This is a package for creation and handling of Discrete Global Grids or Point collections. We hope extend the interface also to projected grids(images) in the future.

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.596401 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

This package should be installable through pip:

pip install pygeogrids

To install the package use pip 6.0 or later. On linux systems pykdtree will be installed whereas on windows systems scipy cKDTree will be used. pykdtree is faster than the scipy implementation but it is at the moment not available for Windows systems.

For now the main features are:

• Creation of grids
• Nearest neighbor search
• conversion of grid piont indices to lat, lon
• Storage of grids and loading grids from CF-compatible netCDF files
• Calculation of lookup tables between grids
• Support for different Geodetic Datums using pyproj.

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 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 pygeogrids environment which you can activate by using source activate pygeogrids.

If you want to contribute please follow these steps:

• Fork the pygeogrids repository to your account
• Clone the repository
• make a new feature branch from the pygeogrids 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 3.2.3. For details and usage information on PyScaffold see https://pyscaffold.org/.