HERA #19
lerdmann1601
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HERA
#19
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HERA v1.2.1
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.
🖥️ Platform Support
📦 Compatibility
📥 Installation
Option 1: MATLAB Toolbox
The easiest way to use HERA within MATLAB.
.mltbx) file.HERA.start_ranking).Option 2: Python Package
Integrate HERA into your Python data science pipelines.
pip3 install hera-matlab.import hera_matlab.Option 3: Standalone Application
Supported Platform: macOS (Apple Silicon)
No MATLAB license required.
HERA_Runtime_Installer_...) to set up the application and automatically download the MATLAB Runtime.🚀 Key Features
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
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
calculate_ranking.mto prevent potential ranking instabilities caused by numerical precision errors when effect sizes are near zero.Recent Features (from v1.2.0)
(For a full list of features, see the v1.2.0 Release Notes)
📈 Scientific Validation: Convergence Analysis
HERA.start_ranking('convergence', 'true')) to validate the stability of default robust convergence parameters.🐍 Python Integration 2.0
.pyi): Added type hinting files to provide better autocompletion and static analysis support in basic Python IDEs.Full Changelog: v1.2.0...v1.2.1
This discussion was created from the release HERA.
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