def test_PrfIntensityReducer():
"""Test the methods of the PrfIntensityReducer class"""
reflections = generate_integrated_test_reflections()
reflections = PrfIntensityReducer.reduce_on_intensities(reflections)
assert list(reflections["intensity.prf.value"]) == [1.0, 2.0, 3.0, 6.0]
assert list(reflections["intensity.prf.variance"]) == [0.1, 0.2, 0.3, 0.6]
reflections = generate_test_reflections_for_scaling()
reflections = PrfIntensityReducer.apply_scaling_factors(reflections)
assert list(reflections["intensity.prf.value"]) == [1.0, 3.0, 4.0, 20.0, 3.0]
assert list(reflections["intensity.prf.variance"]) == pytest.approx(
[0.1, 0.3, 0.4, 0.5 * 16.0, 0.6 * 0.25]
)
# check it still passes with no partiality correction
reflections = generate_test_reflections_for_scaling()
del reflections["partiality"]
reflections = PrfIntensityReducer.apply_scaling_factors(reflections)
assert list(reflections["intensity.prf.value"]) == [1.0, 2.0, 3.0, 4.0, 20.0, 3.0]
# test IsgiI selecting
r = flex.reflection_table()
r["intensity.prf.value"] = flex.double([1.0, 2.0])
r["intensity.prf.variance"] = flex.double([1.0, 1.0])
r = PrfIntensityReducer.filter_on_min_isigi(r, 1.5)
assert list(r["intensity.prf.value"]) == [2.0]
# now test a typical case - reflection table with inv scale factor,
# check that we only apply that correction and do any relevant filtering
reflections = generate_integrated_test_reflections()
reflections["qe"] = flex.double(6, 2)
reflections = PrfIntensityReducer.filter_for_export(reflections)
assert list(reflections["intensity.prf.value"]) == pytest.approx(
[1.0 / 2.0, 2.0 / 2.0, 3.0 / 2.0, 6.0 / 2.0]
)
assert list(reflections["intensity.prf.variance"]) == pytest.approx(
[0.1 / 4.0, 0.2 / 4.0, 0.3 / 4.0, 0.6 / 4.0]
)
assert list(reflections["fractioncalc"]) == [1.0] * 4
assert "intensity.sum.value" not in reflections
assert "intensity.scale.value" not in reflections
assert "intensity.sum.variance" not in reflections
assert "intensity.scale.variance" not in reflections
def test_IntensityReducer_instantiations():
"""Test that all classes can be instantiated (have the required implemented
methods) and have an intensities list with at least one str values"""
allowed_intensities = FilterForExportAlgorithm.allowed_intensities
SumIntensityReducer()
assert all(i in allowed_intensities for i in SumIntensityReducer.intensities)
PrfIntensityReducer()
assert all(i in allowed_intensities for i in PrfIntensityReducer.intensities)
SumAndPrfIntensityReducer()
assert all(i in allowed_intensities for i in SumAndPrfIntensityReducer.intensities)
ScaleIntensityReducer()
assert all(i in allowed_intensities for i in ScaleIntensityReducer.intensities)
def test_checks_in_reduce_data_for_export():
"""Test for graceful failures if serious problems with the data are found."""
# If no valid ids, should raise sorry
r = flex.reflection_table()
r["id"] = flex.int([-1, -1, -1])
r["intensity.prf.value"] = flex.double(3, 1.0)
r["intensity.prf.variance"] = flex.double(3, 1.0)
with pytest.raises(ValueError):
r = PrfIntensityReducer.filter_for_export(r)
# If no valid prf, should raise NoProfilesException
r = flex.reflection_table()
r["id"] = flex.int([0, 0])
r["intensity.prf.value"] = flex.double([1.0, 2.0])
r["intensity.prf.variance"] = flex.double([0.0, 1.0])
r.set_flags(flex.bool([False, False]), r.flags.integrated_prf)
with pytest.raises(NoProfilesException):
r = PrfIntensityReducer.filter_for_export(r)
r.set_flags(flex.bool([True, True]), r.flags.integrated_prf)
# Should filter bad variances
r = PrfIntensityReducer.filter_bad_variances(r)
assert r.size() == 1
# If reflection table is empty
r = flex.reflection_table()
with pytest.raises(AssertionError):
r = PrfIntensityReducer.filter_for_export(r)
# What if all ice ring
r = generate_simple_table()
r.set_flags(flex.bool([True, True, True]), r.flags.in_powder_ring)
with pytest.raises(ValueError):
_ = PrfIntensityReducer.filter_for_export(r,
filter_ice_rings=True,
min_isigi=1.0,
partiality_threshold=0.99)
# What if none left on SigI
r = generate_simple_table()
with pytest.raises(ValueError):
_ = PrfIntensityReducer.filter_for_export(r,
filter_ice_rings=False,
min_isigi=4.0,
partiality_threshold=0.99)