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Class for working with TiledProjectionSystems (TPS)

Project description

A python class for working with TiledProjectionSystems (TPS).

It’s a python package that handles the geometric and geographic operations of a gridded and tiled projection system. It was designed for data cubes ingesting satellite imagery and builds the basis for the Equi7Grid (see

It also includes a nice and handy realisation of the UTM/UPS grid system, using the TiledProjectionSystems (TPS) approach.


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 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


This package should be installable through pip:

pip install pytileproj

Installs for scipy and gdal are required from conda or conda-forge.


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 recommend a conda environment.

Example installation script

The following script will install miniconda and setup the environment on a UNIX like system. Miniconda will be installed into $HOME/miniconda.

wget -O
bash -b -p $HOME/miniconda
export PATH="$HOME/miniconda/bin:$PATH"
conda create -n pytileproj_env python=3.6 numpy scipy pip gdal pyproj shapely
source activate pytileproj_env

This script adds $HOME/miniconda/bin temporarily to the PATH to do this permanently add export PATH="$HOME/miniconda/bin:$PATH" to your .bashrc or .zshrc

The last line in the example activates the pytileproj_env environment.

After that you should be able to run:

python test

to run the test suite.


If you want to contribute please follow these steps:

  • Fork the pytileproj repository to your account

  • Clone the repository

  • make a new feature branch from the pytileproj 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 3.3. For details and usage information on PyScaffold see

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pytileproj-0.0.16.tar.gz (570.8 kB view hashes)

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