Bug#1117996: dials: autopkgtest regression with scikit-learn 1.7.2

[Timo Röhling]

Source: dials
Version: 3.25.0+dfsg3-2
Severity: important
User: debian-science at lists.debian.org
Usertags: scikit-learn-1.7

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Dear maintainer,

your package has an autopkgtest regression with scikit-learn 1.7.2.
Relevant excerpt from 
https://ci.debian.net/packages/d/dials/unstable/amd64/65190517/ 
follows:


1210s ____________________________ test_IhTable_freework _____________________________
1210s
1210s large_reflection_table = <dials_array_family_flex_ext.reflection_table object at 0x7fa84e3c7330>
1210s small_reflection_table = <dials_array_family_flex_ext.reflection_table object at 0x7fa84e3c4fe0>
1210s test_sg = <cctbx_sgtbx_ext.space_group object at 0x7fa84e3c7e70>
1210s
1210s     def test_IhTable_freework(large_reflection_table, small_reflection_table, test_sg):
1210s         sel1 = flex.bool(7, True)
1210s         sel1[6] = False
1210s         sel2 = flex.bool(4, True)
1210s         sel2[1] = False
1210s
1210s >       Ih_table = IhTable(
1210s             reflection_tables=[
1210s                 large_reflection_table.select(sel1),
1210s                 small_reflection_table.select(sel2),
1210s             ],
1210s             indices_lists=[sel1.iselection(), sel2.iselection()],
1210s             space_group=test_sg,
1210s             nblocks=2,
1210s             free_set_percentage=50.0,
1210s         )
1210s
1210s tests/algorithms/scaling/test_Ih_table.py:461:
1210s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
1210s /usr/lib/python3/dist-packages/dials/algorithms/scaling/Ih_table.py:132: in __init__
1210s     self.extract_free_set()
1210s /usr/lib/python3/dist-packages/dials/algorithms/scaling/Ih_table.py:438: in extract_free_set
1210s     free_block = IhTableBlock(
1210s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
1210s
1210s self = <dials.algorithms.scaling.Ih_table.IhTableBlock object at 0x7fa82807f770>
1210s n_groups = 3, n_refl = np.int64(5), n_datasets = 2
1210s
1210s     def __init__(self, n_groups: int, n_refl: int, n_datasets: int = 1):
1210s         """Create empty datastructures to which data can later be added."""
1210s         self.Ih_table = pd.DataFrame()
1210s         self.block_selections = [None] * n_datasets
1210s >       self.h_index_matrix = sparse.matrix(n_refl, n_groups)
1210s                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
1210s E       Boost.Python.ArgumentError: Python argument types in
1210s E           matrix.__init__(matrix, numpy.int64, int)
1210s E       did not match C++ signature:
1210s E           __init__(boost::python::api::object, unsigned long rows, unsigned long columns, boost::python::list elements_by_columns)
1210s E           __init__(_object*, unsigned long rows, unsigned long columns)
1210s
1210s /usr/lib/python3/dist-packages/dials/algorithms/scaling/Ih_table.py:519: ArgumentError


Cheers
Timo

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