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v1.1 (03 Jan 2013)#

This document explains the changes made to Iris for this release (View all changes.)

Features#

With the release of Iris 1.1, we are introducing support for Mac OS X. Version 1.1 also sees the first batch of performance enhancements, with some notable improvements to netCDF/PP import.

  • Support for Mac OS X.

  • GRIB1 import now supports time units of “3 hours”.

  • Fieldsfile import now supports unpacked and “CRAY” 32-bit packed data in 64-bit Fieldsfiles.

  • PP file import now supports “CRAY” 32-bit packed data.

  • Various performance improvements, particularly for netCDF import, PP import, and constraints.

  • GRIB2 export now supports level types of altitude and height (codes 102 and 103).

  • iris.analysis.cartography.area_weights now supports non-standard dimension orders.

  • PP file import now adds the “forecast_reference_time” for fields where LBTIM is 11, 12, 13, 31, or 32.

  • PP file import now supports LBTIM values of 1, 2, and 3.

  • Fieldsfile import now has some support for ancillary files.

  • Coordinate categorisation functions added for day-of-year and user-defined seasons.

  • GRIB2 import now has partial support for probability data defined with product template 4.9.

Coordinate Categorisation#

An add_day_of_year() categorisation function has been added to the existing suite in iris.coord_categorisation.

Custom Seasons#

The conventional seasonal categorisation functions have been complemented by two groups of functions which handle user-defined, custom seasons.

The first group of functions is:

  • iris.coord_categorisation.add_custom_season()

  • iris.coord_categorisation.add_custom_season_number()

  • iris.coord_categorisation.add_custom_season_year()

These functions mimic their non-custom versions, but with the addition of a seasons parameter which is used to define the custom seasons. These seasons are defined by concatenating the single letter abbreviations of the relevant, consecutive months.

For example, to categorise a Cube based on “winter” and “summer” months, one might do:

>>> seasons = ['mamjja', 'sondjf']
>>> iris.coord_categorisation.add_custom_season(cube, 'time', seasons)
>>> print(cube.coord('season').points)
['ondjfm' 'ondjfm' 'mamjja' 'mamjja' 'mamjja' 'mamjja' 'mamjja' 'mamjja'
 'ondjfm' 'ondjfm' 'ondjfm' 'ondjfm']

The other custom season function is:

  • iris.coord_categorisation.add_custom_season_membership().

This function adds a coordinate containing True/False values determined by membership of a single custom season.

Bugs Fixed#

  • PP export no longer attempts to set/overwrite the STASH code based on the standard_name.

  • Cell comparisons now work consistently, which fixes a bug where bounded_cell > point_cell compares the point to the bounds but, point_cell < bounded_cell compares the points.

  • Fieldsfile import now correctly recognises pre v3.1 and post v5.2 versions, which fixes a bug where the two were interchanged.

  • iris.analysis.trajectory.interpolate now handles hybrid-height.