Skip to content

CHANGELOG.md

Latest commit

 

History

History
87 lines (59 loc) · 3.99 KB

CHANGELOG.md

File metadata and controls

87 lines (59 loc) · 3.99 KB

Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[0.2.0] - 2025-07-09

🎉 Major Release - Dependency Removal & Codebase Modernization

This release represents a substantial modernization of the timecorr package, removing external dependencies, improving code quality, and enhancing documentation.

🔥 Breaking Changes

  • Removed brainconn dependency: Implemented core graph theory functions directly (eigenvector centrality, PageRank, node strength) to eliminate external dependency issues
  • Cleaned up public API: Removed non-existent functions from API documentation that were causing import errors

✨ New Features

  • GitHub Actions CI/CD: Added automated testing on Python 3.8-3.11 for all pushes and pull requests
  • Enhanced documentation: All user-facing functions now have comprehensive NumPy-style docstrings with examples
  • Direct graph theory implementation: Native implementations of eigenvector_centrality_und(), pagerank_centrality(), and strengths_und()

🛠️ Improvements

  • Code formatting: Applied black and isort across entire codebase for consistent style
  • Import organization: Cleaned up import statements throughout the project
  • Documentation cleanup: Removed build artifacts and redundant files from docs/ directory
  • Tutorial enhancements: Fixed and verified all tutorial notebooks and examples
  • Test coverage: Maintained 100% test coverage with 131 passing tests

🐛 Bug Fixes

  • Fixed kernel parameter errors in Mexican Hat weights (changed 'var' to 'sigma')
  • Fixed reshape errors in applications tutorial
  • Resolved deprecation warnings by replacing np.math.pi with math.pi
  • Fixed PCA dimension errors by limiting to number of samples
  • Fixed padding logic for different array dimensions and list inputs

📚 Documentation

  • API Documentation: Updated to reflect only existing functions, removed references to non-existent ones
  • Enhanced docstrings: Added comprehensive documentation for all major user-facing functions:
    • gaussian_weights(), laplace_weights(), mexican_hat_weights(), eye_weights()
    • isfc(), autofc(), timecorr()
    • All functions now include parameter descriptions, return values, and usage examples
  • Tutorial improvements: Fixed and verified all Jupyter notebooks and Python examples
  • README updates: Enhanced with working examples and current API information

🧹 Cleanup

  • Removed outdated files: Cleaned up PNG files, temporary scripts, and build artifacts
  • Docker removal: Removed outdated Docker setup with broken notebook
  • Makefile cleanup: Removed outdated Makefile using deprecated nosetests
  • File organization: Streamlined repository structure removing unnecessary files

🔧 Development

  • Modern workflow: Transitioned from nose to pytest for testing
  • Linting: Applied comprehensive code formatting and style improvements
  • CI/CD: Automated testing pipeline for continuous integration
  • Development guide: Added CLAUDE.md for development guidance

📦 Dependencies

  • Removed: brainconn (replaced with native implementations)
  • Updated: All dependencies to supported versions
  • Simplified: Reduced external dependency footprint

🧪 Testing

  • 131 tests passing: Complete test suite with comprehensive coverage
  • Cross-platform: Verified on multiple Python versions (3.8-3.11)
  • Automated: GitHub Actions ensures tests run on every change

📈 Performance

  • Reduced dependencies: Faster installation and reduced potential conflicts
  • Native implementations: Direct graph theory calculations without external calls
  • Optimized imports: Improved import organization and reduced overhead

[0.1.7] - Previous Release

Previous functionality maintained with various bug fixes and improvements.