Iris: A Python library for analysing and visualising meteorological and oceanographic data sets
M. Office. Exeter, Devon, v2.0 edition, (2010-2018)
Abstract
The Iris library implements a data model to create a data abstraction layer which isolates analysis and visualisation code from data format specifics. The data model we have chosen is the CF Data Model. The implementation of this model we have called an Iris Cube.
Iris currently supports read/write access to a range of data formats, including (CF-)netCDF, GRIB, and PP; fundamental data manipulation operations, such as arithmetic, interpolation, and statistics; and a range of integrated plotting options.
Iris is published under an LGPLv3 licence.
%0 Generic
%1 Office20102018Iris
%A Office, Met
%C Exeter, Devon
%D 2010-2018
%K visualisation colleagues software
%T Iris: A Python library for analysing and visualising meteorological and oceanographic data sets
%U http://scitools.org.uk/iris/
%X The Iris library implements a data model to create a data abstraction layer which isolates analysis and visualisation code from data format specifics. The data model we have chosen is the CF Data Model. The implementation of this model we have called an Iris Cube.
Iris currently supports read/write access to a range of data formats, including (CF-)netCDF, GRIB, and PP; fundamental data manipulation operations, such as arithmetic, interpolation, and statistics; and a range of integrated plotting options.
Iris is published under an LGPLv3 licence.
%7 v2.0
@manual{Office20102018Iris,
abstract = {The Iris library implements a data model to create a data abstraction layer which isolates analysis and visualisation code from data format specifics. The data model we have chosen is the CF Data Model. The implementation of this model we have called an Iris Cube.
Iris currently supports read/write access to a range of data formats, including (CF-)netCDF, GRIB, and PP; fundamental data manipulation operations, such as arithmetic, interpolation, and statistics; and a range of integrated plotting options.
Iris is published under an LGPLv3 licence.},
added-at = {2018-06-18T21:23:34.000+0200},
address = {Exeter, Devon},
author = {Office, Met},
biburl = {https://www.bibsonomy.org/bibtex/298e3964e7d71a8a10642d2e38b00b079/pbett},
citeulike-article-id = {14562959},
citeulike-linkout-0 = {http://scitools.org.uk/iris/},
edition = {v2.0},
interhash = {369d4a4e5dadafcda20d1921c8cbb3be},
intrahash = {98e3964e7d71a8a10642d2e38b00b079},
keywords = {visualisation colleagues software},
posted-at = {2018-04-06 20:48:13},
priority = {2},
timestamp = {2018-06-22T18:39:21.000+0200},
title = {Iris: A Python library for analysing and visualising meteorological and oceanographic data sets},
url = {http://scitools.org.uk/iris/},
year = {2010-2018}
}