Added a check innp.quantile to raise aValueError when theweights parameter are all zero, preventing invalid computations. Added corresponding tests to verify this behavior.

Closes#28589.

fix quantile all zeros error

1dbd180

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galio1237 commentedMar 27, 2025

Hello,

I'm a new contributor to this project and have submitted this pull request to address [Issue#28589].

However, I noticed that some of the status checks are failing. I've reviewed the output but am unsure how to resolve these issues. Could someone please provide guidance on the reasons for these failures and suggest steps to address them?

Thank you for your assistance.

tylerjereddy reviewed

Mar 28, 2025

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numpy/lib/tests/test_function_base.py

		with pytest.raises(ValueError, match="Weights must contain non-zero value."):
		np.quantile(y, 0.5, weights=w, method="inverted_cdf")

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tylerjereddyMar 28, 2025

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Could someone please provide guidance on the reasons for these failures and suggest steps to address them?

You can reproduce the linter failure observed in CI locally by runningspin lint on your branch. Purging the extra blank line it complains about will allowspin lint to pass locally and in CI. I checked the full test suite locally on this branch and it seems "ok."

The Qemu job failure in CI is clearly unrelated so don't worry about that.

For bug fixes, we usually prefix commits and titles of PRs withBUG:. You can find the list of prefixes in our docs.

Note for other NumPy devs--gh-28594 is very similar to this.