smap-io 0.8

SMAP (Soil Moisture Active Passive) data readers

SMAP (Soil Moisture Active Passive) data readers.

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.596391 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

Setup of a complete environment with conda can be performed using the following commands:

$ conda create -q -n smap_io -c conda-forge numpy h5py pyproj netcdf4 pyresample pandas
$ source activate smap_io
$ pip install smap_io

You can also install all needed (conda and pip) dependencies at once using the following commands after cloning this repository. This is recommended for developers of the package.

$ git clone https://github.com/TUW-GEO/smap_io.git --recursive
$ cd smap_io
$ conda create -n smap_io python=3.6 # or any supported python version
$ source activate smap_io
$ conda update -f environment.yml
$ python setup.py develop

Supported Products

• SPL3SMP: SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture

Additional products will we added when need arises, feel free to open an issue to add a new data product or even better a pull request.

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.

Guidelines

If you want to contribute please follow these steps:

• Fork the smap_io repository to your account

• make a new feature branch from the smap_io 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