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Readers and converters for data from the GLDAS Noah Land Surface Model. Written in Python.

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gldas

ci cov pip doc

Readers and converters for data from the GLDAS Noah Land Surface Model. Written in Python.

Works great in combination with pytesmo.

Citation

If you use the software in a publication then please cite it using the Zenodo DOI. Be aware that this badge links to the latest package version.

Please select your specific version at https://doi.org/10.5281/zenodo.596427 to get the DOI of that version. You should normally always use the DOI for the specific version of your record in citations. This is to ensure that other researchers can access the exact research artefact you used for reproducibility.

You can find additional information regarding DOI versioning at http://help.zenodo.org/#versioning

Installation

This package can be installed via pip from pypi.org. The minimum required python version is 3.9.

To read grib files on Windows systems, it might be necessary to use conda to install pygrib first:

conda install pygrib

Afterwards you can install the gldas package and all other dependencies via

pip install gldas

Supported Products

At the moment this package supports GLDAS Noah data version 1 in grib format (reading, time series creation) and GLDAS Noah data version 2.0 and version 2.1 in netCDF format (download, reading, time series creation) with a spatial sampling of 0.25 degrees. It should be easy to extend the package to support other GLDAS based products. This will be done as need arises.

Contribute

We are happy if you want to contribute. Please raise an issue explaining what is missing or if you find a bug. We will also gladly accept pull requests against our master branch for new features or bug fixes.

Development setup

For Development we also recommend a conda environment. You can create one including test dependencies and debugger by running conda create -n gldas python=3.12, then conda env update -f environment.yml to install all dependencies. Finally, call pip install -e .[testing]. Now everything should be in place to run tests and develop new features.

Guidelines

If you want to contribute please follow these steps:

  • Fork the gldas repository to your account
  • Clone the repository, make sure you use git clone --recursive to also get the test data repository.
  • make a new feature branch from the gldas master branch
  • Add your feature
  • Please include tests for your contributions in one of the test directories. We use py.test so a simple function called test_my_feature is enough
  • submit a pull request to our master branch

Note

This project has been set up using PyScaffold 2.5.6. For details and usage information on PyScaffold see http://pyscaffold.readthedocs.org/.