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| Name: python310-datashader | Distribution: openSUSE Tumbleweed |
| Version: 0.16.3 | Vendor: openSUSE |
| Release: 4.1 | Build date: Sun Sep 22 14:17:10 2024 |
| Group: Unspecified | Build host: reproducible |
| Size: 26938423 | Source RPM: python-datashader-0.16.3-4.1.src.rpm |
| Packager: https://bugs.opensuse.org | |
| Url: https://datashader.org | |
| Summary: Data visualization toolchain based on aggregating into a grid | |
Traditional visualization systems treat plotting as a unitary process transforming incoming data into an onscreen or printed image, with parameters that can be specified beforehand that affect the final result. While this approach works for small collections of data that can be viewed in their entirety, the visualization for large datasets is often the only way to understand what the data consists of, and there is no objective way to set the parameters to reveal this data. The datashader library breaks up the rendering pipeline into a series of stages where user-defined computations can be performed, allowing the visualization to adapt to and reveal the underlying properties of the dataset, i.e. the datashader pipeline allows computation *on the visualization*, not just on the dataset, allowing it to do automatic ranging and scaling that takes the current visualization constraints into account. For instance, where a traditional system would use a transparency/opacity parameter to show the density of overlapping points in a scatterplot, datashader can automatically calculate how many datapoints are mapped to each pixel, scaling the representation to accurately convey the data at every location, with no saturation, overplotting, or underplotting issues.
BSD-3-Clause
* Sun Sep 22 2024 Ben Greiner <code@bnavigator.de>
- Don't require runtime requirements for building: Avoid resolver
conflict for numpy with numba
* Fri Aug 30 2024 Ben Greiner <code@bnavigator.de>
- Unpin numpy 2
* Thu Jul 11 2024 Steve Kowalik <steven.kowalik@suse.com>
- Restrict numpy to < 2.
* Mon Jul 08 2024 Dirk Müller <dmueller@suse.com>
- 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
* Mon Jun 24 2024 Steve Kowalik <steven.kowalik@suse.com>
- 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.
* Sat Mar 02 2024 Ben Greiner <code@bnavigator.de>
- Skip python39: no xarray anymore
- Add datashader-pr1314-fix-pandas2.2-tests.patch
gh#holoviz/datashader#1314
* Fri Feb 09 2024 Daniel Garcia <daniel.garcia@suse.com>
- 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
* Mon Oct 30 2023 Dirk Müller <dmueller@suse.com>
- 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)
* Wed Sep 20 2023 Markéta Machová <mmachova@suse.com>
- Add pd21.patch to support Pandas 2.1
* Mon Sep 18 2023 Dirk Müller <dmueller@suse.com>
- 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
* Sun Aug 13 2023 Dirk Müller <dmueller@suse.com>
- 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
* Fri Jun 02 2023 Ben Greiner <code@bnavigator.de>
- Mention dropped patches:
* Do-not-use-warnings-from-numpy.patch
* numpy-1.24.patch
* Thu Jun 01 2023 Ben Greiner <code@bnavigator.de>
- 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
* Mon May 29 2023 Dirk Müller <dmueller@suse.com>
- reenable python311 (dask available)
* Wed Mar 22 2023 Ben Greiner <code@bnavigator.de>
- Skip python38: No xarray anymore
- Skip python311: No dask-all and numba yet
* Tue Feb 07 2023 Daniel Garcia <daniel.garcia@suse.com>
- 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)
* Mon Nov 21 2022 Ben Greiner <code@bnavigator.de>
- 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
* Tue Apr 26 2022 Matej Cepl <mcepl@suse.com>
- Remove skip_python310, it is not needed anymore.
* Mon Jan 31 2022 Ben Greiner <code@bnavigator.de>
- 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
* Thu Apr 01 2021 Ben Greiner <code@bnavigator.de>
- Add datashader-pr996-numpy-ragged.patch in order to fix
failures with NumPy 1.20 -- gh#holoviz/datashader#995 and
gh#holoviz/datashader#996
* Thu Mar 18 2021 Atri Bhattacharya <badshah400@gmail.com>
- 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.
* Fri Feb 12 2021 Dirk Müller <dmueller@suse.com>
- skip python 36
* Sat Jan 02 2021 Benjamin Greiner <code@bnavigator.de>
- Test in _multibuild flavor in order to avoid build dependency
cycle with holoviews
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