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GitHub / 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.
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Dan-Boat%2FPyESD
Stars: 36
Forks: 8
Open Issues: 0
License: mit
Language: Python
Repo Size: 68.4 MB
Dependencies:
407
Created: over 2 years ago
Updated: 2 months ago
Last pushed: 3 months ago
Last synced: about 1 month ago
Commit Stats
Commits: 163
Authors: 2
Mean commits per author: 81.5
Development Distribution Score: 0.067
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/Dan-Boat/PyESD
Topics: deep-learning, downscaling, ensemble-machine-learning, machine-learning, precipitation, sckit-learn, tensorflow2
Files
Dependencies
- Keras-Preprocessing >=1.1.2
- cftime >=1.6.0
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- Sphinx * development
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