Metadata-Version: 1.1
Name: repurpose
Version: 0.6
Summary: Package for image to timeseries to image conversion
Home-page: https://github.com/TUW-GEO/repurpose
Author: Christoph Paulik
Author-email: christoph.paulik@geo.tuwien.ac.at
License: new-bsd
Description-Content-Type: UNKNOWN
Description: =========
        repurpose
        =========
        
        .. image:: https://travis-ci.org/TUW-GEO/repurpose.svg?branch=master
            :target: https://travis-ci.org/TUW-GEO/repurpose
        
        .. image:: https://coveralls.io/repos/github/TUW-GEO/repurpose/badge.svg?branch=master
           :target: https://coveralls.io/github/TUW-GEO/repurpose?branch=master
        
        .. image:: https://badge.fury.io/py/repurpose.svg
            :target: http://badge.fury.io/py/repurpose
        
        .. image:: https://readthedocs.org/projects/repurpose/badge/?version=latest
           :target: http://repurpose.readthedocs.org/
        
        
        This package provides routines for the conversion of image formats to time
        series and vice versa. It is part of the `poets° project
        <http://tuw-geo.github.io/poets/>`_ and works best with the readers and writers
        supported there. The main use case is for data that is sampled irregularly in
        space or time. If you have data that is sampled in regular intervals then there
        are alternatives to this package which might be better for your use case. See
        `Alternatives`_ for more detail.
        
        The readers and writers have to conform to the API specifications of the base
        classes defined in `pygeobase <https://github.com/TUW-GEO/pygeobase>`_ to work
        without adpation.
        
        Citation
        ========
        
        .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.593577.svg
           :target: https://doi.org/10.5281/zenodo.593577
        
        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.593577 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
        
        Installation
        ============
        
        This package should be installable through pip:
        
        .. code::
        
            pip install repurpose
        
        Modules
        =======
        
        It includes two main modules:
        
        - ``img2ts`` for image/swath to time series conversion, including support for
          spatial resampling.
        - ``ts2img`` for time series to image conversion, including support for temporal
          resampling. This module is very experimental at the moment.
        
        Alternatives
        ============
        
        If you have data that can be represented as a 3D datacube then these projects
        might be better suited to your needs.
        
        - `PyReshaper <https://github.com/NCAR/PyReshaper>`_ is a package that works
          with NetCDF input and output and converts time slices into a time series
          representation.
        - `Climate Data Operators (CDO)
          <https://code.zmaw.de/projects/cdo/embedded/index.html>`_ can work with
          several input formats, stack them and change the chunking to allow time series
          optimized access. It assumes regular sampling in space and time as far as we
          know.
        - `netCDF Operators (NCO) <http://nco.sourceforge.net/#Definition>`_ are similar
          to CDO with a stronger focus on netCDF.
        
        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 recommend a ``conda`` environment
        
        Guidelines
        ----------
        
        If you want to contribute please follow these steps:
        
        - Fork the repurpose repository to your account
        - make a new feature branch from the repurpose 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 2.4.4. For details and usage
        information on PyScaffold see http://pyscaffold.readthedocs.org/.
        
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
