Version 0.11.0
This release includes major contributions from @maihde (generalizing count_cat to by
, span for colorize), @jonmmease (Dask quadmesh support), @philippjfr and @jbednar (count_cat/by/colorize/docs/bugfixes), and Barry Bragg, Jr. (TMS tileset speedups).
New features (see getting_started/2_Pipeline.ipynb for examples):
- New
by()
categorical aggregator, extendingcount_cat
to work with other reduction functions, no longer justcount
. Allows binning of aggregates separately per category value, so that you can compare how that aggregate is affected by category value. (#875, #902, #904, #906). See example in the holoviews docs. - Support for negative and zero values in
tf.shade
for categorical aggregates. (#896, #909, #910, #908) - Support for
span
in _colorize(). (#875, #910) - Support for Dask-based quadmesh rendering for rectilinear and curvilinear mesh types (#885, #913)
- Support for GPU-based raster mesh rendering (via
Canvas.quadmesh
) (#872) - Faster TMS tileset generation (#886)
- Expanded performance guide (#868)
Bugfixes:
Compatibility (breaking changes and deprecations):
- To allow negative-valued aggregates, count_cat now weights categories according to how far they are from the minimum aggregate value observed, while previously they were referenced to zero. Previous behavior can be restored by passing
color_baseline=0
tocount_cat
orby
. count_cat
is now deprecated and removed from the docs; useby(..., count())
instead.- Result of a
count()
aggregation is nowuint32
, notint32
, to distinguish counts from other aggregation types (#910). - tf.shade now only treats zero values as missing for
count
aggregates (uint
); zero is otherwise a valid value distinct from NaN (#910). alpha
is now respected as the upper end of the alpha range for both _colorize() and _interpolate() in tf.shade; previously only _interpolate respected it.- Added new nansum_missing utility for working with Numpy>1.9, where nansum no longer returns NaN for all-NaN values.
- ds.geo and ds.spatial modules are now deprecated; their contents have moved to xarray_spatial and spatialpandas, respectively. (#894)
Download and install: https://datashader.org/getting_started