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from __future__ import annotations
import json
import os
import shutil
import subprocess
import gemmi
import pytest
import iotbx.cif
from cctbx import sgtbx, uctbx
from dxtbx.model.experiment_list import ExperimentListFactory
from dxtbx.serialize import load
from iotbx import mtz
from dials.array_family import flex
from dials.command_line.slice_sequence import slice_experiments, slice_reflections
from dials.util.multi_dataset_handling import assign_unique_identifiers
def run_export(export_format, dials_data, tmp_path):
result = subprocess.run(
[
shutil.which("dials.export"),
"format=" + export_format,
dials_data("centroid_test_data", pathlib=True) / "experiments.json",
dials_data("centroid_test_data", pathlib=True) / "integrated.pickle",
],
cwd=tmp_path,
capture_output=True,
)
assert not result.returncode and not result.stderr
assert (tmp_path / f"integrated.{export_format}").is_file()
def test_nxs(dials_data, tmp_path):
run_export("nxs", dials_data, tmp_path)
def test_mtz(dials_data, tmp_path):
result = subprocess.run(
[
shutil.which("dials.export"),
"format=mtz",
"project_name=ham",
"crystal_name=spam",
dials_data("centroid_test_data", pathlib=True) / "experiments.json",
dials_data("centroid_test_data", pathlib=True) / "integrated.pickle",
],
cwd=tmp_path,
capture_output=True,
)
assert not result.returncode and not result.stderr
assert (tmp_path / "integrated.mtz").is_file()
mtz_obj = mtz.object(str(tmp_path / "integrated.mtz"))
assert mtz_obj.crystals()[1].name() == "spam"
assert mtz_obj.crystals()[1].project_name() == "ham"
def test_mtz_recalculated_cell(dials_data, tmp_path):
# First run dials.two_theta_refine to ensure that the crystals have
# recalculated_unit_cell set
scaled_expt = (
dials_data("x4wide_processed", pathlib=True) / "AUTOMATIC_DEFAULT_scaled.expt"
)
scaled_refl = (
dials_data("x4wide_processed", pathlib=True) / "AUTOMATIC_DEFAULT_scaled.refl"
)
result = subprocess.run(
[shutil.which("dials.two_theta_refine"), scaled_expt, scaled_refl],
cwd=tmp_path,
capture_output=True,
)
assert (tmp_path / "refined_cell.expt").is_file()
refined_expt = load.experiment_list(
tmp_path / "refined_cell.expt", check_format=False
)
ttr_cell = refined_expt.crystals()[0].get_recalculated_unit_cell()
d_min = 1.3
result = subprocess.run(
[
shutil.which("dials.export"),
"format=mtz",
tmp_path / "refined_cell.expt",
scaled_refl,
f"d_min={d_min:f}",
],
cwd=tmp_path,
capture_output=True,
)
assert not result.returncode and not result.stderr
assert (tmp_path / "scaled.mtz").is_file()
# The resulting mtz should have the same unit cell set as the recalculated_unit_cell
# from dials.two_theta_refine
for ma in mtz.object(str(tmp_path / "scaled.mtz")).as_miller_arrays():
assert ttr_cell.parameters() == pytest.approx(ma.unit_cell().parameters())
assert ma.d_min() >= d_min
def test_mtz_best_unit_cell(dials_data, tmp_path):
scaled_expt = (
dials_data("x4wide_processed", pathlib=True) / "AUTOMATIC_DEFAULT_scaled.expt"
)
scaled_refl = (
dials_data("x4wide_processed", pathlib=True) / "AUTOMATIC_DEFAULT_scaled.refl"
)
best_unit_cell = uctbx.unit_cell((42, 42, 39, 90, 90, 90))
d_min = 1.5
result = subprocess.run(
[
shutil.which("dials.export"),
"format=mtz",
scaled_expt,
scaled_refl,
f"d_min={d_min:f}",
"best_unit_cell={:g},{:g},{:g},{:g},{:g},{:g}".format(
*best_unit_cell.parameters()
),
],
cwd=tmp_path,
capture_output=True,
)
assert not result.returncode and not result.stderr
assert (tmp_path / "scaled.mtz").is_file()
# The resulting mtz should have the best_unit_cell as input to dials.export
for ma in mtz.object(str(tmp_path / "scaled.mtz")).as_miller_arrays():
assert best_unit_cell.parameters() == pytest.approx(ma.unit_cell().parameters())
assert ma.d_min() >= d_min
def test_multi_sequence_integrated_mtz(dials_data, tmp_path):
"""Test dials.export on multi-sequence integrated data."""
# first combine two integrated files
data = dials_data("multi_crystal_proteinase_k", pathlib=True)
result = subprocess.run(
[
shutil.which("dials.combine_experiments"),
data / "experiments_1.json",
data / "reflections_1.pickle",
data / "experiments_2.json",
data / "reflections_2.pickle",
],
cwd=tmp_path,
capture_output=True,
)
assert not result.returncode and not result.stderr
assert (tmp_path / "combined.refl").is_file()
assert (tmp_path / "combined.expt").is_file()
# now export
result = subprocess.run(
[
shutil.which("dials.export"),
"format=mtz",
"mtz.hklout=integrated.mtz",
tmp_path / "combined.refl",
tmp_path / "combined.expt",
],
cwd=tmp_path,
capture_output=True,
)
assert not result.returncode and not result.stderr
assert (tmp_path / "integrated.mtz").is_file()
def test_mtz_multi_wavelength(dials_data, tmp_path):
"""Test multi-wavelength mtz export"""
# First make suitable input - multi datasets experiment list and reflection
# table with different wavelengths
mcp = dials_data("multi_crystal_proteinase_k", pathlib=True)
exp_1 = load.experiment_list(mcp / "experiments_1.json", check_format=False)
exp_2 = load.experiment_list(mcp / "experiments_2.json", check_format=False)
refl_1 = flex.reflection_table.from_file(mcp / "reflections_1.pickle")
refl_2 = flex.reflection_table.from_file(mcp / "reflections_2.pickle")
exp_1[0].beam.set_wavelength(0.5)
exp_2[0].beam.set_wavelength(1.0)
exp_1.extend(exp_2)
reflection_list = [refl_1, refl_2]
exps, refls = assign_unique_identifiers(exp_1, reflection_list)
joint_refl = flex.reflection_table()
for r in refls:
joint_refl.extend(r)
exps.as_json(tmp_path / "tmp_exp.expt")
joint_refl.as_file(tmp_path / "tmp_refl.refl")
# Now run
result = subprocess.run(
[
shutil.which("dials.export"),
tmp_path / "tmp_exp.expt",
tmp_path / "tmp_refl.refl",
"format=mtz",
"mtz.hklout=unmerged.mtz",
],
env={"DIALS_EXPORT_DO_NOT_CHECK_FORMAT": "True", **os.environ},
cwd=tmp_path,
capture_output=True,
)
assert not result.returncode and not result.stderr
assert (tmp_path / "unmerged.mtz").is_file()
# Inspect output
m = mtz.object(str(tmp_path / "unmerged.mtz")).crystals()
n_batches = []
wavelengths = []
for crystal in m:
for dataset in crystal.datasets():
wavelengths.append(dataset.wavelength())
n_batches.append(dataset.n_batches())
assert n_batches == [0, 25, 25] # base, dataset1, dataset2
assert wavelengths == [0, 0.5, 1.0] # base, dataset1, dataset2
def test_mtz_primitive_cell(dials_data, tmp_path):
scaled_expt = dials_data("insulin_processed", pathlib=True) / "scaled.expt"
scaled_refl = dials_data("insulin_processed", pathlib=True) / "scaled.refl"
# Export in I23
subprocess.run(
[
shutil.which("dials.export"),
scaled_expt,
scaled_refl,
"mtz.hklout=reference.mtz",
],
cwd=tmp_path,
capture_output=True,
).check_returncode()
# Now reindex to the primitive setting
expts = load.experiment_list(scaled_expt, check_format=False)
cs = expts[0].crystal.get_crystal_symmetry()
cb_op = cs.change_of_basis_op_to_primitive_setting()
subprocess.run(
[
shutil.which("dials.reindex"),
scaled_expt,
scaled_refl,
f'change_of_basis_op="{cb_op}"',
],
cwd=tmp_path,
).check_returncode()
# Export the reindexed experiments/reflections - internally this will
# reindex back to I23
subprocess.run(
[
shutil.which("dials.export"),
tmp_path / "reindexed.expt",
tmp_path / "reindexed.refl",
"mtz.hklout=from_reindexed.mtz",
],
cwd=tmp_path,
capture_output=True,
).check_returncode()
# Now read both files and check that relevant data are identical
mtz1 = gemmi.read_mtz_file(str(tmp_path / "reference.mtz"))
mtz2 = gemmi.read_mtz_file(str(tmp_path / "from_reindexed.mtz"))
assert mtz1.spacegroup == mtz2.spacegroup
assert mtz1.cell == mtz2.cell
assert (mtz1.array == mtz2.array).all()
for b1, b2 in zip(mtz1.batches, mtz2.batches):
assert list(b1.ints) == list(b2.ints)
assert list(b1.floats) == list(b2.floats)
@pytest.mark.parametrize("compress", [None, "gz", "bz2", "xz"])
@pytest.mark.parametrize("hklout", [None, "my.cif"])
def test_mmcif(compress, hklout, dials_data, tmp_path):
# Call dials.export after integration
command = [
shutil.which("dials.export"),
"format=mmcif",
dials_data("centroid_test_data", pathlib=True) / "experiments.json",
dials_data("centroid_test_data", pathlib=True) / "integrated.pickle",
]
if hklout is not None:
command.append(f"mmcif.hklout={hklout}")
else:
hklout = "integrated.cif"
if compress is not None:
command.append(f"mmcif.compress={compress}")
hklin = hklout + "." + compress
else:
hklin = hklout
result = subprocess.run(command, cwd=tmp_path, capture_output=True)
assert not result.returncode and not result.stderr
assert (tmp_path / hklin).is_file()
@pytest.mark.skipif(
shutil.which("gemmi") is None, reason="Could not find gemmi executable"
)
@pytest.mark.parametrize("pdb_version", ["v5", "v5_next"])
def test_mmcif_on_scaled_data(dials_data, tmp_path, pdb_version):
"""Call dials.export format=mmcif after scaling"""
scaled_expt = (
dials_data("x4wide_processed", pathlib=True) / "AUTOMATIC_DEFAULT_scaled.expt"
)
scaled_refl = (
dials_data("x4wide_processed", pathlib=True) / "AUTOMATIC_DEFAULT_scaled.refl"
)
command = [
shutil.which("dials.export"),
"format=mmcif",
scaled_expt,
scaled_refl,
"mmcif.hklout=scaled.mmcif",
"compress=None",
f"pdb_version={pdb_version}",
]
result = subprocess.run(command, cwd=tmp_path, capture_output=True)
assert not result.returncode and not result.stderr
assert (tmp_path / "scaled.mmcif").is_file()
model = iotbx.cif.reader(file_path=str(tmp_path / "scaled.mmcif")).model()
if pdb_version == "v5":
assert "_pdbx_diffrn_data_section.id" not in model["dials"].keys()
# check that gemmi can understand the output
cmd = [
shutil.which("gemmi"),
"cif2mtz",
tmp_path / "scaled.mmcif",
tmp_path / "test.mtz",
]
result = subprocess.run(cmd, cwd=tmp_path, capture_output=True)
assert not result.returncode and not result.stderr
assert (tmp_path / "test.mtz").is_file()
elif pdb_version == "v5_next":
assert "_pdbx_diffrn_data_section.id" in model["dials"].keys()
def test_mmcif_p1_narrow_wedge(dials_data, tmp_path):
"""Call dials.export format=mmcif after scaling"""
data_dir = dials_data("x4wide_processed", pathlib=True)
refl = flex.reflection_table.from_file(data_dir / "AUTOMATIC_DEFAULT_scaled.refl")
refl = slice_reflections(refl, [(1, 3)])
refl.as_file(tmp_path / "p1_narrow.refl")
expts = load.experiment_list(
data_dir / "AUTOMATIC_DEFAULT_scaled.expt", check_format=False
)
expts = slice_experiments(expts, [(1, 3)])
expts[0].crystal.set_space_group(sgtbx.space_group())
expts.as_file(tmp_path / "p1_narrow.expt")
command = [
shutil.which("dials.export"),
"format=mmcif",
tmp_path / "p1_narrow.expt",
tmp_path / "p1_narrow.refl",
"mmcif.hklout=scaled.mmcif",
"compress=None",
]
result = subprocess.run(command, cwd=tmp_path, capture_output=True)
assert not result.returncode and not result.stderr
assert (tmp_path / "scaled.mmcif").is_file()
model = iotbx.cif.reader(file_path=str(tmp_path / "scaled.mmcif")).model()
assert model["dials"]["_reflns.pdbx_redundancy"] == "1.0"
assert model["dials"]["_reflns.pdbx_CC_half"] == "0.0"
def test_xds_ascii(dials_data, tmp_path):
# Call dials.export
result = subprocess.run(
[
shutil.which("dials.export"),
"intensity=sum",
"format=xds_ascii",
dials_data("centroid_test_data", pathlib=True) / "experiments.json",
dials_data("centroid_test_data", pathlib=True) / "integrated.pickle",
],
cwd=tmp_path,
capture_output=True,
)
assert not result.returncode and not result.stderr
assert (tmp_path / "DIALS.HKL").is_file()
psi_values = {
(-9, 7, -10): 153.430361,
(-5, 11, -26): 175.559441,
(-4, 23, 24): 129.468070,
(2, 10, 20): 147.947274,
}
with (tmp_path / "DIALS.HKL").open() as fh:
for record in fh:
if record.startswith("!"):
continue
tokens = record.split()
hkl = tuple(map(int, tokens[:3]))
if hkl not in psi_values:
continue
psi = float(tokens[-1])
assert psi == pytest.approx(psi_values[hkl], abs=0.1)
def test_sadabs(dials_data, tmp_path):
# Call dials.export
result = subprocess.run(
[
shutil.which("dials.export"),
"intensity=sum",
"mtz.partiality_threshold=0.99",
"format=sadabs",
dials_data("centroid_test_data", pathlib=True) / "experiments.json",
dials_data("centroid_test_data", pathlib=True) / "integrated.pickle",
],
cwd=tmp_path,
capture_output=True,
)
assert not result.returncode and not result.stderr
assert (tmp_path / "integrated.sad").is_file()
direction_cosines = {
(-9, 7, -10): (0.51253, -0.72107, 0.84696, -0.68476, -0.14130, -0.10561),
(-5, 11, -26): (0.51310, -0.62895, 0.84711, -0.59223, -0.13830, -0.50366),
(-4, 23, 24): (0.51308, -0.60578, 0.84711, -0.31416, -0.13840, 0.73099),
(2, 10, 20): (0.51239, -0.46605, 0.84693, -0.61521, -0.14204, 0.63586),
}
with (tmp_path / "integrated.sad").open() as fh:
for record in fh:
record = record.replace("-", " -")
tokens = record.split()
hkl = tuple(map(int, tokens[:3]))
cosines = tuple(map(float, tokens[6:12]))
if hkl not in direction_cosines:
continue
assert cosines == pytest.approx(direction_cosines[hkl], abs=0.001)
def test_json(dials_data, tmp_path):
# Call dials.export
result = subprocess.run(
[
shutil.which("dials.export"),
"format=json",
dials_data("centroid_test_data", pathlib=True)
/ "imported_experiments.json",
dials_data("centroid_test_data", pathlib=True) / "strong.pickle",
],
cwd=tmp_path,
capture_output=True,
)
assert not result.returncode and not result.stderr
assert (tmp_path / "rlp.json").is_file()
with open(tmp_path / "rlp.json", mode="rb") as fh:
d = json.load(fh)
assert set(d) == {"imageset_id", "experiments", "rlp", "experiment_id"}
assert d["rlp"][:3] == [0.123413, 0.576679, 0.186326], d["rlp"][:3]
assert d["imageset_id"][0] == 0
assert d["experiment_id"][0] == 0
experiments = ExperimentListFactory.from_dict(d["experiments"])
imgset = experiments.imagesets()
assert len(imgset) == 1
def test_json_shortened(dials_data, tmp_path):
# Call dials.export
result = subprocess.run(
[
shutil.which("dials.export"),
"format=json",
dials_data("centroid_test_data", pathlib=True) / "experiments.json",
dials_data("centroid_test_data", pathlib=True) / "integrated.pickle",
"json.filename=integrated.json",
"n_digits=4",
"compact=False",
],
cwd=tmp_path,
capture_output=True,
)
assert not result.returncode and not result.stderr
assert (tmp_path / "integrated.json").is_file()
with open(tmp_path / "integrated.json", mode="rb") as fh:
d = json.load(fh)
assert "imageset_id" in d
assert "rlp" in d
assert "experiment_id" in d
assert d["rlp"][:3] == [-0.5975, -0.6141, 0.4702], d["rlp"][:3]
assert d["imageset_id"][0] == 0
assert d["experiment_id"][0] == 0
def test_shelx(dials_data, tmp_path):
# Call dials.export
result = subprocess.run(
[
shutil.which("dials.export"),
"intensity=scale",
"format=shelx",
dials_data("l_cysteine_4_sweeps_scaled", pathlib=True)
/ "scaled_20_25.expt",
dials_data("l_cysteine_4_sweeps_scaled", pathlib=True)
/ "scaled_20_25.refl",
],
cwd=tmp_path,
capture_output=True,
)
assert not result.returncode and not result.stderr
assert (tmp_path / "dials.hkl").is_file()
intensities_sigmas = {
(4, 2, 4): (173.14, 15.39),
(3, -3, -3): (324.13, 25.92),
(4, 0, 2): (876.02, 69.34),
(3, -2, -1): (463.11, 36.76),
}
with (tmp_path / "dials.hkl").open() as fh:
max_intensity = -9999.0
for record in fh:
tokens = record.split()
hkl = tuple(map(int, tokens[:3]))
i_sigi = tuple(map(float, tokens[3:5]))
if hkl not in intensities_sigmas:
if i_sigi[0] > max_intensity:
max_intensity = i_sigi[0]
continue
assert i_sigi == pytest.approx(intensities_sigmas[hkl], abs=0.001)
assert max_intensity == pytest.approx(9999.00, abs=0.001)
def test_shelx_ins(dials_data, tmp_path):
# Call dials.export
result = subprocess.run(
[
shutil.which("dials.export"),
"intensity=scale",
"format=shelx",
dials_data("l_cysteine_4_sweeps_scaled", pathlib=True)
/ "scaled_20_25.expt",
dials_data("l_cysteine_4_sweeps_scaled", pathlib=True)
/ "scaled_20_25.refl",
],
cwd=tmp_path,
capture_output=True,
)
assert not result.returncode and not result.stderr
assert (tmp_path / "dials.ins").is_file()
cell_esds = {
"CELL": (5.48154, 8.21578, 12.14570, 90.0000, 90.0000, 90.0000),
"ZERR": (0.00050, 0.00073, 0.00109, 0.0034, 0.0037, 0.0037),
}
with (tmp_path / "dials.ins").open() as fh:
for line in fh:
tokens = line.split()
instruction = tokens[0]
if instruction in cell_esds:
result = tuple(map(float, tokens[2:8]))
assert result == pytest.approx(cell_esds[instruction], abs=0.0001)
def test_shelx_ins_best_unit_cell(dials_data, tmp_path):
# Call dials.export
result = subprocess.run(
[
shutil.which("dials.export"),
"intensity=scale",
"format=shelx",
"best_unit_cell=5,8,12,90,90,90",
dials_data("l_cysteine_4_sweeps_scaled", pathlib=True)
/ "scaled_20_25.expt",
dials_data("l_cysteine_4_sweeps_scaled", pathlib=True)
/ "scaled_20_25.refl",
],
cwd=tmp_path,
capture_output=True,
)
assert not result.returncode and not result.stderr
assert (tmp_path / "dials.ins").is_file()
cell_esds = {
"CELL": (5.0, 8.0, 12.0, 90.0, 90.0, 90.0),
}
with (tmp_path / "dials.ins").open() as fh:
for line in fh:
tokens = line.split()
instruction = tokens[0]
assert instruction != "ZERR"
if instruction in cell_esds:
result = tuple(map(float, tokens[2:8]))
assert result == pytest.approx(cell_esds[instruction], abs=0.001)
def test_shelx_ins_composition(dials_data, tmp_path):
# Call dials.export
result = subprocess.run(
[
shutil.which("dials.export"),
"intensity=scale",
"format=shelx",
"composition=C3H7NO2S",
dials_data("l_cysteine_4_sweeps_scaled", pathlib=True)
/ "scaled_20_25.expt",
dials_data("l_cysteine_4_sweeps_scaled", pathlib=True)
/ "scaled_20_25.refl",
],
cwd=tmp_path,
capture_output=True,
)
assert not result.returncode and not result.stderr
assert (tmp_path / "dials.ins").is_file()
sfac_unit = {
"SFAC": "C H N O S",
"UNIT": "12 28 4 8 4",
}
with (tmp_path / "dials.ins").open() as fh:
for line in fh:
tokens = line.split()
instruction = tokens[0]
if instruction in sfac_unit:
result = " ".join(tokens[1:6])
assert result == sfac_unit[instruction]
def test_export_sum_or_profile_only(dials_data, tmp_path):
expt = dials_data("insulin_processed", pathlib=True) / "integrated.expt"
refl = dials_data("insulin_processed", pathlib=True) / "integrated.refl"
for remove in "prf", "sum":
removed = tmp_path / f"removed_{remove}.refl"
data = flex.reflection_table.from_file(refl)
del data[f"intensity.{remove}.value"]
del data[f"intensity.{remove}.variance"]
data.as_file(removed)
result = subprocess.run(
[
shutil.which("dials.export"),
expt,
removed,
f"mtz.hklout=removed_{remove}.mtz",
],
cwd=tmp_path,
capture_output=True,
)
assert not result.returncode and not result.stderr
assert (tmp_path / f"removed_{remove}.mtz").is_file()
@pytest.mark.parametrize("intensity_choice", ["profile", "sum"])
def test_pets(dials_data, tmp_path, intensity_choice):
expt = dials_data("quartz_processed", pathlib=True) / "integrated.expt"
refl = dials_data("quartz_processed", pathlib=True) / "integrated.refl"
# Call dials.export
result = subprocess.run(
[
shutil.which("dials.export"),
"intensity=scale",
"format=pets",
"id=0",
"step=1",
"n_merged=2",
"intensity=" + intensity_choice,
"filename_prefix=" + intensity_choice,
expt,
refl,
],
cwd=tmp_path,
capture_output=True,
)
assert not result.returncode and not result.stderr
output = tmp_path / (intensity_choice + ".cif_pets")
# On windows, \r\n endings are written; but our reference is \n
output_data = output.read_bytes().replace(b"\r\n", b"\n")
if intensity_choice == "profile":
reference = dials_data("quartz_processed", pathlib=True) / "dials_prf.cif_pets"
else:
reference = dials_data("quartz_processed", pathlib=True) / "dials_dyn.cif_pets"
assert output_data == reference.read_bytes()
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