release.yaml

name: CI
on:
  push:
  pull_request:
    # branches:
    #   - main
  
jobs:
  format:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: psf/black@stable 
  lint:
    name: Lint with flake8
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - uses: actions/setup-python@v5
        with:
          python-version: "3.11"
      - name: Install flake8
        run: pip install flake8 flake8-bugbear
      - name: Lint with flake8  
        run: flake8 src
  # legacy testing of t-test
  run-tutorial-ttest:
    name: Run - random_small - t-test
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: "3.11"
      - name: Install dependencies
        run: pip install .
      - name: Prepare tutorial data
        run: |
          cd tutorial
          move-dl data=random_small task=encode_data --cfg job
          move-dl data=random_small task=encode_data
          # - name: Identify associations - t-test
      # at least 4 refits needed for t-test
      - name: Identify associations - t-test
        run: |
          cd tutorial
          move-dl data=random_small task=random_small__id_assoc_ttest --cfg job
          move-dl data=random_small task=random_small__id_assoc_ttest task.training_loop.num_epochs=30 task.num_refits=4
  # categorical dataset pertubation - single and multiprocessed
  run-tutorial-cat-pert-single:
    name: Run - random_small - singleprocess
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: "3.11"
      - name: Install dependencies
        run: pip install .
      - name: Prepare tutorial data
        run: |
          cd tutorial
          move-dl data=random_small task=encode_data --cfg job
          move-dl data=random_small task=encode_data
      - name: Train model and analyze latent space
        run: |
          cd tutorial
          move-dl data=random_small task=random_small__latent --cfg job
          move-dl data=random_small task=random_small__latent task.training_loop.num_epochs=100
      - name: Identify associations - bayes factors
        run: |
          cd tutorial
          move-dl data=random_small task=random_small__id_assoc_bayes --cfg job
          move-dl data=random_small task=random_small__id_assoc_bayes task.training_loop.num_epochs=100 task.num_refits=2
      - name: Identify associations - bayes factors - w/o training
        run: |
          cd tutorial
          move-dl data=random_small task=random_small__id_assoc_bayes --cfg job
          move-dl data=random_small task=random_small__id_assoc_bayes task.training_loop.num_epochs=100 task.num_refits=2
  run-tutorial-cat-pert-multi:
    name: Run - random_small - multiprocess
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: "3.11"
      - name: Install dependencies
        run: pip install .
      - name: Prepare tutorial data
        run: |
          cd tutorial
          move-dl data=random_small task=encode_data --cfg job
          move-dl data=random_small task=encode_data
      - name: Train model and analyze latent space - multiprocess
        run: |
          cd tutorial
          move-dl data=random_small task=random_small__latent --cfg job
          move-dl data=random_small task=random_small__latent task.training_loop.num_epochs=100 task.multiprocess=true
      - name: Identify associations - bayes factors - multiprocess
        run: |
          cd tutorial
          move-dl data=random_small task=random_small__id_assoc_bayes --cfg job
          move-dl data=random_small task=random_small__id_assoc_bayes task.training_loop.num_epochs=100 task.num_refits=2 task.multiprocess=true
      - name: Identify associations - bayes factors - multiprocess w/o training
        run: |
          cd tutorial
          move-dl data=random_small task=random_small__id_assoc_bayes --cfg job
          move-dl data=random_small task=random_small__id_assoc_bayes task.training_loop.num_epochs=100 task.num_refits=2 task.multiprocess=true
  # continous dataset perturbation - single and multiprocessed
  run-tutorial-cont-pert-multi:
    name: Run - random_continuous - multiprocess
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: "3.11"
      - name: Install dependencies
        run: pip install .
      - name: Prepare tutorial data
        run: |
          cd tutorial
          move-dl data=random_continuous task=encode_data --cfg job
          move-dl data=random_continuous task=encode_data
      - name: Train model and analyze latent space - multiprocess
        run: |
          cd tutorial
          move-dl data=random_continuous task=random_continuous__latent task.multiprocess=true --cfg job
          move-dl data=random_continuous task=random_continuous__latent task.multiprocess=true
      - name: Identify associations - bayes factors - multiprocess
        run: |
          cd tutorial
          move-dl data=random_continuous task=random_continuous__id_assoc_bayes task.multiprocess=true --cfg job
          move-dl data=random_continuous task=random_continuous__id_assoc_bayes task.num_refits=1 task.multiprocess=true
      - name: Identify associations - bayes factors - multiprocess w/o training
        run: |
          cd tutorial
          move-dl data=random_continuous task=random_continuous__id_assoc_bayes task.multiprocess=true --cfg job
          move-dl data=random_continuous task=random_continuous__id_assoc_bayes task.num_refits=1 task.multiprocess=true
  run-tutorial-cont-pert-single:
      name: Run - random_continuous - singleprocess
      runs-on: ubuntu-latest
      steps:
        - uses: actions/checkout@v4
        - uses: actions/setup-python@v5
          with:
            python-version: "3.11"
        - name: Install dependencies
          run: pip install .
        - name: Prepare tutorial data
          run: |
            cd tutorial
            move-dl data=random_continuous task=encode_data
        - name: Train model and analyze latent space
          run: |
            cd tutorial
            move-dl data=random_continuous task=random_continuous__latent --cfg job
            move-dl data=random_continuous task=random_continuous__latent
        - name: Identify associations - bayes factors
          run: |
            cd tutorial
            move-dl data=random_continuous task=random_continuous__id_assoc_bayes --cfg job
            move-dl data=random_continuous task=random_continuous__id_assoc_bayes task.num_refits=1
        - name: Identify associations - bayes factors - w/o training (repeat)
          run: |
            cd tutorial
            move-dl data=random_continuous task=random_continuous__id_assoc_bayes --cfg job
            move-dl data=random_continuous task=random_continuous__id_assoc_bayes task.num_refits=1
        # this reuses the same model trained in analyze latent space
        - name: Identify associations - KS
          run: |
            cd tutorial
            move-dl data=random_continuous task=random_continuous__id_assoc_ks --cfg job
            move-dl data=random_continuous task=random_continuous__id_assoc_ks task.num_refits=1
    
  publish:
    name: Publish package
    runs-on: ubuntu-latest
    if: startsWith(github.ref, 'refs/tags')
    needs:
      - format
      - lint
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: "3.11"
      - name: Install twine and build
        run: python -m pip install --upgrade twine build
      - name: Build
        run: python -m build
      - name: Publish package  
        uses: pypa/gh-action-pypi-publish@release/v1
        with:
          user: __token__
          password: ${{ secrets.PYPI_API_TOKEN }}