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dsshow crashing with AttributeError after numpy update #1209
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Hi @DStauffman. This was fixed in #1176. There will be a new release of |
The latest numpy=1.24 version installed via readthedocs is incompatible with datashader=0.14.4, resulting in an error like `AttributeError: module 'numpy' has no attribute 'warnings'`. This was reported in holoviz/datashader#1209 and fixed in holoviz/datashader#1176, but will need to wait for datashader>=0.14.5 to be released.
* 🐛 Fix DatashaderRasterizer to allow N:1 instead of just 1:1 Used to wrong boolean operator (should be and, not or) which meant DatashaderRasterizer didn't work when the vector_datapipe was length 1 and canvas_datapipe was length 2 or more. This prevents false errors like `ValueError: Unmatched lengths for the canvas datapipe (XarrayCanvasIterDataPipe) and vector datapipe (PyogrioReaderIterDataPipe). The vector datapipe's length (1) should either be (1) to allow for broadcasting, or match the canvas datapipe's length of (2)`. Patches the bugfix at #39 from zen3geo v0.3.0. Also updated a unit test to use a 2:1 canvas:vector ratio to prevent regression. * 📌 Temporarily pin numpy<1.24 to prevent AttributeError The latest numpy=1.24 version installed via readthedocs is incompatible with datashader=0.14.4, resulting in an error like `AttributeError: module 'numpy' has no attribute 'warnings'`. This was reported in holoviz/datashader#1209 and fixed in holoviz/datashader#1176, but will need to wait for datashader>=0.14.5 to be released.
Any ETA for the release? Numpy 1.24 is already quite old, this could (should) be a bugfix release that does not wait for all the issues in the v0.14.5 milestone. |
There is a dev release 0.14.5a1 out on PyPI (https://pypi.org/project/datashader/0.14.5a1/) and the The timing of numpy 1.24 isn't relevant, it is the timing of the numba release that supports numpy 1.24. That was 0.57 which was released 2 weeks ago. |
Right, I did not notice the pre-release! Thanks for handling the numba changes. |
ALL software version info
Description of expected behavior and the observed behavior
In datashader\core.py, function bypixel throws an error with the np.warnings command:
Seems to be fine in older versions of numpy. I'm not sure if this is now expected behavior that needs to be adapted or if it's an upstream bug in numpy.
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