def __init__(self, model_id="SBT", n_elements=4):
if (model_id is None): return
self.model_id = model_id
pos = emma.position
if (type(model_id) == type("")):
if (model_id == "SBT"):
emma.model.__init__(
self,
crystal.special_position_settings(
crystal.symmetry((16.8986, 16.8986, 16.8986, 61.1483,
61.1483, 61.1483), "R -3 m :R")),
(pos("SI1", (-0.3584, 0.2844, 0.4622)),
pos("SI2", (-0.2133, 0.9659, -0.6653)),
pos("SI3", (-0.8358, 0.7, 0.3431)),
pos("SI4", (0.4799, 1.836, 0.6598))))
else:
raise RuntimeError("Unknown model_id: " + model_id)
else:
structure = random_structure.xray_structure(model_id,
elements=["S"] *
n_elements,
volume_per_atom=50.,
min_distance=2.0)
positions = []
for scatterer in structure.scatterers():
positions.append(emma.position(scatterer.label,
scatterer.site))
emma.model.__init__(self, structure, positions)
def get_emma_model_from_pdb(file_name=None,
pdb_records=None,
crystal_symmetry=None):
assert [file_name, pdb_records].count(None) == 1
if (pdb_records is None):
pdb_inp = iotbx.pdb.input(file_name=file_name)
else:
pdb_inp = iotbx.pdb.input(source_info=None, lines=pdb_records)
crystal_symmetry = pdb_inp.crystal_symmetry(
crystal_symmetry=crystal_symmetry,
weak_symmetry=True)
if (not crystal_symmetry or crystal_symmetry.unit_cell() is None):
raise RuntimeError("Unit cell parameters unknown for model %s." %(
file_name))
if (crystal_symmetry.space_group_info() is None):
raise RuntimeError("Space group unknown.")
positions = []
for atom in pdb_inp.atoms_with_labels():
positions.append(emma.position(
":".join([str(len(positions)+1),
atom.name, atom.resname, atom.chain_id]),
crystal_symmetry.unit_cell().fractionalize(atom.xyz)))
assert len(positions) > 0
result = emma.model(
crystal_symmetry.special_position_settings(),
positions)
if (file_name is not None):
result.label = file_name
return result
def random_symmetry_mates(self):
new_positions = []
for pos in self.positions():
equiv = sgtbx.sym_equiv_sites(self.site_symmetry(pos.site))
i = random.randrange(equiv.coordinates().size())
new_positions.append(emma.position(pos.label, equiv.coordinates()[i]))
return self.create_new_test_model(new_positions)
def random_symmetry_mates(self):
new_positions = []
for pos in self.positions():
equiv = sgtbx.sym_equiv_sites(self.site_symmetry(pos.site))
i = random.randrange(equiv.coordinates().size())
new_positions.append(emma.position(pos.label, equiv.coordinates()[i]))
return self.create_new_test_model(new_positions)
def __init__(self, model_id="SBT", n_elements=4):
if (model_id is None): return
self.model_id = model_id
pos = emma.position
if (type(model_id) == type("")):
if (model_id == "SBT"):
emma.model.__init__(self,
crystal.special_position_settings(crystal.symmetry(
(16.8986, 16.8986, 16.8986, 61.1483, 61.1483, 61.1483),
"R -3 m :R")),
(pos("SI1", (-0.3584, 0.2844, 0.4622)),
pos("SI2", (-0.2133, 0.9659, -0.6653)),
pos("SI3", (-0.8358, 0.7, 0.3431)),
pos("SI4", (0.4799, 1.836, 0.6598))))
else:
raise RuntimeError, "Unknown model_id: " + model_id
else:
structure = random_structure.xray_structure(
model_id,
elements=["S"]*n_elements,
volume_per_atom=50.,
min_distance=2.0)
positions = []
for scatterer in structure.scatterers():
positions.append(emma.position(scatterer.label, scatterer.site))
emma.model.__init__(self, structure, positions)
def get_emma_model_from_pdb(file_name=None,
pdb_records=None,
crystal_symmetry=None):
assert [file_name, pdb_records].count(None) == 1
if (pdb_records is None):
pdb_inp = iotbx.pdb.input(file_name=file_name)
else:
pdb_inp = iotbx.pdb.input(source_info=None, lines=pdb_records)
crystal_symmetry = pdb_inp.crystal_symmetry(
crystal_symmetry=crystal_symmetry, weak_symmetry=True)
if (not crystal_symmetry or crystal_symmetry.unit_cell() is None):
raise RuntimeError("Unit cell parameters unknown for model %s." %
(file_name))
if (crystal_symmetry.space_group_info() is None):
raise RuntimeError("Space group unknown.")
positions = []
for atom in pdb_inp.atoms_with_labels():
positions.append(
emma.position(
":".join([
str(len(positions) + 1), atom.name, atom.resname,
atom.chain_id
]),
crystal_symmetry.unit_cell().fractionalize(atom.xyz)))
assert len(positions) > 0
result = emma.model(crystal_symmetry.special_position_settings(),
positions)
if (file_name is not None):
result.label = file_name
return result
def shake_positions(self, gauss_sigma=0.2, min_distance=1.0):
new_positions = []
for pos in self.positions():
new_coor = random_structure.random_modify_site(
special_position_settings=self,
site=pos.site,
gauss_sigma=gauss_sigma,
max_distance=min_distance * 0.99)
new_positions.append(emma.position(pos.label, new_coor))
return self.create_new_test_model(new_positions)
def shake_positions(self, gauss_sigma=0.2, min_distance=1.0):
new_positions = []
for pos in self.positions():
new_coor = random_structure.random_modify_site(
special_position_settings=self,
site=pos.site,
gauss_sigma=gauss_sigma,
max_distance=min_distance*0.99)
new_positions.append(emma.position(pos.label, new_coor))
return self.create_new_test_model(new_positions)
def get_emma_model_from_solve(file_name, crystal_symmetry):
positions = []
for line in open(file_name):
flds = line.split()
if (len(flds) < 4 or flds[0].lower() != "xyz"): continue
site = [float(x) for x in flds[1:4]]
positions.append(emma.position("site" + str(len(positions) + 1), site))
assert len(positions) > 0
result = emma.model(crystal_symmetry.special_position_settings(),
positions)
result.label = file_name
return result
def __init__(self,
ucparams,
sgsymbol,
convention,
format,
coor_type,
skip_columns,
coordinates,
other_symmetry=None):
self.ucparams = ucparams
self.sgsymbol = sgsymbol
self.convention = convention
self.other_symmetry = other_symmetry
self.coordinate_format = None
if (format == "generic"):
skip_columns = io_utils.interpret_skip_columns(skip_columns)
self.positions = []
for line in coordinates:
label, site = interpret_generic_coordinate_line(
line, skip_columns)
if (label == ""): label = "Site" + str(len(self.positions) + 1)
if (coor_type != "Fractional"):
site = self.get_unit_cell().fractionalize(site)
self.positions.append(emma.position(label, site))
self.coordinate_format = "generic"
else:
if (self.coordinate_format is None):
try:
import iotbx.pdb
pdb_inp = iotbx.pdb.input(source_info=None,
lines=coordinates)
except KeyboardInterrupt:
raise
except Exception:
pass
else:
self.pdb_model = pdb_file_to_emma_model(
self.crystal_symmetry(), pdb_inp, other_symmetry)
if (len(self.pdb_model.positions()) > 0):
self.coordinate_format = "pdb"
if (self.coordinate_format is None):
try:
from iotbx.cns import sdb_reader
self.sdb_files = sdb_reader.multi_sdb_parser(coordinates)
except KeyboardInterrupt:
raise
except Exception:
pass
else:
self.coordinate_format = "sdb"
if (self.coordinate_format is None):
raise RuntimeError("Coordinate format unknown.")
self.i_next_model = 0
def apply_random_eucl_op(self, models_are_diffraction_index_equivalent=0):
match_symmetry = emma.euclidean_match_symmetry(
self.space_group_info(),
use_k2l=True, use_l2n=(not models_are_diffraction_index_equivalent))
i = random.randrange(match_symmetry.rt_mx.order_z())
eucl_symop = match_symmetry.rt_mx(i)
shift = [0.5 - random.random() for i in xrange(3)]
allowed_shift = matrix.col(match_symmetry.filter_shift(shift, selector=1))
new_positions = []
for pos in self.positions():
new_site = matrix.col(eucl_symop * pos.site) + allowed_shift
new_positions.append(emma.position(pos.label, new_site.elems))
return self.create_new_test_model(new_positions)
def get_emma_model_from_solve(file_name, crystal_symmetry):
positions = []
for line in open(file_name):
flds = line.split()
if (len(flds) < 4 or flds[0].lower() != "xyz"): continue
site = [float(x) for x in flds[1:4]]
positions.append(emma.position("site"+str(len(positions)+1), site))
assert len(positions) > 0
result = emma.model(
crystal_symmetry.special_position_settings(),
positions)
result.label = file_name
return result
def sdb_file_to_emma_model(crystal_symmetry, sdb_file):
positions = []
for i, site in zip(count(1), sdb_file.sites):
if (crystal_symmetry.unit_cell() is None):
raise RuntimeError("Unit cell parameters unknown.")
positions.append(
emma.position(
":".join((str(i), site.segid, site.type)),
crystal_symmetry.unit_cell().fractionalize(
(site.x, site.y, site.z))))
m = emma.model(crystal_symmetry.special_position_settings(), positions)
m.label = sdb_file.file_name
return m
def sdb_file_to_emma_model(crystal_symmetry, sdb_file):
positions = []
for i,site in zip(count(1),sdb_file.sites):
if (crystal_symmetry.unit_cell() is None):
raise RuntimeError("Unit cell parameters unknown.")
positions.append(emma.position(
":".join((str(i), site.segid, site.type)),
crystal_symmetry.unit_cell().fractionalize((site.x, site.y, site.z))))
m = emma.model(
crystal_symmetry.special_position_settings(),
positions)
m.label = sdb_file.file_name
return m
def apply_random_eucl_op(self, models_are_diffraction_index_equivalent=0):
match_symmetry = emma.euclidean_match_symmetry(
self.space_group_info(),
use_k2l=True, use_l2n=(not models_are_diffraction_index_equivalent))
i = random.randrange(match_symmetry.rt_mx.order_z())
eucl_symop = match_symmetry.rt_mx(i)
shift = [0.5 - random.random() for i in range(3)]
allowed_shift = matrix.col(match_symmetry.filter_shift(shift, selector=1))
new_positions = []
for pos in self.positions():
new_site = matrix.col(eucl_symop * pos.site) + allowed_shift
new_positions.append(emma.position(pos.label, new_site.elems))
return self.create_new_test_model(new_positions)
def add_random_positions(self, number_of_new_positions=3, label="R",
min_distance=1.0):
existing_sites = []
for pos in self.positions():
existing_sites.append(pos.site)
new_sites = random_structure.random_sites(
special_position_settings=self,
existing_sites=existing_sites,
n_new=number_of_new_positions,
min_hetero_distance=min_distance,
general_positions_only=False)
new_positions = []
i = 0
for site in new_sites:
i += 1
new_positions.append(emma.position("%s%d" % (label, i), site))
return self.create_new_test_model(self.positions() + new_positions)
def add_random_positions(self, number_of_new_positions=3, label="R",
min_distance=1.0):
existing_sites = []
for pos in self.positions():
existing_sites.append(pos.site)
new_sites = random_structure.random_sites(
special_position_settings=self,
existing_sites=existing_sites,
n_new=number_of_new_positions,
min_hetero_distance=min_distance,
general_positions_only=False)
new_positions = []
i = 0
for site in new_sites:
i += 1
new_positions.append(emma.position("%s%d" % (label, i), site))
return self.create_new_test_model(self.positions() + new_positions)
def __init__(self, ucparams, sgsymbol, convention,
format, coor_type, skip_columns, coordinates,
other_symmetry=None):
self.ucparams = ucparams
self.sgsymbol = sgsymbol
self.convention = convention
self.other_symmetry = other_symmetry
self.coordinate_format = None
if (format == "generic"):
skip_columns = io_utils.interpret_skip_columns(skip_columns)
self.positions = []
for line in coordinates:
label, site = interpret_generic_coordinate_line(line, skip_columns)
if (label == ""): label = "Site" + str(len(self.positions)+1)
if (coor_type != "Fractional"):
site = self.get_unit_cell().fractionalize(site)
self.positions.append(emma.position(label, site))
self.coordinate_format = "generic"
else:
if (self.coordinate_format is None):
try:
import iotbx.pdb
pdb_inp = iotbx.pdb.input(source_info=None, lines=coordinates)
except KeyboardInterrupt: raise
except Exception:
pass
else:
self.pdb_model = pdb_file_to_emma_model(
self.crystal_symmetry(), pdb_inp, other_symmetry)
if (len(self.pdb_model.positions()) > 0):
self.coordinate_format = "pdb"
if (self.coordinate_format is None):
try:
from iotbx.cns import sdb_reader
self.sdb_files = sdb_reader.multi_sdb_parser(coordinates)
except KeyboardInterrupt: raise
except Exception:
pass
else:
self.coordinate_format = "sdb"
if (self.coordinate_format is None):
raise RuntimeError("Coordinate format unknown.")
self.i_next_model = 0
def pdb_file_to_emma_model(crystal_symmetry, pdb_inp, other_symmetry):
crystal_symmetry = pdb_inp.crystal_symmetry(
crystal_symmetry=crystal_symmetry, weak_symmetry=False)
if (other_symmetry is not None):
crystal_symmetry = crystal_symmetry.join_symmetry(
other_symmetry=other_symmetry, force=False)
positions = []
for atom in pdb_inp.atoms_with_labels():
if (crystal_symmetry.unit_cell() is None):
raise RuntimeError("Unit cell parameters unknown.")
positions.append(
emma.position(
":".join([
str(len(positions) + 1), atom.name, atom.resname,
atom.chain_id
]),
crystal_symmetry.unit_cell().fractionalize(atom.xyz)))
m = emma.model(crystal_symmetry.special_position_settings(), positions)
m.label = "Other model"
return m
def get_emma_models_from_lst(file_name, crystal_symmetry):
read_flag = False
positions = []
re_lst_header = re.compile("Try *([0-9]+), CPU *([0-9]+), CC All/Weak *([-0-9\.]+) */ *([-0-9\.]+)")
for l in open(file_name):
if l.startswith(" x y z"):
read_flag = True
positions = []
elif read_flag and l.strip() == "":
read_flag = False
elif read_flag:
site = map(float, (l[:8], l[8:16], l[16:24]))
positions.append(emma.position(str(len(positions)+1), site))
elif l.startswith(" Try "):
r = re_lst_header.search(l)
itry, ccall, ccweak = r.group(1), r.group(3), r.group(4)
ret = emma.model(crystal_symmetry.special_position_settings(), positions)
ret.label = "Try%s_CCall_%s_CCweak_%s" % (itry, ccall, ccweak)
yield (ret, itry, ccall, ccweak)
def pdb_file_to_emma_model(crystal_symmetry, pdb_inp, other_symmetry):
crystal_symmetry = pdb_inp.crystal_symmetry(
crystal_symmetry=crystal_symmetry,
weak_symmetry=False)
if (other_symmetry is not None):
crystal_symmetry = crystal_symmetry.join_symmetry(
other_symmetry=other_symmetry,
force=False)
positions = []
for atom in pdb_inp.atoms_with_labels():
if (crystal_symmetry.unit_cell() is None):
raise RuntimeError("Unit cell parameters unknown.")
positions.append(emma.position(
":".join([str(len(positions)+1),
atom.name, atom.resname, atom.chain_id]),
crystal_symmetry.unit_cell().fractionalize(atom.xyz)))
m = emma.model(
crystal_symmetry.special_position_settings(),
positions)
m.label = "Other model"
return m
def get_emma_model_from_sdb(file_name, crystal_symmetry):
sdb_files = sdb_reader.multi_sdb_parser(open(file_name))
if (len(sdb_files) > 1):
raise MultipleEntriesError(
"SDB file %s may contain only one structure." % file_name)
assert len(sdb_files) == 1
sdb_file = sdb_files[0]
crystal_symmetry = crystal_symmetry.join_symmetry(
other_symmetry=sdb_file.crystal_symmetry(),
force=True)
positions = []
for i,site in enumerate(sdb_file.sites):
if (crystal_symmetry.unit_cell() is None):
raise RuntimeError("Unit cell parameters unknown.")
positions.append(emma.position(
":".join((str(i+1), site.segid, site.type)),
crystal_symmetry.unit_cell().fractionalize((site.x, site.y, site.z))))
assert len(positions) > 0
result = emma.model(
crystal_symmetry.special_position_settings(),
positions)
result.label = sdb_file.file_name
return result
def get_emma_model_from_sdb(file_name, crystal_symmetry):
sdb_files = sdb_reader.multi_sdb_parser(open(file_name))
if (len(sdb_files) > 1):
raise MultipleEntriesError(
"SDB file %s may contain only one structure." % file_name)
assert len(sdb_files) == 1
sdb_file = sdb_files[0]
crystal_symmetry = crystal_symmetry.join_symmetry(
other_symmetry=sdb_file.crystal_symmetry(), force=True)
positions = []
for i, site in enumerate(sdb_file.sites):
if (crystal_symmetry.unit_cell() is None):
raise RuntimeError("Unit cell parameters unknown.")
positions.append(
emma.position(
":".join((str(i + 1), site.segid, site.type)),
crystal_symmetry.unit_cell().fractionalize(
(site.x, site.y, site.z))))
assert len(positions) > 0
result = emma.model(crystal_symmetry.special_position_settings(),
positions)
result.label = sdb_file.file_name
return result
def exercise_one_structure(
target_structure,
flipping_type,
anomalous_flag,
d_min,
grid_resolution_factor=1.0 / 2,
verbose=False,
amplitude_type="F",
):
assert amplitude_type in ("F", "E", "quasi-E")
# Generate its structure factors
f_target = (
miller.build_set(
crystal_symmetry=target_structure,
anomalous_flag=target_structure.scatterers().count_anomalous() != 0,
d_min=d_min,
)
.structure_factors_from_scatterers(xray_structure=target_structure, algorithm="direct")
.f_calc()
)
f_target_in_p1 = f_target.expand_to_p1().as_non_anomalous_array().merge_equivalents().array()
f_obs = f_target.as_amplitude_array()
# Unleash charge flipping on the amplitudes
flipping = flipping_type(delta=None)
extra = group_args()
if amplitude_type == "E":
extra.normalisations_for = lambda f: f.amplitude_normalisations(
target_structure.unit_cell_content(omit=("H", "D"))
)
elif amplitude_type == "quasi-E":
extra.normalisations_for = charge_flipping.amplitude_quasi_normalisations
solving = charge_flipping.solving_iterator(
flipping, f_obs, yield_during_delta_guessing=True, yield_solving_interval=1, **extra.__dict__
)
s = StringIO()
charge_flipping.loop(solving, verbose="highly", out=s)
if verbose:
print s.getvalue()
# check whether a phase transition has occured
assert solving.had_phase_transition
flipping = solving.flipping_iterator
f_result_in_p1 = solving.flipping_iterator.f_calc
# Euclidean matching of the peaks from the obtained map
# against those of the correct structure (in P1)
target_structure = target_structure.select(target_structure.scattering_types() == "H", negate=True)
target_structure_in_p1 = target_structure.expand_to_p1()
search_parameters = maptbx.peak_search_parameters(
interpolate=True, min_distance_sym_equiv=1.0, max_clusters=int(target_structure_in_p1.scatterers().size() * 1.2)
)
peak_search_outcome = flipping.rho_map.peak_search(search_parameters)
peak_structure = emma.model(
target_structure_in_p1.crystal_symmetry().special_position_settings(),
positions=[emma.position("Q%i" % i, x) for i, x in enumerate(peak_search_outcome.all().sites())],
)
refined_matches = emma.model_matches(
target_structure_in_p1.as_emma_model(), peak_structure, tolerance=0.5, break_if_match_with_no_singles=False
).refined_matches
m = refined_matches[0]
assert m.rms < 0.2, m.rms # no farther than that
assert m.rt.r in (mat.identity(3), mat.inversion(3))
reference_shift = -refined_matches[0].rt.t
# Find the translation to bring back the structure to the same space-group
# setting as the starting f_obs from correlation map analysis
is_allowed = lambda x: f_target.space_group_info().is_allowed_origin_shift(x, tolerance=0.1)
first_correct_correlation_peak = None
for i, (f_calc, shift, cc_peak_height) in enumerate(solving.f_calc_solutions):
if is_allowed(shift - reference_shift) or is_allowed(shift + reference_shift):
first_correct_correlation_peak = i
break
else:
if verbose == "more":
print "++ Incorrect peak: shift=(%.3f, %.3f, %.3f), height=%.2f" % (tuple(shift) + (cc_peak_height,))
print " Reference shift=(%.3f, %.3f, %.3f)" % tuple(reference_shift)
assert first_correct_correlation_peak is not None
if verbose and first_correct_correlation_peak != 0:
print "** First correct correlation peak: #%i (%.3f) **" % (first_correct_correlation_peak, cc_peak_height)
# check Euclidean matching in the original space-group
search_parameters = maptbx.peak_search_parameters(
interpolate=True, min_distance_sym_equiv=1.0, max_clusters=int(1.5 * target_structure.scatterers().size())
)
solution_fft_map = f_calc.fft_map(symmetry_flags=maptbx.use_space_group_symmetry)
solution_peaks = solution_fft_map.peak_search(search_parameters, verify_symmetry=False)
solution_peak_structure = emma.model(
target_structure.crystal_symmetry().special_position_settings(),
positions=[emma.position("Q%i" % i, x) for i, x in enumerate(solution_peaks.all().sites())],
)
refined_matches = emma.model_matches(
target_structure.as_emma_model(), solution_peak_structure, break_if_match_with_no_singles=False
).refined_matches
assert refined_matches
m = refined_matches[0]
assert not m.singles1, m.show() # all sites match a peak
assert m.rms < 0.15, m.rms # no farther than that
assert m.rt.r in (mat.identity(3), mat.inversion(3))
# success!
if verbose:
print "@@ Success @@"
def run():
import sys
reflection_file_name = sys.argv[1]
import iotbx.cif
miller_arrays = iotbx.cif.reader(
file_path=reflection_file_name).as_miller_arrays()
for miller_array in miller_arrays:
s = str(miller_array.info())
if '_meas' in s:
if miller_array.is_xray_intensity_array():
break
elif miller_array.is_xray_amplitude_array():
break
if not ('_meas' in str(miller_array.info())
and (miller_array.is_xray_amplitude_array()
or miller_array.is_xray_intensity_array())):
print "Sorry: CIF does not contain an appropriate miller array"
return
miller_array.show_comprehensive_summary()
print
if (miller_array.is_xray_intensity_array()):
print "Converting intensities to amplitudes."
miller_array = miller_array.as_amplitude_array()
print
miller_array.setup_binner(auto_binning=True)
miller_array.binner().show_summary()
print
all_e_values = miller_array.quasi_normalize_structure_factors().sort(
by_value="data")
large_e_values = all_e_values.select(all_e_values.data() > 1.2)
print "number of large_e_values:", large_e_values.size()
print
from cctbx import dmtbx
triplets = dmtbx.triplet_generator(large_e_values)
from cctbx.array_family import flex
print "triplets per reflection: min,max,mean: %d, %d, %.2f" % (
flex.min(triplets.n_relations()),
flex.max(triplets.n_relations()),
flex.mean(triplets.n_relations().as_double()))
print "total number of triplets:", flex.sum(triplets.n_relations())
print
input_phases = large_e_values \
.random_phases_compatible_with_phase_restrictions()
tangent_formula_phases = input_phases.data()
for i in xrange(10):
tangent_formula_phases = triplets.apply_tangent_formula(
amplitudes=large_e_values.data(),
phases_rad=tangent_formula_phases,
selection_fixed=None,
use_fixed_only=False,
reuse_results=True)
e_map_coeff = large_e_values.phase_transfer(
phase_source=tangent_formula_phases)
from cctbx import maptbx
e_map = e_map_coeff.fft_map(
symmetry_flags=maptbx.use_space_group_symmetry)
e_map.apply_sigma_scaling()
e_map.statistics().show_summary(prefix="e_map ")
print
peak_search = e_map.peak_search(parameters=maptbx.peak_search_parameters(
min_distance_sym_equiv=1.2))
peaks = peak_search.all(max_clusters=10)
print "e_map peak list"
print " fractional coordinates peak height"
for site,height in zip(peaks.sites(), peaks.heights()):
print " (%9.6f, %9.6f, %9.6f)" % site, "%10.3f" % height
print
if (len(sys.argv) > 2):
coordinate_file_name = sys.argv[2]
xray_structure = iotbx.cif.reader(
file_path=coordinate_file_name).build_crystal_structures(
data_block_name="I")
xray_structure.show_summary().show_scatterers()
print
f_calc = abs(miller_array.structure_factors_from_scatterers(
xray_structure=xray_structure,
algorithm="direct").f_calc())
correlation = flex.linear_correlation(f_calc.data(), miller_array.data())
assert correlation.is_well_defined()
print "correlation of f_obs and f_calc: %.4f" % correlation.coefficient()
print
reference_model = xray_structure.as_emma_model()
assert reference_model.unit_cell().is_similar_to(e_map.unit_cell())
assert reference_model.space_group() == e_map.space_group()
from cctbx import euclidean_model_matching as emma
peak_model = emma.model(special_position_settings=reference_model)
for i,site in enumerate(peaks.sites()):
peak_model.add_position(emma.position(label="peak%02d" % i, site=site))
matches = emma.model_matches(
model1=reference_model,
model2=peak_model,
tolerance=1.,
models_are_diffraction_index_equivalent=True)
for match in matches.refined_matches:
match.show()
def exercise_one_structure(
target_structure,
flipping_type,
anomalous_flag,
d_min,
grid_resolution_factor=1. / 2,
verbose=False,
amplitude_type="F",
):
assert amplitude_type in ('F', 'E', 'quasi-E')
# Generate its structure factors
f_target = miller.build_set(
crystal_symmetry=target_structure,
anomalous_flag=target_structure.scatterers().count_anomalous() != 0,
d_min=d_min).structure_factors_from_scatterers(
xray_structure=target_structure, algorithm="direct").f_calc()
f_target_in_p1 = f_target.expand_to_p1()\
.as_non_anomalous_array()\
.merge_equivalents().array()
f_obs = f_target.as_amplitude_array()
# Unleash charge flipping on the amplitudes
flipping = flipping_type(delta=None)
extra = group_args()
if amplitude_type == 'E':
extra.normalisations_for = lambda f: f.amplitude_normalisations(
target_structure.unit_cell_content(omit=('H', 'D')))
elif amplitude_type == 'quasi-E':
extra.normalisations_for = charge_flipping.amplitude_quasi_normalisations
solving = charge_flipping.solving_iterator(
flipping,
f_obs,
yield_during_delta_guessing=True,
yield_solving_interval=1,
**extra.__dict__)
s = StringIO()
charge_flipping.loop(solving, verbose="highly", out=s)
if verbose:
print s.getvalue()
# check whether a phase transition has occured
assert solving.had_phase_transition
flipping = solving.flipping_iterator
f_result_in_p1 = solving.flipping_iterator.f_calc
# Euclidean matching of the peaks from the obtained map
# against those of the correct structure (in P1)
target_structure = target_structure.select(
target_structure.scattering_types() == "H", negate=True)
target_structure_in_p1 = target_structure.expand_to_p1()
search_parameters = maptbx.peak_search_parameters(
interpolate=True,
min_distance_sym_equiv=1.,
max_clusters=int(target_structure_in_p1.scatterers().size() * 1.2))
peak_search_outcome = flipping.rho_map.peak_search(search_parameters)
peak_structure = emma.model(
target_structure_in_p1.crystal_symmetry().special_position_settings(),
positions=[
emma.position('Q%i' % i, x)
for i, x in enumerate(peak_search_outcome.all().sites())
])
refined_matches = emma.model_matches(
target_structure_in_p1.as_emma_model(),
peak_structure,
tolerance=0.5,
break_if_match_with_no_singles=False).refined_matches
m = refined_matches[0]
assert m.rms < 0.2, m.rms # no farther than that
assert m.rt.r in (mat.identity(3), mat.inversion(3))
reference_shift = -refined_matches[0].rt.t
# Find the translation to bring back the structure to the same space-group
# setting as the starting f_obs from correlation map analysis
is_allowed = lambda x: f_target.space_group_info().is_allowed_origin_shift(
x, tolerance=0.1)
first_correct_correlation_peak = None
for i, (f_calc, shift,
cc_peak_height) in enumerate(solving.f_calc_solutions):
if (is_allowed(shift - reference_shift)
or is_allowed(shift + reference_shift)):
first_correct_correlation_peak = i
break
else:
if verbose == "more":
print "++ Incorrect peak: shift=(%.3f, %.3f, %.3f), height=%.2f"\
% (tuple(shift)+(cc_peak_height,))
print " Reference shift=(%.3f, %.3f, %.3f)" % tuple(
reference_shift)
assert first_correct_correlation_peak is not None
if verbose and first_correct_correlation_peak != 0:
print "** First correct correlation peak: #%i (%.3f) **"\
% (first_correct_correlation_peak, cc_peak_height)
# check Euclidean matching in the original space-group
search_parameters = maptbx.peak_search_parameters(
interpolate=True,
min_distance_sym_equiv=1.,
max_clusters=int(1.5 * target_structure.scatterers().size()))
solution_fft_map = f_calc.fft_map(
symmetry_flags=maptbx.use_space_group_symmetry)
solution_peaks = solution_fft_map.peak_search(search_parameters,
verify_symmetry=False)
solution_peak_structure = emma.model(
target_structure.crystal_symmetry().special_position_settings(),
positions=[
emma.position('Q%i' % i, x)
for i, x in enumerate(solution_peaks.all().sites())
])
refined_matches = emma.model_matches(
target_structure.as_emma_model(),
solution_peak_structure,
break_if_match_with_no_singles=False).refined_matches
assert refined_matches
m = refined_matches[0]
assert not m.singles1, m.show() # all sites match a peak
assert m.rms < 0.15, m.rms # no farther than that
assert m.rt.r in (mat.identity(3), mat.inversion(3))
# success!
if verbose:
print "@@ Success @@"
def run():
import sys
reflection_file_name = sys.argv[1]
import iotbx.cif
miller_arrays = iotbx.cif.reader(
file_path=reflection_file_name).as_miller_arrays()
for miller_array in miller_arrays:
s = str(miller_array.info())
if '_meas' in s:
if miller_array.is_xray_intensity_array():
break
elif miller_array.is_xray_amplitude_array():
break
if not ('_meas' in str(miller_array.info()) and
(miller_array.is_xray_amplitude_array()
or miller_array.is_xray_intensity_array())):
print "Sorry: CIF does not contain an appropriate miller array"
return
miller_array.show_comprehensive_summary()
print
if (miller_array.is_xray_intensity_array()):
print "Converting intensities to amplitudes."
miller_array = miller_array.as_amplitude_array()
print
miller_array.setup_binner(auto_binning=True)
miller_array.binner().show_summary()
print
all_e_values = miller_array.quasi_normalize_structure_factors().sort(
by_value="data")
large_e_values = all_e_values.select(all_e_values.data() > 1.2)
print "number of large_e_values:", large_e_values.size()
print
from cctbx import dmtbx
triplets = dmtbx.triplet_generator(large_e_values)
from cctbx.array_family import flex
print "triplets per reflection: min,max,mean: %d, %d, %.2f" % (
flex.min(triplets.n_relations()), flex.max(triplets.n_relations()),
flex.mean(triplets.n_relations().as_double()))
print "total number of triplets:", flex.sum(triplets.n_relations())
print
input_phases = large_e_values \
.random_phases_compatible_with_phase_restrictions()
tangent_formula_phases = input_phases.data()
for i in xrange(10):
tangent_formula_phases = triplets.apply_tangent_formula(
amplitudes=large_e_values.data(),
phases_rad=tangent_formula_phases,
selection_fixed=None,
use_fixed_only=False,
reuse_results=True)
e_map_coeff = large_e_values.phase_transfer(
phase_source=tangent_formula_phases)
from cctbx import maptbx
e_map = e_map_coeff.fft_map(symmetry_flags=maptbx.use_space_group_symmetry)
e_map.apply_sigma_scaling()
e_map.statistics().show_summary(prefix="e_map ")
print
peak_search = e_map.peak_search(parameters=maptbx.peak_search_parameters(
min_distance_sym_equiv=1.2))
peaks = peak_search.all(max_clusters=10)
print "e_map peak list"
print " fractional coordinates peak height"
for site, height in zip(peaks.sites(), peaks.heights()):
print " (%9.6f, %9.6f, %9.6f)" % site, "%10.3f" % height
print
if (len(sys.argv) > 2):
coordinate_file_name = sys.argv[2]
xray_structure = iotbx.cif.reader(
file_path=coordinate_file_name).build_crystal_structures(
data_block_name="I")
xray_structure.show_summary().show_scatterers()
print
f_calc = abs(
miller_array.structure_factors_from_scatterers(
xray_structure=xray_structure, algorithm="direct").f_calc())
correlation = flex.linear_correlation(f_calc.data(),
miller_array.data())
assert correlation.is_well_defined()
print "correlation of f_obs and f_calc: %.4f" % correlation.coefficient(
)
print
reference_model = xray_structure.as_emma_model()
assert reference_model.unit_cell().is_similar_to(e_map.unit_cell())
assert reference_model.space_group() == e_map.space_group()
from cctbx import euclidean_model_matching as emma
peak_model = emma.model(special_position_settings=reference_model)
for i, site in enumerate(peaks.sites()):
peak_model.add_position(
emma.position(label="peak%02d" % i, site=site))
matches = emma.model_matches(
model1=reference_model,
model2=peak_model,
tolerance=1.,
models_are_diffraction_index_equivalent=True)
for match in matches.refined_matches:
match.show()