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SimonBlankeSimonBlanke
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add script and workflow to generate markdown page for search-space coverage
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‎.github/workflows/update-ml-parameter-docs.yml‎

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name: Update ML Parameter Coverage Documentation
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on:
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# Trigger when search data is updated
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push:
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paths:
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- 'src/surfaces/search_data/**'
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- 'collect_ml_search_data.py'
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- 'generate_parameter_coverage_docs.py'
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# Allow manual triggering
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workflow_dispatch:
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# Run weekly to check for updates
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schedule:
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- cron: '0 6 * * 1' # Every Monday at 6 AM UTC
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jobs:
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update-docs:
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runs-on: ubuntu-latest
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permissions:
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contents: write
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pull-requests: write
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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with:
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fetch-depth: 0
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: '3.9'
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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 -r requirements.txt || echo "No requirements.txt found"
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# Install package in development mode
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pip install -e .
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- name: Install additional ML dependencies
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run: |
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pip install scikit-learn numpy pandas
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- name: Check if search data exists
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id: check_data
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run: |
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if [ -d "src/surfaces/search_data" ] && [ "$(ls -A src/surfaces/search_data 2>/dev/null)" ]; then
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echo "data_exists=true" >> $GITHUB_OUTPUT
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echo "Found search data files:"
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ls -la src/surfaces/search_data/
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else
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echo "data_exists=false" >> $GITHUB_OUTPUT
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echo "No search data found"
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fi
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- name: Generate parameter coverage documentation
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run: |
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echo "Generating ML parameter coverage documentation..."
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python generate_parameter_coverage_docs.py --output docs/ML_PARAMETER_COVERAGE.md
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# Also generate JSON data for potential API usage
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python generate_parameter_coverage_docs.py --json --output docs/ml_parameter_coverage.json
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echo "Documentation generated successfully"
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- name: Check for documentation changes
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id: check_changes
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run: |
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# Create docs directory if it doesn't exist
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mkdir -p docs
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# Check if files have changed
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git add docs/ML_PARAMETER_COVERAGE.md docs/ml_parameter_coverage.json 2>/dev/null || true
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if git diff --cached --quiet; then
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echo "changes_detected=false" >> $GITHUB_OUTPUT
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echo "No changes detected in documentation"
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else
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echo "changes_detected=true" >> $GITHUB_OUTPUT
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echo "Documentation changes detected"
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# Show what changed
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echo "Changes:"
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git diff --cached --name-only
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fi
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- name: Create Pull Request
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if: steps.check_changes.outputs.changes_detected == 'true'
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uses: peter-evans/create-pull-request@v5
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with:
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token: ${{ secrets.GITHUB_TOKEN }}
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commit-message: |
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📊 Update ML parameter coverage documentation
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Auto-generated documentation update showing current parameter
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coverage for machine learning test functions.
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- Updated ML_PARAMETER_COVERAGE.md with current database status
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- Updated ml_parameter_coverage.json with raw data
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🤖 Generated with GitHub Actions
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title: "📊 Update ML Parameter Coverage Documentation"
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body: |
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## 📊 ML Parameter Coverage Documentation Update
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This PR contains automatically generated updates to the machine learning parameter coverage documentation.
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### What's Updated
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- `docs/ML_PARAMETER_COVERAGE.md` - Human-readable documentation tables
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- `docs/ml_parameter_coverage.json` - Machine-readable JSON data
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### Current Status
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${{ steps.check_data.outputs.data_exists == 'true' && '✅ Search data databases found and analyzed' || '⚠️ No search data found - documentation shows default ranges only' }}
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### How to Collect More Data
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To improve parameter coverage, run:
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```bash
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# Install dependencies
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pip install -e .
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# Collect data for all ML functions
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python collect_ml_search_data.py --all
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# Or collect for specific functions
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python collect_ml_search_data.py k_neighbors_classifier
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python collect_ml_search_data.py k_neighbors_regressor
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python collect_ml_search_data.py gradient_boosting_regressor
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```
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### Manual Trigger
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This workflow can also be triggered manually from the Actions tab if you want to update documentation after collecting new data.
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---
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🤖 **Auto-generated by GitHub Actions** • [View workflow](../actions/workflows/update-ml-parameter-docs.yml)
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branch: update-ml-docs
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delete-branch: true
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draft: false
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labels: |
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documentation
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automated
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ml-functions
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- name: Summary
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run: |
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echo "## Workflow Summary" >> $GITHUB_STEP_SUMMARY
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echo "" >> $GITHUB_STEP_SUMMARY
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if [ "${{ steps.check_data.outputs.data_exists }}" == "true" ]; then
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echo "✅ **Search data found**: Documentation generated from existing databases" >> $GITHUB_STEP_SUMMARY
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else
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echo "⚠️ **No search data found**: Documentation shows default parameter ranges only" >> $GITHUB_STEP_SUMMARY
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fi
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echo "" >> $GITHUB_STEP_SUMMARY
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if [ "${{ steps.check_changes.outputs.changes_detected }}" == "true" ]; then
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echo "📄 **Documentation updated**: A pull request has been created with the latest parameter coverage information" >> $GITHUB_STEP_SUMMARY
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else
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echo "📄 **No changes**: Documentation is already up to date" >> $GITHUB_STEP_SUMMARY
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fi
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echo "" >> $GITHUB_STEP_SUMMARY
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echo "### Files Generated" >> $GITHUB_STEP_SUMMARY
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echo "- \`docs/ML_PARAMETER_COVERAGE.md\` - User-friendly documentation" >> $GITHUB_STEP_SUMMARY
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echo "- \`docs/ml_parameter_coverage.json\` - Machine-readable data" >> $GITHUB_STEP_SUMMARY
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echo "" >> $GITHUB_STEP_SUMMARY
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echo "### Next Steps" >> $GITHUB_STEP_SUMMARY
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echo "1. Review the generated pull request if changes were detected" >> $GITHUB_STEP_SUMMARY
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echo "2. To collect more data, run \`python collect_ml_search_data.py --all\`" >> $GITHUB_STEP_SUMMARY
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echo "3. Commit any new search data to trigger automatic documentation updates" >> $GITHUB_STEP_SUMMARY

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