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apoorvalalapoorvalal
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add FEs and some tests
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‎.github/workflows/comprehensive-tests.yml‎

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name: Comprehensive Tests
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on:
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push:
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branches: [ "*" ]
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pull_request:
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branches: [ "*" ]
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schedule:
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# Run tests weekly on Sundays at 2 AM UTC
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- cron: '0 2 * * 0'
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jobs:
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test-matrix:
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name: Test Python ${{ matrix.python-version }} on ${{ matrix.os }}
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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: [ubuntu-latest, macos-latest]
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python-version: ["3.9", "3.10", "3.11", "3.12"]
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exclude:
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# Skip some combinations to reduce CI time
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- os: macos-latest
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python-version: "3.9"
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- os: macos-latest
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python-version: "3.10"
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steps:
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- name: Checkout code
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uses: actions/checkout@v4
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v4
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with:
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python-version: ${{ matrix.python-version }}
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- name: Cache pip dependencies
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uses: actions/cache@v3
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with:
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path: ~/.cache/pip
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key: ${{ runner.os }}-pip-${{ matrix.python-version }}-${{ hashFiles('pyproject.toml') }}
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restore-keys: |
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${{ runner.os }}-pip-${{ matrix.python-version }}-
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${{ runner.os }}-pip-
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- name: Install system dependencies (Ubuntu)
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if: matrix.os == 'ubuntu-latest'
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run: |
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sudo apt-get update
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sudo apt-get install -y build-essential
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- name: Install Python dependencies
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run: |
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python -m pip install --upgrade pip wheel setuptools
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pip install pytest pytest-cov pytest-xdist
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- name: Install jaxonometrics
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run: |
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pip install -e .
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- name: Install test dependencies
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run: |
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pip install pyfixest pandas
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- name: Verify installation
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run: |
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python -c "import jaxonometrics; print('jaxonometrics version:', jaxonometrics.__version__)"
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python -c "import jax; print('JAX version:', jax.__version__)"
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python -c "import pyfixest; print('pyfixest available')"
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- name: Run basic tests
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run: |
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python -m pytest tests/test_linear.py -v
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- name: Run fixed effects tests
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run: |
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python -m pytest tests/test_fe.py -v
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- name: Run all tests with coverage
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run: |
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python -m pytest tests/ -v --cov=jaxonometrics --cov-report=xml --cov-report=term
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- name: Upload coverage to Codecov
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if: matrix.python-version == '3.11' && matrix.os == 'ubuntu-latest'
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uses: codecov/codecov-action@v3
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with:
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file: ./coverage.xml
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flags: unittests
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name: codecov-umbrella
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test-performance:
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name: Performance Tests
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runs-on: ubuntu-latest
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steps:
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- name: Checkout code
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uses: actions/checkout@v4
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- name: Set up Python 3.11
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uses: actions/setup-python@v4
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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-benchmark
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pip install -e .
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pip install pyfixest pandas
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- name: Run performance benchmarks
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run: |
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python -c "
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import numpy as np
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import time
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import jax.numpy as jnp
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from jaxonometrics import LinearRegression
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# Performance test
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print('Running performance test...')
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np.random.seed(42)
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n_obs = 10000
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X = jnp.asarray(np.random.randn(n_obs, 5))
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y = jnp.asarray(np.random.randn(n_obs))
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model = LinearRegression(solver='lineax')
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start_time = time.time()
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model.fit(X, y)
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end_time = time.time()
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print(f'Linear regression on {n_obs} obs took {end_time - start_time:.4f} seconds')
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print('Performance test passed!')
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"
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test-examples:
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name: Test Examples and Documentation
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runs-on: ubuntu-latest
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steps:
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- name: Checkout code
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uses: actions/checkout@v4
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- name: Set up Python 3.11
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uses: actions/setup-python@v4
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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 jupyter nbconvert
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pip install -e .
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pip install pyfixest pandas matplotlib seaborn
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- name: Test example notebooks (if any)
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run: |
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# Test any Jupyter notebooks in nb/ directory
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if [ -d "nb" ]; then
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echo "Testing notebooks..."
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for notebook in nb/*.ipynb; do
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if [ -f "$notebook" ]; then
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echo "Testing $notebook"
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jupyter nbconvert --to script --execute "$notebook"
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fi
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done
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else
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echo "No notebooks directory found, skipping notebook tests"
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fi
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- name: Test README examples
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run: |
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python -c "
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# Test basic API examples from README
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import numpy as np
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import jax.numpy as jnp
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from jaxonometrics import LinearRegression
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print('Testing basic LinearRegression API...')
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# Generate sample data
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np.random.seed(42)
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X = jnp.asarray(np.random.randn(100, 3))
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y = jnp.asarray(np.random.randn(100))
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# Test basic fitting
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model = LinearRegression(solver='lineax')
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model.fit(X, y)
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# Test prediction
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y_pred = model.predict(X)
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print(f'Coefficients shape: {model.params[\"coef\"].shape}')
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print(f'Predictions shape: {y_pred.shape}')
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print('README examples test passed!')
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"

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