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Support Numpy 1.25+ #1623

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merged 4 commits into from
Oct 10, 2023
Merged

Support Numpy 1.25+ #1623

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f7f9322
cap numpy version below 2
rwedge Oct 4, 2023
9d95ed8
update failing copulas test to use truncnorm
rwedge Oct 6, 2023
512208d
update failing constraints test to use truncnorm
rwedge Oct 6, 2023
b95609b
update failing evaluation test to use truncnorm
rwedge Oct 6, 2023
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4 changes: 2 additions & 2 deletions setup.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,8 +18,8 @@
'cloudpickle>=2.1.0,<3.0',
'Faker>=10,<15',
'graphviz>=0.13.2,<1',
"numpy>=1.20.0,<1.25.0;python_version<'3.10'",
"numpy>=1.23.3,<1.25.0;python_version>='3.10'",
"numpy>=1.20.0,<2;python_version<'3.10'",
"numpy>=1.23.3,<2;python_version>='3.10'",
"pandas>=1.1.3;python_version<'3.10'",
"pandas>=1.3.4;python_version>='3.10' and python_version<'3.11'",
"pandas>=1.5.0;python_version>='3.11'",
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4 changes: 2 additions & 2 deletions tests/integration/evaluation/test_single_table.py
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Expand Up @@ -12,13 +12,13 @@ def test_evaluation():
data = pd.DataFrame({'col': [1, 2, 3]})
metadata = SingleTableMetadata()
metadata.add_column('col', sdtype='numerical')
synthesizer = GaussianCopulaSynthesizer(metadata)
synthesizer = GaussianCopulaSynthesizer(metadata, default_distribution='truncnorm')

# Run and Assert
synthesizer.fit(data)
samples = synthesizer.sample(10)
score = evaluate_quality(data, samples, metadata).get_score()
assert score == 0.8333333333333334
assert score == 0.8666666666666667

diagnostic = run_diagnostic(data, samples, metadata).get_results()
assert diagnostic == {
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14 changes: 7 additions & 7 deletions tests/integration/single_table/test_constraints.py
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Expand Up @@ -534,7 +534,7 @@ def test_scalar_range_constraint_with_datetimes_and_nones():
})

metadata.validate()
synth = GaussianCopulaSynthesizer(metadata)
synth = GaussianCopulaSynthesizer(metadata, default_distribution='truncnorm')
synth.add_constraints([
{
'constraint_class': 'ScalarRange',
Expand All @@ -555,26 +555,26 @@ def test_scalar_range_constraint_with_datetimes_and_nones():
# Assert
expected_sampled = pd.DataFrame({
'A': {
0: '2020-03-03',
0: '2020-02-04',
1: np.nan,
2: '2020-03-03',
2: '2020-02-07',
3: np.nan,
4: np.nan,
5: '2020-03-03',
5: '2020-02-29',
6: np.nan,
7: np.nan,
8: np.nan,
9: '2020-02-27',
9: '2020-02-02',
},
'B': {
0: np.nan,
1: np.nan,
2: np.nan,
3: np.nan,
4: np.nan,
5: '2021-04-14',
5: '2021-11-22',
6: np.nan,
7: '2021-05-21',
7: '2021-06-19',
8: np.nan,
9: np.nan,
}
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4 changes: 2 additions & 2 deletions tests/integration/single_table/test_copulas.py
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Expand Up @@ -345,7 +345,7 @@ def test_numerical_columns_gets_pii():
'numerical': {'sdtype': 'numerical'}
}
})
synth = GaussianCopulaSynthesizer(metadata)
synth = GaussianCopulaSynthesizer(metadata, default_distribution='truncnorm')
synth.fit(data)

# Run
Expand All @@ -366,7 +366,7 @@ def test_numerical_columns_gets_pii():
8: 'Davidland',
9: 'Port Christopher'
},
'numerical': {0: 21, 1: 24, 2: 22, 3: 23, 4: 22, 5: 24, 6: 23, 7: 23, 8: 24, 9: 23}
'numerical': {0: 22, 1: 24, 2: 22, 3: 23, 4: 22, 5: 24, 6: 23, 7: 24, 8: 24, 9: 24}
})
pd.testing.assert_frame_equal(expected_sampled, sampled)

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