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

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esa_cci_sm

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Reading and reshuffling of CCI soil moisture Written in Python.

Installation

Installing the package can be done via pip:

pip install esa_cci_sm

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

git clone git@github.com:TUW-GEO/esa_cci_sm.git --recursive esa_cci_sm
cd ./esa_cci_sm
conda env create -f environment.yml
source activate esa_cci_sm
pip install -e .

To checkout our testdata files, you need to have `Git LFS<https://git-lfs.github.com/>`_ installed on your machine.

Supported Products

At the moment this package supports ESA CCI soil moisture data version v02.x, v03.x, v04.x and v05.x, v06.x, v07.x 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.

Guidelines

If you want to contribute please follow these steps:

  • Fork the esa_cci_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 esa_cci_sm master branch
  • Add your feature
  • Please include tests for your contributions in one of the test directories. We use pytest 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/.

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

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