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‎.github/workflows/test.yml

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name: pytest
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on:
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pull_request:
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push:
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branches: [main]
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paths:
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- ".github/workflows/*"
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- "pymc_experimental/**"
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- "setup.py"
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- "pyproject.toml"
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- "buildosx"
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- "conda-envs/**"
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- "codecov.yml"
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jobs:
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ubuntu:
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strategy:
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matrix:
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os: [ubuntu-18.04]
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floatx: [float32, float64]
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fail-fast: false
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runs-on: ${{ matrix.os }}
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env:
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TEST_SUBSET: ${{ matrix.test-subset }}
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AESARA_FLAGS: floatX=${{ matrix.floatx }},gcc__cxxflags='-march=native'
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defaults:
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run:
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shell: bash -l {0}
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steps:
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- uses: actions/checkout@v2
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- name: Cache conda
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uses: actions/cache@v1
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env:
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# Increase this value to reset cache if environment-test-py38.yml has not changed
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CACHE_NUMBER: 0
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with:
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path: ~/conda_pkgs_dir
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key: ${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-${{
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hashFiles('conda-envs/environment-test-py38.yml') }}
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- name: Cache multiple paths
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uses: actions/cache@v2
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env:
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# Increase this value to reset cache if requirements.txt has not changed
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CACHE_NUMBER: 0
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with:
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path: |
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~/.cache/pip
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$RUNNER_TOOL_CACHE/Python/*
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~\AppData\Local\pip\Cache
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key: ${{ runner.os }}-build-${{ matrix.python-version }}-${{
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hashFiles('requirements.txt') }}
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- uses: conda-incubator/setup-miniconda@v2
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with:
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miniforge-variant: Mambaforge
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miniforge-version: latest
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mamba-version: "*"
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activate-environment: pymc-test-py38
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channel-priority: strict
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environment-file: conda-envs/environment-test-py38.yml
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use-mamba: true
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use-only-tar-bz2: true # IMPORTANT: This needs to be set for caching to work properly!
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- name: Install-pymc
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run: |
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conda activate pymc-test-py38
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pip install -e .
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python --version
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- name: Run tests
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run: |
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conda activate pymc-test-py38
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python -m pytest -vv --cov=pymc_experimental --cov-append --cov-report=xml --cov-report term --durations=50 $TEST_SUBSET
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- name: Upload coverage to Codecov
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uses: codecov/codecov-action@v2
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with:
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env_vars: TEST_SUBSET
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name: ${{ matrix.os }} ${{ matrix.floatx }}
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fail_ci_if_error: false
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windows:
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strategy:
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matrix:
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os: [windows-latest]
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floatx: [float32, float64]
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fail-fast: false
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runs-on: ${{ matrix.os }}
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env:
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TEST_SUBSET: ${{ matrix.test-subset }}
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AESARA_FLAGS: floatX=${{ matrix.floatx }},gcc__cxxflags='-march=core2'
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defaults:
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run:
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shell: cmd
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steps:
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- uses: actions/checkout@v2
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- name: Cache conda
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uses: actions/cache@v1
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env:
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# Increase this value to reset cache if conda-envs/environment-test-py37.yml has not changed
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CACHE_NUMBER: 0
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with:
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path: ~/conda_pkgs_dir
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key: ${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-${{
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hashFiles('conda-envs/windows-environment-test-py37.yml') }}
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- name: Cache multiple paths
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uses: actions/cache@v2
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env:
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# Increase this value to reset cache if requirements.txt has not changed
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CACHE_NUMBER: 0
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with:
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path: |
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~/.cache/pip
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$RUNNER_TOOL_CACHE/Python/*
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~\AppData\Local\pip\Cache
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key: ${{ runner.os }}-build-${{ matrix.python-version }}-${{
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hashFiles('requirements.txt') }}
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- uses: conda-incubator/setup-miniconda@v2
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with:
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miniforge-variant: Mambaforge
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miniforge-version: latest
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mamba-version: "*"
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activate-environment: pymc-test-py37
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channel-priority: strict
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environment-file: conda-envs/windows-environment-test-py37.yml
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use-mamba: true
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use-only-tar-bz2: true # IMPORTANT: This needs to be set for caching to work properly!
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- name: Install-pymc
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run: |
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conda activate pymc-test-py37
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pip install -e .
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python --version
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- name: Run tests
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# This job uses a cmd shell, therefore the environment variable syntax is different!
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# The ">-" in the next line replaces newlines with spaces (see https://stackoverflow.com/a/66809682).
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run: >-
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conda activate pymc-test-py37 &&
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python -m pytest -vv --cov=pymc_experimental --doctest-modules pymc_experimental --cov-append --cov-report=xml --cov-report term --durations=50 %TEST_SUBSET%
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- name: Upload coverage to Codecov
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uses: codecov/codecov-action@v2
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with:
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env_vars: TEST_SUBSET
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name: ${{ matrix.os }} ${{ matrix.floatx }}
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fail_ci_if_error: false

‎.gitignore

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*.pyc
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*.sw[op]
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examples/*.png
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nb_examples/
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nb_tutorials/
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build/*
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dist/*
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*.egg-info/
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.ipynb_checkpoints
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tmtags
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tags
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.DS_Store
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.cache
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# IntelliJ IDE
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.idea
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*.iml
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# Sphinx
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_build
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docs/jupyter_execute
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docs/.jupyter_cache
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docs/**/generated/*
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# Merge tool
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*.orig
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# Docker development
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# notebooks/
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# air speed velocity (asv)
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benchmarks/env/
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benchmarks/html/
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benchmarks/results/
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.pytest_cache/
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# Visual Studio / VSCode
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.vs/
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.vscode/
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.mypy_cache
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pytestdebug.log
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.dir-locals.el
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.pycheckers
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# Codespaces
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pythonenv*

‎.gitpod.yml

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tasks:
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- name: initialize
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init: |
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mkdir -p .vscode
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mkdir -p ~/.local/bin/
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echo '{"python.defaultInterpreterPath": "/home/gitpod/micromamba/envs/pymc-test-py39/bin/python"}' > .vscode/settings.json
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curl -Ls https://micro.mamba.pm/api/micromamba/linux-64/latest | tar -xvj -C ~/.local/ bin/micromamba
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~/.local/bin/micromamba shell init -s bash -p ~/micromamba
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source ~/.bashrc
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micromamba create -yf conda-envs/environment-test-py39.yml
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pip install -r requirements-dev.txt
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command: |
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micromamba activate pymc-test-py39
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pip install -e .
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vscode:
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extensions:
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- eamodio.gitlens
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- ms-python.python
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github:
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prebuilds:
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# enable for master branch
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master: true
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# enable for other branches (defaults to false)
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branches: true
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# enable for pull requests coming from this repo (defaults to true)
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pullRequests: true
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# enable for pull requests coming from forks (defaults to false)
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pullRequestsFromForks: false
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# add a check to pull requests (defaults to true)
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addCheck: true
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# add a "Review in Gitpod" button as a comment to pull requests (defaults to false)
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addComment: false
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# add a "Review in Gitpod" button to the pull request's description (defaults to false)
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addBadge: false
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# add a label once the prebuild is ready to pull requests (defaults to false)
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addLabel: false

‎.readthedocs.yaml

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# Read the Docs configuration file
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# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
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version: 2
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build:
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os: ubuntu-20.04
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tools:
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python: "3.9"
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python:
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install:
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- requirements: requirements-docs.txt
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- requirements: requirements.txt
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- method: pip
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path: .

‎CODE_OF_CONDUCT.md

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# PyMC Code of Conduct
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## Our Pledge
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In the interest of fostering an open and welcoming environment, we as
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contributors and maintainers pledge to making participation in our project and
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our community a harassment-free experience for everyone, regardless of age, body
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size, disability, ethnicity, sex characteristics, gender identity and expression,
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level of experience, education, socio-economic status, nationality, personal
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appearance, race, religion, or sexual identity and orientation.
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## Our Standards
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Examples of behavior that contributes to creating a positive environment
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include:
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* Using welcoming and inclusive language
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* Being respectful of differing viewpoints and experiences
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* Gracefully accepting constructive criticism
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* Focusing on what is best for the community
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* Showing empathy towards other community members
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Examples of unacceptable behavior by participants include:
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* The use of sexualized language or imagery and unwelcome sexual attention or
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advances
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* Trolling, insulting/derogatory comments, and personal or political attacks
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* Public or private harassment
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* Publishing others' private information, such as a physical or electronic
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address, without explicit permission
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* Other conduct which could reasonably be considered inappropriate in a
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professional setting
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## Our Responsibilities
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Project maintainers are responsible for clarifying the standards of acceptable
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behavior and are expected to take appropriate and fair corrective action in
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response to any instances of unacceptable behavior.
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Project maintainers have the right and responsibility to remove, edit, or
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reject comments, commits, code, wiki edits, issues, and other contributions
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that are not aligned to this Code of Conduct, or to ban temporarily or
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permanently any contributor for other behaviors that they deem inappropriate,
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threatening, offensive, or harmful.
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## Scope
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This Code of Conduct applies both within project spaces and in public spaces
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when an individual is representing the project or its community. Examples of
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representing a project or community include using an official project e-mail
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address, posting via an official social media account, or acting as an appointed
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representative at an online or offline event. Representation of a project may be
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further defined and clarified by project maintainers.
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## Enforcement
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Instances of abusive, harassing, or otherwise unacceptable behavior may be
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reported by contacting PyMC developer Christopher Fonnesbeck via email
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(chris.fonnesbeck@vanderbilt.edu) or phone (615-955-0380). Alternatively, you
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may also contact NumFOCUS Executive Director Leah Silen (512-222-5449) or
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fill an anonymous report using [NumFOCUS Typeform](https://numfocus.typeform.com/to/ynjGdT).
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As PyMC is a member of NumFOCUS and subscribes to their code of conduct as a
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precondition for continued membership. All complaints will be reviewed and
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investigated and will result in a response that is deemed necessary and
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appropriate to the circumstances. The project team is obligated to maintain
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confidentiality with regard to the reporter of an incident. Further details of
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specific enforcement policies may be posted separately.
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Project maintainers who do not follow or enforce the Code of Conduct in good
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faith may face temporary or permanent repercussions as determined by other
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members of the project's leadership.
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## Attribution
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This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4,
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available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html
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[homepage]: https://www.contributor-covenant.org

‎CONTRIBUTING.md

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# Contributing guide
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Page in construction, for now go to https://github.com/pymc-devs/pymc-experimental#questions.

‎README.md

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# Proposal: `pymc-experimental` repository
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# Welcome to `pymc-experimental`
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<a href="https://gitpod.io/#https://github.com/pymc-devs/pymc-experimental">
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<img
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src="https://img.shields.io/badge/Contribute%20with-Gitpod-908a85?logo=gitpod"
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alt="Contribute with Gitpod"
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/>
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</a>
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As PyMC continues to mature and expand its functionality to accomodate more domains of application, we increasingly see cutting-edge methodologies, highly specialized statistical distributions, and complex models appear. While this adds to the functinoality and relevance of the project, it can also introduce instability and impose a burden on testing and quality control. To help address this, a `pymc-experimental` respository could act as a home for new additions to PyMC, which may include unusual probability distribitions, advanced model fitting algorithms, or any code that may be inappropriate to include in the `pymc` repository, but may want to be made available to users.
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As PyMC continues to mature and expand its functionality to accommodate more domains of application, we increasingly see cutting-edge methodologies, highly specialized statistical distributions, and complex models appear.
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While this adds to the functionality and relevance of the project, it can also introduce instability and impose a burden on testing and quality control.
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To reduce the burden on the main `pymc` repository, this `pymc-experimental` repository can become the aggregator and testing ground for new additions to PyMC.
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This may include unusual probability distributions, advanced model fitting algorithms, innovative yet not fully tested methods or any code that may be inappropriate to include in the `pymc` repository, but may want to be made available to users.
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If implemented thoughtfully, a `pymc-experimental` repository could act as the first step in the PyMC development pipeline, where all novel code is introduced until it is obvious that it belongs in the main repository. This would improve the stability and streamline the testing overhead of the `pymc` respository.
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The `pymc-experimental` repository can be understood as the first step in the PyMC development pipeline, where all novel code is introduced until it is obvious that it belongs in the main repository.
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We hope that this organization improves the stability and streamlines the testing overhead of the `pymc` repository, while allowing users and developers to test and evaluate cutting-edge methods and not yet fully mature features.
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`pymc-experimental` would be designed to mirror the namespaces in `pymc` to make usage and migration as easy as possible. For example, a `ParabolicFractal` distribution could be used analogously to those in `pymc`:
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`pymc-experimental` would be designed to mirror the namespaces in `pymc` to make usage and migration as easy as possible.
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For example, a `ParabolicFractal` distribution could be used analogously to those in `pymc`:
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```python
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import pymc as pm
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### What belongs in `pymc-experimental`?
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- newly-implemented statistical methodologies
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- newly-implemented statistical methods, for example step methods or model construction helpers
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- distributions that are tricky to sample from or test
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- infrequently-used fitting methods or distributions
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- any code that requires additional optimization before it can be used in practice
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### What does not belong in `pymc-experimental`?
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### Should `pymc-experimental` be a submodule?
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- Case studies
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- Implementations that cannot be applied generically, for example because they are tied to variables from a toy example
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### Should there be more than one add-on repository?
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Since there is a lot of code that we may not want in the main repository, does it make sense to have more than one additional repository? For exmaple, `pymc-experimental` may just include methods that are not fully developed, tested and trusted, while code that is known to work well and has adequate test coverage could reside in a `pymc-extras` (or similar) repository.
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Since there is a lot of code that we may not want in the main repository, does it make sense to have more than one additional repository?
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For example, `pymc-experimental` may just include methods that are not fully developed, tested and trusted, while code that is known to work well and has adequate test coverage, but is still too specialized to become part of `pymc` could reside in a `pymc-extras` (or similar) repository.
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### How can we minimize the additional burden of additional project repositories?
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### Unanswered questions & ToDos
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This project is still young and many things have not been answered or implemented.
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Please get involved!
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* What are guidlines for organizing submodules?
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* Proposal: No default imports of WIP/unstable submodules. By importing manually we can avoid breaking the package if a submodule breaks, for example because of an updated dependency.
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* How can we minimize the additional burden of additional project repositories?
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* ToDo: Setting up a basic CI pipeline

‎buildosx

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#!/bin/sh
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export CFLAGS="-arch x86_64"
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export FFLAGS="-static -ff2c -arch x86_64"
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export LDFLAGS="-Wall -undefined dynamic_lookup -bundle -arch x86_64"
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rm -rf build
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python setupegg.py bdist_egg

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