anag_factory
06b53b5c2d
- Drop support for Python 3.11: added %global skip_python311 1 in spec file
(bsc#1263906)
- update to 0.19.0:
* Deprecate pyct functions fetch_data, copy_examples, examples
* Optimized numba code for QuadMesh (3D support)
* Add support for Python 3.14
* Improved performance for dask-based raster
* Compatibility:
+ Compatibility with Pandas 3.0
+ Compatibility with Numpy 2.0
- Move Pillow and dask-dataframe to Recommends as they are now optional.
- Remove deprecated nbsmoke from test dependencies
- Remove deprecated dask-expr from tests
- Update to 0.18.2:
* Breaking Changes:
+ Drop support for Python 3.9
+ Making dask and pillow optional dependencies
* Enhancements:
+ Add more information to repr of reductions
+ Edge bundling speedup using optimized numba code
* Compatibility:
+ Compatibility with Pillow 11.3.0
+ Compatibility with cuDF 24.12
+ Compatibility with dask 2025.1 and dask-expr 2
+ Compatibility with pixi v0.40.0
+ Compatibility with Python 3.13
* Bugfixes:
+ Fix segfault when quadmesh reduction wrongly exceeded the array size
+ PDF scaling bug
* Maintenance:
+ Move to pixi and hatchling
- Don't require runtime requirements for building: Avoid resolver
conflict for numpy with numba
- Unpin numpy 2
- Restrict numpy to < 2.
- update to 0.16.3:
* Add fail-fast for datasets outside the visible extent
* Compatibility with cudf 2024.06
* Compatibility with geopandas 1.0 and dask-geopandas 0.4.0
- Update to 0.16.2:
* Remove artifact from Polygon rendering (#1341)
* Python 3.12 support (#1317)
* Basic dask_expr support (#1317)
* Numpy 2.0 support (#1306)
* Remove redundant py2 helper code (#1316)
- Remove upper bound on pytest.
- Add patch datashader-pr1314-fix-pandas2.2-tests.patch:
* Included upstream.
- Skip python39: no xarray anymore
- Add datashader-pr1314-fix-pandas2.2-tests.patch
gh#holoviz/datashader#1314
- Drop DataShape requirement, it's included and maintained in
datashader since 0.16.0
* gh#holoviz/datashader#1003
* gh#holoviz/datashader#1284
- Use %pyproject macros to build the package
- skip known failing test with latest dask gh#holoviz/datashader#1032
- update to 0.16.0:
* Support rendering of GeoPandas GeoDataFrames as lines, points
and polygons
* Implement lines using 2D xarray with common x coordinates
* Add debug logging to compiler module (#1280)
* Vendor DataShape (#1284)
* Don't use object as base class (#1286)
* Fix typos using codespell (#1288)
* Fix float16 being a floating type. (#1290)
* Simplify line _internal_build_extend (#1294)
* Update to latest holoviz_tasks (#1281)
* Support Pandas 2.1 (#1276, #1287)
* Replace np.NaN with np.nan (#1289)
* Drop support for Python 3.8 (#1291)
- drop pd21.patch (upstream)
- Add pd21.patch to support Pandas 2.1
- update to 0.15.2:
* This release adds antialiased line support for inspection
reductions such as max_n and where, including within
categorical by reductions. It also improves support
for summary reductions and adds CUDA implementations
of std and var reductions
- update to 0.15.1:
* Fix single category reductions
* Ensure categorical column order is the same across dask partitions
* see https://github.com/holoviz/datashader/releases/tag/v0.15.1
- Mention dropped patches:
* Do-not-use-warnings-from-numpy.patch
* numpy-1.24.patch
- Update to 0.15.0
* This release provides significant improvements for inspection
reductions by adding new first_n, last_n, max_n and min_n
reductions, and providing Dask and CUDA support for all
existing and new inspection reductions including where. It also
provides support for Numba 0.57, NumPy 1.24 and Python 3.11,
and drops support for Python 3.7.
## Enhancements:
### Inspection reductions:
* Reduction append functions return index not boolean (#1180)
* first_n, last_n, max_n and min_n reductions (#1184)
* Add cuda argument to _build_combine (#1194)
* Support max_n and min_n reductions on GPU (#1196)
* Use fast cuda mutex available in numba 0.57 (#1212)
* Dask support for first, last, first_n and last_n reductions
(#1214)
* Wrap use of cuda mutex in where reductions (#1217)
* Cuda and cuda-with-dask support for inspection reductions
(#1219)
### Other:
* x and y range attributes on returned aggregations (#1198)
* Make datashader.composite imports lazy for faster import time
(#1222)
## Bug fixes
* Fix conversion from cupy in categorical rescale_discrete_levels
(#1179)
* Validate canvas width, height (#1183)
* Support antialiasing in pipeline API (#1213)
- Add pyarrow to tests, run tests in parallel with xdist
- Fix dependencies
- reenable python311 (dask available)
- Skip python38: No xarray anymore
- Skip python311: No dask-all and numba yet
- Add Do-not-use-warnings-from-numpy.patch and numpy-1.24.patch to fix issues
with latest numpy gh#holoviz/datashader#1176 gh#holoviz/datashader#1158
- Update to 0.14.4
* This release adds a new where reduction that provides improved inspection
capabilities and adds support for colormaps that are tuples of hex values.
There are also various bug fixes and compatibility improvements.
Thanks to @ianthomas23, @maximlt and @Hoxbro.
## Enhancements:
* New where reduction to provide improved inspection functionality:
- Add new where reduction (#1155)
- Where reduction using dataframe row index (#1164)
- CUDA support for where reduction (#1167)
- User guide page for where reduction (#1172)
* Support colormaps that are tuples of hex values (#1173)
* Add governance docs (#1165)
* Improve documentation build system (#1170, #1171)
* Improvements to CI:
- Rename default branch from master to main (#1156)
- Use holoviz_task install action (#1163)
## Bug fixes:
* Validate calculated log canvas range (#1154)
* Better validate canvas.line() coordinate lengths (#1160)
* Return early in eq_hist() if all data masked out (#1168)
## Compatibility:
* Follow recommended numba best practice.
- Ensure cuda functions are correctly jitted (#1153)
- nopython=True everywhere (#1162)
* Update dependencies:
- Pip pyarrow in tests dependencies (#1174)
- Update to 0.14.3
* This release fixes a bug related to spatial indexing of
spatialpandas.GeoDataFrames, and introduces enhancements to
antialiased lines, benchmarking and GPU support.
## Enhancements:
* Improvements to antialiased lines:
- Fit antialiased line code within usual numba/dask framework
(#1142)
- Refactor stage 2 aggregation for antialiased lines (#1145)
- Support compound reductions for antialiased lines on the CPU
(#1146)
* New benchmark framework:
- Add benchmarking framework using asv (#1120)
- Add cudf, dask and dask-cudf Canvas.line benchmarks (#1140)
* Improvements to GPU support:
- Cupy implementation of eq_hist (#1129)
* Improvements to dependency management (#1111, #1116)
* Improvements to CI (#1132, #1135, #1136, #1137, #1143)
## Bug fixes:
* Ensure spatial index _sindex is retained on dataframe copy
(#1122)
- Version 0.14.2
* This is a bug fix release to fix an important divide by zero
bug in antialiased lines, along with improvements to
documentation and handling of dependencies.
## Enhancements:
* Improvements to handling of dependencies:
- Correct dask and bokeh dependencies (#1104)
- Add requests as an install dependency (#1105)
- Better handle returned dask npartitions in tests (#1107)
## Bug fixes:
* Fix antialiased line divide by zero bug (#1099)
- Version 0.14.1
* This release provides a number of important bug fixes and small
enhancements from Ian Thomas along with infrastructure
improvements from Maxime Liquet and new reductions from
@tselea.
## Enhancements:
* Improvements to antialiased lines:
- Support antialiased lines for categorical aggregates (#1081,
#1083)
- Correctly handle NaNs in antialiased line coordinates (#1097)
* Improvements to rescale_discrete_levels for how='eq_hist':
* Correct implementation of rescale_discrete_levels (#1078)
* Check before calling rescale_discrete_levels (#1085)
* Remove empty histogram bins in eq_hist (#1094)
* Implementation of first and last reduction (#1093) for data
types other than raster.
## Bug fixes:
* Do not snap trimesh vertices to pixel grid (#1092)
* Correctly orient (y, x) arrays for xarray (#1095)
* Infrastructure/build fixes (#1080, #1089, #1096)
- Version 0.14.0
* This release has been nearly a year in the making, with major
new contributions from Ian Thomas, Thuy Do Thi Minh, Simon
Høxbro Hansen, Maxime Liquet, and James Bednar, and additional
support from Andrii Oriekhov, Philipp Rudiger, and Ajay Thorve.
## Enhancements:
* Full support for antialiased lines of specified width (#1048,
#1072). Previous antialiasing support was limited to
single-pixel lines and certain floating-point reduction
functions. Now supports arbitrary widths and arbitrary
reduction functions, making antialiasing fully supported.
Performance ranges from 1.3x to 14x slower than the simplest
zero-width implementation; see benchmarks.
* Fixed an issue with visibility on zoomed-in points plots and on
overlapping line plots that was first reported in 2017, with a
new option rescale_discrete_levels for how='eq_hist' (#1055)
* Added a categorical color_key for 2D (unstacked) aggregates
(#1020), for producing plots where each pixel has at most one
category value
## Bugfixes:
* Fixed details of the raster coordinate calculations to match
other primitives, making it simpler to overlay separately
rendered results (#959, #1046)
* Various fixes and extensions for cupy/CUDA, e.g. to use cuda
for category_binning, spread, and dynspread, including
cupy.interp where appropriate (#1015, #1016, #1044, #1050,
#1060)
* Infrastructure/build/ecosystem fixes (#1022, #1025, #1027,
#1036, #1045, #1049, #1050, #1057, #1061, #1062, #1063, #1064)
## Compatibility:
* Canvas.line() option antialias=True is now deprecated; use
line_width=1 (or another nonzero value) instead. (#1048)
* Removed long-deprecated bokeh_ext.py (#1059)
* Dropped support for Python 2.7 (actually already dropped from
the tests in Datashader 0.12) and 3.6 (no longer supported by
many downstream libraries like rioxarray, but several of them
are not properly declaring that restriction, making 3.6 much
more difficult to support.) (#1033)
- Drop upstreamed fixes
* datashader-pr1022-RaggedTests.patch
* datashader-pr1025-testfixes.patch
- Remove skip_python310, it is not needed anymore.
- Update to 0.13.0
* Defined new dynspread metric based on counting the fraction of
non-empty pixels that have non-empty pixels within a given
radius. The resulting dynspread behavior is much more intuitive
than the old behavior, which counted already-spread pixels as
if they were neighbors (#1001)
* Added ds.count() as the default reduction for ds.by (#1004)
* Fixed array-bounds reading error in dynspread (#1001)
* Fix color_key argument for dsshow (#986)
* Added Matplotlib output to the 3_Interactivity getting started
page. (#1009)
* Misc docs fixes (#1007)
* Fix nan assignment to integer array in RaggedArray (#1008)
* Any usage of dynspread with datatypes other than points should
be replaced with spread(), which will do what was probably
intended by the original dynspread call, i.e. to make isolated
lines and shapes visible. Strictly speaking, dynspread could
still be useful for other glyph types if that glyph is
contained entirely in a pixel, e.g. if a polygon or line
segment is located within the pixel bounds, but that seems
unlikely.
* Dynspread may need to have the threshold or max_px arguments
updated to achieve the same spreading as in previous releases,
though the new behavior is normally going to be more useful
than the old.
- Drop datashader-pr996-numpy-ragged.patch
- Add datashader-pr1022-RaggedTests.patch
- Add datashader-pr1025-testfixes.patch
- Skip remaining failing ragged tests gh#holoviz/datashader#1043
- Add datashader-pr996-numpy-ragged.patch in order to fix
failures with NumPy 1.20 -- gh#holoviz/datashader#995 and
gh#holoviz/datashader#996
- Update to version 0.12.1:
* Fix for xarray 0.17 raster files, supporting various nodata
conventions (gh#holoviz/datashader#991)
* Fix RaggedArray groupby test
* Disable the interactivity warning on the homepage
(gh#holoviz/datashader#983)
- Add BuildRequires: python-numpy now needed for building.
- skip python 36
- Test in _multibuild flavor in order to avoid build dependency
cycle with holoviews
- update to version 0.11.1:
* Fixes support for cuDF 0.13 and Numba 0.48 (#933)
* Fixes for cuDF support on Numba>=0.51 (#934, #947)
* Fixes tile generation using aggregators with output of boolean
dtype (#949)
* Fixes for CI and build infrastructure (#935, #948, #951)
* Updates to docstrings (b1349e3, #950)
- version update to 0.11.0
New features (see getting_started/2_Pipeline.ipynb for examples):
New by() categorical aggregator, extending count_cat to work with other reduction functions, no longer just count. 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)
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 Dask-based raster mesh rendering (via Canvas.quadmesh) (#872)
Faster TMS tileset generation (#886)
Expanded performance guide (#868)
Bugfixes:
Misc bugfixes and improvements (#874, #882, #888, #889, #890, #891)
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 to count_cat or by.
count_cat is now deprecated and removed from the docs; use by(..., count()) instead.
Result of a count() aggregation is now uint32, not int32, 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)
- %python3_only -> %python_alternative
- Update to 0.10.0:
* Compatibility with new pandas, numba and llvm
- update to version 0.9.0:
* New features:
+ Support for CUDA GPU dataframes (cudf and dask_cudf) (#794,
#793, #821, #841, #842)
+ Documented new quadmesh support (renaming user guide section
5_Rasters to 5_Grids to reflect the more-general grid support)
(#805)
* Bugfixes and compatibility:
+ Avoid double-counting line segments that fit entirely into a
single rendered pixel (#839)
+ Improved geospatial toolbox, including 75X speedups to viewshed
algorithm (#811, #824, #844)
- Fix build dependencies.
- Update to 0.8.0:
* Compatibility with latest Numba, Intake, Pandas, and Xarray (#763, #768, #791)
* Improved datetime support (#803)
* Simplified docs (now built on Travis, and no longer requiring GeoViews) and examples (now on examples.pyviz.org)
* Skip rendering of empty tiles (#760)
* Improved performance for point, area, and line glyphs (#780)
* InteractiveImage and Pipeline are now deprecated; removed from examples (#751)
- Disable python2 builds.
This requires xarray, which requires python3 now.
- Update to version 0.7.0
+ New features:
* Simplified Panel-based dashboard using new Param features; now only 48 lines with fewer new concepts (#707)
* Added pandas ExtensionArray and Dask support for storing homogeneous ragged arrays (#687)
* Added SpatialPointsFrame and updated census, osm-1billion, and osm examples to use it (#702, #706, #708)
* Expanded 8_Geography.ipynb to document other geo-related functions
* Added Dask support for trimesh rendering, though computing the mesh initially still requires vertices and simplicies to fit into memory (#696)
* Add zero-copy rendering of row-oriented line coordinates, using a new axis argument (#694)
+ Bugfixes and compatibility:
* Added lnglat_to_meters to geo module; new code should import it from there (#708)
- Update to version 0.6.9
+ New features:
* Replaced outdated 536-line Bokeh dashboard.py with 71-line Panel+HoloViews dashboard.ipynb (#676)
* Allow aggregating xarray objects (in addition to Pandas and Dask DataFrames) (#675)
* Create WMTS tiles from Datashader data (#636)
* Added various geographic utility functions (ndvi, slope, aspect, hillshade, mean, bump map, Perlin noise) (#661)
* Made OpenSky data public (#691)
+ Bugfixes and compatibility:
* Fix array bounds error on line glyph (#683)
* Fixed the span argument to tf.shade (#680)
* Fixed composite.add (for use in spreading) to clip colors rather than overflow (#689)
* Fixed gerrymandering shape file (#688)
* Updated to match Bokeh (#656), Dask (#681, #667), Pandas/Numpy (#697)
- Remove upstream included python-datashader-dask-api-change-fix.patch
- Added patch to fix broken test_dask tests.
* python-datashader-dask-api-change-fix.patch
Upstream URL: https://github.com/pyviz/datashader/pull/667
- Update to version 0.6.8
+ New features:
* Added Strange Attractors example (#632)
* Major speedup: optimized dask datashape detection (#634)
+ Bugfixes and compatibility:
* Silenced inappropriate warnings (#631)
* Fixed various other bugs, including #644
* Added handling for zero data and zero range (#612, #648)
- Switch to pypi sources
- Fix dependencies.
- Rebuilt with the new numba
- Update to 0.6.7:
- Supports dask >= 0.18.
- InteractiveImage is now deprecated; please use the Datashader
support in HoloViews instead.
- Updated installation and example instructions to use new
datashader command.
- Ensured transparent (not black) image is returned when there is no
data to plot (thanks to Nick Xie)
- Simplified getting-started example (thanks to David Jones)
- Fix some grammar issues.
- Use %license tag
- Update to 0.6.5
+ New features:
- Trimesh support: Rendering of irregular triangular meshes
using Canvas.trimesh() (see user guide) (#525,#552)
- Added a new website at datashader.org, with new Getting
Started pages and an extensive User Guide, with about 50%
new material not previously in example notebooks. Built
entirely from Jupyter notebooks, which can be run in the
examples/ directory. Website is now complete except for
sections on points (see the nyc_taxi example in the
meantime).
- Canvas.raster() now accepts xarray Dataset types, not just
DataArrays, with the specific DataArray selectable from the
Dataset using the column= argument of a supplied
aggregation function.
- tf.Images() now displays anything with an HTML
representation, to allow laying out Pandas dataframes
alongside datashader output.
+ Bugfixes and compatibility:
- Changed Raster API to match other glyph types:
> Now accepts a reduction function via an agg= argument
like Canvas.line(), Canvas.points(), etc. The previous
downsample_method is still accepted for this release, but
is now deprecated.
> upsample_method is now interpolate, accepting linear=True
or linear=False; the previous spelling is now deprecated.
> The layer= argument previously accepted a 1-based integer
index, which was confusing given the standard Python
0-based indexing elsewhere. Changed to accept an xarray
coordinate, which can be a 1-based index if that's what is
defined on the array, but also works with arbitrary
floating-point coordinates (e.g. for a depth parameter in
an image stack).
> Now auto-ranges in x and y when not given explicit ranges,
instead of raising an error.
- Fixed various bugs, including one generating incorrect output
in Canvas.raster(agg='mode')
- initial version
OBS-URL: https://build.opensuse.org/request/show/1360240
OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/python-datashader?expand=0&rev=37