v1.2.1

HERA

HERA is a robust MATLAB toolbox designed for the scientific benchmarking of clustered data. It offers hierarchical-compensatory ranking logic, advanced effect-size statistics, and automated reporting capabilities.

For more information please refer to the Readme and Project Documentation.

What's New in v1.2.1? (Minor Update)

This patch release improves the transparency and extensibility of the HERA ecosystem by including the complete deployment infrastructure within the toolbox. It also includes an important robustness improvement for ranking calculations.

Note: Since v1.2.1 is a fast-follow update, the features from v1.2.0 are included below to provide a complete overview of the recent upgrades.

📦 Enhanced Packaging

• Deployment Scripts Included: The MATLAB toolbox now includes all deploy/ scripts (e.g., build_HERA_matlab.m, build_HERA_python.m), allowing users to inspect the build process or recreate the standalone runtime, Python package and MATLAB toolbox locally.

🔧 Bug Fixes & Improvements

• Ranking Robustness: Added epsilon-based floating-point comparisons in calculate_ranking.m to prevent potential ranking instabilities caused by numerical precision errors when effect sizes are near zero.

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Recent Features (from v1.2.0)

(For a full list of features, see the v1.2.0 Release Notes)

📈 Scientific Validation: Convergence Analysis

• New Module: Added a dedicated Convergence Analysis mode (HERA.start_ranking('convergence', 'true')) to validate the stability of default robust convergence parameters.
• Simulation: Implements simulation loops to analyze how ranking, threshold and BCa confidence interval stability changes with different sample sizes and data distribution scenarios.

🐍 Python Integration 2.0

• Smart Type Conversion: The Python wrapper now automatically detects and converts NumPy arrays and Pandas DataFrames/Series into MATLAB-compatible types. You can now pass your data directly to HERA without manual formatting!
• Type Stubs (.pyi): Added type hinting files to provide better autocompletion and static analysis support in basic Python IDEs.

🖥️ Platform Support

• MATLAB Toolbox & Python Package: Windows, macOS (Intel & Apple Silicon), Linux
• Standalone Application: macOS (Apple Silicon ONLY)

📦 Compatibility

• MATLAB: Compatible with R2020a and newer.
• Python: Requires Python 3.9 through 3.12. and Matlab Runtime R2025b (25.2).

Full Changelog: v1.2.0...v1.2.1