Comments (6)
astrofrog
commented on August 23, 2024
1
Thanks for reporting this, this definitely seems like a bug! I'm going to be able to address this in the next few weeks but if anyone has a chance to investigate and open a pull request, I'll happily review it!
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astrofrog
commented on August 23, 2024
Glancing at the code, I think the issue is that we currently assume all arrays have the same memory layout since we use a single NpyIter_AdvancedNew for all arrays. This should clearly be generalized to avoid the kind of issue described above.
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astrofrog
commented on August 23, 2024
I found the issue, PR forthcoming
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astrofrog
commented on August 23, 2024
@LucasCampos - could you check whether things work fine with the latest developer version?
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LucasCampos
commented on August 23, 2024
Hey! Thanks for suck a quick reponse. I can confirm that the new code works locally as well!
Numpy version 1.18.1
Fast-histogram version 0.9.dev2+g82f140b
NOT EXPLICITLY COPYING THE DATA
===FAST-HIST===
[[0. 0. 0. ... 0. 0. 0. ]
[0.00524697 0.11627543 0.00218829 ... 0. 0. 0. ]
[0. 0.0233833 0.08906353 ... 0. 0. 0. ]
...
[0. 0. 0. ... 0. 0. 0. ]
[0. 0. 0. ... 0. 0. 0. ]
[0. 0. 0. ... 0. 0. 0. ]]
===NUMPY===
[[0. 0. 0. ... 0. 0. 0. ]
[0.00524697 0.11627543 0.00218829 ... 0. 0. 0. ]
[0. 0.0233833 0.08906353 ... 0. 0. 0. ]
...
[0. 0. 0. ... 0. 0. 0. ]
[0. 0. 0. ... 0. 0. 0. ]
[0. 0. 0. ... 0. 0. 0. ]]
EXPLICITLY COPYING THE DATA
===FAST-HIST===
[[0. 0. 0. ... 0. 0. 0. ]
[0.00524697 0.11627543 0.00218829 ... 0. 0. 0. ]
[0. 0.0233833 0.08906353 ... 0. 0. 0. ]
...
[0. 0. 0. ... 0. 0. 0. ]
[0. 0. 0. ... 0. 0. 0. ]
[0. 0. 0. ... 0. 0. 0. ]]
===NUMPY===
[[0. 0. 0. ... 0. 0. 0. ]
[0.00524697 0.11627543 0.00218829 ... 0. 0. 0. ]
[0. 0.0233833 0.08906353 ... 0. 0. 0. ]
...
[0. 0. 0. ... 0. 0. 0. ]
[0. 0. 0. ... 0. 0. 0. ]
[0. 0. 0. ... 0. 0. 0. ]]
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astrofrog
commented on August 23, 2024
@LucasCampos - thanks! I'll make a new release.
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Related Issues (20)
- Add support for 32-bit and non-native-endian HOT 1
- Incorrect work for 3d np.array HOT 1
- Hypothesis failures HOT 2
- histogram result has strange spikes as compared to numpy histogram HOT 3
- Add 3D or N-d histogram function HOT 2
- Release the GIL
- Add OpenMP HOT 2
- setup_requires without install_requires not supported by NumPy HOT 2
- Numpy version in pyproject.toml should be pinned
- messing around with alternatives
- upstreaming HOT 2
- Long doubles make histogram2d fail subtly, maybe add type check? HOT 3
- Bug in v0.7: Incorrect way to translate input number to histogram bin HOT 1
- Improve how we generate test cases with hypothesis HOT 1
- Suggestion: memory allocation enhancement
- [0.11] Segmentation fault on tests HOT 5
- different result compared to numpy HOT 4
- histogram1d returns incorrect bins due to rounding error
- Thanks for all the work HOT 1
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