def test_simple_outlier_rejection(generated_Ih_table):
"""Test the simple outlier rejection algorithm."""
zmax = 6.0
outlier_rej = SimpleNormDevOutlierRejection(generated_Ih_table, zmax)
outlier_rej.run()
outliers = outlier_rej.final_outlier_arrays
assert len(outliers) == 1
assert list(outliers[0]) == [4, 5, 6, 7, 8, 9]
def test_multi_dataset_outlier_rejection(test_sg):
"""Test outlier rejection with two datasets."""
rt1 = flex.reflection_table()
rt1["intensity"] = flex.double(
[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 20.0, 400.0, 10.0])
rt1["variance"] = flex.double(9, 1.0)
rt1["inverse_scale_factor"] = flex.double(9, 1.0)
rt1["miller_index"] = flex.miller_index([
(0, 0, 1),
(0, 0, 1),
(0, 0, 1),
(0, 0, 1),
(0, 0, 2),
(0, 0, 2),
(0, 0, 2),
(0, 0, 2),
(0, 0, 3),
])
rt1.set_flags(
flex.bool(
[True, False, False, False, False, False, False, False, False]),
rt1.flags.excluded_for_scaling,
)
rt1.set_flags(flex.bool(9, False), rt1.flags.user_excluded_in_scaling)
rt2 = flex.reflection_table()
rt2["intensity"] = flex.double([10.0, 20.0, 500.0])
rt2["variance"] = flex.double(3, 1.0)
rt2["inverse_scale_factor"] = flex.double(3, 1.0)
rt2["miller_index"] = flex.miller_index([(0, 0, 23), (0, 0, 1), (0, 0, 2)])
rt2.set_flags(flex.bool([False, False, False]),
rt1.flags.excluded_for_scaling)
rt2.set_flags(flex.bool(3, False), rt2.flags.user_excluded_in_scaling)
Ih_table = IhTable([rt1, rt2], test_sg, nblocks=1)
zmax = 6.0
outlier_rej = SimpleNormDevOutlierRejection(Ih_table, zmax)
outlier_rej.run()
outliers = outlier_rej.final_outlier_arrays
assert len(outliers) == 2
assert list(outliers[0]) == [4, 5, 6, 7]
assert list(outliers[1]) == [1, 2]
outlier_rej = NormDevOutlierRejection(Ih_table, zmax)
outlier_rej.run()
outliers = outlier_rej.final_outlier_arrays
assert len(outliers) == 2
assert list(outliers[0]) == [7, 6]
assert list(outliers[1]) == [1, 2]