Metadata-Version: 1.0
Name: repurpose
Version: 0.4
Summary: Package for image to timeseries to image conversion
Home-page: UNKNOWN
Author: Christoph Paulik
Author-email: christoph.paulik@geo.tuwien.ac.at
License: new-bsd
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://zenodo.org/badge/12761/TUW-GEO/repurpose.svg
           :target: https://zenodo.org/badge/latestdoi/12761/TUW-GEO/repurpose
        
        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.
        
        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.
        
        Documentation
        =============
        
        |Documentation Status|
        
        .. |Documentation Status| image:: https://readthedocs.org/projects/repurpose/badge/?version=latest
           :target: http://repurpose.readthedocs.org/
        
        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.
        
        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
