From ee21dc65044bcd1cf7d1f40004caca30af0ce121 Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Fri, 5 Jun 2026 18:12:34 +0100 Subject: [PATCH 01/32] Setup nightingale-distribution-track package --- .../nightingale-distribution-track/README.md | 7 + .../package.json | 40 ++ .../src/index.ts | 3 + .../src/nightingale-distribution-track.ts | 482 ++++++++++++++++++ .../mockData/sample-distribution-data.json | 32 ++ .../nightingale-distribution-track.test.ts | 7 + .../tsconfig.json | 7 + .../NightingaleDistributionTrack.stories.mdx | 35 ++ .../NightingaleDistributionTrack.stories.ts | 175 +++++++ 9 files changed, 788 insertions(+) create mode 100644 packages/nightingale-distribution-track/README.md create mode 100644 packages/nightingale-distribution-track/package.json create mode 100644 packages/nightingale-distribution-track/src/index.ts create mode 100644 packages/nightingale-distribution-track/src/nightingale-distribution-track.ts create mode 100644 packages/nightingale-distribution-track/tests/mockData/sample-distribution-data.json create mode 100644 packages/nightingale-distribution-track/tests/nightingale-distribution-track.test.ts create mode 100644 packages/nightingale-distribution-track/tsconfig.json create mode 100644 stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.mdx create mode 100644 stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts diff --git a/packages/nightingale-distribution-track/README.md b/packages/nightingale-distribution-track/README.md new file mode 100644 index 000000000..5bded2528 --- /dev/null +++ b/packages/nightingale-distribution-track/README.md @@ -0,0 +1,7 @@ +# nightingale-distribution-track + +[![Published on NPM](https://img.shields.io/npm/v/@nightingale-elements/nightingale-distribution-track.svg)](https://www.npmjs.com/package/@nightingale-elements/nightingale-distribution-track) + +The `nightingale-distribution-track` component ... + +TODO: diff --git a/packages/nightingale-distribution-track/package.json b/packages/nightingale-distribution-track/package.json new file mode 100644 index 000000000..05686d6e1 --- /dev/null +++ b/packages/nightingale-distribution-track/package.json @@ -0,0 +1,40 @@ +{ + "name": "@nightingale-elements/nightingale-distribution-track", + "version": "5.6.0", + "description": "Track for showing distribution of a variable on each residue position.", + "files": [ + "dist", + "src" + ], + "main": "dist/index.js", + "module": "dist/index.js", + "type": "module", + "types": "dist/index.d.ts", + "scripts": { + "build": "rollup --config ../../rollup.config.mjs", + "test": "../../node_modules/.bin/jest --config ../../jest.config.js ./tests/*" + }, + "keywords": [ + "nightingale", + "webcomponents", + "customelements" + ], + "repository": { + "type": "git", + "url": "https://github.com/ebi-webcomponents/nightingale.git" + }, + "bugs": { + "url": "https://github.com/ebi-webcomponents/nightingale/issues" + }, + "homepage": "https://ebi-webcomponents.github.io/nightingale/", + "author": "Adam Midlik ", + "license": "MIT", + "publishConfig": { + "access": "public" + }, + "sideEffects": false, + "dependencies": { + "@nightingale-elements/nightingale-new-core": "^5.6.0", + "d3": "7.9.0" + } +} diff --git a/packages/nightingale-distribution-track/src/index.ts b/packages/nightingale-distribution-track/src/index.ts new file mode 100644 index 000000000..a32bca1a0 --- /dev/null +++ b/packages/nightingale-distribution-track/src/index.ts @@ -0,0 +1,3 @@ +import NightingaleDistributionTrack, { } from "./nightingale-distribution-track"; + +export { NightingaleDistributionTrack as default }; diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts new file mode 100644 index 000000000..2632720fa --- /dev/null +++ b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts @@ -0,0 +1,482 @@ +import NightingaleElement, { + BinarySearch, + createEvent, + customElementOnce, + Refresher, + Stamp, + withCanvas, + withDimensions, + withHighlight, + withManager, + withMargin, + withPosition, + withResizable, + withZoom, +} from "@nightingale-elements/nightingale-new-core"; +import { BaseType, select, Selection } from "d3"; +import { html, PropertyValues } from "lit"; +import { property } from "lit/decorators.js"; + + +const ATTRIBUTES_THAT_TRIGGER_REFRESH: string[] = [ + "length", "width", "height", + "margin-top", "margin-bottom", "margin-left", "margin-right", "margin-color", + "font-family", "min-font-size", "fade-font-size", "max-font-size", +] satisfies (keyof NightingaleDistributionTrack)[]; +const ATTRIBUTES_THAT_TRIGGER_DATA_RESET: string[] = ["letter-order"] satisfies (keyof NightingaleDistributionTrack)[]; + +/** Order of amino acids in a column (top-to-bottom) */ +const AMINO_ACID_ORDER = Array.from("HYAVLIMFWSTQNKRDEPCG"); // Old Protvista order: HYSTQNAVLIMFWDEPKRCG +/** Color to be used for unknown amino acids */ +const DEFAULT_COLOR = "#AAAAAA"; +/** Colors for amino acid groups, based on Clustal (https://www.jalview.org/help/html/colourSchemes/clustal.html) */ +const AMINO_GROUP_COLOR = { + aromatic: "#15A4A4", + hydrophobic: "#80A0F0", + polar: "#15C015", + positive: "#F01505", + negative: "#C048C0", + proline: "#C0C000", + cysteine: "#F08080", + glycine: "#F09048", +}; +/** Colors for individual amino acids, based on Clustal (https://www.jalview.org/help/html/colourSchemes/clustal.html) */ +const AMINO_ACID_COLOR = { + H: AMINO_GROUP_COLOR.aromatic, + Y: AMINO_GROUP_COLOR.aromatic, + A: AMINO_GROUP_COLOR.hydrophobic, + V: AMINO_GROUP_COLOR.hydrophobic, + L: AMINO_GROUP_COLOR.hydrophobic, + I: AMINO_GROUP_COLOR.hydrophobic, + M: AMINO_GROUP_COLOR.hydrophobic, + F: AMINO_GROUP_COLOR.hydrophobic, + W: AMINO_GROUP_COLOR.hydrophobic, + S: AMINO_GROUP_COLOR.polar, + T: AMINO_GROUP_COLOR.polar, + N: AMINO_GROUP_COLOR.polar, + Q: AMINO_GROUP_COLOR.polar, + K: AMINO_GROUP_COLOR.positive, + R: AMINO_GROUP_COLOR.positive, + D: AMINO_GROUP_COLOR.negative, + E: AMINO_GROUP_COLOR.negative, + P: AMINO_GROUP_COLOR.proline, + C: AMINO_GROUP_COLOR.cysteine, + G: AMINO_GROUP_COLOR.glycine, +}; +/** Color for rectangle stroke */ +const STROKE_COLOR = "#D3D3D3"; +/** Line width for rectangle stroke */ +const LINE_WIDTH = 1; +/** Maximum line width relative to column width (overrides `LINE_WIDTH` when zoomed out too much) */ +const MAX_REL_LINE_WIDTH = 0.2; + + +/** Amino acid probability for each amino acid for each position */ +interface Probabilities { [letter: string]: number[] } + +/** Vertical position for each amino acid for each position */ +interface YPositions { + start: { [letter: string]: number[] }, + end: { [letter: string]: number[] }, +} + +type LetterOrder = "default" | "probability"; + +/** Type for `NightingaleDistributionTrack.data`` */ +export interface DistributionData { + /** Sequence number for each position */ + index: number[], + /** Amino acid probability for each amino acid for each position */ + probabilities: Probabilities, +} + + +@customElementOnce("nightingale-distribution-track") +export default class NightingaleDistributionTrack extends withCanvas( + withManager( + withZoom( + withResizable( + withMargin( + withPosition(withDimensions(withHighlight(NightingaleElement))) + ) + ) + ) + ) +) { + /** Order of amino acids within a column (top-to-bottom). default = fixed order based on amino acid groups, probability = on every position sort by descending probability */ + @property({ type: String }) + "letter-order": LetterOrder = "default"; + + /** Font family for labels (can be a list of multiple font families separated by comma, like in CSS) */ + @property({ type: String }) + "font-family": string = "Helvetica,sans-serif"; + + /** Font size below which labels are hidden */ + @property({ type: Number }) + "min-font-size": number = 6; + + /** Column width below which labels are shown with lower opacity */ + @property({ type: Number }) + "fade-font-size": number = 12; + + /** Maximum font size for labels */ + @property({ type: Number }) + "max-font-size": number = 24; + + + #data?: DistributionData; + private yPositions?: YPositions; + protected highlighted?: Selection; + + + override connectedCallback() { + super.connectedCallback(); + if (this.data) this.createTrack(); + } + + /** Distribution data, e.g. TODO: example */ + get data(): DistributionData | undefined { + return this.#data; + } + set data(data: DistributionData | undefined) { + this.#data = data; + if (data) { + if (this["letter-order"] === "probability") { + this.yPositions = computeYPositions_ProbabilityOrder(data.probabilities); + } else { + this.yPositions = computeYPositions_FixedOrder(data.probabilities, AMINO_ACID_ORDER); + } + } else { + this.yPositions = undefined + } + this.createTrack(); + } + + override attributeChangedCallback(name: string, oldValue: string | null, newValue: string | null): void { + super.attributeChangedCallback(name, oldValue, newValue); + if (ATTRIBUTES_THAT_TRIGGER_DATA_RESET.includes(name)) { + // Calling `this.data` setter to recompute `this.positions` and run `this.createTrack()` + this.data = this.data; // eslint-disable-line no-self-assign + } else if (ATTRIBUTES_THAT_TRIGGER_REFRESH.includes(name)) { + this.onDimensionsChange(); + this.createTrack(); + } + } + + protected createTrack() { + if (this.svg) { + this.svg.selectAll("g").remove(); + this.unbindEvents(this.svg); + } + this.svg = select(this as unknown as NightingaleElement) + .selectAll("svg") + .attr("width", this.width) + .attr("height", this.height); + if (this.svg) { // this check is necessary because `svg` setter does not always set + this.bindEvents(this.svg); + this.highlighted = this.svg.append("g").attr("class", "highlighted"); + } + } + + refresh() { + this.requestDraw(); + this.updateHighlight(); + } + + private readonly _drawStamp = new Stamp(() => { + const stamp: Record = { + "data": this["data"], + "canvasCtx": this["canvasCtx"], + "canvasScale": this["canvasScale"], + "display-start": this["display-start"], + "display-end": this["display-end"], + }; + for (const attr of ATTRIBUTES_THAT_TRIGGER_DATA_RESET) { + stamp[attr] = this.getAttribute(attr); + } + for (const attr of ATTRIBUTES_THAT_TRIGGER_REFRESH) { + stamp[attr] = this.getAttribute(attr); + } + return stamp; + }); + + /** Request canvas redraw. */ + private requestDraw = () => this._drawer.requestRefresh(); + private readonly _drawer = Refresher(() => this._draw()); + /** Do not call directly! Call `requestDraw` instead to avoid browser freezing. */ + private _draw(): void { + if (!this._drawStamp.update().changed) return; + this.adjustCanvasCtxLogicalSize(); + this.clearCanvas(); + this.drawColumns(); + this.drawMargins(); + } + + private clearCanvas() { + const ctx = this.canvasCtx; + if (!ctx) return; + ctx.clearRect(0, 0, ctx.canvas.width, ctx.canvas.height); + } + + private drawColumns() { + const ctx = this.canvasCtx; + if (!ctx) return; + if (!this.data) return; + + const scale = this.canvasScale; + const baseWidthInCss = this.getSingleBaseWidth(); + const baseWidth = scale * baseWidthInCss; + const fontOpacity = this.getFontOpacity(baseWidthInCss); + const columnOffset = scale * this["margin-top"]; + const columnHeight = scale * (this["height"] - this["margin-top"] - this["margin-bottom"]); + + ctx.lineWidth = scale * Math.min(LINE_WIDTH, MAX_REL_LINE_WIDTH * baseWidthInCss); + ctx.strokeStyle = STROKE_COLOR; + ctx.textAlign = "center"; + ctx.textBaseline = "middle"; + + const leftEdgeSeq = this.getSeqPositionFromX(0 - 0.5 * LINE_WIDTH) ?? -Infinity; + const rightEdgeSeq = this.getSeqPositionFromX(this.width + 0.5 * LINE_WIDTH) ?? Infinity; + const iFrom = Math.max(0, BinarySearch.firstGteqIndex(this.data.index, leftEdgeSeq - 1, x => x)); + const iTo = Math.min(this.data.index.length, BinarySearch.firstGteqIndex(this.data.index, rightEdgeSeq, x => x)); + + for (let i = iFrom; i < iTo; i++) { + const x = scale * this.getXFromSeqPosition(this.data.index[i]); + const textX = x + 0.5 * baseWidth; + + for (const letter in this.yPositions?.start) { + const relStart = Math.min(this.yPositions.start[letter][i], 1); + const relEnd = Math.min(this.yPositions.end[letter][i], 1); + const start = relStart * columnHeight + columnOffset; + const end = relEnd * columnHeight + columnOffset; + const height = end - start; + + // Draw rectangle + ctx.globalAlpha = 1; + ctx.fillStyle = AMINO_ACID_COLOR[letter as keyof typeof AMINO_ACID_COLOR] ?? DEFAULT_COLOR; + ctx.fillRect(x, start, baseWidth, height); + ctx.strokeRect(x, start, baseWidth, height); + + // Draw letter + if (fontOpacity === 0) continue; + const fontSize = Math.min(baseWidth, height, scale * this["max-font-size"]); + if (fontSize < scale * this["min-font-size"]) continue; + const textY = start + 0.5 * height; + ctx.globalAlpha = fontOpacity; + ctx.fillStyle = "black"; + ctx.font = `${fontSize}px ${this["font-family"]}`; + ctx.fillText(letter, textX, textY); + } + } + } + + private drawMargins() { + const ctx = this.canvasCtx; + if (!ctx) return; + + const canvasWidth = ctx.canvas.width; + const canvasHeight = ctx.canvas.height; + const marginLeft = this["margin-left"] * this.canvasScale; + const marginRight = this["margin-right"] * this.canvasScale; + const marginTop = this["margin-top"] * this.canvasScale; + const marginBottom = this["margin-bottom"] * this.canvasScale; + + ctx.globalAlpha = 1; + ctx.fillStyle = this["margin-color"]; + ctx.fillRect(0, 0, marginLeft, canvasHeight); + ctx.fillRect(canvasWidth - marginRight, 0, marginRight, canvasHeight); + ctx.fillRect(marginLeft, 0, canvasWidth - marginLeft - marginRight, marginTop); + ctx.fillRect(marginLeft, canvasHeight - marginBottom, canvasWidth - marginLeft - marginRight, marginBottom); + } + + private getFontOpacity(baseWidthInCss: number): number { + if (baseWidthInCss < this["min-font-size"]) { + return 0; + } else if (baseWidthInCss < this["fade-font-size"]) { + return (baseWidthInCss - this["min-font-size"]) / (this["fade-font-size"] - this["min-font-size"]); + } else { + return 1; + } + } + + protected updateHighlight() { + if (!this.highlighted) return; + const highlights = this.highlighted + .selectAll("rect") + .data(this.highlightedRegion.segments); + + highlights + .enter() + .append("rect") + .style("pointer-events", "none") + .merge(highlights) + .attr("fill", this["highlight-color"]) + .attr("height", this.height) + .attr("x", d => this.getXFromSeqPosition(d.start)) + .attr("width", d => Math.max(0, this.getSingleBaseWidth() * (d.end - d.start + 1))); + + highlights.exit().remove(); + } + + override zoomRefreshed() { + super.zoomRefreshed(); + if (this.getWidthWithMargins() > 0) this.refresh(); + } + + override firstUpdated(_changedProperties: PropertyValues) { + super.firstUpdated(_changedProperties); + this.createTrack(); + } + + override render() { + return html` +
+
+ + +
+
+ `; + } + + override onCanvasScaleChange() { + super.onCanvasScaleChange(); + this.refresh(); + } + + + private bindEvents(target: Selection): void { + target.on("click.NightingaleDistributionTrack", (event: MouseEvent) => this.handleClick(event)); + target.on("mousemove.NightingaleDistributionTrack", (event: MouseEvent) => this.handleMousemove(event)); + target.on("mouseout.NightingaleDistributionTrack", (event: MouseEvent) => this.handleMouseout(event)); + } + + private unbindEvents(target: Selection): void { + target.on("click.NightingaleDistributionTrack", null); + target.on("mousemove.NightingaleDistributionTrack", null); + target.on("mouseout.NightingaleDistributionTrack", null); + } + + private handleClick(event: MouseEvent): void { + const pointed = this.getPointedAminoAcid(event.offsetX, event.offsetY); + if (pointed === undefined) { + return; + } + const withHighlight = this.getAttribute("highlight-event") === "onclick"; + const customEvent = createEvent( + "click", + pointed, + withHighlight, + true, + pointed.position, + pointed.position, + event.target instanceof HTMLElement ? event.target : undefined, + event, + this, + ); + this.dispatchEvent(customEvent); + } + + private handleMousemove(event: MouseEvent): void { + const pointed = this.getPointedAminoAcid(event.offsetX, event.offsetY); + if (pointed === undefined) { + return this.handleMouseout(event); + } + const withHighlight = this.getAttribute("highlight-event") === "onmouseover"; + const customEvent = createEvent( + "mouseover", + pointed, + withHighlight, + false, + pointed.position, + pointed.position, + event.target instanceof HTMLElement ? event.target : undefined, + event, + this, + ); + this.dispatchEvent(customEvent); + } + + private handleMouseout(event: MouseEvent): void { + const withHighlight = this.getAttribute("highlight-event") === "onmouseover"; + const customEvent = createEvent( + "mouseout", + null, + withHighlight, + undefined, + undefined, + undefined, + event.target instanceof HTMLElement ? event.target : undefined, + event, + this + ); + this.dispatchEvent(customEvent); + } + + private getPointedAminoAcid(svgX: number, svgY: number): { position: number, aa: string, probability: number } | undefined { + if (!this.data) return undefined; + if (!this.yPositions) return undefined; + const continuousPosition = this.getSeqPositionFromX(svgX); + if (continuousPosition === undefined) return undefined; + const position = Math.floor(continuousPosition); + const i = BinarySearch.firstEqIndex(this.data.index, position, x => x); + if (i === undefined) return undefined; + const relativeY = (svgY - this["margin-top"]) / (this["height"] - this["margin-top"] - this["margin-bottom"]); + for (const letter in this.yPositions.start) { + if (relativeY >= this.yPositions.start[letter][i] && relativeY < this.yPositions.end[letter][i]) { + return { position, aa: letter, probability: this.data.probabilities[letter][i] ?? 0 }; + } + } + return undefined; + } +} + + +function computeYPositions_FixedOrder(probabilities: Probabilities, order: string[]): YPositions { + const normalizedOrder = normalizeOrder(Object.keys(probabilities), order); + const start: { [letter: string]: number[] } = {}; + const end: { [letter: string]: number[] } = {}; + for (const letter of normalizedOrder) { + start[letter] = []; + end[letter] = []; + } + const n = Math.max(0, ...normalizedOrder.map(letter => probabilities[letter].length)); + for (let i = 0; i < n; i++) { + let cum = 0; + for (const letter of normalizedOrder) { + start[letter].push(cum); + cum += probabilities[letter][i] ?? 0; + end[letter].push(cum); + } + } + return { start, end }; +} + +function computeYPositions_ProbabilityOrder(probabilities: Probabilities): YPositions { + const alphabet = Object.keys(probabilities); + const start: { [letter: string]: number[] } = {}; + const end: { [letter: string]: number[] } = {}; + for (const letter of alphabet) { + start[letter] = []; + end[letter] = []; + } + const n = Math.max(0, ...alphabet.map(letter => probabilities[letter].length)); + for (let i = 0; i < n; i++) { + let cum = 0; + alphabet.sort((a, b) => (probabilities[b][i] ?? 0) - (probabilities[a][i] ?? 0)); + for (const letter of alphabet) { + start[letter].push(cum); + cum += probabilities[letter][i] ?? 0; + end[letter].push(cum); + } + } + return { start, end }; +} + +function normalizeOrder(present: string[], order: string[]) { + const presentSet = new Set(present); + const orderSet = new Set(order); + const ordered = order.filter(s => presentSet.has(s)); + const rest = present.filter(s => !orderSet.has(s)); + return ordered.concat(rest); +} diff --git a/packages/nightingale-distribution-track/tests/mockData/sample-distribution-data.json b/packages/nightingale-distribution-track/tests/mockData/sample-distribution-data.json new file mode 100644 index 000000000..8c64aa59c --- /dev/null +++ b/packages/nightingale-distribution-track/tests/mockData/sample-distribution-data.json @@ -0,0 +1,32 @@ +{ + "__comment__": "This is real data coming from https://www.ebi.ac.uk/pdbe/graph-api/pdb/sequence_conservation/1tqn/1", + "identifier": "1tqn", + "main_track_color": "#808080", + "sub_track_color": "#d3d3d3", + "data": { + "index": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 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0.035, 0.017, 0.018, 0.018, 0.018, 0.02, 0.024, 0.026, 0.023, 0.025, 0.031, 0.038] + }, + "length": 482, + "seq_id": "f605e37dc591194cfc8a9a7b94c629c5" +} \ No newline at end of file diff --git a/packages/nightingale-distribution-track/tests/nightingale-distribution-track.test.ts b/packages/nightingale-distribution-track/tests/nightingale-distribution-track.test.ts new file mode 100644 index 000000000..882524c80 --- /dev/null +++ b/packages/nightingale-distribution-track/tests/nightingale-distribution-track.test.ts @@ -0,0 +1,7 @@ +describe("nightingale-distribution-track tests", () => { + test("foo", () => { + expect(2+2).toEqual(4); + }); +}); + +// TODO tests diff --git a/packages/nightingale-distribution-track/tsconfig.json b/packages/nightingale-distribution-track/tsconfig.json new file mode 100644 index 000000000..6a62dbc48 --- /dev/null +++ b/packages/nightingale-distribution-track/tsconfig.json @@ -0,0 +1,7 @@ +{ + "extends": "../../tsconfig.json", + "compilerOptions": { + "outDir": "./dist" + }, + "include": ["./src"] +} diff --git a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.mdx b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.mdx new file mode 100644 index 000000000..785841335 --- /dev/null +++ b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.mdx @@ -0,0 +1,35 @@ +import { Meta, Description } from "@storybook/addon-docs"; + +import Readme from "../../packages/nightingale-conservation-track/README.md"; +import ParentReadme from "../../packages/nightingale-new-core/src/nightingale-base-element.md"; +import dimensionsReadme from "../../packages/nightingale-new-core/src/mixins/withDimensions/README.md"; +import highlightReadme from "../../packages/nightingale-new-core/src/mixins/withHighlight/README.md"; +import managerReadme from "../../packages/nightingale-new-core/src/mixins/withManager/README.md"; +import marginReadme from "../../packages/nightingale-new-core/src/mixins/withMargin/README.md"; +import positionReadme from "../../packages/nightingale-new-core/src/mixins/withPosition/README.md"; +import resizableReadme from "../../packages/nightingale-new-core/src/mixins/withResizable/README.md"; +import zoomReadme from "../../packages/nightingale-new-core/src/mixins/withZoom/README.md"; + + + +{Readme} + +
+ +

Mixins

+ +

+ This component implement the following mixins, and therefore it includes their + attributes and properties. +

+{dimensionsReadme} +{highlightReadme} +{managerReadme} +{marginReadme} +{positionReadme} +{resizableReadme} +{zoomReadme} + +

Parent Class

+ +{ParentReadme} diff --git a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts new file mode 100644 index 000000000..9f077d725 --- /dev/null +++ b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts @@ -0,0 +1,175 @@ +import { type ArgTypes, Meta, Story } from "@storybook/web-components"; +import { html } from "lit-html"; +import "../../packages/nightingale-distribution-track/src/index"; +import { type DistributionData } from "../../packages/nightingale-distribution-track/src/nightingale-distribution-track"; +import sampleDistributionData from "../../packages/nightingale-distribution-track/tests/mockData/sample-distribution-data.json"; + + +export default { title: "Components/Tracks/Distribution Track" } as Meta; + + +const DefaultArgs = { + "letter-order": "default", + "min-width": 400, + "height": 200, + "highlight-event": "onmouseover", + "highlight-color": "#EB3BFF22", + "margin-color": "#ffffffdd", +}; +type Args = typeof DefaultArgs; + +const ArgumentTypes: Partial> = { + "highlight-event": { control: "select", options: ["onmouseover", "onclick"] }, + "letter-order": { control: "select", options: ["default", "probability"] }, +}; + + +const sampleSequence = "MALYGTHSHGLFKKLGIPGPTPLPFLGNILSYHKGFCMFDMECHKKYGKVWGFYDGQQPVLAITDPDMIKTVLVKECYSVFTNRRPFGPVGFMKSAISIAEDEEWKRLRSLLSPTFTSGKLKEMVPIIAQYGDVLVRNLRREAETGKPVTLKDVFGAYSMDVITSTSFGVNIDSLNNPQDPFVENTKKLLRFDFLDPFFLSITVFPFLIPILEVLNICVFPREVTNFLRKSVKRMKESRLEDTQKHRVDFLQLMIDSQNSKETESHKALSDLELVAQSIIFIFAGYETTSSVLSFIMYELATHPDVQQKLQEEIDAVLPNKAPPTYDTVLQMEYLDMVVNETLRLFPIAMRLERVCKKDVEINGMFIPKGVVVMIPSYALHRDPKYWTEPEKFLPERFSKKNKDNIDPYIYTPFGSGPRNCIGMRFALMNMKLALIRVLQNFSFKPCKETQIPLKLSLGGLLQPEKPVVLKVESRDGTVSGAHHHH"; + +function prepareDistributionData(data: typeof sampleDistributionData): DistributionData { + const out: DistributionData = { + index: data.data.index, + probabilities: {}, + }; + for (const field in data.data) { + if (data.data.hasOwnProperty(field) && field.startsWith('probability_')) { + const letter = field.slice('probability_'.length); + out.probabilities[letter] = data.data[field as keyof typeof data.data]; + } + } + return out; +} + +function prepareLinegraphData(data: typeof sampleDistributionData) { + const chart1 = { + name: "chart1", + color: "#707070", + fill: "#808080", + lineCurve: "curveStep", + range: [0, 10], + values: data.data.index.map((position, i) => ({ position, value: data.data.conservation_score[i] })), + }; + return [chart1]; +} + + +function nightingaleNavigation(args: Args & { length: number }) { + return html` +
+
+ + +
`; +} + +function nightingaleSequence(args: Args & { length: number }) { + const sequence = sampleSequence; + return html` +
+
+ + +
`; +} + +function nightingaleLinegraphTrack(args: Args & { length: number, id: number }) { + return html` +
+
Linegraph
+ + + +
`; +} + +function nightingaleDistributionTrack(args: Args & { length: number, id: number }) { + return html` +
+
Distribution
+ + +
`; +} + + +function makeStory(options: { length: number }): Story { + const template: Story = (args: Args) => { + return html` + + Use Ctrl+scroll to zoom. +
+ + +
+ ${nightingaleNavigation({ ...args, length: options.length })} + ${nightingaleSequence({ ...args, length: options.length })} + ${nightingaleLinegraphTrack({ ...args, length: options.length, id: 0 })} + ${nightingaleDistributionTrack({ ...args, length: options.length, id: 0 })} +
+ +
`; + } + + const story: Story = template.bind({}); + story.args = { ...DefaultArgs }; + story.argTypes = ArgumentTypes; + story.play = async () => { + await customElements.whenDefined("nightingale-linegraph-track"); + for (const track of document.getElementsByTagName("nightingale-linegraph-track")) { + (track as any).data = prepareLinegraphData(sampleDistributionData); + } + await customElements.whenDefined("nightingale-distribution-track"); + for (const track of document.getElementsByTagName("nightingale-distribution-track")) { + (track as any).data = prepareDistributionData(sampleDistributionData); + } + }; + return story; +} + + +export const LinegraphAndDistribution = makeStory({ + length: sampleSequence.length, +}); From dc3cb2089a8cac96cc63f36b4d794bed4ac27f79 Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Tue, 9 Jun 2026 16:26:22 +0100 Subject: [PATCH 02/32] Squashed commit of the following: commit edb0f14568c102e4596c4e5fddee46fb18130427 Author: Adam Midlik Date: Tue Jun 9 16:22:10 2026 +0100 nightingale-distribution-track: remove old mock data commit 123d5515c6a4d0eaa19059e956bea3d0545b2892 Author: Adam Midlik Date: Tue Jun 9 16:11:12 2026 +0100 nightingale-distribution-track: clip mock data commit 7c19d493c72607fb08bce6d319e1725f6abf7296 Author: Adam Midlik Date: Tue Jun 9 16:05:48 2026 +0100 nightingale-distribution-track: minify mock data commit 0d814e9bd941fce622188a2e64ccb9eb1b6d2155 Author: Adam Midlik Date: Tue Jun 9 15:47:59 2026 +0100 nightingale-distribution-track: proper y-scaling, show outliers commit 9d13c4435714fe53c3f6b6a6ca410aea43ed7b60 Author: Adam Midlik Date: Mon Jun 8 16:12:00 2026 +0100 nightingale-distribution-track: support multiple datasets commit fd05f2f6d54054444598d65abfd21925ff57d84b Author: Adam Midlik Date: Mon Jun 8 15:49:18 2026 +0100 nightingale-distribution-track: basic rendering --- .../src/nightingale-conservation-track.ts | 2 + .../src/nightingale-distribution-track.ts | 391 +++++++++-------- .../tests/mockData/sample-1.json | 404 ++++++++++++++++++ .../mockData/sample-distribution-data.json | 32 -- .../nightingale-distribution-track.test.ts | 84 +++- .../NightingaleDistributionTrack.stories.mdx | 4 +- .../NightingaleDistributionTrack.stories.ts | 84 +++- 7 files changed, 769 insertions(+), 232 deletions(-) create mode 100644 packages/nightingale-distribution-track/tests/mockData/sample-1.json delete mode 100644 packages/nightingale-distribution-track/tests/mockData/sample-distribution-data.json diff --git a/packages/nightingale-conservation-track/src/nightingale-conservation-track.ts b/packages/nightingale-conservation-track/src/nightingale-conservation-track.ts index f46389a0c..c2afb68bb 100644 --- a/packages/nightingale-conservation-track/src/nightingale-conservation-track.ts +++ b/packages/nightingale-conservation-track/src/nightingale-conservation-track.ts @@ -187,6 +187,8 @@ export default class NightingaleConservationTrack extends withCanvas( const stamp: Record = { "data": this["data"], "canvasCtx": this["canvasCtx"], + "canvasWidth": this["width"], + "canvasHeight": this["height"], "canvasScale": this["canvasScale"], "display-start": this["display-start"], "display-end": this["display-end"], diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts index 2632720fa..bad0f5fe1 100644 --- a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts +++ b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts @@ -13,7 +13,7 @@ import NightingaleElement, { withResizable, withZoom, } from "@nightingale-elements/nightingale-new-core"; -import { BaseType, select, Selection } from "d3"; +import { BaseType, select, Selection, color, scaleLinear, randomNormal, randomUniform, randomLcg } from "d3"; import { html, PropertyValues } from "lit"; import { property } from "lit/decorators.js"; @@ -22,47 +22,11 @@ const ATTRIBUTES_THAT_TRIGGER_REFRESH: string[] = [ "length", "width", "height", "margin-top", "margin-bottom", "margin-left", "margin-right", "margin-color", "font-family", "min-font-size", "fade-font-size", "max-font-size", + "y-min", "y-max", "hide-outliers", ] satisfies (keyof NightingaleDistributionTrack)[]; -const ATTRIBUTES_THAT_TRIGGER_DATA_RESET: string[] = ["letter-order"] satisfies (keyof NightingaleDistributionTrack)[]; - -/** Order of amino acids in a column (top-to-bottom) */ -const AMINO_ACID_ORDER = Array.from("HYAVLIMFWSTQNKRDEPCG"); // Old Protvista order: HYSTQNAVLIMFWDEPKRCG -/** Color to be used for unknown amino acids */ -const DEFAULT_COLOR = "#AAAAAA"; -/** Colors for amino acid groups, based on Clustal (https://www.jalview.org/help/html/colourSchemes/clustal.html) */ -const AMINO_GROUP_COLOR = { - aromatic: "#15A4A4", - hydrophobic: "#80A0F0", - polar: "#15C015", - positive: "#F01505", - negative: "#C048C0", - proline: "#C0C000", - cysteine: "#F08080", - glycine: "#F09048", -}; -/** Colors for individual amino acids, based on Clustal (https://www.jalview.org/help/html/colourSchemes/clustal.html) */ -const AMINO_ACID_COLOR = { - H: AMINO_GROUP_COLOR.aromatic, - Y: AMINO_GROUP_COLOR.aromatic, - A: AMINO_GROUP_COLOR.hydrophobic, - V: AMINO_GROUP_COLOR.hydrophobic, - L: AMINO_GROUP_COLOR.hydrophobic, - I: AMINO_GROUP_COLOR.hydrophobic, - M: AMINO_GROUP_COLOR.hydrophobic, - F: AMINO_GROUP_COLOR.hydrophobic, - W: AMINO_GROUP_COLOR.hydrophobic, - S: AMINO_GROUP_COLOR.polar, - T: AMINO_GROUP_COLOR.polar, - N: AMINO_GROUP_COLOR.polar, - Q: AMINO_GROUP_COLOR.polar, - K: AMINO_GROUP_COLOR.positive, - R: AMINO_GROUP_COLOR.positive, - D: AMINO_GROUP_COLOR.negative, - E: AMINO_GROUP_COLOR.negative, - P: AMINO_GROUP_COLOR.proline, - C: AMINO_GROUP_COLOR.cysteine, - G: AMINO_GROUP_COLOR.glycine, -}; +const ATTRIBUTES_THAT_TRIGGER_DATA_RESET: string[] = [] satisfies (keyof NightingaleDistributionTrack)[]; + + /** Color for rectangle stroke */ const STROKE_COLOR = "#D3D3D3"; /** Line width for rectangle stroke */ @@ -70,26 +34,38 @@ const LINE_WIDTH = 1; /** Maximum line width relative to column width (overrides `LINE_WIDTH` when zoomed out too much) */ const MAX_REL_LINE_WIDTH = 0.2; - -/** Amino acid probability for each amino acid for each position */ -interface Probabilities { [letter: string]: number[] } - -/** Vertical position for each amino acid for each position */ -interface YPositions { - start: { [letter: string]: number[] }, - end: { [letter: string]: number[] }, +/** Default fill color for boxes (stroke color will be derived from this) */ +const DEFAULT_DATA_COLOR = "#cccccc"; +/** Gap between columns relative to base width */ +const COLUMN_GAP = 0.2; +/** Gap between boxes within a column relative to box width */ +const BOX_GAP = 0.1; +/** Whisker width relative to box width */ +const WHISKER_REL_WIDTH = 0.6; +/** Outlier jitter width relative to box width */ +const JITTER_REL_WIDTH = 0.4; +/** Radius for the circles representing outliers */ +const OUTLIER_RADIUS = 2; + + +interface Distribution { + position: number, + values: number[], } -type LetterOrder = "default" | "probability"; +export interface DistributionDataset { + name: string, + color?: string, + positions: Distribution[], +} /** Type for `NightingaleDistributionTrack.data`` */ -export interface DistributionData { - /** Sequence number for each position */ - index: number[], - /** Amino acid probability for each amino acid for each position */ - probabilities: Probabilities, -} +export type DistributionData = DistributionDataset[]; +const OptionalNumber = (str: string | null) => { + if (str) return Number(str); + return undefined; +}; @customElementOnce("nightingale-distribution-track") export default class NightingaleDistributionTrack extends withCanvas( @@ -103,10 +79,6 @@ export default class NightingaleDistributionTrack extends withCanvas( ) ) ) { - /** Order of amino acids within a column (top-to-bottom). default = fixed order based on amino acid groups, probability = on every position sort by descending probability */ - @property({ type: String }) - "letter-order": LetterOrder = "default"; - /** Font family for labels (can be a list of multiple font families separated by comma, like in CSS) */ @property({ type: String }) "font-family": string = "Helvetica,sans-serif"; @@ -123,9 +95,21 @@ export default class NightingaleDistributionTrack extends withCanvas( @property({ type: Number }) "max-font-size": number = 24; + /** Bottom limit for Y-axis (default: minimum computed from data) */ + @property({ converter: OptionalNumber }) + "y-min"?: number; + + /** Top limit for Y-axis (default: maximum computed from data) */ + @property({ converter: OptionalNumber }) + "y-max"?: number; + + /** Turns off rendering of outliers */ + @property({ type: Boolean }) + "hide-outliers"?: boolean; + #data?: DistributionData; - private yPositions?: YPositions; + private preprocessedData?: PreprocessedData; protected highlighted?: Selection; @@ -134,23 +118,20 @@ export default class NightingaleDistributionTrack extends withCanvas( if (this.data) this.createTrack(); } - /** Distribution data, e.g. TODO: example */ get data(): DistributionData | undefined { return this.#data; } set data(data: DistributionData | undefined) { this.#data = data; - if (data) { - if (this["letter-order"] === "probability") { - this.yPositions = computeYPositions_ProbabilityOrder(data.probabilities); - } else { - this.yPositions = computeYPositions_FixedOrder(data.probabilities, AMINO_ACID_ORDER); - } - } else { - this.yPositions = undefined - } + this.preprocessedData = data ? preprocessData(data) : undefined; this.createTrack(); } + /** Return the range of Y values corresponding to bottom and top of the viewport (excluding margins) */ + getYLimits(): [yMin: number, yMax: number] { + const yMin = this["y-min"] ?? this.preprocessedData?.yLimits.min ?? 0; + const yMax = this["y-max"] ?? this.preprocessedData?.yLimits.max ?? 100; + return [yMin, yMax]; + } override attributeChangedCallback(name: string, oldValue: string | null, newValue: string | null): void { super.attributeChangedCallback(name, oldValue, newValue); @@ -187,6 +168,8 @@ export default class NightingaleDistributionTrack extends withCanvas( const stamp: Record = { "data": this["data"], "canvasCtx": this["canvasCtx"], + "canvasWidth": this["width"], + "canvasHeight": this["height"], "canvasScale": this["canvasScale"], "display-start": this["display-start"], "display-end": this["display-end"], @@ -208,7 +191,7 @@ export default class NightingaleDistributionTrack extends withCanvas( if (!this._drawStamp.update().changed) return; this.adjustCanvasCtxLogicalSize(); this.clearCanvas(); - this.drawColumns(); + this.drawBoxplot(); this.drawMargins(); } @@ -218,54 +201,102 @@ export default class NightingaleDistributionTrack extends withCanvas( ctx.clearRect(0, 0, ctx.canvas.width, ctx.canvas.height); } - private drawColumns() { + private drawBoxplot() { const ctx = this.canvasCtx; if (!ctx) return; - if (!this.data) return; + if (!this.data || !this.preprocessedData) return; + + const nData = this.data.length; const scale = this.canvasScale; const baseWidthInCss = this.getSingleBaseWidth(); const baseWidth = scale * baseWidthInCss; - const fontOpacity = this.getFontOpacity(baseWidthInCss); const columnOffset = scale * this["margin-top"]; const columnHeight = scale * (this["height"] - this["margin-top"] - this["margin-bottom"]); + const xColumnOffset = baseWidth * 0.5 * COLUMN_GAP; + const xColumnWidth = baseWidth * (1 - COLUMN_GAP); + const xBoxWidth = xColumnWidth / nData * (1 - BOX_GAP); + const yScale = scaleLinear(this.getYLimits(), [columnOffset + columnHeight, columnOffset]); + const outlierRadius = scale * OUTLIER_RADIUS; + + const yMedianExtra = scale * 1; ctx.lineWidth = scale * Math.min(LINE_WIDTH, MAX_REL_LINE_WIDTH * baseWidthInCss); ctx.strokeStyle = STROKE_COLOR; ctx.textAlign = "center"; ctx.textBaseline = "middle"; - const leftEdgeSeq = this.getSeqPositionFromX(0 - 0.5 * LINE_WIDTH) ?? -Infinity; - const rightEdgeSeq = this.getSeqPositionFromX(this.width + 0.5 * LINE_WIDTH) ?? Infinity; - const iFrom = Math.max(0, BinarySearch.firstGteqIndex(this.data.index, leftEdgeSeq - 1, x => x)); - const iTo = Math.min(this.data.index.length, BinarySearch.firstGteqIndex(this.data.index, rightEdgeSeq, x => x)); - - for (let i = iFrom; i < iTo; i++) { - const x = scale * this.getXFromSeqPosition(this.data.index[i]); - const textX = x + 0.5 * baseWidth; + const start = Math.floor(this.getSeqPositionFromX(0) ?? 1); + const end = Math.floor(this.getSeqPositionFromX(this.width) ?? 1); + for (let iData = 0; iData < nData; iData++) { + const dataset = this.preprocessedData.datasets[iData]; + if (!dataset) continue; + + const dataColor = this.data[iData].color ?? DEFAULT_DATA_COLOR; + const boxFill = dataColor; + const boxStroke = color(boxFill)!.darker(2).formatHex(); + + const xBoxOffset = xColumnOffset + xColumnWidth * (iData + 0.5 * BOX_GAP) / nData; + const xCenter = xBoxOffset + 0.5 * xBoxWidth; + const xWhiskerHalfWidth = 0.5 * WHISKER_REL_WIDTH * xBoxWidth; + const xWhiskerOffset = xCenter - xWhiskerHalfWidth; + const xWhiskerEnd = xCenter + xWhiskerHalfWidth; + const xJitterHalfWidth = 0.5 * JITTER_REL_WIDTH * xBoxWidth; + + for (let i = start; i <= end; i++) { + const datum = dataset[i]; + if (!datum) continue; + + const x = scale * this.getXFromSeqPosition(i); + const yMedian = yScale(datum.median); + const yBoxLow = yScale(datum.boxLow); + const yBoxHigh = yScale(datum.boxHigh); + const yWhiskerLow = yScale(datum.whiskerLow); + const yWhiskerHigh = yScale(datum.whiskerHigh); - for (const letter in this.yPositions?.start) { - const relStart = Math.min(this.yPositions.start[letter][i], 1); - const relEnd = Math.min(this.yPositions.end[letter][i], 1); - const start = relStart * columnHeight + columnOffset; - const end = relEnd * columnHeight + columnOffset; - const height = end - start; - - // Draw rectangle ctx.globalAlpha = 1; - ctx.fillStyle = AMINO_ACID_COLOR[letter as keyof typeof AMINO_ACID_COLOR] ?? DEFAULT_COLOR; - ctx.fillRect(x, start, baseWidth, height); - ctx.strokeRect(x, start, baseWidth, height); - - // Draw letter - if (fontOpacity === 0) continue; - const fontSize = Math.min(baseWidth, height, scale * this["max-font-size"]); - if (fontSize < scale * this["min-font-size"]) continue; - const textY = start + 0.5 * height; - ctx.globalAlpha = fontOpacity; - ctx.fillStyle = "black"; - ctx.font = `${fontSize}px ${this["font-family"]}`; - ctx.fillText(letter, textX, textY); + + // Whiskers + ctx.strokeStyle = boxStroke; + ctx.beginPath(); + ctx.moveTo(x + xWhiskerOffset, yWhiskerHigh); + ctx.lineTo(x + xWhiskerEnd, yWhiskerHigh); + ctx.moveTo(x + xWhiskerOffset, yWhiskerLow); + ctx.lineTo(x + xWhiskerEnd, yWhiskerLow); + ctx.moveTo(x + xCenter, yWhiskerHigh); + ctx.lineTo(x + xCenter, yWhiskerLow); + ctx.stroke(); + + // Box + ctx.fillStyle = boxFill; + ctx.strokeStyle = boxStroke; + ctx.fillRect(x + xBoxOffset, yBoxHigh, xBoxWidth, yBoxLow - yBoxHigh); + ctx.strokeRect(x + xBoxOffset, yBoxHigh, xBoxWidth, yBoxLow - yBoxHigh); + + // Median + ctx.fillStyle = boxStroke; + ctx.strokeStyle = boxStroke; + ctx.fillRect(x + xBoxOffset, yMedian - yMedianExtra, xBoxWidth, 2 * yMedianExtra); + ctx.strokeRect(x + xBoxOffset, yMedian - yMedianExtra, xBoxWidth, 2 * yMedianExtra); + + // Outliers + if (!this["hide-outliers"]) { + const xJitter = xJitterHalfWidth !== 0 ? + randomUniform.source(randomLcg(i * nData + iData))(xCenter - xJitterHalfWidth, xCenter + xJitterHalfWidth) + : () => xCenter; + ctx.globalAlpha = 0.25; + ctx.fillStyle = boxStroke; + for (const outlier of datum.outliersHigh) { + ctx.beginPath(); + ctx.arc(x + xJitter(), yScale(outlier), outlierRadius, 0, 2 * Math.PI); + ctx.fill(); + } + for (const outlier of datum.outliersLow) { + ctx.beginPath(); + ctx.arc(x + xJitter(), yScale(outlier), outlierRadius, 0, 2 * Math.PI); + ctx.fill(); + } + } } } } @@ -289,16 +320,6 @@ export default class NightingaleDistributionTrack extends withCanvas( ctx.fillRect(marginLeft, canvasHeight - marginBottom, canvasWidth - marginLeft - marginRight, marginBottom); } - private getFontOpacity(baseWidthInCss: number): number { - if (baseWidthInCss < this["min-font-size"]) { - return 0; - } else if (baseWidthInCss < this["fade-font-size"]) { - return (baseWidthInCss - this["min-font-size"]) / (this["fade-font-size"] - this["min-font-size"]); - } else { - return 1; - } - } - protected updateHighlight() { if (!this.highlighted) return; const highlights = this.highlighted @@ -358,14 +379,14 @@ export default class NightingaleDistributionTrack extends withCanvas( } private handleClick(event: MouseEvent): void { - const pointed = this.getPointedAminoAcid(event.offsetX, event.offsetY); + const pointed = this.getPointedDatum(event.offsetX, event.offsetY); if (pointed === undefined) { return; } const withHighlight = this.getAttribute("highlight-event") === "onclick"; const customEvent = createEvent( "click", - pointed, + null, // TODO: pass (pointed.datum ?? null), withHighlight, true, pointed.position, @@ -378,14 +399,14 @@ export default class NightingaleDistributionTrack extends withCanvas( } private handleMousemove(event: MouseEvent): void { - const pointed = this.getPointedAminoAcid(event.offsetX, event.offsetY); + const pointed = this.getPointedDatum(event.offsetX, event.offsetY); if (pointed === undefined) { - return this.handleMouseout(event); + return; } const withHighlight = this.getAttribute("highlight-event") === "onmouseover"; const customEvent = createEvent( "mouseover", - pointed, + null, // TODO: pass (pointed.datum ?? null), withHighlight, false, pointed.position, @@ -413,70 +434,100 @@ export default class NightingaleDistributionTrack extends withCanvas( this.dispatchEvent(customEvent); } - private getPointedAminoAcid(svgX: number, svgY: number): { position: number, aa: string, probability: number } | undefined { - if (!this.data) return undefined; - if (!this.yPositions) return undefined; + private getPointedDatum(svgX: number, svgY: number): { position: number, datum: PreprocessedDatum | undefined } | undefined { const continuousPosition = this.getSeqPositionFromX(svgX); if (continuousPosition === undefined) return undefined; const position = Math.floor(continuousPosition); - const i = BinarySearch.firstEqIndex(this.data.index, position, x => x); - if (i === undefined) return undefined; - const relativeY = (svgY - this["margin-top"]) / (this["height"] - this["margin-top"] - this["margin-bottom"]); - for (const letter in this.yPositions.start) { - if (relativeY >= this.yPositions.start[letter][i] && relativeY < this.yPositions.end[letter][i]) { - return { position, aa: letter, probability: this.data.probabilities[letter][i] ?? 0 }; - } - } - return undefined; + const datum = this.preprocessedData?.datasets[0][position]; // TODO: consider multiple datasets + return { position, datum }; } } -function computeYPositions_FixedOrder(probabilities: Probabilities, order: string[]): YPositions { - const normalizedOrder = normalizeOrder(Object.keys(probabilities), order); - const start: { [letter: string]: number[] } = {}; - const end: { [letter: string]: number[] } = {}; - for (const letter of normalizedOrder) { - start[letter] = []; - end[letter] = []; +type PreprocessedData = ReturnType; + +function preprocessData(data: DistributionData) { + const preprocessedDatasets = data.map(preprocessDataset); + return { + datasets: preprocessedDatasets, + yLimits: getExtremes(preprocessedDatasets), } - const n = Math.max(0, ...normalizedOrder.map(letter => probabilities[letter].length)); - for (let i = 0; i < n; i++) { - let cum = 0; - for (const letter of normalizedOrder) { - start[letter].push(cum); - cum += probabilities[letter][i] ?? 0; - end[letter].push(cum); - } +} + +function preprocessDataset(dataset: DistributionDataset) { + const out: { [position: number]: PreprocessedDatum } = {}; + for (const datum of dataset.positions) { + out[datum.position] = preprocessDatum(datum); } - return { start, end }; + return out; +} + +interface PreprocessedDatum { + position: number, + values: number[], + median: number, + boxLow: number, + boxHigh: number, + whiskerLow: number, + whiskerHigh: number, + outliersLow: number[], + outliersHigh: number[], + minimum: number, + maximum: number, +} + +function preprocessDatum(datum: Distribution): PreprocessedDatum { + const sorted = datum.values.slice().sort((a, b) => a - b); + const median = getQuantile(sorted, 0.5); + const q1 = getQuantile(sorted, 0.25); + const q3 = getQuantile(sorted, 0.75); + const iqr = q3 - q1; + /** Index of the first value >= q1 - 1.5 * IQR (low whisker) */ + const iWhiskerLow = BinarySearch.firstGteqIndex(sorted, q1 - 1.5 * iqr, x => x) + const stop = BinarySearch.firstGteqIndex(sorted, q3 + 1.5 * iqr, x => x); + /** Index of the last value <= q3 + 1.5 * IQR (high whisker) */ + const iWhiskerHigh = (stop >= sorted.length || sorted[stop] > q3 + 1.5 * iqr) ? stop - 1 : stop; + + return { + position: datum.position, + values: sorted, + median, + boxLow: q1, + boxHigh: q3, + whiskerLow: sorted[iWhiskerLow], + whiskerHigh: sorted[iWhiskerHigh], + outliersLow: sorted.slice(0, iWhiskerLow), + outliersHigh: sorted.slice(iWhiskerHigh + 1, undefined), + minimum: sorted[0], + maximum: sorted[sorted.length - 1], + }; } -function computeYPositions_ProbabilityOrder(probabilities: Probabilities): YPositions { - const alphabet = Object.keys(probabilities); - const start: { [letter: string]: number[] } = {}; - const end: { [letter: string]: number[] } = {}; - for (const letter of alphabet) { - start[letter] = []; - end[letter] = []; +export function getQuantile(sortedValues: number[], p: number) { + const i_ = (sortedValues.length - 1) * p; + if (i_ >= sortedValues.length - 1) { + return sortedValues[sortedValues.length - 1]; } - const n = Math.max(0, ...alphabet.map(letter => probabilities[letter].length)); - for (let i = 0; i < n; i++) { - let cum = 0; - alphabet.sort((a, b) => (probabilities[b][i] ?? 0) - (probabilities[a][i] ?? 0)); - for (const letter of alphabet) { - start[letter].push(cum); - cum += probabilities[letter][i] ?? 0; - end[letter].push(cum); + const i = Math.floor(i_); + const q = i_ - i; + return sortedValues[i] * (1 - q) + sortedValues[i + 1] * q; +} + +/** Gets the Y-axis limits for the given preprocessed data */ +function getExtremes(data: { [position: number]: PreprocessedDatum }[]) { + let min = Infinity; + let max = -Infinity; + + for (const dataset of data) { + for (const position in dataset) { + const datum = dataset[position]; + if (datum.minimum < min) min = datum.minimum; + if (datum.maximum > max) max = datum.maximum; } } - return { start, end }; -} -function normalizeOrder(present: string[], order: string[]) { - const presentSet = new Set(present); - const orderSet = new Set(order); - const ordered = order.filter(s => presentSet.has(s)); - const rest = present.filter(s => !orderSet.has(s)); - return ordered.concat(rest); + return { + min: min === Infinity ? undefined : min, + max: max === -Infinity ? undefined : max, + }; } diff --git a/packages/nightingale-distribution-track/tests/mockData/sample-1.json b/packages/nightingale-distribution-track/tests/mockData/sample-1.json new file mode 100644 index 000000000..4a05c399c --- /dev/null +++ b/packages/nightingale-distribution-track/tests/mockData/sample-1.json @@ -0,0 +1,404 @@ +{ + "positions": [ + { + "position": 1, + "values": [289.8,123.6,75.6,244.3,135.4,245.9,247.3,302.5,64.4,218.0,243.6,231.0,245.3,133.1,287.9,291.0,246.7,242.5,27.5,105.4,249.4,236.2] + }, + { + "position": 2, + "values": [117.2,134.0,89.6,60.0,151.5,85.2,119.9,139.4,86.7,188.4,106.3,133.5,152.0,115.2,134.3,118.2,123.7,118.3,114.2,111.8,111.0,80.3,191.0,131.0,160.8,113.2,151.3,69.5,77.2,161.9,108.1,53.3,112.7,136.9,126.4,91.6,209.3,116.4,76.2,122.0,69.5,137.4,135.5,119.1,122.2,110.6,117.0,16.2,148.0,187.1,118.4,73.7,121.7,126.0,55.4,119.7,88.0,106.6,109.0] + 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+ } + ] +} \ No newline at end of file diff --git a/packages/nightingale-distribution-track/tests/mockData/sample-distribution-data.json b/packages/nightingale-distribution-track/tests/mockData/sample-distribution-data.json deleted file mode 100644 index 8c64aa59c..000000000 --- a/packages/nightingale-distribution-track/tests/mockData/sample-distribution-data.json +++ /dev/null @@ -1,32 +0,0 @@ -{ - "__comment__": "This is real data coming from https://www.ebi.ac.uk/pdbe/graph-api/pdb/sequence_conservation/1tqn/1", - "identifier": "1tqn", - "main_track_color": "#808080", - "sub_track_color": "#d3d3d3", - "data": { - "index": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 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-describe("nightingale-distribution-track tests", () => { - test("foo", () => { - expect(2+2).toEqual(4); +import { getQuantile } from "../src/nightingale-distribution-track"; + + +describe("getQuantile", () => { + // test("foo", () => { + // expect(2 + 2).toEqual(4); + // }); + + // Basic quantile calculations + test("calculates median (0.5 quantile) of odd-length array", () => { + expect(getQuantile([1, 2, 3, 4, 5], 0.5)).toEqual(3); + }); + + test("calculates median (0.5 quantile) of even-length array", () => { + expect(getQuantile([1, 2, 3, 4], 0.5)).toEqual(2.5); + }); + + // Edge cases for quantile values + test("returns minimum value for quantile 0", () => { + expect(getQuantile([1, 2, 3, 4, 5], 0)).toEqual(1); + }); + + test("returns maximum value for quantile 1", () => { + expect(getQuantile([1, 2, 3, 4, 5], 1)).toEqual(5); + }); + + // Quartile calculations + test("calculates first quartile (0.25)", () => { + expect(getQuantile([1, 2, 3, 4, 5], 0.25)).toEqual(2); + }); + + test("calculates third quartile (0.75)", () => { + expect(getQuantile([1, 2, 3, 4, 5], 0.75)).toEqual(4); + }); + + // Small arrays + test("handles single-element array", () => { + expect(getQuantile([5], 0.5)).toEqual(5); + expect(getQuantile([5], 0.1)).toEqual(5); + }); + + test("handles two-element array", () => { + expect(getQuantile([1, 5], 0.5)).toEqual(3); + expect(getQuantile([1, 5], 0.1)).toEqual(1.4); + expect(getQuantile([1, 5], 0.25)).toEqual(2); + expect(getQuantile([1, 5], 0.75)).toEqual(4); + expect(getQuantile([1, 5], 0.9)).toEqual(4.6); + }); + + // Negative numbers + test("works with negative values", () => { + expect(getQuantile([-5, -3, 0, 3, 5], 0.5)).toEqual(0); + }); + + test("calculates quantile with all negative values", () => { + expect(getQuantile([-5, -4, -3, -2, -1], 0.5)).toEqual(-3); }); -}); -// TODO tests + // Floating-point values + test("works with floating-point values", () => { + expect(getQuantile([1.5, 2.5, 3.5, 4.5], 0.5)).toEqual(3); + }); + + // Duplicate values + test("handles array with duplicate values", () => { + expect(getQuantile([1, 2, 2, 2, 5], 0.5)).toEqual(2); + }); + + // Various array sizes + test("calculates quantile for larger array", () => { + const largeArray = Array.from({ length: 101 }, (_, i) => i); + expect(getQuantile(largeArray, 0.5)).toEqual(50); + }); + + test("calculates deciles correctly", () => { + const array = Array.from({ length: 11 }, (_, i) => i); + expect(getQuantile(array, 0.1)).toEqual(1); + expect(getQuantile(array, 0.2)).toEqual(2); + expect(getQuantile(array, 0.9)).toEqual(9); + }); +}); diff --git a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.mdx b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.mdx index 785841335..3eec0d724 100644 --- a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.mdx +++ b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.mdx @@ -1,6 +1,6 @@ import { Meta, Description } from "@storybook/addon-docs"; -import Readme from "../../packages/nightingale-conservation-track/README.md"; +import Readme from "../../packages/nightingale-distribution-track/README.md"; import ParentReadme from "../../packages/nightingale-new-core/src/nightingale-base-element.md"; import dimensionsReadme from "../../packages/nightingale-new-core/src/mixins/withDimensions/README.md"; import highlightReadme from "../../packages/nightingale-new-core/src/mixins/withHighlight/README.md"; @@ -10,7 +10,7 @@ import positionReadme from "../../packages/nightingale-new-core/src/mixins/withP import resizableReadme from "../../packages/nightingale-new-core/src/mixins/withResizable/README.md"; import zoomReadme from "../../packages/nightingale-new-core/src/mixins/withZoom/README.md"; - + {Readme} diff --git a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts index 9f077d725..8657c7c9b 100644 --- a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts +++ b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts @@ -2,52 +2,60 @@ import { type ArgTypes, Meta, Story } from "@storybook/web-components"; import { html } from "lit-html"; import "../../packages/nightingale-distribution-track/src/index"; import { type DistributionData } from "../../packages/nightingale-distribution-track/src/nightingale-distribution-track"; -import sampleDistributionData from "../../packages/nightingale-distribution-track/tests/mockData/sample-distribution-data.json"; +import sampleDistributionData from "../../packages/nightingale-distribution-track/tests/mockData/sample-1.json"; export default { title: "Components/Tracks/Distribution Track" } as Meta; const DefaultArgs = { - "letter-order": "default", "min-width": 400, "height": 200, "highlight-event": "onmouseover", "highlight-color": "#EB3BFF22", "margin-color": "#ffffffdd", + "y-min": 0 as number | undefined, + "y-max": undefined as number | undefined, + "hide-outliers": false, }; type Args = typeof DefaultArgs; const ArgumentTypes: Partial> = { "highlight-event": { control: "select", options: ["onmouseover", "onclick"] }, - "letter-order": { control: "select", options: ["default", "probability"] }, + "y-min": { control: "select", options: [undefined, 0, 100, 200, 300, 400, 500] }, + "y-max": { control: "select", options: [undefined, 0, 100, 200, 300, 400, 500] }, }; -const sampleSequence = "MALYGTHSHGLFKKLGIPGPTPLPFLGNILSYHKGFCMFDMECHKKYGKVWGFYDGQQPVLAITDPDMIKTVLVKECYSVFTNRRPFGPVGFMKSAISIAEDEEWKRLRSLLSPTFTSGKLKEMVPIIAQYGDVLVRNLRREAETGKPVTLKDVFGAYSMDVITSTSFGVNIDSLNNPQDPFVENTKKLLRFDFLDPFFLSITVFPFLIPILEVLNICVFPREVTNFLRKSVKRMKESRLEDTQKHRVDFLQLMIDSQNSKETESHKALSDLELVAQSIIFIFAGYETTSSVLSFIMYELATHPDVQQKLQEEIDAVLPNKAPPTYDTVLQMEYLDMVVNETLRLFPIAMRLERVCKKDVEINGMFIPKGVVVMIPSYALHRDPKYWTEPEKFLPERFSKKNKDNIDPYIYTPFGSGPRNCIGMRFALMNMKLALIRVLQNFSFKPCKETQIPLKLSLGGLLQPEKPVVLKVESRDGTVSGAHHHH"; - -function prepareDistributionData(data: typeof sampleDistributionData): DistributionData { - const out: DistributionData = { - index: data.data.index, - probabilities: {}, - }; - for (const field in data.data) { - if (data.data.hasOwnProperty(field) && field.startsWith('probability_')) { - const letter = field.slice('probability_'.length); - out.probabilities[letter] = data.data[field as keyof typeof data.data]; - } - } - return out; +const sampleSequence = "MALYGTHSHGLFKKLGIPGPTPLPFLGNILSYHKGFCMFDMECHKKYGKVWGFYDGQQPVLAITDPDMIKTVLVKECYSVFTNRRPFGPVGFMKSAISIA"; + +function prepareDistributionData(data: DistributionData[number]): DistributionData { + return [ + { + name: 'Data1', + color: '#0088ff', + positions: data.positions, + }, + { + name: 'Data2', + color: '#ff8800', + positions: data.positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.9) })), + }, + ]; } -function prepareLinegraphData(data: typeof sampleDistributionData) { +function prepareLinegraphData(data: DistributionData) { + const values = data[0].positions.map(pos => ({ position: pos.position, value: pos.values.reduce((a, b) => a + b, 0) / pos.values.length })); + const bulgarianConstant = 10 / Math.max(...values.map(v => v.value)); + values.forEach(v => v.value *= bulgarianConstant); // I don't know how to set Y-range to linegraph track, this will do + const chart1 = { name: "chart1", color: "#707070", fill: "#808080", lineCurve: "curveStep", range: [0, 10], - values: data.data.index.map((position, i) => ({ position, value: data.data.conservation_score[i] })), + values: values, }; return [chart1]; } @@ -64,7 +72,8 @@ function nightingaleNavigation(args: Args & { length: number }) { length="${args["length"]}" highlight-color=${args["highlight-color"]} margin-color=${args["margin-color"]} - show-highlight + show-highlight + display-end="10" > `; @@ -125,7 +134,9 @@ function nightingaleDistributionTrack(args: Args & { length: number, id: number margin-top=10 margin-bottom=20 use-ctrl-to-zoom - letter-order=${args["letter-order"]} + y-min=${args["y-min"]} + y-max=${args["y-max"]} + ?hide-outliers=${args["hide-outliers"]} > `; @@ -156,14 +167,17 @@ function makeStory(options: { length: number }): Story { const story: Story = template.bind({}); story.args = { ...DefaultArgs }; story.argTypes = ArgumentTypes; + const distributionData = prepareDistributionData(sampleDistributionData as any); + const linegraphData = prepareLinegraphData(distributionData); + story.play = async () => { await customElements.whenDefined("nightingale-linegraph-track"); for (const track of document.getElementsByTagName("nightingale-linegraph-track")) { - (track as any).data = prepareLinegraphData(sampleDistributionData); + (track as any).data = linegraphData; } await customElements.whenDefined("nightingale-distribution-track"); for (const track of document.getElementsByTagName("nightingale-distribution-track")) { - (track as any).data = prepareDistributionData(sampleDistributionData); + (track as any).data = distributionData; } }; return story; @@ -173,3 +187,27 @@ function makeStory(options: { length: number }): Story { export const LinegraphAndDistribution = makeStory({ length: sampleSequence.length, }); + +// function processDistributionData(csvData: string): DistributionData { +// console.log('csvData', csvData.length) +// const lines = csvData.trim().split('\n').map(line => line.trim()).filter(line => line.length > 0); +// const header = lines[0].split(',').map(h => h.trim()); +// const unp_res_id = header.indexOf('unp_res_id'); +// const raw_score = header.indexOf('raw_score'); +// const grouped: { [unp_res_id: number]: number[] } = {}; +// for (let i = 1; i < lines.length; i++) { +// const values = lines[i].split(',').map(v => v.trim()); +// const resId = parseInt(values[unp_res_id]); +// const score = parseFloat(values[raw_score]); +// (grouped[resId] ??= []).push(score); +// } +// const resIds = Object.keys(grouped).map(Number).sort((a, b) => a - b); +// return { +// positions: resIds.map(pos => ({ +// position: pos, +// values: grouped[pos] +// })), +// index: [1, 2, 3], +// probabilities: { 'A': [1, 1, 1] }, +// }; +// } From 32075203ae7fa1afde88471c06cf7f0c63b81d40 Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Wed, 10 Jun 2026 13:57:57 +0100 Subject: [PATCH 03/32] nightingale-distribution-track: zoomed-out visualization --- .../src/nightingale-distribution-track.ts | 101 ++++++++++++++++-- .../NightingaleDistributionTrack.stories.ts | 50 ++++----- 2 files changed, 117 insertions(+), 34 deletions(-) diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts index bad0f5fe1..e4c94b632 100644 --- a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts +++ b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts @@ -13,7 +13,7 @@ import NightingaleElement, { withResizable, withZoom, } from "@nightingale-elements/nightingale-new-core"; -import { BaseType, select, Selection, color, scaleLinear, randomNormal, randomUniform, randomLcg } from "d3"; +import { BaseType, color, randomLcg, randomUniform, scaleLinear, select, Selection } from "d3"; import { html, PropertyValues } from "lit"; import { property } from "lit/decorators.js"; @@ -46,6 +46,8 @@ const WHISKER_REL_WIDTH = 0.6; const JITTER_REL_WIDTH = 0.4; /** Radius for the circles representing outliers */ const OUTLIER_RADIUS = 2; +/** Column widths in CSS pixels, between which transition from "background" to "foreground" visualization happens */ +const FG_BG_TRANSITION_BASE_WIDTHS = [4, 5]; interface Distribution { @@ -207,7 +209,6 @@ export default class NightingaleDistributionTrack extends withCanvas( if (!this.data || !this.preprocessedData) return; const nData = this.data.length; - const scale = this.canvasScale; const baseWidthInCss = this.getSingleBaseWidth(); const baseWidth = scale * baseWidthInCss; @@ -215,11 +216,12 @@ export default class NightingaleDistributionTrack extends withCanvas( const columnHeight = scale * (this["height"] - this["margin-top"] - this["margin-bottom"]); const xColumnOffset = baseWidth * 0.5 * COLUMN_GAP; const xColumnWidth = baseWidth * (1 - COLUMN_GAP); + const xColumnOffsetRight = xColumnOffset + xColumnWidth; const xBoxWidth = xColumnWidth / nData * (1 - BOX_GAP); const yScale = scaleLinear(this.getYLimits(), [columnOffset + columnHeight, columnOffset]); const outlierRadius = scale * OUTLIER_RADIUS; - const yMedianExtra = scale * 1; + const [fgAlpha, bgAlpha] = this.getFgBgOpacity(baseWidthInCss / nData); ctx.lineWidth = scale * Math.min(LINE_WIDTH, MAX_REL_LINE_WIDTH * baseWidthInCss); ctx.strokeStyle = STROKE_COLOR; @@ -227,7 +229,47 @@ export default class NightingaleDistributionTrack extends withCanvas( ctx.textBaseline = "middle"; const start = Math.floor(this.getSeqPositionFromX(0) ?? 1); - const end = Math.floor(this.getSeqPositionFromX(this.width) ?? 1); + /** Exclusive */ + const stop = Math.floor(this.getSeqPositionFromX(this.width) ?? 1) + 1; + + // "Background" + if (bgAlpha !== 0) { + for (let iData = 0; iData < nData; iData++) { + const dataset = this.preprocessedData.datasets[iData]; + if (!dataset) continue; + + const dataColor = this.data[iData].color ?? DEFAULT_DATA_COLOR; + const boxFill = dataColor; + const boxStroke = color(boxFill)!.darker(2).formatHex(); + ctx.globalAlpha = 0.25 * bgAlpha; + + const x = (i: number) => scale * this.getXFromSeqPosition(i); + // const yMin = (i: number) => yScale(dataset[i].minimum); + // const yMax = (i: number) => yScale(dataset[i].maximum); + const yWhiskerLow = (i: number) => yScale(dataset[i].whiskerLow); + const yWhiskerHigh = (i: number) => yScale(dataset[i].whiskerHigh); + // const yBoxLow = (i: number) => yScale(dataset[i].boxLow); + // const yBoxHigh = (i: number) => yScale(dataset[i].boxHigh); + const yMedianLow = (i: number) => yScale(dataset[i].median + yMedianExtra); + const yMedianHigh = (i: number) => yScale(dataset[i].median - yMedianExtra); + + const segments = getContiguousSegments(start, stop, i => i in dataset); + for (const segment of segments) { + ctx.globalAlpha = 0.25 * bgAlpha; + ctx.fillStyle = boxFill; + // drawSilhouette(ctx, segment, x, yMin, yMax, [xColumnOffset, xColumnOffsetRight], 'fill'); + drawSilhouette(ctx, segment, x, yWhiskerLow, yWhiskerHigh, [xColumnOffset, xColumnOffsetRight], 'fill'); + // drawSilhouette(ctx, segment, x, yBoxLow, yBoxHigh, [xColumnOffset, xColumnOffsetRight], 'fill'); + ctx.globalAlpha = 0.5 * bgAlpha; + ctx.fillStyle = boxStroke; + ctx.strokeStyle = boxStroke; + drawSilhouette(ctx, segment, x, yMedianLow, yMedianHigh, [xColumnOffset, xColumnOffsetRight], 'fill+stroke'); + } + } + } + + // "Foreground" + if (fgAlpha===0) return; for (let iData = 0; iData < nData; iData++) { const dataset = this.preprocessedData.datasets[iData]; if (!dataset) continue; @@ -243,7 +285,7 @@ export default class NightingaleDistributionTrack extends withCanvas( const xWhiskerEnd = xCenter + xWhiskerHalfWidth; const xJitterHalfWidth = 0.5 * JITTER_REL_WIDTH * xBoxWidth; - for (let i = start; i <= end; i++) { + for (let i = start; i < stop; i++) { const datum = dataset[i]; if (!datum) continue; @@ -254,7 +296,7 @@ export default class NightingaleDistributionTrack extends withCanvas( const yWhiskerLow = yScale(datum.whiskerLow); const yWhiskerHigh = yScale(datum.whiskerHigh); - ctx.globalAlpha = 1; + ctx.globalAlpha = fgAlpha; // Whiskers ctx.strokeStyle = boxStroke; @@ -284,7 +326,7 @@ export default class NightingaleDistributionTrack extends withCanvas( const xJitter = xJitterHalfWidth !== 0 ? randomUniform.source(randomLcg(i * nData + iData))(xCenter - xJitterHalfWidth, xCenter + xJitterHalfWidth) : () => xCenter; - ctx.globalAlpha = 0.25; + ctx.globalAlpha = 0.25 * fgAlpha; ctx.fillStyle = boxStroke; for (const outlier of datum.outliersHigh) { ctx.beginPath(); @@ -297,6 +339,7 @@ export default class NightingaleDistributionTrack extends withCanvas( ctx.fill(); } } + // TODO: fix outlier alpha rendering when 0 < fgAlpha < 1 (can be done without two canvases? with globalCompositeOperation?) } } } @@ -320,6 +363,18 @@ export default class NightingaleDistributionTrack extends withCanvas( ctx.fillRect(marginLeft, canvasHeight - marginBottom, canvasWidth - marginLeft - marginRight, marginBottom); } + private getFgBgOpacity(baseWidthInCss: number): [fgAlpha: number, bgAlpha: number] { + const [transitionMin, transitionMax] = FG_BG_TRANSITION_BASE_WIDTHS; + if (baseWidthInCss <= transitionMin) { + return [0, 1]; + } else if (baseWidthInCss >= transitionMax) { + return [1, 0]; + } else { + const fgAlpha = (baseWidthInCss - transitionMin) / (transitionMax - transitionMin); + return [fgAlpha, 1 - fgAlpha]; + } + } + protected updateHighlight() { if (!this.highlighted) return; const highlights = this.highlighted @@ -531,3 +586,35 @@ function getExtremes(data: { [position: number]: PreprocessedDatum }[]) { max: max === -Infinity ? undefined : max, }; } + +function getContiguousSegments(start: number, stop: number, isPresent: (i: number) => boolean): [start: number, stop: number][] { + const segments: [number, number][] = []; + for (let i = start; i < stop; i++) { + if (isPresent(i)) { + if (i === segments[segments.length - 1]?.[1]) { + segments[segments.length - 1][1]++; + } else { + segments.push([i, i + 1]); + } + } + } + return segments; +} + +function drawSilhouette(ctx: CanvasRenderingContext2D, [sStart, sStop]: [number, number], getX: (i: number) => number, getYLow: (i: number) => number, getYHigh: (i: number) => number, [columnOffsetLeft, columnOffsetRight]: [number, number], style: 'fill' | 'stroke' | 'fill+stroke') { + ctx.beginPath(); + for (let i = sStart; i < sStop; i++) { + const x = getX(i); + const yHigh = getYHigh(i); + ctx.lineTo(x + columnOffsetLeft, yHigh); + ctx.lineTo(x + columnOffsetRight, yHigh); + } + for (let i = sStop - 1; i >= sStart; i--) { + const x = getX(i); + const yLow = getYLow(i); + ctx.lineTo(x + columnOffsetRight, yLow); + ctx.lineTo(x + columnOffsetLeft, yLow); + } + if (style.includes('fill')) ctx.fill(); + if (style.includes('stroke')) ctx.stroke(); +} diff --git a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts index 8657c7c9b..c9ac9317c 100644 --- a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts +++ b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts @@ -27,23 +27,43 @@ const ArgumentTypes: Partial> = { }; -const sampleSequence = "MALYGTHSHGLFKKLGIPGPTPLPFLGNILSYHKGFCMFDMECHKKYGKVWGFYDGQQPVLAITDPDMIKTVLVKECYSVFTNRRPFGPVGFMKSAISIA"; +const nDataRepeat = 10; + +const sampleSequence = "MALYGTHSHGLFKKLGIPGPTPLPFLGNILSYHKGFCMFDMECHKKYGKVWGFYDGQQPVLAITDPDMIKTVLVKECYSVFTNRRPFGPVGFMKSAISIA".repeat(nDataRepeat); function prepareDistributionData(data: DistributionData[number]): DistributionData { + const positions = data.positions.slice(); + const shift = data.positions.length; + for (let i = 1; i < nDataRepeat; i++) { + for (const pos of data.positions) { + positions.push({ position: pos.position + i * shift, values: pos.values }); + } + } + return [ { name: 'Data1', color: '#0088ff', - positions: data.positions, + positions: positions, + // positions: remove(positions, 3, 5, 6, 35), // DEBUG }, { name: 'Data2', color: '#ff8800', - positions: data.positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.9) })), + positions: positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), + // positions: remove(positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), 1, 7), // DEBUG }, ]; } +function remove(arr: T[], ...indices: number[]) { + const out = arr.slice(); + for (const i of indices.sort((a, b) => b - a)) { + out.splice(i, 1); + } + return out; +} + function prepareLinegraphData(data: DistributionData) { const values = data[0].positions.map(pos => ({ position: pos.position, value: pos.values.reduce((a, b) => a + b, 0) / pos.values.length })); const bulgarianConstant = 10 / Math.max(...values.map(v => v.value)); @@ -187,27 +207,3 @@ function makeStory(options: { length: number }): Story { export const LinegraphAndDistribution = makeStory({ length: sampleSequence.length, }); - -// function processDistributionData(csvData: string): DistributionData { -// console.log('csvData', csvData.length) -// const lines = csvData.trim().split('\n').map(line => line.trim()).filter(line => line.length > 0); -// const header = lines[0].split(',').map(h => h.trim()); -// const unp_res_id = header.indexOf('unp_res_id'); -// const raw_score = header.indexOf('raw_score'); -// const grouped: { [unp_res_id: number]: number[] } = {}; -// for (let i = 1; i < lines.length; i++) { -// const values = lines[i].split(',').map(v => v.trim()); -// const resId = parseInt(values[unp_res_id]); -// const score = parseFloat(values[raw_score]); -// (grouped[resId] ??= []).push(score); -// } -// const resIds = Object.keys(grouped).map(Number).sort((a, b) => a - b); -// return { -// positions: resIds.map(pos => ({ -// position: pos, -// values: grouped[pos] -// })), -// index: [1, 2, 3], -// probabilities: { 'A': [1, 1, 1] }, -// }; -// } From 84a26e119a7d2197d721e2f50a05487c21f2d909 Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Wed, 10 Jun 2026 16:26:25 +0100 Subject: [PATCH 04/32] nightingale-distribution-track: refactor zoomed-out and zoomed-in visualization --- .../src/nightingale-distribution-track.ts | 208 +++++++++++------- 1 file changed, 129 insertions(+), 79 deletions(-) diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts index e4c94b632..179adf0eb 100644 --- a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts +++ b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts @@ -49,6 +49,10 @@ const OUTLIER_RADIUS = 2; /** Column widths in CSS pixels, between which transition from "background" to "foreground" visualization happens */ const FG_BG_TRANSITION_BASE_WIDTHS = [4, 5]; +function makeStrokeColor(fillColor: string): string | undefined { + return color(fillColor)?.darker(2).formatHex(); +} + interface Distribution { position: number, @@ -193,7 +197,13 @@ export default class NightingaleDistributionTrack extends withCanvas( if (!this._drawStamp.update().changed) return; this.adjustCanvasCtxLogicalSize(); this.clearCanvas(); - this.drawBoxplot(); + const params = this.getDrawingMeasurements(); + if (params.bgAlpha > 0) { + this.drawSimplifiedVisualization(params); + } + if (params.fgAlpha > 0) { + this.drawBoxplotVisualization(params); + } this.drawMargins(); } @@ -203,93 +213,35 @@ export default class NightingaleDistributionTrack extends withCanvas( ctx.clearRect(0, 0, ctx.canvas.width, ctx.canvas.height); } - private drawBoxplot() { + /** Draw full boxplot visualization ("foreground" / zoomed-in) */ + private drawBoxplotVisualization(params: ReturnType) { const ctx = this.canvasCtx; if (!ctx) return; if (!this.data || !this.preprocessedData) return; - const nData = this.data.length; - const scale = this.canvasScale; - const baseWidthInCss = this.getSingleBaseWidth(); - const baseWidth = scale * baseWidthInCss; - const columnOffset = scale * this["margin-top"]; - const columnHeight = scale * (this["height"] - this["margin-top"] - this["margin-bottom"]); - const xColumnOffset = baseWidth * 0.5 * COLUMN_GAP; - const xColumnWidth = baseWidth * (1 - COLUMN_GAP); - const xColumnOffsetRight = xColumnOffset + xColumnWidth; - const xBoxWidth = xColumnWidth / nData * (1 - BOX_GAP); - const yScale = scaleLinear(this.getYLimits(), [columnOffset + columnHeight, columnOffset]); - const outlierRadius = scale * OUTLIER_RADIUS; - const yMedianExtra = scale * 1; - const [fgAlpha, bgAlpha] = this.getFgBgOpacity(baseWidthInCss / nData); - - ctx.lineWidth = scale * Math.min(LINE_WIDTH, MAX_REL_LINE_WIDTH * baseWidthInCss); - ctx.strokeStyle = STROKE_COLOR; - ctx.textAlign = "center"; - ctx.textBaseline = "middle"; + const { nDatasets, xColumnLeft, xColumnWidth, xScale, yScale, yMedianExtra, lineWidth, outlierRadius, fgAlpha, start, stop } = params; + ctx.lineWidth = lineWidth; - const start = Math.floor(this.getSeqPositionFromX(0) ?? 1); - /** Exclusive */ - const stop = Math.floor(this.getSeqPositionFromX(this.width) ?? 1) + 1; - - // "Background" - if (bgAlpha !== 0) { - for (let iData = 0; iData < nData; iData++) { - const dataset = this.preprocessedData.datasets[iData]; - if (!dataset) continue; - - const dataColor = this.data[iData].color ?? DEFAULT_DATA_COLOR; - const boxFill = dataColor; - const boxStroke = color(boxFill)!.darker(2).formatHex(); - ctx.globalAlpha = 0.25 * bgAlpha; - - const x = (i: number) => scale * this.getXFromSeqPosition(i); - // const yMin = (i: number) => yScale(dataset[i].minimum); - // const yMax = (i: number) => yScale(dataset[i].maximum); - const yWhiskerLow = (i: number) => yScale(dataset[i].whiskerLow); - const yWhiskerHigh = (i: number) => yScale(dataset[i].whiskerHigh); - // const yBoxLow = (i: number) => yScale(dataset[i].boxLow); - // const yBoxHigh = (i: number) => yScale(dataset[i].boxHigh); - const yMedianLow = (i: number) => yScale(dataset[i].median + yMedianExtra); - const yMedianHigh = (i: number) => yScale(dataset[i].median - yMedianExtra); - - const segments = getContiguousSegments(start, stop, i => i in dataset); - for (const segment of segments) { - ctx.globalAlpha = 0.25 * bgAlpha; - ctx.fillStyle = boxFill; - // drawSilhouette(ctx, segment, x, yMin, yMax, [xColumnOffset, xColumnOffsetRight], 'fill'); - drawSilhouette(ctx, segment, x, yWhiskerLow, yWhiskerHigh, [xColumnOffset, xColumnOffsetRight], 'fill'); - // drawSilhouette(ctx, segment, x, yBoxLow, yBoxHigh, [xColumnOffset, xColumnOffsetRight], 'fill'); - ctx.globalAlpha = 0.5 * bgAlpha; - ctx.fillStyle = boxStroke; - ctx.strokeStyle = boxStroke; - drawSilhouette(ctx, segment, x, yMedianLow, yMedianHigh, [xColumnOffset, xColumnOffsetRight], 'fill+stroke'); - } - } - } - - // "Foreground" - if (fgAlpha===0) return; - for (let iData = 0; iData < nData; iData++) { - const dataset = this.preprocessedData.datasets[iData]; + for (let iDataset = 0; iDataset < nDatasets; iDataset++) { + const dataset = this.preprocessedData.datasets[iDataset]; if (!dataset) continue; - const dataColor = this.data[iData].color ?? DEFAULT_DATA_COLOR; + const dataColor = this.data[iDataset].color ?? DEFAULT_DATA_COLOR; const boxFill = dataColor; - const boxStroke = color(boxFill)!.darker(2).formatHex(); + const boxStroke = makeStrokeColor(boxFill)!; - const xBoxOffset = xColumnOffset + xColumnWidth * (iData + 0.5 * BOX_GAP) / nData; + const xBoxOffset = xColumnLeft + (iDataset + 0.5 * BOX_GAP) * xColumnWidth / nDatasets; + const xBoxWidth = (1 - BOX_GAP) * xColumnWidth / nDatasets; const xCenter = xBoxOffset + 0.5 * xBoxWidth; - const xWhiskerHalfWidth = 0.5 * WHISKER_REL_WIDTH * xBoxWidth; - const xWhiskerOffset = xCenter - xWhiskerHalfWidth; - const xWhiskerEnd = xCenter + xWhiskerHalfWidth; - const xJitterHalfWidth = 0.5 * JITTER_REL_WIDTH * xBoxWidth; + const xWhiskerLeft = xCenter - 0.5 * WHISKER_REL_WIDTH * xBoxWidth; + const xWhiskerRight = xCenter + 0.5 * WHISKER_REL_WIDTH * xBoxWidth; + const xJitterHalfwidth = 0.5 * JITTER_REL_WIDTH * xBoxWidth; for (let i = start; i < stop; i++) { const datum = dataset[i]; if (!datum) continue; - const x = scale * this.getXFromSeqPosition(i); + const x = xScale(i); const yMedian = yScale(datum.median); const yBoxLow = yScale(datum.boxLow); const yBoxHigh = yScale(datum.boxHigh); @@ -301,10 +253,10 @@ export default class NightingaleDistributionTrack extends withCanvas( // Whiskers ctx.strokeStyle = boxStroke; ctx.beginPath(); - ctx.moveTo(x + xWhiskerOffset, yWhiskerHigh); - ctx.lineTo(x + xWhiskerEnd, yWhiskerHigh); - ctx.moveTo(x + xWhiskerOffset, yWhiskerLow); - ctx.lineTo(x + xWhiskerEnd, yWhiskerLow); + ctx.moveTo(x + xWhiskerLeft, yWhiskerHigh); + ctx.lineTo(x + xWhiskerRight, yWhiskerHigh); + ctx.moveTo(x + xWhiskerLeft, yWhiskerLow); + ctx.lineTo(x + xWhiskerRight, yWhiskerLow); ctx.moveTo(x + xCenter, yWhiskerHigh); ctx.lineTo(x + xCenter, yWhiskerLow); ctx.stroke(); @@ -323,8 +275,8 @@ export default class NightingaleDistributionTrack extends withCanvas( // Outliers if (!this["hide-outliers"]) { - const xJitter = xJitterHalfWidth !== 0 ? - randomUniform.source(randomLcg(i * nData + iData))(xCenter - xJitterHalfWidth, xCenter + xJitterHalfWidth) + const xJitter = xJitterHalfwidth !== 0 ? + randomUniform.source(randomLcg(i * nDatasets + iDataset))(xCenter - xJitterHalfwidth, xCenter + xJitterHalfwidth) : () => xCenter; ctx.globalAlpha = 0.25 * fgAlpha; ctx.fillStyle = boxStroke; @@ -344,6 +296,104 @@ export default class NightingaleDistributionTrack extends withCanvas( } } + /** Draw simplified visualization ("background" / zoomed-out) */ + private drawSimplifiedVisualization(params: ReturnType) { + const ctx = this.canvasCtx; + if (!ctx) return; + if (!this.data || !this.preprocessedData) return; + + const { nDatasets, xColumnLeft, xColumnRight, xScale, yScale, yMedianExtra, lineWidth, bgAlpha, start, stop } = params; + ctx.lineWidth = lineWidth; + + for (let iDataset = 0; iDataset < nDatasets; iDataset++) { + const dataset = this.preprocessedData.datasets[iDataset]; + if (!dataset) continue; + + const dataColor = this.data[iDataset].color ?? DEFAULT_DATA_COLOR; + const boxFill = dataColor; + const boxStroke = makeStrokeColor(boxFill)!; + ctx.globalAlpha = 0.25 * bgAlpha; + + // const yMin = (i: number) => yScale(dataset[i].minimum); + // const yMax = (i: number) => yScale(dataset[i].maximum); + const yWhiskerLow = (i: number) => yScale(dataset[i].whiskerLow); + const yWhiskerHigh = (i: number) => yScale(dataset[i].whiskerHigh); + // const yBoxLow = (i: number) => yScale(dataset[i].boxLow); + // const yBoxHigh = (i: number) => yScale(dataset[i].boxHigh); + const yMedianLow = (i: number) => yScale(dataset[i].median + yMedianExtra); + const yMedianHigh = (i: number) => yScale(dataset[i].median - yMedianExtra); + + const segments = getContiguousSegments(start, stop, i => i in dataset); + for (const segment of segments) { + ctx.globalAlpha = 0.25 * bgAlpha; + ctx.fillStyle = boxFill; + // drawSilhouette(ctx, segment, xScale, yMin, yMax, [xColumnOffset, xColumnOffsetRight], 'fill'); + drawSilhouette(ctx, segment, xScale, yWhiskerLow, yWhiskerHigh, [xColumnLeft, xColumnRight], 'fill'); + // drawSilhouette(ctx, segment, xScale, yBoxLow, yBoxHigh, [xColumnOffset, xColumnOffsetRight], 'fill'); + ctx.globalAlpha = 0.5 * bgAlpha; + ctx.fillStyle = boxStroke; + ctx.strokeStyle = boxStroke; + drawSilhouette(ctx, segment, xScale, yMedianLow, yMedianHigh, [xColumnLeft, xColumnRight], 'fill+stroke'); + } + } + } + + private getDrawingMeasurements() { + const nDatasets = this.preprocessedData?.datasets.length ?? 1; + const canvasScale = this.canvasScale; + const xBaseWidthInCss = this.getSingleBaseWidth(); + const xBaseWidth = canvasScale * xBaseWidthInCss; + const xColumnLeft = xBaseWidth * 0.5 * COLUMN_GAP; + const xColumnWidth = xBaseWidth * (1 - COLUMN_GAP); + const xColumnRight = xColumnLeft + xColumnWidth; + const xScale = (i: number) => canvasScale * this.getXFromSeqPosition(i); + + const yColumnOffset = canvasScale * this["margin-top"]; + const yColumnHeight = canvasScale * (this["height"] - this["margin-top"] - this["margin-bottom"]); + const yScale = scaleLinear(this.getYLimits(), [yColumnOffset + yColumnHeight, yColumnOffset]); + const yMedianExtra = canvasScale * 1; + + const lineWidth = canvasScale * Math.min(LINE_WIDTH, MAX_REL_LINE_WIDTH * xBaseWidthInCss); + const outlierRadius = canvasScale * OUTLIER_RADIUS; + + + const [fgAlpha, bgAlpha] = this.getFgBgOpacity(xBaseWidthInCss / nDatasets); + + const start = Math.floor(this.getSeqPositionFromX(0) ?? 1); + const stop = Math.floor(this.getSeqPositionFromX(this.width) ?? 1) + 1; + + return { + /** Number of dataset (independent variables) */ + nDatasets, + /** Ratio of canvas logical size versus canvas display size */ + canvasScale, + /** Horizontal offset of the displayed column from the beginning of the slot, in canvas space */ + xColumnLeft, + /** Horizontal offset of the right edge of displayed column from the beginning of the slot, in canvas space */ + xColumnRight, + /** Width of displayed column, in canvas space */ + xColumnWidth, + /** Scale from sequence position to horizontal offset of the slot in canvas space (does not consider column gap) */ + xScale, + /** Scale from value of independent variable to vertical position in canvas space */ + yScale, + /** Amount for vertically thickening the median rectangle, in canvas space */ + yMedianExtra, + /** Line width for strokes, in canvas space */ + lineWidth, + /** Circle radius for drawing outliers, in canvas space */ + outlierRadius, + /** Opacity of the "foreground" (zoomed-in) visualization */ + fgAlpha, + /** Opacity of the "background" (zoomed-out) visualization */ + bgAlpha, + /** Sequence position of the first rendered datapoint */ + start, + /** Sequence position of the last rendered datapoint + 1 */ + stop, + }; + } + private drawMargins() { const ctx = this.canvasCtx; if (!ctx) return; From 72b41af04923a0b3101f76919c5dde5aa31ea7b7 Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Thu, 11 Jun 2026 11:20:32 +0100 Subject: [PATCH 05/32] nightingale-distribution-track: fix outlier rendering with alpha --- .../src/nightingale-distribution-track.ts | 173 ++++++++++-------- .../nightingale-distribution-track.test.ts | 4 - 2 files changed, 96 insertions(+), 81 deletions(-) diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts index 179adf0eb..effa2dd91 100644 --- a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts +++ b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts @@ -27,8 +27,6 @@ const ATTRIBUTES_THAT_TRIGGER_REFRESH: string[] = [ const ATTRIBUTES_THAT_TRIGGER_DATA_RESET: string[] = [] satisfies (keyof NightingaleDistributionTrack)[]; -/** Color for rectangle stroke */ -const STROKE_COLOR = "#D3D3D3"; /** Line width for rectangle stroke */ const LINE_WIDTH = 1; /** Maximum line width relative to column width (overrides `LINE_WIDTH` when zoomed out too much) */ @@ -49,8 +47,8 @@ const OUTLIER_RADIUS = 2; /** Column widths in CSS pixels, between which transition from "background" to "foreground" visualization happens */ const FG_BG_TRANSITION_BASE_WIDTHS = [4, 5]; -function makeStrokeColor(fillColor: string): string | undefined { - return color(fillColor)?.darker(2).formatHex(); +function makeStrokeColor(dataColor: string): string | undefined { + return color(dataColor)?.darker(2).formatHex(); } @@ -196,39 +194,70 @@ export default class NightingaleDistributionTrack extends withCanvas( private _draw(): void { if (!this._drawStamp.update().changed) return; this.adjustCanvasCtxLogicalSize(); - this.clearCanvas(); - const params = this.getDrawingMeasurements(); - if (params.bgAlpha > 0) { - this.drawSimplifiedVisualization(params); + if (!this.canvasCtx) return; + this.clearCanvas(this.canvasCtx); + this.drawData(this.canvasCtx); + this.drawMargins(this.canvasCtx); + } + + private getOffscreenCanvas(): [canvas: HTMLCanvasElement, canvasContext?: CanvasRenderingContext2D] { + this._offscreenCanvas ??= document.createElement("canvas"); + const width = this.canvasCtx?.canvas.width ?? 1; + const height = this.canvasCtx?.canvas.height ?? 1; + if (this._offscreenCanvas.width !== width) { + this._offscreenCanvas.width = width; } - if (params.fgAlpha > 0) { - this.drawBoxplotVisualization(params); + if (this._offscreenCanvas.height !== height) { + this._offscreenCanvas.height = height; } - this.drawMargins(); + const ctx = this._offscreenCanvas.getContext('2d') ?? undefined; + return [this._offscreenCanvas, ctx]; } + private _offscreenCanvas?: HTMLCanvasElement; - private clearCanvas() { - const ctx = this.canvasCtx; - if (!ctx) return; + private clearCanvas(ctx: CanvasRenderingContext2D) { ctx.clearRect(0, 0, ctx.canvas.width, ctx.canvas.height); } + private drawData(ctx: CanvasRenderingContext2D) { + const [fgAlpha, bgAlpha] = this.getFgBgOpacity(); + + // Draw background (zoomed-out) visualization + if (bgAlpha > 0) { + this.drawSimplifiedVisualization(ctx, bgAlpha); + } + + // Draw foreground (zoomed-in) visualization + if (fgAlpha === 1) { + // Draw foreground visualization directly + this.drawBoxplotVisualization(ctx); + } else if (fgAlpha > 0) { + // Draw foreground visualization via an auxiliary canvas (cannot be drawn directly to the main canvas, because overlapping outliers would create opacity > fgAlpha) + const [auxCanvas, auxCtx] = this.getOffscreenCanvas(); + if (auxCtx) { + this.clearCanvas(auxCtx); + this.drawBoxplotVisualization(auxCtx); + ctx.globalAlpha = fgAlpha; + ctx.drawImage(auxCanvas, 0, 0); + } + } + } + /** Draw full boxplot visualization ("foreground" / zoomed-in) */ - private drawBoxplotVisualization(params: ReturnType) { - const ctx = this.canvasCtx; - if (!ctx) return; + private drawBoxplotVisualization(ctx: CanvasRenderingContext2D) { if (!this.data || !this.preprocessedData) return; - const { nDatasets, xColumnLeft, xColumnWidth, xScale, yScale, yMedianExtra, lineWidth, outlierRadius, fgAlpha, start, stop } = params; + const { xColumnLeft, xColumnWidth, xScale, yScale, yMedianExtra, lineWidth, outlierRadius, start, stop } = this.getDrawingMeasurements(); ctx.lineWidth = lineWidth; + const nDatasets = this.preprocessedData?.datasets.length ?? 1; for (let iDataset = 0; iDataset < nDatasets; iDataset++) { const dataset = this.preprocessedData.datasets[iDataset]; if (!dataset) continue; const dataColor = this.data[iDataset].color ?? DEFAULT_DATA_COLOR; - const boxFill = dataColor; - const boxStroke = makeStrokeColor(boxFill)!; + const fillColor = dataColor; + const strokeColor = makeStrokeColor(dataColor)!; const xBoxOffset = xColumnLeft + (iDataset + 0.5 * BOX_GAP) * xColumnWidth / nDatasets; const xBoxWidth = (1 - BOX_GAP) * xColumnWidth / nDatasets; @@ -248,10 +277,10 @@ export default class NightingaleDistributionTrack extends withCanvas( const yWhiskerLow = yScale(datum.whiskerLow); const yWhiskerHigh = yScale(datum.whiskerHigh); - ctx.globalAlpha = fgAlpha; + ctx.globalAlpha = 1; // Whiskers - ctx.strokeStyle = boxStroke; + ctx.strokeStyle = strokeColor; ctx.beginPath(); ctx.moveTo(x + xWhiskerLeft, yWhiskerHigh); ctx.lineTo(x + xWhiskerRight, yWhiskerHigh); @@ -262,14 +291,14 @@ export default class NightingaleDistributionTrack extends withCanvas( ctx.stroke(); // Box - ctx.fillStyle = boxFill; - ctx.strokeStyle = boxStroke; + ctx.fillStyle = fillColor; + ctx.strokeStyle = strokeColor; ctx.fillRect(x + xBoxOffset, yBoxHigh, xBoxWidth, yBoxLow - yBoxHigh); ctx.strokeRect(x + xBoxOffset, yBoxHigh, xBoxWidth, yBoxLow - yBoxHigh); // Median - ctx.fillStyle = boxStroke; - ctx.strokeStyle = boxStroke; + ctx.fillStyle = strokeColor; + ctx.strokeStyle = strokeColor; ctx.fillRect(x + xBoxOffset, yMedian - yMedianExtra, xBoxWidth, 2 * yMedianExtra); ctx.strokeRect(x + xBoxOffset, yMedian - yMedianExtra, xBoxWidth, 2 * yMedianExtra); @@ -278,8 +307,8 @@ export default class NightingaleDistributionTrack extends withCanvas( const xJitter = xJitterHalfwidth !== 0 ? randomUniform.source(randomLcg(i * nDatasets + iDataset))(xCenter - xJitterHalfwidth, xCenter + xJitterHalfwidth) : () => xCenter; - ctx.globalAlpha = 0.25 * fgAlpha; - ctx.fillStyle = boxStroke; + ctx.globalAlpha = 0.25; + ctx.fillStyle = strokeColor; for (const outlier of datum.outliersHigh) { ctx.beginPath(); ctx.arc(x + xJitter(), yScale(outlier), outlierRadius, 0, 2 * Math.PI); @@ -291,28 +320,25 @@ export default class NightingaleDistributionTrack extends withCanvas( ctx.fill(); } } - // TODO: fix outlier alpha rendering when 0 < fgAlpha < 1 (can be done without two canvases? with globalCompositeOperation?) } } } /** Draw simplified visualization ("background" / zoomed-out) */ - private drawSimplifiedVisualization(params: ReturnType) { - const ctx = this.canvasCtx; - if (!ctx) return; + private drawSimplifiedVisualization(ctx: CanvasRenderingContext2D, alpha: number) { if (!this.data || !this.preprocessedData) return; - const { nDatasets, xColumnLeft, xColumnRight, xScale, yScale, yMedianExtra, lineWidth, bgAlpha, start, stop } = params; + const { xColumnLeft, xColumnRight, xScale, yScale, yMedianExtra, lineWidth, start, stop } = this.getDrawingMeasurements(); ctx.lineWidth = lineWidth; + const nDatasets = this.preprocessedData?.datasets.length ?? 1; for (let iDataset = 0; iDataset < nDatasets; iDataset++) { const dataset = this.preprocessedData.datasets[iDataset]; if (!dataset) continue; const dataColor = this.data[iDataset].color ?? DEFAULT_DATA_COLOR; - const boxFill = dataColor; - const boxStroke = makeStrokeColor(boxFill)!; - ctx.globalAlpha = 0.25 * bgAlpha; + const fillColor = dataColor; + const strokeColor = makeStrokeColor(dataColor)!; // const yMin = (i: number) => yScale(dataset[i].minimum); // const yMax = (i: number) => yScale(dataset[i].maximum); @@ -325,21 +351,37 @@ export default class NightingaleDistributionTrack extends withCanvas( const segments = getContiguousSegments(start, stop, i => i in dataset); for (const segment of segments) { - ctx.globalAlpha = 0.25 * bgAlpha; - ctx.fillStyle = boxFill; - // drawSilhouette(ctx, segment, xScale, yMin, yMax, [xColumnOffset, xColumnOffsetRight], 'fill'); + ctx.globalAlpha = 0.25 * alpha; + ctx.fillStyle = fillColor; + // drawSilhouette(ctx, segment, xScale, yMin, yMax, [xColumnLeft, xColumnRight], 'fill'); drawSilhouette(ctx, segment, xScale, yWhiskerLow, yWhiskerHigh, [xColumnLeft, xColumnRight], 'fill'); - // drawSilhouette(ctx, segment, xScale, yBoxLow, yBoxHigh, [xColumnOffset, xColumnOffsetRight], 'fill'); - ctx.globalAlpha = 0.5 * bgAlpha; - ctx.fillStyle = boxStroke; - ctx.strokeStyle = boxStroke; + // drawSilhouette(ctx, segment, xScale, yBoxLow, yBoxHigh, [xColumnLeft, xColumnRight], 'fill'); + + ctx.globalAlpha = 0.5 * alpha; + ctx.fillStyle = strokeColor; + ctx.strokeStyle = strokeColor; drawSilhouette(ctx, segment, xScale, yMedianLow, yMedianHigh, [xColumnLeft, xColumnRight], 'fill+stroke'); } } } + private drawMargins(ctx: CanvasRenderingContext2D) { + const canvasWidth = ctx.canvas.width; + const canvasHeight = ctx.canvas.height; + const marginLeft = this["margin-left"] * this.canvasScale; + const marginRight = this["margin-right"] * this.canvasScale; + const marginTop = this["margin-top"] * this.canvasScale; + const marginBottom = this["margin-bottom"] * this.canvasScale; + + ctx.globalAlpha = 1; + ctx.fillStyle = this["margin-color"]; + ctx.fillRect(0, 0, marginLeft, canvasHeight); + ctx.fillRect(canvasWidth - marginRight, 0, marginRight, canvasHeight); + ctx.fillRect(marginLeft, 0, canvasWidth - marginLeft - marginRight, marginTop); + ctx.fillRect(marginLeft, canvasHeight - marginBottom, canvasWidth - marginLeft - marginRight, marginBottom); + } + private getDrawingMeasurements() { - const nDatasets = this.preprocessedData?.datasets.length ?? 1; const canvasScale = this.canvasScale; const xBaseWidthInCss = this.getSingleBaseWidth(); const xBaseWidth = canvasScale * xBaseWidthInCss; @@ -356,15 +398,10 @@ export default class NightingaleDistributionTrack extends withCanvas( const lineWidth = canvasScale * Math.min(LINE_WIDTH, MAX_REL_LINE_WIDTH * xBaseWidthInCss); const outlierRadius = canvasScale * OUTLIER_RADIUS; - - const [fgAlpha, bgAlpha] = this.getFgBgOpacity(xBaseWidthInCss / nDatasets); - const start = Math.floor(this.getSeqPositionFromX(0) ?? 1); const stop = Math.floor(this.getSeqPositionFromX(this.width) ?? 1) + 1; return { - /** Number of dataset (independent variables) */ - nDatasets, /** Ratio of canvas logical size versus canvas display size */ canvasScale, /** Horizontal offset of the displayed column from the beginning of the slot, in canvas space */ @@ -383,10 +420,6 @@ export default class NightingaleDistributionTrack extends withCanvas( lineWidth, /** Circle radius for drawing outliers, in canvas space */ outlierRadius, - /** Opacity of the "foreground" (zoomed-in) visualization */ - fgAlpha, - /** Opacity of the "background" (zoomed-out) visualization */ - bgAlpha, /** Sequence position of the first rendered datapoint */ start, /** Sequence position of the last rendered datapoint + 1 */ @@ -394,33 +427,19 @@ export default class NightingaleDistributionTrack extends withCanvas( }; } - private drawMargins() { - const ctx = this.canvasCtx; - if (!ctx) return; - - const canvasWidth = ctx.canvas.width; - const canvasHeight = ctx.canvas.height; - const marginLeft = this["margin-left"] * this.canvasScale; - const marginRight = this["margin-right"] * this.canvasScale; - const marginTop = this["margin-top"] * this.canvasScale; - const marginBottom = this["margin-bottom"] * this.canvasScale; - - ctx.globalAlpha = 1; - ctx.fillStyle = this["margin-color"]; - ctx.fillRect(0, 0, marginLeft, canvasHeight); - ctx.fillRect(canvasWidth - marginRight, 0, marginRight, canvasHeight); - ctx.fillRect(marginLeft, 0, canvasWidth - marginLeft - marginRight, marginTop); - ctx.fillRect(marginLeft, canvasHeight - marginBottom, canvasWidth - marginLeft - marginRight, marginBottom); - } - - private getFgBgOpacity(baseWidthInCss: number): [fgAlpha: number, bgAlpha: number] { + /** Compute opacity for the "foreground" (zoomed-in) and "background" (zoomed-out) visualization */ + private getFgBgOpacity(): [fgAlpha: number, bgAlpha: number] { + const nDatasets = this.preprocessedData?.datasets.length ?? 1; + /** Approximate boxplot box width, in CSS pixels. No need to consider column gap and box gap here. */ + const boxWidth = this.getSingleBaseWidth() / nDatasets; const [transitionMin, transitionMax] = FG_BG_TRANSITION_BASE_WIDTHS; - if (baseWidthInCss <= transitionMin) { + + if (boxWidth <= transitionMin) { return [0, 1]; - } else if (baseWidthInCss >= transitionMax) { + } else if (boxWidth >= transitionMax) { return [1, 0]; } else { - const fgAlpha = (baseWidthInCss - transitionMin) / (transitionMax - transitionMin); + const fgAlpha = (boxWidth - transitionMin) / (transitionMax - transitionMin); return [fgAlpha, 1 - fgAlpha]; } } @@ -539,7 +558,7 @@ export default class NightingaleDistributionTrack extends withCanvas( this.dispatchEvent(customEvent); } - private getPointedDatum(svgX: number, svgY: number): { position: number, datum: PreprocessedDatum | undefined } | undefined { + private getPointedDatum(svgX: number, _svgY: number): { position: number, datum: PreprocessedDatum | undefined } | undefined { const continuousPosition = this.getSeqPositionFromX(svgX); if (continuousPosition === undefined) return undefined; const position = Math.floor(continuousPosition); diff --git a/packages/nightingale-distribution-track/tests/nightingale-distribution-track.test.ts b/packages/nightingale-distribution-track/tests/nightingale-distribution-track.test.ts index 46ae1bebe..978ad0851 100644 --- a/packages/nightingale-distribution-track/tests/nightingale-distribution-track.test.ts +++ b/packages/nightingale-distribution-track/tests/nightingale-distribution-track.test.ts @@ -2,10 +2,6 @@ import { getQuantile } from "../src/nightingale-distribution-track"; describe("getQuantile", () => { - // test("foo", () => { - // expect(2 + 2).toEqual(4); - // }); - // Basic quantile calculations test("calculates median (0.5 quantile) of odd-length array", () => { expect(getQuantile([1, 2, 3, 4, 5], 0.5)).toEqual(3); From 2897b9faf7270daeb7cfbfa25c5394d5c9d8856a Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Fri, 12 Jun 2026 16:33:24 +0100 Subject: [PATCH 06/32] nightingale-distribution-track: experiment with quartile computation --- .../src/nightingale-distribution-track.ts | 231 ++++++++++++++++-- .../NightingaleDistributionTrack.stories.ts | 28 ++- 2 files changed, 224 insertions(+), 35 deletions(-) diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts index effa2dd91..4265cbd53 100644 --- a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts +++ b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts @@ -13,7 +13,7 @@ import NightingaleElement, { withResizable, withZoom, } from "@nightingale-elements/nightingale-new-core"; -import { BaseType, color, randomLcg, randomUniform, scaleLinear, select, Selection } from "d3"; +import { BaseType, color, randomLcg, randomUniform, scaleLinear, select, Selection, TypedArray } from "d3"; import { html, PropertyValues } from "lit"; import { property } from "lit/decorators.js"; @@ -127,7 +127,9 @@ export default class NightingaleDistributionTrack extends withCanvas( } set data(data: DistributionData | undefined) { this.#data = data; + console.time('preprocessData') this.preprocessedData = data ? preprocessData(data) : undefined; + console.timeEnd('preprocessData') this.createTrack(); } /** Return the range of Y values corresponding to bottom and top of the viewport (excluding margins) */ @@ -195,9 +197,11 @@ export default class NightingaleDistributionTrack extends withCanvas( if (!this._drawStamp.update().changed) return; this.adjustCanvasCtxLogicalSize(); if (!this.canvasCtx) return; + console.time('draw distr') this.clearCanvas(this.canvasCtx); this.drawData(this.canvasCtx); this.drawMargins(this.canvasCtx); + console.timeEnd('draw distr') } private getOffscreenCanvas(): [canvas: HTMLCanvasElement, canvasContext?: CanvasRenderingContext2D] { @@ -580,54 +584,123 @@ function preprocessData(data: DistributionData) { function preprocessDataset(dataset: DistributionDataset) { const out: { [position: number]: PreprocessedDatum } = {}; + + // const flat = dataset.positions.flatMap(pos => pos.values); + // console.time('flat sort') + // flat.sort((a, b) => a - b) + // console.timeEnd('flat sort') + // multisort(dataset.positions.map(pos => pos.values)) + for (const datum of dataset.positions) { out[datum.position] = preprocessDatum(datum); } return out; } +function multisort(arrays: number[][]) { + const n = arrays.reduce((count, array) => count + array.length, 0); + const indices = new Uint32Array(n); + const sources = new Uint32Array(n); + const values = new Float32Array(n); + let target = 0; + console.time('multisort fill') + for (let iArray = 0, nArrays = arrays.length; iArray < nArrays; iArray++) { + const array = arrays[iArray]; + for (let i = 0, m = array.length; i < m; i++) { + indices[target] = target; + sources[target] = iArray; + values[target] = array[i]; + target++; + } + } + console.timeEnd('multisort fill') + + console.time('multisort sort') + // values.sort(); + indices.sort((i, j) => sources[i] - sources[j] || values[i] - values[j]); + console.timeEnd('multisort sort') + + // const flat = dataset.positions.flatMap(pos => pos.values); + // TODO: continue here +} + interface PreprocessedDatum { position: number, - values: number[], + values: number[] | TypedArray, median: number, boxLow: number, boxHigh: number, whiskerLow: number, whiskerHigh: number, - outliersLow: number[], - outliersHigh: number[], + outliersLow: number[] | TypedArray, + outliersHigh: number[] | TypedArray, minimum: number, maximum: number, } function preprocessDatum(datum: Distribution): PreprocessedDatum { - const sorted = datum.values.slice().sort((a, b) => a - b); - const median = getQuantile(sorted, 0.5); - const q1 = getQuantile(sorted, 0.25); - const q3 = getQuantile(sorted, 0.75); + // const sorted = new Float32Array(datum.values).sort(); + const values = new Float32Array(datum.values); + + const [q1, med, q3] = sneakyQuartiles(values); + + // const medTrue = getQuantile(sorted, 0.5); + // const q1True = getQuantile(sorted, 0.25); + // const q3True = getQuantile(sorted, 0.75); + + // if (med !== medTrue) throw new Error('med !== medTrue') + // if (q1 !== q1True) throw new Error('q1 !== q1True') + // if (q3 !== q3True) throw new Error('q3 !== q3True') + const iqr = q3 - q1; - /** Index of the first value >= q1 - 1.5 * IQR (low whisker) */ - const iWhiskerLow = BinarySearch.firstGteqIndex(sorted, q1 - 1.5 * iqr, x => x) - const stop = BinarySearch.firstGteqIndex(sorted, q3 + 1.5 * iqr, x => x); - /** Index of the last value <= q3 + 1.5 * IQR (high whisker) */ - const iWhiskerHigh = (stop >= sorted.length || sorted[stop] > q3 + 1.5 * iqr) ? stop - 1 : stop; + // /** Index of the first value >= q1 - 1.5 * IQR (low whisker) */ + // const iWhiskerLow = BinarySearch.firstGteqIndex(sorted, q1 - 1.5 * iqr, x => x) + // const stop = BinarySearch.firstGteqIndex(sorted, q3 + 1.5 * iqr, x => x); + // /** Index of the last value <= q3 + 1.5 * IQR (high whisker) */ + // const iWhiskerHigh = (stop >= sorted.length || sorted[stop] > q3 + 1.5 * iqr) ? stop - 1 : stop; + const _whiskerLow = q1 - 1.5 * iqr; + const _whiskerHigh = q3 + 1.5 * iqr; + const iWhiskerLow = splitByPivot(values, 0, values.length, _whiskerLow, getAux(values.length)); + const iWhiskerHighExcl = splitByPivot(values, iWhiskerLow, values.length, _whiskerHigh, getAux(values.length)); // This is not exact if _whiskerHigh occurs in data + const whiskerLow = min(values, iWhiskerLow, iWhiskerHighExcl); + const whiskerHigh = max(values, iWhiskerLow, iWhiskerHighExcl); return { position: datum.position, - values: sorted, - median, + values: values, + median: med, boxLow: q1, boxHigh: q3, - whiskerLow: sorted[iWhiskerLow], - whiskerHigh: sorted[iWhiskerHigh], - outliersLow: sorted.slice(0, iWhiskerLow), - outliersHigh: sorted.slice(iWhiskerHigh + 1, undefined), - minimum: sorted[0], - maximum: sorted[sorted.length - 1], + // whiskerLow: sorted[iWhiskerLow], + // whiskerHigh: sorted[iWhiskerHigh], + whiskerLow, + whiskerHigh, + // outliersLow: sorted.slice(0, iWhiskerLow), + // outliersHigh: sorted.slice(iWhiskerHigh + 1, undefined), + outliersLow: values.slice(0, iWhiskerLow), + outliersHigh: values.slice(iWhiskerHighExcl, undefined), + // minimum: sorted[0], + // maximum: sorted[sorted.length - 1], + minimum: min(values), + maximum: max(values), }; } -export function getQuantile(sortedValues: number[], p: number) { +// TIMINGS (nDatasets=1, nRepeat=1000): +// preprocessData original: 2055 ms +// preprocessData original Float32Array: 560 ms +// preprocessData sneakyQuartiles: 526 ms + +// flat sort: 3150 ms +// flat sort Float32Array: 564 ms +// multisort sort: 2472 ms + +// preprocessData - only compute medians (sort): 2028 +// preprocessData - only compute medians (sort, Float32Array): 500 +// preprocessData - only compute medians (d3): 1409 +// preprocessData - only compute medians (d3, Float32Array): 1485 + +export function getQuantile(sortedValues: ArrayLike, p: number) { const i_ = (sortedValues.length - 1) * p; if (i_ >= sortedValues.length - 1) { return sortedValues[sortedValues.length - 1]; @@ -687,3 +760,117 @@ function drawSilhouette(ctx: CanvasRenderingContext2D, [sStart, sStop]: [number, if (style.includes('fill')) ctx.fill(); if (style.includes('stroke')) ctx.stroke(); } + +export function max(array: ArrayLike, from = 0, to = array.length): number { + let out = array[from]; + for (let i = from; i < to; i++) { + const value = array[i]; + if (value > out) out = value; + } + return out; +} + +export function min(array: ArrayLike, from = 0, to = array.length): number { + let out = array[from]; + for (let i = from; i < to; i++) { + const value = array[i]; + if (value < out) out = value; + } + return out; +} + +export function sneakyQuartiles(values: Float32Array): [q1: number, median: number, q3: number] { + if (values.length < 4) { + values.sort(); + return [getQuantile(values, 0.25), getQuantile(values, 0.5), getQuantile(values, 0.75)]; + } + + const j1_ = (values.length - 1) * 0.25; + const j1 = Math.ceil(j1_); + const z1 = j1 - j1_; + + const j2_ = (values.length - 1) * 0.5; + const j2 = Math.ceil(j2_); + const z2 = j2 - j2_; + + const j3_ = (values.length - 1) * 0.75; + const j3 = Math.ceil(j3_); + const z3 = j3 - j3_; + + split(values, j2, 0, undefined); + split(values, j1, 0, j2); + split(values, j3, j2, undefined); + + const q1 = max(values, 0, j1) * z1 + min(values, j1, j2) * (1 - z1); + const q2 = max(values, j1, j2) * z2 + min(values, j2, j3) * (1 - z2); + const q3 = max(values, j2, j3) * z3 + min(values, j3, undefined) * (1 - z3); + return [q1, q2, q3]; +} + +function mid(a: number, b: number, c: number): number { + if (a < b) { + if (b < c) return b; + if (a < c) return c; + return a; + } else { + // a >= b + if (b > c) return b; + if (a > c) return c; + return a; + } +} + +let _aux: Float32Array | undefined; +function getAux(length: number): Float32Array { + if (_aux?.length !== length) { + _aux = new Float32Array(length); + } + return _aux; +} + +/** Rearrange values in `array[from:to]` so that `max(array[from:splitPosition]) <= min(array[splitPosition:to])`. */ +function split(array: Float32Array, splitPosition: number, from = 0, to = array.length) { + const aux = getAux(array.length); + // let pivLow = min(array, from, to); + // let pivHigh = max(array, from, to); + + while (true) { + let pivot = mid(array[0], array[splitPosition], array[array.length - 1]); + // let pivot = (pivLow * (to - splitPosition) + pivHigh * (splitPosition - from)) / (to - from); + let s = splitByPivot(array, from, to, pivot, aux); + if (s === from || s === to) { + const minimum = min(array, from, to); + const maximum = max(array, from, to); + if (minimum === maximum) return; + pivot = 0.5 * (minimum + maximum); + s = splitByPivot(array, from, to, pivot, aux); + } + if (s === splitPosition) { + return; + } else if (s < splitPosition) { + from = s; + // pivLow = pivot; + } else { + to = s; + // pivHigh = pivot; + } + } +} + +/** Rearrange values in `array[from:to]` so that all values =pivot. Return index of the first value >=pivot. */ +function splitByPivot(array: Float32Array, from: number, to: number, pivot: number, aux: Float32Array) { + let tgtLeft = from; + let tgtRight = to - 1; + for (let i = from; i < to; i++) { + const element = array[i]; + if (element < pivot) { + aux[tgtLeft++] = element; + } else { + aux[tgtRight--] = element; + } + } + for (let i = from; i < to; i++) { + array[i] = aux[i]; + } + return tgtLeft; +} diff --git a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts index c9ac9317c..ac1d74caf 100644 --- a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts +++ b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts @@ -27,11 +27,12 @@ const ArgumentTypes: Partial> = { }; -const nDataRepeat = 10; +const nDataRepeat = 100; const sampleSequence = "MALYGTHSHGLFKKLGIPGPTPLPFLGNILSYHKGFCMFDMECHKKYGKVWGFYDGQQPVLAITDPDMIKTVLVKECYSVFTNRRPFGPVGFMKSAISIA".repeat(nDataRepeat); function prepareDistributionData(data: DistributionData[number]): DistributionData { + console.time('prepareDistributionData') const positions = data.positions.slice(); const shift = data.positions.length; for (let i = 1; i < nDataRepeat; i++) { @@ -39,6 +40,7 @@ function prepareDistributionData(data: DistributionData[number]): DistributionDa positions.push({ position: pos.position + i * shift, values: pos.values }); } } + console.timeEnd('prepareDistributionData') return [ { @@ -47,12 +49,12 @@ function prepareDistributionData(data: DistributionData[number]): DistributionDa positions: positions, // positions: remove(positions, 3, 5, 6, 35), // DEBUG }, - { - name: 'Data2', - color: '#ff8800', - positions: positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), - // positions: remove(positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), 1, 7), // DEBUG - }, + // { + // name: 'Data2', + // color: '#ff8800', + // positions: positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), + // // positions: remove(positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), 1, 7), // DEBUG + // }, ]; } @@ -93,7 +95,7 @@ function nightingaleNavigation(args: Args & { length: number }) { highlight-color=${args["highlight-color"]} margin-color=${args["margin-color"]} show-highlight - display-end="10" + display-end="100" > `; @@ -188,13 +190,13 @@ function makeStory(options: { length: number }): Story { story.args = { ...DefaultArgs }; story.argTypes = ArgumentTypes; const distributionData = prepareDistributionData(sampleDistributionData as any); - const linegraphData = prepareLinegraphData(distributionData); + // const linegraphData = prepareLinegraphData(distributionData); story.play = async () => { - await customElements.whenDefined("nightingale-linegraph-track"); - for (const track of document.getElementsByTagName("nightingale-linegraph-track")) { - (track as any).data = linegraphData; - } + // await customElements.whenDefined("nightingale-linegraph-track"); + // for (const track of document.getElementsByTagName("nightingale-linegraph-track")) { + // (track as any).data = linegraphData; + // } await customElements.whenDefined("nightingale-distribution-track"); for (const track of document.getElementsByTagName("nightingale-distribution-track")) { (track as any).data = distributionData; From 015b2761faa38702234c9b84c339f866c89a1f5b Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Fri, 12 Jun 2026 17:03:59 +0100 Subject: [PATCH 07/32] nightingale-distribution-track: remove sneakyQuartile implementation (insignificant optimization) --- .../src/nightingale-distribution-track.ts | 182 ++---------------- 1 file changed, 17 insertions(+), 165 deletions(-) diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts index 4265cbd53..be27253db 100644 --- a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts +++ b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts @@ -639,67 +639,33 @@ interface PreprocessedDatum { } function preprocessDatum(datum: Distribution): PreprocessedDatum { - // const sorted = new Float32Array(datum.values).sort(); - const values = new Float32Array(datum.values); - - const [q1, med, q3] = sneakyQuartiles(values); - - // const medTrue = getQuantile(sorted, 0.5); - // const q1True = getQuantile(sorted, 0.25); - // const q3True = getQuantile(sorted, 0.75); - - // if (med !== medTrue) throw new Error('med !== medTrue') - // if (q1 !== q1True) throw new Error('q1 !== q1True') - // if (q3 !== q3True) throw new Error('q3 !== q3True') + const sorted = new Float32Array(datum.values).sort(); + const median = getQuantile(sorted, 0.5); + const q1 = getQuantile(sorted, 0.25); + const q3 = getQuantile(sorted, 0.75); const iqr = q3 - q1; - // /** Index of the first value >= q1 - 1.5 * IQR (low whisker) */ - // const iWhiskerLow = BinarySearch.firstGteqIndex(sorted, q1 - 1.5 * iqr, x => x) - // const stop = BinarySearch.firstGteqIndex(sorted, q3 + 1.5 * iqr, x => x); - // /** Index of the last value <= q3 + 1.5 * IQR (high whisker) */ - // const iWhiskerHigh = (stop >= sorted.length || sorted[stop] > q3 + 1.5 * iqr) ? stop - 1 : stop; - const _whiskerLow = q1 - 1.5 * iqr; - const _whiskerHigh = q3 + 1.5 * iqr; - const iWhiskerLow = splitByPivot(values, 0, values.length, _whiskerLow, getAux(values.length)); - const iWhiskerHighExcl = splitByPivot(values, iWhiskerLow, values.length, _whiskerHigh, getAux(values.length)); // This is not exact if _whiskerHigh occurs in data - const whiskerLow = min(values, iWhiskerLow, iWhiskerHighExcl); - const whiskerHigh = max(values, iWhiskerLow, iWhiskerHighExcl); + /** Index of the first value >= q1 - 1.5 * IQR (low whisker) */ + const iWhiskerLow = BinarySearch.firstGteqIndex(sorted, q1 - 1.5 * iqr, x => x) + const stop = BinarySearch.firstGteqIndex(sorted, q3 + 1.5 * iqr, x => x); + /** Index of the last value <= q3 + 1.5 * IQR (high whisker) */ + const iWhiskerHigh = (stop >= sorted.length || sorted[stop] > q3 + 1.5 * iqr) ? stop - 1 : stop; return { position: datum.position, - values: values, - median: med, + values: sorted, + median: median, boxLow: q1, boxHigh: q3, - // whiskerLow: sorted[iWhiskerLow], - // whiskerHigh: sorted[iWhiskerHigh], - whiskerLow, - whiskerHigh, - // outliersLow: sorted.slice(0, iWhiskerLow), - // outliersHigh: sorted.slice(iWhiskerHigh + 1, undefined), - outliersLow: values.slice(0, iWhiskerLow), - outliersHigh: values.slice(iWhiskerHighExcl, undefined), - // minimum: sorted[0], - // maximum: sorted[sorted.length - 1], - minimum: min(values), - maximum: max(values), + whiskerLow: sorted[iWhiskerLow], + whiskerHigh: sorted[iWhiskerHigh], + outliersLow: sorted.slice(0, iWhiskerLow), + outliersHigh: sorted.slice(iWhiskerHigh + 1, undefined), + minimum: sorted[0], + maximum: sorted[sorted.length - 1], }; } -// TIMINGS (nDatasets=1, nRepeat=1000): -// preprocessData original: 2055 ms -// preprocessData original Float32Array: 560 ms -// preprocessData sneakyQuartiles: 526 ms - -// flat sort: 3150 ms -// flat sort Float32Array: 564 ms -// multisort sort: 2472 ms - -// preprocessData - only compute medians (sort): 2028 -// preprocessData - only compute medians (sort, Float32Array): 500 -// preprocessData - only compute medians (d3): 1409 -// preprocessData - only compute medians (d3, Float32Array): 1485 - export function getQuantile(sortedValues: ArrayLike, p: number) { const i_ = (sortedValues.length - 1) * p; if (i_ >= sortedValues.length - 1) { @@ -760,117 +726,3 @@ function drawSilhouette(ctx: CanvasRenderingContext2D, [sStart, sStop]: [number, if (style.includes('fill')) ctx.fill(); if (style.includes('stroke')) ctx.stroke(); } - -export function max(array: ArrayLike, from = 0, to = array.length): number { - let out = array[from]; - for (let i = from; i < to; i++) { - const value = array[i]; - if (value > out) out = value; - } - return out; -} - -export function min(array: ArrayLike, from = 0, to = array.length): number { - let out = array[from]; - for (let i = from; i < to; i++) { - const value = array[i]; - if (value < out) out = value; - } - return out; -} - -export function sneakyQuartiles(values: Float32Array): [q1: number, median: number, q3: number] { - if (values.length < 4) { - values.sort(); - return [getQuantile(values, 0.25), getQuantile(values, 0.5), getQuantile(values, 0.75)]; - } - - const j1_ = (values.length - 1) * 0.25; - const j1 = Math.ceil(j1_); - const z1 = j1 - j1_; - - const j2_ = (values.length - 1) * 0.5; - const j2 = Math.ceil(j2_); - const z2 = j2 - j2_; - - const j3_ = (values.length - 1) * 0.75; - const j3 = Math.ceil(j3_); - const z3 = j3 - j3_; - - split(values, j2, 0, undefined); - split(values, j1, 0, j2); - split(values, j3, j2, undefined); - - const q1 = max(values, 0, j1) * z1 + min(values, j1, j2) * (1 - z1); - const q2 = max(values, j1, j2) * z2 + min(values, j2, j3) * (1 - z2); - const q3 = max(values, j2, j3) * z3 + min(values, j3, undefined) * (1 - z3); - return [q1, q2, q3]; -} - -function mid(a: number, b: number, c: number): number { - if (a < b) { - if (b < c) return b; - if (a < c) return c; - return a; - } else { - // a >= b - if (b > c) return b; - if (a > c) return c; - return a; - } -} - -let _aux: Float32Array | undefined; -function getAux(length: number): Float32Array { - if (_aux?.length !== length) { - _aux = new Float32Array(length); - } - return _aux; -} - -/** Rearrange values in `array[from:to]` so that `max(array[from:splitPosition]) <= min(array[splitPosition:to])`. */ -function split(array: Float32Array, splitPosition: number, from = 0, to = array.length) { - const aux = getAux(array.length); - // let pivLow = min(array, from, to); - // let pivHigh = max(array, from, to); - - while (true) { - let pivot = mid(array[0], array[splitPosition], array[array.length - 1]); - // let pivot = (pivLow * (to - splitPosition) + pivHigh * (splitPosition - from)) / (to - from); - let s = splitByPivot(array, from, to, pivot, aux); - if (s === from || s === to) { - const minimum = min(array, from, to); - const maximum = max(array, from, to); - if (minimum === maximum) return; - pivot = 0.5 * (minimum + maximum); - s = splitByPivot(array, from, to, pivot, aux); - } - if (s === splitPosition) { - return; - } else if (s < splitPosition) { - from = s; - // pivLow = pivot; - } else { - to = s; - // pivHigh = pivot; - } - } -} - -/** Rearrange values in `array[from:to]` so that all values =pivot. Return index of the first value >=pivot. */ -function splitByPivot(array: Float32Array, from: number, to: number, pivot: number, aux: Float32Array) { - let tgtLeft = from; - let tgtRight = to - 1; - for (let i = from; i < to; i++) { - const element = array[i]; - if (element < pivot) { - aux[tgtLeft++] = element; - } else { - aux[tgtRight--] = element; - } - } - for (let i = from; i < to; i++) { - array[i] = aux[i]; - } - return tgtLeft; -} From cce933cc9e08b8172116f382b78be752901b14cb Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Fri, 12 Jun 2026 17:22:54 +0100 Subject: [PATCH 08/32] nightingale-distribution-track: sortIfNeeded --- .../src/nightingale-distribution-track.ts | 54 +++++++------------ .../NightingaleDistributionTrack.stories.ts | 3 +- 2 files changed, 22 insertions(+), 35 deletions(-) diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts index be27253db..4d2f82a9f 100644 --- a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts +++ b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts @@ -585,45 +585,12 @@ function preprocessData(data: DistributionData) { function preprocessDataset(dataset: DistributionDataset) { const out: { [position: number]: PreprocessedDatum } = {}; - // const flat = dataset.positions.flatMap(pos => pos.values); - // console.time('flat sort') - // flat.sort((a, b) => a - b) - // console.timeEnd('flat sort') - // multisort(dataset.positions.map(pos => pos.values)) - for (const datum of dataset.positions) { out[datum.position] = preprocessDatum(datum); } return out; } -function multisort(arrays: number[][]) { - const n = arrays.reduce((count, array) => count + array.length, 0); - const indices = new Uint32Array(n); - const sources = new Uint32Array(n); - const values = new Float32Array(n); - let target = 0; - console.time('multisort fill') - for (let iArray = 0, nArrays = arrays.length; iArray < nArrays; iArray++) { - const array = arrays[iArray]; - for (let i = 0, m = array.length; i < m; i++) { - indices[target] = target; - sources[target] = iArray; - values[target] = array[i]; - target++; - } - } - console.timeEnd('multisort fill') - - console.time('multisort sort') - // values.sort(); - indices.sort((i, j) => sources[i] - sources[j] || values[i] - values[j]); - console.timeEnd('multisort sort') - - // const flat = dataset.positions.flatMap(pos => pos.values); - // TODO: continue here -} - interface PreprocessedDatum { position: number, values: number[] | TypedArray, @@ -639,7 +606,7 @@ interface PreprocessedDatum { } function preprocessDatum(datum: Distribution): PreprocessedDatum { - const sorted = new Float32Array(datum.values).sort(); + const sorted = sortIfNeeded(new Float32Array(datum.values)); const median = getQuantile(sorted, 0.5); const q1 = getQuantile(sorted, 0.25); const q3 = getQuantile(sorted, 0.75); @@ -666,6 +633,25 @@ function preprocessDatum(datum: Distribution): PreprocessedDatum { }; } +/** Check whether `array` is sorted, sort if not. */ +function sortIfNeeded(array: T): T { + if (!arrayIsSorted(array)) { + array.sort(); + } + return array; +} + +/** Decide whether `array` is sorted. */ +function arrayIsSorted(array: TypedArray): boolean { + for (let i = 1, n = array.length; i < n; i++) { + if (array[i - 1] > array[i]) { + return false; + } + } + return true; +} + +/** Get p-quantile of the dataset. Input values must be sorted for this to work. */ export function getQuantile(sortedValues: ArrayLike, p: number) { const i_ = (sortedValues.length - 1) * p; if (i_ >= sortedValues.length - 1) { diff --git a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts index ac1d74caf..0b3ead68f 100644 --- a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts +++ b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts @@ -33,7 +33,8 @@ const sampleSequence = "MALYGTHSHGLFKKLGIPGPTPLPFLGNILSYHKGFCMFDMECHKKYGKVWGFYDG function prepareDistributionData(data: DistributionData[number]): DistributionData { console.time('prepareDistributionData') - const positions = data.positions.slice(); + // const positions = data.positions.slice(); + const positions = data.positions.map(pos => ({ position: pos.position, values: pos.values.sort() })); const shift = data.positions.length; for (let i = 1; i < nDataRepeat; i++) { for (const pos of data.positions) { From 7418c353cd168818a0d68772c67b2bbf70d8378d Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Mon, 15 Jun 2026 13:55:15 +0100 Subject: [PATCH 09/32] nightingale-distribution-track: zoomed-out-range attribute --- .../src/nightingale-distribution-track.ts | 82 +++++++++++++++---- .../NightingaleDistributionTrack.stories.ts | 26 +++--- 2 files changed, 81 insertions(+), 27 deletions(-) diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts index 4d2f82a9f..8997117a6 100644 --- a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts +++ b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts @@ -14,7 +14,7 @@ import NightingaleElement, { withZoom, } from "@nightingale-elements/nightingale-new-core"; import { BaseType, color, randomLcg, randomUniform, scaleLinear, select, Selection, TypedArray } from "d3"; -import { html, PropertyValues } from "lit"; +import { html, PropertyDeclaration, PropertyValues } from "lit"; import { property } from "lit/decorators.js"; @@ -22,7 +22,7 @@ const ATTRIBUTES_THAT_TRIGGER_REFRESH: string[] = [ "length", "width", "height", "margin-top", "margin-bottom", "margin-left", "margin-right", "margin-color", "font-family", "min-font-size", "fade-font-size", "max-font-size", - "y-min", "y-max", "hide-outliers", + "y-min", "y-max", "hide-outliers", "zoomed-out-range", ] satisfies (keyof NightingaleDistributionTrack)[]; const ATTRIBUTES_THAT_TRIGGER_DATA_RESET: string[] = [] satisfies (keyof NightingaleDistributionTrack)[]; @@ -66,11 +66,32 @@ export interface DistributionDataset { /** Type for `NightingaleDistributionTrack.data`` */ export type DistributionData = DistributionDataset[]; -const OptionalNumber = (str: string | null) => { +type AttributeConverter = NonNullable['converter']>; + +const OptionalNumberAttributeConverter: AttributeConverter = (str) => { if (str) return Number(str); return undefined; }; +function EnumAttributeConverter(allowedValues: readonly T[], defaultValue?: D): AttributeConverter { + const theDefault = defaultValue ?? allowedValues[0]; + + return (str) => { + if (!str) { + return theDefault; + } + if (allowedValues.includes(str as T)) { + return str as T; + } else { + console.warn(`Value '${str}' is not valid for attribute of type ${allowedValues.map(v => `'${v}'`).join(' | ')}. Falling back to default value ('${theDefault}').`); + return theDefault; + } + }; +} + +export const ZoomedOutRangeOptions = ['extremes', 'whiskers', 'box', 'none'] as const; +export type ZoomedOutRangeOption = typeof ZoomedOutRangeOptions[number]; + @customElementOnce("nightingale-distribution-track") export default class NightingaleDistributionTrack extends withCanvas( withManager( @@ -100,17 +121,21 @@ export default class NightingaleDistributionTrack extends withCanvas( "max-font-size": number = 24; /** Bottom limit for Y-axis (default: minimum computed from data) */ - @property({ converter: OptionalNumber }) + @property({ converter: OptionalNumberAttributeConverter }) "y-min"?: number; /** Top limit for Y-axis (default: maximum computed from data) */ - @property({ converter: OptionalNumber }) + @property({ converter: OptionalNumberAttributeConverter }) "y-max"?: number; /** Turns off rendering of outliers */ @property({ type: Boolean }) "hide-outliers"?: boolean; + /** What kind of data should be shown as shaded range in zoomed-out visualization */ + @property({ converter: EnumAttributeConverter(ZoomedOutRangeOptions, 'whiskers') }) + "zoomed-out-range": ZoomedOutRangeOption; // TODO: enum-type in other components? + #data?: DistributionData; private preprocessedData?: PreprocessedData; @@ -344,23 +369,43 @@ export default class NightingaleDistributionTrack extends withCanvas( const fillColor = dataColor; const strokeColor = makeStrokeColor(dataColor)!; - // const yMin = (i: number) => yScale(dataset[i].minimum); - // const yMax = (i: number) => yScale(dataset[i].maximum); - const yWhiskerLow = (i: number) => yScale(dataset[i].whiskerLow); - const yWhiskerHigh = (i: number) => yScale(dataset[i].whiskerHigh); - // const yBoxLow = (i: number) => yScale(dataset[i].boxLow); - // const yBoxHigh = (i: number) => yScale(dataset[i].boxHigh); const yMedianLow = (i: number) => yScale(dataset[i].median + yMedianExtra); const yMedianHigh = (i: number) => yScale(dataset[i].median - yMedianExtra); + let yRangeLow: ((i: number) => number) | undefined; + let yRangeHigh: ((i: number) => number) | undefined; + switch (this['zoomed-out-range']) { + case 'extremes': + yRangeLow = (i: number) => yScale(dataset[i].minimum); + yRangeHigh = (i: number) => yScale(dataset[i].maximum); + break; + case 'whiskers': + yRangeLow = (i: number) => yScale(dataset[i].whiskerLow); + yRangeHigh = (i: number) => yScale(dataset[i].whiskerHigh); + break; + case 'box': + yRangeLow = (i: number) => yScale(dataset[i].boxLow); + yRangeHigh = (i: number) => yScale(dataset[i].boxHigh); + break; + case 'none': + yRangeLow = undefined; + yRangeHigh = undefined; + break; + } + const segments = getContiguousSegments(start, stop, i => i in dataset); - for (const segment of segments) { - ctx.globalAlpha = 0.25 * alpha; - ctx.fillStyle = fillColor; - // drawSilhouette(ctx, segment, xScale, yMin, yMax, [xColumnLeft, xColumnRight], 'fill'); - drawSilhouette(ctx, segment, xScale, yWhiskerLow, yWhiskerHigh, [xColumnLeft, xColumnRight], 'fill'); - // drawSilhouette(ctx, segment, xScale, yBoxLow, yBoxHigh, [xColumnLeft, xColumnRight], 'fill'); + // Shaded range + if (yRangeLow && yRangeHigh) { + for (const segment of segments) { + ctx.globalAlpha = 0.25 * alpha; + ctx.fillStyle = fillColor; + drawSilhouette(ctx, segment, xScale, yRangeLow, yRangeHigh, [xColumnLeft, xColumnRight], 'fill'); + } + } + + // Median + for (const segment of segments) { ctx.globalAlpha = 0.5 * alpha; ctx.fillStyle = strokeColor; ctx.strokeStyle = strokeColor; @@ -712,3 +757,6 @@ function drawSilhouette(ctx: CanvasRenderingContext2D, [sStart, sStop]: [number, if (style.includes('fill')) ctx.fill(); if (style.includes('stroke')) ctx.stroke(); } + +// TODO: implement data pooling/smoothing for too zoomed-out visualization (like heatmap) +// TODO: axis ticks diff --git a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts index 0b3ead68f..3593946f3 100644 --- a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts +++ b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts @@ -1,7 +1,7 @@ import { type ArgTypes, Meta, Story } from "@storybook/web-components"; import { html } from "lit-html"; import "../../packages/nightingale-distribution-track/src/index"; -import { type DistributionData } from "../../packages/nightingale-distribution-track/src/nightingale-distribution-track"; +import { type DistributionData, ZoomedOutRangeOptions } from "../../packages/nightingale-distribution-track/src/nightingale-distribution-track"; import sampleDistributionData from "../../packages/nightingale-distribution-track/tests/mockData/sample-1.json"; @@ -17,6 +17,7 @@ const DefaultArgs = { "y-min": 0 as number | undefined, "y-max": undefined as number | undefined, "hide-outliers": false, + "zoomed-out-range": 'whiskers', }; type Args = typeof DefaultArgs; @@ -24,10 +25,13 @@ const ArgumentTypes: Partial> = { "highlight-event": { control: "select", options: ["onmouseover", "onclick"] }, "y-min": { control: "select", options: [undefined, 0, 100, 200, 300, 400, 500] }, "y-max": { control: "select", options: [undefined, 0, 100, 200, 300, 400, 500] }, + "zoomed-out-range": { control: "select", options: ZoomedOutRangeOptions }, }; const nDataRepeat = 100; +// Around 100k datapoints (nDataRepeat=1000), canvas draw takes > 40ms +// Around 400k datapoints (nDataRepeat=4000), aliasing makes data invisible (causes artifacts even before) const sampleSequence = "MALYGTHSHGLFKKLGIPGPTPLPFLGNILSYHKGFCMFDMECHKKYGKVWGFYDGQQPVLAITDPDMIKTVLVKECYSVFTNRRPFGPVGFMKSAISIA".repeat(nDataRepeat); @@ -68,18 +72,19 @@ function remove(arr: T[], ...indices: number[]) { } function prepareLinegraphData(data: DistributionData) { + console.time('prepareLinegraphData') const values = data[0].positions.map(pos => ({ position: pos.position, value: pos.values.reduce((a, b) => a + b, 0) / pos.values.length })); - const bulgarianConstant = 10 / Math.max(...values.map(v => v.value)); - values.forEach(v => v.value *= bulgarianConstant); // I don't know how to set Y-range to linegraph track, this will do + const max = values.reduce((old, v) => v.value > old ? v.value : old, 0); const chart1 = { name: "chart1", color: "#707070", fill: "#808080", lineCurve: "curveStep", - range: [0, 10], + range: [0, max], values: values, }; + console.timeEnd('prepareLinegraphData') return [chart1]; } @@ -155,11 +160,12 @@ function nightingaleDistributionTrack(args: Args & { length: number, id: number highlight-color="${args["highlight-color"]}" margin-color=${args["margin-color"]} margin-top=10 - margin-bottom=20 + margin-bottom=10 use-ctrl-to-zoom y-min=${args["y-min"]} y-max=${args["y-max"]} ?hide-outliers=${args["hide-outliers"]} + zoomed-out-range=${args["zoomed-out-range"]} > `; @@ -191,13 +197,13 @@ function makeStory(options: { length: number }): Story { story.args = { ...DefaultArgs }; story.argTypes = ArgumentTypes; const distributionData = prepareDistributionData(sampleDistributionData as any); - // const linegraphData = prepareLinegraphData(distributionData); + const linegraphData = prepareLinegraphData(distributionData); story.play = async () => { - // await customElements.whenDefined("nightingale-linegraph-track"); - // for (const track of document.getElementsByTagName("nightingale-linegraph-track")) { - // (track as any).data = linegraphData; - // } + await customElements.whenDefined("nightingale-linegraph-track"); + for (const track of document.getElementsByTagName("nightingale-linegraph-track")) { + (track as any).data = linegraphData; + } await customElements.whenDefined("nightingale-distribution-track"); for (const track of document.getElementsByTagName("nightingale-distribution-track")) { (track as any).data = distributionData; From 37dcec8ec05541ea51827b85fd6520cbabb056d7 Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Tue, 16 Jun 2026 17:12:46 +0100 Subject: [PATCH 10/32] nightingale-distribution-track: zoomed-out visualization downsampling --- .../src/downsampling.ts | 175 ++++++++++++++++++ .../src/nightingale-distribution-track.ts | 145 ++++++++++++++- .../NightingaleDistributionTrack.stories.ts | 17 +- 3 files changed, 326 insertions(+), 11 deletions(-) create mode 100644 packages/nightingale-distribution-track/src/downsampling.ts diff --git a/packages/nightingale-distribution-track/src/downsampling.ts b/packages/nightingale-distribution-track/src/downsampling.ts new file mode 100644 index 000000000..3b2240b2e --- /dev/null +++ b/packages/nightingale-distribution-track/src/downsampling.ts @@ -0,0 +1,175 @@ +type PoolingFunction = (...values: number[]) => number; + + +/** Helper object for downsampling 1D number arrays, with caching */ +export type Downsampler = { + /** Column count of the original data */ + nColumns: number, + /** Downsampled version of the original data (index {nColumn}x{nRows} holds the original data) */ + downsampled: { [resolution: number]: Float32Array }, + /** Function used to compute downsampled value from multiple source values */ + poolingFunction: PoolingFunction, +} + +export const Downsampler = { + /** Create a new downsampler for a 2D number array */ + fromNumbers(data: Float32Array, poolingFunction: PoolingFunction): Downsampler { + const result: Downsampler = { nColumns: data.length, downsampled: {}, poolingFunction }; + set(result, data.length, data); + return result; + }, + + /** Return the original (full-size) data */ + getOriginal(downsampler: Downsampler): Float32Array { + return get(downsampler, downsampler.nColumns)!; + }, + + /** Get data downsampled approximately to `minResolution`. + * The returned resolution will be at least `minResolution` but less then double that, in each dimension. + * The returned data will be equal to the original data if `minResolution` is big enough. */ + getDownsampled(downsampler: Downsampler, minResolution: number): Float32Array { + const targetResolution = downsamplingTarget(downsampler.nColumns, minResolution); + // console.log('minResolution', minResolution, 'downsamplingTarget', targetResolution) + return getOrCompute(downsampler, targetResolution); + }, +}; + + +/** Return `m`, a power of 2 or equal to `nDatapoints`, such that: + * `nPixels <= m < 2*nPixels` or `m === nDatapoints < nPixels` */ +function downsamplingTarget(nDatapoints: number, nPixels: number): number { + let result = 1; + while (result < nPixels && result < nDatapoints) { + result = Math.min(2 * result, nDatapoints); + } + return result; +} + +/** Get data downsampled to `resolution` (exactly) if already computed. Do not compute anything. */ +function get(downsampler: Downsampler, resolution: number): Float32Array | undefined { + return downsampler.downsampled[resolution]; +} + +/** Save data downsampled to `resolution`. */ +function set(downsampler: Downsampler, resolution: number, value: Float32Array): void { + downsampler.downsampled[resolution] = value; +} + +/** Get data downsampled to `resolution` (exactly), with caching. */ +function getOrCompute(downsampler: Downsampler, resolution: number): Float32Array { + const cached = get(downsampler, resolution); + if (cached) { + return cached; + } else { + const srcResolution = downsamplingSource(resolution, downsampler.nColumns); + if (!srcResolution || srcResolution > downsampler.nColumns) throw new Error('AssertionError'); + // console.log('getOrCompute', srcResolution, '->', resolution) + const srcData = getOrCompute(downsampler, srcResolution); + console.time(`downsampleNumbers ${srcData.length}->${resolution}`) + const result = downsampleNumbers(srcData, resolution, downsampler.poolingFunction); + console.timeEnd(`downsampleNumbers ${srcData.length}->${resolution}`) + set(downsampler, resolution, result); + return result; + } +} + +/** Return resolution from which `wanted` resolution should be obtained by downsampling. + * This will have either X length or Y length doubled relative to `wanted` (or same as in `original` if doubled would be more that original) + * and the other length kept the same. + * Return `undefined` if `wanted` is already equal to `original`. */ +function downsamplingSource(wanted: number, original: number): number | undefined { + if (wanted > original) { + throw new Error('ArgumentError: Cannot downsample to higher resolution than original'); + } + if (wanted === original) { + // We already have it + return undefined; + } + return Math.min(2 * wanted, original); +} + + +/** Downsample 2D array of numbers to a new size. */ +function downsampleNumbers(input: Float32Array, newSize: number, poolingFunction: PoolingFunction): Float32Array { + // console.log('downsampleNumbers', input.length, '->', newSize) + + if (input.length === 2 * newSize) { + return downsampleNumbers_halveX(input, poolingFunction); + } + return downsampleNumbers_general(input, newSize, poolingFunction); +} + +/** Downsample 2D array of numbers to a new size - implementation for general sizes. */ +function downsampleNumbers_general(input: Float32Array, newSize: number, poolingFunction: PoolingFunction): Float32Array { + const w0 = input.length; + const w1 = newSize; + const { from, to } = resamplingCoefficients(w0, w1); + const out = input.slice(0, w1).fill(NaN) as Float32Array; + const n = from.length; + for (let j = 0; j < n; j++) { // column index + const oldValue = out[to[j]]; + const inputValue = input[from[j]]; + if (isNaN(oldValue)) { + out[to[j]] = inputValue; + } else { + out[to[j]] = poolingFunction(oldValue, inputValue); + } + } + return out; +} + +/** Downsample 2D array of numbers to a new size - simplified implementation for special cases when newX===oldX/2, newY===oldY. */ +function downsampleNumbers_halveX(input: Float32Array, poolingFunction: PoolingFunction): Float32Array { + const w0 = input.length; + const w1 = Math.floor(w0 / 2); + const out = input.slice(0, w1).fill(NaN) as Float32Array; + for (let j = 0; j < w1; j++) { // column index + const old1 = input[2 * j]; + const old2 = input[2 * j + 1]; + out[j] = poolingFunction(old1, old2); + } + return out; +} + +/** Calculate the weights of how much each pixel in the old image contributes to pixels in the new image, for 1D images + * (pixel `from[i]` contributes to pixel `to[i]` with weight `weight[i]`). + * Typically one old pixel will contribute to more new pixels and vice versa. + * Sum of weights contributed to each new pixel must be equal to 1. + * To use for 2D images, calculate row-wise and column-wise weights and multiply them. */ +function resamplingCoefficients(nOld: number, nNew: number): { from: number[], to: number[], weight: number[] } { + const scale = nNew / nOld; + let i = 0; // Current pixel in the old image + let j = 0; // Current pixel in the new image + let p = 0; // Current continuous position in the new image + const from = []; + const to = []; + const weight = []; + while (p < nNew) { + const nextINotch = scale * (i + 1); + const nextJNotch = j + 1; + if (nextINotch <= nextJNotch) { + from.push(i); + to.push(j); + weight.push(nextINotch - p); + p = nextINotch; + i += 1; + if (nextINotch === nextJNotch) { + j += 1; + } + } else { + from.push(i); + to.push(j); + weight.push(nextJNotch - p); + p = nextJNotch; + j += 1; + } + } + return { + /** Index of a pixel in the old image */ + from, + /** Index of a pixel in the new image */ + to, + /** How much the `from` pixel's value contributes to the `to` pixel */ + weight, + }; +} diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts index 8997117a6..3fc97d601 100644 --- a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts +++ b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts @@ -13,9 +13,10 @@ import NightingaleElement, { withResizable, withZoom, } from "@nightingale-elements/nightingale-new-core"; -import { BaseType, color, randomLcg, randomUniform, scaleLinear, select, Selection, TypedArray } from "d3"; +import { BaseType, color, max, min, randomLcg, randomUniform, scaleLinear, select, Selection, TypedArray } from "d3"; import { html, PropertyDeclaration, PropertyValues } from "lit"; import { property } from "lit/decorators.js"; +import { Downsampler } from "./downsampling"; const ATTRIBUTES_THAT_TRIGGER_REFRESH: string[] = [ @@ -30,6 +31,7 @@ const ATTRIBUTES_THAT_TRIGGER_DATA_RESET: string[] = [] satisfies (keyof Nightin /** Line width for rectangle stroke */ const LINE_WIDTH = 1; /** Maximum line width relative to column width (overrides `LINE_WIDTH` when zoomed out too much) */ +// const MAX_REL_LINE_WIDTH = 0.2; const MAX_REL_LINE_WIDTH = 0.2; /** Default fill color for boxes (stroke color will be derived from this) */ @@ -46,6 +48,10 @@ const JITTER_REL_WIDTH = 0.4; const OUTLIER_RADIUS = 2; /** Column widths in CSS pixels, between which transition from "background" to "foreground" visualization happens */ const FG_BG_TRANSITION_BASE_WIDTHS = [4, 5]; +/** Approximate width of a column in screen pixels, when showing downsampled data in "background" visualization. + * (higher value means more responsive but lower-resolution visualization). */ +// const BG_DOWNSAMPLING_PIXELS_PER_COLUMN = 2; +const BG_DOWNSAMPLING_PIXELS_PER_COLUMN = 1; function makeStrokeColor(dataColor: string): string | undefined { return color(dataColor)?.darker(2).formatHex(); @@ -354,7 +360,7 @@ export default class NightingaleDistributionTrack extends withCanvas( } /** Draw simplified visualization ("background" / zoomed-out) */ - private drawSimplifiedVisualization(ctx: CanvasRenderingContext2D, alpha: number) { + private drawSimplifiedVisualization_orig(ctx: CanvasRenderingContext2D, alpha: number) { if (!this.data || !this.preprocessedData) return; const { xColumnLeft, xColumnRight, xScale, yScale, yMedianExtra, lineWidth, start, stop } = this.getDrawingMeasurements(); @@ -369,8 +375,8 @@ export default class NightingaleDistributionTrack extends withCanvas( const fillColor = dataColor; const strokeColor = makeStrokeColor(dataColor)!; - const yMedianLow = (i: number) => yScale(dataset[i].median + yMedianExtra); - const yMedianHigh = (i: number) => yScale(dataset[i].median - yMedianExtra); + const yMedianLow = (i: number) => yScale(dataset[i].median) + yMedianExtra; + const yMedianHigh = (i: number) => yScale(dataset[i].median) - yMedianExtra; let yRangeLow: ((i: number) => number) | undefined; let yRangeHigh: ((i: number) => number) | undefined; @@ -414,6 +420,91 @@ export default class NightingaleDistributionTrack extends withCanvas( } } + // TODO: continue here + // TODO: try to use downsampling + + /** Draw simplified visualization ("background" / zoomed-out) */ + private drawSimplifiedVisualization(ctx: CanvasRenderingContext2D, alpha: number) { + if (!this.data || !this.preprocessedData) return; + + const { xColumnLeft, xColumnRight, xScale, yScale, yMedianExtra, lineWidth, start, stop } = this.getDrawingMeasurements(); + ctx.lineWidth = lineWidth; + + const nDatasets = this.preprocessedData?.datasets.length ?? 1; + for (let iDataset = 0; iDataset < nDatasets; iDataset++) { + const dataset = this.preprocessedData.datasets[iDataset]; + if (!dataset) continue; + + const { offset, length, downsamplers } = getDownsamplerForDataset(dataset); // TODO: refactor this to compute only once + + const dataColor = this.data[iDataset].color ?? DEFAULT_DATA_COLOR; + const fillColor = dataColor; + const strokeColor = makeStrokeColor(dataColor)!; + + const resolution = (xScale(length) - xScale(0)) / BG_DOWNSAMPLING_PIXELS_PER_COLUMN; + + const medianLow = Downsampler.getDownsampled(downsamplers.medianLow, resolution); + const medianHigh = Downsampler.getDownsampled(downsamplers.medianHigh, resolution); + const downScale = length / medianLow.length; + + // console.log('resolution', resolution, 'downScale', downScale, `(${length} -> ${medLow.length})`) + + const yMedianLow = (j: number) => yScale(medianLow[j]) + yMedianExtra; + const yMedianHigh = (j: number) => yScale(medianHigh[j]) - yMedianExtra; + + let yRangeLow: ((j: number) => number) | undefined; + let yRangeHigh: ((j: number) => number) | undefined; + switch (this['zoomed-out-range']) { + case 'extremes': + const minimum = Downsampler.getDownsampled(downsamplers.minimum, resolution); + const maximum = Downsampler.getDownsampled(downsamplers.maximum, resolution); + yRangeLow = (j: number) => yScale(minimum[j]); + yRangeHigh = (j: number) => yScale(maximum[j]); + break; + case 'whiskers': + const whiskerLow = Downsampler.getDownsampled(downsamplers.whiskerLow, resolution); + const whiskerHigh = Downsampler.getDownsampled(downsamplers.whiskerHigh, resolution); + yRangeLow = (j: number) => yScale(whiskerLow[j]); + yRangeHigh = (j: number) => yScale(whiskerHigh[j]); + break; + case 'box': + const boxLow = Downsampler.getDownsampled(downsamplers.boxLow, resolution); + const boxHigh = Downsampler.getDownsampled(downsamplers.boxHigh, resolution); + yRangeLow = (j: number) => yScale(boxLow[j]); + yRangeHigh = (j: number) => yScale(boxHigh[j]); + break; + case 'none': + yRangeLow = undefined; + yRangeHigh = undefined; + break; + } + + // const segments = getContiguousSegments(start, stop, i => i in dataset); + const jStart = Math.max(0, Math.floor((start - offset) / downScale)); + const jStop = Math.min(medianLow.length, Math.ceil((stop - offset) / downScale)); + const jSegments = getContiguousSegments(jStart, jStop, j => !isNaN(medianLow[j])); + + const jXScale = (j: number) => xScale(offset + j * downScale); + + // Shaded range + if (yRangeLow && yRangeHigh) { + for (const segment of jSegments) { + ctx.globalAlpha = 0.25 * alpha; + ctx.fillStyle = fillColor; + drawSilhouette(ctx, segment, jXScale, yRangeLow, yRangeHigh, [xColumnLeft, xColumnRight], 'fill'); + } + } + + // Median + for (const segment of jSegments) { + ctx.globalAlpha = 0.5 * alpha; + ctx.fillStyle = strokeColor; + ctx.strokeStyle = strokeColor; + drawSilhouette(ctx, segment, jXScale, yMedianLow, yMedianHigh, [xColumnLeft, xColumnRight], 'fill+stroke'); + } + } + } + private drawMargins(ctx: CanvasRenderingContext2D) { const canvasWidth = ctx.canvas.width; const canvasHeight = ctx.canvas.height; @@ -758,5 +849,51 @@ function drawSilhouette(ctx: CanvasRenderingContext2D, [sStart, sStop]: [number, if (style.includes('stroke')) ctx.stroke(); } +function datasetToArrays(dataset: PreprocessedData['datasets'][number]) { + const positions = Object.values(dataset).map(d => d.position); + const offset = min(positions) ?? 1; + const stop = (max(positions) ?? 0) + 1; + const length = stop - offset; + const median = new Float32Array(length).fill(NaN); + const boxLow = new Float32Array(length).fill(NaN); + const boxHigh = new Float32Array(length).fill(NaN); + const whiskerLow = new Float32Array(length).fill(NaN); + const whiskerHigh = new Float32Array(length).fill(NaN); + const minimum = new Float32Array(length).fill(NaN); + const maximum = new Float32Array(length).fill(NaN); + for (const pos of Object.values(dataset)) { + median[pos.position - offset] = pos.median; + boxLow[pos.position - offset] = pos.boxLow; + boxHigh[pos.position - offset] = pos.boxHigh; + whiskerLow[pos.position - offset] = pos.whiskerLow; + whiskerHigh[pos.position - offset] = pos.whiskerHigh; + minimum[pos.position - offset] = pos.minimum; + maximum[pos.position - offset] = pos.maximum; + } + return { + offset, + length, + arrays: { median, boxLow, boxHigh, whiskerLow, whiskerHigh, minimum, maximum }, + }; +} + +function getDownsamplerForDataset(dataset: PreprocessedData['datasets'][number]) { + const { offset, length, arrays } = datasetToArrays(dataset); + return { + offset, + length, + downsamplers: { + medianLow: Downsampler.fromNumbers(arrays.median, Math.min), + medianHigh: Downsampler.fromNumbers(arrays.median, Math.max), + boxLow: Downsampler.fromNumbers(arrays.boxLow, Math.min), + boxHigh: Downsampler.fromNumbers(arrays.boxHigh, Math.max), + whiskerLow: Downsampler.fromNumbers(arrays.whiskerLow, Math.min), + whiskerHigh: Downsampler.fromNumbers(arrays.whiskerHigh, Math.max), + minimum: Downsampler.fromNumbers(arrays.minimum, Math.min), + maximum: Downsampler.fromNumbers(arrays.maximum, Math.max), + }, + }; +} + // TODO: implement data pooling/smoothing for too zoomed-out visualization (like heatmap) // TODO: axis ticks diff --git a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts index 3593946f3..83fa8ca39 100644 --- a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts +++ b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts @@ -29,7 +29,10 @@ const ArgumentTypes: Partial> = { }; -const nDataRepeat = 100; +// const nDataRepeat = 20_000; +const nDataRepeat = 1_000; +// const nDataRepeat = 81; +// const nDataRepeat = 82; // Around 100k datapoints (nDataRepeat=1000), canvas draw takes > 40ms // Around 400k datapoints (nDataRepeat=4000), aliasing makes data invisible (causes artifacts even before) @@ -186,7 +189,7 @@ function makeStory(options: { length: number }): Story {
${nightingaleNavigation({ ...args, length: options.length })} ${nightingaleSequence({ ...args, length: options.length })} - ${nightingaleLinegraphTrack({ ...args, length: options.length, id: 0 })} + ${nightingaleDistributionTrack({ ...args, length: options.length, id: 0 })}
@@ -197,13 +200,13 @@ function makeStory(options: { length: number }): Story { story.args = { ...DefaultArgs }; story.argTypes = ArgumentTypes; const distributionData = prepareDistributionData(sampleDistributionData as any); - const linegraphData = prepareLinegraphData(distributionData); + // const linegraphData = prepareLinegraphData(distributionData); story.play = async () => { - await customElements.whenDefined("nightingale-linegraph-track"); - for (const track of document.getElementsByTagName("nightingale-linegraph-track")) { - (track as any).data = linegraphData; - } + // await customElements.whenDefined("nightingale-linegraph-track"); + // for (const track of document.getElementsByTagName("nightingale-linegraph-track")) { + // (track as any).data = linegraphData; + // } await customElements.whenDefined("nightingale-distribution-track"); for (const track of document.getElementsByTagName("nightingale-distribution-track")) { (track as any).data = distributionData; From 1148d7bcf127bfec43cb39b1fd65355dc21d6c6b Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Tue, 16 Jun 2026 17:47:26 +0100 Subject: [PATCH 11/32] nightingale-distribution-track: downsampling - only compute once --- .../src/nightingale-distribution-track.ts | 70 +++++++++++-------- 1 file changed, 39 insertions(+), 31 deletions(-) diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts index 3fc97d601..342fc79a8 100644 --- a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts +++ b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts @@ -280,17 +280,17 @@ export default class NightingaleDistributionTrack extends withCanvas( /** Draw full boxplot visualization ("foreground" / zoomed-in) */ private drawBoxplotVisualization(ctx: CanvasRenderingContext2D) { - if (!this.data || !this.preprocessedData) return; + if (!this.preprocessedData) return; const { xColumnLeft, xColumnWidth, xScale, yScale, yMedianExtra, lineWidth, outlierRadius, start, stop } = this.getDrawingMeasurements(); ctx.lineWidth = lineWidth; - const nDatasets = this.preprocessedData?.datasets.length ?? 1; + const nDatasets = this.preprocessedData.datasets.length; for (let iDataset = 0; iDataset < nDatasets; iDataset++) { const dataset = this.preprocessedData.datasets[iDataset]; if (!dataset) continue; - const dataColor = this.data[iDataset].color ?? DEFAULT_DATA_COLOR; + const dataColor = dataset.color ?? DEFAULT_DATA_COLOR; const fillColor = dataColor; const strokeColor = makeStrokeColor(dataColor)!; @@ -302,7 +302,7 @@ export default class NightingaleDistributionTrack extends withCanvas( const xJitterHalfwidth = 0.5 * JITTER_REL_WIDTH * xBoxWidth; for (let i = start; i < stop; i++) { - const datum = dataset[i]; + const datum = dataset.positions[i]; if (!datum) continue; const x = xScale(i); @@ -366,32 +366,32 @@ export default class NightingaleDistributionTrack extends withCanvas( const { xColumnLeft, xColumnRight, xScale, yScale, yMedianExtra, lineWidth, start, stop } = this.getDrawingMeasurements(); ctx.lineWidth = lineWidth; - const nDatasets = this.preprocessedData?.datasets.length ?? 1; + const nDatasets = this.preprocessedData.datasets.length; for (let iDataset = 0; iDataset < nDatasets; iDataset++) { const dataset = this.preprocessedData.datasets[iDataset]; if (!dataset) continue; - const dataColor = this.data[iDataset].color ?? DEFAULT_DATA_COLOR; + const dataColor = dataset.color ?? DEFAULT_DATA_COLOR; const fillColor = dataColor; const strokeColor = makeStrokeColor(dataColor)!; - const yMedianLow = (i: number) => yScale(dataset[i].median) + yMedianExtra; - const yMedianHigh = (i: number) => yScale(dataset[i].median) - yMedianExtra; + const yMedianLow = (i: number) => yScale(dataset.positions[i].median) + yMedianExtra; + const yMedianHigh = (i: number) => yScale(dataset.positions[i].median) - yMedianExtra; let yRangeLow: ((i: number) => number) | undefined; let yRangeHigh: ((i: number) => number) | undefined; switch (this['zoomed-out-range']) { case 'extremes': - yRangeLow = (i: number) => yScale(dataset[i].minimum); - yRangeHigh = (i: number) => yScale(dataset[i].maximum); + yRangeLow = (i: number) => yScale(dataset.positions[i].minimum); + yRangeHigh = (i: number) => yScale(dataset.positions[i].maximum); break; case 'whiskers': - yRangeLow = (i: number) => yScale(dataset[i].whiskerLow); - yRangeHigh = (i: number) => yScale(dataset[i].whiskerHigh); + yRangeLow = (i: number) => yScale(dataset.positions[i].whiskerLow); + yRangeHigh = (i: number) => yScale(dataset.positions[i].whiskerHigh); break; case 'box': - yRangeLow = (i: number) => yScale(dataset[i].boxLow); - yRangeHigh = (i: number) => yScale(dataset[i].boxHigh); + yRangeLow = (i: number) => yScale(dataset.positions[i].boxLow); + yRangeHigh = (i: number) => yScale(dataset.positions[i].boxHigh); break; case 'none': yRangeLow = undefined; @@ -399,7 +399,7 @@ export default class NightingaleDistributionTrack extends withCanvas( break; } - const segments = getContiguousSegments(start, stop, i => i in dataset); + const segments = getContiguousSegments(start, stop, i => i in dataset.positions); // Shaded range if (yRangeLow && yRangeHigh) { @@ -421,7 +421,8 @@ export default class NightingaleDistributionTrack extends withCanvas( } // TODO: continue here - // TODO: try to use downsampling + // TODO: change downsampling to always halve (better performance and more consistent first transition) + // TODO: fade-out transition when downsampling? /** Draw simplified visualization ("background" / zoomed-out) */ private drawSimplifiedVisualization(ctx: CanvasRenderingContext2D, alpha: number) { @@ -435,9 +436,9 @@ export default class NightingaleDistributionTrack extends withCanvas( const dataset = this.preprocessedData.datasets[iDataset]; if (!dataset) continue; - const { offset, length, downsamplers } = getDownsamplerForDataset(dataset); // TODO: refactor this to compute only once + const { offset, length, downsamplers } = dataset.downsampling; - const dataColor = this.data[iDataset].color ?? DEFAULT_DATA_COLOR; + const dataColor = dataset.color ?? DEFAULT_DATA_COLOR; const fillColor = dataColor; const strokeColor = makeStrokeColor(dataColor)!; @@ -702,13 +703,14 @@ export default class NightingaleDistributionTrack extends withCanvas( const continuousPosition = this.getSeqPositionFromX(svgX); if (continuousPosition === undefined) return undefined; const position = Math.floor(continuousPosition); - const datum = this.preprocessedData?.datasets[0][position]; // TODO: consider multiple datasets + const datum = this.preprocessedData?.datasets[0].positions[position]; // TODO: consider multiple datasets return { position, datum }; } } type PreprocessedData = ReturnType; +type PreprocessedDataset = ReturnType; function preprocessData(data: DistributionData) { const preprocessedDatasets = data.map(preprocessDataset); @@ -719,12 +721,17 @@ function preprocessData(data: DistributionData) { } function preprocessDataset(dataset: DistributionDataset) { - const out: { [position: number]: PreprocessedDatum } = {}; + const preprocessedPositions: PreprocessedPositions = {}; for (const datum of dataset.positions) { - out[datum.position] = preprocessDatum(datum); + preprocessedPositions[datum.position] = preprocessDatum(datum); } - return out; + // return out; + return { + ...dataset, + positions: preprocessedPositions, + downsampling: getDownsamplerForDataset(preprocessedPositions), + }; } interface PreprocessedDatum { @@ -741,6 +748,8 @@ interface PreprocessedDatum { maximum: number, } +type PreprocessedPositions = { [position: number]: PreprocessedDatum } + function preprocessDatum(datum: Distribution): PreprocessedDatum { const sorted = sortIfNeeded(new Float32Array(datum.values)); const median = getQuantile(sorted, 0.5); @@ -799,13 +808,13 @@ export function getQuantile(sortedValues: ArrayLike, p: number) { } /** Gets the Y-axis limits for the given preprocessed data */ -function getExtremes(data: { [position: number]: PreprocessedDatum }[]) { +function getExtremes(data: PreprocessedDataset[]) { let min = Infinity; let max = -Infinity; for (const dataset of data) { - for (const position in dataset) { - const datum = dataset[position]; + for (const position in dataset.positions) { + const datum = dataset.positions[position]; if (datum.minimum < min) min = datum.minimum; if (datum.maximum > max) max = datum.maximum; } @@ -849,8 +858,8 @@ function drawSilhouette(ctx: CanvasRenderingContext2D, [sStart, sStop]: [number, if (style.includes('stroke')) ctx.stroke(); } -function datasetToArrays(dataset: PreprocessedData['datasets'][number]) { - const positions = Object.values(dataset).map(d => d.position); +function datasetToArrays(data: PreprocessedPositions) { + const positions = Object.values(data).map(d => d.position); const offset = min(positions) ?? 1; const stop = (max(positions) ?? 0) + 1; const length = stop - offset; @@ -861,7 +870,7 @@ function datasetToArrays(dataset: PreprocessedData['datasets'][number]) { const whiskerHigh = new Float32Array(length).fill(NaN); const minimum = new Float32Array(length).fill(NaN); const maximum = new Float32Array(length).fill(NaN); - for (const pos of Object.values(dataset)) { + for (const pos of Object.values(data)) { median[pos.position - offset] = pos.median; boxLow[pos.position - offset] = pos.boxLow; boxHigh[pos.position - offset] = pos.boxHigh; @@ -877,8 +886,8 @@ function datasetToArrays(dataset: PreprocessedData['datasets'][number]) { }; } -function getDownsamplerForDataset(dataset: PreprocessedData['datasets'][number]) { - const { offset, length, arrays } = datasetToArrays(dataset); +function getDownsamplerForDataset(data: PreprocessedPositions) { + const { offset, length, arrays } = datasetToArrays(data); return { offset, length, @@ -895,5 +904,4 @@ function getDownsamplerForDataset(dataset: PreprocessedData['datasets'][number]) }; } -// TODO: implement data pooling/smoothing for too zoomed-out visualization (like heatmap) // TODO: axis ticks From dc9948aef90a11578a3be1f20dfcbc55601e2f1a Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Wed, 17 Jun 2026 14:38:43 +0100 Subject: [PATCH 12/32] nightingale-distribution-track: simplify downsampling (always halve) --- .../src/downsampling.ts | 178 +++++------------- .../src/nightingale-distribution-track.ts | 66 ------- 2 files changed, 42 insertions(+), 202 deletions(-) diff --git a/packages/nightingale-distribution-track/src/downsampling.ts b/packages/nightingale-distribution-track/src/downsampling.ts index 3b2240b2e..e3bffe5e6 100644 --- a/packages/nightingale-distribution-track/src/downsampling.ts +++ b/packages/nightingale-distribution-track/src/downsampling.ts @@ -4,9 +4,9 @@ type PoolingFunction = (...values: number[]) => number; /** Helper object for downsampling 1D number arrays, with caching */ export type Downsampler = { /** Column count of the original data */ - nColumns: number, - /** Downsampled version of the original data (index {nColumn}x{nRows} holds the original data) */ - downsampled: { [resolution: number]: Float32Array }, + originalLength: number, + /** Downsampled versions of the original data (index `1` holds the original data) */ + downsampled: { [scale: number]: Float32Array | undefined }, /** Function used to compute downsampled value from multiple source values */ poolingFunction: PoolingFunction, } @@ -14,162 +14,68 @@ export type Downsampler = { export const Downsampler = { /** Create a new downsampler for a 2D number array */ fromNumbers(data: Float32Array, poolingFunction: PoolingFunction): Downsampler { - const result: Downsampler = { nColumns: data.length, downsampled: {}, poolingFunction }; - set(result, data.length, data); - return result; + return { + originalLength: data.length, + poolingFunction, + downsampled: { 1: data }, + }; }, /** Return the original (full-size) data */ getOriginal(downsampler: Downsampler): Float32Array { - return get(downsampler, downsampler.nColumns)!; + return downsampler.downsampled[1]!; }, - /** Get data downsampled approximately to `minResolution`. - * The returned resolution will be at least `minResolution` but less then double that, in each dimension. - * The returned data will be equal to the original data if `minResolution` is big enough. */ - getDownsampled(downsampler: Downsampler, minResolution: number): Float32Array { - const targetResolution = downsamplingTarget(downsampler.nColumns, minResolution); - // console.log('minResolution', minResolution, 'downsamplingTarget', targetResolution) - return getOrCompute(downsampler, targetResolution); + /** Get data downsampled approximately to `minLength`. + * The returned data length will be at least `minLength` but less then double that. + * Exception: The returned data will be equal to the original data if `minLength > originalData.length`. */ + getDownsampled(downsampler: Downsampler, minLength: number): Float32Array { + const targetScale = downsamplingTargetScale(downsampler.originalLength, minLength); + return getOrCompute(downsampler, targetScale); }, }; - -/** Return `m`, a power of 2 or equal to `nDatapoints`, such that: - * `nPixels <= m < 2*nPixels` or `m === nDatapoints < nPixels` */ -function downsamplingTarget(nDatapoints: number, nPixels: number): number { - let result = 1; - while (result < nPixels && result < nDatapoints) { - result = Math.min(2 * result, nDatapoints); - } - return result; -} - -/** Get data downsampled to `resolution` (exactly) if already computed. Do not compute anything. */ -function get(downsampler: Downsampler, resolution: number): Float32Array | undefined { - return downsampler.downsampled[resolution]; -} - -/** Save data downsampled to `resolution`. */ -function set(downsampler: Downsampler, resolution: number, value: Float32Array): void { - downsampler.downsampled[resolution] = value; +/** Return `scale`, a power of 2, such that: + * `nPixels <= nDatapoints/scale < 2*nPixels` or `scale === 1 && nDatapoints < 2*nPixels` */ +function downsamplingTargetScale(nDatapoints: number, nPixels: number): number { + nDatapoints = Math.max(1, nDatapoints); + nPixels = Math.max(1, nPixels); + const log2scaleExact = Math.log2(nDatapoints / nPixels); + const log2scale = Math.max(0, Math.floor(log2scaleExact)); + return 2 ** log2scale; } -/** Get data downsampled to `resolution` (exactly), with caching. */ -function getOrCompute(downsampler: Downsampler, resolution: number): Float32Array { - const cached = get(downsampler, resolution); +/** Get data downsampled by `scale`, with caching. `scale` must be a power of 2. Resulting data length will be `Math.ceil(original.length / scale)` */ +function getOrCompute(downsampler: Downsampler, scale: number): Float32Array { + const cached = downsampler.downsampled[scale]; if (cached) { return cached; } else { - const srcResolution = downsamplingSource(resolution, downsampler.nColumns); - if (!srcResolution || srcResolution > downsampler.nColumns) throw new Error('AssertionError'); - // console.log('getOrCompute', srcResolution, '->', resolution) - const srcData = getOrCompute(downsampler, srcResolution); - console.time(`downsampleNumbers ${srcData.length}->${resolution}`) - const result = downsampleNumbers(srcData, resolution, downsampler.poolingFunction); - console.timeEnd(`downsampleNumbers ${srcData.length}->${resolution}`) - set(downsampler, resolution, result); + if (scale <= 1) throw new Error('AssertionError: getOrCompute'); + const srcData = getOrCompute(downsampler, scale / 2); + const result = downsampleNumbers_halve(srcData, downsampler.poolingFunction); + downsampler.downsampled[scale] = result; return result; } } -/** Return resolution from which `wanted` resolution should be obtained by downsampling. - * This will have either X length or Y length doubled relative to `wanted` (or same as in `original` if doubled would be more that original) - * and the other length kept the same. - * Return `undefined` if `wanted` is already equal to `original`. */ -function downsamplingSource(wanted: number, original: number): number | undefined { - if (wanted > original) { - throw new Error('ArgumentError: Cannot downsample to higher resolution than original'); - } - if (wanted === original) { - // We already have it - return undefined; - } - return Math.min(2 * wanted, original); -} - - -/** Downsample 2D array of numbers to a new size. */ -function downsampleNumbers(input: Float32Array, newSize: number, poolingFunction: PoolingFunction): Float32Array { - // console.log('downsampleNumbers', input.length, '->', newSize) - - if (input.length === 2 * newSize) { - return downsampleNumbers_halveX(input, poolingFunction); - } - return downsampleNumbers_general(input, newSize, poolingFunction); -} - -/** Downsample 2D array of numbers to a new size - implementation for general sizes. */ -function downsampleNumbers_general(input: Float32Array, newSize: number, poolingFunction: PoolingFunction): Float32Array { - const w0 = input.length; - const w1 = newSize; - const { from, to } = resamplingCoefficients(w0, w1); - const out = input.slice(0, w1).fill(NaN) as Float32Array; - const n = from.length; - for (let j = 0; j < n; j++) { // column index - const oldValue = out[to[j]]; - const inputValue = input[from[j]]; - if (isNaN(oldValue)) { - out[to[j]] = inputValue; - } else { - out[to[j]] = poolingFunction(oldValue, inputValue); - } - } - return out; -} - -/** Downsample 2D array of numbers to a new size - simplified implementation for special cases when newX===oldX/2, newY===oldY. */ -function downsampleNumbers_halveX(input: Float32Array, poolingFunction: PoolingFunction): Float32Array { +/** Downsample array of numbers to a new size `ceil(input.length / 2)`. */ +function downsampleNumbers_halve(input: Float32Array, poolingFunction: PoolingFunction): Float32Array { const w0 = input.length; - const w1 = Math.floor(w0 / 2); - const out = input.slice(0, w1).fill(NaN) as Float32Array; - for (let j = 0; j < w1; j++) { // column index + const w1Paired = Math.floor(w0 / 2); + const w1 = Math.ceil(w0 / 2); + const out = new Float32Array(w1).fill(NaN); + for (let j = 0; j < w1Paired; j++) { // column index const old1 = input[2 * j]; const old2 = input[2 * j + 1]; out[j] = poolingFunction(old1, old2); } + if (w0 % 2) { + // Odd length of input array -> just copy last element + out[w1 - 1] = input[w0 - 1]; + } return out; } -/** Calculate the weights of how much each pixel in the old image contributes to pixels in the new image, for 1D images - * (pixel `from[i]` contributes to pixel `to[i]` with weight `weight[i]`). - * Typically one old pixel will contribute to more new pixels and vice versa. - * Sum of weights contributed to each new pixel must be equal to 1. - * To use for 2D images, calculate row-wise and column-wise weights and multiply them. */ -function resamplingCoefficients(nOld: number, nNew: number): { from: number[], to: number[], weight: number[] } { - const scale = nNew / nOld; - let i = 0; // Current pixel in the old image - let j = 0; // Current pixel in the new image - let p = 0; // Current continuous position in the new image - const from = []; - const to = []; - const weight = []; - while (p < nNew) { - const nextINotch = scale * (i + 1); - const nextJNotch = j + 1; - if (nextINotch <= nextJNotch) { - from.push(i); - to.push(j); - weight.push(nextINotch - p); - p = nextINotch; - i += 1; - if (nextINotch === nextJNotch) { - j += 1; - } - } else { - from.push(i); - to.push(j); - weight.push(nextJNotch - p); - p = nextJNotch; - j += 1; - } - } - return { - /** Index of a pixel in the old image */ - from, - /** Index of a pixel in the new image */ - to, - /** How much the `from` pixel's value contributes to the `to` pixel */ - weight, - }; -} +// TODO: solve pooling NaNs +// TODO: convert to class diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts index 342fc79a8..cbf066b55 100644 --- a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts +++ b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts @@ -359,69 +359,6 @@ export default class NightingaleDistributionTrack extends withCanvas( } } - /** Draw simplified visualization ("background" / zoomed-out) */ - private drawSimplifiedVisualization_orig(ctx: CanvasRenderingContext2D, alpha: number) { - if (!this.data || !this.preprocessedData) return; - - const { xColumnLeft, xColumnRight, xScale, yScale, yMedianExtra, lineWidth, start, stop } = this.getDrawingMeasurements(); - ctx.lineWidth = lineWidth; - - const nDatasets = this.preprocessedData.datasets.length; - for (let iDataset = 0; iDataset < nDatasets; iDataset++) { - const dataset = this.preprocessedData.datasets[iDataset]; - if (!dataset) continue; - - const dataColor = dataset.color ?? DEFAULT_DATA_COLOR; - const fillColor = dataColor; - const strokeColor = makeStrokeColor(dataColor)!; - - const yMedianLow = (i: number) => yScale(dataset.positions[i].median) + yMedianExtra; - const yMedianHigh = (i: number) => yScale(dataset.positions[i].median) - yMedianExtra; - - let yRangeLow: ((i: number) => number) | undefined; - let yRangeHigh: ((i: number) => number) | undefined; - switch (this['zoomed-out-range']) { - case 'extremes': - yRangeLow = (i: number) => yScale(dataset.positions[i].minimum); - yRangeHigh = (i: number) => yScale(dataset.positions[i].maximum); - break; - case 'whiskers': - yRangeLow = (i: number) => yScale(dataset.positions[i].whiskerLow); - yRangeHigh = (i: number) => yScale(dataset.positions[i].whiskerHigh); - break; - case 'box': - yRangeLow = (i: number) => yScale(dataset.positions[i].boxLow); - yRangeHigh = (i: number) => yScale(dataset.positions[i].boxHigh); - break; - case 'none': - yRangeLow = undefined; - yRangeHigh = undefined; - break; - } - - const segments = getContiguousSegments(start, stop, i => i in dataset.positions); - - // Shaded range - if (yRangeLow && yRangeHigh) { - for (const segment of segments) { - ctx.globalAlpha = 0.25 * alpha; - ctx.fillStyle = fillColor; - drawSilhouette(ctx, segment, xScale, yRangeLow, yRangeHigh, [xColumnLeft, xColumnRight], 'fill'); - } - } - - // Median - for (const segment of segments) { - ctx.globalAlpha = 0.5 * alpha; - ctx.fillStyle = strokeColor; - ctx.strokeStyle = strokeColor; - drawSilhouette(ctx, segment, xScale, yMedianLow, yMedianHigh, [xColumnLeft, xColumnRight], 'fill+stroke'); - } - } - } - - // TODO: continue here - // TODO: change downsampling to always halve (better performance and more consistent first transition) // TODO: fade-out transition when downsampling? /** Draw simplified visualization ("background" / zoomed-out) */ @@ -448,8 +385,6 @@ export default class NightingaleDistributionTrack extends withCanvas( const medianHigh = Downsampler.getDownsampled(downsamplers.medianHigh, resolution); const downScale = length / medianLow.length; - // console.log('resolution', resolution, 'downScale', downScale, `(${length} -> ${medLow.length})`) - const yMedianLow = (j: number) => yScale(medianLow[j]) + yMedianExtra; const yMedianHigh = (j: number) => yScale(medianHigh[j]) - yMedianExtra; @@ -480,7 +415,6 @@ export default class NightingaleDistributionTrack extends withCanvas( break; } - // const segments = getContiguousSegments(start, stop, i => i in dataset); const jStart = Math.max(0, Math.floor((start - offset) / downScale)); const jStop = Math.min(medianLow.length, Math.ceil((stop - offset) / downScale)); const jSegments = getContiguousSegments(jStart, jStop, j => !isNaN(medianLow[j])); From 6dc5d3c2503be601c567802b11c43d5b58cdb340 Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Wed, 17 Jun 2026 14:58:25 +0100 Subject: [PATCH 13/32] nightingale-distribution-track: refactor Downsampler to a class --- .../src/downsampling.ts | 70 ++++++++----------- .../src/nightingale-distribution-track.ts | 32 ++++----- 2 files changed, 46 insertions(+), 56 deletions(-) diff --git a/packages/nightingale-distribution-track/src/downsampling.ts b/packages/nightingale-distribution-track/src/downsampling.ts index e3bffe5e6..88cbf852f 100644 --- a/packages/nightingale-distribution-track/src/downsampling.ts +++ b/packages/nightingale-distribution-track/src/downsampling.ts @@ -2,37 +2,42 @@ type PoolingFunction = (...values: number[]) => number; /** Helper object for downsampling 1D number arrays, with caching */ -export type Downsampler = { - /** Column count of the original data */ - originalLength: number, - /** Downsampled versions of the original data (index `1` holds the original data) */ - downsampled: { [scale: number]: Float32Array | undefined }, - /** Function used to compute downsampled value from multiple source values */ - poolingFunction: PoolingFunction, -} +export class Downsampler { + /** Downsampled versions of the original data (index 1 holds the original data; indices 2, 4, 8 etc. hold increasingly downsampled data) */ + private readonly downsampled: { [scale: number]: Float32Array | undefined } = {}; -export const Downsampler = { - /** Create a new downsampler for a 2D number array */ - fromNumbers(data: Float32Array, poolingFunction: PoolingFunction): Downsampler { - return { - originalLength: data.length, - poolingFunction, - downsampled: { 1: data }, - }; - }, + /** Create a new downsampler for a 1D number array */ + constructor(data: Float32Array, private readonly poolingFunction: PoolingFunction) { + this.downsampled[1] = data; + } - /** Return the original (full-size) data */ - getOriginal(downsampler: Downsampler): Float32Array { - return downsampler.downsampled[1]!; - }, + /** Return the original full-size data */ + getOriginal(): Float32Array { + return this.downsampled[1]!; + } /** Get data downsampled approximately to `minLength`. * The returned data length will be at least `minLength` but less then double that. * Exception: The returned data will be equal to the original data if `minLength > originalData.length`. */ - getDownsampled(downsampler: Downsampler, minLength: number): Float32Array { - const targetScale = downsamplingTargetScale(downsampler.originalLength, minLength); - return getOrCompute(downsampler, targetScale); - }, + getDownsampled(minLength: number): Float32Array { + const targetScale = downsamplingTargetScale(this.getOriginal().length, minLength); + return this.getOrCompute(targetScale); + } + + /** Get data downsampled by `scale`, with caching. `scale` must be a power of 2. Resulting data length will be `Math.ceil(original.length / scale)` */ + private getOrCompute(scale: number): Float32Array { + const cached = this.downsampled[scale]; + if (cached) { + return cached; + } else { + if (scale <= 1) throw new Error('AssertionError: Downsampler.getOrCompute'); + const srcData = this.getOrCompute(scale / 2); + const result = downsampleNumbers_halve(srcData, this.poolingFunction); + this.downsampled[scale] = result; + return result; + } + } + }; /** Return `scale`, a power of 2, such that: @@ -45,20 +50,6 @@ function downsamplingTargetScale(nDatapoints: number, nPixels: number): number { return 2 ** log2scale; } -/** Get data downsampled by `scale`, with caching. `scale` must be a power of 2. Resulting data length will be `Math.ceil(original.length / scale)` */ -function getOrCompute(downsampler: Downsampler, scale: number): Float32Array { - const cached = downsampler.downsampled[scale]; - if (cached) { - return cached; - } else { - if (scale <= 1) throw new Error('AssertionError: getOrCompute'); - const srcData = getOrCompute(downsampler, scale / 2); - const result = downsampleNumbers_halve(srcData, downsampler.poolingFunction); - downsampler.downsampled[scale] = result; - return result; - } -} - /** Downsample array of numbers to a new size `ceil(input.length / 2)`. */ function downsampleNumbers_halve(input: Float32Array, poolingFunction: PoolingFunction): Float32Array { const w0 = input.length; @@ -78,4 +69,3 @@ function downsampleNumbers_halve(input: Float32Array, poolingFunction: PoolingFu } // TODO: solve pooling NaNs -// TODO: convert to class diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts index cbf066b55..eca71a855 100644 --- a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts +++ b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts @@ -381,8 +381,8 @@ export default class NightingaleDistributionTrack extends withCanvas( const resolution = (xScale(length) - xScale(0)) / BG_DOWNSAMPLING_PIXELS_PER_COLUMN; - const medianLow = Downsampler.getDownsampled(downsamplers.medianLow, resolution); - const medianHigh = Downsampler.getDownsampled(downsamplers.medianHigh, resolution); + const medianLow = downsamplers.medianLow.getDownsampled(resolution); + const medianHigh = downsamplers.medianHigh.getDownsampled(resolution); const downScale = length / medianLow.length; const yMedianLow = (j: number) => yScale(medianLow[j]) + yMedianExtra; @@ -392,20 +392,20 @@ export default class NightingaleDistributionTrack extends withCanvas( let yRangeHigh: ((j: number) => number) | undefined; switch (this['zoomed-out-range']) { case 'extremes': - const minimum = Downsampler.getDownsampled(downsamplers.minimum, resolution); - const maximum = Downsampler.getDownsampled(downsamplers.maximum, resolution); + const minimum = downsamplers.minimum.getDownsampled(resolution); + const maximum = downsamplers.maximum.getDownsampled(resolution); yRangeLow = (j: number) => yScale(minimum[j]); yRangeHigh = (j: number) => yScale(maximum[j]); break; case 'whiskers': - const whiskerLow = Downsampler.getDownsampled(downsamplers.whiskerLow, resolution); - const whiskerHigh = Downsampler.getDownsampled(downsamplers.whiskerHigh, resolution); + const whiskerLow = downsamplers.whiskerLow.getDownsampled(resolution); + const whiskerHigh = downsamplers.whiskerHigh.getDownsampled(resolution); yRangeLow = (j: number) => yScale(whiskerLow[j]); yRangeHigh = (j: number) => yScale(whiskerHigh[j]); break; case 'box': - const boxLow = Downsampler.getDownsampled(downsamplers.boxLow, resolution); - const boxHigh = Downsampler.getDownsampled(downsamplers.boxHigh, resolution); + const boxLow = downsamplers.boxLow.getDownsampled(resolution); + const boxHigh = downsamplers.boxHigh.getDownsampled(resolution); yRangeLow = (j: number) => yScale(boxLow[j]); yRangeHigh = (j: number) => yScale(boxHigh[j]); break; @@ -826,14 +826,14 @@ function getDownsamplerForDataset(data: PreprocessedPositions) { offset, length, downsamplers: { - medianLow: Downsampler.fromNumbers(arrays.median, Math.min), - medianHigh: Downsampler.fromNumbers(arrays.median, Math.max), - boxLow: Downsampler.fromNumbers(arrays.boxLow, Math.min), - boxHigh: Downsampler.fromNumbers(arrays.boxHigh, Math.max), - whiskerLow: Downsampler.fromNumbers(arrays.whiskerLow, Math.min), - whiskerHigh: Downsampler.fromNumbers(arrays.whiskerHigh, Math.max), - minimum: Downsampler.fromNumbers(arrays.minimum, Math.min), - maximum: Downsampler.fromNumbers(arrays.maximum, Math.max), + medianLow: new Downsampler(arrays.median, Math.min), + medianHigh: new Downsampler(arrays.median, Math.max), + boxLow: new Downsampler(arrays.boxLow, Math.min), + boxHigh: new Downsampler(arrays.boxHigh, Math.max), + whiskerLow: new Downsampler(arrays.whiskerLow, Math.min), + whiskerHigh: new Downsampler(arrays.whiskerHigh, Math.max), + minimum: new Downsampler(arrays.minimum, Math.min), + maximum: new Downsampler(arrays.maximum, Math.max), }, }; } From fe32a01533096e3cbe421a38e1883f76f3f318e8 Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Wed, 17 Jun 2026 15:27:57 +0100 Subject: [PATCH 14/32] nightingale-distribution-track: downsampling - handle gaps in data --- .../src/downsampling.ts | 27 ++++++++++++++----- .../src/nightingale-distribution-track.ts | 16 +++++------ .../NightingaleDistributionTrack.stories.ts | 11 +++++--- 3 files changed, 37 insertions(+), 17 deletions(-) diff --git a/packages/nightingale-distribution-track/src/downsampling.ts b/packages/nightingale-distribution-track/src/downsampling.ts index 88cbf852f..dcbf4fd46 100644 --- a/packages/nightingale-distribution-track/src/downsampling.ts +++ b/packages/nightingale-distribution-track/src/downsampling.ts @@ -1,4 +1,17 @@ -type PoolingFunction = (...values: number[]) => number; +type PoolingFunction = (a: number, b: number) => number; + +const PoolingFunctions = { + max(a: number, b: number): number { + if (isNaN(a) || a < b) return b; + else return a; + }, + min(a: number, b: number): number { + if (isNaN(a) || a > b) return b; + else return a; + }, +} satisfies Record; + +type PoolingMethod = keyof typeof PoolingFunctions; /** Helper object for downsampling 1D number arrays, with caching */ @@ -6,9 +19,13 @@ export class Downsampler { /** Downsampled versions of the original data (index 1 holds the original data; indices 2, 4, 8 etc. hold increasingly downsampled data) */ private readonly downsampled: { [scale: number]: Float32Array | undefined } = {}; + /** Function used to compute downsampled value from multiple source values */ + private readonly poolingFunction: PoolingFunction; + /** Create a new downsampler for a 1D number array */ - constructor(data: Float32Array, private readonly poolingFunction: PoolingFunction) { + constructor(data: Float32Array, readonly poolingMethod: PoolingMethod) { this.downsampled[1] = data; + this.poolingFunction = PoolingFunctions[poolingMethod]; } /** Return the original full-size data */ @@ -17,7 +34,7 @@ export class Downsampler { } /** Get data downsampled approximately to `minLength`. - * The returned data length will be at least `minLength` but less then double that. + * The returned data length will be at least `minLength` but less than `2*minLength`. * Exception: The returned data will be equal to the original data if `minLength > originalData.length`. */ getDownsampled(minLength: number): Float32Array { const targetScale = downsamplingTargetScale(this.getOriginal().length, minLength); @@ -37,8 +54,8 @@ export class Downsampler { return result; } } +} -}; /** Return `scale`, a power of 2, such that: * `nPixels <= nDatapoints/scale < 2*nPixels` or `scale === 1 && nDatapoints < 2*nPixels` */ @@ -67,5 +84,3 @@ function downsampleNumbers_halve(input: Float32Array, poolingFunction: PoolingFu } return out; } - -// TODO: solve pooling NaNs diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts index eca71a855..4ac049870 100644 --- a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts +++ b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts @@ -826,14 +826,14 @@ function getDownsamplerForDataset(data: PreprocessedPositions) { offset, length, downsamplers: { - medianLow: new Downsampler(arrays.median, Math.min), - medianHigh: new Downsampler(arrays.median, Math.max), - boxLow: new Downsampler(arrays.boxLow, Math.min), - boxHigh: new Downsampler(arrays.boxHigh, Math.max), - whiskerLow: new Downsampler(arrays.whiskerLow, Math.min), - whiskerHigh: new Downsampler(arrays.whiskerHigh, Math.max), - minimum: new Downsampler(arrays.minimum, Math.min), - maximum: new Downsampler(arrays.maximum, Math.max), + medianLow: new Downsampler(arrays.median, 'min'), + medianHigh: new Downsampler(arrays.median, 'max'), + boxLow: new Downsampler(arrays.boxLow, 'min'), + boxHigh: new Downsampler(arrays.boxHigh, 'max'), + whiskerLow: new Downsampler(arrays.whiskerLow, 'min'), + whiskerHigh: new Downsampler(arrays.whiskerHigh, 'max'), + minimum: new Downsampler(arrays.minimum, 'min'), + maximum: new Downsampler(arrays.maximum, 'max'), }, }; } diff --git a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts index 83fa8ca39..545eb4592 100644 --- a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts +++ b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts @@ -55,13 +55,18 @@ function prepareDistributionData(data: DistributionData[number]): DistributionDa name: 'Data1', color: '#0088ff', positions: positions, - // positions: remove(positions, 3, 5, 6, 35), // DEBUG + // positions: remove(positions, 3, 4, 5, 6, 35), // DEBUG + // positions: remove(positions, 3, 4, 5, 6, + // ...new Array(50).fill(0).map((_, i) => 35 + i), + // ...new Array(500).fill(0).map((_, i) => 500 + i), + // ...new Array(5000).fill(0).map((_, i) => 5000 + i), + // ), // DEBUG }, // { // name: 'Data2', // color: '#ff8800', - // positions: positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), - // // positions: remove(positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), 1, 7), // DEBUG + // // positions: positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), + // positions: remove(positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), 1, 7), // DEBUG // }, ]; } From 4c6cd4ffe4f0d25b194244d0c97806df222e87a1 Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Thu, 18 Jun 2026 13:58:38 +0100 Subject: [PATCH 15/32] nightingale-distribution-track: use alpha to hide downsampling transitions --- .../src/downsampling.ts | 62 +++++++++--- .../src/nightingale-distribution-track.ts | 98 ++++++++++++++++++- 2 files changed, 148 insertions(+), 12 deletions(-) diff --git a/packages/nightingale-distribution-track/src/downsampling.ts b/packages/nightingale-distribution-track/src/downsampling.ts index dcbf4fd46..c114d7a49 100644 --- a/packages/nightingale-distribution-track/src/downsampling.ts +++ b/packages/nightingale-distribution-track/src/downsampling.ts @@ -1,10 +1,12 @@ type PoolingFunction = (a: number, b: number) => number; const PoolingFunctions = { + /** Like `Math.max` but handles `NaN` (`max(1, 2) -> 2`, `max(1, NaN) -> 1`, `max(NaN, 2) -> 2`, `max(NaN, NaN) -> NaN`) */ max(a: number, b: number): number { if (isNaN(a) || a < b) return b; else return a; }, + /** Like `Math.min` but handles `NaN` (`min(1, 2) -> 1`, `min(1, NaN) -> 1`, `min(NaN, 2) -> 2`, `min(NaN, NaN) -> NaN`) */ min(a: number, b: number): number { if (isNaN(a) || a > b) return b; else return a; @@ -37,12 +39,20 @@ export class Downsampler { * The returned data length will be at least `minLength` but less than `2*minLength`. * Exception: The returned data will be equal to the original data if `minLength > originalData.length`. */ getDownsampled(minLength: number): Float32Array { - const targetScale = downsamplingTargetScale(this.getOriginal().length, minLength); + const targetScale = this.downsamplingTargetScale(minLength); return this.getOrCompute(targetScale); } + /** Get data downsampled approximately to `minLength`. + * The returned data length will be at least `minLength` but less than `2*minLength`. + * Exception: The returned data will be equal to the original data if `minLength > originalData.length`. */ + getDownsampledSoft(minLength: number) { + const targetScales = this.downsamplingTargetScaleSoft(minLength); + return targetScales.map(targetScale => ({ weight: targetScale.weight, data: this.getOrCompute(targetScale.scale) })); + } + /** Get data downsampled by `scale`, with caching. `scale` must be a power of 2. Resulting data length will be `Math.ceil(original.length / scale)` */ - private getOrCompute(scale: number): Float32Array { + getOrCompute(scale: number): Float32Array { const cached = this.downsampled[scale]; if (cached) { return cached; @@ -54,19 +64,49 @@ export class Downsampler { return result; } } -} + /** Return `scale`, a power of 2, such that: + * `nPixels <= nDatapoints/scale < 2*nPixels` or `scale === 1 && nDatapoints < 2*nPixels` */ + downsamplingTargetScale(nPixels: number): number { + const nDatapoints = Math.max(1, this.getOriginal().length); + nPixels = Math.max(1, nPixels); + const log2scaleExact = Math.log2(nDatapoints / nPixels); + const log2scale = Math.max(0, Math.floor(log2scaleExact)); + return 2 ** log2scale; + } -/** Return `scale`, a power of 2, such that: - * `nPixels <= nDatapoints/scale < 2*nPixels` or `scale === 1 && nDatapoints < 2*nPixels` */ -function downsamplingTargetScale(nDatapoints: number, nPixels: number): number { - nDatapoints = Math.max(1, nDatapoints); - nPixels = Math.max(1, nPixels); - const log2scaleExact = Math.log2(nDatapoints / nPixels); - const log2scale = Math.max(0, Math.floor(log2scaleExact)); - return 2 ** log2scale; + /** Return `scale`, a power of 2, such that: + * `nPixels <= nDatapoints/scale < 2*nPixels` or `scale === 1 && nDatapoints < 2*nPixels` */ + downsamplingTargetScaleSoft(nPixels: number) { + const nDatapoints = Math.max(1, this.getOriginal().length); + nPixels = Math.max(1, nPixels); + const log2scale = Math.max(0, Math.log2(nDatapoints / nPixels)); + const log2scaleFloor = Math.floor(log2scale); + const wNext = log2scale - log2scaleFloor; + if (wNext === 0) { + return [ + { scale: 2 ** log2scaleFloor, weight: 1 }, + ]; + } else { + return [ + { scale: 2 ** (log2scaleFloor + 1), weight: wNext }, + { scale: 2 ** log2scaleFloor, weight: 1 - wNext }, + ]; + } + } } + +// /** Return `scale`, a power of 2, such that: +// * `nPixels <= nDatapoints/scale < 2*nPixels` or `scale === 1 && nDatapoints < 2*nPixels` */ +// function downsamplingTargetScale(nDatapoints: number, nPixels: number): number { +// nDatapoints = Math.max(1, nDatapoints); +// nPixels = Math.max(1, nPixels); +// const log2scaleExact = Math.log2(nDatapoints / nPixels); +// const log2scale = Math.max(0, Math.floor(log2scaleExact)); +// return 2 ** log2scale; +// } + /** Downsample array of numbers to a new size `ceil(input.length / 2)`. */ function downsampleNumbers_halve(input: Float32Array, poolingFunction: PoolingFunction): Float32Array { const w0 = input.length; diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts index 4ac049870..497f32fd0 100644 --- a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts +++ b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts @@ -362,7 +362,7 @@ export default class NightingaleDistributionTrack extends withCanvas( // TODO: fade-out transition when downsampling? /** Draw simplified visualization ("background" / zoomed-out) */ - private drawSimplifiedVisualization(ctx: CanvasRenderingContext2D, alpha: number) { + private drawSimplifiedVisualization1(ctx: CanvasRenderingContext2D, alpha: number) { if (!this.data || !this.preprocessedData) return; const { xColumnLeft, xColumnRight, xScale, yScale, yMedianExtra, lineWidth, start, stop } = this.getDrawingMeasurements(); @@ -440,6 +440,89 @@ export default class NightingaleDistributionTrack extends withCanvas( } } + /** Draw simplified visualization ("background" / zoomed-out) */ + private drawSimplifiedVisualization(ctx: CanvasRenderingContext2D, alpha: number) { + if (!this.data || !this.preprocessedData) return; + + const { xColumnLeft, xColumnRight, xScale, yScale, yMedianExtra, lineWidth, start, stop } = this.getDrawingMeasurements(); + ctx.lineWidth = lineWidth; + + const nDatasets = this.preprocessedData?.datasets.length ?? 1; + for (let iDataset = 0; iDataset < nDatasets; iDataset++) { + const dataset = this.preprocessedData.datasets[iDataset]; + if (!dataset) continue; + + const { offset, length, downsamplers } = dataset.downsampling; + + const dataColor = dataset.color ?? DEFAULT_DATA_COLOR; + const fillColor = dataColor; + const strokeColor = makeStrokeColor(dataColor)!; + + const resolution = (xScale(length) - xScale(0)) / BG_DOWNSAMPLING_PIXELS_PER_COLUMN; + const downSamplingScales = downsamplers.medianLow.downsamplingTargetScaleSoft(resolution); + + for (const { scale, weight } of downSamplingScales) { + ctx.lineWidth = (scale === 1) ? 1 : lineWidth; + const medianLow = downsamplers.medianLow.getOrCompute(scale); + const medianHigh = downsamplers.medianHigh.getOrCompute(scale); + const downScale = length / medianLow.length; + + const yMedianLow = (j: number) => yScale(medianLow[j]) + yMedianExtra; + const yMedianHigh = (j: number) => yScale(medianHigh[j]) - yMedianExtra; + + let yRangeLow: ((j: number) => number) | undefined; + let yRangeHigh: ((j: number) => number) | undefined; + switch (this['zoomed-out-range']) { + case 'extremes': + const minimum = downsamplers.minimum.getOrCompute(scale); + const maximum = downsamplers.maximum.getOrCompute(scale); + yRangeLow = (j: number) => yScale(minimum[j]); + yRangeHigh = (j: number) => yScale(maximum[j]); + break; + case 'whiskers': + const whiskerLow = downsamplers.whiskerLow.getOrCompute(scale); + const whiskerHigh = downsamplers.whiskerHigh.getOrCompute(scale); + yRangeLow = (j: number) => yScale(whiskerLow[j]); + yRangeHigh = (j: number) => yScale(whiskerHigh[j]); + break; + case 'box': + const boxLow = downsamplers.boxLow.getOrCompute(scale); + const boxHigh = downsamplers.boxHigh.getOrCompute(scale); + yRangeLow = (j: number) => yScale(boxLow[j]); + yRangeHigh = (j: number) => yScale(boxHigh[j]); + break; + case 'none': + yRangeLow = undefined; + yRangeHigh = undefined; + break; + } + + const jStart = Math.max(0, Math.floor((start - offset) / downScale)); + const jStop = Math.min(medianLow.length, Math.ceil((stop - offset) / downScale)); + const jSegments = getContiguousSegments(jStart, jStop, j => !isNaN(medianLow[j])); + + const jXScale = (j: number) => xScale(offset + j * downScale); + + // Shaded range + if (yRangeLow && yRangeHigh) { + for (const segment of jSegments) { + ctx.globalAlpha = weightAlpha(0.25 * alpha, weight); + ctx.fillStyle = fillColor; + drawSilhouette(ctx, segment, jXScale, yRangeLow, yRangeHigh, [xColumnLeft, xColumnRight], 'fill'); + } + } + + // Median + for (const segment of jSegments) { + ctx.globalAlpha = weightAlpha(0.5 * alpha, weight); + ctx.fillStyle = strokeColor; + ctx.strokeStyle = strokeColor; + drawSilhouette(ctx, segment, jXScale, yMedianLow, yMedianHigh, [xColumnLeft, xColumnRight], 'fill+stroke'); + } + } + } + } + private drawMargins(ctx: CanvasRenderingContext2D) { const canvasWidth = ctx.canvas.width; const canvasHeight = ctx.canvas.height; @@ -838,4 +921,17 @@ function getDownsamplerForDataset(data: PreprocessedPositions) { }; } +function weightAlpha(alpha: number, weight: number) { + if (alpha === 1) { + // Avoid ill-defined expressions (division by zero) + return (weight > 0) ? 1 : 0; + } + const transpTotal = 1 - alpha; + const transpW = 1 - alpha * weight; + const transpWComplement = 1 - alpha * (1 - weight); + const correctionFactor = Math.sqrt(transpTotal / (transpW * transpWComplement)); + const transpWCorrected = transpW * correctionFactor; + return 1 - transpWCorrected; +} + // TODO: axis ticks From b8ec8a8212ee7b7b47bcd7cf36e9034c9170ca4c Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Thu, 18 Jun 2026 15:37:22 +0100 Subject: [PATCH 16/32] nightingale-distribution-track: use alpha to hide downsampling transitions - refactor --- .../src/downsampling.ts | 80 +++++------- .../src/nightingale-distribution-track.ts | 116 +++--------------- 2 files changed, 51 insertions(+), 145 deletions(-) diff --git a/packages/nightingale-distribution-track/src/downsampling.ts b/packages/nightingale-distribution-track/src/downsampling.ts index c114d7a49..5598b3a60 100644 --- a/packages/nightingale-distribution-track/src/downsampling.ts +++ b/packages/nightingale-distribution-track/src/downsampling.ts @@ -25,7 +25,7 @@ export class Downsampler { private readonly poolingFunction: PoolingFunction; /** Create a new downsampler for a 1D number array */ - constructor(data: Float32Array, readonly poolingMethod: PoolingMethod) { + constructor(data: Float32Array, public readonly poolingMethod: PoolingMethod) { this.downsampled[1] = data; this.poolingFunction = PoolingFunctions[poolingMethod]; } @@ -35,58 +35,55 @@ export class Downsampler { return this.downsampled[1]!; } - /** Get data downsampled approximately to `minLength`. - * The returned data length will be at least `minLength` but less than `2*minLength`. - * Exception: The returned data will be equal to the original data if `minLength > originalData.length`. */ - getDownsampled(minLength: number): Float32Array { - const targetScale = this.downsamplingTargetScale(minLength); - return this.getOrCompute(targetScale); + /** Get data downsampled so that `downsampledColumnWidth ~ originalColumnWidth * originalData.length / downsampledData.length ~ 1`. + * Return original data if `originalColumnWidth > 1`. */ + getDownsampledForColumnWidth(originalColumnWidth: number): Float32Array { + const targetScale = Downsampler.targetDownsamplingScale(originalColumnWidth); + return this.getDownsampledByScale(targetScale); } - /** Get data downsampled approximately to `minLength`. - * The returned data length will be at least `minLength` but less than `2*minLength`. - * Exception: The returned data will be equal to the original data if `minLength > originalData.length`. */ - getDownsampledSoft(minLength: number) { - const targetScales = this.downsamplingTargetScaleSoft(minLength); - return targetScales.map(targetScale => ({ weight: targetScale.weight, data: this.getOrCompute(targetScale.scale) })); - } - - /** Get data downsampled by `scale`, with caching. `scale` must be a power of 2. Resulting data length will be `Math.ceil(original.length / scale)` */ - getOrCompute(scale: number): Float32Array { + /** Get data downsampled by `scale`, with caching. `scale` must be a power of 2, greater or equal to 1 (i.e. 1, 2, 4, 8, 16...). + * Length of the resulting data will be `Math.ceil(originalData.length / scale)` */ + getDownsampledByScale(scale: number): Float32Array { + if (scale < 1) throw new Error(`Downsampler.getDownsampledByScale: invalid scale ${scale}, scale must be a power of 2, greater or equal to 1`); + if (Math.log2(scale) % 1) throw new Error(`Downsampler.getDownsampledByScale: invalid scale ${scale}, scale must be a power of 2, greater or equal to 1`); const cached = this.downsampled[scale]; if (cached) { return cached; } else { - if (scale <= 1) throw new Error('AssertionError: Downsampler.getOrCompute'); - const srcData = this.getOrCompute(scale / 2); + const srcData = this.getDownsampledByScale(scale / 2); const result = downsampleNumbers_halve(srcData, this.poolingFunction); this.downsampled[scale] = result; return result; } } - /** Return `scale`, a power of 2, such that: - * `nPixels <= nDatapoints/scale < 2*nPixels` or `scale === 1 && nDatapoints < 2*nPixels` */ - downsamplingTargetScale(nPixels: number): number { - const nDatapoints = Math.max(1, this.getOriginal().length); - nPixels = Math.max(1, nPixels); - const log2scaleExact = Math.log2(nDatapoints / nPixels); - const log2scale = Math.max(0, Math.floor(log2scaleExact)); - return 2 ** log2scale; + /** Return `scale`, a power of 2, such that + * `0.5 < originalColumnWidth*scale <= 1` (or `scale === 1` if `originalColumnWidth > 1`) */ + static targetDownsamplingScale(originalColumnWidth: number): number { + if (originalColumnWidth > 1) { + return 1; + } + const log2scale = -Math.log2(originalColumnWidth); + const log2scaleFloor = Math.floor(log2scale); + return 2 ** log2scaleFloor; } - /** Return `scale`, a power of 2, such that: - * `nPixels <= nDatapoints/scale < 2*nPixels` or `scale === 1 && nDatapoints < 2*nPixels` */ - downsamplingTargetScaleSoft(nPixels: number) { - const nDatapoints = Math.max(1, this.getOriginal().length); - nPixels = Math.max(1, nPixels); - const log2scale = Math.max(0, Math.log2(nDatapoints / nPixels)); + /** Return one or two scales, each being a power of 2, such that: + * - in case of two scales: `1 < originalColumnWidth*scale1 < 2` and `0.5 < originalColumnWidth*scale2 < 1`, `scale1 = 2 * scale2` + * - in case of one scale: `originalColumnWidth*scale === 1` (or `scale === 1` if `originalColumnWidth > 1`) + * + * Weights of the scales sum up to 1 (the closer `originalColumnWidth*scale` is to 1, the higher its weight). + */ + static targetDownsamplingScalesForTransition(originalColumnWidth: number) { + if (originalColumnWidth > 1) { + return [{ scale: 1, weight: 1 }]; + } + const log2scale = -Math.log2(originalColumnWidth); const log2scaleFloor = Math.floor(log2scale); const wNext = log2scale - log2scaleFloor; if (wNext === 0) { - return [ - { scale: 2 ** log2scaleFloor, weight: 1 }, - ]; + return [{ scale: 2 ** log2scaleFloor, weight: 1 }]; } else { return [ { scale: 2 ** (log2scaleFloor + 1), weight: wNext }, @@ -96,17 +93,6 @@ export class Downsampler { } } - -// /** Return `scale`, a power of 2, such that: -// * `nPixels <= nDatapoints/scale < 2*nPixels` or `scale === 1 && nDatapoints < 2*nPixels` */ -// function downsamplingTargetScale(nDatapoints: number, nPixels: number): number { -// nDatapoints = Math.max(1, nDatapoints); -// nPixels = Math.max(1, nPixels); -// const log2scaleExact = Math.log2(nDatapoints / nPixels); -// const log2scale = Math.max(0, Math.floor(log2scaleExact)); -// return 2 ** log2scale; -// } - /** Downsample array of numbers to a new size `ceil(input.length / 2)`. */ function downsampleNumbers_halve(input: Float32Array, poolingFunction: PoolingFunction): Float32Array { const w0 = input.length; diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts index 497f32fd0..68c5cdbfb 100644 --- a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts +++ b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts @@ -50,7 +50,7 @@ const OUTLIER_RADIUS = 2; const FG_BG_TRANSITION_BASE_WIDTHS = [4, 5]; /** Approximate width of a column in screen pixels, when showing downsampled data in "background" visualization. * (higher value means more responsive but lower-resolution visualization). */ -// const BG_DOWNSAMPLING_PIXELS_PER_COLUMN = 2; +// const BG_DOWNSAMPLING_PIXELS_PER_COLUMN = 4; const BG_DOWNSAMPLING_PIXELS_PER_COLUMN = 1; function makeStrokeColor(dataColor: string): string | undefined { @@ -359,87 +359,6 @@ export default class NightingaleDistributionTrack extends withCanvas( } } - // TODO: fade-out transition when downsampling? - - /** Draw simplified visualization ("background" / zoomed-out) */ - private drawSimplifiedVisualization1(ctx: CanvasRenderingContext2D, alpha: number) { - if (!this.data || !this.preprocessedData) return; - - const { xColumnLeft, xColumnRight, xScale, yScale, yMedianExtra, lineWidth, start, stop } = this.getDrawingMeasurements(); - ctx.lineWidth = lineWidth; - - const nDatasets = this.preprocessedData?.datasets.length ?? 1; - for (let iDataset = 0; iDataset < nDatasets; iDataset++) { - const dataset = this.preprocessedData.datasets[iDataset]; - if (!dataset) continue; - - const { offset, length, downsamplers } = dataset.downsampling; - - const dataColor = dataset.color ?? DEFAULT_DATA_COLOR; - const fillColor = dataColor; - const strokeColor = makeStrokeColor(dataColor)!; - - const resolution = (xScale(length) - xScale(0)) / BG_DOWNSAMPLING_PIXELS_PER_COLUMN; - - const medianLow = downsamplers.medianLow.getDownsampled(resolution); - const medianHigh = downsamplers.medianHigh.getDownsampled(resolution); - const downScale = length / medianLow.length; - - const yMedianLow = (j: number) => yScale(medianLow[j]) + yMedianExtra; - const yMedianHigh = (j: number) => yScale(medianHigh[j]) - yMedianExtra; - - let yRangeLow: ((j: number) => number) | undefined; - let yRangeHigh: ((j: number) => number) | undefined; - switch (this['zoomed-out-range']) { - case 'extremes': - const minimum = downsamplers.minimum.getDownsampled(resolution); - const maximum = downsamplers.maximum.getDownsampled(resolution); - yRangeLow = (j: number) => yScale(minimum[j]); - yRangeHigh = (j: number) => yScale(maximum[j]); - break; - case 'whiskers': - const whiskerLow = downsamplers.whiskerLow.getDownsampled(resolution); - const whiskerHigh = downsamplers.whiskerHigh.getDownsampled(resolution); - yRangeLow = (j: number) => yScale(whiskerLow[j]); - yRangeHigh = (j: number) => yScale(whiskerHigh[j]); - break; - case 'box': - const boxLow = downsamplers.boxLow.getDownsampled(resolution); - const boxHigh = downsamplers.boxHigh.getDownsampled(resolution); - yRangeLow = (j: number) => yScale(boxLow[j]); - yRangeHigh = (j: number) => yScale(boxHigh[j]); - break; - case 'none': - yRangeLow = undefined; - yRangeHigh = undefined; - break; - } - - const jStart = Math.max(0, Math.floor((start - offset) / downScale)); - const jStop = Math.min(medianLow.length, Math.ceil((stop - offset) / downScale)); - const jSegments = getContiguousSegments(jStart, jStop, j => !isNaN(medianLow[j])); - - const jXScale = (j: number) => xScale(offset + j * downScale); - - // Shaded range - if (yRangeLow && yRangeHigh) { - for (const segment of jSegments) { - ctx.globalAlpha = 0.25 * alpha; - ctx.fillStyle = fillColor; - drawSilhouette(ctx, segment, jXScale, yRangeLow, yRangeHigh, [xColumnLeft, xColumnRight], 'fill'); - } - } - - // Median - for (const segment of jSegments) { - ctx.globalAlpha = 0.5 * alpha; - ctx.fillStyle = strokeColor; - ctx.strokeStyle = strokeColor; - drawSilhouette(ctx, segment, jXScale, yMedianLow, yMedianHigh, [xColumnLeft, xColumnRight], 'fill+stroke'); - } - } - } - /** Draw simplified visualization ("background" / zoomed-out) */ private drawSimplifiedVisualization(ctx: CanvasRenderingContext2D, alpha: number) { if (!this.data || !this.preprocessedData) return; @@ -447,6 +366,9 @@ export default class NightingaleDistributionTrack extends withCanvas( const { xColumnLeft, xColumnRight, xScale, yScale, yMedianExtra, lineWidth, start, stop } = this.getDrawingMeasurements(); ctx.lineWidth = lineWidth; + const originalColumnWidth = (xScale(1) - xScale(0)) / BG_DOWNSAMPLING_PIXELS_PER_COLUMN; + const downsamplingLevels = Downsampler.targetDownsamplingScalesForTransition(originalColumnWidth); + const nDatasets = this.preprocessedData?.datasets.length ?? 1; for (let iDataset = 0; iDataset < nDatasets; iDataset++) { const dataset = this.preprocessedData.datasets[iDataset]; @@ -458,14 +380,12 @@ export default class NightingaleDistributionTrack extends withCanvas( const fillColor = dataColor; const strokeColor = makeStrokeColor(dataColor)!; - const resolution = (xScale(length) - xScale(0)) / BG_DOWNSAMPLING_PIXELS_PER_COLUMN; - const downSamplingScales = downsamplers.medianLow.downsamplingTargetScaleSoft(resolution); - - for (const { scale, weight } of downSamplingScales) { + // Overlay two downsampling levels (e.g. 8x and 4x) to hide the transition between levels and create illusion of smooth zooming + for (const { scale, weight } of downsamplingLevels) { ctx.lineWidth = (scale === 1) ? 1 : lineWidth; - const medianLow = downsamplers.medianLow.getOrCompute(scale); - const medianHigh = downsamplers.medianHigh.getOrCompute(scale); - const downScale = length / medianLow.length; + const medianLow = downsamplers.medianLow.getDownsampledByScale(scale); + const medianHigh = downsamplers.medianHigh.getDownsampledByScale(scale); + const exactScale = length / medianLow.length; // This might be slightly different from `scale` which is always a power of two. const yMedianLow = (j: number) => yScale(medianLow[j]) + yMedianExtra; const yMedianHigh = (j: number) => yScale(medianHigh[j]) - yMedianExtra; @@ -474,20 +394,20 @@ export default class NightingaleDistributionTrack extends withCanvas( let yRangeHigh: ((j: number) => number) | undefined; switch (this['zoomed-out-range']) { case 'extremes': - const minimum = downsamplers.minimum.getOrCompute(scale); - const maximum = downsamplers.maximum.getOrCompute(scale); + const minimum = downsamplers.minimum.getDownsampledByScale(scale); + const maximum = downsamplers.maximum.getDownsampledByScale(scale); yRangeLow = (j: number) => yScale(minimum[j]); yRangeHigh = (j: number) => yScale(maximum[j]); break; case 'whiskers': - const whiskerLow = downsamplers.whiskerLow.getOrCompute(scale); - const whiskerHigh = downsamplers.whiskerHigh.getOrCompute(scale); + const whiskerLow = downsamplers.whiskerLow.getDownsampledByScale(scale); + const whiskerHigh = downsamplers.whiskerHigh.getDownsampledByScale(scale); yRangeLow = (j: number) => yScale(whiskerLow[j]); yRangeHigh = (j: number) => yScale(whiskerHigh[j]); break; case 'box': - const boxLow = downsamplers.boxLow.getOrCompute(scale); - const boxHigh = downsamplers.boxHigh.getOrCompute(scale); + const boxLow = downsamplers.boxLow.getDownsampledByScale(scale); + const boxHigh = downsamplers.boxHigh.getDownsampledByScale(scale); yRangeLow = (j: number) => yScale(boxLow[j]); yRangeHigh = (j: number) => yScale(boxHigh[j]); break; @@ -497,11 +417,11 @@ export default class NightingaleDistributionTrack extends withCanvas( break; } - const jStart = Math.max(0, Math.floor((start - offset) / downScale)); - const jStop = Math.min(medianLow.length, Math.ceil((stop - offset) / downScale)); + const jStart = Math.max(0, Math.floor((start - offset) / exactScale)); + const jStop = Math.min(medianLow.length, Math.ceil((stop - offset) / exactScale)); const jSegments = getContiguousSegments(jStart, jStop, j => !isNaN(medianLow[j])); - const jXScale = (j: number) => xScale(offset + j * downScale); + const jXScale = (j: number) => xScale(offset + j * exactScale); // Shaded range if (yRangeLow && yRangeHigh) { From 11ecb209d90edca3a18d8a5cae8cd5400043c7c2 Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Mon, 22 Jun 2026 13:47:16 +0100 Subject: [PATCH 17/32] nightingale-distribution-track: elaborate events, nested highlights --- .../src/nightingale-distribution-track.ts | 111 ++++++++++++++++-- .../src/utils/bindEvents.ts | 33 +++++- .../NightingaleDistributionTrack.stories.ts | 24 ++-- 3 files changed, 143 insertions(+), 25 deletions(-) diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts index 68c5cdbfb..8a4b73d1c 100644 --- a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts +++ b/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts @@ -14,7 +14,7 @@ import NightingaleElement, { withZoom, } from "@nightingale-elements/nightingale-new-core"; import { BaseType, color, max, min, randomLcg, randomUniform, scaleLinear, select, Selection, TypedArray } from "d3"; -import { html, PropertyDeclaration, PropertyValues } from "lit"; +import { ComplexAttributeConverter, html, PropertyDeclaration, PropertyValues } from "lit"; import { property } from "lit/decorators.js"; import { Downsampler } from "./downsampling"; @@ -47,7 +47,7 @@ const JITTER_REL_WIDTH = 0.4; /** Radius for the circles representing outliers */ const OUTLIER_RADIUS = 2; /** Column widths in CSS pixels, between which transition from "background" to "foreground" visualization happens */ -const FG_BG_TRANSITION_BASE_WIDTHS = [4, 5]; +const FG_BG_TRANSITION_BASE_WIDTHS = [4, 5] as const; /** Approximate width of a column in screen pixels, when showing downsampled data in "background" visualization. * (higher value means more responsive but lower-resolution visualization). */ // const BG_DOWNSAMPLING_PIXELS_PER_COLUMN = 4; @@ -98,6 +98,8 @@ function EnumAttributeConverter(allowedValues: re export const ZoomedOutRangeOptions = ['extremes', 'whiskers', 'box', 'none'] as const; export type ZoomedOutRangeOption = typeof ZoomedOutRangeOptions[number]; + +// TODO: rename to nightingale-boxplot-track @customElementOnce("nightingale-distribution-track") export default class NightingaleDistributionTrack extends withCanvas( withManager( @@ -142,10 +144,18 @@ export default class NightingaleDistributionTrack extends withCanvas( @property({ converter: EnumAttributeConverter(ZoomedOutRangeOptions, 'whiskers') }) "zoomed-out-range": ZoomedOutRangeOption; // TODO: enum-type in other components? + /** Turn on showing secondary highlights, which indicate selected subcolumn within a column (in case of multiple dataset). */ + @property({ type: Boolean }) + "show-nested-highlights"?: boolean; + + /** Position of secondary highlight in from "position/iDataset", or "" if none. */ + @property({ type: String, reflect: true }) + private "nested-highlight": string = ""; #data?: DistributionData; private preprocessedData?: PreprocessedData; protected highlighted?: Selection; + protected nestedHighlighted?: Selection; override connectedCallback() { @@ -193,12 +203,14 @@ export default class NightingaleDistributionTrack extends withCanvas( if (this.svg) { // this check is necessary because `svg` setter does not always set this.bindEvents(this.svg); this.highlighted = this.svg.append("g").attr("class", "highlighted"); + this.nestedHighlighted = this.svg.append("g").attr("class", "highlighted-datapoint"); } } refresh() { this.requestDraw(); this.updateHighlight(); + this.updateNestedHighlight(); } private readonly _drawStamp = new Stamp(() => { @@ -541,6 +553,35 @@ export default class NightingaleDistributionTrack extends withCanvas( highlights.exit().remove(); } + protected updateNestedHighlight() { + if (!this.nestedHighlighted) return; + const nestedHighlightLocation = NestedHighlight.parse(this["nested-highlight"]); + const nDatasets = this.preprocessedData?.datasets.length ?? 1; + const showNestedHighlight = this["show-nested-highlights"] && nDatasets > 1 && nestedHighlightLocation !== undefined; + + const highlights = this.nestedHighlighted + .selectAll("rect") + .data(showNestedHighlight ? [nestedHighlightLocation] : []); + + const baseWidth = this.getSingleBaseWidth(); + const columnOffset = baseWidth * 0.5 * COLUMN_GAP; + const columnWidth = baseWidth * (1 - COLUMN_GAP); + const datumWidth = columnWidth / nDatasets; + + highlights + .enter() + .append("rect") + .style("pointer-events", "none") + .merge(highlights) + .attr("fill", this["highlight-color"]) + .attr("opacity", this.getFgBgOpacity()[0]) + .attr("height", this.height) + .attr("x", ([position, iDataset]) => this.getXFromSeqPosition(position) + columnOffset + iDataset * datumWidth) + .attr("width", datumWidth); + + highlights.exit().remove(); + } + override zoomRefreshed() { super.zoomRefreshed(); if (this.getWidthWithMargins() > 0) this.refresh(); @@ -585,10 +626,22 @@ export default class NightingaleDistributionTrack extends withCanvas( if (pointed === undefined) { return; } + const feature: Parameters[1] = pointed.datum ? + { + type: 'distribution', + position: pointed.position, + dataset: { name: pointed.dataset.name, color: pointed.dataset.color ?? DEFAULT_DATA_COLOR }, + datum: pointed.datum, + } + : undefined; const withHighlight = this.getAttribute("highlight-event") === "onclick"; + if (withHighlight) { + this["nested-highlight"] = NestedHighlight.format(pointed.iDataset !== undefined ? [pointed.position, pointed.iDataset] : undefined); + } + const customEvent = createEvent( "click", - null, // TODO: pass (pointed.datum ?? null), + feature, withHighlight, true, pointed.position, @@ -605,10 +658,22 @@ export default class NightingaleDistributionTrack extends withCanvas( if (pointed === undefined) { return; } + const feature: Parameters[1] = pointed.datum ? + { + type: 'distribution', + position: pointed.position, + dataset: { name: pointed.dataset.name, color: pointed.dataset.color ?? DEFAULT_DATA_COLOR }, + datum: pointed.datum, + } + : undefined;// TODO: factor out; + const withHighlight = this.getAttribute("highlight-event") === "onmouseover"; + if (withHighlight) { + this["nested-highlight"] = NestedHighlight.format(pointed.iDataset !== undefined ? [pointed.position, pointed.iDataset] : undefined); + } const customEvent = createEvent( "mouseover", - null, // TODO: pass (pointed.datum ?? null), + feature, withHighlight, false, pointed.position, @@ -622,6 +687,9 @@ export default class NightingaleDistributionTrack extends withCanvas( private handleMouseout(event: MouseEvent): void { const withHighlight = this.getAttribute("highlight-event") === "onmouseover"; + if (withHighlight) { + this["nested-highlight"] = NestedHighlight.format(undefined); + } const customEvent = createEvent( "mouseout", null, @@ -636,12 +704,20 @@ export default class NightingaleDistributionTrack extends withCanvas( this.dispatchEvent(customEvent); } - private getPointedDatum(svgX: number, _svgY: number): { position: number, datum: PreprocessedDatum | undefined } | undefined { + private getPointedDatum(svgX: number, _svgY: number): { position: number, iDataset: number, dataset: PreprocessedDataset, datum: PreprocessedDatum } | { position: number, iDataset: undefined, dataset: undefined, datum: undefined } | undefined { const continuousPosition = this.getSeqPositionFromX(svgX); if (continuousPosition === undefined) return undefined; const position = Math.floor(continuousPosition); - const datum = this.preprocessedData?.datasets[0].positions[position]; // TODO: consider multiple datasets - return { position, datum }; + const fractional = continuousPosition - position; + const fractionalWithinColumn = (fractional - 0.5 * COLUMN_GAP) / (1 - COLUMN_GAP); + const nDatasets = this.preprocessedData?.datasets.length ?? 1; + const iDataset = Math.max(0, Math.min(nDatasets - 1, Math.floor(fractionalWithinColumn * nDatasets))); + const dataset = this.preprocessedData?.datasets[iDataset]; + const datum = dataset?.positions[position]; + if (!datum) { + return { position, iDataset: undefined, dataset: undefined, datum: undefined }; + } + return { position, iDataset, dataset, datum }; } } @@ -663,7 +739,6 @@ function preprocessDataset(dataset: DistributionDataset) { for (const datum of dataset.positions) { preprocessedPositions[datum.position] = preprocessDatum(datum); } - // return out; return { ...dataset, positions: preprocessedPositions, @@ -673,16 +748,16 @@ function preprocessDataset(dataset: DistributionDataset) { interface PreprocessedDatum { position: number, - values: number[] | TypedArray, + values: Float32Array, median: number, boxLow: number, boxHigh: number, whiskerLow: number, whiskerHigh: number, - outliersLow: number[] | TypedArray, - outliersHigh: number[] | TypedArray, minimum: number, maximum: number, + outliersLow: Float32Array, + outliersHigh: Float32Array, } type PreprocessedPositions = { [position: number]: PreprocessedDatum } @@ -854,4 +929,18 @@ function weightAlpha(alpha: number, weight: number) { return 1 - transpWCorrected; } +type NestedHighlight = [position: number, iDataset: number] | undefined; +const NestedHighlight = { + format(value: NestedHighlight): string { + if (!value) return ''; + return `${value[0]}${this.SEPARATOR}${value[1]}`; + }, + parse(str: string): NestedHighlight { + if (str.trim() === '') return undefined; + const [a, b] = str.split(this.SEPARATOR).map(Number); + return [a, b]; + }, + SEPARATOR: '/', +}; + // TODO: axis ticks diff --git a/packages/nightingale-new-core/src/utils/bindEvents.ts b/packages/nightingale-new-core/src/utils/bindEvents.ts index 1be62db30..ea11475b4 100644 --- a/packages/nightingale-new-core/src/utils/bindEvents.ts +++ b/packages/nightingale-new-core/src/utils/bindEvents.ts @@ -1,6 +1,6 @@ -import NightingaleBaseElement from "../nightingale-base-element"; +import { BaseType, Selection } from "d3"; import { WithHighlightInterface } from "../mixins/withHighlight"; -import { Selection, BaseType } from "d3"; +import NightingaleBaseElement from "../nightingale-base-element"; export const HIGHLIGHT_EVENT = "highlight-event"; @@ -20,11 +20,32 @@ type SequenceBaseData = { position: number; aa: string; }; +type DistributionData = { + type: 'distribution'; + position: number; + dataset: { + name: string; + color: string; + }; + datum: { + position: number; + values: Float32Array; + median: number; + boxLow: number; + boxHigh: number; + whiskerLow: number; + whiskerHigh: number; + minimum: number; + maximum: number; + outliersLow: Float32Array; + outliersHigh: Float32Array; + }; +}; -type detailInterface = { +type EventDetail = { eventType: EventType; coords: null | [number, number]; - feature?: FeatureData | SequenceBaseData | null; + feature?: FeatureData | SequenceBaseData | DistributionData | null; target?: HTMLElement; highlight?: string; selectedId?: string | null; @@ -33,7 +54,7 @@ type detailInterface = { export function createEvent( type: EventType, - feature: FeatureData | SequenceBaseData | null = null, + feature: FeatureData | SequenceBaseData | DistributionData | null = null, withHighlight = false, withId = false, start?: number, @@ -48,7 +69,7 @@ export function createEvent( feature = (feature as FeatureData)?.feature || feature; } - const detail: detailInterface = { + const detail: EventDetail = { eventType: type, feature, target, diff --git a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts index 545eb4592..7448918cc 100644 --- a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts +++ b/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts @@ -17,6 +17,7 @@ const DefaultArgs = { "y-min": 0 as number | undefined, "y-max": undefined as number | undefined, "hide-outliers": false, + "show-nested-highlights": true, "zoomed-out-range": 'whiskers', }; type Args = typeof DefaultArgs; @@ -30,9 +31,9 @@ const ArgumentTypes: Partial> = { // const nDataRepeat = 20_000; -const nDataRepeat = 1_000; +// const nDataRepeat = 1_000; // const nDataRepeat = 81; -// const nDataRepeat = 82; +const nDataRepeat = 82; // Around 100k datapoints (nDataRepeat=1000), canvas draw takes > 40ms // Around 400k datapoints (nDataRepeat=4000), aliasing makes data invisible (causes artifacts even before) @@ -62,12 +63,18 @@ function prepareDistributionData(data: DistributionData[number]): DistributionDa // ...new Array(5000).fill(0).map((_, i) => 5000 + i), // ), // DEBUG }, - // { - // name: 'Data2', - // color: '#ff8800', - // // positions: positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), - // positions: remove(positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), 1, 7), // DEBUG - // }, + { + name: 'Data2', + color: '#ff8800', + // positions: positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), + positions: remove(positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), 1, 7), // DEBUG + }, + { + name: 'Data3', + color: '#00aa44', + // positions: positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), + positions: remove(positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.93) })), 1, 7), // DEBUG + }, ]; } @@ -173,6 +180,7 @@ function nightingaleDistributionTrack(args: Args & { length: number, id: number y-min=${args["y-min"]} y-max=${args["y-max"]} ?hide-outliers=${args["hide-outliers"]} + ?show-nested-highlights=${args["show-nested-highlights"]} zoomed-out-range=${args["zoomed-out-range"]} > From 3535944c8fb09520e664cb6c41118fc0dfeee048 Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Mon, 22 Jun 2026 17:02:07 +0100 Subject: [PATCH 18/32] nightingale-distribution-track: rename to nightingale-boxplot-track --- packages/nightingale-boxplot-track/README.md | 7 ++ .../package.json | 4 +- .../src/downsampling.ts | 0 .../nightingale-boxplot-track/src/index.ts | 3 + .../src/nightingale-boxplot-track.ts} | 100 +++++++++--------- .../tests/mockData/sample-1.json | 0 .../nightingale-distribution-track.test.ts | 2 +- .../tsconfig.json | 0 .../nightingale-distribution-track/README.md | 7 -- .../src/index.ts | 3 - .../src/utils/bindEvents.ts | 9 +- .../NightingaleBoxplotTrack.stories.mdx} | 4 +- .../NightingaleBoxplotTrack.stories.ts} | 77 +++----------- 13 files changed, 87 insertions(+), 129 deletions(-) create mode 100644 packages/nightingale-boxplot-track/README.md rename packages/{nightingale-distribution-track => nightingale-boxplot-track}/package.json (90%) rename packages/{nightingale-distribution-track => nightingale-boxplot-track}/src/downsampling.ts (100%) create mode 100644 packages/nightingale-boxplot-track/src/index.ts rename packages/{nightingale-distribution-track/src/nightingale-distribution-track.ts => nightingale-boxplot-track/src/nightingale-boxplot-track.ts} (92%) rename packages/{nightingale-distribution-track => nightingale-boxplot-track}/tests/mockData/sample-1.json (100%) rename packages/{nightingale-distribution-track => nightingale-boxplot-track}/tests/nightingale-distribution-track.test.ts (97%) rename packages/{nightingale-distribution-track => nightingale-boxplot-track}/tsconfig.json (100%) delete mode 100644 packages/nightingale-distribution-track/README.md delete mode 100644 packages/nightingale-distribution-track/src/index.ts rename stories/{22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.mdx => 22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.mdx} (90%) rename stories/{22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts => 22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts} (66%) diff --git a/packages/nightingale-boxplot-track/README.md b/packages/nightingale-boxplot-track/README.md new file mode 100644 index 000000000..219fbac5a --- /dev/null +++ b/packages/nightingale-boxplot-track/README.md @@ -0,0 +1,7 @@ +# nightingale-boxplot-track + +[![Published on NPM](https://img.shields.io/npm/v/@nightingale-elements/nightingale-boxplot-track.svg)](https://www.npmjs.com/package/@nightingale-elements/nightingale-boxplot-track) + +The `nightingale-boxplot-track` component ... + +TODO: diff --git a/packages/nightingale-distribution-track/package.json b/packages/nightingale-boxplot-track/package.json similarity index 90% rename from packages/nightingale-distribution-track/package.json rename to packages/nightingale-boxplot-track/package.json index 05686d6e1..6f4f444dc 100644 --- a/packages/nightingale-distribution-track/package.json +++ b/packages/nightingale-boxplot-track/package.json @@ -1,7 +1,7 @@ { - "name": "@nightingale-elements/nightingale-distribution-track", + "name": "@nightingale-elements/nightingale-boxplot-track", "version": "5.6.0", - "description": "Track for showing distribution of a variable on each residue position.", + "description": "Track for showing distribution of a variable on each residue position via boxplots.", "files": [ "dist", "src" diff --git a/packages/nightingale-distribution-track/src/downsampling.ts b/packages/nightingale-boxplot-track/src/downsampling.ts similarity index 100% rename from packages/nightingale-distribution-track/src/downsampling.ts rename to packages/nightingale-boxplot-track/src/downsampling.ts diff --git a/packages/nightingale-boxplot-track/src/index.ts b/packages/nightingale-boxplot-track/src/index.ts new file mode 100644 index 000000000..3020179c1 --- /dev/null +++ b/packages/nightingale-boxplot-track/src/index.ts @@ -0,0 +1,3 @@ +import NightingaleBoxplotTrack, { } from "./nightingale-boxplot-track"; + +export { NightingaleBoxplotTrack as default }; diff --git a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts similarity index 92% rename from packages/nightingale-distribution-track/src/nightingale-distribution-track.ts rename to packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts index 8a4b73d1c..9f1d152c9 100644 --- a/packages/nightingale-distribution-track/src/nightingale-distribution-track.ts +++ b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts @@ -24,8 +24,8 @@ const ATTRIBUTES_THAT_TRIGGER_REFRESH: string[] = [ "margin-top", "margin-bottom", "margin-left", "margin-right", "margin-color", "font-family", "min-font-size", "fade-font-size", "max-font-size", "y-min", "y-max", "hide-outliers", "zoomed-out-range", -] satisfies (keyof NightingaleDistributionTrack)[]; -const ATTRIBUTES_THAT_TRIGGER_DATA_RESET: string[] = [] satisfies (keyof NightingaleDistributionTrack)[]; +] satisfies (keyof NightingaleBoxplotTrack)[]; +const ATTRIBUTES_THAT_TRIGGER_DATA_RESET: string[] = [] satisfies (keyof NightingaleBoxplotTrack)[]; /** Line width for rectangle stroke */ @@ -58,19 +58,24 @@ function makeStrokeColor(dataColor: string): string | undefined { } -interface Distribution { +interface BoxplotDatum { + /** Position in the sequence (1-based) */ position: number, - values: number[], + /** Array of values of independent variable at the position */ + values: ArrayLike, } -export interface DistributionDataset { +export interface BoxplotDataset { + /** Name of the dataset */ name: string, + /** Color of the dataset visualization */ color?: string, - positions: Distribution[], + /** Array of boxplot data for individual positions in the sequence */ + positions: BoxplotDatum[], } -/** Type for `NightingaleDistributionTrack.data`` */ -export type DistributionData = DistributionDataset[]; +/** Type for `NightingaleBoxplotTrack.data`` */ +export type BoxplotData = BoxplotDataset[]; type AttributeConverter = NonNullable['converter']>; @@ -100,8 +105,8 @@ export type ZoomedOutRangeOption = typeof ZoomedOutRangeOptions[number]; // TODO: rename to nightingale-boxplot-track -@customElementOnce("nightingale-distribution-track") -export default class NightingaleDistributionTrack extends withCanvas( +@customElementOnce("nightingale-boxplot-track") +export default class NightingaleBoxplotTrack extends withCanvas( withManager( withZoom( withResizable( @@ -152,7 +157,7 @@ export default class NightingaleDistributionTrack extends withCanvas( @property({ type: String, reflect: true }) private "nested-highlight": string = ""; - #data?: DistributionData; + #data?: BoxplotData; private preprocessedData?: PreprocessedData; protected highlighted?: Selection; protected nestedHighlighted?: Selection; @@ -163,14 +168,12 @@ export default class NightingaleDistributionTrack extends withCanvas( if (this.data) this.createTrack(); } - get data(): DistributionData | undefined { + get data(): BoxplotData | undefined { return this.#data; } - set data(data: DistributionData | undefined) { + set data(data: BoxplotData | undefined) { this.#data = data; - console.time('preprocessData') this.preprocessedData = data ? preprocessData(data) : undefined; - console.timeEnd('preprocessData') this.createTrack(); } /** Return the range of Y values corresponding to bottom and top of the viewport (excluding margins) */ @@ -240,11 +243,9 @@ export default class NightingaleDistributionTrack extends withCanvas( if (!this._drawStamp.update().changed) return; this.adjustCanvasCtxLogicalSize(); if (!this.canvasCtx) return; - console.time('draw distr') this.clearCanvas(this.canvasCtx); this.drawData(this.canvasCtx); this.drawMargins(this.canvasCtx); - console.timeEnd('draw distr') } private getOffscreenCanvas(): [canvas: HTMLCanvasElement, canvasContext?: CanvasRenderingContext2D] { @@ -610,15 +611,15 @@ export default class NightingaleDistributionTrack extends withCanvas( private bindEvents(target: Selection): void { - target.on("click.NightingaleDistributionTrack", (event: MouseEvent) => this.handleClick(event)); - target.on("mousemove.NightingaleDistributionTrack", (event: MouseEvent) => this.handleMousemove(event)); - target.on("mouseout.NightingaleDistributionTrack", (event: MouseEvent) => this.handleMouseout(event)); + target.on("click.NightingaleBoxplotTrack", (event: MouseEvent) => this.handleClick(event)); + target.on("mousemove.NightingaleBoxplotTrack", (event: MouseEvent) => this.handleMousemove(event)); + target.on("mouseout.NightingaleBoxplotTrack", (event: MouseEvent) => this.handleMouseout(event)); } private unbindEvents(target: Selection): void { - target.on("click.NightingaleDistributionTrack", null); - target.on("mousemove.NightingaleDistributionTrack", null); - target.on("mouseout.NightingaleDistributionTrack", null); + target.on("click.NightingaleBoxplotTrack", null); + target.on("mousemove.NightingaleBoxplotTrack", null); + target.on("mouseout.NightingaleBoxplotTrack", null); } private handleClick(event: MouseEvent): void { @@ -626,22 +627,16 @@ export default class NightingaleDistributionTrack extends withCanvas( if (pointed === undefined) { return; } - const feature: Parameters[1] = pointed.datum ? - { - type: 'distribution', - position: pointed.position, - dataset: { name: pointed.dataset.name, color: pointed.dataset.color ?? DEFAULT_DATA_COLOR }, - datum: pointed.datum, - } - : undefined; + const withHighlight = this.getAttribute("highlight-event") === "onclick"; if (withHighlight) { - this["nested-highlight"] = NestedHighlight.format(pointed.iDataset !== undefined ? [pointed.position, pointed.iDataset] : undefined); + const iDataset = pointed.feature?.dataset.index; + this["nested-highlight"] = NestedHighlight.format(iDataset !== undefined ? [pointed.position, iDataset] : undefined); } const customEvent = createEvent( "click", - feature, + pointed.feature, withHighlight, true, pointed.position, @@ -658,22 +653,16 @@ export default class NightingaleDistributionTrack extends withCanvas( if (pointed === undefined) { return; } - const feature: Parameters[1] = pointed.datum ? - { - type: 'distribution', - position: pointed.position, - dataset: { name: pointed.dataset.name, color: pointed.dataset.color ?? DEFAULT_DATA_COLOR }, - datum: pointed.datum, - } - : undefined;// TODO: factor out; const withHighlight = this.getAttribute("highlight-event") === "onmouseover"; if (withHighlight) { - this["nested-highlight"] = NestedHighlight.format(pointed.iDataset !== undefined ? [pointed.position, pointed.iDataset] : undefined); + const iDataset = pointed.feature?.dataset.index; + this["nested-highlight"] = NestedHighlight.format(iDataset !== undefined ? [pointed.position, iDataset] : undefined); } + const customEvent = createEvent( "mouseover", - feature, + pointed.feature, withHighlight, false, pointed.position, @@ -704,7 +693,7 @@ export default class NightingaleDistributionTrack extends withCanvas( this.dispatchEvent(customEvent); } - private getPointedDatum(svgX: number, _svgY: number): { position: number, iDataset: number, dataset: PreprocessedDataset, datum: PreprocessedDatum } | { position: number, iDataset: undefined, dataset: undefined, datum: undefined } | undefined { + private getPointedDatum(svgX: number, _svgY: number) { const continuousPosition = this.getSeqPositionFromX(svgX); if (continuousPosition === undefined) return undefined; const position = Math.floor(continuousPosition); @@ -712,12 +701,25 @@ export default class NightingaleDistributionTrack extends withCanvas( const fractionalWithinColumn = (fractional - 0.5 * COLUMN_GAP) / (1 - COLUMN_GAP); const nDatasets = this.preprocessedData?.datasets.length ?? 1; const iDataset = Math.max(0, Math.min(nDatasets - 1, Math.floor(fractionalWithinColumn * nDatasets))); + const dataset = this.preprocessedData?.datasets[iDataset]; const datum = dataset?.positions[position]; if (!datum) { - return { position, iDataset: undefined, dataset: undefined, datum: undefined }; + return { position, feature: undefined }; } - return { position, iDataset, dataset, datum }; + + type EventFeatureData = Parameters[1]; + const feature: EventFeatureData = { + type: 'boxplot', + position: position, + dataset: { + index: iDataset, + name: dataset.name, + color: dataset.color ?? DEFAULT_DATA_COLOR, + }, + datum: datum, + }; + return { position, feature }; } } @@ -725,7 +727,7 @@ export default class NightingaleDistributionTrack extends withCanvas( type PreprocessedData = ReturnType; type PreprocessedDataset = ReturnType; -function preprocessData(data: DistributionData) { +function preprocessData(data: BoxplotData) { const preprocessedDatasets = data.map(preprocessDataset); return { datasets: preprocessedDatasets, @@ -733,7 +735,7 @@ function preprocessData(data: DistributionData) { } } -function preprocessDataset(dataset: DistributionDataset) { +function preprocessDataset(dataset: BoxplotDataset) { const preprocessedPositions: PreprocessedPositions = {}; for (const datum of dataset.positions) { @@ -762,7 +764,7 @@ interface PreprocessedDatum { type PreprocessedPositions = { [position: number]: PreprocessedDatum } -function preprocessDatum(datum: Distribution): PreprocessedDatum { +function preprocessDatum(datum: BoxplotDatum): PreprocessedDatum { const sorted = sortIfNeeded(new Float32Array(datum.values)); const median = getQuantile(sorted, 0.5); const q1 = getQuantile(sorted, 0.25); diff --git a/packages/nightingale-distribution-track/tests/mockData/sample-1.json b/packages/nightingale-boxplot-track/tests/mockData/sample-1.json similarity index 100% rename from packages/nightingale-distribution-track/tests/mockData/sample-1.json rename to packages/nightingale-boxplot-track/tests/mockData/sample-1.json diff --git a/packages/nightingale-distribution-track/tests/nightingale-distribution-track.test.ts b/packages/nightingale-boxplot-track/tests/nightingale-distribution-track.test.ts similarity index 97% rename from packages/nightingale-distribution-track/tests/nightingale-distribution-track.test.ts rename to packages/nightingale-boxplot-track/tests/nightingale-distribution-track.test.ts index 978ad0851..9b393d275 100644 --- a/packages/nightingale-distribution-track/tests/nightingale-distribution-track.test.ts +++ b/packages/nightingale-boxplot-track/tests/nightingale-distribution-track.test.ts @@ -1,4 +1,4 @@ -import { getQuantile } from "../src/nightingale-distribution-track"; +import { getQuantile } from "../src/nightingale-boxplot-track"; describe("getQuantile", () => { diff --git a/packages/nightingale-distribution-track/tsconfig.json b/packages/nightingale-boxplot-track/tsconfig.json similarity index 100% rename from packages/nightingale-distribution-track/tsconfig.json rename to packages/nightingale-boxplot-track/tsconfig.json diff --git a/packages/nightingale-distribution-track/README.md b/packages/nightingale-distribution-track/README.md deleted file mode 100644 index 5bded2528..000000000 --- a/packages/nightingale-distribution-track/README.md +++ /dev/null @@ -1,7 +0,0 @@ -# nightingale-distribution-track - -[![Published on NPM](https://img.shields.io/npm/v/@nightingale-elements/nightingale-distribution-track.svg)](https://www.npmjs.com/package/@nightingale-elements/nightingale-distribution-track) - -The `nightingale-distribution-track` component ... - -TODO: diff --git a/packages/nightingale-distribution-track/src/index.ts b/packages/nightingale-distribution-track/src/index.ts deleted file mode 100644 index a32bca1a0..000000000 --- a/packages/nightingale-distribution-track/src/index.ts +++ /dev/null @@ -1,3 +0,0 @@ -import NightingaleDistributionTrack, { } from "./nightingale-distribution-track"; - -export { NightingaleDistributionTrack as default }; diff --git a/packages/nightingale-new-core/src/utils/bindEvents.ts b/packages/nightingale-new-core/src/utils/bindEvents.ts index ea11475b4..12c039462 100644 --- a/packages/nightingale-new-core/src/utils/bindEvents.ts +++ b/packages/nightingale-new-core/src/utils/bindEvents.ts @@ -20,10 +20,11 @@ type SequenceBaseData = { position: number; aa: string; }; -type DistributionData = { - type: 'distribution'; +type BoxplotData = { + type: 'boxplot'; position: number; dataset: { + index: number; name: string; color: string; }; @@ -45,7 +46,7 @@ type DistributionData = { type EventDetail = { eventType: EventType; coords: null | [number, number]; - feature?: FeatureData | SequenceBaseData | DistributionData | null; + feature?: FeatureData | SequenceBaseData | BoxplotData | null; target?: HTMLElement; highlight?: string; selectedId?: string | null; @@ -54,7 +55,7 @@ type EventDetail = { export function createEvent( type: EventType, - feature: FeatureData | SequenceBaseData | DistributionData | null = null, + feature: FeatureData | SequenceBaseData | BoxplotData | null = null, withHighlight = false, withId = false, start?: number, diff --git a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.mdx b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.mdx similarity index 90% rename from stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.mdx rename to stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.mdx index 3eec0d724..0cfc0d0d5 100644 --- a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.mdx +++ b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.mdx @@ -1,6 +1,6 @@ import { Meta, Description } from "@storybook/addon-docs"; -import Readme from "../../packages/nightingale-distribution-track/README.md"; +import Readme from "../../packages/nightingale-boxplot-track/README.md"; import ParentReadme from "../../packages/nightingale-new-core/src/nightingale-base-element.md"; import dimensionsReadme from "../../packages/nightingale-new-core/src/mixins/withDimensions/README.md"; import highlightReadme from "../../packages/nightingale-new-core/src/mixins/withHighlight/README.md"; @@ -10,7 +10,7 @@ import positionReadme from "../../packages/nightingale-new-core/src/mixins/withP import resizableReadme from "../../packages/nightingale-new-core/src/mixins/withResizable/README.md"; import zoomReadme from "../../packages/nightingale-new-core/src/mixins/withZoom/README.md"; - + {Readme} diff --git a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts similarity index 66% rename from stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts rename to stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts index 7448918cc..cdf8b2c8a 100644 --- a/stories/22.NightingaleDistributionTrack/NightingaleDistributionTrack.stories.ts +++ b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts @@ -1,11 +1,11 @@ import { type ArgTypes, Meta, Story } from "@storybook/web-components"; import { html } from "lit-html"; -import "../../packages/nightingale-distribution-track/src/index"; -import { type DistributionData, ZoomedOutRangeOptions } from "../../packages/nightingale-distribution-track/src/nightingale-distribution-track"; -import sampleDistributionData from "../../packages/nightingale-distribution-track/tests/mockData/sample-1.json"; +import "../../packages/nightingale-boxplot-track/src/index"; +import { type BoxplotData, ZoomedOutRangeOptions } from "../../packages/nightingale-boxplot-track/src/nightingale-boxplot-track"; +import sampleBoxplotData from "../../packages/nightingale-boxplot-track/tests/mockData/sample-1.json"; -export default { title: "Components/Tracks/Distribution Track" } as Meta; +export default { title: "Components/Tracks/Boxplot Track" } as Meta; const DefaultArgs = { @@ -39,8 +39,7 @@ const nDataRepeat = 82; const sampleSequence = "MALYGTHSHGLFKKLGIPGPTPLPFLGNILSYHKGFCMFDMECHKKYGKVWGFYDGQQPVLAITDPDMIKTVLVKECYSVFTNRRPFGPVGFMKSAISIA".repeat(nDataRepeat); -function prepareDistributionData(data: DistributionData[number]): DistributionData { - console.time('prepareDistributionData') +function prepareBoxplotData(data: { positions: { position: number, values: number[] }[] }): BoxplotData { // const positions = data.positions.slice(); const positions = data.positions.map(pos => ({ position: pos.position, values: pos.values.sort() })); const shift = data.positions.length; @@ -49,7 +48,6 @@ function prepareDistributionData(data: DistributionData[number]): DistributionDa positions.push({ position: pos.position + i * shift, values: pos.values }); } } - console.timeEnd('prepareDistributionData') return [ { @@ -86,23 +84,6 @@ function remove(arr: T[], ...indices: number[]) { return out; } -function prepareLinegraphData(data: DistributionData) { - console.time('prepareLinegraphData') - const values = data[0].positions.map(pos => ({ position: pos.position, value: pos.values.reduce((a, b) => a + b, 0) / pos.values.length })); - const max = values.reduce((old, v) => v.value > old ? v.value : old, 0); - - const chart1 = { - name: "chart1", - color: "#707070", - fill: "#808080", - lineCurve: "curveStep", - range: [0, max], - values: values, - }; - console.timeEnd('prepareLinegraphData') - return [chart1]; -} - function nightingaleNavigation(args: Args & { length: number }) { return html` @@ -142,32 +123,12 @@ function nightingaleSequence(args: Args & { length: number }) { `; } -function nightingaleLinegraphTrack(args: Args & { length: number, id: number }) { - return html` -
-
Linegraph
- - - -
`; -} - -function nightingaleDistributionTrack(args: Args & { length: number, id: number }) { +function nightingaleBoxplotTrack(args: Args & { length: number, id: number }) { return html`
-
Distribution
- Boxplot
+ - + `; } @@ -202,8 +163,7 @@ function makeStory(options: { length: number }): Story {
${nightingaleNavigation({ ...args, length: options.length })} ${nightingaleSequence({ ...args, length: options.length })} - - ${nightingaleDistributionTrack({ ...args, length: options.length, id: 0 })} + ${nightingaleBoxplotTrack({ ...args, length: options.length, id: 0 })}
`; @@ -212,23 +172,18 @@ function makeStory(options: { length: number }): Story { const story: Story = template.bind({}); story.args = { ...DefaultArgs }; story.argTypes = ArgumentTypes; - const distributionData = prepareDistributionData(sampleDistributionData as any); - // const linegraphData = prepareLinegraphData(distributionData); + const boxplotData = prepareBoxplotData(sampleBoxplotData as any); story.play = async () => { - // await customElements.whenDefined("nightingale-linegraph-track"); - // for (const track of document.getElementsByTagName("nightingale-linegraph-track")) { - // (track as any).data = linegraphData; - // } - await customElements.whenDefined("nightingale-distribution-track"); - for (const track of document.getElementsByTagName("nightingale-distribution-track")) { - (track as any).data = distributionData; + await customElements.whenDefined("nightingale-boxplot-track"); + for (const track of document.getElementsByTagName("nightingale-boxplot-track")) { + (track as any).data = boxplotData; } }; return story; } -export const LinegraphAndDistribution = makeStory({ +export const Boxplot = makeStory({ length: sampleSequence.length, }); From f081c8f04da1835f08835782eaf85d6698a76910 Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Tue, 23 Jun 2026 10:47:03 +0100 Subject: [PATCH 19/32] nightingale-distribution-track: move OptionalNumberAttributeConverter, EnumAttributeConverter to core --- .../src/nightingale-boxplot-track.ts | 34 ++-------- .../src/nightingale-conservation-track.ts | 10 +-- packages/nightingale-new-core/src/index.ts | 1 + .../src/utils/attribute-converters.ts | 65 +++++++++++++++++++ 4 files changed, 78 insertions(+), 32 deletions(-) create mode 100644 packages/nightingale-new-core/src/utils/attribute-converters.ts diff --git a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts index 9f1d152c9..72b6bc74d 100644 --- a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts +++ b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts @@ -2,6 +2,8 @@ import NightingaleElement, { BinarySearch, createEvent, customElementOnce, + EnumAttributeConverter, + OptionalNumberAttributeConverter, Refresher, Stamp, withCanvas, @@ -14,7 +16,7 @@ import NightingaleElement, { withZoom, } from "@nightingale-elements/nightingale-new-core"; import { BaseType, color, max, min, randomLcg, randomUniform, scaleLinear, select, Selection, TypedArray } from "d3"; -import { ComplexAttributeConverter, html, PropertyDeclaration, PropertyValues } from "lit"; +import { html, PropertyValues } from "lit"; import { property } from "lit/decorators.js"; import { Downsampler } from "./downsampling"; @@ -50,7 +52,6 @@ const OUTLIER_RADIUS = 2; const FG_BG_TRANSITION_BASE_WIDTHS = [4, 5] as const; /** Approximate width of a column in screen pixels, when showing downsampled data in "background" visualization. * (higher value means more responsive but lower-resolution visualization). */ -// const BG_DOWNSAMPLING_PIXELS_PER_COLUMN = 4; const BG_DOWNSAMPLING_PIXELS_PER_COLUMN = 1; function makeStrokeColor(dataColor: string): string | undefined { @@ -74,37 +75,13 @@ export interface BoxplotDataset { positions: BoxplotDatum[], } -/** Type for `NightingaleBoxplotTrack.data`` */ +/** Type for `NightingaleBoxplotTrack.data` */ export type BoxplotData = BoxplotDataset[]; -type AttributeConverter = NonNullable['converter']>; - -const OptionalNumberAttributeConverter: AttributeConverter = (str) => { - if (str) return Number(str); - return undefined; -}; - -function EnumAttributeConverter(allowedValues: readonly T[], defaultValue?: D): AttributeConverter { - const theDefault = defaultValue ?? allowedValues[0]; - - return (str) => { - if (!str) { - return theDefault; - } - if (allowedValues.includes(str as T)) { - return str as T; - } else { - console.warn(`Value '${str}' is not valid for attribute of type ${allowedValues.map(v => `'${v}'`).join(' | ')}. Falling back to default value ('${theDefault}').`); - return theDefault; - } - }; -} - export const ZoomedOutRangeOptions = ['extremes', 'whiskers', 'box', 'none'] as const; export type ZoomedOutRangeOption = typeof ZoomedOutRangeOptions[number]; -// TODO: rename to nightingale-boxplot-track @customElementOnce("nightingale-boxplot-track") export default class NightingaleBoxplotTrack extends withCanvas( withManager( @@ -147,7 +124,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( /** What kind of data should be shown as shaded range in zoomed-out visualization */ @property({ converter: EnumAttributeConverter(ZoomedOutRangeOptions, 'whiskers') }) - "zoomed-out-range": ZoomedOutRangeOption; // TODO: enum-type in other components? + "zoomed-out-range": ZoomedOutRangeOption; /** Turn on showing secondary highlights, which indicate selected subcolumn within a column (in case of multiple dataset). */ @property({ type: Boolean }) @@ -946,3 +923,4 @@ const NestedHighlight = { }; // TODO: axis ticks +// TODO: tooltips (example in storybook for PoC) diff --git a/packages/nightingale-conservation-track/src/nightingale-conservation-track.ts b/packages/nightingale-conservation-track/src/nightingale-conservation-track.ts index c2afb68bb..cba37b3a5 100644 --- a/packages/nightingale-conservation-track/src/nightingale-conservation-track.ts +++ b/packages/nightingale-conservation-track/src/nightingale-conservation-track.ts @@ -2,6 +2,7 @@ import NightingaleElement, { BinarySearch, createEvent, customElementOnce, + EnumAttributeConverter, Refresher, Stamp, withCanvas, @@ -80,9 +81,10 @@ interface YPositions { end: { [letter: string]: number[] }, } -type LetterOrder = "default" | "probability"; +const LetterOrders = ["default", "probability"] as const; +type LetterOrder = typeof LetterOrders[number]; -/** Type for `NightingaleConservationTrack.data`` */ +/** Type for `NightingaleConservationTrack.data` */ export interface SequenceConservationData { /** Sequence number for each position */ index: number[], @@ -104,8 +106,8 @@ export default class NightingaleConservationTrack extends withCanvas( ) ) { /** Order of amino acids within a column (top-to-bottom). default = fixed order based on amino acid groups, probability = on every position sort by descending probability */ - @property({ type: String }) - "letter-order": LetterOrder = "default"; + @property({ converter: EnumAttributeConverter(LetterOrders, "default") }) + "letter-order": LetterOrder; /** Font family for labels (can be a list of multiple font families separated by comma, like in CSS) */ @property({ type: String }) diff --git a/packages/nightingale-new-core/src/index.ts b/packages/nightingale-new-core/src/index.ts index 0631b9e5c..5ee8e94d6 100644 --- a/packages/nightingale-new-core/src/index.ts +++ b/packages/nightingale-new-core/src/index.ts @@ -7,6 +7,7 @@ export { default as withManager } from "./mixins/withManager/index"; export { default as withHighlight } from "./mixins/withHighlight/index"; export { default as withSVGHighlight } from "./mixins/withHighlight/SVG/index"; export { default as withZoom } from "./mixins/withZoom/index"; +export { EnumAttributeConverter, OptionalNumberAttributeConverter } from "./utils/attribute-converters"; export { default as bindEvents, createEvent } from "./utils/bindEvents"; export { contrastingColor, getColor } from "./utils/colors"; export { default as Region } from "./utils/Region"; diff --git a/packages/nightingale-new-core/src/utils/attribute-converters.ts b/packages/nightingale-new-core/src/utils/attribute-converters.ts new file mode 100644 index 000000000..6742b3e3b --- /dev/null +++ b/packages/nightingale-new-core/src/utils/attribute-converters.ts @@ -0,0 +1,65 @@ +import { ComplexAttributeConverter } from "lit"; + + +/** + * Attribute converter for attributes of type `number|undefined`. + * Attribute value empty string or `null` is interpreted as `undefined`; non-empty string is parsed as number. + * Example: + * + * ```ts + * class NightingaleExampleTrack { + * ;@property({ converter: OptionalNumberAttributeConverter }) + * "y-min"?: number; + * } + * ``` + * */ +export const OptionalNumberAttributeConverter: ComplexAttributeConverter = { + fromAttribute(str) { + if (!str) { // null or empty string + return undefined; + } else { + return Number(str); + } + }, + toAttribute(value) { + if (value === undefined) { + return ""; + } else { + return String(value); + } + }, +} + +/** + * Create an attribute converter for attribute that allows a fixed set of string values. + * Passing an invalid value to the attribute will result in a warning and using the default value instead. + * Example: + * + * ```ts + * const Weekdays = ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"] as const; + * type Weekday = typeof Weekdays[number]; + * + * class NightingaleExampleTrack { + * ;@property({ converter: EnumAttributeConverter(Weekdays, "Mon") }) + * day: Weekday; + * } + * ``` + * */ +export function EnumAttributeConverter(allowedValues: readonly T[], defaultValue: D): ComplexAttributeConverter { + return { + fromAttribute(str) { + if (!str) { // null or empty string + return defaultValue; + } + if (allowedValues.includes(str as T)) { // valid string + return str as T; + } else { // invalid string + console.warn(`Value "${str}" is not valid for attribute of type ${allowedValues.map(v => `"${v}"`).join(" | ")}. Falling back to default value ("${defaultValue}").`); + return defaultValue; + } + }, + toAttribute(value) { + return value; + }, + }; +} From 66f5c1b10a0bca272f04995df702456ed3d98ceb Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Tue, 23 Jun 2026 11:34:06 +0100 Subject: [PATCH 20/32] nightingale-boxplot-track: remove dead code --- .../src/nightingale-boxplot-track.ts | 30 +++++-------------- 1 file changed, 8 insertions(+), 22 deletions(-) diff --git a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts index 72b6bc74d..f2a248ac6 100644 --- a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts +++ b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts @@ -24,7 +24,6 @@ import { Downsampler } from "./downsampling"; const ATTRIBUTES_THAT_TRIGGER_REFRESH: string[] = [ "length", "width", "height", "margin-top", "margin-bottom", "margin-left", "margin-right", "margin-color", - "font-family", "min-font-size", "fade-font-size", "max-font-size", "y-min", "y-max", "hide-outliers", "zoomed-out-range", ] satisfies (keyof NightingaleBoxplotTrack)[]; const ATTRIBUTES_THAT_TRIGGER_DATA_RESET: string[] = [] satisfies (keyof NightingaleBoxplotTrack)[]; @@ -33,7 +32,6 @@ const ATTRIBUTES_THAT_TRIGGER_DATA_RESET: string[] = [] satisfies (keyof Nightin /** Line width for rectangle stroke */ const LINE_WIDTH = 1; /** Maximum line width relative to column width (overrides `LINE_WIDTH` when zoomed out too much) */ -// const MAX_REL_LINE_WIDTH = 0.2; const MAX_REL_LINE_WIDTH = 0.2; /** Default fill color for boxes (stroke color will be derived from this) */ @@ -94,22 +92,6 @@ export default class NightingaleBoxplotTrack extends withCanvas( ) ) ) { - /** Font family for labels (can be a list of multiple font families separated by comma, like in CSS) */ - @property({ type: String }) - "font-family": string = "Helvetica,sans-serif"; - - /** Font size below which labels are hidden */ - @property({ type: Number }) - "min-font-size": number = 6; - - /** Column width below which labels are shown with lower opacity */ - @property({ type: Number }) - "fade-font-size": number = 12; - - /** Maximum font size for labels */ - @property({ type: Number }) - "max-font-size": number = 24; - /** Bottom limit for Y-axis (default: minimum computed from data) */ @property({ converter: OptionalNumberAttributeConverter }) "y-min"?: number; @@ -383,28 +365,32 @@ export default class NightingaleBoxplotTrack extends withCanvas( let yRangeLow: ((j: number) => number) | undefined; let yRangeHigh: ((j: number) => number) | undefined; switch (this['zoomed-out-range']) { - case 'extremes': + case 'extremes': { const minimum = downsamplers.minimum.getDownsampledByScale(scale); const maximum = downsamplers.maximum.getDownsampledByScale(scale); yRangeLow = (j: number) => yScale(minimum[j]); yRangeHigh = (j: number) => yScale(maximum[j]); break; - case 'whiskers': + } + case 'whiskers': { const whiskerLow = downsamplers.whiskerLow.getDownsampledByScale(scale); const whiskerHigh = downsamplers.whiskerHigh.getDownsampledByScale(scale); yRangeLow = (j: number) => yScale(whiskerLow[j]); yRangeHigh = (j: number) => yScale(whiskerHigh[j]); break; - case 'box': + } + case 'box': { const boxLow = downsamplers.boxLow.getDownsampledByScale(scale); const boxHigh = downsamplers.boxHigh.getDownsampledByScale(scale); yRangeLow = (j: number) => yScale(boxLow[j]); yRangeHigh = (j: number) => yScale(boxHigh[j]); break; - case 'none': + } + case 'none': { yRangeLow = undefined; yRangeHigh = undefined; break; + } } const jStart = Math.max(0, Math.floor((start - offset) / exactScale)); From e21916732a2a96c68ec262bbbced70e62b32228e Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Tue, 23 Jun 2026 12:13:14 +0100 Subject: [PATCH 21/32] nightingale-boxplot-track: show-axis --- .../src/nightingale-boxplot-track.ts | 15 ++++++++++++--- .../NightingaleBoxplotTrack.stories.ts | 10 ++++++++-- 2 files changed, 20 insertions(+), 5 deletions(-) diff --git a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts index f2a248ac6..e38ae7404 100644 --- a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts +++ b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts @@ -15,7 +15,7 @@ import NightingaleElement, { withResizable, withZoom, } from "@nightingale-elements/nightingale-new-core"; -import { BaseType, color, max, min, randomLcg, randomUniform, scaleLinear, select, Selection, TypedArray } from "d3"; +import { axisLeft, BaseType, color, max, min, randomLcg, randomUniform, scaleLinear, select, Selection, TypedArray } from "d3"; import { html, PropertyValues } from "lit"; import { property } from "lit/decorators.js"; import { Downsampler } from "./downsampling"; @@ -24,7 +24,7 @@ import { Downsampler } from "./downsampling"; const ATTRIBUTES_THAT_TRIGGER_REFRESH: string[] = [ "length", "width", "height", "margin-top", "margin-bottom", "margin-left", "margin-right", "margin-color", - "y-min", "y-max", "hide-outliers", "zoomed-out-range", + "y-min", "y-max", "show-axis", "hide-outliers", "zoomed-out-range", ] satisfies (keyof NightingaleBoxplotTrack)[]; const ATTRIBUTES_THAT_TRIGGER_DATA_RESET: string[] = [] satisfies (keyof NightingaleBoxplotTrack)[]; @@ -112,6 +112,10 @@ export default class NightingaleBoxplotTrack extends withCanvas( @property({ type: Boolean }) "show-nested-highlights"?: boolean; + /** Turn on vertical axis. */ + @property({ type: Boolean }) + "show-axis"?: boolean; + /** Position of secondary highlight in from "position/iDataset", or "" if none. */ @property({ type: String, reflect: true }) private "nested-highlight": string = ""; @@ -166,6 +170,12 @@ export default class NightingaleBoxplotTrack extends withCanvas( this.bindEvents(this.svg); this.highlighted = this.svg.append("g").attr("class", "highlighted"); this.nestedHighlighted = this.svg.append("g").attr("class", "highlighted-datapoint"); + if (this["show-axis"]) { + const yScale = scaleLinear(this.getYLimits(), [this.height - this["margin-bottom"], this["margin-top"]]); + this.svg.append("g").attr("class", "y-axis") + .attr("transform", `translate(${this["margin-left"]},0)`) + .call(axisLeft(yScale)); + } } } @@ -908,5 +918,4 @@ const NestedHighlight = { SEPARATOR: '/', }; -// TODO: axis ticks // TODO: tooltips (example in storybook for PoC) diff --git a/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts index cdf8b2c8a..1d1375d41 100644 --- a/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts +++ b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts @@ -14,10 +14,12 @@ const DefaultArgs = { "highlight-event": "onmouseover", "highlight-color": "#EB3BFF22", "margin-color": "#ffffffdd", + "margin-left": 30, "y-min": 0 as number | undefined, "y-max": undefined as number | undefined, - "hide-outliers": false, + "show-axis": true, "show-nested-highlights": true, + "hide-outliers": false, "zoomed-out-range": 'whiskers', }; type Args = typeof DefaultArgs; @@ -96,6 +98,7 @@ function nightingaleNavigation(args: Args & { length: number }) { length="${args["length"]}" highlight-color=${args["highlight-color"]} margin-color=${args["margin-color"]} + margin-left=${args["margin-left"]} show-highlight display-end="100" > @@ -117,6 +120,7 @@ function nightingaleSequence(args: Args & { length: number }) { highlight-event="${args["highlight-event"]}" highlight-color=${args["highlight-color"]} margin-color=${args["margin-color"]} + margin-left=${args["margin-left"]} use-ctrl-to-zoom > @@ -137,11 +141,13 @@ function nightingaleBoxplotTrack(args: Args & { length: number, id: number }) { margin-color=${args["margin-color"]} margin-top=10 margin-bottom=10 + margin-left=${args["margin-left"]} use-ctrl-to-zoom y-min=${args["y-min"]} y-max=${args["y-max"]} - ?hide-outliers=${args["hide-outliers"]} + ?show-axis=${args["show-axis"]} ?show-nested-highlights=${args["show-nested-highlights"]} + ?hide-outliers=${args["hide-outliers"]} zoomed-out-range=${args["zoomed-out-range"]} > From ba5ccc09ee641160bf9c186cd1afe223e28a8664 Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Wed, 24 Jun 2026 14:43:22 +0100 Subject: [PATCH 22/32] Canvas tracks - fix highlight rendered over margin --- .../src/nightingale-boxplot-track.ts | 42 ++++++++----------- .../src/nightingale-conservation-track.ts | 35 +++++----------- .../src/nightingale-track-canvas.ts | 18 ++++---- .../NightingaleTrackCanvas.stories.ts | 4 +- .../NightingaleBoxplotTrack.stories.ts | 1 + 5 files changed, 38 insertions(+), 62 deletions(-) diff --git a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts index e38ae7404..73440c64f 100644 --- a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts +++ b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts @@ -122,8 +122,9 @@ export default class NightingaleBoxplotTrack extends withCanvas( #data?: BoxplotData; private preprocessedData?: PreprocessedData; - protected highlighted?: Selection; - protected nestedHighlighted?: Selection; + protected svgHighlights?: Selection; + protected svgNestedHighlights?: Selection; + protected svgMargins?: Selection; override connectedCallback() { @@ -168,8 +169,9 @@ export default class NightingaleBoxplotTrack extends withCanvas( .attr("height", this.height); if (this.svg) { // this check is necessary because `svg` setter does not always set this.bindEvents(this.svg); - this.highlighted = this.svg.append("g").attr("class", "highlighted"); - this.nestedHighlighted = this.svg.append("g").attr("class", "highlighted-datapoint"); + this.svgHighlights = this.svg.append("g").attr("class", "highlighted"); + this.svgNestedHighlights = this.svg.append("g").attr("class", "nested-highlighted"); + this.svgMargins = this.svg.append("g").attr("class", "margin"); if (this["show-axis"]) { const yScale = scaleLinear(this.getYLimits(), [this.height - this["margin-bottom"], this["margin-top"]]); this.svg.append("g").attr("class", "y-axis") @@ -183,6 +185,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( this.requestDraw(); this.updateHighlight(); this.updateNestedHighlight(); + this.updateMargins(); } private readonly _drawStamp = new Stamp(() => { @@ -214,7 +217,6 @@ export default class NightingaleBoxplotTrack extends withCanvas( if (!this.canvasCtx) return; this.clearCanvas(this.canvasCtx); this.drawData(this.canvasCtx); - this.drawMargins(this.canvasCtx); } private getOffscreenCanvas(): [canvas: HTMLCanvasElement, canvasContext?: CanvasRenderingContext2D] { @@ -429,22 +431,6 @@ export default class NightingaleBoxplotTrack extends withCanvas( } } - private drawMargins(ctx: CanvasRenderingContext2D) { - const canvasWidth = ctx.canvas.width; - const canvasHeight = ctx.canvas.height; - const marginLeft = this["margin-left"] * this.canvasScale; - const marginRight = this["margin-right"] * this.canvasScale; - const marginTop = this["margin-top"] * this.canvasScale; - const marginBottom = this["margin-bottom"] * this.canvasScale; - - ctx.globalAlpha = 1; - ctx.fillStyle = this["margin-color"]; - ctx.fillRect(0, 0, marginLeft, canvasHeight); - ctx.fillRect(canvasWidth - marginRight, 0, marginRight, canvasHeight); - ctx.fillRect(marginLeft, 0, canvasWidth - marginLeft - marginRight, marginTop); - ctx.fillRect(marginLeft, canvasHeight - marginBottom, canvasWidth - marginLeft - marginRight, marginBottom); - } - private getDrawingMeasurements() { const canvasScale = this.canvasScale; const xBaseWidthInCss = this.getSingleBaseWidth(); @@ -509,8 +495,8 @@ export default class NightingaleBoxplotTrack extends withCanvas( } protected updateHighlight() { - if (!this.highlighted) return; - const highlights = this.highlighted + if (!this.svgHighlights) return; + const highlights = this.svgHighlights .selectAll("rect") .data(this.highlightedRegion.segments); @@ -528,12 +514,12 @@ export default class NightingaleBoxplotTrack extends withCanvas( } protected updateNestedHighlight() { - if (!this.nestedHighlighted) return; + if (!this.svgNestedHighlights) return; const nestedHighlightLocation = NestedHighlight.parse(this["nested-highlight"]); const nDatasets = this.preprocessedData?.datasets.length ?? 1; const showNestedHighlight = this["show-nested-highlights"] && nDatasets > 1 && nestedHighlightLocation !== undefined; - const highlights = this.nestedHighlighted + const highlights = this.svgNestedHighlights .selectAll("rect") .data(showNestedHighlight ? [nestedHighlightLocation] : []); @@ -556,6 +542,10 @@ export default class NightingaleBoxplotTrack extends withCanvas( highlights.exit().remove(); } + protected updateMargins() { + this.renderMarginOnGroup(this.svgMargins); + } + override zoomRefreshed() { super.zoomRefreshed(); if (this.getWidthWithMargins() > 0) this.refresh(); @@ -919,3 +909,5 @@ const NestedHighlight = { }; // TODO: tooltips (example in storybook for PoC) +// - combined tooltip for all datasets at the same position (table) +// TODO: test on new API once available diff --git a/packages/nightingale-conservation-track/src/nightingale-conservation-track.ts b/packages/nightingale-conservation-track/src/nightingale-conservation-track.ts index cba37b3a5..cb17ec1be 100644 --- a/packages/nightingale-conservation-track/src/nightingale-conservation-track.ts +++ b/packages/nightingale-conservation-track/src/nightingale-conservation-track.ts @@ -128,7 +128,8 @@ export default class NightingaleConservationTrack extends withCanvas( #data?: SequenceConservationData; private yPositions?: YPositions; - protected highlighted?: Selection; + protected svgHighlights?: Selection; + protected svgMargins?: Selection; override connectedCallback() { @@ -176,13 +177,15 @@ export default class NightingaleConservationTrack extends withCanvas( .attr("height", this.height); if (this.svg) { // this check is necessary because `svg` setter does not always set this.bindEvents(this.svg); - this.highlighted = this.svg.append("g").attr("class", "highlighted"); + this.svgHighlights = this.svg.append("g").attr("class", "highlighted"); + this.svgMargins = this.svg.append("g").attr("class", "margin"); } } refresh() { this.requestDraw(); this.updateHighlight(); + this.updateMargins(); } private readonly _drawStamp = new Stamp(() => { @@ -213,7 +216,6 @@ export default class NightingaleConservationTrack extends withCanvas( this.adjustCanvasCtxLogicalSize(); this.clearCanvas(); this.drawColumns(); - this.drawMargins(); } private clearCanvas() { @@ -274,25 +276,6 @@ export default class NightingaleConservationTrack extends withCanvas( } } - private drawMargins() { - const ctx = this.canvasCtx; - if (!ctx) return; - - const canvasWidth = ctx.canvas.width; - const canvasHeight = ctx.canvas.height; - const marginLeft = this["margin-left"] * this.canvasScale; - const marginRight = this["margin-right"] * this.canvasScale; - const marginTop = this["margin-top"] * this.canvasScale; - const marginBottom = this["margin-bottom"] * this.canvasScale; - - ctx.globalAlpha = 1; - ctx.fillStyle = this["margin-color"]; - ctx.fillRect(0, 0, marginLeft, canvasHeight); - ctx.fillRect(canvasWidth - marginRight, 0, marginRight, canvasHeight); - ctx.fillRect(marginLeft, 0, canvasWidth - marginLeft - marginRight, marginTop); - ctx.fillRect(marginLeft, canvasHeight - marginBottom, canvasWidth - marginLeft - marginRight, marginBottom); - } - private getFontOpacity(baseWidthInCss: number): number { if (baseWidthInCss < this["min-font-size"]) { return 0; @@ -304,8 +287,8 @@ export default class NightingaleConservationTrack extends withCanvas( } protected updateHighlight() { - if (!this.highlighted) return; - const highlights = this.highlighted + if (!this.svgHighlights) return; + const highlights = this.svgHighlights .selectAll("rect") .data(this.highlightedRegion.segments); @@ -322,6 +305,10 @@ export default class NightingaleConservationTrack extends withCanvas( highlights.exit().remove(); } + protected updateMargins() { + this.renderMarginOnGroup(this.svgMargins); + } + override zoomRefreshed() { super.zoomRefreshed(); if (this.getWidthWithMargins() > 0) this.refresh(); diff --git a/packages/nightingale-track-canvas/src/nightingale-track-canvas.ts b/packages/nightingale-track-canvas/src/nightingale-track-canvas.ts index 689b0ba47..f86fa6453 100644 --- a/packages/nightingale-track-canvas/src/nightingale-track-canvas.ts +++ b/packages/nightingale-track-canvas/src/nightingale-track-canvas.ts @@ -14,6 +14,8 @@ export default class NightingaleTrackCanvas extends withCanvas(NightingaleTrack) /** Feature fragments, stored in a data structure for fast range queries */ private fragmentCollection?: RangeCollection; + protected svgMargins?: Selection; + protected override createTrack() { if (this.svg) { this.svg.selectAll("g").remove(); @@ -26,12 +28,14 @@ export default class NightingaleTrackCanvas extends withCanvas(NightingaleTrack) if (this.svg) { // this check is necessary because `svg` setter does not always set this.bindEvents(this.svg); this.highlighted = this.svg.append("g").attr("class", "highlighted"); + this.svgMargins = this.svg.append("g").attr("class", "margin"); } } override refresh() { super.refresh(); this.requestDraw(); + this.updateMargins(); } override render() { @@ -135,18 +139,10 @@ export default class NightingaleTrackCanvas extends withCanvas(NightingaleTrack) } } } + } - // Draw margins - ctx.globalAlpha = 1; - ctx.fillStyle = this["margin-color"]; - const marginLeft = this["margin-left"] * scale; - const marginRight = this["margin-right"] * scale; - const marginTop = this["margin-top"] * scale; - const marginBottom = this["margin-bottom"] * scale; - ctx.fillRect(0, 0, marginLeft, canvasHeight); - ctx.fillRect(canvasWidth - marginRight, 0, marginRight, canvasHeight); - ctx.fillRect(marginLeft, 0, canvasWidth - marginLeft - marginRight, marginTop); - ctx.fillRect(marginLeft, canvasHeight - marginBottom, canvasWidth - marginLeft - marginRight, marginBottom); + protected updateMargins() { + this.renderMarginOnGroup(this.svgMargins); } private _unknownShapeWarningPrinted = new Set(); diff --git a/stories/18.NightingaleTrackCanvas/NightingaleTrackCanvas.stories.ts b/stories/18.NightingaleTrackCanvas/NightingaleTrackCanvas.stories.ts index 4e178eb3d..c34b0cf71 100644 --- a/stories/18.NightingaleTrackCanvas/NightingaleTrackCanvas.stories.ts +++ b/stories/18.NightingaleTrackCanvas/NightingaleTrackCanvas.stories.ts @@ -13,8 +13,8 @@ const DefaultArgs = { "highlight-event": "onmouseover", // "onmouseover"|"onclick" "highlight-color": "#EB3BFF22", "margin-color": "#ffffffdd", // "transparent" - "margin-left": "10", - "margin-right": "10", + "margin-left": 10, + "margin-right": 10, "layout": "non-overlapping", // "default"|"non-overlapping" }; type Args = typeof DefaultArgs; diff --git a/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts index 1d1375d41..d4b82f1ce 100644 --- a/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts +++ b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts @@ -184,6 +184,7 @@ function makeStory(options: { length: number }): Story { await customElements.whenDefined("nightingale-boxplot-track"); for (const track of document.getElementsByTagName("nightingale-boxplot-track")) { (track as any).data = boxplotData; + track.addEventListener('change', (e) => console.log((e as CustomEvent).detail)) } }; return story; From c9e2386999ef18ca6ca65711e47e76cb94aa0d09 Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Wed, 24 Jun 2026 15:47:40 +0100 Subject: [PATCH 23/32] nightingale-boxplot-track: inclue info about all datasets in event data --- .../src/nightingale-boxplot-track.ts | 21 ++++------ .../src/utils/bindEvents.ts | 41 ++++++++++--------- .../NightingaleBoxplotTrack.stories.ts | 34 +++++++++++---- 3 files changed, 56 insertions(+), 40 deletions(-) diff --git a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts index 73440c64f..6a241f07e 100644 --- a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts +++ b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts @@ -593,7 +593,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( const withHighlight = this.getAttribute("highlight-event") === "onclick"; if (withHighlight) { - const iDataset = pointed.feature?.dataset.index; + const iDataset = pointed.feature?.datasetIndex; this["nested-highlight"] = NestedHighlight.format(iDataset !== undefined ? [pointed.position, iDataset] : undefined); } @@ -619,7 +619,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( const withHighlight = this.getAttribute("highlight-event") === "onmouseover"; if (withHighlight) { - const iDataset = pointed.feature?.dataset.index; + const iDataset = pointed.feature?.datasetIndex; this["nested-highlight"] = NestedHighlight.format(iDataset !== undefined ? [pointed.position, iDataset] : undefined); } @@ -665,22 +665,15 @@ export default class NightingaleBoxplotTrack extends withCanvas( const nDatasets = this.preprocessedData?.datasets.length ?? 1; const iDataset = Math.max(0, Math.min(nDatasets - 1, Math.floor(fractionalWithinColumn * nDatasets))); - const dataset = this.preprocessedData?.datasets[iDataset]; - const datum = dataset?.positions[position]; - if (!datum) { - return { position, feature: undefined }; - } - type EventFeatureData = Parameters[1]; const feature: EventFeatureData = { type: 'boxplot', position: position, - dataset: { - index: iDataset, - name: dataset.name, - color: dataset.color ?? DEFAULT_DATA_COLOR, - }, - datum: datum, + data: this.preprocessedData?.datasets.map(dataset => ({ + dataset: { name: dataset.name, color: dataset.color ?? DEFAULT_DATA_COLOR }, + datum: dataset?.positions[position], + })) ?? [], + datasetIndex: iDataset, }; return { position, feature }; } diff --git a/packages/nightingale-new-core/src/utils/bindEvents.ts b/packages/nightingale-new-core/src/utils/bindEvents.ts index 12c039462..d304b1d66 100644 --- a/packages/nightingale-new-core/src/utils/bindEvents.ts +++ b/packages/nightingale-new-core/src/utils/bindEvents.ts @@ -21,26 +21,29 @@ type SequenceBaseData = { aa: string; }; type BoxplotData = { - type: 'boxplot'; + type: "boxplot"; position: number; - dataset: { - index: number; - name: string; - color: string; - }; - datum: { - position: number; - values: Float32Array; - median: number; - boxLow: number; - boxHigh: number; - whiskerLow: number; - whiskerHigh: number; - minimum: number; - maximum: number; - outliersLow: Float32Array; - outliersHigh: Float32Array; - }; + data: { + dataset: { + name: string; + color: string; + }; + datum?: { + position: number; + values: Float32Array; + median: number; + boxLow: number; + boxHigh: number; + whiskerLow: number; + whiskerHigh: number; + minimum: number; + maximum: number; + outliersLow: Float32Array; + outliersHigh: Float32Array; + }; + }[]; + /** Index into `data`, indicates which dataset is being pointed at */ + datasetIndex: number; }; type EventDetail = { diff --git a/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts index d4b82f1ce..af0e23b50 100644 --- a/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts +++ b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts @@ -1,3 +1,4 @@ +import { type createEvent } from "@nightingale-elements/nightingale-new-core"; import { type ArgTypes, Meta, Story } from "@storybook/web-components"; import { html } from "lit-html"; import "../../packages/nightingale-boxplot-track/src/index"; @@ -69,12 +70,12 @@ function prepareBoxplotData(data: { positions: { position: number, values: numbe // positions: positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), positions: remove(positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), 1, 7), // DEBUG }, - { - name: 'Data3', - color: '#00aa44', - // positions: positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), - positions: remove(positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.93) })), 1, 7), // DEBUG - }, + // { + // name: 'Data3', + // color: '#00aa44', + // // positions: positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), + // positions: remove(positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.93) })), 1, 7), // DEBUG + // }, ]; } @@ -184,7 +185,26 @@ function makeStory(options: { length: number }): Story { await customElements.whenDefined("nightingale-boxplot-track"); for (const track of document.getElementsByTagName("nightingale-boxplot-track")) { (track as any).data = boxplotData; - track.addEventListener('change', (e) => console.log((e as CustomEvent).detail)) + track.addEventListener('change', (e) => { + const detail = (e as CustomEvent).detail; + if (!('eventType' in detail)) return; + if (detail.eventType !== 'click') return; + const fmtInt = (x: number | undefined) => x?.toFixed(0).padStart(7) ?? ' '; + const fmtFloat = (x: number | undefined) => x?.toFixed(2).padStart(7) ?? ' '; + type EventFeatureData = Parameters[1]; + const feature = detail.feature as EventFeatureData; + if (feature && 'type' in feature && feature.type === 'boxplot') { + console.log('='.repeat(40)) + console.log(['Dataset ', ...feature.data.map(d => d.dataset.name)].join(' | ')) + console.log(['Color ', ...feature.data.map(d => d.dataset.color)].join(' | ')) + console.log(['#Datapoints', ...feature.data.map(d => fmtInt(d.datum?.values.length))].join(' | ')) + console.log(['#Outliers ', ...feature.data.map(d => fmtInt(d.datum?.outliersHigh && d.datum?.outliersLow ? d.datum.outliersHigh.length + d.datum.outliersLow.length : undefined))].join(' | ')) + console.log(['Maximum ', ...feature.data.map(d => fmtFloat(d.datum?.maximum))].join(' | ')) + console.log(['Median ', ...feature.data.map(d => fmtFloat(d.datum?.median))].join(' | ')) + console.log(['Minimum ', ...feature.data.map(d => fmtFloat(d.datum?.minimum))].join(' | ')) + console.log([' ', ...feature.data.map((d, i) => i === feature.datasetIndex ? '-------' : ' ')].join(' ')) + } + }) } }; return story; From 50c0dd3832e672c768b491fe0118c7d05c1048e6 Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Fri, 26 Jun 2026 10:06:06 +0100 Subject: [PATCH 24/32] nightingale-boxplot-track: tooltip demo --- .../src/nightingale-boxplot-track.ts | 2 - .../NightingaleBoxplotTrack.stories.ts | 62 ++++++++++++------- 2 files changed, 41 insertions(+), 23 deletions(-) diff --git a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts index 6a241f07e..49acaf66a 100644 --- a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts +++ b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts @@ -901,6 +901,4 @@ const NestedHighlight = { SEPARATOR: '/', }; -// TODO: tooltips (example in storybook for PoC) -// - combined tooltip for all datasets at the same position (table) // TODO: test on new API once available diff --git a/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts index af0e23b50..66cb939bd 100644 --- a/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts +++ b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts @@ -2,6 +2,7 @@ import { type createEvent } from "@nightingale-elements/nightingale-new-core"; import { type ArgTypes, Meta, Story } from "@storybook/web-components"; import { html } from "lit-html"; import "../../packages/nightingale-boxplot-track/src/index"; +import NightingaleBoxplotTrack from "../../packages/nightingale-boxplot-track/src/nightingale-boxplot-track"; import { type BoxplotData, ZoomedOutRangeOptions } from "../../packages/nightingale-boxplot-track/src/nightingale-boxplot-track"; import sampleBoxplotData from "../../packages/nightingale-boxplot-track/tests/mockData/sample-1.json"; @@ -22,6 +23,7 @@ const DefaultArgs = { "show-nested-highlights": true, "hide-outliers": false, "zoomed-out-range": 'whiskers', + "tooltips": true, }; type Args = typeof DefaultArgs; @@ -155,9 +157,46 @@ function nightingaleBoxplotTrack(args: Args & { length: number, id: number }) { `; } +/** This is a demonstration of how to use CustomEvents on the `nightingale-boxplot-track` component. Tooltips are not a part of the component. */ +function handleTooltip(event: CustomEvent, args: Args) { + if (event.detail.eventType !== 'mouseover' && event.detail.eventType !== 'mouseout') return; + + type EventFeatureData = Parameters[1]; + const feature: EventFeatureData = event.detail.feature; + let tooltipDiv = document.getElementById('boxplot-tooltip'); + if (args.tooltips && feature && 'type' in feature && feature.type === 'boxplot') { + // Show tooltip + if (!tooltipDiv) { + tooltipDiv = document.createElement('div'); + tooltipDiv.id = 'boxplot-tooltip'; + Object.assign(tooltipDiv.style, { position: 'fixed', background: 'white', border: '1px solid #ccc', padding: '6px', boxShadow: '0 2px 6px rgba(0,0,0,0.2)', zIndex: '666', fontFamily: 'sans-serif', fontSize: '12px' }); + document.body.appendChild(tooltipDiv); + } + const rows = [ + ['', ...feature.data.map(d => `${d.dataset.name}`)], + ['nDatapoints', ...feature.data.map(d => d.datum?.values.length ?? '-')], + ['nOutliers', ...feature.data.map(d => d.datum?.outliersHigh && d.datum?.outliersLow ? d.datum.outliersHigh.length + d.datum.outliersLow.length : '-')], + ['Max', ...feature.data.map(d => d.datum?.maximum.toFixed(2) ?? '-')], + ['Median', ...feature.data.map(d => d.datum?.median.toFixed(2) ?? '-')], + ['Min', ...feature.data.map(d => d.datum?.minimum.toFixed(2) ?? '-')], + ]; + const rowsHtml = rows.map((row) => `${row.map((cell, index) => `${cell}`).join('')}`).join(''); + tooltipDiv.innerHTML = `${rowsHtml}
`; + const mouseEvent: MouseEvent | undefined = event.detail.parentEvent; + tooltipDiv.style.left = `${(mouseEvent?.clientX ?? 0) + 10}px`; + tooltipDiv.style.top = `${(mouseEvent?.clientY ?? 0) + 10}px`; + } else { + // Hide tooltip + tooltipDiv?.remove(); + } +} + function makeStory(options: { length: number }): Story { + let currentArgs: Args = { ...DefaultArgs }; + const template: Story = (args: Args) => { + currentArgs = args; return html` Use Ctrl+scroll to zoom. @@ -184,27 +223,8 @@ function makeStory(options: { length: number }): Story { story.play = async () => { await customElements.whenDefined("nightingale-boxplot-track"); for (const track of document.getElementsByTagName("nightingale-boxplot-track")) { - (track as any).data = boxplotData; - track.addEventListener('change', (e) => { - const detail = (e as CustomEvent).detail; - if (!('eventType' in detail)) return; - if (detail.eventType !== 'click') return; - const fmtInt = (x: number | undefined) => x?.toFixed(0).padStart(7) ?? ' '; - const fmtFloat = (x: number | undefined) => x?.toFixed(2).padStart(7) ?? ' '; - type EventFeatureData = Parameters[1]; - const feature = detail.feature as EventFeatureData; - if (feature && 'type' in feature && feature.type === 'boxplot') { - console.log('='.repeat(40)) - console.log(['Dataset ', ...feature.data.map(d => d.dataset.name)].join(' | ')) - console.log(['Color ', ...feature.data.map(d => d.dataset.color)].join(' | ')) - console.log(['#Datapoints', ...feature.data.map(d => fmtInt(d.datum?.values.length))].join(' | ')) - console.log(['#Outliers ', ...feature.data.map(d => fmtInt(d.datum?.outliersHigh && d.datum?.outliersLow ? d.datum.outliersHigh.length + d.datum.outliersLow.length : undefined))].join(' | ')) - console.log(['Maximum ', ...feature.data.map(d => fmtFloat(d.datum?.maximum))].join(' | ')) - console.log(['Median ', ...feature.data.map(d => fmtFloat(d.datum?.median))].join(' | ')) - console.log(['Minimum ', ...feature.data.map(d => fmtFloat(d.datum?.minimum))].join(' | ')) - console.log([' ', ...feature.data.map((d, i) => i === feature.datasetIndex ? '-------' : ' ')].join(' ')) - } - }) + (track as NightingaleBoxplotTrack).data = boxplotData; + track.addEventListener('change', event => handleTooltip(event as CustomEvent, currentArgs)); } }; return story; From ceccdb36285e77e28d964797e69ac742e7df8dca Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Fri, 26 Jun 2026 19:16:16 +0100 Subject: [PATCH 25/32] nightingale-boxplot-track: convert some consts to attibutes --- .../src/nightingale-boxplot-track.ts | 94 ++++++++++++------- .../NightingaleBoxplotTrack.stories.ts | 25 ++++- 2 files changed, 80 insertions(+), 39 deletions(-) diff --git a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts index 49acaf66a..b936099d0 100644 --- a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts +++ b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts @@ -21,10 +21,12 @@ import { property } from "lit/decorators.js"; import { Downsampler } from "./downsampling"; +// TODO: track via decorators? const ATTRIBUTES_THAT_TRIGGER_REFRESH: string[] = [ "length", "width", "height", "margin-top", "margin-bottom", "margin-left", "margin-right", "margin-color", - "y-min", "y-max", "show-axis", "hide-outliers", "zoomed-out-range", + "y-min", "y-max", "show-axis", "zoomed-out-range", + "column-gap", "box-gap", "whisker-width", "outlier-jitter-width", "outlier-radius", "zoom-transition-range", ] satisfies (keyof NightingaleBoxplotTrack)[]; const ATTRIBUTES_THAT_TRIGGER_DATA_RESET: string[] = [] satisfies (keyof NightingaleBoxplotTrack)[]; @@ -36,18 +38,7 @@ const MAX_REL_LINE_WIDTH = 0.2; /** Default fill color for boxes (stroke color will be derived from this) */ const DEFAULT_DATA_COLOR = "#cccccc"; -/** Gap between columns relative to base width */ -const COLUMN_GAP = 0.2; -/** Gap between boxes within a column relative to box width */ -const BOX_GAP = 0.1; -/** Whisker width relative to box width */ -const WHISKER_REL_WIDTH = 0.6; -/** Outlier jitter width relative to box width */ -const JITTER_REL_WIDTH = 0.4; -/** Radius for the circles representing outliers */ -const OUTLIER_RADIUS = 2; -/** Column widths in CSS pixels, between which transition from "background" to "foreground" visualization happens */ -const FG_BG_TRANSITION_BASE_WIDTHS = [4, 5] as const; + /** Approximate width of a column in screen pixels, when showing downsampled data in "background" visualization. * (higher value means more responsive but lower-resolution visualization). */ const BG_DOWNSAMPLING_PIXELS_PER_COLUMN = 1; @@ -100,10 +91,6 @@ export default class NightingaleBoxplotTrack extends withCanvas( @property({ converter: OptionalNumberAttributeConverter }) "y-max"?: number; - /** Turns off rendering of outliers */ - @property({ type: Boolean }) - "hide-outliers"?: boolean; - /** What kind of data should be shown as shaded range in zoomed-out visualization */ @property({ converter: EnumAttributeConverter(ZoomedOutRangeOptions, 'whiskers') }) "zoomed-out-range": ZoomedOutRangeOption; @@ -117,9 +104,41 @@ export default class NightingaleBoxplotTrack extends withCanvas( "show-axis"?: boolean; /** Position of secondary highlight in from "position/iDataset", or "" if none. */ - @property({ type: String, reflect: true }) + @property({ type: String, reflect: true }) // not using attribute converter here, because change detection would not work correctly private "nested-highlight": string = ""; + /** Width of the gap between displayed columns relative to the width of one sequence position (allowed range: 0-1, default: 0.2) */ + @property({ type: Number }) + "column-gap": number = 0.2; + + /** Width of the gap between boxes within a column relative to the column width (allowed range: 0-1, default: 0.1) */ + @property({ type: Number }) + "box-gap": number = 0.1; + + /** Whisker width relative to the box width (allowed range: 0-1, default: 0.6) */ + @property({ type: Number }) + "whisker-width": number = 0.6; + + /** Width of random noise (jitter) to be added to the X-position of the outliers, relative to the box width (allowed range: 0-1, default: 0.4) */ + @property({ type: Number }) + "outlier-jitter-width": number = 0.4; + + /** Radius for the circles representing outliers, in CSS pixels (default: 2). Set to 0 to supress outlier rendering. */ + @property({ type: Number }) + "outlier-radius": number = 2; + + /** Column width (in CSS pixels), where the transition from zoomed-out simplified visualization to zoomed-in boxplot visualization happens. + * Can be either one number (for sharp transition) or a hyphen-separated range. + * If there are multiple datasets, the width will be divided by the number of datasets. + * Use "0" to always show zoomed-in visualization (or preferrably "0.5-1" to avoid perfomance issues). + * Use "Infinity" to always show zoomed-out visualization. + * (default: "4-5") + * */ + @property({ type: String }) + "zoom-transition-range": string = '4-5'; + + // TODO: continue here replacing consts by above props + #data?: BoxplotData; private preprocessedData?: PreprocessedData; protected svgHighlights?: Selection; @@ -278,12 +297,12 @@ export default class NightingaleBoxplotTrack extends withCanvas( const fillColor = dataColor; const strokeColor = makeStrokeColor(dataColor)!; - const xBoxOffset = xColumnLeft + (iDataset + 0.5 * BOX_GAP) * xColumnWidth / nDatasets; - const xBoxWidth = (1 - BOX_GAP) * xColumnWidth / nDatasets; + const xBoxOffset = xColumnLeft + (iDataset + 0.5 * this["box-gap"]) * xColumnWidth / nDatasets; + const xBoxWidth = (1 - this["box-gap"]) * xColumnWidth / nDatasets; const xCenter = xBoxOffset + 0.5 * xBoxWidth; - const xWhiskerLeft = xCenter - 0.5 * WHISKER_REL_WIDTH * xBoxWidth; - const xWhiskerRight = xCenter + 0.5 * WHISKER_REL_WIDTH * xBoxWidth; - const xJitterHalfwidth = 0.5 * JITTER_REL_WIDTH * xBoxWidth; + const xWhiskerLeft = xCenter - 0.5 * this["whisker-width"] * xBoxWidth; + const xWhiskerRight = xCenter + 0.5 * this["whisker-width"] * xBoxWidth; + const xJitterHalfwidth = 0.5 * this["outlier-jitter-width"] * xBoxWidth; for (let i = start; i < stop; i++) { const datum = dataset.positions[i]; @@ -322,7 +341,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( ctx.strokeRect(x + xBoxOffset, yMedian - yMedianExtra, xBoxWidth, 2 * yMedianExtra); // Outliers - if (!this["hide-outliers"]) { + if (outlierRadius > 0) { const xJitter = xJitterHalfwidth !== 0 ? randomUniform.source(randomLcg(i * nDatasets + iDataset))(xCenter - xJitterHalfwidth, xCenter + xJitterHalfwidth) : () => xCenter; @@ -435,8 +454,8 @@ export default class NightingaleBoxplotTrack extends withCanvas( const canvasScale = this.canvasScale; const xBaseWidthInCss = this.getSingleBaseWidth(); const xBaseWidth = canvasScale * xBaseWidthInCss; - const xColumnLeft = xBaseWidth * 0.5 * COLUMN_GAP; - const xColumnWidth = xBaseWidth * (1 - COLUMN_GAP); + const xColumnLeft = xBaseWidth * 0.5 * this["column-gap"]; + const xColumnWidth = xBaseWidth * (1 - this["column-gap"]); const xColumnRight = xColumnLeft + xColumnWidth; const xScale = (i: number) => canvasScale * this.getXFromSeqPosition(i); @@ -446,7 +465,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( const yMedianExtra = canvasScale * 1; const lineWidth = canvasScale * Math.min(LINE_WIDTH, MAX_REL_LINE_WIDTH * xBaseWidthInCss); - const outlierRadius = canvasScale * OUTLIER_RADIUS; + const outlierRadius = canvasScale * this["outlier-radius"]; const start = Math.floor(this.getSeqPositionFromX(0) ?? 1); const stop = Math.floor(this.getSeqPositionFromX(this.width) ?? 1) + 1; @@ -482,7 +501,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( const nDatasets = this.preprocessedData?.datasets.length ?? 1; /** Approximate boxplot box width, in CSS pixels. No need to consider column gap and box gap here. */ const boxWidth = this.getSingleBaseWidth() / nDatasets; - const [transitionMin, transitionMax] = FG_BG_TRANSITION_BASE_WIDTHS; + const [transitionMin, transitionMax] = this.getZoomTransitionRange(); if (boxWidth <= transitionMin) { return [0, 1]; @@ -494,6 +513,13 @@ export default class NightingaleBoxplotTrack extends withCanvas( } } + private getZoomTransitionRange(): [number, number] { + const nums = this["zoom-transition-range"].split('-').map(Number); + const [a, b] = nums.length >= 2 ? [nums[0], nums[1]] : [nums[0], nums[0]] + if (isNaN(a) || isNaN(b)) return [0, 0]; + return [a, b]; + } + protected updateHighlight() { if (!this.svgHighlights) return; const highlights = this.svgHighlights @@ -524,8 +550,8 @@ export default class NightingaleBoxplotTrack extends withCanvas( .data(showNestedHighlight ? [nestedHighlightLocation] : []); const baseWidth = this.getSingleBaseWidth(); - const columnOffset = baseWidth * 0.5 * COLUMN_GAP; - const columnWidth = baseWidth * (1 - COLUMN_GAP); + const columnOffset = baseWidth * 0.5 * this["column-gap"]; + const columnWidth = baseWidth * (1 - this["column-gap"]); const datumWidth = columnWidth / nDatasets; highlights @@ -661,7 +687,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( if (continuousPosition === undefined) return undefined; const position = Math.floor(continuousPosition); const fractional = continuousPosition - position; - const fractionalWithinColumn = (fractional - 0.5 * COLUMN_GAP) / (1 - COLUMN_GAP); + const fractionalWithinColumn = (fractional - 0.5 * this["column-gap"]) / (1 - this["column-gap"]); const nDatasets = this.preprocessedData?.datasets.length ?? 1; const iDataset = Math.max(0, Math.min(nDatasets - 1, Math.floor(fractionalWithinColumn * nDatasets))); @@ -891,14 +917,14 @@ type NestedHighlight = [position: number, iDataset: number] | undefined; const NestedHighlight = { format(value: NestedHighlight): string { if (!value) return ''; - return `${value[0]}${this.SEPARATOR}${value[1]}`; + return `${value[0]}/${value[1]}`; }, parse(str: string): NestedHighlight { if (str.trim() === '') return undefined; - const [a, b] = str.split(this.SEPARATOR).map(Number); + const [a, b] = str.split('/').map(Number); return [a, b]; }, - SEPARATOR: '/', }; +// TODO: docs (here and in readme) // TODO: test on new API once available diff --git a/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts index 66cb939bd..e58aae509 100644 --- a/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts +++ b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts @@ -17,11 +17,16 @@ const DefaultArgs = { "highlight-color": "#EB3BFF22", "margin-color": "#ffffffdd", "margin-left": 30, + "show-axis": true, "y-min": 0 as number | undefined, "y-max": undefined as number | undefined, - "show-axis": true, "show-nested-highlights": true, - "hide-outliers": false, + "column-gap": 0.2, + "box-gap": 0.1, + "whisker-width": 0.6, + "outlier-jitter-width": 0.4, + "outlier-radius": 2, + "zoom-transition-range": "4-5", "zoomed-out-range": 'whiskers', "tooltips": true, }; @@ -31,6 +36,11 @@ const ArgumentTypes: Partial> = { "highlight-event": { control: "select", options: ["onmouseover", "onclick"] }, "y-min": { control: "select", options: [undefined, 0, 100, 200, 300, 400, 500] }, "y-max": { control: "select", options: [undefined, 0, 100, 200, 300, 400, 500] }, + "column-gap": { control: { type: "number", min: 0, max: 1, step: 0.05 } }, + "box-gap": { control: { type: "number", min: 0, max: 1, step: 0.05 } }, + "whisker-width": { control: { type: "number", min: 0, max: 1, step: 0.05 } }, + "outlier-jitter-width": { control: { type: "number", min: 0, max: 1, step: 0.05 } }, + "outlier-radius": { control: { type: "number", min: 0, step: 0.5 } }, "zoomed-out-range": { control: "select", options: ZoomedOutRangeOptions }, }; @@ -103,7 +113,7 @@ function nightingaleNavigation(args: Args & { length: number }) { margin-color=${args["margin-color"]} margin-left=${args["margin-left"]} show-highlight - display-end="100" + display-end="30" > `; @@ -146,12 +156,17 @@ function nightingaleBoxplotTrack(args: Args & { length: number, id: number }) { margin-bottom=10 margin-left=${args["margin-left"]} use-ctrl-to-zoom + ?show-axis=${args["show-axis"]} y-min=${args["y-min"]} y-max=${args["y-max"]} - ?show-axis=${args["show-axis"]} ?show-nested-highlights=${args["show-nested-highlights"]} - ?hide-outliers=${args["hide-outliers"]} + column-gap=${args["column-gap"]} + box-gap=${args["box-gap"]} + whisker-width=${args["whisker-width"]} + outlier-jitter-width=${args["outlier-jitter-width"]} + outlier-radius=${args["outlier-radius"]} zoomed-out-range=${args["zoomed-out-range"]} + zoom-transition-range=${args["zoom-transition-range"]} > `; From 16a58d0253a4303ceb347c54b7d59ff408562b13 Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Mon, 29 Jun 2026 13:38:17 +0100 Subject: [PATCH 26/32] nightingale-boxplot-track: review docstrings --- .../src/nightingale-boxplot-track.ts | 150 ++++++++++++------ .../src/utils/bindEvents.ts | 10 +- .../src/utils/refresher.ts | 5 +- .../NightingaleBoxplotTrack.stories.ts | 8 +- 4 files changed, 117 insertions(+), 56 deletions(-) diff --git a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts index b936099d0..a5a49181c 100644 --- a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts +++ b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts @@ -21,19 +21,18 @@ import { property } from "lit/decorators.js"; import { Downsampler } from "./downsampling"; -// TODO: track via decorators? const ATTRIBUTES_THAT_TRIGGER_REFRESH: string[] = [ "length", "width", "height", "margin-top", "margin-bottom", "margin-left", "margin-right", "margin-color", - "y-min", "y-max", "show-axis", "zoomed-out-range", + "y-min", "y-max", "show-axis", "zoomed-out-outline", "column-gap", "box-gap", "whisker-width", "outlier-jitter-width", "outlier-radius", "zoom-transition-range", ] satisfies (keyof NightingaleBoxplotTrack)[]; const ATTRIBUTES_THAT_TRIGGER_DATA_RESET: string[] = [] satisfies (keyof NightingaleBoxplotTrack)[]; -/** Line width for rectangle stroke */ +/** Line width for rectangle stroke, in CSS pixels */ const LINE_WIDTH = 1; -/** Maximum line width relative to column width (overrides `LINE_WIDTH` when zoomed out too much) */ +/** Maximum line width relative to base width (width of one sequence position) (overrides `LINE_WIDTH` when zoomed out too much) */ const MAX_REL_LINE_WIDTH = 0.2; /** Default fill color for boxes (stroke color will be derived from this) */ @@ -43,18 +42,21 @@ const DEFAULT_DATA_COLOR = "#cccccc"; * (higher value means more responsive but lower-resolution visualization). */ const BG_DOWNSAMPLING_PIXELS_PER_COLUMN = 1; +/** Return stroke color matching a given fill color (darker version of the same color) */ function makeStrokeColor(dataColor: string): string | undefined { return color(dataColor)?.darker(2).formatHex(); } +/** Data for a single boxplot (subcolumn) in the visualization (i.e. a single sequence position for a single dataset) */ interface BoxplotDatum { /** Position in the sequence (1-based) */ position: number, - /** Array of values of independent variable at the position */ + /** Array of values of the independent variable at the position */ values: ArrayLike, } +/** Data for a single dataset in the visualization (i.e. all sequence positions for a single dataset) */ export interface BoxplotDataset { /** Name of the dataset */ name: string, @@ -64,13 +66,18 @@ export interface BoxplotDataset { positions: BoxplotDatum[], } -/** Type for `NightingaleBoxplotTrack.data` */ +/** Data for `NightingaleBoxplotTrack`. + * A list of one or more datasets, where each dataset contains boxplot data for individual positions in the sequence. + * In case of multiple datasets, the boxplots for each dataset will be shown side-by-side at each sequence position. */ export type BoxplotData = BoxplotDataset[]; -export const ZoomedOutRangeOptions = ['extremes', 'whiskers', 'box', 'none'] as const; -export type ZoomedOutRangeOption = typeof ZoomedOutRangeOptions[number]; +/** Options for what kind of data can be shown as the shaded outline in zoomed-out visualization */ +export const ZoomedOutOutlineOptions = ['extremes', 'whiskers', 'box', 'none'] as const; +/** Options for what kind of data can be shown as the shaded outline in zoomed-out visualization */ +export type ZoomedOutOutlineOption = typeof ZoomedOutOutlineOptions[number]; +/** A Nightingale track for showing distribution of a variable on each residue position via boxplots */ @customElementOnce("nightingale-boxplot-track") export default class NightingaleBoxplotTrack extends withCanvas( withManager( @@ -83,19 +90,19 @@ export default class NightingaleBoxplotTrack extends withCanvas( ) ) ) { - /** Bottom limit for Y-axis (default: minimum computed from data) */ + /** Bottom limit for Y-axis (default: minimum computed from data). */ @property({ converter: OptionalNumberAttributeConverter }) "y-min"?: number; - /** Top limit for Y-axis (default: maximum computed from data) */ + /** Top limit for Y-axis (default: maximum computed from data). */ @property({ converter: OptionalNumberAttributeConverter }) "y-max"?: number; - /** What kind of data should be shown as shaded range in zoomed-out visualization */ - @property({ converter: EnumAttributeConverter(ZoomedOutRangeOptions, 'whiskers') }) - "zoomed-out-range": ZoomedOutRangeOption; + /** What kind of data should be shown as the shaded outline in zoomed-out visualization. */ + @property({ converter: EnumAttributeConverter(ZoomedOutOutlineOptions, 'whiskers') }) + "zoomed-out-outline": ZoomedOutOutlineOption; - /** Turn on showing secondary highlights, which indicate selected subcolumn within a column (in case of multiple dataset). */ + /** Turn on showing nested highlights, which indicate selected subcolumn within a column (in case of multiple datasets). */ @property({ type: Boolean }) "show-nested-highlights"?: boolean; @@ -103,23 +110,23 @@ export default class NightingaleBoxplotTrack extends withCanvas( @property({ type: Boolean }) "show-axis"?: boolean; - /** Position of secondary highlight in from "position/iDataset", or "" if none. */ + /** Position of nested highlight in form "position/iDataset", or "" if none. */ @property({ type: String, reflect: true }) // not using attribute converter here, because change detection would not work correctly private "nested-highlight": string = ""; - /** Width of the gap between displayed columns relative to the width of one sequence position (allowed range: 0-1, default: 0.2) */ + /** Width of the gap between displayed columns, relative to the base width (width of one sequence position) (allowed range: 0-1, default: 0.2). */ @property({ type: Number }) "column-gap": number = 0.2; - /** Width of the gap between boxes within a column relative to the column width (allowed range: 0-1, default: 0.1) */ + /** Width of the gap between boxes within a column, relative to the column width (allowed range: 0-1, default: 0.1). */ @property({ type: Number }) "box-gap": number = 0.1; - /** Whisker width relative to the box width (allowed range: 0-1, default: 0.6) */ + /** Boxplot whisker width, relative to the box width (allowed range: 0-1, default: 0.6). */ @property({ type: Number }) "whisker-width": number = 0.6; - /** Width of random noise (jitter) to be added to the X-position of the outliers, relative to the box width (allowed range: 0-1, default: 0.4) */ + /** Width of random noise (jitter) to be added to the X-position of the outliers, relative to the box width (allowed range: 0-1, default: 0.4). */ @property({ type: Number }) "outlier-jitter-width": number = 0.4; @@ -127,22 +134,23 @@ export default class NightingaleBoxplotTrack extends withCanvas( @property({ type: Number }) "outlier-radius": number = 2; - /** Column width (in CSS pixels), where the transition from zoomed-out simplified visualization to zoomed-in boxplot visualization happens. + /** Column width(s), in CSS pixels, where the transition from zoomed-out simplified visualization to zoomed-in boxplot visualization happens. * Can be either one number (for sharp transition) or a hyphen-separated range. - * If there are multiple datasets, the width will be divided by the number of datasets. + * If there are multiple datasets, this width(s) will be divided by the number of datasets. * Use "0" to always show zoomed-in visualization (or preferrably "0.5-1" to avoid perfomance issues). * Use "Infinity" to always show zoomed-out visualization. - * (default: "4-5") - * */ + * (default: "4-5") */ @property({ type: String }) - "zoom-transition-range": string = '4-5'; + "zoom-transition-range": string = "4-5"; - // TODO: continue here replacing consts by above props #data?: BoxplotData; private preprocessedData?: PreprocessedData; + /** D3 selection for SVG group for highlights (excluding nested highlights) */ protected svgHighlights?: Selection; + /** D3 selection for SVG group for nested highlights */ protected svgNestedHighlights?: Selection; + /** D3 selection for SVG group for margins */ protected svgMargins?: Selection; @@ -151,6 +159,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( if (this.data) this.createTrack(); } + /** Get or set the data for the boxplot track */ get data(): BoxplotData | undefined { return this.#data; } @@ -159,6 +168,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( this.preprocessedData = data ? preprocessData(data) : undefined; this.createTrack(); } + /** Return the range of Y values corresponding to bottom and top of the viewport (excluding margins) */ getYLimits(): [yMin: number, yMax: number] { const yMin = this["y-min"] ?? this.preprocessedData?.yLimits.min ?? 0; @@ -200,13 +210,14 @@ export default class NightingaleBoxplotTrack extends withCanvas( } } - refresh() { + protected refresh() { this.requestDraw(); this.updateHighlight(); this.updateNestedHighlight(); this.updateMargins(); } + /** Stamp for tracking changes to the drawing parameters (when the stamp changes, canvas redraw is needed) */ private readonly _drawStamp = new Stamp(() => { const stamp: Record = { "data": this["data"], @@ -238,6 +249,8 @@ export default class NightingaleBoxplotTrack extends withCanvas( this.drawData(this.canvasCtx); } + /** Get a clean auxiliary offscreen canvas for drawing, of the same size as the main canvas. + * Only one offscreen canvas can be use at any time, because it is reused. */ private getOffscreenCanvas(): [canvas: HTMLCanvasElement, canvasContext?: CanvasRenderingContext2D] { this._offscreenCanvas ??= document.createElement("canvas"); const width = this.canvasCtx?.canvas.width ?? 1; @@ -249,14 +262,18 @@ export default class NightingaleBoxplotTrack extends withCanvas( this._offscreenCanvas.height = height; } const ctx = this._offscreenCanvas.getContext('2d') ?? undefined; + this.clearCanvas(ctx); return [this._offscreenCanvas, ctx]; } private _offscreenCanvas?: HTMLCanvasElement; - private clearCanvas(ctx: CanvasRenderingContext2D) { + /** Clear the canvas. */ + private clearCanvas(ctx: CanvasRenderingContext2D | undefined) { + if (!ctx) return; ctx.clearRect(0, 0, ctx.canvas.width, ctx.canvas.height); } + /** Draw the data on the canvas. */ private drawData(ctx: CanvasRenderingContext2D) { const [fgAlpha, bgAlpha] = this.getFgBgOpacity(); @@ -270,10 +287,9 @@ export default class NightingaleBoxplotTrack extends withCanvas( // Draw foreground visualization directly this.drawBoxplotVisualization(ctx); } else if (fgAlpha > 0) { - // Draw foreground visualization via an auxiliary canvas (cannot be drawn directly to the main canvas, because overlapping outliers would create opacity > fgAlpha) + // Draw foreground visualization via an auxiliary canvas (cannot be drawn directly to the main canvas, because overlapping outliers would add up and create opacity > fgAlpha) const [auxCanvas, auxCtx] = this.getOffscreenCanvas(); if (auxCtx) { - this.clearCanvas(auxCtx); this.drawBoxplotVisualization(auxCtx); ctx.globalAlpha = fgAlpha; ctx.drawImage(auxCanvas, 0, 0); @@ -393,49 +409,50 @@ export default class NightingaleBoxplotTrack extends withCanvas( const yMedianLow = (j: number) => yScale(medianLow[j]) + yMedianExtra; const yMedianHigh = (j: number) => yScale(medianHigh[j]) - yMedianExtra; - let yRangeLow: ((j: number) => number) | undefined; - let yRangeHigh: ((j: number) => number) | undefined; - switch (this['zoomed-out-range']) { + let yOutlineLow: ((j: number) => number) | undefined; + let yOulineHigh: ((j: number) => number) | undefined; + switch (this['zoomed-out-outline']) { case 'extremes': { const minimum = downsamplers.minimum.getDownsampledByScale(scale); const maximum = downsamplers.maximum.getDownsampledByScale(scale); - yRangeLow = (j: number) => yScale(minimum[j]); - yRangeHigh = (j: number) => yScale(maximum[j]); + yOutlineLow = (j: number) => yScale(minimum[j]); + yOulineHigh = (j: number) => yScale(maximum[j]); break; } case 'whiskers': { const whiskerLow = downsamplers.whiskerLow.getDownsampledByScale(scale); const whiskerHigh = downsamplers.whiskerHigh.getDownsampledByScale(scale); - yRangeLow = (j: number) => yScale(whiskerLow[j]); - yRangeHigh = (j: number) => yScale(whiskerHigh[j]); + yOutlineLow = (j: number) => yScale(whiskerLow[j]); + yOulineHigh = (j: number) => yScale(whiskerHigh[j]); break; } case 'box': { const boxLow = downsamplers.boxLow.getDownsampledByScale(scale); const boxHigh = downsamplers.boxHigh.getDownsampledByScale(scale); - yRangeLow = (j: number) => yScale(boxLow[j]); - yRangeHigh = (j: number) => yScale(boxHigh[j]); + yOutlineLow = (j: number) => yScale(boxLow[j]); + yOulineHigh = (j: number) => yScale(boxHigh[j]); break; } case 'none': { - yRangeLow = undefined; - yRangeHigh = undefined; + yOutlineLow = undefined; + yOulineHigh = undefined; break; } } + // j-prefixed variables refer to indices in the downsampled data const jStart = Math.max(0, Math.floor((start - offset) / exactScale)); const jStop = Math.min(medianLow.length, Math.ceil((stop - offset) / exactScale)); const jSegments = getContiguousSegments(jStart, jStop, j => !isNaN(medianLow[j])); const jXScale = (j: number) => xScale(offset + j * exactScale); - // Shaded range - if (yRangeLow && yRangeHigh) { + // Shaded outline + if (yOutlineLow && yOulineHigh) { for (const segment of jSegments) { ctx.globalAlpha = weightAlpha(0.25 * alpha, weight); ctx.fillStyle = fillColor; - drawSilhouette(ctx, segment, jXScale, yRangeLow, yRangeHigh, [xColumnLeft, xColumnRight], 'fill'); + drawSilhouette(ctx, segment, jXScale, yOutlineLow, yOulineHigh, [xColumnLeft, xColumnRight], 'fill'); } } @@ -450,6 +467,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( } } + /** Get a set of shared measurement variables for drawing the boxplot visualizations. */ private getDrawingMeasurements() { const canvasScale = this.canvasScale; const xBaseWidthInCss = this.getSingleBaseWidth(); @@ -481,7 +499,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( xColumnWidth, /** Scale from sequence position to horizontal offset of the slot in canvas space (does not consider column gap) */ xScale, - /** Scale from value of independent variable to vertical position in canvas space */ + /** Scale from value of the independent variable to vertical position in canvas space */ yScale, /** Amount for vertically thickening the median rectangle, in canvas space */ yMedianExtra, @@ -520,6 +538,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( return [a, b]; } + /** Update the SVG highlights (excluding nested highlights) */ protected updateHighlight() { if (!this.svgHighlights) return; const highlights = this.svgHighlights @@ -539,6 +558,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( highlights.exit().remove(); } + /** Update the SVG nested highlights (indicate the pointed subcolumn within the highlighted column) */ protected updateNestedHighlight() { if (!this.svgNestedHighlights) return; const nestedHighlightLocation = NestedHighlight.parse(this["nested-highlight"]); @@ -568,6 +588,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( highlights.exit().remove(); } + /** Update the SVG margins */ protected updateMargins() { this.renderMarginOnGroup(this.svgMargins); } @@ -668,6 +689,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( if (withHighlight) { this["nested-highlight"] = NestedHighlight.format(undefined); } + const customEvent = createEvent( "mouseout", null, @@ -682,6 +704,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( this.dispatchEvent(customEvent); } + /** Get the datum pointed by the mouse cursor at the given SVG coordinates */ private getPointedDatum(svgX: number, _svgY: number) { const continuousPosition = this.getSeqPositionFromX(svgX); if (continuousPosition === undefined) return undefined; @@ -706,9 +729,10 @@ export default class NightingaleBoxplotTrack extends withCanvas( } +/** Preprocessed data for the boxplot track */ type PreprocessedData = ReturnType; -type PreprocessedDataset = ReturnType; +/** Preprocess data for the boxplot track */ function preprocessData(data: BoxplotData) { const preprocessedDatasets = data.map(preprocessDataset); return { @@ -717,6 +741,10 @@ function preprocessData(data: BoxplotData) { } } +/** Preprocessed data for a single dataset */ +type PreprocessedDataset = ReturnType; + +/** Preprocess data for a single dataset */ function preprocessDataset(dataset: BoxplotDataset) { const preprocessedPositions: PreprocessedPositions = {}; @@ -726,26 +754,39 @@ function preprocessDataset(dataset: BoxplotDataset) { return { ...dataset, positions: preprocessedPositions, - downsampling: getDownsamplerForDataset(preprocessedPositions), + downsampling: getDownsamplersForDataset(preprocessedPositions), }; } +/** Preprocessed data for a single position in a single dataset */ interface PreprocessedDatum { + /** Position in the sequence */ position: number, + /** All values at this position, sorted */ values: Float32Array, + /** Median value */ median: number, + /** Lower bound of the box (lower quartile) */ boxLow: number, + /** Upper bound of the box (upper quartile) */ boxHigh: number, + /** Lower bound of the whisker (lower quartile - 1.5 * IQR) */ whiskerLow: number, + /** Upper bound of the whisker (upper quartile + 1.5 * IQR) */ whiskerHigh: number, + /** Minimum value */ minimum: number, + /** Maximum value */ maximum: number, + /** Outliers below the whisker */ outliersLow: Float32Array, + /** Outliers above the whisker */ outliersHigh: Float32Array, } type PreprocessedPositions = { [position: number]: PreprocessedDatum } +/** Preprocess data for a single position in a dataset */ function preprocessDatum(datum: BoxplotDatum): PreprocessedDatum { const sorted = sortIfNeeded(new Float32Array(datum.values)); const median = getQuantile(sorted, 0.5); @@ -803,7 +844,7 @@ export function getQuantile(sortedValues: ArrayLike, p: number) { return sortedValues[i] * (1 - q) + sortedValues[i + 1] * q; } -/** Gets the Y-axis limits for the given preprocessed data */ +/** Get automatic Y-axis limits for the given preprocessed data (minimum and maximum value of the whole dataset). */ function getExtremes(data: PreprocessedDataset[]) { let min = Infinity; let max = -Infinity; @@ -822,6 +863,8 @@ function getExtremes(data: PreprocessedDataset[]) { }; } +/** Get contiguous segments within the integer range [start, stop), where `isPresent` returns true for each index. + * Return segments as an array of [start, stop) pairs. */ function getContiguousSegments(start: number, stop: number, isPresent: (i: number) => boolean): [start: number, stop: number][] { const segments: [number, number][] = []; for (let i = start; i < stop; i++) { @@ -836,6 +879,7 @@ function getContiguousSegments(start: number, stop: number, isPresent: (i: numbe return segments; } +/** Draw a silhouette for the given segments. */ function drawSilhouette(ctx: CanvasRenderingContext2D, [sStart, sStop]: [number, number], getX: (i: number) => number, getYLow: (i: number) => number, getYHigh: (i: number) => number, [columnOffsetLeft, columnOffsetRight]: [number, number], style: 'fill' | 'stroke' | 'fill+stroke') { ctx.beginPath(); for (let i = sStart; i < sStop; i++) { @@ -854,6 +898,7 @@ function drawSilhouette(ctx: CanvasRenderingContext2D, [sStart, sStop]: [number, if (style.includes('stroke')) ctx.stroke(); } +/** Convert preprocessed dataset from array of objects to object of arrays, for downsampling. */ function datasetToArrays(data: PreprocessedPositions) { const positions = Object.values(data).map(d => d.position); const offset = min(positions) ?? 1; @@ -882,7 +927,8 @@ function datasetToArrays(data: PreprocessedPositions) { }; } -function getDownsamplerForDataset(data: PreprocessedPositions) { +/** Get a set of downsamplers for each data type (median, minimum, ...) for a preprocessed dataset */ +function getDownsamplersForDataset(data: PreprocessedPositions) { const { offset, length, arrays } = datasetToArrays(data); return { offset, @@ -900,6 +946,9 @@ function getDownsamplerForDataset(data: PreprocessedPositions) { }; } +/** Adjust opacity value (`alpha`) for rendering two overlaying visualizations. + * This is done in such a way that overlaying of two visualizations with weights `weight` and `1-weight` will give the desired total opacity `alpha` in the overlapping area. + * (Naive `alpha*weight` would result in overlapping areas being more transparent than intended). */ function weightAlpha(alpha: number, weight: number) { if (alpha === 1) { // Avoid ill-defined expressions (division by zero) @@ -913,12 +962,15 @@ function weightAlpha(alpha: number, weight: number) { return 1 - transpWCorrected; } +/** Location of nested highlight (sequence position and 0-based dataset index within the position). */ type NestedHighlight = [position: number, iDataset: number] | undefined; const NestedHighlight = { + /** Format `NestedHighlight` in the form "position/iDataset", or "" if undefined. */ format(value: NestedHighlight): string { if (!value) return ''; return `${value[0]}/${value[1]}`; }, + /** Format `NestedHighlight` from the form "position/iDataset", or "" if undefined. */ parse(str: string): NestedHighlight { if (str.trim() === '') return undefined; const [a, b] = str.split('/').map(Number); @@ -926,5 +978,5 @@ const NestedHighlight = { }, }; -// TODO: docs (here and in readme) +// TODO: docs in readme // TODO: test on new API once available diff --git a/packages/nightingale-new-core/src/utils/bindEvents.ts b/packages/nightingale-new-core/src/utils/bindEvents.ts index d304b1d66..57ddd51c5 100644 --- a/packages/nightingale-new-core/src/utils/bindEvents.ts +++ b/packages/nightingale-new-core/src/utils/bindEvents.ts @@ -22,14 +22,20 @@ type SequenceBaseData = { }; type BoxplotData = { type: "boxplot"; + /** Position in the sequence */ position: number; + /** Data for the boxplot at this position (from all datasets) */ data: { + /** Common properties of the whole dataset */ dataset: { name: string; color: string; }; - datum?: { + /** Boxplot data at this position */ + datum: { + /** Position in the sequence */ position: number; + /** All values of the independent variable at this position */ values: Float32Array; median: number; boxLow: number; @@ -40,7 +46,7 @@ type BoxplotData = { maximum: number; outliersLow: Float32Array; outliersHigh: Float32Array; - }; + } | undefined; }[]; /** Index into `data`, indicates which dataset is being pointed at */ datasetIndex: number; diff --git a/packages/nightingale-new-core/src/utils/refresher.ts b/packages/nightingale-new-core/src/utils/refresher.ts index 210fc17f4..a24b024d7 100644 --- a/packages/nightingale-new-core/src/utils/refresher.ts +++ b/packages/nightingale-new-core/src/utils/refresher.ts @@ -64,14 +64,17 @@ export class Stamp { private currentStampValue: Record = {}; /** Update the current stamp value (using the return value of `stampFunction`). - * Return `true` if the stamp value has changed since the last `update`, `false` otherwise. + * Return an object with old and new stamp value and whether it has changed. * (Stamp value comparison is performed by shallow object comparison.) */ update() { const oldValue = this.currentStampValue; this.currentStampValue = this.stampFunction(); return { + /** The old stamp value (before the update) */ oldValue, + /** The new stamp value (after the update) */ newValue: this.currentStampValue, + /** Whether the stamp value has changed */ changed: !objectShallowEquals(oldValue, this.currentStampValue), }; } diff --git a/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts index e58aae509..127afad58 100644 --- a/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts +++ b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts @@ -3,7 +3,7 @@ import { type ArgTypes, Meta, Story } from "@storybook/web-components"; import { html } from "lit-html"; import "../../packages/nightingale-boxplot-track/src/index"; import NightingaleBoxplotTrack from "../../packages/nightingale-boxplot-track/src/nightingale-boxplot-track"; -import { type BoxplotData, ZoomedOutRangeOptions } from "../../packages/nightingale-boxplot-track/src/nightingale-boxplot-track"; +import { type BoxplotData, ZoomedOutOutlineOptions } from "../../packages/nightingale-boxplot-track/src/nightingale-boxplot-track"; import sampleBoxplotData from "../../packages/nightingale-boxplot-track/tests/mockData/sample-1.json"; @@ -27,7 +27,7 @@ const DefaultArgs = { "outlier-jitter-width": 0.4, "outlier-radius": 2, "zoom-transition-range": "4-5", - "zoomed-out-range": 'whiskers', + "zoomed-out-outline": 'whiskers', "tooltips": true, }; type Args = typeof DefaultArgs; @@ -41,7 +41,7 @@ const ArgumentTypes: Partial> = { "whisker-width": { control: { type: "number", min: 0, max: 1, step: 0.05 } }, "outlier-jitter-width": { control: { type: "number", min: 0, max: 1, step: 0.05 } }, "outlier-radius": { control: { type: "number", min: 0, step: 0.5 } }, - "zoomed-out-range": { control: "select", options: ZoomedOutRangeOptions }, + "zoomed-out-outline": { control: "select", options: ZoomedOutOutlineOptions }, }; @@ -165,7 +165,7 @@ function nightingaleBoxplotTrack(args: Args & { length: number, id: number }) { whisker-width=${args["whisker-width"]} outlier-jitter-width=${args["outlier-jitter-width"]} outlier-radius=${args["outlier-radius"]} - zoomed-out-range=${args["zoomed-out-range"]} + zoomed-out-outline=${args["zoomed-out-outline"]} zoom-transition-range=${args["zoom-transition-range"]} > From 2506e273d0db901c5545082a4d375ffc199e49ae Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Mon, 29 Jun 2026 13:43:48 +0100 Subject: [PATCH 27/32] nightingale-boxplot-track: unify quotemark style --- .../src/nightingale-boxplot-track.ts | 56 ++++++++++--------- .../NightingaleBoxplotTrack.stories.ts | 42 +++++++------- 2 files changed, 51 insertions(+), 47 deletions(-) diff --git a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts index a5a49181c..3810a86dc 100644 --- a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts +++ b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts @@ -72,7 +72,7 @@ export interface BoxplotDataset { export type BoxplotData = BoxplotDataset[]; /** Options for what kind of data can be shown as the shaded outline in zoomed-out visualization */ -export const ZoomedOutOutlineOptions = ['extremes', 'whiskers', 'box', 'none'] as const; +export const ZoomedOutOutlineOptions = ["extremes", "whiskers", "box", "none"] as const; /** Options for what kind of data can be shown as the shaded outline in zoomed-out visualization */ export type ZoomedOutOutlineOption = typeof ZoomedOutOutlineOptions[number]; @@ -99,7 +99,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( "y-max"?: number; /** What kind of data should be shown as the shaded outline in zoomed-out visualization. */ - @property({ converter: EnumAttributeConverter(ZoomedOutOutlineOptions, 'whiskers') }) + @property({ converter: EnumAttributeConverter(ZoomedOutOutlineOptions, "whiskers") }) "zoomed-out-outline": ZoomedOutOutlineOption; /** Turn on showing nested highlights, which indicate selected subcolumn within a column (in case of multiple datasets). */ @@ -261,7 +261,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( if (this._offscreenCanvas.height !== height) { this._offscreenCanvas.height = height; } - const ctx = this._offscreenCanvas.getContext('2d') ?? undefined; + const ctx = this._offscreenCanvas.getContext("2d") ?? undefined; this.clearCanvas(ctx); return [this._offscreenCanvas, ctx]; } @@ -411,29 +411,29 @@ export default class NightingaleBoxplotTrack extends withCanvas( let yOutlineLow: ((j: number) => number) | undefined; let yOulineHigh: ((j: number) => number) | undefined; - switch (this['zoomed-out-outline']) { - case 'extremes': { + switch (this["zoomed-out-outline"]) { + case "extremes": { const minimum = downsamplers.minimum.getDownsampledByScale(scale); const maximum = downsamplers.maximum.getDownsampledByScale(scale); yOutlineLow = (j: number) => yScale(minimum[j]); yOulineHigh = (j: number) => yScale(maximum[j]); break; } - case 'whiskers': { + case "whiskers": { const whiskerLow = downsamplers.whiskerLow.getDownsampledByScale(scale); const whiskerHigh = downsamplers.whiskerHigh.getDownsampledByScale(scale); yOutlineLow = (j: number) => yScale(whiskerLow[j]); yOulineHigh = (j: number) => yScale(whiskerHigh[j]); break; } - case 'box': { + case "box": { const boxLow = downsamplers.boxLow.getDownsampledByScale(scale); const boxHigh = downsamplers.boxHigh.getDownsampledByScale(scale); yOutlineLow = (j: number) => yScale(boxLow[j]); yOulineHigh = (j: number) => yScale(boxHigh[j]); break; } - case 'none': { + case "none": { yOutlineLow = undefined; yOulineHigh = undefined; break; @@ -452,7 +452,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( for (const segment of jSegments) { ctx.globalAlpha = weightAlpha(0.25 * alpha, weight); ctx.fillStyle = fillColor; - drawSilhouette(ctx, segment, jXScale, yOutlineLow, yOulineHigh, [xColumnLeft, xColumnRight], 'fill'); + drawSilhouette(ctx, segment, jXScale, yOutlineLow, yOulineHigh, [xColumnLeft, xColumnRight], "fill"); } } @@ -461,7 +461,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( ctx.globalAlpha = weightAlpha(0.5 * alpha, weight); ctx.fillStyle = strokeColor; ctx.strokeStyle = strokeColor; - drawSilhouette(ctx, segment, jXScale, yMedianLow, yMedianHigh, [xColumnLeft, xColumnRight], 'fill+stroke'); + drawSilhouette(ctx, segment, jXScale, yMedianLow, yMedianHigh, [xColumnLeft, xColumnRight], "fill+stroke"); } } } @@ -532,7 +532,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( } private getZoomTransitionRange(): [number, number] { - const nums = this["zoom-transition-range"].split('-').map(Number); + const nums = this["zoom-transition-range"].split("-").map(Number); const [a, b] = nums.length >= 2 ? [nums[0], nums[1]] : [nums[0], nums[0]] if (isNaN(a) || isNaN(b)) return [0, 0]; return [a, b]; @@ -716,7 +716,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( type EventFeatureData = Parameters[1]; const feature: EventFeatureData = { - type: 'boxplot', + type: "boxplot", position: position, data: this.preprocessedData?.datasets.map(dataset => ({ dataset: { name: dataset.name, color: dataset.color ?? DEFAULT_DATA_COLOR }, @@ -880,7 +880,11 @@ function getContiguousSegments(start: number, stop: number, isPresent: (i: numbe } /** Draw a silhouette for the given segments. */ -function drawSilhouette(ctx: CanvasRenderingContext2D, [sStart, sStop]: [number, number], getX: (i: number) => number, getYLow: (i: number) => number, getYHigh: (i: number) => number, [columnOffsetLeft, columnOffsetRight]: [number, number], style: 'fill' | 'stroke' | 'fill+stroke') { +function drawSilhouette( + ctx: CanvasRenderingContext2D, [sStart, sStop]: [number, number], + getX: (i: number) => number, getYLow: (i: number) => number, getYHigh: (i: number) => number, + [columnOffsetLeft, columnOffsetRight]: [number, number], style: "fill" | "stroke" | "fill+stroke" +) { ctx.beginPath(); for (let i = sStart; i < sStop; i++) { const x = getX(i); @@ -894,8 +898,8 @@ function drawSilhouette(ctx: CanvasRenderingContext2D, [sStart, sStop]: [number, ctx.lineTo(x + columnOffsetRight, yLow); ctx.lineTo(x + columnOffsetLeft, yLow); } - if (style.includes('fill')) ctx.fill(); - if (style.includes('stroke')) ctx.stroke(); + if (style.includes("fill")) ctx.fill(); + if (style.includes("stroke")) ctx.stroke(); } /** Convert preprocessed dataset from array of objects to object of arrays, for downsampling. */ @@ -934,14 +938,14 @@ function getDownsamplersForDataset(data: PreprocessedPositions) { offset, length, downsamplers: { - medianLow: new Downsampler(arrays.median, 'min'), - medianHigh: new Downsampler(arrays.median, 'max'), - boxLow: new Downsampler(arrays.boxLow, 'min'), - boxHigh: new Downsampler(arrays.boxHigh, 'max'), - whiskerLow: new Downsampler(arrays.whiskerLow, 'min'), - whiskerHigh: new Downsampler(arrays.whiskerHigh, 'max'), - minimum: new Downsampler(arrays.minimum, 'min'), - maximum: new Downsampler(arrays.maximum, 'max'), + medianLow: new Downsampler(arrays.median, "min"), + medianHigh: new Downsampler(arrays.median, "max"), + boxLow: new Downsampler(arrays.boxLow, "min"), + boxHigh: new Downsampler(arrays.boxHigh, "max"), + whiskerLow: new Downsampler(arrays.whiskerLow, "min"), + whiskerHigh: new Downsampler(arrays.whiskerHigh, "max"), + minimum: new Downsampler(arrays.minimum, "min"), + maximum: new Downsampler(arrays.maximum, "max"), }, }; } @@ -967,13 +971,13 @@ type NestedHighlight = [position: number, iDataset: number] | undefined; const NestedHighlight = { /** Format `NestedHighlight` in the form "position/iDataset", or "" if undefined. */ format(value: NestedHighlight): string { - if (!value) return ''; + if (!value) return ""; return `${value[0]}/${value[1]}`; }, /** Format `NestedHighlight` from the form "position/iDataset", or "" if undefined. */ parse(str: string): NestedHighlight { - if (str.trim() === '') return undefined; - const [a, b] = str.split('/').map(Number); + if (str.trim() === "") return undefined; + const [a, b] = str.split("/").map(Number); return [a, b]; }, }; diff --git a/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts index 127afad58..946b3970e 100644 --- a/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts +++ b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts @@ -27,7 +27,7 @@ const DefaultArgs = { "outlier-jitter-width": 0.4, "outlier-radius": 2, "zoom-transition-range": "4-5", - "zoomed-out-outline": 'whiskers', + "zoomed-out-outline": "whiskers", "tooltips": true, }; type Args = typeof DefaultArgs; @@ -66,8 +66,8 @@ function prepareBoxplotData(data: { positions: { position: number, values: numbe return [ { - name: 'Data1', - color: '#0088ff', + name: "Data1", + color: "#0088ff", positions: positions, // positions: remove(positions, 3, 4, 5, 6, 35), // DEBUG // positions: remove(positions, 3, 4, 5, 6, @@ -77,14 +77,14 @@ function prepareBoxplotData(data: { positions: { position: number, values: numbe // ), // DEBUG }, { - name: 'Data2', - color: '#ff8800', + name: "Data2", + color: "#ff8800", // positions: positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), positions: remove(positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), 1, 7), // DEBUG }, // { - // name: 'Data3', - // color: '#00aa44', + // name: "Data3", + // color: "#00aa44", // // positions: positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), // positions: remove(positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.93) })), 1, 7), // DEBUG // }, @@ -174,28 +174,28 @@ function nightingaleBoxplotTrack(args: Args & { length: number, id: number }) { /** This is a demonstration of how to use CustomEvents on the `nightingale-boxplot-track` component. Tooltips are not a part of the component. */ function handleTooltip(event: CustomEvent, args: Args) { - if (event.detail.eventType !== 'mouseover' && event.detail.eventType !== 'mouseout') return; + if (event.detail.eventType !== "mouseover" && event.detail.eventType !== "mouseout") return; type EventFeatureData = Parameters[1]; const feature: EventFeatureData = event.detail.feature; - let tooltipDiv = document.getElementById('boxplot-tooltip'); - if (args.tooltips && feature && 'type' in feature && feature.type === 'boxplot') { + let tooltipDiv = document.getElementById("boxplot-tooltip"); + if (args.tooltips && feature && "type" in feature && feature.type === "boxplot") { // Show tooltip if (!tooltipDiv) { - tooltipDiv = document.createElement('div'); - tooltipDiv.id = 'boxplot-tooltip'; - Object.assign(tooltipDiv.style, { position: 'fixed', background: 'white', border: '1px solid #ccc', padding: '6px', boxShadow: '0 2px 6px rgba(0,0,0,0.2)', zIndex: '666', fontFamily: 'sans-serif', fontSize: '12px' }); + tooltipDiv = document.createElement("div"); + tooltipDiv.id = "boxplot-tooltip"; + Object.assign(tooltipDiv.style, { position: "fixed", background: "white", border: "1px solid #ccc", padding: "6px", boxShadow: "0 2px 6px rgba(0,0,0,0.2)", zIndex: "666", fontFamily: "sans-serif", fontSize: "12px" }); document.body.appendChild(tooltipDiv); } const rows = [ - ['', ...feature.data.map(d => `${d.dataset.name}`)], - ['nDatapoints', ...feature.data.map(d => d.datum?.values.length ?? '-')], - ['nOutliers', ...feature.data.map(d => d.datum?.outliersHigh && d.datum?.outliersLow ? d.datum.outliersHigh.length + d.datum.outliersLow.length : '-')], - ['Max', ...feature.data.map(d => d.datum?.maximum.toFixed(2) ?? '-')], - ['Median', ...feature.data.map(d => d.datum?.median.toFixed(2) ?? '-')], - ['Min', ...feature.data.map(d => d.datum?.minimum.toFixed(2) ?? '-')], + ["", ...feature.data.map(d => `${d.dataset.name}`)], + ["nDatapoints", ...feature.data.map(d => d.datum?.values.length ?? "-")], + ["nOutliers", ...feature.data.map(d => d.datum?.outliersHigh && d.datum?.outliersLow ? d.datum.outliersHigh.length + d.datum.outliersLow.length : "-")], + ["Max", ...feature.data.map(d => d.datum?.maximum.toFixed(2) ?? "-")], + ["Median", ...feature.data.map(d => d.datum?.median.toFixed(2) ?? "-")], + ["Min", ...feature.data.map(d => d.datum?.minimum.toFixed(2) ?? "-")], ]; - const rowsHtml = rows.map((row) => `${row.map((cell, index) => `${cell}`).join('')}`).join(''); + const rowsHtml = rows.map((row) => `${row.map((cell, index) => `${cell}`).join("")}`).join(""); tooltipDiv.innerHTML = `${rowsHtml}
`; const mouseEvent: MouseEvent | undefined = event.detail.parentEvent; tooltipDiv.style.left = `${(mouseEvent?.clientX ?? 0) + 10}px`; @@ -239,7 +239,7 @@ function makeStory(options: { length: number }): Story { await customElements.whenDefined("nightingale-boxplot-track"); for (const track of document.getElementsByTagName("nightingale-boxplot-track")) { (track as NightingaleBoxplotTrack).data = boxplotData; - track.addEventListener('change', event => handleTooltip(event as CustomEvent, currentArgs)); + track.addEventListener("change", event => handleTooltip(event as CustomEvent, currentArgs)); } }; return story; From 582cf73f8bdb3b94c5361bb29576689d5a33cebb Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Tue, 30 Jun 2026 16:11:14 +0100 Subject: [PATCH 28/32] nightingale-boxplot-track: README --- packages/nightingale-boxplot-track/README.md | 179 +++++++++++++++++- .../src/nightingale-boxplot-track.ts | 6 +- 2 files changed, 180 insertions(+), 5 deletions(-) diff --git a/packages/nightingale-boxplot-track/README.md b/packages/nightingale-boxplot-track/README.md index 219fbac5a..c19a81908 100644 --- a/packages/nightingale-boxplot-track/README.md +++ b/packages/nightingale-boxplot-track/README.md @@ -2,6 +2,181 @@ [![Published on NPM](https://img.shields.io/npm/v/@nightingale-elements/nightingale-boxplot-track.svg)](https://www.npmjs.com/package/@nightingale-elements/nightingale-boxplot-track) -The `nightingale-boxplot-track` component ... +Nightingale boxplot track component is used to display the distribution of a variable at each sequence position using boxplots. It allows displaying multiple distribution datasets, rendered side-by-side at each sequence position. -TODO: +## Usage + +```html + +``` + +#### Setting the data through property + +```javascript +await customElements.whenDefined("nightingale-boxplot-track"); +const track = document.getElementById("track"); +if (track) { + // Showing 2 datasets on a sequence of 3 amino acids: + (track as any).data = [ + { + name: "Blue dataset", + color: "#0088ff", + positions: [ + { position: 1, values: [0.2, 0.5, 0.7, 0.9] }, + { position: 2, values: [0.1, 0.3, 0.5, 0.8] }, + { position: 3, values: [0.0, 0.2, 0.6, 0.8] }, + ], + }, + { + name: "Orange dataset", + color: "#ff8800", + positions: [ + { position: 1, values: [0.1, 0.3, 0.5, 0.8] }, + { position: 2, values: [0.0, 0.2, 0.6, 0.8] }, + { position: 3, values: [0.2, 0.5, 0.7, 0.9] }, + ], + }, + ]; +} +``` + +The `data` property expects a value of type [`BoxplotData`](./src/nightingale-boxplot-track.ts#L72) - an array of datasets, where each dataset has the following structure: + +```javascript +{ + name: string, + color?: string, + positions: { + position: number, + values: number[], + }[], +} +``` + +The component will compute the median, quartiles, whiskers, and outliers from the values array for each position. + +## Visualization description + +The components displays a boxplot at each sequence position where data have been provided (or multiple boxplots if there are multiple dataset). +Each boxplot shows the following data: + +``` + • ╮┄┄┄┄┄┄┄┄ Maximum + •• │ Outliers high + •• ╯ + ──┬── - Whisker high (highest value <= Q3 + 1.5 * IQR) + │ + │ +┌──┴──┐ - Box high = Q3 +┝━━━━━┥ - Median +│ │ +└──┬──┘ - Box low = Q1 + │ + ──┴── - Whisker low (lowest value >= Q1 - 1.5 * IQR) + ••• ╮ + • │ Outliers low + •• ╯┄┄┄┄┄┄┄┄ Minimum +``` + +\* Q1 = lower quartile, Q3 = upper quartile, IQR = Q3 - Q1 = interquartile range. + +### "zoomed-out" visualization + +When the view becomes too much zoomed-out and boxplots become poorly visible, the component will switch from boxplot visualization to simplified "zoomed-out" visualization. This visualization shows the median at each position in darker color, and optionally a lighter shaded outline representing extremes or whisker range or box range, depending on the `zoomed-out-outline` attribute (default: whisker range). The `zoom-transition-range` attributes controls when exactly this transition happens. If there are multiple datasets, they are overlaid on one another, being distinguishable by their color (rather then displayed side-by-side as boxplots). + +### Downsampling + +When the view becomes over more zoomed-out (column width < 1 screen pixel), the component will downsample the displayed simplified visualization data. This is done to ensure performance for very long sequences and shouldn't be visually noticeable. + +## API Reference + +### Attributes + +#### `y-min?: number, y-max?: number` + +Bottom and top limit for the Y-axis. If either is not set, it will be inferred from the data (minimum/maximum of all data values). + +#### `show-axis?: boolean (default: false)` + +Turn on or off displaying the vertical axis. + +#### `show-nested-highlights?: boolean (default: false)` + +Turn on or off displaying nested hightlights. Nested hightlights indicate the selected subcolumn (dataset) within the highlighted column (sequence position). This applies only when multiple datasets are displayed. + +#### `zoomed-out-outline?: "extremes" | "whiskers" | "box" | "none" (default: "whiskers")` + +Choose what kind of data is shown as the shaded outline in the simplified zoomed-out view (in addition to the darker lines showing median). + +- `"extremes"` - the outline covers the range between minimum and maximum; +- `"whiskers"` - the outline covers the same range as the whiskers in the boxplot; +- `"box"` - the outline covers the same range as the box in the boxplot (quartiles); +- `"none"` - no outline is rendered. + +#### `column-gap?: number (default: 0.2)` + +Width of the gap between displayed columns, relative to the base width (width of one sequence position). + +(= _Column gap_ / _Base width_ in the figure below) + +#### `box-gap?: number (default: 0.1)` + +Width of the gap between boxes within a column, relative to the column width divided by the number of datasets (= _Box gap_ / (_Column width_ / _N datasets_) = _Box gap_ / (_Box width_ + _Box gap_) in the figure below). + +#### `whisker-width?: number (default: 0.6)` + +Boxplot whisker width, relative to the box width (= _Whisker width_ / _Box width_ in the figure below). + +#### `outlier-jitter-width?: number (default: 0.4)` + +Width of random noise added to the X-position of outliers, relative to the box width (= _Outlier jitter width_ / _Box width_ in the figure below). + +#### `outlier-radius?: number (default: 2)` + +Radius of the circles used to render outliers, in CSS pixels. + +#### `zoom-transition-range?: string (default: "4-5")` + +Base width(s), in CSS pixels, where the transition from "zoomed-out" simplified visualization to "zoomed-in" boxplot visualization happens. + +`zoom-transition-range` can be either one number (for a sharp transition, e.g. `"4"`) or a hyphen-separated range (for a smooth transition, e.g. `"4-5"`). + +If there are multiple datasets, this width(s) will be multiplied by the number of datasets, to compensate for narrower space for each dataset. + +- Use `"0"` to always show "zoomed-in" boxplot visualization. (This is not recommended, as it will prevent downsampling and may cause performance issues. However, you can use sufficiently small values, such as `"0.5-1"`, to achieve the same goal without performance issues). + +* Use `"Infinity"` to always show "zoomed-out" visualization. + +#### Overview of width measurements + +(2 sequence positions with 2 datasets) + +``` + Seq. position 1 Seq. position 2 +<────────────────────><────────────────────> Base width +┄><────────────────><┄┄><────────────────><┄ Column width, Column gap + ><─────><><─────>< ><─────><><─────>< Box width, Box gap* + <───> <───> <───> <───> Whisker width + ──┬── ──┬── ──┬── ──┬── + ┌──┴──┐ ┌──┴──┐ ┌──┴──┐ ┌──┴──┐ + │ │ │ │ │ │ │ │ + ┝━━━━━┥ ┝━━━━━┥ ┝━━━━━┥ ┝━━━━━┥ + │ │ │ │ │ │ │ │ + └──┬──┘ └──┬──┘ └──┬──┘ └──┬──┘ + ──┴── ──┴── ──┴── ──┴── + ••• • • •• • • + • • •• • + <─> <─> <─> <─> Outlier jitter width +``` + +\* Full _Box gap_ between the boxes in a column, 1/2 _Box gap_ before the first and after the last box in a column + +### Events + +// TODO: + +### Other attributes and properties + +This component inherits from `NightingaleElement`. + +The component implements the following mixins: `withCanvas`, `withManager`, `withZoom`, `withResizable`, `withMargin`, `withPosition`, `withDimensions`, `withHighlight`. diff --git a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts index 3810a86dc..12dd18d4f 100644 --- a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts +++ b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts @@ -66,7 +66,7 @@ export interface BoxplotDataset { positions: BoxplotDatum[], } -/** Data for `NightingaleBoxplotTrack`. +/** Data for `NightingaleBoxplotTrack`. * A list of one or more datasets, where each dataset contains boxplot data for individual positions in the sequence. * In case of multiple datasets, the boxplots for each dataset will be shown side-by-side at each sequence position. */ export type BoxplotData = BoxplotDataset[]; @@ -134,9 +134,9 @@ export default class NightingaleBoxplotTrack extends withCanvas( @property({ type: Number }) "outlier-radius": number = 2; - /** Column width(s), in CSS pixels, where the transition from zoomed-out simplified visualization to zoomed-in boxplot visualization happens. + /** Base width(s), in CSS pixels, where the transition from zoomed-out simplified visualization to zoomed-in boxplot visualization happens. * Can be either one number (for sharp transition) or a hyphen-separated range. - * If there are multiple datasets, this width(s) will be divided by the number of datasets. + * If there are multiple datasets, this width(s) will be multiplied by the number of datasets, to compensate for narrower space for each dataset. * Use "0" to always show zoomed-in visualization (or preferrably "0.5-1" to avoid perfomance issues). * Use "Infinity" to always show zoomed-out visualization. * (default: "4-5") */ From 5c68bddc50a0e503b0ec8cd525105c222f42cd3a Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Wed, 1 Jul 2026 10:45:15 +0100 Subject: [PATCH 29/32] nightingale-boxplot-track: finish README --- packages/nightingale-boxplot-track/README.md | 112 ++++++++++++------ .../src/nightingale-boxplot-track.ts | 3 - .../src/utils/bindEvents.ts | 6 +- 3 files changed, 81 insertions(+), 40 deletions(-) diff --git a/packages/nightingale-boxplot-track/README.md b/packages/nightingale-boxplot-track/README.md index c19a81908..2e99db42b 100644 --- a/packages/nightingale-boxplot-track/README.md +++ b/packages/nightingale-boxplot-track/README.md @@ -4,52 +4,54 @@ Nightingale boxplot track component is used to display the distribution of a variable at each sequence position using boxplots. It allows displaying multiple distribution datasets, rendered side-by-side at each sequence position. +Most of the rendering is implemented via HTML canvas, but some non-critical parts are implemented via SVG (e.g. highlights). + ## Usage ```html - + ``` #### Setting the data through property -```javascript +```typescript await customElements.whenDefined("nightingale-boxplot-track"); const track = document.getElementById("track"); if (track) { - // Showing 2 datasets on a sequence of 3 amino acids: - (track as any).data = [ - { - name: "Blue dataset", - color: "#0088ff", - positions: [ - { position: 1, values: [0.2, 0.5, 0.7, 0.9] }, - { position: 2, values: [0.1, 0.3, 0.5, 0.8] }, - { position: 3, values: [0.0, 0.2, 0.6, 0.8] }, - ], - }, - { - name: "Orange dataset", - color: "#ff8800", - positions: [ - { position: 1, values: [0.1, 0.3, 0.5, 0.8] }, - { position: 2, values: [0.0, 0.2, 0.6, 0.8] }, - { position: 3, values: [0.2, 0.5, 0.7, 0.9] }, - ], - }, - ]; + // Showing 2 datasets on a sequence of 3 amino acids: + (track as any).data = [ + { + name: "Blue dataset", + color: "#0088ff", + positions: [ + { position: 1, values: [0.2, 0.5, 0.7, 0.9] }, + { position: 2, values: [0.1, 0.3, 0.5, 0.8] }, + { position: 3, values: [0.0, 0.2, 0.6, 0.8] }, + ], + }, + { + name: "Orange dataset", + color: "#ff8800", + positions: [ + { position: 1, values: [0.1, 0.3, 0.5, 0.8] }, + { position: 2, values: [0.0, 0.2, 0.6, 0.8] }, + { position: 3, values: [0.2, 0.5, 0.7, 0.9] }, + ], + }, + ]; } ``` -The `data` property expects a value of type [`BoxplotData`](./src/nightingale-boxplot-track.ts#L72) - an array of datasets, where each dataset has the following structure: +The `data` property expects a value of type `BoxplotData` - an array of datasets, where each dataset has the following structure: -```javascript +```typescript { - name: string, - color?: string, - positions: { - position: number, - values: number[], - }[], + name: string, + color?: string, + positions: Array<{ + position: number, + values: Array, + }>, } ``` @@ -94,12 +96,14 @@ When the view becomes over more zoomed-out (column width < 1 screen pixel), the #### `y-min?: number, y-max?: number` -Bottom and top limit for the Y-axis. If either is not set, it will be inferred from the data (minimum/maximum of all data values). +Bottom and top limit for the Y-axis. If either of these is not set, it will be inferred from the data (minimum/maximum of all data values). #### `show-axis?: boolean (default: false)` Turn on or off displaying the vertical axis. +The axis is rendered in the left margin of the component. The margin attributes must be set accordingly to provide enough space for the axis (e.g. `margin-left="30"`). + #### `show-nested-highlights?: boolean (default: false)` Turn on or off displaying nested hightlights. Nested hightlights indicate the selected subcolumn (dataset) within the highlighted column (sequence position). This applies only when multiple datasets are displayed. @@ -152,7 +156,7 @@ If there are multiple datasets, this width(s) will be multiplied by the number o (2 sequence positions with 2 datasets) ``` - Seq. position 1 Seq. position 2 + Seq. position 1 Seq. position 2 <────────────────────><────────────────────> Base width ┄><────────────────><┄┄><────────────────><┄ Column width, Column gap ><─────><><─────>< ><─────><><─────>< Box width, Box gap* @@ -173,7 +177,47 @@ If there are multiple datasets, this width(s) will be multiplied by the number o ### Events -// TODO: +As `nightingale-boxplot-track` implements from `withZoom` and `withHighlight`, it will respond to zooming changes, highlight events, and emit events when interacting with boxplots (helpful if you want to display tooltips, integrate with other components etc.). + +When the user clicks on or hovers over the component, the component emits a `CustomEvent` with type `"change"` and with `detail` of the following structure: + +```typescript +{ + eventType: "mouseover" | "mouseout" | "click", + parentEvent?: Event, + feature?: { + type: "boxplot", + /** Position in the sequence */ + position: number, + /** Data for the boxplot at this position from all datasets (one item for each dataset) */ + data: Array<{ + /** Common properties of the whole dataset */ + dataset: { + name: string, + color: string, + }, + /** Boxplot data at this position */ + datum?: { + /** Position in the sequence */ + position: number, + /** All values of the independent variable at this position */ + values: Float32Array, + median: number, + boxLow: number, + boxHigh: number, + whiskerLow: number, + whiskerHigh: number, + minimum: number, + maximum: number, + outliersLow: Float32Array, + outliersHigh: Float32Array, + }, + }>, + /** Index into `data`, indicates which dataset is being pointed at */ + datasetIndex: number, + } | null, +} +``` ### Other attributes and properties diff --git a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts index 12dd18d4f..b6c7322a9 100644 --- a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts +++ b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts @@ -981,6 +981,3 @@ const NestedHighlight = { return [a, b]; }, }; - -// TODO: docs in readme -// TODO: test on new API once available diff --git a/packages/nightingale-new-core/src/utils/bindEvents.ts b/packages/nightingale-new-core/src/utils/bindEvents.ts index 57ddd51c5..2719d2744 100644 --- a/packages/nightingale-new-core/src/utils/bindEvents.ts +++ b/packages/nightingale-new-core/src/utils/bindEvents.ts @@ -24,8 +24,8 @@ type BoxplotData = { type: "boxplot"; /** Position in the sequence */ position: number; - /** Data for the boxplot at this position (from all datasets) */ - data: { + /** Data for the boxplot at this position from all datasets (one item for each dataset) */ + data: Array<{ /** Common properties of the whole dataset */ dataset: { name: string; @@ -47,7 +47,7 @@ type BoxplotData = { outliersLow: Float32Array; outliersHigh: Float32Array; } | undefined; - }[]; + }>; /** Index into `data`, indicates which dataset is being pointed at */ datasetIndex: number; }; From 31a55c8b0f120fad0e1ad229ec93894a3c0a5406 Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Wed, 1 Jul 2026 11:23:05 +0100 Subject: [PATCH 30/32] nightingale-boxplot-track: final cleanup --- packages/nightingale-boxplot-track/README.md | 136 ++++++++++-------- .../src/nightingale-boxplot-track.ts | 14 +- .../NightingaleBoxplotTrack.stories.ts | 28 +--- 3 files changed, 86 insertions(+), 92 deletions(-) diff --git a/packages/nightingale-boxplot-track/README.md b/packages/nightingale-boxplot-track/README.md index 2e99db42b..a5f4eeb1a 100644 --- a/packages/nightingale-boxplot-track/README.md +++ b/packages/nightingale-boxplot-track/README.md @@ -9,36 +9,50 @@ Most of the rendering is implemented via HTML canvas, but some non-critical part ## Usage ```html - + ``` #### Setting the data through property ```typescript -await customElements.whenDefined("nightingale-boxplot-track"); -const track = document.getElementById("track"); +await customElements.whenDefined('nightingale-boxplot-track'); +const track = document.getElementById('track'); if (track) { - // Showing 2 datasets on a sequence of 3 amino acids: - (track as any).data = [ - { - name: "Blue dataset", - color: "#0088ff", - positions: [ - { position: 1, values: [0.2, 0.5, 0.7, 0.9] }, - { position: 2, values: [0.1, 0.3, 0.5, 0.8] }, - { position: 3, values: [0.0, 0.2, 0.6, 0.8] }, - ], - }, - { - name: "Orange dataset", - color: "#ff8800", - positions: [ - { position: 1, values: [0.1, 0.3, 0.5, 0.8] }, - { position: 2, values: [0.0, 0.2, 0.6, 0.8] }, - { position: 3, values: [0.2, 0.5, 0.7, 0.9] }, - ], - }, - ]; + // Showing 2 datasets on a sequence of 3 amino acids: + (track as any).data = [ + { + name: 'Blue dataset', + color: '#0088ff', + positions: [ + { position: 1, values: [0.2, 0.5, 0.7, 0.9] }, + { position: 2, values: [0.1, 0.3, 0.5, 0.8] }, + { position: 3, values: [0.0, 0.2, 0.6, 0.8] }, + ], + }, + { + name: 'Orange dataset', + color: '#ff8800', + positions: [ + { position: 1, values: [0.1, 0.3, 0.5, 0.8] }, + { position: 2, values: [0.0, 0.2, 0.6, 0.8] }, + { position: 3, values: [0.2, 0.5, 0.7, 0.9] }, + ], + }, + ]; } ``` @@ -46,12 +60,12 @@ The `data` property expects a value of type `BoxplotData` - an array of datasets ```typescript { - name: string, - color?: string, - positions: Array<{ - position: number, - values: Array, - }>, + name: string, + color?: string, + positions: Array<{ + position: number, + values: Array, + }>, } ``` @@ -183,39 +197,39 @@ When the user clicks on or hovers over the component, the component emits a `Cus ```typescript { - eventType: "mouseover" | "mouseout" | "click", - parentEvent?: Event, - feature?: { - type: "boxplot", - /** Position in the sequence */ - position: number, - /** Data for the boxplot at this position from all datasets (one item for each dataset) */ - data: Array<{ - /** Common properties of the whole dataset */ - dataset: { - name: string, - color: string, - }, - /** Boxplot data at this position */ - datum?: { + eventType: "mouseover" | "mouseout" | "click", + parentEvent?: Event, + feature?: { + type: "boxplot", /** Position in the sequence */ position: number, - /** All values of the independent variable at this position */ - values: Float32Array, - median: number, - boxLow: number, - boxHigh: number, - whiskerLow: number, - whiskerHigh: number, - minimum: number, - maximum: number, - outliersLow: Float32Array, - outliersHigh: Float32Array, - }, - }>, - /** Index into `data`, indicates which dataset is being pointed at */ - datasetIndex: number, - } | null, + /** Data for the boxplot at this position from all datasets (one item for each dataset) */ + data: Array<{ + /** Common properties of the whole dataset */ + dataset: { + name: string, + color: string, + }, + /** Boxplot data at this position */ + datum?: { + /** Position in the sequence */ + position: number, + /** All values of the independent variable at this position */ + values: Float32Array, + median: number, + boxLow: number, + boxHigh: number, + whiskerLow: number, + whiskerHigh: number, + minimum: number, + maximum: number, + outliersLow: Float32Array, + outliersHigh: Float32Array, + }, + }>, + /** Index into `data`, indicates which dataset is being pointed at */ + datasetIndex: number, + } | null, } ``` diff --git a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts index b6c7322a9..ccfba8158 100644 --- a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts +++ b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts @@ -98,22 +98,22 @@ export default class NightingaleBoxplotTrack extends withCanvas( @property({ converter: OptionalNumberAttributeConverter }) "y-max"?: number; - /** What kind of data should be shown as the shaded outline in zoomed-out visualization. */ - @property({ converter: EnumAttributeConverter(ZoomedOutOutlineOptions, "whiskers") }) - "zoomed-out-outline": ZoomedOutOutlineOption; + /** Turn on vertical axis. */ + @property({ type: Boolean }) + "show-axis"?: boolean; /** Turn on showing nested highlights, which indicate selected subcolumn within a column (in case of multiple datasets). */ @property({ type: Boolean }) "show-nested-highlights"?: boolean; - /** Turn on vertical axis. */ - @property({ type: Boolean }) - "show-axis"?: boolean; - /** Position of nested highlight in form "position/iDataset", or "" if none. */ @property({ type: String, reflect: true }) // not using attribute converter here, because change detection would not work correctly private "nested-highlight": string = ""; + /** What kind of data should be shown as the shaded outline in zoomed-out visualization. */ + @property({ converter: EnumAttributeConverter(ZoomedOutOutlineOptions, "whiskers") }) + "zoomed-out-outline": ZoomedOutOutlineOption; + /** Width of the gap between displayed columns, relative to the base width (width of one sequence position) (allowed range: 0-1, default: 0.2). */ @property({ type: Number }) "column-gap": number = 0.2; diff --git a/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts index 946b3970e..e3cde73e7 100644 --- a/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts +++ b/stories/22.NightingaleBoxplotTrack/NightingaleBoxplotTrack.stories.ts @@ -2,8 +2,7 @@ import { type createEvent } from "@nightingale-elements/nightingale-new-core"; import { type ArgTypes, Meta, Story } from "@storybook/web-components"; import { html } from "lit-html"; import "../../packages/nightingale-boxplot-track/src/index"; -import NightingaleBoxplotTrack from "../../packages/nightingale-boxplot-track/src/nightingale-boxplot-track"; -import { type BoxplotData, ZoomedOutOutlineOptions } from "../../packages/nightingale-boxplot-track/src/nightingale-boxplot-track"; +import NightingaleBoxplotTrack, { type BoxplotData, ZoomedOutOutlineOptions } from "../../packages/nightingale-boxplot-track/src/nightingale-boxplot-track"; import sampleBoxplotData from "../../packages/nightingale-boxplot-track/tests/mockData/sample-1.json"; @@ -45,18 +44,11 @@ const ArgumentTypes: Partial> = { }; -// const nDataRepeat = 20_000; -// const nDataRepeat = 1_000; -// const nDataRepeat = 81; const nDataRepeat = 82; -// Around 100k datapoints (nDataRepeat=1000), canvas draw takes > 40ms -// Around 400k datapoints (nDataRepeat=4000), aliasing makes data invisible (causes artifacts even before) - const sampleSequence = "MALYGTHSHGLFKKLGIPGPTPLPFLGNILSYHKGFCMFDMECHKKYGKVWGFYDGQQPVLAITDPDMIKTVLVKECYSVFTNRRPFGPVGFMKSAISIA".repeat(nDataRepeat); function prepareBoxplotData(data: { positions: { position: number, values: number[] }[] }): BoxplotData { - // const positions = data.positions.slice(); - const positions = data.positions.map(pos => ({ position: pos.position, values: pos.values.sort() })); + const positions = data.positions.map(pos => ({ position: pos.position, values: pos.values.sort() })); // Sorting values for each position is not required by the boxplot track, but can make loading faster. const shift = data.positions.length; for (let i = 1; i < nDataRepeat; i++) { for (const pos of data.positions) { @@ -69,25 +61,13 @@ function prepareBoxplotData(data: { positions: { position: number, values: numbe name: "Data1", color: "#0088ff", positions: positions, - // positions: remove(positions, 3, 4, 5, 6, 35), // DEBUG - // positions: remove(positions, 3, 4, 5, 6, - // ...new Array(50).fill(0).map((_, i) => 35 + i), - // ...new Array(500).fill(0).map((_, i) => 500 + i), - // ...new Array(5000).fill(0).map((_, i) => 5000 + i), - // ), // DEBUG }, { name: "Data2", color: "#ff8800", - // positions: positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), - positions: remove(positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), 1, 7), // DEBUG + // Dummy data: multiply Data1 by a constant and remove some positions + positions: remove(positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), 1, 7, 8, 9, 10), }, - // { - // name: "Data3", - // color: "#00aa44", - // // positions: positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.8) })), - // positions: remove(positions.map(pos => ({ ...pos, values: pos.values.map(v => v * 0.93) })), 1, 7), // DEBUG - // }, ]; } From 6bc8b04e099d6d304b95ec8dc22f1539b674bbfe Mon Sep 17 00:00:00 2001 From: Adam Midlik Date: Thu, 13 Aug 2026 11:11:10 +0100 Subject: [PATCH 31/32] nightingale-boxplot-track PR feedback --- .../src/nightingale-boxplot-track.ts | 9 +-------- .../src/utils/attribute-converters.ts | 8 ++++++-- 2 files changed, 7 insertions(+), 10 deletions(-) diff --git a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts index ccfba8158..093147b42 100644 --- a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts +++ b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts @@ -27,7 +27,6 @@ const ATTRIBUTES_THAT_TRIGGER_REFRESH: string[] = [ "y-min", "y-max", "show-axis", "zoomed-out-outline", "column-gap", "box-gap", "whisker-width", "outlier-jitter-width", "outlier-radius", "zoom-transition-range", ] satisfies (keyof NightingaleBoxplotTrack)[]; -const ATTRIBUTES_THAT_TRIGGER_DATA_RESET: string[] = [] satisfies (keyof NightingaleBoxplotTrack)[]; /** Line width for rectangle stroke, in CSS pixels */ @@ -178,10 +177,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( override attributeChangedCallback(name: string, oldValue: string | null, newValue: string | null): void { super.attributeChangedCallback(name, oldValue, newValue); - if (ATTRIBUTES_THAT_TRIGGER_DATA_RESET.includes(name)) { - // Calling `this.data` setter to recompute `this.positions` and run `this.createTrack()` - this.data = this.data; // eslint-disable-line no-self-assign - } else if (ATTRIBUTES_THAT_TRIGGER_REFRESH.includes(name)) { + if (ATTRIBUTES_THAT_TRIGGER_REFRESH.includes(name)) { this.onDimensionsChange(); this.createTrack(); } @@ -228,9 +224,6 @@ export default class NightingaleBoxplotTrack extends withCanvas( "display-start": this["display-start"], "display-end": this["display-end"], }; - for (const attr of ATTRIBUTES_THAT_TRIGGER_DATA_RESET) { - stamp[attr] = this.getAttribute(attr); - } for (const attr of ATTRIBUTES_THAT_TRIGGER_REFRESH) { stamp[attr] = this.getAttribute(attr); } diff --git a/packages/nightingale-new-core/src/utils/attribute-converters.ts b/packages/nightingale-new-core/src/utils/attribute-converters.ts index 6742b3e3b..c74878516 100644 --- a/packages/nightingale-new-core/src/utils/attribute-converters.ts +++ b/packages/nightingale-new-core/src/utils/attribute-converters.ts @@ -17,9 +17,13 @@ export const OptionalNumberAttributeConverter: ComplexAttributeConverter Date: Thu, 13 Aug 2026 14:01:55 +0100 Subject: [PATCH 32/32] Change ATTRIBUTES_THAT_TRIGGER_REFRESH to set (in multiple tracks) --- .../src/nightingale-boxplot-track.ts | 6 +++--- .../src/nightingale-conservation-track.ts | 13 ++++++++----- .../src/mixins/withZoom/index.ts | 6 ++++-- packages/nightingale-track/src/nightingale-track.ts | 10 +++++----- 4 files changed, 20 insertions(+), 15 deletions(-) diff --git a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts index 093147b42..d5f59ceff 100644 --- a/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts +++ b/packages/nightingale-boxplot-track/src/nightingale-boxplot-track.ts @@ -21,12 +21,12 @@ import { property } from "lit/decorators.js"; import { Downsampler } from "./downsampling"; -const ATTRIBUTES_THAT_TRIGGER_REFRESH: string[] = [ +const ATTRIBUTES_THAT_TRIGGER_REFRESH = new Set([ "length", "width", "height", "margin-top", "margin-bottom", "margin-left", "margin-right", "margin-color", "y-min", "y-max", "show-axis", "zoomed-out-outline", "column-gap", "box-gap", "whisker-width", "outlier-jitter-width", "outlier-radius", "zoom-transition-range", -] satisfies (keyof NightingaleBoxplotTrack)[]; +] satisfies (keyof NightingaleBoxplotTrack)[]); /** Line width for rectangle stroke, in CSS pixels */ @@ -177,7 +177,7 @@ export default class NightingaleBoxplotTrack extends withCanvas( override attributeChangedCallback(name: string, oldValue: string | null, newValue: string | null): void { super.attributeChangedCallback(name, oldValue, newValue); - if (ATTRIBUTES_THAT_TRIGGER_REFRESH.includes(name)) { + if (ATTRIBUTES_THAT_TRIGGER_REFRESH.has(name)) { this.onDimensionsChange(); this.createTrack(); } diff --git a/packages/nightingale-conservation-track/src/nightingale-conservation-track.ts b/packages/nightingale-conservation-track/src/nightingale-conservation-track.ts index cb17ec1be..0d505aea3 100644 --- a/packages/nightingale-conservation-track/src/nightingale-conservation-track.ts +++ b/packages/nightingale-conservation-track/src/nightingale-conservation-track.ts @@ -19,12 +19,15 @@ import { html, PropertyValues } from "lit"; import { property } from "lit/decorators.js"; -const ATTRIBUTES_THAT_TRIGGER_REFRESH: string[] = [ +const ATTRIBUTES_THAT_TRIGGER_REFRESH = new Set([ "length", "width", "height", "margin-top", "margin-bottom", "margin-left", "margin-right", "margin-color", "font-family", "min-font-size", "fade-font-size", "max-font-size", -] satisfies (keyof NightingaleConservationTrack)[]; -const ATTRIBUTES_THAT_TRIGGER_DATA_RESET: string[] = ["letter-order"] satisfies (keyof NightingaleConservationTrack)[]; +] satisfies (keyof NightingaleConservationTrack)[]); + +const ATTRIBUTES_THAT_TRIGGER_DATA_RESET = new Set([ + "letter-order", +] satisfies (keyof NightingaleConservationTrack)[]); /** Order of amino acids in a column (top-to-bottom) */ const AMINO_ACID_ORDER = Array.from("HYAVLIMFWSTQNKRDEPCG"); // Old Protvista order: HYSTQNAVLIMFWDEPKRCG @@ -157,10 +160,10 @@ export default class NightingaleConservationTrack extends withCanvas( override attributeChangedCallback(name: string, oldValue: string | null, newValue: string | null): void { super.attributeChangedCallback(name, oldValue, newValue); - if (ATTRIBUTES_THAT_TRIGGER_DATA_RESET.includes(name)) { + if (ATTRIBUTES_THAT_TRIGGER_DATA_RESET.has(name)) { // Calling `this.data` setter to recompute `this.positions` and run `this.createTrack()` this.data = this.data; // eslint-disable-line no-self-assign - } else if (ATTRIBUTES_THAT_TRIGGER_REFRESH.includes(name)) { + } else if (ATTRIBUTES_THAT_TRIGGER_REFRESH.has(name)) { this.onDimensionsChange(); this.createTrack(); } diff --git a/packages/nightingale-new-core/src/mixins/withZoom/index.ts b/packages/nightingale-new-core/src/mixins/withZoom/index.ts index d070e3b83..49c604c66 100644 --- a/packages/nightingale-new-core/src/mixins/withZoom/index.ts +++ b/packages/nightingale-new-core/src/mixins/withZoom/index.ts @@ -42,7 +42,9 @@ export interface WithZoomInterface extends WithDimensionsInterface, withPosition zoomRefreshed(): void; } -const ATTRIBUTES_THAT_TRIGGER_REFRESH = ["length", "width", "height"]; +const ATTRIBUTES_THAT_TRIGGER_REFRESH = new Set([ + "length", "width", "height", +] satisfies (keyof WithZoomInterface)[]); const withZoom = >( @@ -71,7 +73,7 @@ const withZoom = >( super.attributeChangedCallback(name, oldValue, newValue); const newV = newValue === "null" ? null : newValue; if (oldValue !== newV) { - if (ATTRIBUTES_THAT_TRIGGER_REFRESH.includes(name)) { + if (ATTRIBUTES_THAT_TRIGGER_REFRESH.has(name)) { this.adjustZoomConstraints(); this.adjustZoom(); } diff --git a/packages/nightingale-track/src/nightingale-track.ts b/packages/nightingale-track/src/nightingale-track.ts index 33b0b06a6..1c8eb4da0 100644 --- a/packages/nightingale-track/src/nightingale-track.ts +++ b/packages/nightingale-track/src/nightingale-track.ts @@ -52,7 +52,10 @@ export type Feature = { }; // TODO: height is not triggering a full redrawn when is changed after first render -const ATTRIBUTES_THAT_TRIGGER_REFRESH = ["length", "width", "height"]; +const ATTRIBUTES_THAT_TRIGGER_REFRESH = new Set([ + "length", "width", "height", + "margin-top", "margin-bottom", "margin-left", "margin-right", "margin-color", +] satisfies (keyof NightingaleTrack)[]); @customElementOnce("nightingale-track") class NightingaleTrack extends withManager( @@ -173,10 +176,7 @@ class NightingaleTrack extends withManager( newValue: string | null ): void { super.attributeChangedCallback(name, oldValue, newValue); - if ( - ATTRIBUTES_THAT_TRIGGER_REFRESH.includes(name) || - name.startsWith("margin-") - ) { + if (ATTRIBUTES_THAT_TRIGGER_REFRESH.has(name)) { this.applyFilters(); this.layoutObj = this.getLayout(); this.createTrack();