ENH: stats: Add nan_policy to zmap. #13166
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The change moves the zscore code to zmap, with the obvious change at the end to compute the z-scores for `scores`. zscore is now just a one-liner that calls zmap. Closes scipygh-12403.
mdhaber
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Dec 9, 2020
mdhaber
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Dec 9, 2020
mdhaber
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Dec 9, 2020
mdhaber
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Dec 9, 2020
mdhaber
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Dec 9, 2020
mdhaber
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Dec 9, 2020
mdhaber
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Dec 9, 2020
mdhaber
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Dec 9, 2020
mdhaber
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mdhaber
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mdhaber
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Looks fine assuming the original code was correct, but I have a question about the ddof parameter - it's not used when nan_policy is omit.
import numpy as np
from scipy.stats import zmap
a = [0.5, 2.0, 2.5, 3]
b = [0, 1, 2, 3, 4]
r1 = zmap(a, b)
r2 = zmap(a, b, ddof = -1)
a = [0.5, 2.0, 2.5, 3, np.nan]
b = [0, 1, 2, 3, 4, np.nan]
r3 = zmap(a, b, nan_policy='omit')
r4 = zmap(a, b, ddof = -1, nan_policy='omit')
print(np.allclose(r1, r3[:-1]))
print(np.allclose(r2, r4[:-1]))
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Thanks for catching that bug, @mdhaber. I pushed an update with a fix and new tests. |
mdhaber
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Dec 11, 2020
| [-0.7071067811865476, 0, 0.7071067811865476]),] | ||
| ) | ||
| def test_zmap(self, x, y, expected): | ||
| z = stats.zmap(x, y) |
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Personally, I'd remove expected above and just calculate it here so that it's easier to verify that the numbers are correct.
expected = (x - np.mean(y))/np.std(y)
Or maybe the compromise is to add the formula as a comment.
Or just leave it alone. Just a thought. : )
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The one failure in Azure job |
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I added a note about this enhancement to the release notes. |
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The change moves the zscore code to zmap, with the obvious
change at the end to compute the z-scores for
scores.zscore is now just a one-liner that calls zmap.
Closes gh-12403.