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BUG: quantile should error when weights are all zeros #28595

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BUG: quantile should error when weights are all zeros #28595

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293ea24
added err messages and tests
Tontonio3 Mar 27, 2025
ae8cd54
Modified tests and added release note
Tontonio3 Mar 27, 2025
565fc75
Fixed tests
Tontonio3 Mar 27, 2025
8309d16
Fixed bug to handle object dtypes
Tontonio3 Mar 27, 2025
04d05f6
Fixed bug to handle object dtypes
Tontonio3 Mar 27, 2025
c76b5ad
Streamlined testing, improved error handling capabilities
Tontonio3 Mar 28, 2025
bfcec09
Changed infinite error message
Tontonio3 Mar 28, 2025
f06a1f8
Bug fix
Tontonio3 Mar 28, 2025
1303b3c
Fixed lint test
Tontonio3 Mar 28, 2025
ad95df2
Improved testing
Tontonio3 Apr 2, 2025
dc14e6b
Changed error handling, made it faster, removed dtype=object special …
Tontonio3 Apr 2, 2025
8eeed6a
More comprehensive testing
Tontonio3 Apr 2, 2025
4fe3444
More comprehensive testing
Tontonio3 Apr 3, 2025
ba2c398
Fixed lint
Tontonio3 Apr 3, 2025
2e8e2ea
Fixed tests
Tontonio3 Apr 3, 2025
3a20796
Fixed CircleCI test
Tontonio3 Apr 7, 2025
40075b3
streamlined checks
Tontonio3 Apr 24, 2025
a83887b
lint fix
Tontonio3 Apr 28, 2025
3d1c7b0
lint fix
Tontonio3 Apr 28, 2025
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Fixed bug to handle object dtypes
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@Tontonio3
Tontonio3 committed Mar 27, 2025
commit 04d05f6f66e4dd130ef84f56292d35b226e68d6d
2 changes: 1 addition & 1 deletion numpy/lib/_function_base_impl.py
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Expand Up @@ -4544,7 +4544,7 @@ def quantile(a,
raise ValueError("Weights must be non-infinite")
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nit: non-infinite-> finite probably

elif np.any(np.isnan(weights)):
raise ValueError("At least one weight is nan")
elif weights.dtype is object:
elif weights.dtype == object:
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Note that this loop can still give unexpected errors, because you are here counting on object arrays to be turned into their values as scalars. E.g.,

np.isnan(np.array([1.,None,np.inf])[1])
# TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

This will be an uninformative error!

I think we have two choices: just not check for object dtype, or convert to float before checking (and then passing on it that conversion fails).

for w in weights:
if np.isnan(w):
raise ValueError("At least one weight is nan")
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