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from __future__ import annotations
import json
import shutil
import subprocess
import pytest
@pytest.mark.parametrize("grouping", ["combined", "individual", "grouped"])
def test_standalone_error_model_refinement_on_scaled_data(
dials_data, tmp_path, grouping
):
location = dials_data("l_cysteine_4_sweeps_scaled", pathlib=True)
refls = location / "scaled_20_25.refl"
expts = location / "scaled_20_25.expt"
# Use a range of options, some default.
command = [
shutil.which("dials.refine_error_model"),
refls,
expts,
"json=error_model.json",
"html=error_model.html",
"intensity_choice=combine",
"combine.Imid=250",
"basic.minimisation=individual",
f"grouping={grouping}",
]
if grouping == "grouped":
command.append("error_model_group='0'")
command.append("error_model_group='1'")
result = subprocess.run(command, cwd=tmp_path, capture_output=True)
assert not result.returncode and not result.stderr
assert tmp_path.joinpath("error_model.html").is_file()
assert tmp_path.joinpath("error_model.json").is_file()
with open(tmp_path.joinpath("error_model.json")) as f:
d = json.load(f)
n_models = sum(
"normal_distribution_plot" in k for k in d["error_model_plots"].keys()
)
if grouping == "combined":
assert n_models == 1
else:
assert n_models == 2
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