This package provides routines for the conversion of image formats to time series and vice versa. It is part of the poets° project 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 to work without adpation.

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.

If you have data that can be represented as a 3D datacube then these projects might be better suited to your needs.

• PyReshaper is a package that works with NetCDF input and output and converts time slices into a time series representation.
• Climate Data Operators (CDO) 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) are similar to CDO with a stronger focus on netCDF.

This project has been set up using PyScaffold 2.4.4. For details and usage information on PyScaffold see http:https://pyscaffold.readthedocs.org/.