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from __future__ import annotations
import pytest
import iotbx.mtz
from cctbx import sgtbx
from cctbx.array_family import flex
from dxtbx.model import Experiment, ExperimentList, Scan
import dials.pychef
def test_observations():
miller_indices = flex.miller_index(
((1, 2, 3), (-1, 2, 3), (1, -2, 3), (4, 5, 6), (4, 5, -6))
)
sg = sgtbx.space_group_info(symbol="I222").group()
anomalous_flag = True
observations = dials.pychef.Observations(miller_indices, sg, anomalous_flag)
groups = observations.observation_groups()
assert list(groups[(1, 2, 3)].iplus()) == [0]
assert list(groups[(1, 2, 3)].iminus()) == [1, 2]
def test_accumulators(dials_data):
f = dials_data("pychef", pathlib=True) / "insulin_dials_scaled_unmerged.mtz"
mtz_object = iotbx.mtz.object(file_name=str(f))
arrays = mtz_object.as_miller_arrays(merge_equivalents=False)
for ma in arrays:
if ma.info().labels == ["BATCH"]:
batches = ma
elif ma.info().labels == ["I", "SIGI"]:
intensities = ma
elif ma.info().labels == ["I(+)", "SIGI(+)", "I(-)", "SIGI(-)"]:
intensities = ma
assert intensities is not None
assert batches is not None
anomalous_flag = True
if anomalous_flag:
intensities = intensities.as_anomalous_array()
stats = dials.pychef.Statistics(intensities, batches.data())
# test completeness
assert stats.iplus_comp_overall.size() == 46
assert stats.iplus_comp_overall[45] == pytest.approx(0.9428352196431997)
assert stats.iminus_comp_overall[44] == pytest.approx(0.07769038941108766)
assert stats.ieither_comp_overall[1] == pytest.approx(0.03721465566852101)
assert stats.iboth_comp_overall[-1] == pytest.approx(0.0779781315940917)
# test rcp,scp
print(list(stats.rcp))
print(list(stats.scp))
assert stats.rcp[45] == pytest.approx(0.04844584637191411)
assert stats.scp[45] == pytest.approx(0.9201295853457298)
# test Rd
print(list(stats.rd))
assert stats.rd[0] == pytest.approx(0.05234416616316846)
def test_interpret_images_to_doses_options():
"""Test handling of command line options for experiments input."""
experiments = ExperimentList()
experiments.append(Experiment(scan=Scan(image_range=(1, 10), oscillation=(0, 1.0))))
experiments.append(Experiment(scan=Scan(image_range=(1, 20), oscillation=(0, 1.0))))
experiments.append(Experiment(scan=Scan(image_range=(1, 10), oscillation=(0, 1.0))))
# Default
starting_doses, dpi = dials.pychef.interpret_images_to_doses_options(
experiments, dose_per_image=[1]
)
assert starting_doses == [0, 0, 0]
assert dpi == [1.0, 1.0, 1.0]
# Multi-sweep measurements on same crystal
starting_doses, dpi = dials.pychef.interpret_images_to_doses_options(
experiments, dose_per_image=[1], shared_crystal=True
)
assert starting_doses == [0, 10, 30]
assert dpi == [1.0, 1.0, 1.0]
# Specify starting doses
starting_doses, dpi = dials.pychef.interpret_images_to_doses_options(
experiments, dose_per_image=[1], starting_doses=[0, 20, 0], shared_crystal=False
)
assert starting_doses == [0, 20, 0]
assert dpi == [1.0, 1.0, 1.0]
# Specify doses per image and shared crystal
starting_doses, dpi = dials.pychef.interpret_images_to_doses_options(
experiments, dose_per_image=[1.0, 2.0, 1.0], shared_crystal=True
)
assert starting_doses == [0, 10, 50]
assert dpi == [1.0, 2.0, 1.0]
# Test error is raised if bad input values for starting doses or dose per image.
with pytest.raises(ValueError):
_, __ = dials.pychef.interpret_images_to_doses_options(
experiments, dose_per_image=[1.0], starting_doses=[0, 1]
)
with pytest.raises(ValueError):
_, __ = dials.pychef.interpret_images_to_doses_options(
experiments, dose_per_image=[1.0, 2.0]
)
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