def best_match(sites1,sites2,crystal_symmetry=None,
reject_if_too_far=None,distance_per_site=None):
assert distance_per_site is not None
# if reject_if_too_far and the centers of the two are further than can
# be reached by the remainders, skip
unit_cell=crystal_symmetry.unit_cell()
sps=crystal_symmetry.special_position_settings(min_distance_sym_equiv=0.5)
from scitbx.array_family import flex
# Match coordinates
from cctbx import sgtbx
# check central atoms if n>5 for each
if sites1.size()>5 and sites2.size()>5:
# what is distance?
index1=sites1.size()//2
index2=sites2.size()//2
x1_ses=sps.sym_equiv_sites(site=sites1[index1])
info=sgtbx.min_sym_equiv_distance_info(reference_sites=x1_ses,
other=sites2[index2])
dd=info.dist()
# what is distance spannable by ends of each?
max_dist=(index1+index2)*distance_per_site
if dd > max_dist:
info.i=index1
info.j=index2
return info # hopeless
best_info=None
best_dist=None
i=0
for site in sites1:
x1_ses=sps.sym_equiv_sites(site=site)
j=0
for site2 in sites2:
info=sgtbx.min_sym_equiv_distance_info(reference_sites=x1_ses,
other=site2)
dd=info.dist()
if best_dist is None or dd<best_dist:
best_dist=dd
best_info=info
best_info.i=i # just tack them on
best_info.j=j
j+=1
i+=1
return best_info
def best_match(sites1,sites2,crystal_symmetry=None,
reject_if_too_far=None,distance_per_site=None):
assert distance_per_site is not None
# if reject_if_too_far and the centers of the two are further than can
# be reached by the remainders, skip
unit_cell=crystal_symmetry.unit_cell()
sps=crystal_symmetry.special_position_settings(min_distance_sym_equiv=0.5)
from scitbx.array_family import flex
# Match coordinates
from cctbx import sgtbx
# check central atoms if n>5 for each
if sites1.size()>5 and sites2.size()>5:
# what is distance?
index1=sites1.size()//2
index2=sites2.size()//2
x1_ses=sps.sym_equiv_sites(site=sites1[index1])
info=sgtbx.min_sym_equiv_distance_info(reference_sites=x1_ses,
other=sites2[index2])
dd=info.dist()
# what is distance spannable by ends of each?
max_dist=(index1+index2)*distance_per_site
if dd > max_dist:
info.i=index1
info.j=index2
return info # hopeless
best_info=None
best_dist=None
i=0
for site in sites1:
x1_ses=sps.sym_equiv_sites(site=site)
j=0
for site2 in sites2:
info=sgtbx.min_sym_equiv_distance_info(reference_sites=x1_ses,
other=site2)
dd=info.dist()
if best_dist is None or dd<best_dist:
best_dist=dd
best_info=info
best_info.i=i # just tack them on
best_info.j=j
j+=1
i+=1
return best_info
def loop(self):
for i_position in xrange(self.wyckoff_table.size()):
site_symmetry_i = self.wyckoff_table.random_site_symmetry(
special_position_settings=self.special_position_settings,
i_position=i_position)
equiv_sites_i = sgtbx.sym_equiv_sites(site_symmetry_i)
for j_position in xrange(self.wyckoff_table.size()):
for n_trial in xrange(self.max_trials_per_position):
site_j = self.wyckoff_table.random_site_symmetry(
special_position_settings=self.
special_position_settings,
i_position=j_position).exact_site()
dist_info = sgtbx.min_sym_equiv_distance_info(
equiv_sites_i, site_j)
if (dist_info.dist() > self.min_cross_distance):
structure = xray.structure(
special_position_settings=self.
special_position_settings,
scatterers=flex.xray_scatterer([
xray.scatterer(
scattering_type=self.scattering_type,
site=site) for site in
[site_symmetry_i.exact_site(), site_j]
]))
yield structure, dist_info.dist()
break
def peak_cluster_reduction(crystal_symmetry, peak_list,
min_peak_distance, max_reduced_peaks):
special_position_settings = crystal.special_position_settings(
crystal_symmetry=crystal_symmetry,
min_distance_sym_equiv=min_peak_distance)
peaks = []
for i,site in enumerate(peak_list.sites()):
peaks.append(dicts.easy(
site=special_position_settings.site_symmetry(site).exact_site(),
height=peak_list.heights()[i]))
reduced_peaks = []
for peak in peaks:
site_symmetry = special_position_settings.site_symmetry(peak.site)
equiv_sites = sgtbx.sym_equiv_sites(site_symmetry)
keep = True
for reduced_peak in reduced_peaks:
dist = sgtbx.min_sym_equiv_distance_info(
equiv_sites, reduced_peak.site).dist()
if (dist < min_peak_distance):
keep = False
break
if (keep == True):
reduced_peaks.append(peak)
if (len(reduced_peaks) == max_reduced_peaks): break
return reduced_peaks
def _accumulate_significant(self, site, height, site_symmetry, equiv_sites):
unit_cell = self.special_position_settings().unit_cell()
orth = unit_cell.orthogonalize
frac = unit_cell.fractionalize
sum_w_sites = matrix.col(orth(site)) * height
sum_w = height
height_cutoff = height * self._cluster_height_fraction
for i in xrange(self._peak_list_index, self._peak_list.size()):
if (self._is_processed[i]): continue
other_height = self._peak_list.heights()[i]
if (other_height < height_cutoff): break
other_site = self._peak_list.sites()[i]
other_site_symmetry = self._special_position_settings.site_symmetry(
other_site)
if ( self._general_positions_only
and not other_site_symmetry.is_point_group_1()):
self._is_processed[i] = True
continue
other_site = other_site_symmetry.exact_site()
dist_info = sgtbx.min_sym_equiv_distance_info(equiv_sites, other_site)
dist = dist_info.dist()
if (dist < self._min_cross_distance):
self._is_processed[i] = True
close_site = dist_info.apply(flex.vec3_double([other_site]))[0]
close_site = site_symmetry.special_op() * close_site
sum_w_sites += matrix.col(orth(close_site)) * other_height
sum_w += other_height
return frac(sum_w_sites / sum_w), height
def _accumulate_significant(self, site, height, site_symmetry,
equiv_sites):
unit_cell = self.special_position_settings().unit_cell()
orth = unit_cell.orthogonalize
frac = unit_cell.fractionalize
sum_w_sites = matrix.col(orth(site)) * height
sum_w = height
height_cutoff = height * self._cluster_height_fraction
for i in xrange(self._peak_list_index, self._peak_list.size()):
if (self._is_processed[i]): continue
other_height = self._peak_list.heights()[i]
if (other_height < height_cutoff): break
other_site = self._peak_list.sites()[i]
other_site_symmetry = self._special_position_settings.site_symmetry(
other_site)
if (self._general_positions_only
and not other_site_symmetry.is_point_group_1()):
self._is_processed[i] = True
continue
other_site = other_site_symmetry.exact_site()
dist_info = sgtbx.min_sym_equiv_distance_info(
equiv_sites, other_site)
dist = dist_info.dist()
if (dist < self._min_cross_distance):
self._is_processed[i] = True
close_site = dist_info.apply(flex.vec3_double([other_site]))[0]
close_site = site_symmetry.special_op() * close_site
sum_w_sites += matrix.col(orth(close_site)) * other_height
sum_w += other_height
return frac(sum_w_sites / sum_w), height
def show_patterson_peaks(self,
min_relative_peak_height=0.1,
show_at_least=3):
print("Patterson peaks for %s:" % str(self.input.info()))
reciprocal_map = self.input
if (reciprocal_map.anomalous_flag()):
reciprocal_map = reciprocal_map.average_bijvoet_mates()
patterson_map = reciprocal_map.patterson_map(
symmetry_flags=maptbx.use_space_group_symmetry)
patterson_map.apply_sigma_scaling()
peak_list = patterson_map.tags().peak_search(
map=patterson_map.real_map(),
parameters=maptbx.peak_search_parameters())
max_height = peak_list.heights()[0]
sym_equiv_origin = sgtbx.sym_equiv_sites(
unit_cell=patterson_map.unit_cell(),
space_group=patterson_map.space_group(),
original_site=(0, 0, 0))
print(" Fractional coordinates Height Distance from origin")
for i_peak in range(peak_list.size()):
height = peak_list.heights()[i_peak]
if (height < max_height * min_relative_peak_height
and i_peak > show_at_least):
break
site = peak_list.sites()[i_peak]
dist_info = sgtbx.min_sym_equiv_distance_info(
sym_equiv_origin, site)
print(" %8.4f %8.4f %8.4f" % (dist_info.sym_op() * site), end=' ')
print(" %8.3f %8.3f" % (height, dist_info.dist()))
print()
def verify_match(model1, model2, tolerance, match_rt, pairs):
adj_tolerance = tolerance * (1 + 1.e-6)
for pair in pairs:
c1 = model1[pair[0]].site
c2 = match_rt * model2[pair[1]].site
equiv_c2 = sgtbx.sym_equiv_sites(model1.site_symmetry(c2.elems))
dist_info = sgtbx.min_sym_equiv_distance_info(equiv_c2, c1)
assert dist_info.dist() < adj_tolerance, str(model1.space_group_info())
def verify_match(model1, model2, tolerance, match_rt, pairs):
adj_tolerance = tolerance * (1 + 1.e-6)
for pair in pairs:
c1 = model1[pair[0]].site
c2 = match_rt * model2[pair[1]].site
equiv_c2 = sgtbx.sym_equiv_sites(model1.site_symmetry(c2.elems))
dist_info = sgtbx.min_sym_equiv_distance_info(equiv_c2, c1)
assert dist_info.dist() < adj_tolerance, str(model1.space_group_info())
def have_suitable_hetero_distance(existing_sites,
sym_equiv_sites_of_other_site,
min_hetero_distance):
for existing_site in existing_sites:
if (sgtbx.min_sym_equiv_distance_info(sym_equiv_sites_of_other_site,
existing_site).dist() <
min_hetero_distance):
return False
return True
def have_suitable_hetero_distance(existing_sites,
sym_equiv_sites_of_other_site,
min_hetero_distance):
for existing_site in existing_sites:
if (sgtbx.min_sym_equiv_distance_info(
sym_equiv_sites_of_other_site, existing_site).dist()
< min_hetero_distance):
return False
return True
def check_peaks(structure, peak_sites, max_min_dist):
for scatterer in structure.scatterers():
site_symmetry = structure.site_symmetry(scatterer.site)
equiv_sites = sgtbx.sym_equiv_sites(site_symmetry)
min_dist = None
for peak_site in peak_sites:
dist_info = sgtbx.min_sym_equiv_distance_info(equiv_sites, peak_site)
if (min_dist is None):
min_dist = dist_info.dist()
else:
min_dist = min(min_dist, dist_info.dist())
assert min_dist <= max_min_dist, (min_dist, max_min_dist)
def check_peaks(structure, peak_sites, max_min_dist):
for scatterer in structure.scatterers():
site_symmetry = structure.site_symmetry(scatterer.site)
equiv_sites = sgtbx.sym_equiv_sites(site_symmetry)
min_dist = None
for peak_site in peak_sites:
dist_info = sgtbx.min_sym_equiv_distance_info(
equiv_sites, peak_site)
if (min_dist is None):
min_dist = dist_info.dist()
else:
min_dist = min(min_dist, dist_info.dist())
assert min_dist <= max_min_dist, (min_dist, max_min_dist)
def next_with_effective_resolution(self):
while 1:
peak_list_index = self._peak_list_index
if (peak_list_index >= self._peak_list.size()): return None
self._peak_list_index += 1
if (self._is_processed is not None):
if (self._is_processed[peak_list_index]): continue
self._is_processed[peak_list_index] = True
grid_index = self._peak_list.grid_indices(peak_list_index)
grid_height = self._peak_list.grid_heights()[peak_list_index]
site = self._peak_list.sites()[peak_list_index]
height = self._peak_list.heights()[peak_list_index]
site_symmetry = self._special_position_settings.site_symmetry(site)
if ( self._general_positions_only
and not site_symmetry.is_point_group_1()):
continue
site = site_symmetry.exact_site()
equiv_sites = sgtbx.sym_equiv_sites(site_symmetry)
keep = True
if (self._sites.size() > 250):
import warnings
warnings.warn(
message="This function should not be used for"
" processing a large number of peaks.",
category=RuntimeWarning)
for s in self._sites:
dist = sgtbx.min_sym_equiv_distance_info(equiv_sites, s).dist()
if (dist < self._min_cross_distance):
keep = False
break
if (keep == True):
if ( self._effective_resolution is not None
and ( self._heights.size() == 0
or height < self._heights[0]
* self._significant_height_fraction)):
site, height = self._accumulate_significant(
site, height, site_symmetry, equiv_sites)
self._peak_list_indices.append(peak_list_index)
self._sites.append(site)
self._heights.append(height)
return cluster_site_info(
peak_list_index=peak_list_index,
grid_index=grid_index,
grid_height=grid_height,
site=site,
height=height)
def compute_refined_matches(ref_model1, ref_model2,
tolerance,
models_are_diffraction_index_equivalent,
shall_break):
match_symmetry = euclidean_match_symmetry(
ref_model1.space_group_info(),
use_k2l=True, use_l2n=(not models_are_diffraction_index_equivalent))
ref_model1_sites = flex.vec3_double([pos.site for pos in ref_model1])
ref_model2_sites = flex.vec3_double([pos.site for pos in ref_model2])
add_pair_ext = ext.add_pair(
tolerance,
ref_model1.unit_cell(),
ref_model1.space_group(),
ref_model1.min_distance_sym_equiv(),
ref_model1_sites,
ref_model2_sites)
accumulated_match_refine_times = match_refine_times()
refined_matches = []
for i_pivot1 in xrange(ref_model1.size()):
for i_pivot2 in xrange(ref_model2.size()):
for eucl_symop in match_symmetry.rt_mx:
c2 = eucl_symop * ref_model2[i_pivot2].site
dist_info = sgtbx.min_sym_equiv_distance_info(
add_pair_ext.equiv1(i_pivot1),
c2,
match_symmetry.continuous_shift_flags)
if (dist_info.dist() < tolerance):
allowed_shift = dist_info.continuous_shifts()
match = match_refine(tolerance,
ref_model1, ref_model2,
match_symmetry,
add_pair_ext,
i_pivot1, i_pivot2,
eucl_symop,
allowed_shift,
accumulated_match_refine_times)
match.rt = match_rt_from_ref_eucl_rt(
ref_model1.cb_op(),
ref_model2.cb_op(),
match.ref_eucl_rt)
refined_matches.append(match)
if shall_break(match):
return refined_matches
#print accumulated_match_refine_times
return refined_matches
def compute_refined_matches(ref_model1, ref_model2,
tolerance,
models_are_diffraction_index_equivalent,
shall_break):
match_symmetry = euclidean_match_symmetry(
ref_model1.space_group_info(),
use_k2l=True, use_l2n=(not models_are_diffraction_index_equivalent))
ref_model1_sites = flex.vec3_double([pos.site for pos in ref_model1])
ref_model2_sites = flex.vec3_double([pos.site for pos in ref_model2])
add_pair_ext = ext.add_pair(
tolerance,
ref_model1.unit_cell(),
ref_model1.space_group(),
ref_model1.min_distance_sym_equiv(),
ref_model1_sites,
ref_model2_sites)
accumulated_match_refine_times = match_refine_times()
refined_matches = []
for i_pivot1 in range(ref_model1.size()):
for i_pivot2 in range(ref_model2.size()):
for eucl_symop in match_symmetry.rt_mx:
c2 = eucl_symop * ref_model2[i_pivot2].site
dist_info = sgtbx.min_sym_equiv_distance_info(
add_pair_ext.equiv1(i_pivot1),
c2,
match_symmetry.continuous_shift_flags)
if (dist_info.dist() < tolerance):
allowed_shift = dist_info.continuous_shifts()
match = match_refine(tolerance,
ref_model1, ref_model2,
match_symmetry,
add_pair_ext,
i_pivot1, i_pivot2,
eucl_symop,
allowed_shift,
accumulated_match_refine_times)
match.rt = match_rt_from_ref_eucl_rt(
ref_model1.cb_op(),
ref_model2.cb_op(),
match.ref_eucl_rt)
refined_matches.append(match)
if shall_break(match):
return refined_matches
#print accumulated_match_refine_times
return refined_matches
def next_with_effective_resolution(self):
while 1:
peak_list_index = self._peak_list_index
if (peak_list_index >= self._peak_list.size()): return None
self._peak_list_index += 1
if (self._is_processed is not None):
if (self._is_processed[peak_list_index]): continue
self._is_processed[peak_list_index] = True
grid_index = self._peak_list.grid_indices(peak_list_index)
grid_height = self._peak_list.grid_heights()[peak_list_index]
site = self._peak_list.sites()[peak_list_index]
height = self._peak_list.heights()[peak_list_index]
site_symmetry = self._special_position_settings.site_symmetry(site)
if (self._general_positions_only
and not site_symmetry.is_point_group_1()):
continue
site = site_symmetry.exact_site()
equiv_sites = sgtbx.sym_equiv_sites(site_symmetry)
keep = True
if (self._sites.size() > 250):
import warnings
warnings.warn(message="This function should not be used for"
" processing a large number of peaks.",
category=RuntimeWarning)
for s in self._sites:
dist = sgtbx.min_sym_equiv_distance_info(equiv_sites, s).dist()
if (dist < self._min_cross_distance):
keep = False
break
if (keep == True):
if (self._effective_resolution is not None and
(self._heights.size() == 0 or height <
self._heights[0] * self._significant_height_fraction)):
site, height = self._accumulate_significant(
site, height, site_symmetry, equiv_sites)
self._peak_list_indices.append(peak_list_index)
self._sites.append(site)
self._heights.append(height)
return cluster_site_info(peak_list_index=peak_list_index,
grid_index=grid_index,
grid_height=grid_height,
site=site,
height=height)
def loop(self):
for i_position in xrange(self.wyckoff_table.size()):
site_symmetry_i = self.wyckoff_table.random_site_symmetry(
special_position_settings=self.special_position_settings,
i_position=i_position)
equiv_sites_i = sgtbx.sym_equiv_sites(site_symmetry_i)
for j_position in xrange(self.wyckoff_table.size()):
for n_trial in xrange(self.max_trials_per_position):
site_j = self.wyckoff_table.random_site_symmetry(
special_position_settings=self.special_position_settings,
i_position=j_position).exact_site()
dist_info = sgtbx.min_sym_equiv_distance_info(equiv_sites_i, site_j)
if (dist_info.dist() > self.min_cross_distance):
structure = xray.structure(
special_position_settings=self.special_position_settings,
scatterers=flex.xray_scatterer(
[xray.scatterer(scattering_type=self.scattering_type, site=site)
for site in [site_symmetry_i.exact_site(), site_j]]))
yield structure, dist_info.dist()
break
def match_sites_by_symmetry(ref_sites,
query_sites,
unit_cell,
space_group,
cutoff=5):
"""Pair sites in query_sites to sites in ref_sites, allowing for symmetry"""
pairings = numpy.zeros((len(ref_sites), len(query_sites)), dtype=numpy.int)
for i_ref, ref in enumerate(ref_sites):
ref_frac = unit_cell.fractionalize(ref)
sym_sites_ref = sgtbx.sym_equiv_sites(space_group=space_group,
unit_cell=unit_cell,
original_site=ref_frac)
for i_query, query in enumerate(query_sites):
query_frac = unit_cell.fractionalize(query)
min_dist = sgtbx.min_sym_equiv_distance_info(
sym_sites_ref, query_frac).dist()
if min_dist < cutoff:
pairings[i_ref, i_query] = 1
return pairings
def show_patterson_peaks(self, min_relative_peak_height=0.1, show_at_least=3):
print "Patterson peaks for %s:" % str(self.input.info())
reciprocal_map = self.input
if reciprocal_map.anomalous_flag():
reciprocal_map = reciprocal_map.average_bijvoet_mates()
patterson_map = reciprocal_map.patterson_map(symmetry_flags=maptbx.use_space_group_symmetry)
patterson_map.apply_sigma_scaling()
peak_list = patterson_map.tags().peak_search(
map=patterson_map.real_map(), parameters=maptbx.peak_search_parameters()
)
max_height = peak_list.heights()[0]
sym_equiv_origin = sgtbx.sym_equiv_sites(
unit_cell=patterson_map.unit_cell(), space_group=patterson_map.space_group(), original_site=(0, 0, 0)
)
print " Fractional coordinates Height Distance from origin"
for i_peak in xrange(peak_list.size()):
height = peak_list.heights()[i_peak]
if height < max_height * min_relative_peak_height and i_peak > show_at_least:
break
site = peak_list.sites()[i_peak]
dist_info = sgtbx.min_sym_equiv_distance_info(sym_equiv_origin, site)
print " %8.4f %8.4f %8.4f" % (dist_info.sym_op() * site),
print " %8.3f %8.3f" % (height, dist_info.dist())
print
def calculate_shortest_diff(self, pair):
c2 = self.apply_eucl_ops(pair[1])
return sgtbx.min_sym_equiv_distance_info(
self.add_pair_ext.equiv1(pair[0]), c2).diff()
def run_call_back(flags, space_group_info):
verbose = flags.Verbose
if (flags.StaticModels):
model1 = (test_model().add_random_positions(2, "A").shuffle_positions(
).random_symmetry_mates().apply_random_eucl_op())
model2 = (test_model().add_random_positions(
3, "B").shuffle_positions().random_symmetry_mates().
apply_random_eucl_op().shake_positions().random_hand())
for i in (0, 1):
m1 = model1
if (i): m1 = model1.transform_to_reference_setting().reset_cb_op()
for j in (0, 1):
m2 = model2
if (j):
m2 = model2.transform_to_reference_setting().reset_cb_op()
if (0 or verbose):
m1.show("Model1(%d)" % (i, ))
m2.show("Model2(%d)" % (j, ))
model_matches = emma.model_matches(m1,
m2,
rms_penalty_per_site=0)
analyze_refined_matches(m1, m2, model_matches.refined_matches,
verbose)
return False
model_core = test_model(space_group_info)
model1 = (model_core.add_random_positions(2, "A"))
model2 = (model_core.add_random_positions(
3, "B").shuffle_positions().random_symmetry_mates().
apply_random_eucl_op().shake_positions().random_hand())
if (0 or verbose):
model_core.show("Core")
model1.show("Model1")
model2.show("Model2")
model_matches = emma.model_matches(model1, model2, rms_penalty_per_site=0)
analyze_refined_matches(model1, model2, model_matches.refined_matches,
verbose)
assert model_matches.consensus_model().size() >= model1.size() - 2
assert model_matches.consensus_model(i_model=2).size() >= model2.size() - 3
model1.expand_to_p1()
model2.as_xray_structure()
for i1, i2, m1, m2 in [(1, 2, model1, model2), (2, 1, model2, model1)]:
m2_t = model_matches.transform_model(i_model=i2)
assert m1.unit_cell().is_similar_to(m2_t.unit_cell())
assert m1.space_group() == m2_t.space_group()
for pair in model_matches.refined_matches[0].pairs:
site1 = m1.positions()[pair[i1 - 1]].site
site2 = m2_t.positions()[pair[i2 - 1]].site
equiv_sites1 = sgtbx.sym_equiv_sites(m1.site_symmetry(site1))
dist_info = sgtbx.min_sym_equiv_distance_info(equiv_sites1, site2)
assert dist_info.dist() < model_matches.tolerance + 1.e-6
site2_closest = dist_info.sym_op() * site2
assert approx_equal(m1.unit_cell().distance(site1, site2_closest),
dist_info.dist())
if (i1 == 1):
singles = model_matches.refined_matches[0].singles2
else:
singles = model_matches.refined_matches[0].singles1
for i_site2 in singles:
site2 = m2_t.positions()[i_site2].site
for i_site1 in range(len(model1.positions())):
site1 = m1.positions()[i_site1].site
equiv_sites1 = sgtbx.sym_equiv_sites(m1.site_symmetry(site1))
dist_info = sgtbx.min_sym_equiv_distance_info(
equiv_sites1, site2)
if (dist_info.dist() < model_matches.tolerance - 1.e-6):
ok = False
for pair in model_matches.refined_matches[0].pairs:
if (pair[i1 - 1] == i_site1):
ok = True
assert ok
def check_with_grid_tags(inp_symmetry, symmetry_flags,
sites_cart, point_distance,
strictly_inside, flag_write_pdb, verbose):
cb_op_inp_ref = inp_symmetry.change_of_basis_op_to_reference_setting()
if (verbose):
print "cb_op_inp_ref.c():", cb_op_inp_ref.c()
ref_symmetry = inp_symmetry.change_basis(cb_op_inp_ref)
search_symmetry = sgtbx.search_symmetry(
flags=symmetry_flags,
space_group_type=ref_symmetry.space_group_info().type(),
seminvariant=ref_symmetry.space_group_info().structure_seminvariants())
assert search_symmetry.continuous_shifts_are_principal()
continuous_shift_flags = search_symmetry.continuous_shift_flags()
if (flag_write_pdb):
tag_sites_frac = flex.vec3_double()
else:
tag_sites_frac = None
if (strictly_inside):
inp_tags = inp_symmetry.gridding(
step=point_distance*.7,
symmetry_flags=symmetry_flags).tags()
if (tag_sites_frac is not None):
for point in flex.nested_loop(inp_tags.n_real()):
if (inp_tags.tags().tag_array()[point] < 0):
point_frac_inp=[float(n)/d for n,d in zip(point, inp_tags.n_real())]
tag_sites_frac.append(point_frac_inp)
if (inp_tags.tags().n_independent() < sites_cart.size()):
print "FAIL:", inp_symmetry.space_group_info(), \
inp_tags.tags().n_independent(), sites_cart.size()
raise AssertionError
else:
inp_tags = inp_symmetry.gridding(
step=point_distance/2.,
symmetry_flags=symmetry_flags).tags()
sites_frac_inp = inp_symmetry.unit_cell().fractionalize(
sites_cart=sites_cart)
rt = cb_op_inp_ref.c().as_double_array()
sites_frac_ref = rt[:9] * sites_frac_inp
sites_frac_ref += rt[9:]
max_distance = 2 * ((.5 * math.sqrt(3) * point_distance) * 2/3.)
if (verbose):
print "max_distance:", max_distance
for point in flex.nested_loop(inp_tags.n_real()):
if (inp_tags.tags().tag_array()[point] < 0):
point_frac_inp = [float(n)/d for n,d in zip(point, inp_tags.n_real())]
if (tag_sites_frac is not None):
tag_sites_frac.append(point_frac_inp)
point_frac_ref = cb_op_inp_ref.c() * point_frac_inp
equiv_points = sgtbx.sym_equiv_sites(
unit_cell=ref_symmetry.unit_cell(),
space_group=search_symmetry.subgroup(),
original_site=point_frac_ref,
minimum_distance=2.e-6,
tolerance=1.e-6)
min_dist = sgtbx.min_sym_equiv_distance_info(
reference_sites=equiv_points,
others=sites_frac_ref,
principal_continuous_allowed_origin_shift_flags
=continuous_shift_flags).dist()
if (min_dist > max_distance):
print "FAIL:", inp_symmetry.space_group_info(), \
point_frac_ref, min_dist
raise AssertionError
if (inp_tags.tags().n_independent()+10 < sites_cart.size()):
print "FAIL:", inp_symmetry.space_group_info(), \
inp_tags.tags().n_independent(), sites_cart.size()
raise AssertionError
if (tag_sites_frac is not None):
dump_pdb(
file_name="tag_sites.pdb",
crystal_symmetry=inp_symmetry,
sites_cart=inp_symmetry.unit_cell().orthogonalize(
sites_frac=tag_sites_frac))
def calculate_shortest_diff(self, pair):
c2 = self.apply_eucl_ops(pair[1])
return sgtbx.min_sym_equiv_distance_info(
self.add_pair_ext.equiv1(pair[0]), c2).diff()
def check_with_grid_tags(inp_symmetry, symmetry_flags, sites_cart,
point_distance, strictly_inside, flag_write_pdb,
verbose):
cb_op_inp_ref = inp_symmetry.change_of_basis_op_to_reference_setting()
if (verbose):
print("cb_op_inp_ref.c():", cb_op_inp_ref.c())
ref_symmetry = inp_symmetry.change_basis(cb_op_inp_ref)
search_symmetry = sgtbx.search_symmetry(
flags=symmetry_flags,
space_group_type=ref_symmetry.space_group_info().type(),
seminvariant=ref_symmetry.space_group_info().structure_seminvariants())
assert search_symmetry.continuous_shifts_are_principal()
continuous_shift_flags = search_symmetry.continuous_shift_flags()
if (flag_write_pdb):
tag_sites_frac = flex.vec3_double()
else:
tag_sites_frac = None
if (strictly_inside):
inp_tags = inp_symmetry.gridding(step=point_distance * .7,
symmetry_flags=symmetry_flags).tags()
if (tag_sites_frac is not None):
for point in flex.nested_loop(inp_tags.n_real()):
if (inp_tags.tags().tag_array()[point] < 0):
point_frac_inp = [
float(n) / d for n, d in zip(point, inp_tags.n_real())
]
tag_sites_frac.append(point_frac_inp)
if (inp_tags.tags().n_independent() < sites_cart.size()):
print("FAIL:", inp_symmetry.space_group_info(), \
inp_tags.tags().n_independent(), sites_cart.size())
raise AssertionError
else:
inp_tags = inp_symmetry.gridding(step=point_distance / 2.,
symmetry_flags=symmetry_flags).tags()
sites_frac_inp = inp_symmetry.unit_cell().fractionalize(
sites_cart=sites_cart)
rt = cb_op_inp_ref.c().as_double_array()
sites_frac_ref = rt[:9] * sites_frac_inp
sites_frac_ref += rt[9:]
max_distance = 2 * ((.5 * math.sqrt(3) * point_distance) * 2 / 3.)
if (verbose):
print("max_distance:", max_distance)
for point in flex.nested_loop(inp_tags.n_real()):
if (inp_tags.tags().tag_array()[point] < 0):
point_frac_inp = [
float(n) / d for n, d in zip(point, inp_tags.n_real())
]
if (tag_sites_frac is not None):
tag_sites_frac.append(point_frac_inp)
point_frac_ref = cb_op_inp_ref.c() * point_frac_inp
equiv_points = sgtbx.sym_equiv_sites(
unit_cell=ref_symmetry.unit_cell(),
space_group=search_symmetry.subgroup(),
original_site=point_frac_ref,
minimum_distance=2.e-6,
tolerance=1.e-6)
min_dist = sgtbx.min_sym_equiv_distance_info(
reference_sites=equiv_points,
others=sites_frac_ref,
principal_continuous_allowed_origin_shift_flags=
continuous_shift_flags).dist()
if (min_dist > max_distance):
print("FAIL:", inp_symmetry.space_group_info(), \
point_frac_ref, min_dist)
raise AssertionError
if (inp_tags.tags().n_independent() + 10 < sites_cart.size()):
print("FAIL:", inp_symmetry.space_group_info(), \
inp_tags.tags().n_independent(), sites_cart.size())
raise AssertionError
if (tag_sites_frac is not None):
dump_pdb(file_name="tag_sites.pdb",
crystal_symmetry=inp_symmetry,
sites_cart=inp_symmetry.unit_cell().orthogonalize(
sites_frac=tag_sites_frac))
# This is the most convenient interface. Essentially we just need
# sgtbx.structure_seminvariants.
#
match_symmetry = euclidean_model_matching.euclidean_match_symmetry(
space_group_info=sym_ref.space_group_info(),
use_k2l=False,
use_l2n=False)
#
# Compute the symmetry operation which maps the center of mass of
# "other" closest to the center of mass of "reference."
#
centers_frac = [
sym_ref.unit_cell().fractionalize(cb_op_to_ref.c() * center_cart)
for center_cart in centers_of_mass]
dist_info = sgtbx.min_sym_equiv_distance_info(
sym_ref.special_position_settings().sym_equiv_sites(centers_frac[0]),
centers_frac[1],
match_symmetry.continuous_shift_flags)
sym_op = cb_op_to_ref.inverse().apply(dist_info.sym_op())
print "Rotation in fractional space:", sym_op.r().as_xyz()
sym_op = sym_op.as_rational().as_float() \
+ matrix.col(dist_info.continuous_shifts())
print "Translation in fractional space: (%s)" % (
", ".join(["%.6g" % t for t in sym_op.t]))
#
centers_frac = [sym_ref.unit_cell().fractionalize(center_cart)
for center_cart in centers_of_mass]
sym_center_frac = sym_op * centers_frac[1]
sym_center_cart = crystal_symmetry.unit_cell().orthogonalize(sym_center_frac)
print "Centers of mass:"
print " Reference: (%s)" % ", ".join(["%8.2f" % v
for v in centers_of_mass[0]])
# This is the most convenient interface. Essentially we just need
# sgtbx.structure_seminvariants.
#
match_symmetry = euclidean_model_matching.euclidean_match_symmetry(
space_group_info=sym_ref.space_group_info(), use_k2l=False, use_l2n=False
)
#
# Compute the symmetry operation which maps the center of mass of
# "other" closest to the center of mass of "reference."
#
centers_frac = [
sym_ref.unit_cell().fractionalize(cb_op_to_ref.c() * center_cart) for center_cart in centers_of_mass
]
dist_info = sgtbx.min_sym_equiv_distance_info(
sym_ref.special_position_settings().sym_equiv_sites(centers_frac[0]),
centers_frac[1],
match_symmetry.continuous_shift_flags,
)
sym_op = cb_op_to_ref.inverse().apply(dist_info.sym_op())
print "Rotation in fractional space:", sym_op.r().as_xyz()
sym_op = sym_op.as_rational().as_float() + matrix.col(dist_info.continuous_shifts())
print "Translation in fractional space: (%s)" % (", ".join(["%.6g" % t for t in sym_op.t]))
#
centers_frac = [sym_ref.unit_cell().fractionalize(center_cart) for center_cart in centers_of_mass]
sym_center_frac = sym_op * centers_frac[1]
sym_center_cart = crystal_symmetry.unit_cell().orthogonalize(sym_center_frac)
print "Centers of mass:"
print " Reference: (%s)" % ", ".join(["%8.2f" % v for v in centers_of_mass[0]])
print " Original other: (%s)" % ", ".join(["%8.2f" % v for v in centers_of_mass[1]])
print " Symmetry related other: (%s)" % ", ".join(["%8.2f" % v for v in sym_center_cart])
print "Cartesian distance between centers of mass: %.4f" % dist_info.dist()
def run(args, command_name="iotbx.pdb.superpose_centers_of_mass"):
if (len(args) == 0): args = ["--help"]
command_line = (option_parser(
usage="%s [options] [reference_file] [other_file] [parameter_file]" %
command_name).enable_show_defaults().enable_symmetry_comprehensive()
).process(args=args)
if (command_line.expert_level is not None):
master_params.show(expert_level=command_line.expert_level,
attributes_level=command_line.attributes_level)
sys.exit(0)
#
# Loop over command-line arguments.
#
parameter_interpreter = master_params.command_line_argument_interpreter()
parsed_params = []
pdb_file_names = []
command_line_params = []
for arg in command_line.args:
arg_is_processed = False
if (os.path.isfile(arg)):
params = None
try:
params = iotbx.phil.parse(file_name=arg)
except KeyboardInterrupt:
raise
except RuntimeError:
pass
else:
if (len(params.objects) == 0):
params = None
if (params is not None):
parsed_params.append(params)
arg_is_processed = True
elif (pdb.is_pdb_file(file_name=arg)):
pdb_file_names.append(arg)
arg_is_processed = True
if (not arg_is_processed):
try:
params = parameter_interpreter.process(arg=arg)
except Sorry as e:
if (not os.path.isfile(arg)): raise
raise Sorry("Unknown file format: %s" % arg)
else:
command_line_params.append(params)
#
# Consolidation of inputs, resulting in effective phil_params.
#
phil_params = master_params.fetch(sources=parsed_params +
command_line_params)
params = phil_params.extract()
for param_group in [params.reference, params.other, params.output]:
if (param_group.file_name is None and len(pdb_file_names) > 0):
param_group.file_name = pdb_file_names[0]
pdb_file_names = pdb_file_names[1:]
if (len(pdb_file_names) > 0):
raise Sorry("Too many PDB file names: %s" %
", ".join([show_string(s) for s in pdb_file_names]))
if (params.output.file_name is None
and params.other.file_name is not None):
name = os.path.basename(params.other.file_name)
if (name.lower().endswith(".pdb")): name = name[:-4]
name += "_superposed.pdb"
params.output.file_name = name
if (params.crystal_symmetry.unit_cell is None):
params.crystal_symmetry.unit_cell = \
command_line.symmetry.unit_cell()
if (params.crystal_symmetry.space_group is None):
params.crystal_symmetry.space_group = \
command_line.symmetry.space_group_info()
phil_params = master_params.format(python_object=params)
phil_params.show()
print("#phil __OFF__")
#
# Final checks.
#
if (params.reference.file_name is None):
raise Sorry("Required file name is missing: reference.file_name")
if (params.other.file_name is None):
raise Sorry("Required file name is missing: other.file_name")
if (params.output.file_name is None):
raise Sorry("Required file name is missing: output.file_name")
#
# Processing of input PDB files.
#
pdb_objs = []
sites_carts = []
centers_of_mass = []
for param_group in [params.reference, params.other]:
pdb_obj = pdb.hierarchy.input(file_name=param_group.file_name)
pdb_obj.atoms = pdb_obj.hierarchy.atoms()
pdb_objs.append(pdb_obj)
sites_carts.append(pdb_obj.atoms.extract_xyz())
sites_sel = sites_carts[-1]
if (param_group.atom_selection is not None):
sel = pdb_obj.hierarchy.atom_selection_cache().selection(
param_group.atom_selection)
sites_sel = sites_sel.select(sel)
print("Number of selected sites:", sites_sel.size())
centers_of_mass.append(sites_sel.mean())
#
# Consolidation of crystal symmetries.
#
crystal_symmetry = command_line.symmetry
for pdb_obj in pdb_objs:
crystal_symmetry_from_pdb = pdb_obj.input.crystal_symmetry()
if (crystal_symmetry_from_pdb is not None):
crystal_symmetry = crystal_symmetry.join_symmetry(
other_symmetry=crystal_symmetry_from_pdb, force=False)
if (crystal_symmetry.unit_cell() is None):
raise Sorry(
"Unknown unit cell parameters."
"\n Use --unit_cell or --symmetry to supply unit cell parameters."
)
if (crystal_symmetry.space_group_info() is None):
raise Sorry(
"Unknown space group symmetry."
"\n Use --space_group or --symmetry to supply symmetry information."
)
crystal_symmetry.show_summary()
#
# Obtain transformation to reference setting.
# To ensure all allowed origin shifts are parallel to the basis vectors.
#
cb_op_to_ref = crystal_symmetry.change_of_basis_op_to_reference_setting()
sym_ref = crystal_symmetry.change_basis(cb_op=cb_op_to_ref)
#
# Obtain allowed origin shifts.
# This is the most convenient interface. Essentially we just need
# sgtbx.structure_seminvariants.
#
match_symmetry = euclidean_model_matching.euclidean_match_symmetry(
space_group_info=sym_ref.space_group_info(),
use_k2l=False,
use_l2n=False)
#
# Compute the symmetry operation which maps the center of mass of
# "other" closest to the center of mass of "reference."
#
centers_frac = [
sym_ref.unit_cell().fractionalize(cb_op_to_ref.c() * center_cart)
for center_cart in centers_of_mass
]
dist_info = sgtbx.min_sym_equiv_distance_info(
sym_ref.special_position_settings().sym_equiv_sites(centers_frac[0]),
centers_frac[1], match_symmetry.continuous_shift_flags)
sym_op = cb_op_to_ref.inverse().apply(dist_info.sym_op())
print("Rotation in fractional space:", sym_op.r().as_xyz())
sym_op = sym_op.as_rational().as_float() \
+ matrix.col(dist_info.continuous_shifts())
print("Translation in fractional space: (%s)" %
(", ".join(["%.6g" % t for t in sym_op.t])))
#
centers_frac = [
sym_ref.unit_cell().fractionalize(center_cart)
for center_cart in centers_of_mass
]
sym_center_frac = sym_op * centers_frac[1]
sym_center_cart = crystal_symmetry.unit_cell().orthogonalize(
sym_center_frac)
print("Centers of mass:")
print(" Reference: (%s)" %
", ".join(["%8.2f" % v for v in centers_of_mass[0]]))
print(" Original other: (%s)" %
", ".join(["%8.2f" % v for v in centers_of_mass[1]]))
print(" Symmetry related other: (%s)" %
", ".join(["%8.2f" % v for v in sym_center_cart]))
print("Cartesian distance between centers of mass: %.4f" %
dist_info.dist())
#
# Internal consistency check (in input setting).
#
assert approx_equal(
crystal_symmetry.unit_cell().distance(centers_frac[0],
sym_center_frac),
dist_info.dist())
#
# Transform atomic coordinates of "other."
#
sites_frac_other = crystal_symmetry.unit_cell().fractionalize(
sites_cart=sites_carts[1])
sites_frac_other_superposed = sym_op * sites_frac_other
sites_cart_other_superposed = crystal_symmetry.unit_cell().orthogonalize(
sites_frac=sites_frac_other_superposed)
#
# Replace original coordinates with transformed coordinates.
#
pdb_objs[1].atoms.set_xyz(new_xyz=sites_cart_other_superposed)
#
# Write (selected) transformed coordinates.
#
pdb_hierarchy = pdb_objs[1].hierarchy
if (params.output.atom_selection is not None):
sel = pdb_hierarchy.atom_selection_cache().selection(
params.output.atom_selection)
pdb_hierarchy = pdb_hierarchy.select(atom_selection=sel)
pdb_hierarchy.write_pdb_file(file_name=params.output.file_name,
crystal_symmetry=crystal_symmetry,
append_end=True,
atoms_reset_serial_first_value=1)
def run_call_back(flags, space_group_info):
verbose = flags.Verbose
if (flags.StaticModels):
model1 = (test_model()
.add_random_positions(2, "A")
.shuffle_positions()
.random_symmetry_mates()
.apply_random_eucl_op()
)
model2 = (test_model()
.add_random_positions(3, "B")
.shuffle_positions()
.random_symmetry_mates()
.apply_random_eucl_op()
.shake_positions()
.random_hand()
)
for i in (0,1):
m1 = model1
if (i): m1 = model1.transform_to_reference_setting().reset_cb_op()
for j in (0,1):
m2 = model2
if (j): m2 = model2.transform_to_reference_setting().reset_cb_op()
if (0 or verbose):
m1.show("Model1(%d)" % (i,))
m2.show("Model2(%d)" % (j,))
model_matches = emma.model_matches(m1, m2, rms_penalty_per_site=0)
analyze_refined_matches(m1, m2, model_matches.refined_matches, verbose)
return False
model_core = test_model(space_group_info)
model1 = (model_core
.add_random_positions(2, "A")
)
model2 = (model_core
.add_random_positions(3, "B")
.shuffle_positions()
.random_symmetry_mates()
.apply_random_eucl_op()
.shake_positions()
.random_hand()
)
if (0 or verbose):
model_core.show("Core")
model1.show("Model1")
model2.show("Model2")
model_matches = emma.model_matches(model1, model2, rms_penalty_per_site=0)
analyze_refined_matches(
model1, model2, model_matches.refined_matches, verbose)
assert model_matches.consensus_model().size() >= model1.size()-2
assert model_matches.consensus_model(i_model=2).size() >= model2.size()-3
model1.expand_to_p1()
model2.as_xray_structure()
for i1,i2,m1,m2 in [(1,2,model1,model2),(2,1,model2,model1)]:
m2_t = model_matches.transform_model(i_model=i2)
assert m1.unit_cell().is_similar_to(m2_t.unit_cell())
assert m1.space_group() == m2_t.space_group()
for pair in model_matches.refined_matches[0].pairs:
site1 = m1.positions()[pair[i1-1]].site
site2 = m2_t.positions()[pair[i2-1]].site
equiv_sites1 = sgtbx.sym_equiv_sites(m1.site_symmetry(site1))
dist_info = sgtbx.min_sym_equiv_distance_info(equiv_sites1, site2)
assert dist_info.dist() < model_matches.tolerance + 1.e-6
site2_closest = dist_info.sym_op() * site2
assert approx_equal(
m1.unit_cell().distance(site1, site2_closest),
dist_info.dist())
if (i1 == 1):
singles = model_matches.refined_matches[0].singles2
else:
singles = model_matches.refined_matches[0].singles1
for i_site2 in singles:
site2 = m2_t.positions()[i_site2].site
for i_site1 in xrange(len(model1.positions())):
site1 = m1.positions()[i_site1].site
equiv_sites1 = sgtbx.sym_equiv_sites(m1.site_symmetry(site1))
dist_info = sgtbx.min_sym_equiv_distance_info(equiv_sites1, site2)
if (dist_info.dist() < model_matches.tolerance - 1.e-6):
ok = False
for pair in model_matches.refined_matches[0].pairs:
if (pair[i1-1] == i_site1):
ok = True
assert ok
