Comments (3)
From [email protected] on November 19, 2010 02:01:27
hmmm, please don't look at it/try it just yet :) I was so excited I didn't check if the results were even correct, and it turns out it computes garbage. I know why, so I'll fix this ASAP. I think and hope the speed will be the same after fixing that, but I'm not sure... Stay tuned...
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From [email protected] on November 19, 2010 02:36:19
For some reason, the correct version is slower than current numexpr. I guess this was too good to be true... It seems like my C optimization tricks from 15 years ago don't work anymore... Please close this ticket (and bury it as deep as possible ;-)). Sorry for the spam.
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From [email protected] on November 19, 2010 02:58:35
Well, at least you experimented with the computing kernel, so you may say that you are kind of an 'expert' with numexpr now. Remember that in order to get a good result you need to get wrong first (and not only once :-)
Status: Invalid
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Related Issues (20)
- ValueError exception for scientific notation with digits after . HOT 2
- It is not possible to disable sanitization via `NUMEXP_SANITIZE` when using `numexpr.NumExpr` HOT 2
- pow with integer arrays that overflow differs from numpy in 2.8.7 HOT 5
- Please upload a pure python wheel to PyPi HOT 2
- ``global_dict`` input ignored in version 2.8.7 HOT 5
- support new numpy complex types HOT 5
- Forbidden Control Character Error for imaginary element HOT 1
- `NPY_MAXARGS` not a compile time constant HOT 3
- Test failures on PyPy3.10: mostly `ValueError: ex_uses_vml parameter is required` HOT 28
- numexpr.test() not working on Mac M1, python 3.9, numpy 2.0.0.dev HOT 2
- [BUG]: Sanitizing regex does not exclude string literals HOT 3
- 2.9.0 tar.gz is missing on pypi HOT 2
- Numexpr engine in pandas fails when using eval on a dataframe HOT 1
- Stale Issues HOT 6
- Copy transpose operation HOT 1
- Tests fail on 12-thread Ryzen 5 HOT 5
- Complex (imaginary) evaluations HOT 7
- Citation preferences
- Is it possible to programatically invert a `numexpr`? HOT 1
- pandas testsuite with numpy 2.0.0rc1 fails on numexpr HOT 1
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