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 test_shift(space_group_info,
d_min=0.8, grid_resolution_factor=0.48, max_prime=5,
verbose=0):
n = 12 // len(space_group_info.group()) or 1
target_structure = random_structure.xray_structure(
space_group_info=space_group_info,
elements=['C']*n,
use_u_iso=False,
use_u_aniso=False,
)
f_target = miller.build_set(
crystal_symmetry=target_structure,
anomalous_flag=False,
d_min=d_min
).structure_factors_from_scatterers(
xray_structure=target_structure,
algorithm="direct").f_calc()
f_obs = abs(f_target)
indices_in_p1 = miller.set.expand_to_p1(f_target)
target_structure_in_p1 = target_structure.expand_to_p1()
reference_translation = matrix.col((0.1, 0.2, 0.7))
structure_in_p1 = target_structure_in_p1.apply_shift(reference_translation)
f_structure_in_p1 = indices_in_p1.structure_factors_from_scatterers(
xray_structure=structure_in_p1,
algorithm="direct").f_calc()
symmetry_flags = translation_search.symmetry_flags(
is_isotropic_search_model=False,
have_f_part=False)
gridding = f_target.crystal_gridding(
symmetry_flags=symmetry_flags,
resolution_factor=grid_resolution_factor,
max_prime=max_prime).n_real()
grid_tags = maptbx.grid_tags(gridding)
for f_calc_in_p1 in (f_structure_in_p1,):
peak_list = run_fast_nv1995(
f_obs=f_obs, f_calc_fixed=None, f_calc_p1=f_calc_in_p1,
symmetry_flags=symmetry_flags, gridding=gridding,
grid_tags=grid_tags, verbose=verbose)
assert peak_list.heights()[0] > 0.9
shift = matrix.col(peak_list.sites()[0])
assert f_target.space_group_info().is_allowed_origin_shift(
shift + reference_translation, tolerance=0.04)
def exercise_grid_tags():
t = maptbx.grid_tags((8,10,12))
assert not t.is_valid()
assert t.tag_array().all() == (8,10,12)
s = sgtbx.space_group_info("P 21")
for i_flags in xrange(8):
f = sgtbx.search_symmetry_flags(
use_space_group_symmetry=i_flags % 2 != 0,
use_space_group_ltr=0,
use_seminvariants=(i_flags//4) % 2 != 0,
use_normalizer_k2l=(i_flags//2) % 2 != 0,
use_normalizer_l2n=False)
t.build(s.type(), f)
assert t.is_valid()
assert t.space_group_type().group() == s.group()
assert t.symmetry_flags() == f
if (f.use_seminvariants()):
assert [(vm.v, vm.m) for vm in t.grid_ss_continuous()] \
== [((0, 1, 0), 10)]
assert t.n_grid_misses() == 0
assert t.n_independent() == (960, 480, 484, 242, 24, 14, 14, 14)[i_flags]
assert t.n_independent() + t.n_dependent() == t.tag_array().size()
for flex_type in flex_types():
d = flex_type(t.tag_array().accessor())
assert t.n_dependent() == 0 \
or approx_equal(t.dependent_correlation(d, 1.e-10).coefficient(),0)
assert t.verify(d, 0)
t.sum_sym_equiv_points(d)
if (i_flags == 0):
assert t.n_independent() == t.tag_array().size()
else:
assert t.n_independent() < t.tag_array().size()
for flex_type in flex_types():
d = flex_type([random.random() for x in xrange(t.tag_array().size())])
d.resize(t.tag_array().accessor())
assert not t.verify(d)
t.sum_sym_equiv_points(d)
assert t.verify(d)
def exercise(space_group_info, redundancy_counter=0):
n_real = (12,12,12)
miller_max = (2,2,2)
gt = maptbx.grid_tags(n_real)
uc = space_group_info.any_compatible_unit_cell(volume=1000)
fl = sgtbx.search_symmetry_flags(use_space_group_symmetry=True)
gt.build(space_group_info.type(), fl)
fft = fftpack.real_to_complex_3d(n_real)
map0 = flex.double(flex.grid(fft.m_real()).set_focus(fft.n_real()), 0)
weight_map = map0.deep_copy()
map = map0.deep_copy()
ta = gt.tag_array()
order_z = space_group_info.group().order_z()
problems_expected = (redundancy_counter != 0)
for ijk in flex.nested_loop(n_real):
t = ta[ijk]
if (t < 0):
xyz = [i/n for i,n in zip(ijk, n_real)]
ss = sgtbx.site_symmetry(
unit_cell=uc,
space_group=space_group_info.group(),
original_site=xyz,
min_distance_sym_equiv=1e-5)
m = space_group_info.group().multiplicity(
site=boost.rational.vector(ijk, n_real))
assert m == ss.multiplicity()
w = m / order_z
weight_map[ijk] = w
map[ijk] = w
elif (redundancy_counter != 0):
redundancy_counter -= 1
ijk_asu = n_dim_index_from_one_dim(i1d=t, sizes=n_real)
assert ta.accessor()(ijk_asu) == t
map[ijk] = map[ijk_asu]
sf_map = fft.forward(map)
del map
mi = miller.index_generator(
space_group_info.type(), False, miller_max).to_array()
assert mi.size() != 0
from_map = maptbx.structure_factors.from_map(
space_group=space_group_info.group(),
anomalous_flag=False,
miller_indices=mi,
complex_map=sf_map,
conjugate_flag=True)
sf = [iround(abs(f)) for f in from_map.data()]
if (sf != [0]*len(sf)):
assert problems_expected
return
else:
not problems_expected
#
map_p1 = map0.deep_copy()
map_sw = map0.deep_copy()
for ijk in flex.nested_loop(n_real):
t = ta[ijk]
if (t < 0):
v = random.random()*2-1
map_p1[ijk] = v
map_sw[ijk] = v * weight_map[ijk]
else:
ijk_asu = n_dim_index_from_one_dim(i1d=t, sizes=n_real)
assert ta.accessor()(ijk_asu) == t
assert map_p1[ijk_asu] != 0
map_p1[ijk] = map_p1[ijk_asu]
#
# fft followed by symmetry summation in reciprocal space
sf_map_sw = fft.forward(map_sw)
del map_sw
sf_sw = maptbx.structure_factors.from_map(
space_group=space_group_info.group(),
anomalous_flag=False,
miller_indices=mi,
complex_map=sf_map_sw,
conjugate_flag=True).data()
del sf_map_sw
#
# symmetry expansion in real space (done above already) followed fft
sf_map_p1 = fft.forward(map_p1)
del map_p1
sf_p1 = maptbx.structure_factors.from_map(
space_group=sgtbx.space_group(),
anomalous_flag=False,
miller_indices=mi,
complex_map=sf_map_p1,
conjugate_flag=True).data()
del sf_map_p1
#
corr = flex.linear_correlation(x=flex.abs(sf_sw), y=flex.abs(sf_p1))
assert corr.is_well_defined
assert approx_equal(corr.coefficient(), 1)
def run_group(symbol):
group = space_group_info(symbol)
print("\n==")
elements = ('C', 'N', 'O', 'H') * 11
struc = random_structure.xray_structure(space_group_info=group,
volume_per_atom=25.,
general_positions_only=False,
elements=elements,
min_distance=1.0)
struc.show_summary()
d_min = 2.
fc = struc.structure_factors(d_min=d_min).f_calc()
symmetry_flags = maptbx.use_space_group_symmetry
fftmap = fc.fft_map(symmetry_flags=symmetry_flags)
grid_size = fftmap.real_map().accessor().focus()
###
rm = fftmap.real_map().deep_copy()
amap0 = asymmetric_map(struc.space_group().type(), rm)
p1_map00 = amap0.symmetry_expanded_map()
assert approx_equal(p1_map00, rm)
#
maptbx.unpad_in_place(rm)
amap1 = asymmetric_map(struc.space_group().type(), rm)
p1_map10 = amap1.symmetry_expanded_map()
assert approx_equal(p1_map00, p1_map10)
###
grid_tags = maptbx.grid_tags(grid_size)
grid_tags.build(fftmap.space_group_info().type(), fftmap.symmetry_flags())
grid_tags.verify(fftmap.real_map())
print("FFT grid_size = ", grid_size)
amap = asymmetric_map(struc.space_group().type(), fftmap.real_map())
afc = amap.structure_factors(fc.indices())
afftmap = amap.map_for_fft()
print("whole cell map size: ", afftmap.accessor().focus())
adata = amap.data()
acc = adata.accessor()
print("Asu map size: ", acc.origin(), " ", acc.last(), " ", acc.focus(), \
" ", acc.all())
df = flex.abs(afc - fc.data())
r1 = flex.sum(df) / flex.sum(flex.abs(fc.data()))
print("R1: ", r1)
assert r1 < 1.e-5
# just to prove to myself that I can shift origin to 000 and then reshape back
adata = adata.shift_origin()
adata.reshape(acc)
#
adata2 = adata.deep_copy() * 2.
amap2 = asymmetric_map(struc.space_group().type(), adata2, grid_size)
afc2 = amap2.structure_factors(fc.indices())
df2 = flex.abs(afc2 * .5 - fc.data())
r12 = flex.sum(df2) / flex.sum(flex.abs(fc.data()))
print("R1 again: ", r12)
assert r12 < 1.e-5
p1_map = amap.symmetry_expanded_map()
assert p1_map.accessor().focus() == grid_size
rel_tol = 1.e-6
n = 0
mean_rel_dif = 0.
for (m1, m2) in zip(fftmap.real_map(), p1_map):
dif = abs(m1 - m2)
av = 0.5 * (abs(m1) + abs(m2))
assert dif <= rel_tol * av, "%f not <= %f * %f" % (dif, rel_tol, av)
if av != 0:
mean_rel_dif = mean_rel_dif + dif / av
n = n + 1
mean_rel_dif = mean_rel_dif / n
print("mean rel err: ", mean_rel_dif)
assert mean_rel_dif < 1.e-6
def test_molecule(space_group_info, use_primitive_setting, flag_f_part,
d_min=3., grid_resolution_factor=0.48, max_prime=5,
verbose=0):
if (use_primitive_setting):
space_group_info = space_group_info.primitive_setting()
elements = ("N", "C", "C", "O", "N", "C", "C", "O")
structure = random_structure.xray_structure(
space_group_info,
elements=elements,
volume_per_atom=50,
min_distance=1.,
general_positions_only=True,
random_u_iso=True,
random_occupancy=True)
if (0 or verbose):
structure.show_summary().show_scatterers()
miller_set_f_obs = miller.build_set(
crystal_symmetry=structure,
anomalous_flag=(random.random() < 0.5),
d_min=d_min)
f_obs = abs(miller_set_f_obs.structure_factors_from_scatterers(
xray_structure=structure,
algorithm="direct").f_calc())
if (0 or verbose):
f_obs.show_summary()
if (0 or verbose):
f_obs.show_array()
miller_set_p1 = miller.set.expand_to_p1(f_obs)
special_position_settings_p1 = crystal.special_position_settings(
crystal_symmetry=miller_set_p1)
structure_p1 = xray.structure(
special_position_settings=special_position_settings_p1)
structure_fixed = xray.structure(special_position_settings=structure)
for scatterer in structure.scatterers():
if (flag_f_part and structure_fixed.scatterers().size()
< structure.scatterers().size()//2):
structure_fixed.add_scatterer(scatterer)
else:
structure_p1.add_scatterer(scatterer)
if (0 or verbose):
if (flag_f_part):
structure_fixed.show_summary().show_scatterers()
structure_p1.show_summary().show_scatterers()
f_calc_fixed = None
if (flag_f_part):
f_calc_fixed = f_obs.structure_factors_from_scatterers(
xray_structure=structure_fixed,
algorithm="direct").f_calc()
f_calc_p1 = miller_set_p1.structure_factors_from_scatterers(
xray_structure=structure_p1,
algorithm="direct").f_calc()
symmetry_flags = translation_search.symmetry_flags(
is_isotropic_search_model=False,
have_f_part=flag_f_part)
gridding = miller_set_f_obs.crystal_gridding(
symmetry_flags=symmetry_flags,
resolution_factor=grid_resolution_factor,
max_prime=max_prime).n_real()
grid_tags = maptbx.grid_tags(gridding)
run_fast_terms(
structure_fixed, structure_p1,
f_obs, f_calc_fixed, f_calc_p1,
symmetry_flags, gridding, grid_tags,
test_origin=True,
verbose=verbose)
peak_list = run_fast_nv1995(
f_obs, f_calc_fixed, f_calc_p1,
symmetry_flags, gridding, grid_tags, verbose)
assert peak_list.heights()[0] > 0.99
def test_atom(space_group_info, use_primitive_setting,
n_elements=3, d_min=3.,
grid_resolution_factor=0.48, max_prime=5, verbose=0):
if (use_primitive_setting):
space_group_info = space_group_info.primitive_setting()
structure = random_structure.xray_structure(
space_group_info,
n_scatterers=n_elements,
volume_per_atom=150,
min_distance=1.,
general_positions_only=True)
miller_set_f_obs = miller.build_set(
crystal_symmetry=structure,
anomalous_flag=(random.random() < 0.5),
d_min=d_min)
symmetry_flags = translation_search.symmetry_flags(
is_isotropic_search_model=True,
have_f_part=(n_elements>=2))
gridding = miller_set_f_obs.crystal_gridding(
symmetry_flags=symmetry_flags,
resolution_factor=grid_resolution_factor,
max_prime=max_prime).n_real()
structure.build_scatterers(
elements=["Se"]*n_elements,
grid=gridding)
if (0 or verbose):
structure.show_summary().show_scatterers()
f_obs = abs(miller_set_f_obs.structure_factors_from_scatterers(
xray_structure=structure,
algorithm="direct").f_calc())
if (0 or verbose):
f_obs.show_summary()
if (0 or verbose):
f_obs.show_array()
miller_set_p1 = miller.set.expand_to_p1(f_obs)
special_position_settings_p1 = crystal.special_position_settings(
crystal_symmetry=miller_set_p1)
structure_fixed = xray.structure(special_position_settings=structure)
for scatterer in structure.scatterers():
structure_p1 = xray.structure(
special_position_settings=special_position_settings_p1)
scatterer_at_origin = scatterer.customized_copy(site=(0,0,0))
structure_p1.add_scatterer(scatterer_at_origin)
if (0 or verbose):
structure_p1.show_summary().show_scatterers()
f_calc_p1 = miller_set_p1.structure_factors_from_scatterers(
xray_structure=structure_p1,
algorithm="direct").f_calc()
if (0 or verbose):
f_calc_p1.show_array()
f_calc_fixed = None
if (structure_fixed.scatterers().size() > 0):
f_calc_fixed = f_obs.structure_factors_from_scatterers(
xray_structure=structure_fixed,
algorithm="direct").f_calc()
symmetry_flags = translation_search.symmetry_flags(
is_isotropic_search_model=True,
have_f_part=(f_calc_fixed is not None))
if (structure_fixed.scatterers().size() <= 1):
gridding = miller_set_f_obs.crystal_gridding(
symmetry_flags=symmetry_flags,
resolution_factor=grid_resolution_factor,
max_prime=max_prime).n_real()
grid_tags = maptbx.grid_tags(gridding)
run_fast_terms(
structure_fixed, structure_p1,
f_obs, f_calc_fixed, f_calc_p1,
symmetry_flags, gridding, grid_tags,
verbose=verbose)
peak_list = run_fast_nv1995(
f_obs, f_calc_fixed, f_calc_p1,
symmetry_flags, gridding, grid_tags, verbose)
structure_fixed.add_scatterer(scatterer)
if (0 or verbose):
structure_fixed.show_summary().show_scatterers()
if (structure_fixed.scatterers().size() < n_elements):
assert peak_list.heights()[0] < 1
else:
assert peak_list.heights()[0] > 0.99
assert peak_list.heights()[0] > 0.99
def exercise(space_group_info, redundancy_counter=0):
n_real = (12, 12, 12)
miller_max = (2, 2, 2)
gt = maptbx.grid_tags(n_real)
uc = space_group_info.any_compatible_unit_cell(volume=1000)
fl = sgtbx.search_symmetry_flags(use_space_group_symmetry=True)
gt.build(space_group_info.type(), fl)
fft = fftpack.real_to_complex_3d(n_real)
map0 = flex.double(flex.grid(fft.m_real()).set_focus(fft.n_real()), 0)
weight_map = map0.deep_copy()
map = map0.deep_copy()
ta = gt.tag_array()
order_z = space_group_info.group().order_z()
problems_expected = (redundancy_counter != 0)
for ijk in flex.nested_loop(n_real):
t = ta[ijk]
if (t < 0):
xyz = [i / n for i, n in zip(ijk, n_real)]
ss = sgtbx.site_symmetry(unit_cell=uc,
space_group=space_group_info.group(),
original_site=xyz,
min_distance_sym_equiv=1e-5)
m = space_group_info.group().multiplicity(
site=boost.rational.vector(ijk, n_real))
assert m == ss.multiplicity()
w = m / order_z
weight_map[ijk] = w
map[ijk] = w
elif (redundancy_counter != 0):
redundancy_counter -= 1
ijk_asu = n_dim_index_from_one_dim(i1d=t, sizes=n_real)
assert ta.accessor()(ijk_asu) == t
map[ijk] = map[ijk_asu]
sf_map = fft.forward(map)
del map
mi = miller.index_generator(space_group_info.type(), False,
miller_max).to_array()
assert mi.size() != 0
from_map = maptbx.structure_factors.from_map(
space_group=space_group_info.group(),
anomalous_flag=False,
miller_indices=mi,
complex_map=sf_map,
conjugate_flag=True)
sf = [iround(abs(f)) for f in from_map.data()]
if (sf != [0] * len(sf)):
assert problems_expected
return
else:
not problems_expected
#
map_p1 = map0.deep_copy()
map_sw = map0.deep_copy()
for ijk in flex.nested_loop(n_real):
t = ta[ijk]
if (t < 0):
v = random.random() * 2 - 1
map_p1[ijk] = v
map_sw[ijk] = v * weight_map[ijk]
else:
ijk_asu = n_dim_index_from_one_dim(i1d=t, sizes=n_real)
assert ta.accessor()(ijk_asu) == t
assert map_p1[ijk_asu] != 0
map_p1[ijk] = map_p1[ijk_asu]
#
# fft followed by symmetry summation in reciprocal space
sf_map_sw = fft.forward(map_sw)
del map_sw
sf_sw = maptbx.structure_factors.from_map(
space_group=space_group_info.group(),
anomalous_flag=False,
miller_indices=mi,
complex_map=sf_map_sw,
conjugate_flag=True).data()
del sf_map_sw
#
# symmetry expansion in real space (done above already) followed fft
sf_map_p1 = fft.forward(map_p1)
del map_p1
sf_p1 = maptbx.structure_factors.from_map(space_group=sgtbx.space_group(),
anomalous_flag=False,
miller_indices=mi,
complex_map=sf_map_p1,
conjugate_flag=True).data()
del sf_map_p1
#
corr = flex.linear_correlation(x=flex.abs(sf_sw), y=flex.abs(sf_p1))
assert corr.is_well_defined
assert approx_equal(corr.coefficient(), 1)
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))
