def run(self, args=None):
"""Execute the script."""
# Parse the command line
self.params, options = self.parser.parse_args(args, show_diff_phil=True)
# Configure the logging
dials.util.log.config(verbosity=options.verbose, logfile=self.params.output.log)
if self.params.hklin is None:
self.parser.print_help()
sys.exit()
iobs = self._extract_data_from_mtz()
i_p1 = merge_in_P1(iobs)
f_p1 = truncate(i_p1)[1]
fsq_p1 = f_p1.customized_copy(data=flex.pow2(f_p1.data()))
logger.info("R_friedel(F) = {0:.5f}".format(r_friedel(f_p1)))
logger.info("R_friedel(F^2) = {0:.5f}".format(r_friedel(fsq_p1)))
logger.info("R_friedel(I) = {0:.5f}".format(r_friedel(i_p1)))
return
def merge_data_to_mtz(params, experiments, reflections):
"""Merge data (at each wavelength) and write to an mtz file object."""
wavelengths = match_wavelengths(
experiments,
absolute_tolerance=params.wavelength_tolerance,
) # wavelengths is an ordered dict
mtz_datasets = [
MTZDataClass(wavelength=w, project_name=params.output.project_name)
for w in wavelengths.keys()
]
dataset_names = params.output.dataset_names
crystal_names = params.output.crystal_names
# check if best_unit_cell is set.
best_unit_cell = params.best_unit_cell
if not best_unit_cell:
best_unit_cell = determine_best_unit_cell(experiments)
reflections[0]["d"] = best_unit_cell.d(reflections[0]["miller_index"])
for expt in experiments:
expt.crystal.unit_cell = best_unit_cell
if len(wavelengths) > 1:
logger.info(
"Multiple wavelengths found: \n%s",
"\n".join(
" Wavlength: %.5f, experiment numbers: %s "
% (k, ",".join(map(str, v)))
for k, v in wavelengths.items()
),
)
if not dataset_names or len(dataset_names) != len(wavelengths):
logger.info(
"Unequal number of dataset names and wavelengths, using default naming."
)
dataset_names = [None] * len(wavelengths)
if not crystal_names or len(crystal_names) != len(wavelengths):
logger.info(
"Unequal number of crystal names and wavelengths, using default naming."
)
crystal_names = [None] * len(wavelengths)
experiments_subsets = []
reflections_subsets = []
for dataset, dname, cname in zip(mtz_datasets, dataset_names, crystal_names):
dataset.dataset_name = dname
dataset.crystal_name = cname
for exp_nos in wavelengths.values():
expids = [experiments[i].identifier for i in exp_nos]
experiments_subsets.append(
ExperimentList([experiments[i] for i in exp_nos])
)
reflections_subsets.append(
reflections[0].select_on_experiment_identifiers(expids)
)
else:
mtz_datasets[0].dataset_name = dataset_names[0]
mtz_datasets[0].crystal_name = crystal_names[0]
experiments_subsets = [experiments]
reflections_subsets = reflections
# merge and truncate the data for each wavelength group
for experimentlist, reflection_table, mtz_dataset in zip(
experiments_subsets, reflections_subsets, mtz_datasets
):
# First generate two merge_equivalents objects, collect merging stats
merged, merged_anomalous, stats_summary = merge(
experimentlist,
reflection_table,
d_min=params.d_min,
d_max=params.d_max,
combine_partials=params.combine_partials,
partiality_threshold=params.partiality_threshold,
best_unit_cell=best_unit_cell,
anomalous=params.anomalous,
assess_space_group=params.assess_space_group,
n_bins=params.merging.n_bins,
use_internal_variance=params.merging.use_internal_variance,
)
merged_array = merged.array()
# Save the relevant data in the mtz_dataset dataclass
# This will add the data for IMEAN/SIGIMEAN
mtz_dataset.merged_array = merged_array
if merged_anomalous:
merged_anomalous_array = merged_anomalous.array()
# This will add the data for I(+), I(-), SIGI(+), SIGI(-), N(+), N(-)
mtz_dataset.merged_anomalous_array = merged_anomalous_array
mtz_dataset.multiplicities = merged_anomalous.redundancies()
else:
merged_anomalous_array = None
# This will add the data for N
mtz_dataset.multiplicities = merged.redundancies()
if params.anomalous:
merged_intensities = merged_anomalous_array
else:
merged_intensities = merged_array
anom_amplitudes = None
if params.truncate:
amplitudes, anom_amplitudes, dano = truncate(merged_intensities)
# This will add the data for F, SIGF
mtz_dataset.amplitudes = amplitudes
# This will add the data for F(+), F(-), SIGF(+), SIGF(-)
mtz_dataset.anomalous_amplitudes = anom_amplitudes
# This will add the data for DANO, SIGDANO
mtz_dataset.dano = dano
# print out analysis statistics
show_wilson_scaling_analysis(merged_intensities)
if stats_summary:
logger.info(stats_summary)
if anom_amplitudes:
logger.info(make_dano_table(anom_amplitudes))
# pass the dataclasses to an MTZ writer to generate the mtz file and return.
return make_merged_mtz_file(mtz_datasets)
def merge_data_to_mtz(params, experiments, reflections):
"""Merge data (at each wavelength) and write to an mtz file object."""
wavelengths = match_wavelengths(
experiments) # wavelengths is an ordered dict
mtz_datasets = [
MTZDataClass(wavelength=w, project_name=params.output.project_name)
for w in wavelengths.keys()
]
dataset_names = params.output.dataset_names
crystal_names = params.output.crystal_names
if len(wavelengths) > 1:
logger.info(
"Multiple wavelengths found: \n%s",
"\n".join(" Wavlength: %.5f, experiment numbers: %s " %
(k, ",".join(map(str, v)))
for k, v in wavelengths.items()),
)
if not dataset_names or len(dataset_names) != len(wavelengths):
logger.info(
"Unequal number of dataset names and wavelengths, using default naming."
)
dataset_names = [None] * len(wavelengths)
if not crystal_names or len(crystal_names) != len(wavelengths):
logger.info(
"Unequal number of crystal names and wavelengths, using default naming."
)
crystal_names = [None] * len(wavelengths)
experiments_subsets = []
reflections_subsets = []
for dataset, dname, cname in zip(mtz_datasets, dataset_names,
crystal_names):
dataset.dataset_name = dname
dataset.crystal_name = cname
for exp_nos in wavelengths.values():
expids = [experiments[i].identifier for i in exp_nos]
experiments_subsets.append(
ExperimentList([experiments[i] for i in exp_nos]))
reflections_subsets.append(
reflections[0].select_on_experiment_identifiers(expids))
else:
mtz_datasets[0].dataset_name = dataset_names[0]
mtz_datasets[0].crystal_name = crystal_names[0]
experiments_subsets = [experiments]
reflections_subsets = reflections
for experimentlist, reflection_table, mtz_dataset in zip(
experiments_subsets, reflections_subsets, mtz_datasets):
# merge and truncate the data
merged_array, merged_anomalous_array, stats_summary = merge(
experimentlist,
reflection_table,
d_min=params.d_min,
d_max=params.d_max,
combine_partials=params.combine_partials,
partiality_threshold=params.partiality_threshold,
anomalous=params.anomalous,
assess_space_group=params.assess_space_group,
n_bins=params.merging.n_bins,
use_internal_variance=params.merging.use_internal_variance,
)
mtz_dataset.merged_array = merged_array
mtz_dataset.merged_anomalous_array = merged_anomalous_array
if params.anomalous:
merged_intensities = merged_anomalous_array
else:
merged_intensities = merged_array
if params.truncate:
amplitudes, anomalous_amplitudes = truncate(merged_intensities)
mtz_dataset.amplitudes = amplitudes
mtz_dataset.anomalous_amplitudes = anomalous_amplitudes
show_wilson_scaling_analysis(merged_intensities)
if stats_summary:
logger.info(stats_summary)
return make_merged_mtz_file(mtz_datasets)