def exercise_value(f_c_in_p1, f_o, flags, n_sampled):
""" where we check against the trusted correlation map implemented
in cctbx.translation_search """
crystal_gridding = f_o.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_o.space_group(),
anomalous_flag=f_o.anomalous_flag(),
miller_indices_f_obs=f_o.indices(),
f_obs=f_o.data(),
f_part=flex.complex_double(), ## no sub-structure is already fixed
miller_indices_p1_f_calc=f_c_in_p1.indices(),
p1_f_calc=f_c_in_p1.data()).target_map()
nx, ny, nz = n = crystal_gridding.n_real()
def sampled_indices():
from random import randrange
yield (0,0,0)
for i in xrange(n_sampled - 1):
yield randrange(0, n[0]), randrange(0, n[1]), randrange(0, n[2])
f_o_sq = f_o.as_intensity_array()
for i,j,k in sampled_indices():
x = (i/nx, j/ny, k/nz)
if random.random() > 0.5: f_o_or_f_o_sq = f_o
else: f_o_or_f_o_sq = f_o_sq
gos = symmetrised_shifted_structure_factors(
f_o_or_f_o_sq, f_c_in_p1, x).misfit(f_o_or_f_o_sq)
assert approx_equal(gos.correlation, correlation_map[i,j,k]), (i,j,k)
def exercise_value(f_c_in_p1, f_o, flags, n_sampled):
""" where we check against the trusted correlation map implemented
in cctbx.translation_search """
crystal_gridding = f_o.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_o.space_group(),
anomalous_flag=f_o.anomalous_flag(),
miller_indices_f_obs=f_o.indices(),
f_obs=f_o.data(),
f_part=flex.complex_double(), ## no sub-structure is already fixed
miller_indices_p1_f_calc=f_c_in_p1.indices(),
p1_f_calc=f_c_in_p1.data()).target_map()
nx, ny, nz = n = crystal_gridding.n_real()
def sampled_indices():
from random import randrange
yield (0, 0, 0)
for i in xrange(n_sampled - 1):
yield randrange(0, n[0]), randrange(0, n[1]), randrange(0, n[2])
f_o_sq = f_o.as_intensity_array()
for i, j, k in sampled_indices():
x = (i / nx, j / ny, k / nz)
if random.random() > 0.5: f_o_or_f_o_sq = f_o
else: f_o_or_f_o_sq = f_o_sq
gos = symmetrised_shifted_structure_factors(f_o_or_f_o_sq, f_c_in_p1,
x).misfit(f_o_or_f_o_sq)
assert approx_equal(gos.correlation, correlation_map[i, j,
k]), (i, j, k)
def run_fast_nv1995(f_obs, f_calc_fixed, f_calc_p1,
symmetry_flags, gridding, grid_tags, verbose):
if (f_calc_fixed is None):
f_part = flex.complex_double()
else:
f_part = f_calc_fixed.data()
assert f_obs.anomalous_flag() == f_calc_p1.anomalous_flag()
fast_nv1995 = translation_search.fast_nv1995(
gridding=gridding,
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=f_part,
miller_indices_p1_f_calc=f_calc_p1.indices(),
p1_f_calc=f_calc_p1.data())
assert fast_nv1995.target_map().all() == gridding
map_stats = maptbx.statistics(fast_nv1995.target_map())
if (0 or verbose):
map_stats.show_summary()
grid_tags.build(f_obs.space_group_info().type(), symmetry_flags)
assert grid_tags.n_grid_misses() == 0
assert grid_tags.verify(fast_nv1995.target_map())
peak_list = maptbx.peak_list(
data=fast_nv1995.target_map(),
tags=grid_tags.tag_array(),
peak_search_level=1,
max_peaks=10,
interpolate=True)
if (0 or verbose):
print "gridding:", gridding
for i,site in enumerate(peak_list.sites()):
print "(%.4f,%.4f,%.4f)" % site, "%.6g" % peak_list.heights()[i]
assert approx_equal(map_stats.max(), flex.max(peak_list.grid_heights()))
return peak_list
def run():
target_structure = random_structure.xray_structure(
space_group_info=sgtbx.space_group_info("I432"),
elements=['C']*6+['O'],
use_u_iso=False,
use_u_aniso=True,
)
shift = tuple(flex.random_double(3))
print "shift to be found: (%.3f, %.3f, %.3f)" % shift
target_structure_in_p1 = target_structure.expand_to_p1().apply_shift(shift)
miller_indices = miller.build_set(
crystal_symmetry=target_structure,
anomalous_flag=True,
d_min=0.8)
f_obs = miller_indices.structure_factors_from_scatterers(
xray_structure=target_structure,
algorithm="direct").f_calc().amplitudes()
miller_indices_in_p1 = miller.build_set(
crystal_symmetry=target_structure_in_p1,
anomalous_flag=True,
d_min=0.8)
f_calc = miller_indices_in_p1.structure_factors_from_scatterers(
xray_structure=target_structure_in_p1,
algorithm="direct").f_calc()
crystal_gridding = f_calc.crystal_gridding(
symmetry_flags=translation_search.symmetry_flags(
is_isotropic_search_model=False,
have_f_part=False),
resolution_factor=1/2
)
omptbx.env.num_threads = 1
t_fast_tf = show_times()
fast_tf_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.indices(),
p1_f_calc=f_calc.data()).target_map()
print
print "Fast translation function"
t_fast_tf()
t_cross_corr = show_times()
for op in target_structure.space_group():
f, op_times_f = f_calc.original_and_transformed(op)
cross_corr_map = miller.fft_map(crystal_gridding,
f * op_times_f.conjugate().data())
print
print "Traditional cross-correlation"
t_cross_corr()
def exercise_fast_nv1995():
space_group = sgtbx.space_group_info("P 21 21 21").group()
miller_indices_f_obs = flex.miller_index(((3, 4, 5), (4, 5, 6)))
f = translation_search.fast_nv1995(
gridding=(20, 20, 36),
space_group=space_group,
anomalous_flag=False,
miller_indices_f_obs=miller_indices_f_obs,
f_obs=flex.double((1, 2)),
f_part=flex.complex_double(),
miller_indices_p1_f_calc=flex.miller_index(((1, 2, 3), )),
p1_f_calc=flex.complex_double((12, )))
assert f.target_map().all() == (20, 20, 36)
def exercise_fast_nv1995():
space_group = sgtbx.space_group_info("P 21 21 21").group()
miller_indices_f_obs = flex.miller_index(((3,4,5),(4,5,6)))
f = translation_search.fast_nv1995(
gridding=(20,20,36),
space_group=space_group,
anomalous_flag=False,
miller_indices_f_obs=miller_indices_f_obs,
f_obs=flex.double((1,2)),
f_part=flex.complex_double(),
miller_indices_p1_f_calc=flex.miller_index(((1,2,3),)),
p1_f_calc=flex.complex_double((12,)))
assert f.target_map().all() == (20,20,36)
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 run():
target_structure = random_structure.xray_structure(
space_group_info=sgtbx.space_group_info("I432"),
elements=['C'] * 6 + ['O'],
use_u_iso=False,
use_u_aniso=True,
)
shift = tuple(flex.random_double(3))
print "shift to be found: (%.3f, %.3f, %.3f)" % shift
target_structure_in_p1 = target_structure.expand_to_p1().apply_shift(shift)
miller_indices = miller.build_set(crystal_symmetry=target_structure,
anomalous_flag=True,
d_min=0.8)
f_obs = miller_indices.structure_factors_from_scatterers(
xray_structure=target_structure,
algorithm="direct").f_calc().amplitudes()
miller_indices_in_p1 = miller.build_set(
crystal_symmetry=target_structure_in_p1,
anomalous_flag=True,
d_min=0.8)
f_calc = miller_indices_in_p1.structure_factors_from_scatterers(
xray_structure=target_structure_in_p1, algorithm="direct").f_calc()
crystal_gridding = f_calc.crystal_gridding(
symmetry_flags=translation_search.symmetry_flags(
is_isotropic_search_model=False, have_f_part=False),
resolution_factor=1 / 2)
omptbx.env.num_threads = 1
t_fast_tf = show_times()
fast_tf_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.indices(),
p1_f_calc=f_calc.data()).target_map()
print
print "Fast translation function"
t_fast_tf()
t_cross_corr = show_times()
for op in target_structure.space_group():
f, op_times_f = f_calc.original_and_transformed(op)
cross_corr_map = miller.fft_map(crystal_gridding,
f * op_times_f.conjugate().data())
print
print "Traditional cross-correlation"
t_cross_corr()
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