BUG: Pass DType class np.average to support weights argument for user-dtypes#31575
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SwayamInSync wants to merge 1 commit into
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BUG: Pass DType class np.average to support weights argument for user-dtypes#31575SwayamInSync wants to merge 1 commit into
np.average to support weights argument for user-dtypes#31575SwayamInSync wants to merge 1 commit into
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SwayamInSync
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np.average to support weights argument for user-dtypesnp.average to support weights argument for user-dtypes
mhvk
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Jun 6, 2026
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| a = np.array([1, 2, 3, 4], dtype=qd) | ||
| w = np.array([4, 3, 2, 1], dtype=qd) | ||
| assert float(np.average(a)) == 2.5 |
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I think one should test that the returned array has the right data type, with, e.g.,
assert_array_equal(np.average(a), np.array(2.5, dtype=qd), strict=True)
Note that it might also be good to make sure the precision is in fact kept, e.g., by writing
a = np.array([1, 2, 3, 4], dtype=qd) + np.array(1e-20, dtype=dq)
w = np.array([4, 3, 2, 1], dtype=qd) - np.array(1e-21, dtype=dq)
(and obviously adjusting the result accordingly)
Member
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This needs the quaddtype test helper from gh-31574. That looks like the reason for the CI failures here (it's very cryptic, but quaddtype had some bugs that caused cryptic crazy issues :)). |
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PR summary
Same fix as #31447
Discovered at numpy/numpy-quaddtype#106
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