Xcast
A High-Performance Data Science Toolkit for the Earth Sciences
Install / Use
/learn @kjhall01/XcastREADME
XCast is a free and open source climate forecasting toolkit written by Kyle Hall & Nachiketa Acharya, designed to help forecasters and earth scientists apply state-of-the-art postprocessing techniques to gridded data sets. <br /> <a href="https://xcast-lib.github.io/"><strong>Explore the docs»</strong></a> <br /> <a href="https://github.com/kjhall01/xcast/issues">Report Bug</a>
</p> </p> <!-- TABLE OF CONTENTS --> <details open="open"> <summary><h2 style="display: inline-block">Table of Contents</h2></summary> <ol> <li><a href="#why-xcast">Why XCast?</a></li> <li><a href="#installation">Installation</a></li> <li><a href="#license">License</a></li> <li><a href="#contact">Contact</a></li> <li><a href="#acknowledgements">Acknowledgements</a></li> </ol> </details>Installation
XCast is distributed on Anaconda , and can be installed like any other Python library with the following command:
conda install -c conda-forge -c hallkjc01 xcast
to set up an XCast environment for use with Jupyter notebook, please use the following commands:
conda create -n xcast_env -c conda-forge -c hallkjc01 xcast xarray netcdf4 jupyter ipykernel
conda activate xcast_env
python -m ipykernel install --name=xcast_env --user
you'll then be able to select xcast_env from the list of available jupyter kernels in your jupyter notebook
License
Distributed under the MIT License. See LICENSE for more information.
Contact
Please make an issue here.
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