documentation/_quarto.yml at main · StochasticTree/documentation · GitHub

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project:
  type: website
  output-dir: _site
  render:
    - "*.qmd"
    - "vignettes/*.qmd"
    - "python-api/reference/*.qmd"
    - "development/*.qmd"
  resources:
    - docs/R_docs/pkgdown/
    - docs/cpp_docs/doxygen/

website:
  title: "StochTree"
  site-url: "https://stochtree.ai/"
  repo-url: "https://github.com/StochasticTree/stochtree"
  repo-actions: [issue]

  navbar:
    left:
      - href: index.qmd
        text: Home
      - href: getting-started.qmd
        text: Getting Started
      - href: about.qmd
        text: About
      - text: R Package
        href: docs/R_docs/pkgdown/index.html
      - text: Python API
        href: python-api/reference/index.qmd
      - text: C++ API
        href: docs/cpp_docs/doxygen/index.html
      - text: Vignettes
        href: vignettes/index.qmd
      - text: Development
        menu:
          - text: Overview
            href: development/index.qmd
          - text: Contributing
            href: development/contributing.qmd
          - text: Adding New Models
            href: development/new-models.qmd
          - text: Roadmap
            href: development/roadmap.qmd

  sidebar:
    - id: python-api
      title: "Python API"
      style: docked
      contents:
        - python-api/reference/index.qmd
        - section: "Core Models"
          contents:
            - python-api/reference/bart.BARTModel.qmd
            - python-api/reference/bcf.BCFModel.qmd
        - section: "Scikit-Learn Interface"
          contents:
            - python-api/reference/sklearn.StochTreeBARTRegressor.qmd
            - python-api/reference/sklearn.StochTreeBARTBinaryClassifier.qmd
        - section: "Low-Level API"
          contents:
            - python-api/reference/data.Dataset.qmd
            - python-api/reference/data.Residual.qmd
            - python-api/reference/forest.Forest.qmd
            - python-api/reference/forest.ForestContainer.qmd
            - python-api/reference/sampler.ForestSampler.qmd
            - python-api/reference/sampler.GlobalVarianceModel.qmd
            - python-api/reference/sampler.LeafVarianceModel.qmd

    - id: vignettes
      title: "Vignettes"
      style: docked
      contents:
        - vignettes/index.qmd
        - section: "Core Models"
          contents:
            - vignettes/bart.qmd
            - vignettes/bcf.qmd
            - vignettes/heteroskedastic.qmd
            - vignettes/ordinal-outcome.qmd
            - vignettes/multivariate-bcf.qmd
        - section: "Practical Topics"
          contents:
            - vignettes/serialization.qmd
            - vignettes/multi-chain.qmd
            - vignettes/tree-inspection.qmd
            - vignettes/summary-plotting.qmd
            - vignettes/prior-calibration.qmd
            - vignettes/sklearn.qmd
        - section: "Low-Level Interface"
          contents:
            - vignettes/custom-sampling.qmd
            - vignettes/ensemble-kernel.qmd
        - section: "Advanced Methods"
          contents:
            - vignettes/targeted-smoothing.qmd
            - vignettes/rdd.qmd
            - vignettes/iv.qmd

format:
  html:
    theme: [minty, assets/custom.scss]
    css: assets/api.css
    toc: true
    toc-depth: 3
    grid:
      body-width: 1000px
      margin-width: 200px

execute:
  freeze: auto

quartodoc:
  package: stochtree
  dir: python-api/reference
  style: pkgdown
  parser: numpy
  render_interlinks: false
  sections:
    - title: Core Models
      desc: High-level model interfaces for supervised learning and causal inference.
      contents:
        - name: bart.BARTModel
          member_order: source
        - name: bcf.BCFModel
          member_order: source
    - title: Scikit-Learn Interface
      desc: stochtree models wrapped as sklearn-compatible estimators.
      contents:
        - name: sklearn.StochTreeBARTRegressor
          member_order: source
        - name: sklearn.StochTreeBARTBinaryClassifier
          member_order: source
    - title: Low-Level API — Data
      desc: Data structures for custom sampling workflows.
      contents:
        - name: data.Dataset
          member_order: source
        - name: data.Residual
          member_order: source
    - title: Low-Level API — Forest
      desc: Forest containers and inspection.
      contents:
        - name: forest.Forest
          member_order: source
        - name: forest.ForestContainer
          member_order: source
    - title: Low-Level API — Samplers
      desc: Sampler classes for building custom models.
      contents:
        - name: sampler.ForestSampler
          member_order: source
        - name: sampler.GlobalVarianceModel
          member_order: source
        - name: sampler.LeafVarianceModel
          member_order: source