8000 Why does indexing an array after boolean comparison provide different results than doing a boolean comparison of an index? · Issue #10982 · numpy/numpy · GitHub
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Why does indexing an array after boolean comparison provide different results than doing a boolean comparison of an index? #10982

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grantmwilliams opened this issue Apr 26, 2018 · 5 comments
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Why does indexing an array after boolean comparison provide different results than doing a boolean comparison of an index? #10982

grantmwilliams opened this issue Apr 26, 2018 · 5 comments
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33 - Question Question about NumPy usage or development

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@grantmwilliams
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So for context this question comes from this post on stackoverflow: https://stackoverflow.com/questions/50047174/array-comparison-not-matching-elementwise-comparison-in-numpy#50047327

I have a numpy array arr. It's a numpy.ndarray, size is (5553110,), dtype=float32.

When I do:

(arr > np.pi )[3154950]
False
(arr[3154950] > np.pi )
True

Why is the first comparison getting it wrong? And how can I fix it?

The values:

arr[3154950]= 3.1415927
np.pi= 3.141592653589793

Is the problem with precision?

Would someone be able to explain the difference in the way numpy approaches the problem? It looks like using np.float64 explicitly fixes the problem, but I'm curious to know if numpy does a different casting in the two indexing methods.
@eric-wieser
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eric-wieser commented Apr 26, 2018 •
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Numpy has different promotion rules for scalars vs arrays, which I'd consider to be a bug (#10322)

In this case, arr is of dtype np.float32, and np.pi is of dtype np.float64.

Your first example is computing arr > np.float32(np.pi), whereas your second is computing np.float64(arr[3154950]) > np.pi

@grantmwilliams
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grantmwilliams 8000 commented Apr 26, 2018

@eric-wieser ah perfect. That's exactly what I was looking for. So in the first example numpy treats the values of the arr as np.float32 to match np.pi correct?

@eric-wieser
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eric-wieser commented Apr 26, 2018 •
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You have that backwards. In the first example numpy throws away precision from np.pi first, casting it from float64 to float32

@grantmwilliams
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Oh right that's totally my bad. Guess i was reading too fast

@h-vetinari h-vetinari mentioned this issue Jan 25, 2019
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@bsipocz bsipocz added the 33 - Question Question about NumPy usage or development label May 21, 2022
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bsipocz commented May 21, 2022

This question has been answered, and links to relevant bug reports are made, so closing the issue. Please reopen if you think it tracks something distinct not duplicated in another issue.
700D

@bsipocz bsipocz closed this as completed May 21, 2022
@AtanasGruev AtanasGruev mentioned this issue Oct 22, 2024
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