# Main code for my master thesis
# Installation - If you use pipenv and pyenv: ` pipenv install -e git+https://github.com/bernharl/ealstm_regional_modeling_camels_gb.git#egg=camelsml --python 3.8 ` - If not using pipenv, this repository should be installable using pip as well.
## Content of the repository This repo is structured like a Python package. All relevant code is found within the camelsml directory.
## Citation
As you can see on the Github page, this repository is a fork of [this repository](https://github.com/kratzert/ealstm_regional_modeling). Therefore, if you use this code, make sure to cite:
` @article{kratzert2019universal, author = {Kratzert, F. and Klotz, D. and Shalev, G. and Klambauer, G. and Hochreiter, S. and Nearing, G.}, title = {Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets}, journal = {Hydrology and Earth System Sciences}, volume = {23}, year = {2019}, number = {12}, pages = {5089--5110}, url = {https://www.hydrol-earth-syst-sci.net/23/5089/2019/}, doi = {10.5194/hess-23-5089-2019} } ` , as well as the thesis connected to this code.
## License [Apache License 2.0](https://github.com/kratzert/ealstm_regional_modeling/blob/master/LICENSE)
1 maintainer
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Release files for camelsml 2.0.1
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Release files / camelsml-2.0.1.tar.gz
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