daops - data-aware operations

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The daops library (pronounced "day-ops") provides a python interface to a set of operations suitable for working with climate simulation outputs. It is typically used with ESGF data sets that are described in NetCDF files. daops is unique in that it accesses a store of fixes defined for datasets that are irregular when compared with others in their population.

When a daops operation, such as subset\ , is requested, the library will look up a database of known fixes before performing and calculations or transformations. The data will be loaded and fixed using the xarray <http://xarray.pydata.org/> library before the any actual operations are sent to its sister library clisops <https://github.com/roocs/clisops>.

• Free software: BSD
• Documentation: https://daops.readthedocs.io

Features

The package has the following features:

• Ability to run data-reduction operations on large climate data sets.
• Knowledge of irregularities/anomalies in some climate data sets.
• Ability to apply fixes to those data sets before operating on them. This process is called normalisation of the data sets.

Credits

This package was created with Cookiecutter and the cedadev/cookiecutter-pypackage project template.

• Cookiecutter: https://github.com/audreyr/cookiecutter
• cookiecutter-pypackage: https://github.com/cedadev/cookiecutter-pypackage

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