v2.2 (11 Oct 2018)#
This document explains the changes made to Iris for this release (View all changes.)
2-Dimensional Coordinate Plotting
To enable this feature, each coordinate passed in for plotting will be automatically checked for contiguity. Coordinate bounds must either be contiguous, or the cube’s data must be masked at the discontiguities in order to avoid plotting errors.
The Iris plot function
iris.plot.quiver() has been added, and this
also works with 2-dimensional plot coordinates.
2-Dimensional Grid Vectors
The Iris functions
iris.analysis.cartography.rotate_grid_vectors() have been added,
allowing you to convert gridcell-oriented vectors to true-North/East ones.
NetCDF Data Variable Chunk Sizes
NetCDF data variable chunk sizes are now utilised at load time for significant performance improvements.
iris.fileformats.um.FieldCollationobjects, which are passed into load callbacks when using
iris.fileformats.um.structured_um_loading(), now have the additional properties:
iris.fileformats.um.FieldCollation.data_field_indices. These provide the file locations of the original data fields, which are otherwise lost in the structured loading process.
iris.util.reverse()can now be used to reverse a cube by specifying one or more coordinates.
Time mean fields can now be saved to PP files as a cell method.
Error messages thrown upon failed addition of an
AuxCoordFactorynow include the name of the required (but absent) coordinate as well as the name of the cube.
iris.util.find_discontiguities()can be used to check for discontiguities in the bounds arrays of cube coordinates. Additionally, discontiguous points in coordinates can be explicitly masked using another new feature
iris.util.array_equal()now has a ‘withnans’ keyword, which provides a NaN-tolerant array comparison.
The bug has been fixed that prevented printing time coordinates with bounds when the time coordinate was measured on a long interval (that is,
“Gracefully filling…” warnings are now only issued when the coordinate or bound data is actually masked.
v2.2.1 (28 May 2019)#
Iris can now correctly unpack a column of header objects when saving a pandas DataFrame to a cube.
fixed a bug in
iris.util.new_axis(): copying the resulting cube resulted in an exception, if it contained an aux-factory.
iris.coords.AuxCoord’s can now test as ‘equal’ even when the points or bounds arrays contain NaN values, if values are the same at all points. Previously this would fail, as conventionally “NaN != NaN” in normal floating-point arithmetic.
Iris is now using the latest version release of dask (currently 0.19.3)
Proj4 has been temporarily pinned to version < 5 while problems with the Mollweide projection are addressed.
Matplotlib has been pinned to version < 3 temporarily while we account for its changes in all SciTools libraries.
Iris’ INSTALL document has been updated to include guidance for running tests.
A link has been added to the Developers’ Guide to make it easier to find the Pull Request Check List.