Mar 27, 2025 · Mar 27, 2025 · Mar 27, 2025 · Mar 27, 2025 · Mar 27, 2025 · Mar 28, 2025
diff --git a/numpy/lib/_function_base_impl.py b/numpy/lib/_function_base_impl.py
                raise ValueError("Weights must be non-infinite")
            elif np.any(np.isnan(weights)):
                raise ValueError("At least one weight is nan")
        elif weights.dtypeis object:
        elif weights.dtype== object:
            for w in weights:
                if np.isnan(w):
                    raise ValueError("At least one weight is nan")
Original file line number	Diff line number	Diff line change
Expand Up		@@ -4544,7 +4544,7 @@ def quantile(a,
		raise ValueError("Weights must be non-infinite")
Copy link Contributor tylerjereddyMar 28, 2025 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. nit: non-infinite-> finite probably
		elif np.any(np.isnan(weights)):
		raise ValueError("At least one weight is nan")
		elif weights.dtypeis object:
		elif weights.dtype== object:
Copy link Contributor mhvkMar 31, 2025 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. 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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