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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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lint fix
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@Tontonio3
Tontonio3 committed Apr 28, 2025
commit a83887b6c0bc09d2ee69e9a61f0fdf72d1d44255
5 changes: 1 addition & 4 deletions numpy/lib/tests/test_function_base.py
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Expand Up @@ -4158,9 +4158,7 @@ def test_inf_zeroes_err(self, err_msg, weight, dty):
a = np.quantile(arr, q, weights=wgts, method=m)

@pytest.mark.parametrize("weight", [[1, np.nan, 1, 1], [1, np.nan, np.nan, 1]])
@pytest.mark.parametrize(["err", "dty"],
[(ValueError, "f8"),
((RuntimeWarning, ValueError), "O")])
@pytest.mark.parametrize(["err", "dty"], [(ValueError, "f8"), ((RuntimeWarning, ValueError), "O")])
def test_nan_err(self, err, dty, weight):

m = "inverted_cdf"
Expand All @@ -4170,7 +4168,6 @@ def test_nan_err(self, err, dty, weight):
with pytest.raises(err):
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might as well use match here too

a = np.quantile(arr, q, weights=wgts, method=m)


class TestLerp:
@hypothesis.given(t0=st.floats(allow_nan=False, allow_infinity=False,
min_value=0, max_value=1),
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