Dan-Boat / 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.

Date Created 2021-11-14 (2 years ago)

Commits 169 (last one about a month ago)

Stargazers 45 (0 this week)

Watchers 5 (0 this week)

Forks 11

License mit

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RepositoryStats indexes 565,600 repositories, of these Dan-Boat/PyESD is ranked #475,560 (16th percentile) for total stargazers, and #326,808 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #90,436/111,362.

Dan-Boat/PyESD is also tagged with popular topics, for these it's ranked: deep-learning (#7,145/8173), machine-learning (#6,779/7699), tensorflow2 (#213/240)

Other Information

There have been 2 releases, the latest one was published on 2023-03-24 (about a year ago) with the name PyESDv1.0.1.

Homepage URL: https://dan-boat.github.io/PyESD/

All Topics

downscaling sckit-learn tensorflow2 deep-learning precipitation machine-learning ensemble-machine-learning

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167 commits on the default branch (main) since jan '22

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updated: 2024-09-25 @ 06:46am, id: 427999214 / R_kgDOGYK_7g