Package: python3-scipy Version: 1.6.1-1 Severity: serious Tags: upstream Justification: FTBFS Control: forwarded -1 https://github.com/scipy/scipy/issues/13585 Control: affects -1 src:pandas src:qutip
scipy 1.6.1 marketed itself as "bug-fix only", but in fact introduced a change in the API handling sparse matrices with COO constructor. Reported upstream at https://github.com/scipy/scipy/issues/13585 with PR proposed at https://github.com/scipy/scipy/pull/13586 This causes pandas and qutip test to fail, so treating as FTBFS (severity serious). scipy 1.6.1 is not fit for bullseye. The signature of the problem is error messages concerning discrepancy dtyped of COO matrices e.g. * pandas (pandas.tests.arrays.sparse.test_array.TestAccessor.test_from_coo): index = pd.MultiIndex.from_arrays([[0, 0, 1, 3], [0, 2, 1, 3]]) expected = pd.Series([4, 9, 7, 5], index=index, dtype="Sparse[int]") > tm.assert_series_equal(result, expected) E AssertionError: Attributes of Series are different E E Attribute "dtype" are different E [left]: Sparse[float64, nan] E [right]: Sparse[int64, 0] /usr/lib/python3/dist-packages/pandas/tests/arrays/sparse/test_array.py:1196: AssertionError * qutip (tests.test_piqs.TestDicke.test_lindbladian): > self.data = np.array(obj, copy=copy, dtype=data_dtype) E TypeError: can't convert complex to float /usr/lib/python3/dist-packages/scipy/sparse/coo.py:161: TypeError
