def test_resolution_cc_half(merging_stats):
result = resolution_analysis.resolution_cc_half(merging_stats, limit=0.82)
assert result.d_min == pytest.approx(1.242, abs=1e-3)
result = resolution_analysis.resolution_cc_half(
merging_stats,
limit=0.82,
cc_half_method="sigma_tau",
model=resolution_analysis.polynomial_fit,
)
assert result.d_min == pytest.approx(1.233, abs=1e-3)
assert flex.max(flex.abs(result.y_obs - result.y_fit)) < 0.04
assert result.critical_values is not None
assert len(result.critical_values) == len(result.d_star_sq)
def test_plot_result(merging_stats):
result = resolution_analysis.resolution_cc_half(merging_stats, limit=0.82)
d = resolution_analysis.plot_result("cc_half", result)
assert "data" in d
assert "layout" in d
result = resolution_analysis.resolution_fit_from_merging_stats(
merging_stats,
"unmerged_i_over_sigma_mean",
resolution_analysis.log_fit,
limit=0.82,
)
d = resolution_analysis.plot_result("isigma", result)
assert "data" in d
assert "layout" in d
def print_scaling_summary(script):
"""Log summary information after scaling."""
logger.info(print_scaling_model_error_summary(script.experiments))
valid_ranges = get_valid_image_ranges(script.experiments)
image_ranges = get_image_ranges(script.experiments)
msg = []
for (img, valid, refl) in zip(image_ranges, valid_ranges,
script.reflections):
if valid:
if len(valid
) > 1 or valid[0][0] != img[0] or valid[-1][1] != img[1]:
msg.append(
"Excluded images for experiment id: %s, image range: %s, limited range: %s"
% (
refl.experiment_identifiers().keys()[0],
list(img),
list(valid),
))
if msg:
msg = ["Summary of image ranges removed:"] + msg
logger.info("\n".join(msg))
# report on partiality of dataset
partials = flex.double()
for r in script.reflections:
if "partiality" in r:
partials.extend(r["partiality"])
not_full_sel = partials < 0.99
not_zero_sel = partials > 0.01
gt_half = partials > 0.5
lt_half = partials < 0.5
partial_gt_half_sel = not_full_sel & gt_half
partial_lt_half_sel = not_zero_sel & lt_half
logger.info("Summary of dataset partialities")
header = ["Partiality (p)", "n_refl"]
rows = [
["all reflections", str(partials.size())],
["p > 0.99", str(not_full_sel.count(False))],
["0.5 < p < 0.99",
str(partial_gt_half_sel.count(True))],
["0.01 < p < 0.5",
str(partial_lt_half_sel.count(True))],
["p < 0.01", str(not_zero_sel.count(False))],
]
logger.info(tabulate(rows, header))
logger.info(
"""
Reflections below a partiality_cutoff of %s are not considered for any
part of the scaling analysis or for the reporting of merging statistics.
Additionally, if applicable, only reflections with a min_partiality > %s
were considered for use when refining the scaling model.
""",
script.params.cut_data.partiality_cutoff,
script.params.reflection_selection.min_partiality,
)
stats = script.merging_statistics_result
if stats:
anom_stats, cut_stats, cut_anom_stats = (None, None, None)
if not script.scaled_miller_array.space_group().is_centric():
anom_stats = script.anom_merging_statistics_result
logger.info(make_merging_statistics_summary(stats))
try:
d_min = resolution_cc_half(stats, limit=0.3).d_min
except RuntimeError as e:
logger.debug(f"Resolution fit failed: {e}")
else:
max_current_res = stats.bins[-1].d_min
if d_min and d_min - max_current_res > 0.005:
logger.info(
"Resolution limit suggested from CC" + "\u00BD" +
" fit (limit CC" + "\u00BD" + "=0.3): %.2f",
d_min,
)
try:
cut_stats, cut_anom_stats = merging_stats_from_scaled_array(
script.scaled_miller_array.resolution_filter(
d_min=d_min),
script.params.output.merging.nbins,
script.params.output.use_internal_variance,
)
except DialsMergingStatisticsError:
pass
else:
if script.scaled_miller_array.space_group().is_centric():
cut_anom_stats = None
logger.info(
table_1_summary(stats, anom_stats, cut_stats, cut_anom_stats))