def exercise_split_unmerged():
import random
random.seed(42)
flex.set_random_seed(42)
from cctbx import crystal
base_set = miller.build_set(
crystal_symmetry=crystal.symmetry(
unit_cell=(10,10,10,90,90,90), space_group_symbol="P1"),
d_min=1.6,
anomalous_flag=False)
indices = base_set.indices()
assert (len(indices) == 510)
unmerged_hkl = flex.miller_index()
unmerged_data = flex.double()
unmerged_sigmas = flex.double()
redundancies = flex.size_t()
# XXX grossly overengineered, but I wanted to get a realistic CC to make sure
# the reflections are being split properly
for i, hkl in enumerate(indices):
n_obs = min(8, 1 + i % 12)
redundancies.append(n_obs)
intensity_merged = (510 - i) + (510 % 27)
for j in range(n_obs):
unmerged_hkl.append(hkl)
intensity = intensity_merged + 20 * (510 % (7 * (j+1)))
sigma = max(0.5, i % 10)
unmerged_data.append(intensity)
unmerged_sigmas.append(sigma)
assert (unmerged_hkl.size() == 2877)
unmerged_array = miller.set(
crystal_symmetry=base_set,
indices=unmerged_hkl,
anomalous_flag=False).array(data=unmerged_data, sigmas=unmerged_sigmas)
split = miller.split_unmerged(
unmerged_indices=unmerged_hkl,
unmerged_data=unmerged_data,
unmerged_sigmas=unmerged_sigmas)
assert (split.data_1.size() == split.data_2.size() == 467)
cc = miller.compute_cc_one_half(unmerged_array)
assert approx_equal(cc, 0.861, eps=0.001)
unmerged_array.setup_binner(n_bins=10)
unmerged_array.set_observation_type_xray_intensity()
result = unmerged_array.cc_one_half(use_binning=True)
assert approx_equal(
result.data[1:-1],
[0.549, 0.789, 0.843, 0.835, 0.863, 0.860, 0.893, 0.847, 0.875, 0.859],
eps=0.05)
def exercise_split_unmerged () :
import random
random.seed(42)
flex.set_random_seed(42)
from cctbx import crystal
base_set = miller.build_set(
crystal_symmetry=crystal.symmetry(
unit_cell=(10,10,10,90,90,90), space_group_symbol="P1"),
d_min=1.6,
anomalous_flag=False)
indices = base_set.indices()
assert (len(indices) == 510)
unmerged_hkl = flex.miller_index()
unmerged_data = flex.double()
unmerged_sigmas = flex.double()
redundancies = flex.size_t()
# XXX grossly overengineered, but I wanted to get a realistic CC to make sure
# the reflections are being split properly
for i, hkl in enumerate(indices) :
n_obs = min(8, 1 + i % 12)
redundancies.append(n_obs)
intensity_merged = (510 - i) + (510 % 27)
for j in range(n_obs) :
unmerged_hkl.append(hkl)
intensity = intensity_merged + 20 * (510 % (7 * (j+1)))
sigma = max(0.5, i % 10)
unmerged_data.append(intensity)
unmerged_sigmas.append(sigma)
assert (unmerged_hkl.size() == 2877)
unmerged_array = miller.set(
crystal_symmetry=base_set,
indices=unmerged_hkl,
anomalous_flag=False).array(data=unmerged_data, sigmas=unmerged_sigmas)
split = miller.split_unmerged(
unmerged_indices=unmerged_hkl,
unmerged_data=unmerged_data,
unmerged_sigmas=unmerged_sigmas)
assert (split.data_1.size() == split.data_2.size() == 467)
cc = miller.compute_cc_one_half(unmerged_array)
assert approx_equal(cc, 0.861, eps=0.001)
unmerged_array.setup_binner(n_bins=10)
unmerged_array.set_observation_type_xray_intensity()
result = unmerged_array.cc_one_half(use_binning=True)
assert approx_equal(
result.data[1:-1],
[0.549, 0.789, 0.843, 0.835, 0.863, 0.860, 0.893, 0.847, 0.875, 0.859],
eps=0.05)
def fast_merging_stats(array):
"""
Quickly calculate required merging stats for intensity combination.
This is a cut-down version of iobtx.merging_statistics.merging_stats.
"""
assert array.sigmas() is not None
positive_sel = array.sigmas() > 0
array = array.select(positive_sel)
array = array.sort("packed_indices")
merge_ext = miller_ext.merge_equivalents_obs(array.indices(),
array.data(),
array.sigmas(),
use_internal_variance=True)
r_meas = merge_ext.r_meas
cc_one_half = miller.compute_cc_one_half(unmerged=array,
return_n_refl=False)
return r_meas, cc_one_half