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TST use global_random_seed in sklearn/decomposition/tests/test_factor_analysis.py #29272

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Merged
merged 6 commits into from
Jun 20, 2024
Merged

TST use global_random_seed in sklearn/decomposition/tests/test_factor_analysis.py #29272

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3f14fc3
test: add global_random_seed
marenwestermann Jun 16, 2024
6a04883
trigger CI [all random seeds] test_factor_analysis
marenwestermann Jun 17, 2024
1782f55
trigger CI no2 [all random seeds] test_factor_analysis
marenwestermann Jun 17, 2024
efc13fc
Merge remote-tracking branch 'upstream/main' into test-factor-analysis
marenwestermann Jun 17, 2024
6bae110
let's try again [all random seeds] test_factor_analysis
marenwestermann Jun 17, 2024
c78f661
[azure parallel] Trigger full CI just in case ...
lesteve Jun 18, 2024
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6 changes: 3 additions & 3 deletions sklearn/decomposition/tests/test_factor_analysis.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,9 +19,9 @@

# Ignore warnings from switching to more power iterations in randomized_svd
@ignore_warnings
def test_factor_analysis():
def test_factor_analysis(global_random_seed):
# Test FactorAnalysis ability to recover the data covariance structure
rng = np.random.RandomState(0)
rng = np.random.RandomState(global_random_seed)
n_samples, n_features, n_components = 20, 5, 3

# Some random settings for the generative model
Expand Down Expand Up @@ -57,7 +57,7 @@ def test_factor_analysis():
# Model Covariance
mcov = fa.get_covariance()
diff = np.sum(np.abs(scov - mcov)) / W.size
assert diff < 0.1, "Mean absolute difference is %f" % diff
assert diff < 0.2, "Mean absolute difference is %f" % diff
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When I added the global_random_seed fixture I got the following test failures:

FAILED sklearn/decomposition/tests/test_factor_analysis.py::test_factor_analysis[16] - AssertionError: Mean absolute difference is 0.170675
FAILED sklearn/decomposition/tests/test_factor_analysis.py::test_factor_analysis[38] - AssertionError: Mean absolute difference is 0.130926
FAILED sklearn/decomposition/tests/test_factor_analysis.py::test_factor_analysis[96] - AssertionError: Mean absolute difference is 0.134258

By increasing the threshold the failures are fixed. 0.2 looks acceptable to me but let me know if you disagree.

fa = FactorAnalysis(
n_components=n_components, noise_variance_init=np.ones(n_features)
)
Expand Down