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Readers and converters for C3S Soil Moisture image and time series data. Written in Python.

Home Page: https://climate.copernicus.eu/

License: MIT License

Python 12.59% Jupyter Notebook 87.41%

c3s_sm's Introduction

c3s_sm

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Reading and reshuffling of C3S soil moisture Written in Python.

Installation

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

git clone [email protected]:TUW-GEO/c3s_sm.git c3s_sm
cd c3s_sm
conda env create -f environment.yml
source activate c3s_sm

Supported Products

At the moment this package supports C3S soil moisture data in netCDF format (reading and time series creation) with a spatial sampling of 0.25 degrees.

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 env create -f environment.yml. This will create a new c3s_sm environment which you can activate by using source activate c3s_sm.

Guidelines

If you want to contribute please follow these steps:

  • Fork the c3s_sm 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 c3s_sm 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. For details and usage information on PyScaffold see http://pyscaffold.readthedocs.org/.

c3s_sm's People

Contributors

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