Xopt/mkdocs.yml at main · dylanmkennedy/Xopt · GitHub

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site_name: Xopt
repo_url: https://github.com/xopt-org/Xopt
repo_name: xopt-org/Xopt

nav:
    - Home: index.md
    - Installation: installation.md
    - Algorithms: algorithms.md
    - Examples:
        - Basics:
            - Basic example: examples/basic/xopt_basic.ipynb
            - Running from the command line: examples/basic/xopt_cli.md
            - Parallel examples: examples/basic/xopt_parallel.ipynb
            - VOCS data structure: examples/basic/xopt_vocs.ipynb
            - Evaluator basic usage: examples/basic/xopt_evaluator.ipynb
            - Working with generators: examples/basic/xopt_generator.ipynb
            - Stopping conditions: examples/basic/xopt_stopping_condition.ipynb
            - Checkpointing and restarts: examples/basic/checkpointing_and_restarts.ipynb
        - Bayesian:
            - Gaussian Process Model Creation:
                - Basic example: examples/gp_model_creation/model_creation.ipynb
                - Batched models: examples/gp_model_creation/batched_model.ipynb
                - Approximate models: examples/gp_model_creation/approximate.ipynb
            - Bayesian Exploration:
                - Bayesian Exploration: examples/bayes_exp/bayesian_exploration.ipynb
                - Bayesian Exploration from yaml: examples/bayes_exp/bayesian_exploration_from_yaml.ipynb
                - Bayesian Exploration with interpolation: examples/bayes_exp/bayesian_exploration_w_interpolation.ipynb
                - Bayesian Exploration with NaNs: examples/bayes_exp/bayesian_exploration_with_nans.ipynb
            - Single Objective Bayesian Optimization:
                - Bayesian optimization tutorial: examples/single_objective_bayes_opt/bo_tutorial.ipynb
                - Constrained optimization: examples/single_objective_bayes_opt/constrained_bo_tutorial.ipynb
                - Upper confidence bound: examples/single_objective_bayes_opt/upper_confidence_bound.ipynb
                - Custom GP models: examples/single_objective_bayes_opt/custom_model.ipynb
                - Interpolated optimization: examples/single_objective_bayes_opt/interpolate_tutorial.ipynb
                - Multi-Fidelity: examples/single_objective_bayes_opt/multi_fidelity_simple.ipynb
                - Time dependent upper confidence bound: examples/single_objective_bayes_opt/time_dependent_bo.ipynb
                - Bayesian Algorithm Execution: examples/single_objective_bayes_opt/bax_tutorial.ipynb
                - Bayesian Optimization with fixed features: examples/single_objective_bayes_opt/fixed_features.ipynb
                - Mixed continuous-discrete optimization: examples/single_objective_bayes_opt/mixed_discrete.ipynb
                - Custom objectives: examples/single_objective_bayes_opt/custom_objective.ipynb
                - Heteroskedastic modeling: examples/single_objective_bayes_opt/heteroskedastic_noise_tutorial.ipynb
                - Noisy Bayesian optimization: examples/single_objective_bayes_opt/noisy_bo_tutorial.ipynb
                - Fast model evaluation: examples/single_objective_bayes_opt/fast_model_eval.ipynb
                - Hessian kernel: examples/single_objective_bayes_opt/hessian_kernel.ipynb
            - Trust Region Bayesian Optimization:
                - Basic example: examples/trust_region_bo/turbo_basics.ipynb
                - Optimization: examples/trust_region_bo/turbo_optimize.ipynb
                - Safety: examples/trust_region_bo/turbo_safety.ipynb
            - Multi-Objective Bayesian Optimization:
                - Expected hypervolume improvement: examples/multi_objective_bayes_opt/mobo.ipynb
                - Multi-fidelity expected hypervolume improvement: examples/multi_objective_bayes_opt/multi_fidelity_mobo.ipynb
                - Multi-generation gaussian process optimization: examples/multi_objective_bayes_opt/mggpo.ipynb
        - Evolutionary / Genetic:
            - CNSGA: examples/ga/cnsga_tnk.ipynb
            - NSGA-II:
              - Overview: examples/ga/nsga2/index.md
              - "YAML Interface":
                - Overview: examples/ga/nsga2/yaml_interface/index.md
                - Companion notebook: examples/ga/nsga2/yaml_interface/nsga2_yaml.ipynb
              - Python interface: examples/ga/nsga2/nsga2_python.ipynb
              - Output conversion: examples/ga/nsga2/nsga2_to_cnsga.ipynb
              - Genetic operators: examples/ga/nsga2/genetic_operators.ipynb

        - Sequential:
            - Nelder-Mead: examples/sequential/neldermead.ipynb
            - Extremum seeking: examples/sequential/extremum_seeking.ipynb
            - RCDS: examples/sequential/rcds.ipynb
        - Other:
            - Latin Hypercube: examples/scipy/latin_hypercube.ipynb
        - Developer:
            - Benchmarking & Profiling: examples/developer/benchmarking.md

    - API:
      - Xopt: api/xopt.md
      - Vocs: api/vocs.md
      - Evaluator: api/evaluator.md
      - Generators:
          - Base generator class: api/generators.md
          - Bayesian generators:
              - Bayesian Generator Class: api/generators/bayesian/bayesian_generator.md
              - Time-Dependent Bayesian Generators: api/generators/bayesian/time_dependent.md
              - Bayesian Exploration: api/generators/bayesian/bayesian_exploration.md
              - Expected Improvement: api/generators/bayesian/expected_improvement.md
              - Multi-Objective BO: api/generators/bayesian/mobo.md
              - Multi-Generation Gaussian Process Optimization: api/generators/bayesian/mggpo.md
              - Multi-Fidelity: api/generators/bayesian/multi_fidelity.md
              - Upper Confidence Bound: api/generators/bayesian/upper_confidence_bound.md
              - TurBO Controllers: api/generators/bayesian/turbo.md
              - Bayesian Algorithm Execution (BAX):
                  - BAX Generator: api/generators/bayesian/bax/bax_generator.md
                  - Acquisition Functions: api/generators/bayesian/bax/acquisition_functions.md
                  - Algorithms: api/generators/bayesian/bax/algorithms.md
                  - Visualization: api/generators/bayesian/bax/visualize.md
              - Model Constructors:
                  - Base Model Constructor: api/generators/bayesian/models/base_model_constructor.md
                  - Standard Model Constructor: api/generators/bayesian/models/standard_model_constructor.md
                  - Time Dependent Model Constructor: api/generators/bayesian/models/time_dependent_model_constructor.md
              - Utilities: api/generators/bayesian/utils.md
          - Genetic generators:
              - CNSGA: api/generators/ga/cnsga.md
              - NSGA-II: api/generators/ga/nsga2.md
              - DEAP Creator: api/generators/ga/deap_creator.md
              - DEAP Fitness with Constraints: api/generators/ga/deap_fitness_with_constraints.md
              - Genetic Operators: api/generators/ga/operators.md
          - Sequential generators:
              - Sequential Base Class: api/generators/sequential/sequential_generator.md
              - RCDS: api/generators/sequential/rcds.md
              - Extremum Seeking: api/generators/sequential/extremumseeking.md
              - Nelder-Mead: api/generators/sequential/neldermead.md
          - Random Generator: api/generators/random.md
          - Deduplicated Base: api/generators/deduplicated.md
          - Generator Utilities: api/generators/utils.md
      - Numerical Optimizers: api/numerical_optimizer.md
      - Stopping Conditions: api/stopping_conditions.md
      - Utilities: api/utils.md

theme:
  icon:
    repo: fontawesome/brands/github
  name: material

  custom_dir: docs/overrides
  features:
    - navigation.top
    - navigation.tabs
    - navigation.indexes
  palette:
    - media: "(prefers-color-scheme: light)"
      scheme: default
      primary: black
      toggle:
        icon: material/toggle-switch-off-outline
        name: Switch to dark mode
    - media: "(prefers-color-scheme: dark)"
      scheme: slate
      primary: black
      toggle:
        icon: material/toggle-switch
        name: Switch to light mode

markdown_extensions:
  - pymdownx.highlight
  - pymdownx.superfences
  - toc:
      permalink: true
  - pymdownx.arithmatex:
      generic: true

extra_javascript:
  # The following are for mathjax rendering of LaTeX formulas:
  - javascripts/mathjax.js
  - https://unpkg.com/mathjax@3/es5/tex-mml-chtml.js

extra:
  generator: false
  social:
    - icon: fontawesome/brands/github
      link: https://github.com/xopt-org/xopt
      name: Xopt

extra_css:
  - stylesheets/extra.css

plugins:
  - search

  - mkdocs-jupyter:
      include_source: True
      execute: False

  - mkdocstrings:
      default_handler: python
      handlers:
        python:
          options:
            filters:
              - "!^_" # exclude all members starting with _
              - "^__init__$" # but always include __init__ modules and methods
            docstring_style: numpy
            docstring_options:
              ignore_init_summary: false
            heading_level: 3
            show_bases: true
            show_source: true
            show_root_toc_entry: false
            inherited_members: true
          rendering:
            show_source: true
            show_root_heading: true

hooks:
  - docs/hooks/zip_generator.py