def _unit_cell_clustering(self, experiments):
crystal_symmetries = [
expt.crystal.get_crystal_symmetry() for expt in experiments
]
lattice_ids = experiments.identifiers()
from dials.algorithms.clustering.unit_cell import UnitCellCluster
from xfel.clustering.cluster_groups import unit_cell_info
ucs = UnitCellCluster.from_crystal_symmetries(crystal_symmetries,
lattice_ids=lattice_ids)
self.unit_cell_clusters, self.unit_cell_dendrogram, _ = ucs.ab_cluster(
self.params.unit_cell_clustering.threshold,
log=self.params.unit_cell_clustering.log,
labels="lattice_id",
write_file_lists=False,
schnell=False,
doplot=False,
)
logger.info(unit_cell_info(self.unit_cell_clusters))
largest_cluster_lattice_ids = None
for cluster in self.unit_cell_clusters:
cluster_lattice_ids = [m.lattice_id for m in cluster.members]
if largest_cluster_lattice_ids is None:
largest_cluster_lattice_ids = cluster_lattice_ids
elif len(cluster_lattice_ids) > len(largest_cluster_lattice_ids):
largest_cluster_lattice_ids = cluster_lattice_ids
dataset_selection = largest_cluster_lattice_ids
return dataset_selection
def unit_cell_clustering(experiments, threshold, log=True, plot_name=None):
from dials.algorithms.clustering.unit_cell import UnitCellCluster
crystal_symmetries = []
for expt in experiments:
crystal_symmetry = expt.crystal.get_crystal_symmetry(
assert_is_compatible_unit_cell=False)
crystal_symmetries.append(crystal_symmetry.niggli_cell())
lattice_ids = [expt.identifier for expt in experiments]
ucs = UnitCellCluster.from_crystal_symmetries(crystal_symmetries,
lattice_ids=lattice_ids)
if plot_name is not None:
import matplotlib
matplotlib.use("Agg")
from matplotlib import pyplot as plt
plt.figure("Andrews-Bernstein distance dendogram", figsize=(12, 8))
ax = plt.gca()
else:
ax = None
clusters, dendrogram, _ = ucs.ab_cluster(
threshold,
log=log,
labels="lattice_id",
write_file_lists=False,
schnell=False,
doplot=(plot_name is not None),
ax=ax,
)
if plot_name is not None:
plt.tight_layout()
plt.savefig(plot_name)
plt.clf()
return clusters, dendrogram
def _unit_cell_clustering(self, experiments):
crystal_symmetries = [
expt.crystal.get_crystal_symmetry() for expt in experiments
]
# lattice ids used to label plots, so want numerical ids
lattice_ids = [
self.identifiers_to_ids_map[i] for i in experiments.identifiers()
]
ucs = UnitCellCluster.from_crystal_symmetries(crystal_symmetries,
lattice_ids=lattice_ids)
self.unit_cell_clusters, self.unit_cell_dendrogram, _ = ucs.ab_cluster(
self.params.unit_cell_clustering.threshold,
log=self.params.unit_cell_clustering.log,
labels="lattice_id",
write_file_lists=False,
schnell=False,
doplot=False,
)
logger.info(unit_cell_info(self.unit_cell_clusters))
largest_cluster_lattice_ids = None
for cluster in self.unit_cell_clusters:
cluster_lattice_ids = [m.lattice_id for m in cluster.members]
if largest_cluster_lattice_ids is None:
largest_cluster_lattice_ids = cluster_lattice_ids
elif len(cluster_lattice_ids) > len(largest_cluster_lattice_ids):
largest_cluster_lattice_ids = cluster_lattice_ids
dataset_selection = largest_cluster_lattice_ids
# now convert to actual identifiers for selection
return [self.ids_to_identifiers_map[i] for i in dataset_selection]
def test_unit_cell():
# generate some random unit cells
sgi = sgtbx.space_group_info("P1")
crystal_symmetries = [
sgi.any_compatible_crystal_symmetry(volume=random.uniform(990, 1010))
for i in range(10)
]
lattice_ids = flex.int_range(0, len(crystal_symmetries)).as_string()
ucs = UnitCellCluster.from_crystal_symmetries(crystal_symmetries,
lattice_ids=lattice_ids)
clusters, dendrogram, _ = ucs.ab_cluster(write_file_lists=False,
doplot=False)
def test_scipy_dendrogram_to_plotly_json():
# generate some random unit cells
sgi = sgtbx.space_group_info("P1")
crystal_symmetries = [
sgi.any_compatible_crystal_symmetry(volume=random.uniform(990, 1010))
for i in range(10)
]
lattice_ids = flex.int_range(0, len(crystal_symmetries)).as_string()
ucs = UnitCellCluster.from_crystal_symmetries(crystal_symmetries,
lattice_ids=lattice_ids)
_, dendrogram, _ = ucs.ab_cluster(write_file_lists=False, doplot=False)
d = plots.scipy_dendrogram_to_plotly_json(dendrogram,
title="Unit cell clustering")
assert set(d) == {"layout", "data"}
def test_UnitCellAnalysisObserver():
# generate some random unit cells
sgi = sgtbx.space_group_info("P1")
unit_cells = [
sgi.any_compatible_unit_cell(volume=random.uniform(990, 1010))
for i in range(10)
]
# generate experiment list
experiments = ExperimentList()
U = matrix.identity(3)
for uc in unit_cells:
B = matrix.sqr(uc.fractionalization_matrix()).transpose()
direct_matrix = (U * B).inverse()
experiments.append(
Experiment(crystal=Crystal(
direct_matrix[:3],
direct_matrix[3:6],
direct_matrix[6:9],
space_group=sgi.group(),
)))
# generate dendrogram
crystal_symmetries = [
expt.crystal.get_crystal_symmetry() for expt in experiments
]
lattice_ids = experiments.identifiers()
ucs = UnitCellCluster.from_crystal_symmetries(crystal_symmetries,
lattice_ids=lattice_ids)
_, dendrogram, _ = ucs.ab_cluster(write_file_lists=False, doplot=False)
# setup script
script = mock.Mock()
script._experiments = experiments
script.unit_cell_dendrogram = dendrogram
# test the observer
observer = observers.UnitCellAnalysisObserver()
observer.update(script)
assert set(observer.data) == {"experiments", "dendrogram"}
d = observer.make_plots()
assert "unit_cell_graphs" in d