# 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)
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file camelsml-2.0.1.tar.gz.
File metadata
- Download URL: camelsml-2.0.1.tar.gz
- Upload date:
- Size: 34.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.9.6
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9e3c514a8497093cb1486d1a2a333bae42abdb6b4a8fb457297755938fc7d91c
|
|
| MD5 |
487fcace88904ad0ee8941ced771ff0e
|
|
| BLAKE2b-256 |
49192e6cae07931394560016416655e99c76fb058d3d2fac8f715808bdf1df27
|