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pypi.org : pyesd

Python Package for Empirical Statistical Downscaling. pyESD is under active development and all colaborators are welcomed. The purpose of the package is to downscale any climate variables e.g. precipitation and temperature using predictors from reanalysis datasets (eg. ERA5) to point scale. pyESD adopts many ML and AL as the transfer function.

Registry - Source - Documentation - JSON
purl: pkg:pypi/pyesd
Keywords: pyESD, Empirical, Statistical, Downscaling, deep-learning, downscaling, ensemble-machine-learning, machine-learning, precipitation, sckit-learn, tensorflow2
License: MIT
Latest release: 11 months ago
First release: about 1 year ago
Downloads: 49 last month
Stars: 36 on GitHub
Forks: 7 on GitHub
Total Commits: 163
Committers: 2
Average commits per author: 81.5
Development Distribution Score (DDS): 0.067
More commit stats: commits.ecosyste.ms
See more repository details: repos.ecosyste.ms
Last synced: about 4 hours ago

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