30 simple efficient module growth from pairtriple data#35
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realmarcin wants to merge 2 commits intomainfrom
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30 simple efficient module growth from pairtriple data#35realmarcin wants to merge 2 commits intomainfrom
realmarcin wants to merge 2 commits intomainfrom
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- Implement PairsDataLoader.build_iterative_module_internal() with alternating gene/condition expansion - Add PairsDataLoader.build_multiple_modules() for discovery attempts - Add build_iterative_module() and discover_functional_modules() MCP tools - Include comprehensive runaway growth prevention and failure analysis - Add enhanced type annotations (Set, Tuple, random import) - Register new functions with FastMCP for external access 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
- Implement PairsDataLoader.categorize_module() for fitness-based module analysis - Add statistical categorization: Growth Enhancing/Inhibiting/Neutral categories - Include variability analysis (High/Moderate/Low) and condition diversity assessment - Add PairsDataLoader.generate_module_summary() for cross-module analysis - Integrate categorization into build_iterative_module_internal() results - Enhance discover_functional_modules() with categorization_analysis section - Add numpy support with fallback calculations for statistical analysis - Include Counter type annotations for mypy compliance Features: - Primary category classification based on mean fitness values - Variability assessment using standard deviation thresholds - Condition diversity evaluation (Broad/Moderate/Narrow response) - Top conditions ranking by average absolute fitness - Summary descriptions and interpretation text - Cross-module statistical summaries with category distribution 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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