def _polishing(self):
while True:
if 0: # Display map
from crys3d.qttbx import map_viewer
map_viewer.display(
fft_map=self.flipping_iterator.f_calc.fft_map(),
iso_level_positive_range_fraction=0.4)
if self.normalisations:
# if we have been working on normalised amplitudes
# (i.e. in practice E's or quasi-E's, it is better to go back to
# F's before polishing.
# According to [6], a few cycles of charge flipping on those F's
# before polishing improves map quality.
self.flipping_iterator.denormalise(self.normalisations)
skewness = flex.double()
for i in xrange(
self.extra_iterations_on_f_after_phase_transition):
next(self.flipping_iterator)
skewness.append(self.flipping_iterator.rho_map.skewness())
if i < 3: continue
stats = scitbx.math.median_statistics(skewness[-3:])
if (stats.median_absolute_deviation <
self.map_skewness_stability_threshold):
break
low_density_elimination = low_density_elimination_iterator(
constant_rho_c=self.flipping_iterator.delta)
low_density_elimination.start(f_obs=self.flipping_iterator.f_obs,
phases=self.flipping_iterator.f_calc,
f_000=0)
for i in xrange(self.polishing_iterations):
next(low_density_elimination)
yield self.evaluating
def _polishing(self):
while 1:
if 0: # Display map
from crys3d.qttbx import map_viewer
map_viewer.display(fft_map=self.flipping_iterator.f_calc.fft_map(),
iso_level_positive_range_fraction=0.4)
if self.normalisations:
# if we have been working on normalised amplitudes
# (i.e. in practice E's or quasi-E's, it is better to go back to
# F's before polishing.
# According to [6], a few cycles of charge flipping on those F's
# before polishing improves map quality.
self.flipping_iterator.denormalise(self.normalisations)
skewness = flex.double()
for i in xrange(self.extra_iterations_on_f_after_phase_transition):
self.flipping_iterator.next()
skewness.append(self.flipping_iterator.rho_map.skewness())
if i < 3: continue
stats = scitbx.math.median_statistics(skewness[-3:])
if (stats.median_absolute_deviation
< self.map_skewness_stability_threshold): break
low_density_elimination = low_density_elimination_iterator(
constant_rho_c=self.flipping_iterator.delta)
low_density_elimination.start(f_obs=self.flipping_iterator.f_obs,
phases=self.flipping_iterator.f_calc,
f_000=0)
for i in xrange(self.polishing_iterations):
low_density_elimination.next()
yield self.evaluating
def f_calc_symmetrisations(f_obs, f_calc_in_p1, min_cc_peak_height):
# The fast correlation map as per cctbx.translation_search.fast_nv1995
# is computed and its peaks studied.
# Inspiration from phenix.substructure.hyss for the parameters tuning.
if 0: # Display f_calc_in_p1
from crys3d.qttbx import map_viewer
map_viewer.display(window_title="f_calc in P1 before fast CC",
fft_map=f_calc_in_p1.fft_map(),
iso_level_positive_range_fraction=0.8)
crystal_gridding = f_obs.crystal_gridding(
symmetry_flags=translation_search.symmetry_flags(
is_isotropic_search_model=False,
have_f_part=False),
resolution_factor=1/3
)
correlation_map = translation_search.fast_nv1995(
gridding=crystal_gridding.n_real(),
space_group=f_obs.space_group(),
anomalous_flag=f_obs.anomalous_flag(),
miller_indices_f_obs=f_obs.indices(),
f_obs=f_obs.data(),
f_part=flex.complex_double(), ## no sub-structure is already fixed
miller_indices_p1_f_calc=f_calc_in_p1.indices(),
p1_f_calc=f_calc_in_p1.data()).target_map()
if 0: # Display correlation_map
from crys3d.qttbx import map_viewer
map_viewer.display(window_title="Fast CC map",
raw_map=correlation_map,
unit_cell=f_calc_in_p1.unit_cell(),
positive_iso_level=0.8)
search_parameters = maptbx.peak_search_parameters(
peak_search_level=1,
peak_cutoff=0.5,
interpolate=True,
min_distance_sym_equiv=1e-6,
general_positions_only=False,
min_cross_distance=f_obs.d_min()/2)
## The correlation map is not a miller.fft_map, just a 3D flex.double
correlation_map_peaks = crystal_gridding.tags().peak_search(
map=correlation_map,
parameters=search_parameters)
# iterate over the strong peak; for each, shift and symmetrised f_calc
for peak in correlation_map_peaks:
if peak.height < min_cc_peak_height: break
sr = symmetry_search.shift_refinement(
f_obs, f_calc_in_p1, peak.site)
yield sr.symmetrised_shifted_sf.f_x, sr.shift, sr.goos.correlation
def f_calc_symmetrisations(f_obs, f_calc_in_p1, min_cc_peak_height):
# The fast correlation map as per cctbx.translation_search.fast_nv1995
# is computed and its peaks studied.
# Inspiration from phenix.substructure.hyss for the parameters tuning.
if 0: # Display f_calc_in_p1
from crys3d.qttbx import map_viewer
map_viewer.display(window_title="f_calc in P1 before fast CC",
fft_map=f_calc_in_p1.fft_map(),
iso_level_positive_range_fraction=0.8)
crystal_gridding = f_obs.crystal_gridding(
symmetry_flags=translation_search.symmetry_flags(
is_isotropic_search_model=False, have_f_part=False),
resolution_factor=1 / 3)
correlation_map = translation_search.fast_nv1995(
gridding=crystal_gridding.n_real(),
space_group=f_obs.space_group(),
anomalous_flag=f_obs.anomalous_flag(),
miller_indices_f_obs=f_obs.indices(),
f_obs=f_obs.data(),
f_part=flex.complex_double(), ## no sub-structure is already fixed
miller_indices_p1_f_calc=f_calc_in_p1.indices(),
p1_f_calc=f_calc_in_p1.data()).target_map()
if 0: # Display correlation_map
from crys3d.qttbx import map_viewer
map_viewer.display(window_title="Fast CC map",
raw_map=correlation_map,
unit_cell=f_calc_in_p1.unit_cell(),
positive_iso_level=0.8)
search_parameters = maptbx.peak_search_parameters(
peak_search_level=1,
peak_cutoff=0.5,
interpolate=True,
min_distance_sym_equiv=1e-6,
general_positions_only=False,
min_cross_distance=f_obs.d_min() / 2)
## The correlation map is not a miller.fft_map, just a 3D flex.double
correlation_map_peaks = crystal_gridding.tags().peak_search(
map=correlation_map, parameters=search_parameters)
# iterate over the strong peak; for each, shift and symmetrised f_calc
for peak in correlation_map_peaks:
if peak.height < min_cc_peak_height: break
sr = symmetry_search.shift_refinement(f_obs, f_calc_in_p1, peak.site)
yield sr.symmetrised_shifted_sf.f_x, sr.shift, sr.goos.correlation
def cross_correlation_peaks(self):
f0 = self.f_in_p1
for op in self.possible_point_group_generators():
f, op_times_f = f0.common_sets(f0.change_basis(
sgtbx.change_of_basis_op(op)),
assert_is_similar_symmetry=False)
#assert f.size() == f0.size()
#XXX a better sanity check is needed here to check the amount of overlap
#XXX between transformed indices
cc_sf = f * op_times_f.conjugate().data() / f.sum_sq()
cc_map = cc_sf.fft_map(
symmetry_flags=maptbx.use_space_group_symmetry,
resolution_factor=self.grid_resolution_factor)
if 0: # display 3D map
from crys3d.qttbx import map_viewer
map_viewer.display(window_title=op.as_xyz(),
fft_map=cc_map,
iso_level_positive_range_fraction=0.8,
wires=True,
orthographic=True)
cc_map_peaks = cc_map.peak_search(self.search_parameters)
peak = cc_map_peaks.next()
yield (op.r(), mat.col(peak.site))
def cross_correlation_peaks(self):
f0 = self.f_in_p1
for op in self.possible_point_group_generators():
f, op_times_f = f0.common_sets(
f0.change_basis(sgtbx.change_of_basis_op(op)),
assert_is_similar_symmetry=False)
#assert f.size() == f0.size()
#XXX a better sanity check is needed here to check the amount of overlap
#XXX between transformed indices
cc_sf = f * op_times_f.conjugate().data() / f.sum_sq()
cc_map = cc_sf.fft_map(
symmetry_flags=maptbx.use_space_group_symmetry,
resolution_factor=self.grid_resolution_factor)
if 0: # display 3D map
from crys3d.qttbx import map_viewer
map_viewer.display(window_title=op.as_xyz(),
fft_map = cc_map,
iso_level_positive_range_fraction=0.8,
wires=True,
orthographic=True)
cc_map_peaks = cc_map.peak_search(self.search_parameters)
peak = cc_map_peaks.next()
yield (op.r(), mat.col(peak.site))