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ci: adding ci testing and release
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‎.github/workflows/ci.yaml

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name: numflow.py CI
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on:
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push:
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branches: [release, main]
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pull_request:
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branches: [main]
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env:
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REGISTRY: ghcr.io
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IMAGE_NAME: ${{ github.repository }}
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jobs:
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test:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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with:
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submodules: "recursive"
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- name: Set up Python 3.11
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uses: actions/setup-python@v3
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with:
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python-version: 3.11
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install pytest pytest-cov
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- name: Build numflow.py package
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run: |
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pip install .
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pip install numpy
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- name: Test with pytest
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run: |
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pytest ./tests/* --cov=numflow
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- name: Upload to Coveralls
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env:
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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COVERALLS_REPO_TOKEN: ${{ secrets.COVERALLS_TOKEN }}
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run: |
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pip install coveralls
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coveralls
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make-wheels:
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name: Make ${{ matrix.os }} wheels
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if: github.event_name == 'push' && contains(github.ref, 'release')
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needs: test
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runs-on: ${{ matrix.os }}
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strategy:
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fail-fast: false
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matrix:
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os: ["macos-latest", "ubuntu-latest", "windows-latest"]
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steps:
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- name: "Checkout repo"
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uses: actions/checkout@v3
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with:
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submodules: "recursive"
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- name: "Build wheels"
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uses: pypa/cibuildwheel@v2.9.0
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- name: Verify clean directory
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run: git diff --exit-code
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shell: bash
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- name: "Upload wheel as artifact"
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uses: actions/upload-artifact@v3
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with:
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name: artifact-${{ matrix.os }}-wheel
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path: ./wheelhouse/*.whl
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make-sdist:
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name: Make source distribution
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if: github.event_name == 'push' && contains(github.ref, 'release')
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needs: test
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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with:
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submodules: "recursive"
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- name: Build SDist
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run: pipx run build --sdist
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- name: Check metadata
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run: pipx run twine check dist/*
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- uses: actions/upload-artifact@v3
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with:
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name: artifact-source-dist
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path: dist/*.tar.gz
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tag-and-release:
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name: Tag commit and create a release
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needs: [make-wheels, make-sdist]
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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with:
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submodules: "recursive"
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- name: Set up Python 3.11
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uses: actions/setup-python@v3
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with:
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python-version: 3.11
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install scikit-build
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- name: "Get release version"
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run: |
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CURRENT_VERSION=$(python3 setup.py --version | tail -1)
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echo "Current version: $CURRENT_VERSION"
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echo "CURRENT_VERSION=v$CURRENT_VERSION" >> $GITHUB_ENV
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- uses: rickstaa/action-create-tag@v1
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with:
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tag: ${{ env.CURRENT_VERSION }}
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- uses: ncipollo/release-action@v1
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with:
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token: ${{ secrets.GITHUB_TOKEN }}
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generateReleaseNotes: true
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tag: ${{ env.CURRENT_VERSION }}
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upload:
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name: Upload to PyPI
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needs: tag-and-release
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runs-on: ubuntu-latest
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environment:
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name: pypi
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url: https://pypi.org/p/numflow
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permissions:
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id-token: write
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steps:
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- name: Download all artifacts
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uses: actions/download-artifact@v3
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with:
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path: dist
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- name: Copy artifacts to dist/ folder
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run: |
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echo "* Downloaded artifacts:"
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ls dist/
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cd dist/
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echo "* Copying artifacts to dist/ folder:"
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find . -mindepth 2 -maxdepth 2 -type f -print -exec mv {} . \;
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echo "* Deleting empty directories:"
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find . -maxdepth 1 -type d -empty -print -exec rmdir {} +
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cd ..
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echo "* Prepared artifacts:"
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ls dist/
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- name: Publish package distributions to PyPI
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uses: pypa/gh-action-pypi-publish@release/v1

‎.github/workflows/wheel.yaml

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name: "Create Python distributions"
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on:
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workflow_dispatch: {}
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jobs:
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make-wheels:
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name: Make ${{ matrix.os }} wheels
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runs-on: ${{ matrix.os }}
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strategy:
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fail-fast: false
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matrix:
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os: ["macos-latest", "ubuntu-latest", "windows-latest"]
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steps:
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- name: "Checkout repo"
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uses: actions/checkout@v3
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with:
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submodules: "recursive"
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- name: "Build wheels"
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uses: pypa/cibuildwheel@v2.9.0
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- name: Verify clean directory
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run: git diff --exit-code
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shell: bash
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- name: "Upload wheel as artifact"
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uses: actions/upload-artifact@v3
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with:
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name: artifact-${{ matrix.os }}-wheel
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path: ./wheelhouse/*.whl
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make-sdist:
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name: Make source distribution
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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with:
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submodules: "recursive"
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- name: Build SDist
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run: pipx run build --sdist
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- name: Check metadata
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run: pipx run twine check dist/*
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- uses: actions/upload-artifact@v3
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with:
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name: artifact-source-dist
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path: dist/*.tar.gz
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upload:
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name: Checkout Artifacts
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needs: [make-wheels, make-sdist]
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runs-on: ubuntu-latest
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steps:
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- name: Download all artifacts
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uses: actions/download-artifact@v3
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with:
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path: dist
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- name: Copy artifacts to dist/ folder
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run: |
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echo "* Downloaded artifacts:"
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ls dist/
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cd dist/
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echo "* Copying artifacts to dist/ folder:"
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find . -mindepth 2 -maxdepth 2 -type f -print -exec mv {} . \;
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echo "* Deleting empty directories:"
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find . -maxdepth 1 -type d -empty -print -exec rmdir {} +
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cd ..
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echo "* Prepared artifacts:"
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ls dist/

‎README.md

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C++ based tool for converting vector field data into models for rendering.
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I made a [blogpost describing the design, there are also some outputs, see more here!](https://vojtatom.github.io/numflow.py)
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## Dev
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Developing the package on localhost is recommanded in devcontainer - see `.devcontainer` folder.

‎tests/test_kernels.py

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field = dataset_kernel(rectilinear_csv_data)
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points = points_kernel([0.1, 0.1, -10], [60, 60, -10], [10, 10, 1])
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glyphs = glyph_kernel(field, points)
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assert glyphs.shape == (100, 3)
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assert np.shape(glyphs) == (100, 3)
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def test_streamline_kernel(rectilinear_csv_data: str):
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field = dataset_kernel(rectilinear_csv_data)
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points = points_kernel([0.1, 0.1, -10], [60, 60, -10], [10, 10, 1])
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streamlines = stream_kernel(field, points, 0, 10)
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assert len(streamlines.l()) == 100
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assert np.shape(streamlines.l()) == (100,)
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assert len(streamlines.t()) == sum(streamlines.l())
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assert len(streamlines.y()) == sum(streamlines.l()) * 3
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assert len(streamlines.f()) == sum(streamlines.l()) * 3
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assert np.shape(streamlines.t()) == (sum(streamlines.l()),)
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assert len(streamlines.y()) == sum(streamlines.l())
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assert np.shape(streamlines.y()) == (sum(streamlines.l()), 3)
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assert len(streamlines.f()) == sum(streamlines.l())
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assert np.shape(streamlines.f()) == (sum(streamlines.l()), 3)
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‎tests/test_visualization.py

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from numflow.compute import RectilinearField3D
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from numflow import Dataset, Visualization, points, random_points
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import json
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import base64
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import numpy as np
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import math
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def nround(x, base=5):
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return base * math.ceil(x/base)
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def test_visualization(rectilinear_csv_data: str):
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dataset = Dataset(rectilinear_csv_data)
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assert dataset.file_name == rectilinear_csv_data
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assert type(dataset.data) == RectilinearField3D
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dataset_name = "rectilinear.csv"
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size = "Size: 72000 elements"
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shape = "Shape: 60 x 60 x 20"
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memory = "Memory consumed: 288000 bytes"
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x_range = "X range: 0.100000 - 60.000000"
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y_range = "Y range: 0.100000 - 60.000000"
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z_range = "Z range: -20.000000 - 0.500000"
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info = dataset.info().split("\n")
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assert info[0][-len(dataset_name):] == dataset_name
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assert info[1] == size
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assert info[2] == shape
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assert info[3] == memory
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assert info[4] == x_range
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assert info[5] == y_range
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assert info[6] == z_range
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layer_z = -10
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vis = Visualization()
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layer = points([0.1, 0.1, layer_z], [60, 60, layer_z], [1000, 1000, 1])
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vis.layer(dataset, layer)
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layerS = points([0.1, 0.1, layer_z], [60, 60, layer_z], [200, 200, 1])
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vis.streamlines(dataset, layerS, tbound=0.01, size=0.2, appearance='transparent', sampling=3, divisions=3)
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vis.glphys(dataset, layer, size=0.2, appearance='transparent')
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vis.save(f"test.flow")
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json_file = open("test.flow")
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data = json.load(json_file)
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json_file.close()
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# there is only one scene
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assert len(data) == 1
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scene = data[0]
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assert len(scene) == 4
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glyph = scene['glyphs']
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layer = scene['layer']
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streamlines = scene['streamlines']
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stats = scene['stats']
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# test glyphs
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# there is only one glyph group
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assert len(glyph) == 1
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glyph_group = glyph[0]
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assert set(glyph_group.keys()) == {'meta', 'points', 'values'}
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gpoints = glyph_group['points']
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gvalues = glyph_group['values']
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# expected size of glyphs is (1000 * 1000 * 3 * 4) bytes
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# also add the base64 encoding - 4/3 * size = 16000000
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assert len(gpoints) == 16000000
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assert len(gvalues) == 16000000
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# test layer
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# there is only one layer group
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assert len(layer) == 1
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layer_group = layer[0]
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assert set(layer_group.keys()) == {'meta', 'values', 'points'}
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lpoints = layer_group['points']
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lvalues = layer_group['values']
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# expected size of layer is (1000 * 1000 * 3 * 4) bytes
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# also add the base64 encoding - 4/3 * size = 16000000
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assert len(lpoints) == nround(1000 * 1000 * 3 * 4 * 4 / 3, 4)
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assert len(lvalues) == nround(1000 * 1000 * 3 * 4 * 4 / 3, 4)
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# test streamlines
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# there is only one streamlines group
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assert len(streamlines) == 1
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streamlines_group = streamlines[0]
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assert set(streamlines_group.keys()) == {'values', 'times', 'meta', 'lengths', 'points'}
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spoints = streamlines_group['points']
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svalues = streamlines_group['values']
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stimes = streamlines_group['times']
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slengths = streamlines_group['lengths']
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# expected size of lengths is (200 * 200 * 4) bytes
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# also add the base64 encoding - 4/3 * size =~ 213336 with corrections
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assert len(slengths) == nround(200 * 200 * 4 * 4 / 3, 4)
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#decode lengths and sum total
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lengths = base64.b64decode(slengths)
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lengths = np.frombuffer(lengths, dtype=np.int32)
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sum_length = np.sum(lengths)
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expected_point_size = nround(sum_length * 3 * 4 * 4 / 3, 4)
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assert len(spoints) == expected_point_size
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assert len(svalues) == expected_point_size
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expected_time_size = nround(sum_length * 4 * 4 / 3, 4)
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assert len(stimes) == expected_time_size
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# test stats
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assert set(stats.keys()) == {'points', 'values'}
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spoints = stats['points']
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svalues = stats['values']
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# expected statistical keys
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assert set(spoints.keys()) == {'max', 'center', 'min', 'scale_factor'}
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assert set(svalues.keys()) == {'y', 'x', 'z', 'xyz'}
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