Metadata-Version: 2.3
Name: seapopym_optimization
Version: 0.0.2.3
Summary: A Python package for optimizing SeapoPym models using DEAP and Dask
License: MIT
Keywords: oceanography,marine ecosystems,marine biology
Author: Jules Lehodey
Author-email: lehodey.jules+seapopym@gmail.com
Requires-Python: >=3.12,<3.13
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Oceanography
Requires-Dist: dask (>=2025.9.0,<2026.0.0)
Requires-Dist: deap (>=1.4.3,<2.0.0)
Requires-Dist: distributed (>=2025.9.0,<2026.0.0)
Requires-Dist: pandera (>=0.26.1,<0.27.0)
Requires-Dist: plotly (>=6.3.0,<7.0.0)
Requires-Dist: salib (>=1.5.1,<2.0.0)
Requires-Dist: scikit-learn (>=1.7.2,<2.0.0)
Requires-Dist: scipy (>=1.16.2,<2.0.0)
Requires-Dist: seapopym (>=0.0.2.5.2,<0.0.3.0.0)
Description-Content-Type: text/markdown

# Seapopym-optimisation

Seapopym-optimisation is a Python project dedicated to the optimization of spatial ecological models, with a focus on the SeapoPym models.
It provides a modular framework for:

-   Model calibration using genetic algorithms,
-   Management and validation of parameter sets,
-   Comparison between simulations and observations (time series, seasonal decomposition, etc.),
-   Use of various cost functions (RMSE, GAM decomposition, STL, and more).

This package was developed by Jules Lehodey as part of his thesis "Data driven modeling approach of mesozooplankton and micronekton functional groups".

