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 calculate_exp_i_two_phi_peaks(xray_structure, d_min,
min_peak_distance,
max_reduced_peaks):
f_h = xray_structure.structure_factors(
anomalous_flag=False,
d_min=d_min).f_calc()
two_i_phi_h = miller.array(
miller_set=f_h,
data=flex.polar(1, flex.arg(f_h.data())*2))
fft_map = two_i_phi_h.fft_map(
d_min=d_min,
symmetry_flags=maptbx.use_space_group_symmetry)
real_map = fft_map.real_map()
real_map = maptbx.copy(real_map, flex.grid(real_map.focus()))
stats = maptbx.statistics(real_map)
if (stats.max() != 0):
real_map /= abs(stats.max())
grid_tags = maptbx.grid_tags(real_map.focus())
grid_tags.build(fft_map.space_group_info().type(), fft_map.symmetry_flags())
grid_tags.verify(real_map)
peak_list = maptbx.peak_list(
data=real_map,
tags=grid_tags.tag_array(),
max_peaks=10*max_reduced_peaks,
interpolate=True)
reduced_peaks = peak_cluster_reduction(
crystal_symmetry=xray_structure,
peak_list=peak_list,
min_peak_distance=min_peak_distance,
max_reduced_peaks=max_reduced_peaks)
return reduced_peaks
def exercise_peak_search():
t = flex.long(flex.grid((3,4,5)))
for flex_type in flex_types():
d = flex_type(flex.grid((3,4,5)))
l = maptbx.peak_list(d, t, peak_search_level=0, interpolate=False)
assert l.gridding() == d.focus()
assert l.grid_indices(0) == (0,0,0)
assert list(l.grid_heights()) == [0]
assert list(l.sites()) == [(0,0,0)]
assert list(l.heights()) == [0]
l = maptbx.peak_list(
d, t, peak_search_level=0,peak_cutoff=-1, interpolate=False)
assert l.gridding() == d.focus()
assert l.grid_indices(0) == (0,0,0)
assert list(l.grid_heights()) == [0]
assert list(l.sites()) == [(0,0,0)]
assert list(l.heights()) == [0]
def run_test(space_group_info, n_elements=5, d_min=1.5,
grid_resolution_factor=1./3, max_prime=5, verbose=0):
structure = random_structure.xray_structure(
space_group_info,
elements=["Si"]*n_elements,
volume_per_atom=200,
min_distance=3.,
general_positions_only=False)
miller_set_f_obs = miller.build_set(
crystal_symmetry=structure,
anomalous_flag=(random.random()>0.5),
d_min=d_min)
f_obs = miller_set_f_obs.structure_factors_from_scatterers(
xray_structure=structure,
algorithm="direct").f_calc()
structure_factor_utils.check_phase_restrictions(f_obs, verbose=verbose)
if (0 or verbose):
f_obs.show_summary()
if (0 or verbose):
f_obs.show_array()
fft_map = f_obs.fft_map(
resolution_factor=grid_resolution_factor,
symmetry_flags=maptbx.use_space_group_symmetry)
p = pickle.dumps(fft_map)
l = pickle.loads(p)
s1 = StringIO()
fft_map.statistics().show_summary(f=s1)
s2 = StringIO()
l.statistics().show_summary(f=s2)
assert not show_diff(s2.getvalue(), s1.getvalue())
#
if (not f_obs.anomalous_flag()):
maptbx_fft_map = maptbx.fft_to_real_map_unpadded(
space_group=fft_map.space_group(),
n_real=fft_map.n_real(),
miller_indices=f_obs.indices(),
data=f_obs.data())
fft_map_unpadded = fft_map.real_map_unpadded(in_place=False)
assert approx_equal(
flex.linear_correlation(
fft_map_unpadded.as_1d(), maptbx_fft_map.as_1d()).coefficient(), 1)
assert approx_equal(
flex.max(flex.abs(maptbx_fft_map - fft_map_unpadded)), 0)
#
fft_map.apply_sigma_scaling()
real_map = maptbx.copy(
fft_map.real_map(),
flex.grid(fft_map.real_map().focus()))
grid_tags = maptbx.grid_tags(real_map.focus())
grid_tags.build(
fft_map.space_group_info().type(),
fft_map.symmetry_flags())
assert grid_tags.n_grid_misses() == 0
assert grid_tags.verify(real_map)
rms = []
for interpolate in (False,True):
peak_list = maptbx.peak_list(
data=real_map,
tags=grid_tags.tag_array(),
peak_search_level=1,
max_peaks=2*n_elements,
interpolate=interpolate)
assert peak_list.gridding() == real_map.focus()
check_peaks(structure, peak_list.sites(), d_min * grid_resolution_factor)
crystal_gridding_tags = fft_map.tags()
cluster_analysis = maptbx.peak_cluster_analysis(
peak_list=peak_list,
special_position_settings=structure,
general_positions_only=False,
effective_resolution=d_min,
min_cross_distance=2,
max_clusters=n_elements).all()
check_peaks(
structure,
cluster_analysis.sites(),
cluster_analysis.min_cross_distance() + d_min * grid_resolution_factor)
structure_from_peaks = xray.structure(structure)
for site in cluster_analysis.sites():
structure_from_peaks.add_scatterer(
xray.scatterer(label="site", scattering_type="", site=site))
emma_matches = emma.model_matches(
structure.as_emma_model(),
structure_from_peaks.as_emma_model(),
tolerance=d_min*2)
rms.append(emma_matches.refined_matches[0].rms)
assert len(emma_matches.refined_matches[0].pairs) == n_elements
# exercise interpolation vs. summation
map_coeffs = f_obs.expand_to_p1()
fft_map = f_obs.fft_map(
resolution_factor=grid_resolution_factor,
symmetry_flags=maptbx.use_space_group_symmetry)
fft_map.apply_volume_scaling()
real_map = fft_map.real_map_unpadded()
sum1 = sum2 = 0
for scatterer in structure.scatterers() :
v1 = real_map.eight_point_interpolation(scatterer.site)
v2 = real_map.tricubic_interpolation(scatterer.site)
v3 = map_coeffs.direct_summation_at_point(scatterer.site)
sum1 += abs(v1 - v3.real)
sum2 += abs(v2 - v3.real)
mean_delta_linear = sum1 / n_elements
mean_delta_cubic = sum2 / n_elements
assert (mean_delta_cubic < mean_delta_linear)
if (0 or verbose):
print "emma rms grid, interpolated: %.2f %.2f" % tuple(rms)
assert rms[0] >= rms[1]
map_1 = fft_map.real_map_unpadded(in_place=False)
map_2 = fft_map.real_map_unpadded(in_place=True)
assert (map_1.all_eq(map_2))
def run_test(space_group_info,
n_elements=5,
d_min=1.5,
grid_resolution_factor=1. / 3,
max_prime=5,
verbose=0):
structure = random_structure.xray_structure(space_group_info,
elements=["Si"] * n_elements,
volume_per_atom=200,
min_distance=3.,
general_positions_only=False)
miller_set_f_obs = miller.build_set(crystal_symmetry=structure,
anomalous_flag=(random.random() > 0.5),
d_min=d_min)
f_obs = miller_set_f_obs.structure_factors_from_scatterers(
xray_structure=structure, algorithm="direct").f_calc()
structure_factor_utils.check_phase_restrictions(f_obs, verbose=verbose)
if (0 or verbose):
f_obs.show_summary()
if (0 or verbose):
f_obs.show_array()
fft_map = f_obs.fft_map(resolution_factor=grid_resolution_factor,
symmetry_flags=maptbx.use_space_group_symmetry)
p = pickle.dumps(fft_map)
l = pickle.loads(p)
s1 = StringIO()
fft_map.statistics().show_summary(f=s1)
s2 = StringIO()
l.statistics().show_summary(f=s2)
assert not show_diff(s2.getvalue(), s1.getvalue())
#
if (not f_obs.anomalous_flag()):
maptbx_fft_map = maptbx.fft_to_real_map_unpadded(
space_group=fft_map.space_group(),
n_real=fft_map.n_real(),
miller_indices=f_obs.indices(),
data=f_obs.data())
fft_map_unpadded = fft_map.real_map_unpadded(in_place=False)
assert approx_equal(
flex.linear_correlation(fft_map_unpadded.as_1d(),
maptbx_fft_map.as_1d()).coefficient(), 1)
assert approx_equal(
flex.max(flex.abs(maptbx_fft_map - fft_map_unpadded)), 0)
#
fft_map.apply_sigma_scaling()
real_map = maptbx.copy(fft_map.real_map(),
flex.grid(fft_map.real_map().focus()))
grid_tags = maptbx.grid_tags(real_map.focus())
grid_tags.build(fft_map.space_group_info().type(),
fft_map.symmetry_flags())
assert grid_tags.n_grid_misses() == 0
assert grid_tags.verify(real_map)
rms = []
for interpolate in (False, True):
peak_list = maptbx.peak_list(data=real_map,
tags=grid_tags.tag_array(),
peak_search_level=1,
max_peaks=2 * n_elements,
interpolate=interpolate)
assert peak_list.gridding() == real_map.focus()
check_peaks(structure, peak_list.sites(),
d_min * grid_resolution_factor)
crystal_gridding_tags = fft_map.tags()
cluster_analysis = maptbx.peak_cluster_analysis(
peak_list=peak_list,
special_position_settings=structure,
general_positions_only=False,
effective_resolution=d_min,
min_cross_distance=2,
max_clusters=n_elements).all()
check_peaks(
structure, cluster_analysis.sites(),
cluster_analysis.min_cross_distance() +
d_min * grid_resolution_factor)
structure_from_peaks = xray.structure(structure)
for site in cluster_analysis.sites():
structure_from_peaks.add_scatterer(
xray.scatterer(label="site", scattering_type="", site=site))
emma_matches = emma.model_matches(structure.as_emma_model(),
structure_from_peaks.as_emma_model(),
tolerance=d_min * 2)
rms.append(emma_matches.refined_matches[0].rms)
assert len(emma_matches.refined_matches[0].pairs) == n_elements
# exercise interpolation vs. summation
map_coeffs = f_obs.expand_to_p1()
fft_map = f_obs.fft_map(resolution_factor=grid_resolution_factor,
symmetry_flags=maptbx.use_space_group_symmetry)
fft_map.apply_volume_scaling()
real_map = fft_map.real_map_unpadded()
sum1 = sum2 = 0
for scatterer in structure.scatterers():
v1 = real_map.eight_point_interpolation(scatterer.site)
v2 = real_map.tricubic_interpolation(scatterer.site)
v3 = map_coeffs.direct_summation_at_point(scatterer.site)
sum1 += abs(v1 - v3.real)
sum2 += abs(v2 - v3.real)
mean_delta_linear = sum1 / n_elements
mean_delta_cubic = sum2 / n_elements
assert (mean_delta_cubic < mean_delta_linear)
if (0 or verbose):
print("emma rms grid, interpolated: %.2f %.2f" % tuple(rms))
assert rms[0] >= rms[1]
map_1 = fft_map.real_map_unpadded(in_place=False)
map_2 = fft_map.real_map_unpadded(in_place=True)
assert (map_1.all_eq(map_2))
