Processing tools and tutorials for users of the C3S satellite soil moisture service ( https://doi.org/10.24381/cds.d7782f18 ). Written in Python.
The c3s_sm package can be installed via
pip install c3s_smWe provide (general) tutorials on using the C3S Soil Moisture data:
These tutorials are designed to run on mybinder.org You can find the code for all examples in this repository.
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.
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.
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.
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 --recursiveto 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
This project has been set up using PyScaffold 2.5. For details and usage information on PyScaffold see http://pyscaffold.readthedocs.org/.