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Author:
Daniel Boateng
License:
MIT license
Summary:
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.
Latest version:
1.0.7
Required dependencies:
cftime
|
cycler
|
eofs
|
geopandas
|
numpy
|
pandas
|
scikit-learn
|
scikit-optimize
|
scipy
|
seaborn
|
tensorflow
|
xarray
|
xgboost
Optional dependencies:
bump2version
|
coverage
|
flake8
|
grip
|
h5netcdf
|
importlib-metadata
|
matplotlib
|
netcdf4
|
packaging
|
pip
|
pydocstyle
|
pytest
|
pytest-cov
|
pytest-runner
|
setuptools
|
sphinx
|
sphinx-rtd-theme
|
tox
|
twine
|
watchdog
|
wheel
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