductor-biomart - - bioconductor-recount3 - - bioconductor-preprocesscore - - bioconductor-fgsea - - bioconductor-org.Hs.eg.db - - bioconductor-ensdb.hsapiens.v86 - - bioconductor-experimenthub - - bioconductor-genomeinfodbdata - - bioconductor-bioccheck - - bioconductor-complexheatmap - - bioconductor-biocstyle - - bioconductor-experimenthubdata - - # Other R utilities - - r-plyr - - r-randomforest - - r-bitops - - r-gtools - - r-kernsmooth - - r-gplots - - r-diagrammer - - r-irlba - - r-ggplot2 - - r-ggrepel - - r-dt - - r-circlize - # Ensure compatible SSL and curl for hdf5r in RStudio Server - - openssl - - libcurl \ No newline at end of file From 4e50c07ad4577962ffff9ca36b2ebf5dfb24feab Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Wed, 6 May 2026 14:49:14 -0600 Subject: [PATCH 16/20] adding examples and document regen --- DESCRIPTION | 8 +-- R/plots.R | 12 ++-- R/utils.R | 22 ++++--- man/AUC.Rd | 14 +++-- man/CLAMPbase.Rd | 50 ++++++++++------ man/CLAMPdotplot.Rd | 20 ++++--- man/CLAMPdotplotAll.Rd | 14 ++--- man/CLAMPfull.Rd | 100 +++++++++++++++++++------------ man/CLAMPfullnVP.Rd | 74 +++++++++++++++-------- man/CLAMPplotTopZ.Rd | 14 +++-- man/CLAMPplotU.Rd | 32 ++++++---- man/binarizeTop.Rd | 6 +- man/celltypeTargets.Rd | 5 +- man/cleanFBM.Rd | 27 +++++---- man/compareBs.Rd | 13 ++-- man/computeRowStatsFBM.Rd | 8 ++- man/cpmCLAMP.Rd | 3 +- man/cpmCLAMPFBM.Rd | 5 +- man/crossVal.Rd | 20 ++++--- man/cross_ZY.Rd | 2 +- man/filterFBM.Rd | 31 ++++++---- man/getAUCstats.Rd | 4 +- man/getChat.Rd | 11 ++-- man/getGMT.Rd | 15 +++-- man/getMatchedPathwayMat.Rd | 6 +- man/getMatchedPathwayMat2.Rd | 6 +- man/getMatchedPathwayMatList.Rd | 29 +++++---- man/getMatchedPathwayMatOld.Rd | 6 +- man/getMaxAUC.Rd | 7 ++- man/getScaleFromSVs.Rd | 3 +- man/gmtListToSparseMat.Rd | 17 +++--- man/majorCellTypes.Rd | 3 +- man/max_correspondence_greedy.Rd | 8 ++- man/mymessage.Rd | 3 +- man/num.pc.Rd | 3 +- man/panDB.Rd | 14 +++-- man/pinv.ridge.Rd | 3 +- man/plotTopZ_Complex.Rd | 26 +++++--- man/preprocessCLAMP.Rd | 8 ++- man/preprocessCLAMPFBM.Rd | 27 +++++---- man/projectCLAMP.Rd | 21 ++++--- man/read_gmt.Rd | 8 ++- man/ridge_B.Rd | 5 +- man/rotateSVD.Rd | 12 ++-- man/select_clamp_k.Rd | 7 +++ man/solveU.Rd | 80 +++++++++++++++---------- man/winsor_topk.Rd | 9 ++- man/zscoreCLAMP.Rd | 8 ++- man/zscoreCLAMPFBM.Rd | 3 +- 49 files changed, 520 insertions(+), 312 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index d76fcb1..369aba9 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -20,10 +20,10 @@ Description: CLAMP performs prior-informed latent variable decomposition of to uncover biologically meaningful patterns that connect genes, pathways, and complex traits in transcriptomics studies. License: GPL-3 -URL: https://mchikina.github.io/CLAMP/, https://github.com/mchikina/CLAMP -BugReports: https://github.com/mchikina/CLAMP/issues +URL: https://chikinalab.github.io/CLAMP/, https://github.com/chikinalab/CLAMP +BugReports: https://github.com/chikinalab/CLAMP/issues Depends: - R (>= 4.4.0), + R (>= 4.6.0), Imports: bigstatsr, circlize, @@ -67,5 +67,5 @@ biocViews: Software, GeneExpression, RNASeq, Transcriptomics, Encoding: UTF-8 LazyData: false Roxygen: list(markdown = TRUE) -RoxygenNote: 7.3.3 Config/testthat/edition: 3 +Config/roxygen2/version: 8.0.0 diff --git a/R/plots.R b/R/plots.R index 2f62e37..9e28a64 100644 --- a/R/plots.R +++ b/R/plots.R @@ -371,7 +371,7 @@ plotTopZ_Complex <- function(clampRes, data, priorMat, #' #' @return Invisibly returns a [ggplot2::ggplot()] object. #' @importFrom ggplot2 ggplot aes geom_tile scale_fill_gradient theme_minimal -#' theme element_text element_blank labs unit +#' @importFrom ggplot2 theme element_text element_blank labs unit #' @importFrom rlang .data #' @importFrom stats hclust dist #' @export @@ -678,9 +678,10 @@ CLAMPplotTopZ <- function(clampRes, data = NULL, priorMat = NULL, top = 50, #' to `x.axis`. #' #' @return Invisibly returns a [ggplot2::ggplot()] object. -#' @importFrom ggplot2 ggplot aes geom_segment geom_point scale_size_continuous -#' scale_colour_gradient scale_x_continuous theme_minimal theme element_text -#' element_blank element_line labs unit +#' @importFrom ggplot2 ggplot aes geom_segment geom_point +#' @importFrom ggplot2 scale_size_continuous scale_colour_gradient +#' @importFrom ggplot2 scale_x_continuous theme_minimal theme element_text +#' @importFrom ggplot2 element_blank element_line labs unit #' @importFrom rlang .data #' @export #' @examples @@ -828,7 +829,8 @@ CLAMPdotplot <- function(clampRes, lv = 1, top = 20, auc.cutoff = 0.6, #' #' @return Invisibly returns a [ggplot2::ggplot()] object. #' @importFrom ggplot2 ggplot aes geom_point scale_colour_gradient -#' scale_size_continuous theme_minimal theme element_text element_line labs +#' @importFrom ggplot2 scale_size_continuous theme_minimal theme +#' @importFrom ggplot2 element_text element_line labs #' @importFrom dplyr group_by slice_max ungroup #' @importFrom rlang .data #' @export diff --git a/R/utils.R b/R/utils.R index d1e6647..246d318 100644 --- a/R/utils.R +++ b/R/utils.R @@ -359,14 +359,11 @@ commonRows <- function(data1, data2) { #' parallel-safe chunks. #' @importFrom bigstatsr big_apply rows_along FBM #' @examples -#' \donttest{ -#' library(bigstatsr) -#' fbm <- FBM(3, 4, init = matrix( +#' fbm <- bigstatsr::FBM(3, 4, init = matrix( #' c(0, 1, 2, NA, 100, 200, 300, 400, 5, 6, 7, 8), #' nrow = 3 #' )) #' cleanFBM(fbm, ncores = 1) -#' } #' #' @export cleanFBM <- function(fbm, ncores = 1) { @@ -474,15 +471,16 @@ computeRowStatsFBM <- function(fbm, ncores = 1) { #' the filtering criteria. #' The original FBM is unchanged. #' @examples -#' \donttest{ -#' library(bigstatsr) -#' fbm <- FBM(5, 3, init = matrix(rnorm(15), nrow = 5)) -#' rs <- list(row_means = rowMeans(fbm[]), row_variances = apply(fbm[], 1, var)) +#' fbm <- bigstatsr::FBM(5, 3, init = matrix(rnorm(15), nrow = 5)) +#' rs <- list( +#' row_means = rowMeans(fbm[]), +#' row_variances = apply(fbm[], 1, var) +#' ) #' out <- filterFBM(fbm, rs, #' mean_cutoff = -0.2, var_cutoff = 0.5, #' backingfile = tempfile() #' ) -#' } +#' #' @importFrom bigstatsr cols_along big_copy #' @export filterFBM <- function(fbm, rowStats, keep_samples_idx = NULL, @@ -1146,6 +1144,12 @@ compute_svd <- function(Y, k = NULL) { #' #' @return An integer: the selected number of latent variables. #' +#' @examples +#' set.seed(1) +#' Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) +#' svdres <- compute_svd(Y, k = 25) +#' select_clamp_k(svdres, n_samples = ncol(Y), svd_k = 25) +#' #' @export select_clamp_k <- function(svdres, n_samples, svd_k, method = c( diff --git a/man/AUC.Rd b/man/AUC.Rd index 1fd0790..3bd72d5 100644 --- a/man/AUC.Rd +++ b/man/AUC.Rd @@ -7,19 +7,23 @@ AUC(labels, values) } \arguments{ -\item{labels}{A numeric or logical vector indicating class labels. Values > 0 are treated as positive.} +\item{labels}{A numeric or logical vector indicating class labels. +Values > 0 are treated as positive.} -\item{values}{A numeric vector of prediction scores corresponding to \code{labels}.} +\item{values}{A numeric vector of prediction scores corresponding to +\code{labels}.} } \value{ A list with: \describe{ \item{\code{auc}}{Estimated AUC, or 0.5 if one class is missing} -\item{\code{pval}}{Wilcoxon test p-value, or \code{NA} if one class is missing} +\item{\code{pval}}{Wilcoxon test p-value, or \code{NA} if one class +is missing} } } \description{ -Computes the area under the ROC curve (AUC) by applying a Wilcoxon rank-sum test -between predicted values for positive and negative labels. This is equivalent to +Computes the area under the ROC curve (AUC) by applying a Wilcoxon +rank-sum test between predicted values for positive and negative labels. +This is equivalent to computing the Mann-Whitney U statistic. } diff --git a/man/CLAMPbase.Rd b/man/CLAMPbase.Rd index 1b161a7..ed85fae 100644 --- a/man/CLAMPbase.Rd +++ b/man/CLAMPbase.Rd @@ -27,7 +27,8 @@ CLAMPbase( ) } \arguments{ -\item{Y}{Input gene expression matrix (genes x samples). Can be dense, sparse (\code{dgCMatrix}), or FBM.} +\item{Y}{Input gene expression matrix (genes x samples). Can be dense, +sparse (\code{dgCMatrix}), or FBM.} \item{clamp_k}{Number of latent variables for CLAMP (final model rank). If \code{NULL}, it is chosen automatically via \code{select_clamp_k()}.} @@ -35,40 +36,51 @@ If \code{NULL}, it is chosen automatically via \code{select_clamp_k()}.} \item{svd_k}{Number of singular values/components to compute in the SVD. If \code{NULL}, defaults to \code{max(2, min(n_genes, n_samples) - 1)}.} -\item{svdres}{Optional precomputed SVD result. If not supplied, it is computed internally.} +\item{svdres}{Optional precomputed SVD result. If not supplied, it is +computed internally.} -\item{L1}{L1 regularization strength for Z. Defaults to scaled singular value.} +\item{L1}{L1 regularization strength for Z. Defaults to scaled singular +value.} -\item{L2}{L2 regularization strength for B. Defaults to scaled singular value.} +\item{L2}{L2 regularization strength for B. Defaults to scaled singular +value.} -\item{Zpos}{Logical; if \code{TRUE}, negative entries in Z are zeroed. Default is \code{TRUE}.} +\item{Zpos}{Logical; if \code{TRUE}, negative entries in Z are zeroed. +Default is \code{TRUE}.} \item{max.iter}{Maximum number of optimization iterations. Default is 200.} \item{tol}{Convergence tolerance for B update. Default is 5e-4.} -\item{trace}{Logical; if \code{TRUE}, prints progress. Default is \code{FALSE}.} +\item{trace}{Logical; if \code{TRUE}, prints progress. Default is +\code{FALSE}.} \item{rseed}{Optional integer for reproducible random initialization of B.} -\item{B}{Optional initial matrix for B. If not provided, initialized from SVD.} +\item{B}{Optional initial matrix for B. If not provided, initialized +from SVD.} \item{scale}{Scaling factor for L1 and L2 when not provided. Default is 1.} \item{pos.adj}{Positive constraint adjustment divisor for L1. Default is 3.} -\item{adaptive.p}{Controls adaptive sparsity in \code{Z}. After each ALS update, +\item{adaptive.p}{Controls adaptive sparsity in \code{Z}. After each ALS +update, negative entries in \code{Z} are assumed to reflect noise. -The cutoff for thresholding is set according to the probability of positive values under -a reflected negative distribution—effectively zeroing out small positive entries likely to be noise. +The cutoff for thresholding is set according to the probability of +positive values under a reflected negative distribution-effectively +zeroing out small positive entries likely to be noise. Smaller values lead to more sparsity. Default is 0.05.} -\item{adaptive.iter}{Number of iterations before adaptive sparsity is applied. Default is 20.} +\item{adaptive.iter}{Number of iterations before adaptive sparsity is +applied. Default is 20.} -\item{cutoff}{Scalar threshold to zero Z values when \code{Zpos = TRUE} and adaptive thresholding +\item{cutoff}{Scalar threshold to zero Z values when \code{Zpos = TRUE} +and adaptive thresholding is not used. Default is 0.} -\item{ncores}{Number of cores to use for parallel computation (only used if Y is an FBM). Default is 1.} +\item{ncores}{Number of cores to use for parallel computation (only used +if Y is an FBM). Default is 1.} \item{clamp_k_method}{Method for selecting \code{clamp_k} when not provided. One of \code{"elbow"} (default), \code{"permutation"}, \code{"gavish_donoho"}, or @@ -86,14 +98,16 @@ A list with components: } \description{ Runs the core matrix factorization procedure of CLAMP, -decomposing the gene expression matrix \code{Y} into latent variables \code{Z} and loadings \code{B}. -It supports sparse, dense, and Filebacked Big Matrices (FBM) as input and includes options for +decomposing the gene expression matrix \code{Y} into latent variables +\code{Z} and loadings \code{B}. It supports sparse, dense, and Filebacked +Big Matrices (FBM) as input and includes options for adaptive sparsity, positive constraints, and regularization. } \details{ -This function is the low-level implementation of CLAMP. It alternates between solving for \code{Z} -given \code{B} and solving for \code{B} given \code{Z}, with optional sparsity and non-negativity -constraints on \code{Z}. Convergence is assessed via relative change in \code{B}. +This function is the low-level implementation of CLAMP. It alternates +between solving for \code{Z} given \code{B} and solving for \code{B} +given \code{Z}, with optional sparsity and non-negativity constraints on +\code{Z}. Convergence is assessed via relative change in \code{B}. } \examples{ # small toy dataset: 5 genes x 4 samples diff --git a/man/CLAMPdotplot.Rd b/man/CLAMPdotplot.Rd index 69ff95f..443802f 100644 --- a/man/CLAMPdotplot.Rd +++ b/man/CLAMPdotplot.Rd @@ -50,18 +50,20 @@ The x-axis and pathway ordering can use either AUC or \code{-log10(FDR)}. \examples{ set.seed(9) pathways <- paste0("Pathway_", 1:20) -lvs <- paste0("LV", 1:5) -nr <- length(pathways) * length(lvs) +lvs <- paste0("LV", 1:5) +nr <- length(pathways) * length(lvs) summ <- data.frame( - pathway = rep(pathways, length(lvs)), - LV = rep(lvs, each = length(pathways)), - AUC = runif(nr, 0.5, 1.0), - FDR = runif(nr, 0, 0.05), - stringsAsFactors = FALSE + pathway = rep(pathways, length(lvs)), + LV = rep(lvs, each = length(pathways)), + AUC = runif(nr, 0.5, 1.0), + FDR = runif(nr, 0, 0.05), + stringsAsFactors = FALSE ) CLAMPdotplot(list(summary = summ), lv = 1, top = 10) -CLAMPdotplot(list(summary = summ), lv = "LV2", x.axis = "-log10(FDR)", - order.by = "-log10(FDR)") +CLAMPdotplot(list(summary = summ), + lv = "LV2", x.axis = "-log10(FDR)", + order.by = "-log10(FDR)" +) } diff --git a/man/CLAMPdotplotAll.Rd b/man/CLAMPdotplotAll.Rd index e5bcd50..26fc8b2 100644 --- a/man/CLAMPdotplotAll.Rd +++ b/man/CLAMPdotplotAll.Rd @@ -38,15 +38,15 @@ associations passing \code{auc.cutoff} and \code{fdr.cutoff} are shown. \examples{ set.seed(9) pathways <- paste0("Pathway_", 1:20) -lvs <- paste0("LV", 1:5) -nr <- length(pathways) * length(lvs) +lvs <- paste0("LV", 1:5) +nr <- length(pathways) * length(lvs) summ <- data.frame( - pathway = rep(pathways, length(lvs)), - LV = rep(lvs, each = length(pathways)), - AUC = runif(nr, 0.5, 1.0), - FDR = runif(nr, 0, 0.2), - stringsAsFactors = FALSE + pathway = rep(pathways, length(lvs)), + LV = rep(lvs, each = length(pathways)), + AUC = runif(nr, 0.5, 1.0), + FDR = runif(nr, 0, 0.2), + stringsAsFactors = FALSE ) CLAMPdotplotAll(list(summary = summ), auc.cutoff = 0.6, fdr.cutoff = 0.15) diff --git a/man/CLAMPfull.Rd b/man/CLAMPfull.Rd index 10640ae..8bc66f4 100644 --- a/man/CLAMPfull.Rd +++ b/man/CLAMPfull.Rd @@ -42,15 +42,18 @@ CLAMPfull( ) } \arguments{ -\item{Y}{Gene expression matrix (genes × samples). Can be dense, sparse (dgCMatrix), or FBM.} +\item{Y}{Gene expression matrix (genes x samples). Can be dense, sparse +(dgCMatrix), or FBM.} -\item{priorMat}{Binary or weighted prior matrix (genes × pathways) linking genes to pathways.} +\item{priorMat}{Binary or weighted prior matrix (genes x pathways) +linking genes to pathways.} \item{Chat}{Ignored in this version (kept for interface compatibility).} \item{svdres}{Optional precomputed SVD result for initialization.} -\item{clamp.base.result}{Optional result from \code{CLAMPbase()} providing initial values.} +\item{clamp.base.result}{Optional result from \code{CLAMPbase()} +providing initial values.} \item{clamp_k}{Number of latent variables for CLAMP (final model rank). If \code{NULL}, it is chosen automatically via \code{select_clamp_k()}.} @@ -58,7 +61,8 @@ If \code{NULL}, it is chosen automatically via \code{select_clamp_k()}.} \item{svd_k}{Number of singular values/components to compute in the SVD. If \code{NULL}, defaults to \code{max(2, min(n_genes, n_samples) - 1)}.} -\item{L1, L2}{Regularization parameters for \code{Z} and \code{B}. Defaults use values from +\item{L1, L2}{Regularization parameters for \code{Z} and \code{B}. +Defaults use values from \code{clamp.base.result}.} \item{cvn}{Number of folds for pathway-level cross-validation. Default: 5.} @@ -67,11 +71,14 @@ If \code{NULL}, defaults to \code{max(2, min(n_genes, n_samples) - 1)}.} \item{trace}{Logical; print iteration progress. Default: \code{TRUE}.} -\item{maxPath}{Maximum number of pathways per LV during U-fitting. Default: 10.} +\item{maxPath}{Maximum number of pathways per LV during U-fitting. +Default: 10.} -\item{doCrossval}{Whether to mask prior entries for CV evaluation. Default: \code{TRUE}.} +\item{doCrossval}{Whether to mask prior entries for CV evaluation. +Default: \code{TRUE}.} -\item{penalty.factor}{Optional vector of per-pathway penalties for glmnet. Default: 1.} +\item{penalty.factor}{Optional vector of per-pathway penalties for glmnet. +Default: 1.} \item{glm_alpha}{Elastic net mixing parameter for U estimation. Default: 0.9.} @@ -81,34 +88,44 @@ If \code{NULL}, defaults to \code{max(2, min(n_genes, n_samples) - 1)}.} \item{seed}{Random seed for CV masking. Default: 123456.} -\item{allGenes}{If \code{TRUE}, adds zero-filled rows for missing genes. Default: \code{FALSE}.} +\item{allGenes}{If \code{TRUE}, adds zero-filled rows for missing genes. +Default: \code{FALSE}.} -\item{rseed}{Reproducibility, coordinate descent updates are done in random order.} +\item{rseed}{Reproducibility, coordinate descent updates are done in +random order.} \item{max.U.updates}{Maximum number of U updates (capped by max.iter).} -\item{pathwaySelection}{Pathway selection mode for U fitting (\code{"fast"} or \code{"complete"}).} +\item{pathwaySelection}{Pathway selection mode for U fitting +(\code{"fast"} or \code{"complete"}).} \item{multiplier}{Variance-prior scaling factor. Default: 5.} -\item{adaptive.p}{Quantile of negative Z values used to define adaptive thresholding. Default: 0.05.} +\item{adaptive.p}{Quantile of negative Z values used to define adaptive +thresholding. Default: 0.05.} -\item{useNNLS}{Whether to use non-negative least squares for U estimation. Default: \code{TRUE}.} +\item{useNNLS}{Whether to use non-negative least squares for U estimation. +Default: \code{TRUE}.} -\item{useRaw}{If \code{TRUE}, uses unthresholded Z in U updates. Default: \code{TRUE}.} +\item{useRaw}{If \code{TRUE}, uses unthresholded Z in U updates. +Default: \code{TRUE}.} \item{refitEvery}{Frequency (in U updates) of full refits. Default: 3.} -\item{useSE}{Logical; whether to use the 1-standard-error rule for internal glmnet fitting. Default is FALSE.} +\item{useSE}{Logical; whether to use the 1-standard-error rule for +internal glmnet fitting. Default is FALSE.} -\item{var.prior}{Logical; if \code{TRUE}, enables adaptive variance prior updates for Z. +\item{var.prior}{Logical; if \code{TRUE}, enables adaptive variance prior +updates for Z. Default: \code{TRUE}.} \item{Uscale}{Logical; whether to scale U columns. Default: \code{FALSE}.} -\item{robust.vp}{Logical; winsorize prior-predicted Z2 values to reduce outlier effects. Default: \code{TRUE}.} +\item{robust.vp}{Logical; winsorize prior-predicted Z2 values to reduce +outlier effects. Default: \code{TRUE}.} -\item{use_cpp}{Logical; if TRUE, use C++ implementation for Z updates. Default is FALSE.} +\item{use_cpp}{Logical; if TRUE, use C++ implementation for Z updates. +Default is FALSE.} \item{clamp_k_method}{Method for selecting \code{clamp_k} when not provided. One of \code{"elbow"} (default), \code{"permutation"}, \code{"gavish_donoho"}, or @@ -129,22 +146,28 @@ A list with elements: } } \description{ -This version performs latent-variable decomposition of a gene expression matrix \code{Y} -guided by prior pathway annotations \code{priorMat}, with simplified and lighter regularization -compared to the original extended CLAMP variant. The algorithm alternates updates of \code{Z}, -\code{B}, and \code{U}, where \code{U} captures pathway–latent variable associations inferred -directly from the data without ridge-regularized projections (\code{Chat} is not used). +This version performs latent-variable decomposition of a gene expression +matrix \code{Y} guided by prior pathway annotations \code{priorMat}, with +simplified and lighter regularization compared to the original extended +CLAMP variant. The algorithm alternates updates of \code{Z}, \code{B}, +and \code{U}, where \code{U} captures pathway-latent variable +associations inferred directly from the data without ridge-regularized +projections (\code{Chat} is not used). } \details{ -Cross-validation can be used to evaluate pathway–LV specificity, and a variance-based prior -(\code{var.prior = TRUE}) introduces adaptive shrinkage of \code{Z} based on how strongly -each latent component aligns with prior pathways. The scaling factor \code{multiplier} (default 5) +Cross-validation can be used to evaluate pathway-LV specificity, and a +variance-based prior (\code{var.prior = TRUE}) introduces adaptive +shrinkage of \code{Z} based on how strongly each latent component aligns +with prior pathways. The scaling factor \code{multiplier} (default 5) controls the strength of this adaptive shrinkage. -This implementation omits ridge-projected priors (\code{Chat}) and uses a lighter variance prior -with a lower default \code{multiplier = 5}, allowing more flexible latent representations. -Setting \code{var.prior = FALSE} reproduces standard CLAMP-like updates. Cross-validation, if -enabled, masks 20\% of gene–pathway associations per column to estimate pathway–LV specificity +This implementation omits ridge-projected priors (\code{Chat}) and uses +a lighter variance prior with a lower default \code{multiplier = 5}, +allowing more flexible latent representations. Setting +\code{var.prior = FALSE} reproduces standard CLAMP-like updates. +Cross-validation, if +enabled, masks 20\% of gene-pathway associations per column to estimate +pathway-LV specificity (reported via AUC and p-values). } \examples{ @@ -152,15 +175,16 @@ set.seed(1) mat <- matrix(rnorm(100), nrow = 10, ncol = 10) base <- CLAMPbase(mat, clamp_k = 5, trace = FALSE, max.iter = 5) prior <- matrix(sample(0:1, 10 * 6, TRUE, prob = c(0.9, 0.1)), - nrow = 10, ncol = 6) + nrow = 10, ncol = 6 +) fit <- CLAMPfull( - Y = mat, - priorMat = prior, - clamp.base.result = base, - doCrossval = FALSE, - adaptive.p = 0, - max.U.updates = 0, - max.iter = 1, - trace = FALSE + Y = mat, + priorMat = prior, + clamp.base.result = base, + doCrossval = FALSE, + adaptive.p = 0, + max.U.updates = 0, + max.iter = 1, + trace = FALSE ) } diff --git a/man/CLAMPfullnVP.Rd b/man/CLAMPfullnVP.Rd index 3995c36..c79e521 100644 --- a/man/CLAMPfullnVP.Rd +++ b/man/CLAMPfullnVP.Rd @@ -40,13 +40,16 @@ CLAMPfullnVP( ) } \arguments{ -\item{Y}{Gene expression matrix (genes x samples). Can be dense, sparse (dgCMatrix), or FBM.} +\item{Y}{Gene expression matrix (genes x samples). Can be dense, sparse +(dgCMatrix), or FBM.} -\item{priorMat}{Binary matrix (genes x pathways) representing prior annotations.} +\item{priorMat}{Binary matrix (genes x pathways) representing prior +annotations.} \item{svdres}{Optional SVD result used for initialization.} -\item{clamp.base.result}{Optional result from \code{CLAMPbase()} to initialize B.} +\item{clamp.base.result}{Optional result from \code{CLAMPbase()} to +initialize B.} \item{clamp_k}{Number of latent variables for CLAMP (final model rank). If \code{NULL}, it is chosen automatically via \code{select_clamp_k()}.} @@ -54,9 +57,11 @@ If \code{NULL}, it is chosen automatically via \code{select_clamp_k()}.} \item{svd_k}{Number of singular values/components to compute in the SVD. If \code{NULL}, defaults to \code{max(2, min(n_genes, n_samples) - 1)}.} -\item{L1}{Regularization strength for Z. If \code{NULL}, initialized from SVD or \code{clamp.base.result}.} +\item{L1}{Regularization strength for Z. If \code{NULL}, initialized from +SVD or \code{clamp.base.result}.} -\item{L2}{Regularization strength for B. If \code{NULL}, initialized from SVD or \code{clamp.base.result}.} +\item{L2}{Regularization strength for B. If \code{NULL}, initialized from +SVD or \code{clamp.base.result}.} \item{top}{If set, keeps only top-n values per column in Z during U updates.} @@ -68,11 +73,14 @@ If \code{NULL}, defaults to \code{max(2, min(n_genes, n_samples) - 1)}.} \item{Chat}{Optional precomputed matrix for solving U.} -\item{maxPath}{Maximum number of pathways/features selected per LV. Default is 10.} +\item{maxPath}{Maximum number of pathways/features selected per LV. +Default is 10.} -\item{doCrossval}{Whether to perform pathway-level cross-validation. Default is \code{TRUE}.} +\item{doCrossval}{Whether to perform pathway-level cross-validation. +Default is \code{TRUE}.} -\item{penalty.factor}{Vector of feature-specific penalties for glmnet. Default: all ones.} +\item{penalty.factor}{Vector of feature-specific penalties for glmnet. +Default: all ones.} \item{glm_alpha}{Elastic net mixing parameter for glmnet. Default is 0.9.} @@ -80,32 +88,41 @@ If \code{NULL}, defaults to \code{max(2, min(n_genes, n_samples) - 1)}.} \item{tol}{Convergence tolerance on relative change in B. Default is 5e-4.} -\item{seed}{Seed for reproducibility of cross-validation masking. Default is 123456.} +\item{seed}{Seed for reproducibility of cross-validation masking. +Default is 123456.} -\item{allGenes}{If \code{TRUE}, zero-fills \code{priorMat} for genes not present. Default is \code{FALSE}.} +\item{allGenes}{If \code{TRUE}, zero-fills \code{priorMat} for genes not +present. Default is \code{FALSE}.} \item{rseed}{Optional seed for randomly reinitializing B and Z.} \item{max.U.updates}{Maximum number of U updates. Default is 5.} -\item{pathwaySelection}{Pathway selection mode: \code{"fast"} or \code{"complete"}.} +\item{pathwaySelection}{Pathway selection mode: \code{"fast"} or +\code{"complete"}.} \item{multiplier}{Scaling factor for adjusting L1 and L2.} -\item{adaptive.p}{Quantile threshold for adaptively zeroing small Z values. After each update, -the \code{adaptive.p}-quantile of negative entries in Z is used (flipped positive) to threshold +\item{adaptive.p}{Quantile threshold for adaptively zeroing small Z +values. After each update, the \code{adaptive.p}-quantile of negative +entries in Z is used (flipped positive) to threshold small positive values, assuming they reflect noise. Default is 0.05.} -\item{useNNLS}{If \code{TRUE}, uses non-negative least squares in U estimation. Default is \code{TRUE}.} +\item{useNNLS}{If \code{TRUE}, uses non-negative least squares in U +estimation. Default is \code{TRUE}.} -\item{useRaw}{If \code{TRUE}, uses unthresholded Z for solving U. Default is \code{TRUE}.} +\item{useRaw}{If \code{TRUE}, uses unthresholded Z for solving U. +Default is \code{TRUE}.} -\item{refitAll}{If \code{TRUE}, refits all U columns every update. Default is \code{FALSE}.} +\item{refitAll}{If \code{TRUE}, refits all U columns every update. +Default is \code{FALSE}.} -\item{useSE}{Logical; passed to the internal \code{solveU()} call. If \code{TRUE}, -enables standard-error–aware selection when fitting U (pathway coefficients). Default is \code{FALSE}.} +\item{useSE}{Logical; passed to the internal \code{solveU()} call. If +\code{TRUE}, enables standard-error-aware selection when fitting U +(pathway coefficients). Default is \code{FALSE}.} -\item{ncores}{Number of cores to use for parallel computation (only used if Y is an FBM). Default is 1.} +\item{ncores}{Number of cores to use for parallel computation (only used +if Y is an FBM). Default is 1.} \item{clamp_k_method}{Method for selecting \code{clamp_k} when not provided. One of \code{"elbow"} (default), \code{"permutation"}, \code{"gavish_donoho"}, or @@ -119,10 +136,12 @@ A list with the following components: \item{\code{U}}{Pathway loadings matrix (pathways x LVs)} \item{\code{C}}{Masked prior matrix used for training} \item{\code{L1}, \code{L2}}{Regularization parameters} -\item{\code{heldOutGenes}}{List of held-out genes per pathway (if CV is enabled)} +\item{\code{heldOutGenes}}{List of held-out genes per pathway (if CV +is enabled)} \item{\code{Uauc}}{AUC matrix from CV evaluation (if enabled)} \item{\code{Up}}{-\code{log10(p)} values from CV evaluation (if enabled)} -\item{\code{summary}}{Data frame of AUC, p-values, and FDR per pathway x LV (if enabled)} +\item{\code{summary}}{Data frame of AUC, p-values, and FDR per pathway +x LV (if enabled)} \item{\code{priorMatCV}}{Masked prior matrix used during CV} \item{\code{priorMat}}{Final filtered prior matrix} \item{\code{withPrior}}{Indices of LVs with non-zero pathway loadings} @@ -131,13 +150,16 @@ A list with the following components: } \description{ Runs the full CLAMP model using a gene expression matrix -and prior pathway annotation matrix. This function performs latent variable decomposition -guided by prior knowledge and includes optional cross-validation to evaluate pathway associations. +and prior pathway annotation matrix. This function performs latent +variable decomposition guided by prior knowledge and includes optional +cross-validation to evaluate pathway associations. } \details{ -The model alternates between solving \code{Z}, \code{B}, and \code{U}. Adaptive sparsity is applied -to \code{Z} using a dynamic threshold based on the negative tail of its distribution. Cross-validation -is used to hold out gene annotations in \code{priorMat} and evaluate latent variable specificity. +The model alternates between solving \code{Z}, \code{B}, and \code{U}. +Adaptive sparsity is applied to \code{Z} using a dynamic threshold based +on the negative tail of its distribution. Cross-validation is used to +hold out gene annotations in \code{priorMat} and evaluate latent variable +specificity. } \examples{ mat <- matrix(rnorm(100), 10, 10) diff --git a/man/CLAMPplotTopZ.Rd b/man/CLAMPplotTopZ.Rd index 5d8c536..e041d57 100644 --- a/man/CLAMPplotTopZ.Rd +++ b/man/CLAMPplotTopZ.Rd @@ -47,12 +47,16 @@ genes are labelled with \code{ggrepel}. \examples{ set.seed(1) genes <- paste0("Gene", 1:80) -lvs <- paste0("LV", 1:4) +lvs <- paste0("LV", 1:4) paths <- paste0("Path", 1:10) -Z <- matrix(abs(rnorm(80 * 4)), nrow = 80, - dimnames = list(genes, lvs)) -U <- matrix(abs(rnorm(10 * 4)), nrow = 10, - dimnames = list(paths, lvs)) +Z <- matrix(abs(rnorm(80 * 4)), + nrow = 80, + dimnames = list(genes, lvs) +) +U <- matrix(abs(rnorm(10 * 4)), + nrow = 10, + dimnames = list(paths, lvs) +) clampRes <- list(Z = Z, U = U) CLAMPplotTopZ(clampRes, top = 20, index = 1:2) } diff --git a/man/CLAMPplotU.Rd b/man/CLAMPplotU.Rd index 4537555..709092d 100644 --- a/man/CLAMPplotU.Rd +++ b/man/CLAMPplotU.Rd @@ -49,24 +49,30 @@ thresholds. Only the top-\code{top} pathways per LV are shown. \examples{ set.seed(42) pathways <- paste0("Path", 1:30) -lvs <- paste0("LV", 1:5) +lvs <- paste0("LV", 1:5) -U <- matrix(abs(rnorm(30 * 5)), nrow = 30, - dimnames = list(pathways, lvs)) -Uauc <- matrix(runif(30 * 5, 0.5, 1.0), nrow = 30, - dimnames = list(pathways, lvs)) -Up <- matrix(runif(30 * 5, 0, 3), nrow = 30, - dimnames = list(pathways, lvs)) +U <- matrix(abs(rnorm(30 * 5)), + nrow = 30, + dimnames = list(pathways, lvs) +) +Uauc <- matrix(runif(30 * 5, 0.5, 1.0), + nrow = 30, + dimnames = list(pathways, lvs) +) +Up <- matrix(runif(30 * 5, 0, 3), + nrow = 30, + dimnames = list(pathways, lvs) +) # Build a minimal summary table nr <- 30 * 5 summ <- data.frame( - pathway = rep(pathways, 5), - LV = rep(lvs, each = 30), - AUC = as.vector(Uauc), - p_value = runif(nr, 0, 0.1), - FDR = runif(nr, 0, 0.1), - stringsAsFactors = FALSE + pathway = rep(pathways, 5), + LV = rep(lvs, each = 30), + AUC = as.vector(Uauc), + p_value = runif(nr, 0, 0.1), + FDR = runif(nr, 0, 0.1), + stringsAsFactors = FALSE ) clampRes <- list(U = U, Uauc = Uauc, Up = Up, summary = summ) diff --git a/man/binarizeTop.Rd b/man/binarizeTop.Rd index 8402b90..605474a 100644 --- a/man/binarizeTop.Rd +++ b/man/binarizeTop.Rd @@ -11,11 +11,13 @@ binarizeTop(Z, top, keepVals = TRUE) \item{top}{Number of top entries to keep in each column.} -\item{keepVals}{If \code{TRUE}, retains original values above the cutoff; otherwise, sets them to 1.} +\item{keepVals}{If \code{TRUE}, retains original values above the cutoff; +otherwise, sets them to 1.} } \value{ A modified matrix with only top entries retained per column. } \description{ -Keeps only the top \code{top} values in each column of a matrix, setting others to 0. +Keeps only the top \code{top} values in each column of a matrix, setting +others to 0. } diff --git a/man/celltypeTargets.Rd b/man/celltypeTargets.Rd index ceb26c3..1c57720 100644 --- a/man/celltypeTargets.Rd +++ b/man/celltypeTargets.Rd @@ -16,8 +16,9 @@ A numeric matrix of cell-type proportions. } \description{ A numeric matrix of estimated cell-type proportions for whole-blood samples. -Rows correspond to sample IDs and columns to major immune cell types. This dataset -can be used for validation or illustrative purposes in CLAMP analyses. +Rows correspond to sample IDs and columns to major immune cell types. +This dataset can be used for validation or illustrative purposes in +CLAMP analyses. } \examples{ data(celltypeTargets) diff --git a/man/cleanFBM.Rd b/man/cleanFBM.Rd index 8e3d384..46513fe 100644 --- a/man/cleanFBM.Rd +++ b/man/cleanFBM.Rd @@ -9,28 +9,33 @@ cleanFBM(fbm, ncores = 1) \arguments{ \item{fbm}{A \code{bigmemory::FBM} or \code{bigstatsr::FBM} object.} -\item{ncores}{Integer; number of cores to use for parallel operations (default 1).} +\item{ncores}{Integer; number of cores to use for parallel operations +(default 1).} } \value{ A list with: \describe{ -\item{max_value}{The maximum value encountered in the FBM (after log transformation if applied).} -\item{had_na}{Logical indicating whether any NA values were found and filled.} +\item{max_value}{The maximum value encountered in the FBM (after log +transformation if applied).} +\item{had_na}{Logical indicating whether any NA values were found +and filled.} } } \description{ -This function inspects an FBM to determine if log-transformation is needed (based on value range) -and whether NA values are present. If the maximum value is >= 100, it applies a log2(x + 1) -transformation in-place. If any NA values are detected, they are replaced with 0. +This function inspects an FBM to determine if log-transformation is needed +(based on value range) and whether NA values are present. If the maximum +value is >= 100, it applies a log2(x + 1) transformation in-place. If any +NA values are detected, they are replaced with 0. } \details{ -Modifies the FBM in place. Uses \code{bigstatsr::big_apply()} to process in parallel-safe chunks. +Modifies the FBM in place. Uses \code{bigstatsr::big_apply()} to process in +parallel-safe chunks. } \examples{ -\donttest{ -library(bigstatsr) -fbm <- FBM(3, 4, init = matrix(c(0, 1, 2, NA, 100, 200, 300, 400, 5, 6, 7, 8), nrow = 3)) +fbm <- bigstatsr::FBM(3, 4, init = matrix( + c(0, 1, 2, NA, 100, 200, 300, 400, 5, 6, 7, 8), + nrow = 3 +)) cleanFBM(fbm, ncores = 1) -} } diff --git a/man/compareBs.Rd b/man/compareBs.Rd index 04966d6..71c19c9 100644 --- a/man/compareBs.Rd +++ b/man/compareBs.Rd @@ -17,7 +17,8 @@ compareBs( } \arguments{ \item{res1, }{res2 Result objects or matrices containing factor loadings. -If a list, must contain element \code{B}; if of class \code{"rsvd"}, \code{t(res$v)} is used.} +If a list, must contain element \code{B}; if of class \code{"rsvd"}, +\code{t(res$v)} is used.} \item{res2}{Second result object or matrix to compare against.} @@ -30,7 +31,8 @@ Pearson, Spearman, AUC, or t-statistic comparison.} \item{ylab}{Label for y-axis (used in plot).} -\item{stat.method}{Statistical test to compare correlations (\code{"t"} or \code{"wilcox"}).} +\item{stat.method}{Statistical test to compare correlations +(\code{"t"} or \code{"wilcox"}).} \item{oneToOne}{Logical, whether to apply one-to-one masking of associations.} } @@ -38,7 +40,8 @@ Pearson, Spearman, AUC, or t-statistic comparison.} A list with: \describe{ \item{plot}{A ggplot object comparing maximal correlations across targets.} -\item{df}{A data.frame with per-target metrics and (if available) top genes.} +\item{df}{A data.frame with per-target metrics and (if available) +top genes.} } } \description{ @@ -60,5 +63,7 @@ target <- matrix(rnorm(20 * 3), ncol = 3) colnames(target) <- c("Trait1", "Trait2", "Trait3") # Compare the two sets of embeddings -res <- compareBs(svd1, svd2, target, method = "p", xlab = "SVD1", ylab = "SVD2") +res <- compareBs(svd1, svd2, target, + method = "p", xlab = "SVD1", ylab = "SVD2" +) } diff --git a/man/computeRowStatsFBM.Rd b/man/computeRowStatsFBM.Rd index d9c83ad..72c5e5f 100644 --- a/man/computeRowStatsFBM.Rd +++ b/man/computeRowStatsFBM.Rd @@ -9,7 +9,8 @@ computeRowStatsFBM(fbm, ncores = 1) \arguments{ \item{fbm}{A \code{bigstatsr::FBM} object.} -\item{ncores}{Integer; number of cores to use for parallel operations (default 1).} +\item{ncores}{Integer; number of cores to use for parallel operations +(default 1).} } \value{ A list with two numeric vectors: @@ -19,6 +20,7 @@ A list with two numeric vectors: } } \description{ -Efficiently computes row sums and row sum-of-squares for a \code{bigstatsr::FBM} using -column-wise chunking, suitable for large datasets that cannot be loaded fully into memory. +Efficiently computes row sums and row sum-of-squares for a +\code{bigstatsr::FBM} using column-wise chunking, suitable for large datasets +that cannot be loaded fully into memory. } diff --git a/man/cpmCLAMP.Rd b/man/cpmCLAMP.Rd index a88326a..c5444ba 100644 --- a/man/cpmCLAMP.Rd +++ b/man/cpmCLAMP.Rd @@ -10,7 +10,8 @@ cpmCLAMP(counts) \item{counts}{A numeric matrix or data.frame of raw counts (genes x samples).} } \value{ -A numeric matrix of CPM values (same dimensions), ready for CLAMP input. +A numeric matrix of CPM values (same dimensions), ready for CLAMP +input. } \description{ Compute counts-per-million (CPM) for CLAMP pipelines diff --git a/man/cpmCLAMPFBM.Rd b/man/cpmCLAMPFBM.Rd index 4e74f9b..2be6d5b 100644 --- a/man/cpmCLAMPFBM.Rd +++ b/man/cpmCLAMPFBM.Rd @@ -11,7 +11,8 @@ cpmCLAMPFBM(fbm_counts, block_size = 1000, ncores = 1) \item{block_size}{Integer; columns per block (default 1000).} -\item{ncores}{Integer; number of cores to use for parallel operations (default 1).} +\item{ncores}{Integer; number of cores to use for parallel operations +(default 1).} } \value{ Invisibly returns the modified FBM (now holding CPM values). @@ -23,7 +24,7 @@ Compute CPM on a file-backed matrix for CLAMP (in-place) library(bigstatsr) mat <- matrix(c(10, 20, 30, 40, 50, 60), nrow = 2, - dimnames = list(c('gene1', 'gene2'), paste0('sample', seq_len(3))) + dimnames = list(c("gene1", "gene2"), paste0("sample", seq_len(3))) ) fbm <- FBM(nrow(mat), ncol(mat), init = mat) cpmCLAMPFBM(fbm, block_size = 1) diff --git a/man/crossVal.Rd b/man/crossVal.Rd index 48f140b..f5b0e9c 100644 --- a/man/crossVal.Rd +++ b/man/crossVal.Rd @@ -7,22 +7,28 @@ crossVal(clampRes, priorMat, priorMatcv) } \arguments{ -\item{clampRes}{A list containing \code{U} (loadings) and \code{Z} (scores) from a CLAMP model.} +\item{clampRes}{A list containing \code{U} (loadings) and \code{Z} +(scores) from a CLAMP model.} -\item{priorMat}{A binary matrix (genes x pathways) indicating original pathway annotations.} +\item{priorMat}{A binary matrix (genes x pathways) indicating original +pathway annotations.} -\item{priorMatcv}{A version of \code{priorMat} used to mask held-out annotations for cross-validation.} +\item{priorMatcv}{A version of \code{priorMat} used to mask held-out +annotations for cross-validation.} } \value{ A list with: \describe{ \item{\code{Uauc}}{Matrix of AUC values (pathways x LVs)} \item{\code{Upval}}{Matrix of \code{-log10(p)} values (pathways x LVs)} -\item{\code{summary}}{Data frame with pathway, LV index, AUC, p-value, and FDR} +\item{\code{summary}}{Data frame with pathway, LV index, AUC, p-value, +and FDR} } } \description{ -Evaluates how well each latent variable in a CLAMP model captures held-out pathway annotations, -using cross-validation over the prior matrix. For each latent variable and associated pathway, -held-out genes are selected and the AUC is computed using their scores in \code{clampRes$Z}. +Evaluates how well each latent variable in a CLAMP model captures +held-out pathway annotations, using cross-validation over the prior +matrix. For each latent variable and associated pathway, held-out genes +are selected and the AUC is computed using their scores in +\code{clampRes$Z}. } diff --git a/man/cross_ZY.Rd b/man/cross_ZY.Rd index a6e68b7..02630e9 100644 --- a/man/cross_ZY.Rd +++ b/man/cross_ZY.Rd @@ -30,5 +30,5 @@ Z <- matrix(rnorm(genes * k), nrow = genes) # Compute Z^T Y res1 <- cross_ZY(Y, Z) -dim(res1) # k × samples +dim(res1) # k × samples } diff --git a/man/filterFBM.Rd b/man/filterFBM.Rd index 1b4eae0..da651fd 100644 --- a/man/filterFBM.Rd +++ b/man/filterFBM.Rd @@ -21,11 +21,14 @@ filterFBM( \item{keep_samples_idx}{Optional integer vector of column indices to retain. Default is \code{filtered_fbm}.} -\item{mean_cutoff}{Optional minimum mean threshold; rows with means below this are removed.} +\item{mean_cutoff}{Optional minimum mean threshold; rows with means below +this are removed.} -\item{var_cutoff}{Optional minimum variance threshold; rows with variances below this are removed.} +\item{var_cutoff}{Optional minimum variance threshold; rows with variances +below this are removed.} -\item{backingfile}{A character string specifying the filename (without extension) for the new FBM.} +\item{backingfile}{A character string specifying the filename (without +extension) for the new FBM.} } \value{ A list with: @@ -35,18 +38,24 @@ A list with: } } \description{ -Filters an FBM based on row-level mean and variance thresholds, returning a new FBM +Filters an FBM based on row-level mean and variance thresholds, returning +a new FBM with only the selected rows. } \details{ -This function creates a new FBM and copies over only the rows that pass the filtering criteria. +This function creates a new FBM and copies over only the rows that pass +the filtering criteria. The original FBM is unchanged. } \examples{ -\donttest{ -library(bigstatsr) -fbm <- FBM(5, 3, init = matrix(rnorm(15), nrow = 5)) -rs <- list(row_means = rowMeans(fbm[]), row_variances = apply(fbm[], 1, var)) -out <- filterFBM(fbm, rs, mean_cutoff = -0.2, var_cutoff = 0.5, backingfile = tempfile()) -} +fbm <- bigstatsr::FBM(5, 3, init = matrix(rnorm(15), nrow = 5)) +rs <- list( + row_means = rowMeans(fbm[]), + row_variances = apply(fbm[], 1, var) +) +out <- filterFBM(fbm, rs, + mean_cutoff = -0.2, var_cutoff = 0.5, + backingfile = tempfile() +) + } diff --git a/man/getAUCstats.Rd b/man/getAUCstats.Rd index 33de724..9517242 100644 --- a/man/getAUCstats.Rd +++ b/man/getAUCstats.Rd @@ -13,6 +13,6 @@ getAUCstats(summary) A named numeric vector with counts for thresholds 0.7, 0.8, and 0.9. } \description{ -Given a summary data frame from cross-validation, reports the number of latent variables -with maximum AUC exceeding 0.7, 0.8, and 0.9. +Given a summary data frame from cross-validation, reports the number of +latent variables with maximum AUC exceeding 0.7, 0.8, and 0.9. } diff --git a/man/getChat.Rd b/man/getChat.Rd index fb047c2..349567c 100644 --- a/man/getChat.Rd +++ b/man/getChat.Rd @@ -7,17 +7,20 @@ getChat(priorMat, scale = TRUE) } \arguments{ -\item{priorMat}{A numeric or sparse matrix (features x pathways) containing prior annotations.} +\item{priorMat}{A numeric or sparse matrix (features x pathways) +containing prior annotations.} -\item{scale}{Logical; if \code{TRUE} (default), standardizes the columns of \code{priorMat} +\item{scale}{Logical; if \code{TRUE} (default), standardizes the columns +of \code{priorMat} before computing \code{Chat}.} } \value{ A numeric matrix \code{Chat} of dimensions (pathways x features). } \description{ -Computes the transformation matrix \code{Chat} used to map from observed data to latent space, -based on a pseudo-inverse of the prior annotation matrix. Optionally standardizes the columns +Computes the transformation matrix \code{Chat} used to map from observed +data to latent space, based on a pseudo-inverse of the prior annotation +matrix. Optionally standardizes the columns of \code{priorMat} before computing. } \examples{ diff --git a/man/getGMT.Rd b/man/getGMT.Rd index bf619e1..19a8c8f 100644 --- a/man/getGMT.Rd +++ b/man/getGMT.Rd @@ -9,21 +9,26 @@ getGMT(url, name = NULL, cache_dir = NULL, redownload = FALSE) \arguments{ \item{url}{A character string specifying the URL to a GMT file.} -\item{name}{Optional name for the GMT file (defaults to the portion after the last '=' in the URL).} +\item{name}{Optional name for the GMT file (defaults to the portion after +the last '=' in the URL).} \item{cache_dir}{Optional directory in which to cache/download the GMT file.} \item{redownload}{Logical; if \code{TRUE}, forces re-download even if cached.} } \value{ -A named list where each element is a character vector of gene names for a given gene set. +A named list where each element is a character vector of gene +names for a given gene set. } \description{ -Downloads a Gene Matrix Transposed (GMT) file from a specified URL, reads it into R as a list, -and removes the temporary file afterward. +Downloads a Gene Matrix Transposed (GMT) file from a specified URL, reads +it into R as a list, and removes the temporary file afterward. } \examples{ -url <- 'https://maayanlab.cloud/Enrichr/geneSetLibrary?mode=text&libraryName=KEGG_2019_Human' +url <- paste0( + "https://maayanlab.cloud/Enrichr/geneSetLibrary", + "?mode=text&libraryName=KEGG_2019_Human" +) gmt_list <- getGMT(url) # list available gene sets names(gmt_list) diff --git a/man/getMatchedPathwayMat.Rd b/man/getMatchedPathwayMat.Rd index 40d0987..67fff90 100644 --- a/man/getMatchedPathwayMat.Rd +++ b/man/getMatchedPathwayMat.Rd @@ -11,10 +11,12 @@ getMatchedPathwayMat(pathMat, new.genes, min.genes = 10) \item{new.genes}{Character vector of gene names to match.} -\item{min.genes}{Minimum number of overlapping genes required to keep a pathway.} +\item{min.genes}{Minimum number of overlapping genes required to keep +a pathway.} } \value{ -A sparse matrix of dimensions \code{length(new.genes)} x filtered pathways. +A sparse matrix of dimensions \code{length(new.genes)} x +filtered pathways. } \description{ Filters a gene-by-pathway annotation matrix to retain only pathways diff --git a/man/getMatchedPathwayMat2.Rd b/man/getMatchedPathwayMat2.Rd index 38b27ab..7029386 100644 --- a/man/getMatchedPathwayMat2.Rd +++ b/man/getMatchedPathwayMat2.Rd @@ -11,10 +11,12 @@ getMatchedPathwayMat2(..., new.genes, min.genes = 10) \item{new.genes}{Character vector of gene names to match.} -\item{min.genes}{Minimum number of overlapping genes required to keep a pathway.} +\item{min.genes}{Minimum number of overlapping genes required to keep +a pathway.} } \value{ -A sparse matrix with rows = \code{new.genes} and columns = filtered pathways from all inputs. +A sparse matrix with rows = \code{new.genes} and columns = +filtered pathways from all inputs. } \description{ Filters gene-by-pathway annotation matrices to retain only pathways diff --git a/man/getMatchedPathwayMatList.Rd b/man/getMatchedPathwayMatList.Rd index 1855653..241e343 100644 --- a/man/getMatchedPathwayMatList.Rd +++ b/man/getMatchedPathwayMatList.Rd @@ -7,20 +7,25 @@ getMatchedPathwayMatList(..., new.genes, min.genes = 10) } \arguments{ -\item{...}{One or more binary matrices (genes × pathways), either base \code{matrix} +\item{...}{One or more binary matrices (genes x pathways), either base +\code{matrix} or sparse \code{Matrix} objects. Row names must be gene identifiers.} -\item{new.genes}{Character vector of gene names to align all pathway matrices to.} +\item{new.genes}{Character vector of gene names to align all pathway +matrices to.} -\item{min.genes}{Integer; minimum number of overlapping genes required for a pathway +\item{min.genes}{Integer; minimum number of overlapping genes required +for a pathway to be retained. Default is 10.} } \value{ -A sparse binary matrix with rows equal to \code{new.genes} and columns equal to +A sparse binary matrix with rows equal to \code{new.genes} and +columns equal to the union of filtered pathways from all input matrices. } \description{ -Filters one or more gene-by-pathway annotation matrices to retain only pathways +Filters one or more gene-by-pathway annotation matrices to retain only +pathways with sufficient overlap with a given target gene set. Each input matrix is restricted to \code{new.genes}, and pathways with fewer than \code{min.genes} overlapping genes are removed. The resulting matrices are column-bound into a @@ -36,15 +41,19 @@ pathways1 <- paste0("Path", 1:5) pathways2 <- paste0("Path", 6:10) mat1 <- matrix(sample(c(0, 1), 100 * 5, replace = TRUE, prob = c(0.9, 0.1)), - nrow = 100, ncol = 5, - dimnames = list(genes, pathways1)) + nrow = 100, ncol = 5, + dimnames = list(genes, pathways1) +) mat2 <- matrix(sample(c(0, 1), 100 * 5, replace = TRUE, prob = c(0.9, 0.1)), - nrow = 100, ncol = 5, - dimnames = list(genes, pathways2)) + nrow = 100, ncol = 5, + dimnames = list(genes, pathways2) +) # Define target genes (subset of total) new.genes <- sample(genes, 50) # Match and filter pathways with at least 5 genes -matched <- getMatchedPathwayMatList(mat1, mat2, new.genes = new.genes, min.genes = 5) +matched <- getMatchedPathwayMatList(mat1, mat2, + new.genes = new.genes, min.genes = 5 +) } diff --git a/man/getMatchedPathwayMatOld.Rd b/man/getMatchedPathwayMatOld.Rd index a98449a..ed7c53d 100644 --- a/man/getMatchedPathwayMatOld.Rd +++ b/man/getMatchedPathwayMatOld.Rd @@ -11,10 +11,12 @@ getMatchedPathwayMatOld(pathMat, new.genes, min.genes = 10) \item{new.genes}{Character vector of gene names to match.} -\item{min.genes}{Minimum number of overlapping genes required to keep a pathway.} +\item{min.genes}{Minimum number of overlapping genes required to keep +a pathway.} } \value{ -A sparse matrix of dimensions \code{length(new.genes)} x filtered pathways. +A sparse matrix of dimensions \code{length(new.genes)} x +filtered pathways. } \description{ Filters a gene-by-pathway annotation matrix to retain only pathways diff --git a/man/getMaxAUC.Rd b/man/getMaxAUC.Rd index d31082d..db9b977 100644 --- a/man/getMaxAUC.Rd +++ b/man/getMaxAUC.Rd @@ -9,12 +9,13 @@ getMaxAUC(summary, verbose = FALSE) \arguments{ \item{summary}{A data frame (e.g., from \code{crossVal()}) .} -\item{verbose}{Logical; if \code{TRUE}, prints counts of LVs exceeding AUC thresholds. Default is \code{FALSE}.} +\item{verbose}{Logical; if \code{TRUE}, prints counts of LVs exceeding AUC +thresholds. Default is \code{FALSE}.} } \value{ A data frame with columns LV index and max_AUC. } \description{ -Summarizes a cross-validation results data frame to extract the highest AUC value -associated with each latent variable (LV). +Summarizes a cross-validation results data frame to extract the highest +AUC value associated with each latent variable (LV). } diff --git a/man/getScaleFromSVs.Rd b/man/getScaleFromSVs.Rd index 39e5d68..aa15ca9 100644 --- a/man/getScaleFromSVs.Rd +++ b/man/getScaleFromSVs.Rd @@ -19,7 +19,8 @@ A numeric scalar giving the estimated scale. If linear extrapolation is unreliable, returns \code{sv[ceiling(0.75 * length(sv))]}. } \description{ -This function estimates a characteristic scale from a vector of singular values +This function estimates a characteristic scale from a vector of singular +values by fitting a linear model to the tail and extrapolating to length \code{n}. The median of the extrapolated values is returned as the estimate. If no sufficiently linear tail is detected (based on \code{min_r2}) or diff --git a/man/gmtListToSparseMat.Rd b/man/gmtListToSparseMat.Rd index 21310bc..cf35b6e 100644 --- a/man/gmtListToSparseMat.Rd +++ b/man/gmtListToSparseMat.Rd @@ -7,25 +7,26 @@ gmtListToSparseMat(gmtList) } \arguments{ -\item{gmtList}{A nested list of gene sets. Outer names are gene set names; each entry is a character -vector of gene names.} +\item{gmtList}{A nested list of gene sets. Outer names are gene set names; +each entry is a character vector of gene names.} } \value{ A sparse binary matrix with genes as rows and gene sets as columns. } \description{ -Converts a list of named gene sets (e.g., from \code{getGMT()}) into a sparse binary matrix -where rows are genes, columns are gene sets, and entries are 1 if the gene is in the set. +Converts a list of named gene sets (e.g., from \code{getGMT()}) into a sparse +binary matrix where rows are genes, columns are gene sets, and entries +are 1 if the gene is in the set. } \examples{ # define a simple nested GMT list gmt1 <- list( - PathwayA = c('Gene1', 'Gene2', 'Gene3'), - PathwayB = c('Gene2', 'Gene4') + PathwayA = c("Gene1", "Gene2", "Gene3"), + PathwayB = c("Gene2", "Gene4") ) gmt2 <- list( - PathwayC = c('Gene1', 'Gene4'), - PathwayD = c('Gene3', 'Gene5') + PathwayC = c("Gene1", "Gene4"), + PathwayD = c("Gene3", "Gene5") ) # combine into a nested list nestedList <- list(gmt1 = gmt1, gmt2 = gmt2) diff --git a/man/majorCellTypes.Rd b/man/majorCellTypes.Rd index e0caa29..4419f6e 100644 --- a/man/majorCellTypes.Rd +++ b/man/majorCellTypes.Rd @@ -6,7 +6,8 @@ \title{Major cell-type annotations} \format{ A factor (or character) vector of length N, -where each element corresponds to a sample and indicates its major cell type. +where each element corresponds to a sample and indicates its major +cell type. } \usage{ data(majorCellTypes) diff --git a/man/max_correspondence_greedy.Rd b/man/max_correspondence_greedy.Rd index 3f9475f..9fa9fa4 100644 --- a/man/max_correspondence_greedy.Rd +++ b/man/max_correspondence_greedy.Rd @@ -7,12 +7,14 @@ max_correspondence_greedy(cor_mat) } \arguments{ -\item{cor_mat}{A square numeric matrix of pairwise correlations (rows = items, cols = items).} +\item{cor_mat}{A square numeric matrix of pairwise correlations +(rows = items, cols = items).} } \value{ A vector of assignments (integer indices). } \description{ -Finds a one-to-one assignment (permutation) between rows and columns of a square correlation matrix -that maximizes the total correlation score, using a greedy algorithm. +Finds a one-to-one assignment (permutation) between rows and columns of a +square correlation matrix that maximizes the total correlation score, +using a greedy algorithm. } diff --git a/man/mymessage.Rd b/man/mymessage.Rd index 31a7b6e..27710f7 100644 --- a/man/mymessage.Rd +++ b/man/mymessage.Rd @@ -13,5 +13,6 @@ mymessage(...) Invisibly returns NULL. Called for side effects (messages). } \description{ -Wrapper around \code{message()} that pastes arguments together into a single string. +Wrapper around \code{message()} that pastes arguments together into a single +string. } diff --git a/man/num.pc.Rd b/man/num.pc.Rd index 45b950e..2538007 100644 --- a/man/num.pc.Rd +++ b/man/num.pc.Rd @@ -7,7 +7,8 @@ num.pc(data, method = c("elbow", "permutation"), B = 20, seed = NULL) } \arguments{ -\item{data}{Either a matrix (e.g. z-scored data) or an SVD result (list with $d).} +\item{data}{Either a matrix (e.g. z-scored data) or an SVD result +(list with $d).} \item{method}{One of "elbow" (fast) or "permutation" (slower).} diff --git a/man/panDB.Rd b/man/panDB.Rd index 92e5c36..544b759 100644 --- a/man/panDB.Rd +++ b/man/panDB.Rd @@ -5,21 +5,23 @@ \alias{panDB} \title{panDB gene-set database} \format{ -A named list of length M, where each element is a gene-set collection. +A named list of length M, where each element is a gene-set +collection. } \usage{ data(panDB) } \value{ -A list of gene-set collections used as priors for pathway-informed modeling. +A list of gene-set collections used as priors for pathway-informed +modeling. } \description{ -A list of curated pathway and biological process gene sets used as prior knowledge -for CLAMP and other latent-variable models. +A list of curated pathway and biological process gene sets used as prior +knowledge for CLAMP and other latent-variable models. } \details{ -Each element corresponds to a functional collection (e.g., KEGG, Reactome, GO), -where each entry contains a character vector of gene symbols. +Each element corresponds to a functional collection (e.g., KEGG, Reactome, +GO), where each entry contains a character vector of gene symbols. } \examples{ data(panDB) diff --git a/man/pinv.ridge.Rd b/man/pinv.ridge.Rd index a837b64..347474a 100644 --- a/man/pinv.ridge.Rd +++ b/man/pinv.ridge.Rd @@ -10,7 +10,8 @@ pinv.ridge(m, alpha = 0) \item{m}{A symmetric numeric matrix (e.g., from \code{crossprod()}).} \item{alpha}{Non-negative scalar specifying the ridge penalty. -A small positive value stabilizes the inversion by shrinking large singular values.} +A small positive value stabilizes the inversion by shrinking large +singular values.} } \value{ A numeric matrix representing the ridge-regularized diff --git a/man/plotTopZ_Complex.Rd b/man/plotTopZ_Complex.Rd index ff69403..d8259b3 100644 --- a/man/plotTopZ_Complex.Rd +++ b/man/plotTopZ_Complex.Rd @@ -20,7 +20,8 @@ plotTopZ_Complex( ) } \arguments{ -\item{clampRes}{A CLAMP result list containing matrices \code{Z}, \code{U}, etc.} +\item{clampRes}{A CLAMP result list containing matrices \code{Z}, +\code{U}, etc.} \item{data}{Expression matrix with genes as rows.} @@ -34,7 +35,8 @@ plotTopZ_Complex( \item{allLVs}{Logical; include all LVs.} -\item{Zheat}{Logical; whether to include the Z matrix as an additional heatmap.} +\item{Zheat}{Logical; whether to include the Z matrix as an additional +heatmap.} \item{LV.names}{Optional character vector for LV names.} @@ -63,22 +65,28 @@ lvs <- paste0("LV", 1:3) # Simulated Z (gene loadings) and U (pathway loadings) Z <- matrix(rnorm(100 * 3), nrow = 100, dimnames = list(genes, lvs)) -U <- matrix(abs(rnorm(50 * 3)), nrow = 50, - dimnames = list(paste0("Path", 1:50), lvs)) +U <- matrix(abs(rnorm(50 * 3)), + nrow = 50, + dimnames = list(paste0("Path", 1:50), lvs) +) # Expression data -expr_data <- matrix(rnorm(100 * 20), nrow = 100, - dimnames = list(genes, samples)) +expr_data <- matrix(rnorm(100 * 20), + nrow = 100, + dimnames = list(genes, samples) +) # Binary gene × pathway matrix priorMat <- matrix(sample(0:1, 100 * 50, replace = TRUE, prob = c(0.9, 0.1)), - nrow = 100, ncol = 50, - dimnames = list(genes, paste0("Path", 1:50))) + nrow = 100, ncol = 50, + dimnames = list(genes, paste0("Path", 1:50)) +) # Create a CLAMP-like result list clampRes <- list(Z = Z, U = U) # Plot top genes and pathway memberships plotTopZ_Complex(clampRes, expr_data, priorMat, - top = 5, top.pathway = 3, index = 1:2, Zheat = TRUE) + top = 5, top.pathway = 3, index = 1:2, Zheat = TRUE +) } diff --git a/man/preprocessCLAMP.Rd b/man/preprocessCLAMP.Rd index 3f5d357..11069b9 100644 --- a/man/preprocessCLAMP.Rd +++ b/man/preprocessCLAMP.Rd @@ -9,9 +9,11 @@ preprocessCLAMP(Y, mean_cutoff = 0, var_cutoff = 0) \arguments{ \item{Y}{Numeric matrix of gene expression (rows = genes, cols = samples)} -\item{mean_cutoff}{Numeric. Minimum row-mean required to keep a gene (default 0).} +\item{mean_cutoff}{Numeric. Minimum row-mean required to keep a gene +(default 0).} -\item{var_cutoff}{Numeric. Minimum row-variance required to keep a gene (default 0).} +\item{var_cutoff}{Numeric. Minimum row-variance required to keep a gene +(default 0).} } \value{ A list with components: @@ -35,7 +37,7 @@ mat <- matrix( 4, 8, 13 ), nrow = 4, byrow = FALSE, - dimnames = list(paste0('gene', seq_len(4)), paste0('sample', seq_len(3))) + dimnames = list(paste0("gene", seq_len(4)), paste0("sample", seq_len(3))) ) # keep genes with mean >= 6 and variance >= 2 diff --git a/man/preprocessCLAMPFBM.Rd b/man/preprocessCLAMPFBM.Rd index 20d4dd6..fab4685 100644 --- a/man/preprocessCLAMPFBM.Rd +++ b/man/preprocessCLAMPFBM.Rd @@ -16,26 +16,33 @@ preprocessCLAMPFBM( \arguments{ \item{fbm}{A bigstatsr::FBM (genes x samples), possibly read-only.} -\item{mean_cutoff}{Numeric or NULL. Minimum row mean to keep (NULL = no mean filter).} +\item{mean_cutoff}{Numeric or NULL. Minimum row mean to keep +(NULL = no mean filter).} -\item{var_cutoff}{Numeric or NULL. Minimum row variance to keep (NULL = no var filter).} +\item{var_cutoff}{Numeric or NULL. Minimum row variance to keep +(NULL = no var filter).} -\item{backingfile}{Character or NULL. Base name for the \emph{copy} FBM and filtered FBM on disk. -If NULL, defaults to paste0(fbm$backingfile, '_preproc') and '_filtered'.} +\item{backingfile}{Character or NULL. Base name for the \emph{copy} FBM and +filtered FBM on disk. If NULL, defaults to +paste0(fbm$backingfile, '_preproc') and '_filtered'.} -\item{block_size}{Number of rows to process at a time when copying data. Default is 1000.} +\item{block_size}{Number of rows to process at a time when copying data. +Default is 1000.} -\item{ncores}{Integer; number of cores to use for parallel operations (default 1).} +\item{ncores}{Integer; number of cores to use for parallel operations +(default 1).} } \value{ A list with: \item{fbm_filtered}{The filtered FBM (writable).} \item{rowStats}{List with row_means & row_variances for fbm_filtered.} -\item{kept_rows}{Integer vector of original row indices that were retained.} +\item{kept_rows}{Integer vector of original row indices that were +retained.} } \description{ -Makes a writable copy of the input FBM, cleans it (log2 transform if needed, fill NAs), -filters rows by mean/variance, and returns the filtered FBM plus stats and indices. +Makes a writable copy of the input FBM, cleans it (log2 transform if +needed, fill NAs), filters rows by mean/variance, and returns the filtered +FBM plus stats and indices. } \examples{ library(bigstatsr) @@ -47,7 +54,7 @@ mat <- matrix( 100, 200, 300 # geneC ), nrow = 3, byrow = TRUE, - dimnames = list(c('geneA', 'geneB', 'geneC'), paste0('s', seq_len(3))) + dimnames = list(c("geneA", "geneB", "geneC"), paste0("s", seq_len(3))) ) fbm <- FBM(nrow(mat), ncol(mat), init = mat) diff --git a/man/projectCLAMP.Rd b/man/projectCLAMP.Rd index 0914835..7e2098b 100644 --- a/man/projectCLAMP.Rd +++ b/man/projectCLAMP.Rd @@ -20,9 +20,11 @@ projectCLAMP( \item{newdata}{A gene expression matrix (genes x samples) to be projected. Can be a standard matrix, sparse matrix, or FBM/big.matrix.} -\item{scale}{Optional numeric multiplier for the L2 regularization terms. Default is 1.} +\item{scale}{Optional numeric multiplier for the L2 regularization terms. +Default is 1.} -\item{ncores}{Number of cores to use for parallel computation (only used if newdata is an FBM). +\item{ncores}{Number of cores to use for parallel computation (only used +if newdata is an FBM). Default is 1.} \item{align}{Logical; if \code{TRUE} (default), row names shared by @@ -34,7 +36,8 @@ available, dimensions must already match.} rows are used for projection.} } \value{ -A matrix \code{B} of projected latent loadings (LVs x samples) for the new dataset. +A matrix \code{B} of projected latent loadings (LVs x samples) +for the new dataset. } \description{ Computes the latent loadings \code{B} for new gene expression data using @@ -51,12 +54,16 @@ subsetting, the computation is optimized using } \examples{ # fit a tiny CLAMP model for projection -Y0 <- matrix(rnorm(5 * 3), nrow = 5, - dimnames = list(paste0("Gene", 1:5), paste0("S", 1:3))) +Y0 <- matrix(rnorm(5 * 3), + nrow = 5, + dimnames = list(paste0("Gene", 1:5), paste0("S", 1:3)) +) base <- CLAMPbase(Y0, clamp_k = 2, max.iter = 1, trace = FALSE) # new data can be provided in a different row order -newY <- matrix(rnorm(5 * 2), nrow = 5, - dimnames = list(rev(rownames(Y0)), paste0("N", 1:2))) +newY <- matrix(rnorm(5 * 2), + nrow = 5, + dimnames = list(rev(rownames(Y0)), paste0("N", 1:2)) +) projB <- projectCLAMP(base, newdata = newY) # check dimensions: 2 latent vars x 2 samples dim(projB) diff --git a/man/read_gmt.Rd b/man/read_gmt.Rd index be4522b..e034a49 100644 --- a/man/read_gmt.Rd +++ b/man/read_gmt.Rd @@ -18,12 +18,14 @@ Parses a local GMT file and returns a list of gene sets. Each gene set is represented as a character vector of unique gene names. } \examples{ -# Bioconductor requires runnable examples. +# Bioconductor requires runnable examples. # We create a dummy GMT file for this example: gmt_file <- tempfile(fileext = ".gmt") writeLines( - c("PATHWAY_A\thttp://link.com\tGENE1\tGENE2\tGENE3", - "PATHWAY_B\thttp://link.com\tGENE2\tGENE4"), + c( + "PATHWAY_A\thttp://link.com\tGENE1\tGENE2\tGENE3", + "PATHWAY_B\thttp://link.com\tGENE2\tGENE4" + ), con = gmt_file ) diff --git a/man/ridge_B.Rd b/man/ridge_B.Rd index e4d0287..d482f75 100644 --- a/man/ridge_B.Rd +++ b/man/ridge_B.Rd @@ -27,7 +27,10 @@ samples <- paste0("S", 1:20) k <- 5 Y <- matrix(rnorm(50 * 20), nrow = 50, dimnames = list(genes, samples)) -Z <- matrix(rnorm(50 * k), nrow = 50, dimnames = list(genes, paste0("LV", 1:k))) +Z <- matrix(rnorm(50 * k), + nrow = 50, + dimnames = list(genes, paste0("LV", 1:k)) +) lambda <- 0.1 L2k <- diag(lambda, k) diff --git a/man/rotateSVD.Rd b/man/rotateSVD.Rd index b862440..44a0740 100644 --- a/man/rotateSVD.Rd +++ b/man/rotateSVD.Rd @@ -7,13 +7,15 @@ rotateSVD(svdres) } \arguments{ -\item{svdres}{A list as returned by \code{svd()}, with components \code{u}, \code{d}, and \code{v}.} +\item{svdres}{A list as returned by \code{svd()}, with components +\code{u}, \code{d}, and \code{v}.} } \value{ -A modified \code{svd}‐result list where each column of \code{$u} has been sign‐flipped -so that its entries sum to a nonnegative value; \code{$v} is flipped correspondingly. +A modified \code{svd}-result list where each column of \code{$u} +has been sign-flipped so that its entries sum to a nonnegative value; +\code{$v} is flipped correspondingly. } \description{ -Ensures consistency in SVD output by flipping signs so that each left singular vector -has a majority of positive entries. +Ensures consistency in SVD output by flipping signs so that each left +singular vector has a majority of positive entries. } diff --git a/man/select_clamp_k.Rd b/man/select_clamp_k.Rd index e688af0..c94878a 100644 --- a/man/select_clamp_k.Rd +++ b/man/select_clamp_k.Rd @@ -51,3 +51,10 @@ via \code{PCAtools::chooseGavishDonoho()}. Requires the raw \code{data} matrix \code{clamp_k <- min(floor(k * 1.5), svd_k)}, scale from the fit.} } } +\examples{ +set.seed(1) +Y <- matrix(rnorm(100 * 30), nrow = 100, ncol = 30) +svdres <- compute_svd(Y, k = 25) +select_clamp_k(svdres, n_samples = ncol(Y), svd_k = 25) + +} diff --git a/man/solveU.Rd b/man/solveU.Rd index 2cdaddd..a859765 100644 --- a/man/solveU.Rd +++ b/man/solveU.Rd @@ -28,42 +28,56 @@ solveU( \arguments{ \item{Z}{A numeric matrix with features (rows) and samples (columns).} -\item{Chat}{(Optional) Precomputed pseudo-inverse of \code{priorMat}; if \code{NULL}, -it is calculated using ridge regularization.} +\item{Chat}{(Optional) Precomputed pseudo-inverse of \code{priorMat}; +if \code{NULL}, it is calculated using ridge regularization.} -\item{priorMat}{A numeric matrix with prior information (features x pathways).} +\item{priorMat}{A numeric matrix with prior information +(features x pathways).} -\item{penalty.factor}{Optional penalty weights for features in \code{priorMat}.} +\item{penalty.factor}{Optional penalty weights for features in +\code{priorMat}.} -\item{pathwaySelection}{Method to select candidate pathways: \code{"fast"} (default) or \code{"complete"}.} +\item{pathwaySelection}{Method to select candidate pathways: \code{"fast"} +(default) or \code{"complete"}.} -\item{alpha}{Elastic net mixing parameter (0 = ridge, 1 = lasso). Default is 0.9.} +\item{alpha}{Elastic net mixing parameter (0 = ridge, 1 = lasso). +Default is 0.9.} -\item{maxPath}{Maximum number of pathways/features selected per column. Default is 10.} +\item{maxPath}{Maximum number of pathways/features selected per column. +Default is 10.} \item{nfolds}{Number of cross-validation folds. Default is 5.} -\item{useSE}{Whether to use the 1-standard-error rule for lambda selection. Default is \code{FALSE}.} +\item{useSE}{Whether to use the 1-standard-error rule for lambda selection. +Default is \code{FALSE}.} -\item{top}{If set, sets to 0 all but the top entries of \code{Z} per column before fitting.} +\item{top}{If set, sets to 0 all but the top entries of \code{Z} per +column before fitting.} -\item{binary}{If \code{TRUE}, fits a binomial model (e.g., classification) to \code{Z}>0. -Can be used incombination with \code{top}. Default is \code{FALSE}.} +\item{binary}{If \code{TRUE}, fits a binomial model (e.g., classification) +to \code{Z}>0. Can be used in combination with \code{top}. +Default is \code{FALSE}.} \item{nlambda}{Number of lambda values for glmnet. Default is 20.} -\item{scale}{Whether to standardize predictors in glmnet. Default is \code{TRUE}.} +\item{scale}{Whether to standardize predictors in glmnet. +Default is \code{TRUE}.} -\item{refit}{Whether to perform relaxed refitting using selected predictors. Default is \code{TRUE}.} +\item{refit}{Whether to perform relaxed refitting using selected +predictors. Default is \code{TRUE}.} -\item{Uprev}{(Optional) Previous U matrix to reuse. In this mode only the columns of \code{U} -that are all zero are estimated. Used internally in \code{CLAMP}.} +\item{Uprev}{(Optional) Previous U matrix to reuse. In this mode only +the columns of \code{U} that are all zero are estimated. Used +internally in \code{CLAMP}.} -\item{useAUC}{Logical; whether to compute pathway–LV associations using AUC (default TRUE) instead of OLS.} +\item{useAUC}{Logical; whether to compute pathway-LV associations using +AUC (default TRUE) instead of OLS.} -\item{intercept}{Logical; whether to include an intercept term in glmnet models. Default is TRUE.} +\item{intercept}{Logical; whether to include an intercept term in glmnet +models. Default is TRUE.} -\item{...}{Additional arguments passed to \code{glmnet()} or \code{cv.glmnet()}.} +\item{...}{Additional arguments passed to \code{glmnet()} or +\code{cv.glmnet()}.} } \value{ A list with one element: @@ -73,30 +87,32 @@ Columns are named \code{LV1}, \code{LV2}, ...} } } \description{ -For each column of a target matrix \code{Z} using pathway or prior annotation \code{priorMat}. -It performs regularization selection using cross-validation and can apply either -Supports continuous or binary response models. Relaxed refitting is supported for final -coefficient estimation. +For each column of a target matrix \code{Z} using pathway or prior +annotation \code{priorMat}. It performs regularization selection using +cross-validation and can apply either Supports continuous or binary +response models. Relaxed refitting is supported for final coefficient +estimation. } \examples{ set.seed(123) genes <- paste0("G", 1:200) -lvs <- paste0("LV", 1:4) +lvs <- paste0("LV", 1:4) paths <- paste0("Path", 1:60) Z <- matrix(rnorm(200 * 4), nrow = 200, dimnames = list(genes, lvs)) priorMat <- matrix(rbinom(200 * 60, 1, 0.07), - nrow = 200, dimnames = list(genes, paths)) + nrow = 200, dimnames = list(genes, paths) +) fit1 <- solveU( - Z = Z, - priorMat = priorMat, - pathwaySelection = "fast", - alpha = 0.9, - maxPath = 10, - nfolds = 5, - binary = FALSE, - refit = TRUE + Z = Z, + priorMat = priorMat, + pathwaySelection = "fast", + alpha = 0.9, + maxPath = 10, + nfolds = 5, + binary = FALSE, + refit = TRUE ) } diff --git a/man/winsor_topk.Rd b/man/winsor_topk.Rd index a051e36..bbf9abe 100644 --- a/man/winsor_topk.Rd +++ b/man/winsor_topk.Rd @@ -12,7 +12,8 @@ winsor_topk(M, k) \item{k}{Integer; number of top elements to cap. Must be >= 1 and <= nrow(M).} } \value{ -A numeric matrix of the same dimensions as \code{M}, winsorized per column. +A numeric matrix of the same dimensions as \code{M}, winsorized +per column. } \description{ For each column, replaces values greater than the k-th largest @@ -20,8 +21,10 @@ entry with that threshold. } \examples{ set.seed(123) -M <- matrix(rnorm(20 * 5, mean = 0, sd = 2), nrow = 20, - dimnames = list(paste0("Gene", 1:20), paste0("S", 1:5))) +M <- matrix(rnorm(20 * 5, mean = 0, sd = 2), + nrow = 20, + dimnames = list(paste0("Gene", 1:20), paste0("S", 1:5)) +) # Display column maxima before winsorization apply(M, 2, max) diff --git a/man/zscoreCLAMP.Rd b/man/zscoreCLAMP.Rd index 15c7cd1..18ebc23 100644 --- a/man/zscoreCLAMP.Rd +++ b/man/zscoreCLAMP.Rd @@ -7,13 +7,15 @@ zscoreCLAMP(Y_filtered, rowStats) } \arguments{ -\item{Y_filtered}{Numeric matrix (genes x samples) returned by preprocessCLAMP} +\item{Y_filtered}{Numeric matrix (genes x samples) returned by +preprocessCLAMP} \item{rowStats}{Data frame with numeric columns \code{mean} and \code{variance}, row-named to match \code{rownames(Y_filtered)}} } \value{ -Numeric matrix of the same dimensions as Y_filtered, with each row centered and scaled. +Numeric matrix of the same dimensions as Y_filtered, with each +row centered and scaled. } \description{ Centers each gene to mean 0 and scales to unit variance. @@ -26,7 +28,7 @@ Y <- matrix( 8, 10, 12 # gene2 counts ), nrow = 2, byrow = TRUE, - dimnames = list(c('gene1', 'gene2'), paste0('sample', seq_len(3))) + dimnames = list(c("gene1", "gene2"), paste0("sample", seq_len(3))) ) # compute per‐gene mean and variance diff --git a/man/zscoreCLAMPFBM.Rd b/man/zscoreCLAMPFBM.Rd index 9c66c2b..b5cab81 100644 --- a/man/zscoreCLAMPFBM.Rd +++ b/man/zscoreCLAMPFBM.Rd @@ -13,7 +13,8 @@ zscoreCLAMPFBM(fbm_filtered, rowStats, chunk_size = 1000, ncores = 1) \item{chunk_size}{Columns per block (default 1000).} -\item{ncores}{Integer; number of cores to use for parallel operations (default 1).} +\item{ncores}{Integer; number of cores to use for parallel operations +(default 1).} } \value{ A normalized FBM with z-scored rows. From bc2e3aac0418629291a29e5b51b5e655a9787c24 Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Thu, 7 May 2026 11:41:20 -0600 Subject: [PATCH 17/20] Adding user choice on compute_svd --- R/utils.R | 36 ++++++++++++++++++++++++++---------- man/compute_svd.Rd | 15 +++++++++++---- 2 files changed, 37 insertions(+), 14 deletions(-) diff --git a/R/utils.R b/R/utils.R index 246d318..6bcb3cf 100644 --- a/R/utils.R +++ b/R/utils.R @@ -1082,14 +1082,17 @@ select_svd_k <- function(Y) { #' Compute a truncated SVD for a CLAMP input matrix #' -#' Dispatches to the appropriate SVD backend based on the class of `Y`: +#' By default, the SVD backend is auto-detected from the class of `Y`: #' `bigstatsr::big_SVD` for `FBM` objects, `irlba::irlba` for sparse -#' `dgCMatrix` objects, and `rsvd::rsvd` otherwise. Used by the CLAMP -#' solvers so that the SVD step is handled in one place. +#' `dgCMatrix` objects, and `rsvd::rsvd` otherwise. A specific backend +#' can be forced via `method`. Used by the CLAMP solvers so that the SVD +#' step is handled in one place. #' #' @param Y A matrix-like object (dense matrix, `dgCMatrix`, or `FBM`). #' @param k Integer number of components to compute. If `NULL` (the #' default), `select_svd_k(Y)` is used. +#' @param method One of `"rsvd"`, `"irlba"`, or `"big_SVD"`. If `NULL` +#' (the default), the backend is auto-detected from the class of `Y`. #' #' @return A list with `d`, `u`, `v` components (structure depends on the #' backend but these three fields are always present). @@ -1100,16 +1103,29 @@ select_svd_k <- function(Y) { #' res <- compute_svd(Y, k = 3) #' length(res$d) #' +#' # Force a specific backend: +#' res2 <- compute_svd(Y, k = 3, method = "rsvd") +#' #' @export -compute_svd <- function(Y, k = NULL) { +compute_svd <- function(Y, k = NULL, method = NULL) { if (is.null(k)) k <- select_svd_k(Y) - if (inherits(Y, "FBM")) { - return(bigstatsr::big_SVD(X = Y, k = k)) - } - if (inherits(Y, "dgCMatrix")) { - return(irlba::irlba(Y, nv = k)) + + if (is.null(method)) { + method <- if (inherits(Y, "FBM")) { + "big_SVD" + } else if (inherits(Y, "dgCMatrix")) { + "irlba" + } else { + "rsvd" + } } - rsvd::rsvd(Y, k = k) + method <- match.arg(method, c("rsvd", "irlba", "big_SVD")) + + switch(method, + big_SVD = bigstatsr::big_SVD(X = Y, k = k), + irlba = irlba::irlba(Y, nv = k), + rsvd = rsvd::rsvd(Y, k = k) + ) } #' Select default number of CLAMP latent variables from an SVD diff --git a/man/compute_svd.Rd b/man/compute_svd.Rd index 67152c1..2512abd 100644 --- a/man/compute_svd.Rd +++ b/man/compute_svd.Rd @@ -4,23 +4,27 @@ \alias{compute_svd} \title{Compute a truncated SVD for a CLAMP input matrix} \usage{ -compute_svd(Y, k = NULL) +compute_svd(Y, k = NULL, method = NULL) } \arguments{ \item{Y}{A matrix-like object (dense matrix, \code{dgCMatrix}, or \code{FBM}).} \item{k}{Integer number of components to compute. If \code{NULL} (the default), \code{select_svd_k(Y)} is used.} + +\item{method}{One of \code{"rsvd"}, \code{"irlba"}, or \code{"big_SVD"}. If \code{NULL} +(the default), the backend is auto-detected from the class of \code{Y}.} } \value{ A list with \code{d}, \code{u}, \code{v} components (structure depends on the backend but these three fields are always present). } \description{ -Dispatches to the appropriate SVD backend based on the class of \code{Y}: +By default, the SVD backend is auto-detected from the class of \code{Y}: \code{bigstatsr::big_SVD} for \code{FBM} objects, \code{irlba::irlba} for sparse -\code{dgCMatrix} objects, and \code{rsvd::rsvd} otherwise. Used by the CLAMP -solvers so that the SVD step is handled in one place. +\code{dgCMatrix} objects, and \code{rsvd::rsvd} otherwise. A specific backend +can be forced via \code{method}. Used by the CLAMP solvers so that the SVD +step is handled in one place. } \examples{ set.seed(1) @@ -28,4 +32,7 @@ Y <- matrix(rnorm(100), nrow = 20, ncol = 5) res <- compute_svd(Y, k = 3) length(res$d) +# Force a specific backend: +res2 <- compute_svd(Y, k = 3, method = "rsvd") + } From 6920eb4d4de4553fb5ad6efb528cce1329fddacc Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Sat, 9 May 2026 10:35:08 -0600 Subject: [PATCH 18/20] Adding gha for website and logos using favicon --- .github/workflows/pkgdown.yaml | 47 +++++++++++++++++++ pkgdown/favicon/apple-touch-icon-120x120.png | Bin 0 -> 9946 bytes pkgdown/favicon/apple-touch-icon-152x152.png | Bin 0 -> 13525 bytes pkgdown/favicon/apple-touch-icon-180x180.png | Bin 0 -> 15918 bytes pkgdown/favicon/apple-touch-icon-60x60.png | Bin 0 -> 3995 bytes pkgdown/favicon/apple-touch-icon-76x76.png | Bin 0 -> 5304 bytes pkgdown/favicon/apple-touch-icon.png | Bin 0 -> 15918 bytes pkgdown/favicon/favicon-16x16.png | Bin 0 -> 874 bytes pkgdown/favicon/favicon-32x32.png | Bin 0 -> 1663 bytes pkgdown/favicon/favicon.ico | Bin 0 -> 13102 bytes 10 files changed, 47 insertions(+) create mode 100644 .github/workflows/pkgdown.yaml create mode 100644 pkgdown/favicon/apple-touch-icon-120x120.png create mode 100644 pkgdown/favicon/apple-touch-icon-152x152.png create mode 100644 pkgdown/favicon/apple-touch-icon-180x180.png create mode 100644 pkgdown/favicon/apple-touch-icon-60x60.png create mode 100644 pkgdown/favicon/apple-touch-icon-76x76.png create mode 100644 pkgdown/favicon/apple-touch-icon.png create mode 100644 pkgdown/favicon/favicon-16x16.png create mode 100644 pkgdown/favicon/favicon-32x32.png create mode 100644 pkgdown/favicon/favicon.ico diff --git a/.github/workflows/pkgdown.yaml b/.github/workflows/pkgdown.yaml new file mode 100644 index 0000000..16c6c8b --- /dev/null +++ b/.github/workflows/pkgdown.yaml @@ -0,0 +1,47 @@ +# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples +# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help +on: + push: + branches: [main, master] + pull_request: + release: + types: [published] + workflow_dispatch: + +name: pkgdown.yaml + +permissions: read-all + +jobs: + pkgdown: + runs-on: ubuntu-latest + # Only restrict concurrency for non-PR jobs + concurrency: + group: pkgdown-${{ github.event_name != 'pull_request' || github.run_id }} + env: + GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} + permissions: + contents: write + steps: + - uses: actions/checkout@v6 + + - uses: r-lib/actions/setup-pandoc@v2 + + - uses: r-lib/actions/setup-r@v2 + + - uses: r-lib/actions/setup-r-dependencies@v2 + with: + extra-packages: any::pkgdown, local::. + needs: website + + - name: Build site + run: pkgdown::build_site_github_pages(new_process = FALSE, install = FALSE) + shell: Rscript {0} + + - name: Deploy to GitHub pages 🚀 + if: github.event_name != 'pull_request' + uses: 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Start at https://github.com/r-lib/actions#where-to-find-help on: push: - branches: [main, master] + branches: [bioconductor_submission] pull_request: release: types: [published] From e0d731e87748fbf1e079443adf4a4aa48593b22d Mon Sep 17 00:00:00 2001 From: Alexander McKim Date: Sat, 9 May 2026 11:16:47 -0600 Subject: [PATCH 20/20] workflow remote point to CLAMPData --- .github/workflows/pkgdown.yaml | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/.github/workflows/pkgdown.yaml b/.github/workflows/pkgdown.yaml index d99c7af..9c57fa3 100644 --- a/.github/workflows/pkgdown.yaml +++ b/.github/workflows/pkgdown.yaml @@ -31,7 +31,12 @@ jobs: - uses: r-lib/actions/setup-r-dependencies@v2 with: - extra-packages: any::pkgdown, local::. + # Remove pivlab/CLAMPData once CLAMPData is on Bioconductor; + # it will then be picked up automatically from DESCRIPTION. + extra-packages: | + any::pkgdown + local::. + pivlab/CLAMPData needs: website - name: Build site

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