def selection_by_symmetry (crystal_symmetries,
source_infos,
exclude_space_group=None,
only_space_group=None,
log=null_out()) :
"""
Return a list of indices for those crystal symmetries which either match the
only_space_group parameter, or do not match exclude_space_group.
"""
from cctbx import sgtbx
if (type(exclude_space_group).__name__ != 'info') :
exclude_space_group = sgtbx.space_group_info(exclude_space_group)
if (type(only_space_group).__name__ != 'info') :
only_space_group = sgtbx.space_group_info(only_space_group)
selection = []
for k, symm in enumerate(symmetries) :
skip = False
sg = None
if (only_space_group is not None) :
if (symm is None) :
skip = True
else :
sg = str(symm.space_group_info())
if (sg != str(only_space_group)) :
skip = True
elif (exclude_space_group is not None) :
if (symm is not None) :
sg = str(symm.space_group_info())
if (sg == str(exclude_space_group)) :
skip = True
if (skip) :
print >> log, " %s is in space group %s, skipping" %(source_infos[k],sg)
else :
selection.append(k)
return selection
def run():
for space_group_symbol in ("P-1",
"P2/m",
"C2/m",
"Pmmm",
"Cmmm",
"Fmmm",
"Immm",
"P4/mmm",
"I4/mmm",
"R-3m",
"P6/mmm",
"Pm-3m",
"Im-3m",
"Fm-3m"):
centric_info = sgtbx.space_group_info(space_group_symbol)
non_centric = sgtbx.space_group()
for i_ltr in xrange(centric_info.group().n_ltr()):
for i_smx in xrange(centric_info.group().n_smx()):
s = centric_info.group()(i_ltr,0,i_smx)
non_centric.expand_smx(s)
assert non_centric.f_inv() == 1
assert non_centric.order_z() * 2 == centric_info.group().order_z()
non_centric_info = sgtbx.space_group_info(group=non_centric)
centric_stats = subgroup_stats(centric_info)
non_centric_stats = subgroup_stats(non_centric_info)
assert len(centric_stats.subgroups) >= 2*len(non_centric_stats.subgroups)
assert centric_stats.n_non_centric >= non_centric_stats.n_non_centric
assert centric_stats.n_chiral == non_centric_stats.n_chiral
assert non_centric_stats.n_non_centric == len(non_centric_stats.subgroups)
assert non_centric_stats.n_non_centric == non_centric_stats.n_chiral
print "OK"
def space_group_info(self, unit_cell=None):
if (self.symbol is None): return None
if (self.category is None):
try: return sgtbx.space_group_info(self.symbol)
except RuntimeError: return None
if (isinstance(unit_cell, uctbx.ext.unit_cell)):
unit_cell = unit_cell.parameters()
if (self.category == rhombohedral):
if (unit_cell is None): return None
(a, b, c, alpha, beta, gamma) = unit_cell
if (abs(a - b) <= 0.01 and is90(alpha) and is90(beta) and is120(gamma)):
basis_symbol = "H"
elif (equiv(a,b,c) and equiv(alpha,beta,gamma)):
basis_symbol = "R"
else:
return None
return sgtbx.space_group_info(
rhombohedral[self.symbol] + ":" + basis_symbol)
if (self.category == short_mono):
if (unit_cell is None): return None
Z, T = self.symbol[0], self.symbol[1:]
(a, b, c, alpha, beta, gamma) = unit_cell
if (is90(alpha) and is90(gamma)):
if (Z == "B"): return None
return sgtbx.space_group_info(Z + " 1 " + T + " 1")
if (is90(alpha) and is90(beta)):
if (Z == "C"): return None
return sgtbx.space_group_info(Z + " 1 1 " + T)
if (self.category == special):
return sgtbx.space_group_info(special[self.symbol])
raise RuntimeError("Programming error (should be unreachable).")
def make_and_place_nodes_and_connections(self, input_sg):
# make the object and name please
object = sgtbx.space_group_info(group=input_sg)
name = str(object)
sg_relations = sub_super_point_group_relations(
input_sg,
self.pg_high,
self.assert_pg)
# loop over the possible outgoing edges
edge_list = {}
for possible_super_sg, used_symops, unused_symops \
in zip(sg_relations.return_next_sg(),
sg_relations.return_next_set(),
sg_relations.return_next_left_over_set()):
# This is enough info to make connections from the given node
edge = edge_object(used =used_symops,
unused = unused_symops,
as_xyz = self.as_xyz)
edge_list[str(sgtbx.space_group_info(group=possible_super_sg)) ] = edge
# place the sg's generated on the queue
if not possible_super_sg in self.queue:
self.queue.append(possible_super_sg)
# place/insert the node with the proper connections please
# print object, type(object)
self.graph.insert_node(name = name,
edge_object = edge_list,
node_object = object)
def exercise_generator_set():
sgi = sgtbx.space_group_info('P1')
sg_generator_set = sgtbx.any_generator_set(sgi.group())
assert sg_generator_set.non_primitive_generators == ()
sgi = sgtbx.space_group_info('P21')
sg_generator_set = sgtbx.any_generator_set(sgi.group())
assert (map(str, sg_generator_set.non_primitive_generators)
== ['-x,y+1/2,-z'])
sgi = sgtbx.space_group_info('Pmmm')
sg_generator_set = sgtbx.any_generator_set(sgi.group())
assert (map(str, sg_generator_set.non_primitive_generators)
== ['-x,-y,-z', 'x,-y,-z', '-x,y,-z'])
for i in xrange(1, 231):
sgi = sgtbx.space_group_info(number=i)
sg = sgi.group()
sg_gen = sgtbx.any_generator_set(sg)
if sg.z2p_op().is_identity_op():
assert sg_gen.non_primitive_generators == sg_gen.primitive_generators
for i in xrange(1, 231):
sgi = sgtbx.space_group_info(number=i)
sg = sgi.group()
sg_gen = sgtbx.any_generator_set(sg)
sg1 = sgtbx.space_group("P1")
for op in sg_gen.non_primitive_generators:
sg1.expand_smx(op)
for t in sg.ltr():
sg1.expand_ltr(t)
assert sg1.type().number() == sg.type().number()
def exercise_d_metrical_matrix_d_params():
def finite_differences(unit_cell, eps=1e-6):
grads = []
for i in range(6):
params = list(unit_cell.parameters())
params[i] += eps
uc = uctbx.unit_cell(parameters=params)
qm = matrix.col(uc.metrical_matrix())
params[i] -= 2*eps
uc = uctbx.unit_cell(parameters=params)
qp = matrix.col(uc.metrical_matrix())
dq = (qm-qp)/(2*eps)
grads.extend(list(dq))
grads = flex.double(grads)
grads.resize(flex.grid((6,6)))
return grads.matrix_transpose()
from cctbx import sgtbx
p1 = sgtbx.space_group_info('P1')
uc = p1.any_compatible_unit_cell(27)
grads = uc.d_metrical_matrix_d_params()
fd_grads = finite_differences(uc)
assert approx_equal(grads, fd_grads)
sgi = sgtbx.space_group_info('I-4')
uc = sgi.any_compatible_unit_cell(volume=18000)
grads = uc.d_metrical_matrix_d_params()
fd_grads = finite_differences(uc)
assert approx_equal(grads, fd_grads)
def show(self, out=None):
if out is None:
out = sys.stdout
print >> out, (
"Input subgroup : %s" % sgtbx.space_group_info(group=self.sg_low))
print >> out, (
"Input lattice group : %s" % sgtbx.space_group_info(group=self.sg_high))
print >> out
print >> out
for set,group,leftover in zip(self.grouped_symops,
self.sg_groups,
self.left_over_symops):
assert(len(set)+len(leftover)==len(self.symops))
print >> out, (
"Supergroup : %s" % sgtbx.space_group_info(group=group))
print >> out, " Used symops:"
for symop in set:
print >> out, " (%s) "%(symop.r().as_hkl())
print >> out
print >> out, " Left over symops:"
for symop in leftover:
if symop is not None:
print >> out, " (%s) "%(symop.r().as_hkl())
else:
print >> out, " None"
print >> out
print >> out
def reference_setting_choices(space_group):
# we used to have
cyclic_permutations = ['x,y,z',
'y,z,x',
'z,x,y' ]
adams_group = sgtbx.space_group_info(
group=space_group.build_derived_group(False, False))
space_group = sgtbx.space_group_info(group=space_group)
# please check that we have something in reference setting
# just to make sure that thne thing is used for it's original purpose
assert space_group.is_reference_setting()
info = []
identity_op = sgtbx.change_of_basis_op('x,y,z').c().r()
for cyclic_permutation in cyclic_permutations:
cob_op = sgtbx.change_of_basis_op(cyclic_permutation)
transformed_adams_group = adams_group.change_basis(cob_op)
transformed_space_group = space_group.change_basis(cob_op)
cob_to_ref_sg = transformed_space_group.\
change_of_basis_op_to_reference_setting()
cob_to_ref_pg = transformed_adams_group.\
change_of_basis_op_to_reference_setting()
adams_norm = False
space_norm = False
# check if the rotation part of the cb_op to ref is
# the identity operator
# if hall symbols are equal, sg's are equal
if (identity_op == cob_to_ref_pg.c().r()):
adams_norm=True
if (identity_op == cob_to_ref_sg.c().r()):
space_norm=True
info_tuple = (cob_op, cob_to_ref_sg, adams_norm, space_norm)
info.append(info_tuple)
possible_additional_transforms = []
# we have to of course take into account the identity operator
possible_additional_transforms.append(info[0][0]*info[0][1])
for ii in info:
if ii[2]: # should fall in the adams normalizer
if not ii[3]: # should NOT fall in the space normalizer
# cob should ONLY be applied on unit cell, not to the sg.
possible_additional_transforms.append(ii[0])
return possible_additional_transforms
def run():
import sys
libtbx.utils.show_times_at_exit()
parser = space_group_option_parser()
parser.option(None, '--skip_extra_tests',
action='store_true',
default=False)
parser.option(None, '--fixed_random_seed',
default=True)
command_line = parser.process(sys.argv[1:])
if not command_line.options.skip_extra_tests:
# the solution-to-target change-of-basis computed as
# reference-to-target x solution-to-reference
# is not a mere translation
exercise(
sgtbx.space_group_info(
'hall: -I 4 2c (1/2*x+1/2*y+1/12,-1/2*x+1/2*y-1/12,z-1/4)'),
shifted_origin=(0, 0.4, 0.9),
verbose=command_line.options.verbose)
exercise(sgtbx.space_group_info('hall: C 2c 2 (x-y,x+y,z)'),
shifted_origin=(0.4, 0.9, 0.6),
verbose=command_line.options.verbose)
# the centring translation search peaks (1/2, 0, 0) which is
# a structure seminvariant: test whether this is rejected
exercise(sgtbx.space_group_info('hall: -P 2a 2a'),
shifted_origin=(0.1, 0.2, 0.6),
verbose=command_line.options.verbose)
# the traditional loop over a selection of space-groups
# the last one, -I 4 2c (1/2*x+1/2*y+1/12,-1/2*x+1/2*y-1/12,z-1/4),
# results in solution_to_target_cb_op being non-trivial.
command_line.loop_over_space_groups(exercise,
shifted_origin=(0.1, 0.2, 0.6))
def __init__(self, f_in_p1, **kwds):
isinstance(f_in_p1, miller.array)
assert f_in_p1.space_group().type().hall_symbol() == ' P 1'
self.f_in_p1 = f_in_p1
adopt_optional_init_args(self, kwds)
self.search_parameters = maptbx.peak_search_parameters(
peak_search_level=3,
interpolate=True,
min_distance_sym_equiv=0.25,
)
self.space_group = sgtbx.space_group('P 1', t_den=sg_t_den)
self.origin = None
self.symmetry_pool = []
self.find_centring_translations()
if self.space_group.order_z() > 1:
f_in_centered = self.f_in_p1.customized_copy(
space_group_info=sgtbx.space_group_info(group=self.space_group)
).eliminate_sys_absent().merge_equivalents().array()
self.cb_op_to_primitive = \
f_in_centered.change_of_basis_op_to_primitive_setting()
self.f_in_p1 = f_in_centered.change_basis(self.cb_op_to_primitive)
self.space_group = self.f_in_p1.space_group()
else:
self.cb_op_to_primitive = sgtbx.change_of_basis_op()
self.f_in_p1 = self.f_in_p1.generate_bijvoet_mates()
self.find_space_group()
self.space_group = sgtbx.space_group(self.space_group.type().hall_symbol(),
t_den=sgtbx.sg_t_den)
self.space_group_info = sgtbx.space_group_info(group=self.space_group)
def tst_compare(): sg1 = construct_rational_point_group( sgtbx.space_group_info( "P 2 2 2" ).group() ) sg2 = construct_rational_point_group( sgtbx.space_group_info( "P 2 2 2" ).group() ) sg3 = construct_rational_point_group( sgtbx.space_group_info( "P 4 2 2" ).group() ) sg4 = construct_rational_point_group( sgtbx.space_group_info( "P 2 2 2 (a+b,a-b,2c)").group() ) assert compare_groups( sg1, sg2 ) assert not compare_groups( sg1, sg3 ) assert not compare_groups( sg1, sg4 )
def combine_symops_and_symbol(space_group_from_ops, space_group_symbol):
space_group_symbol = space_group_symbol.replace(" ","").upper()
z = space_group_symbol[:1]
if ("PABCIFRH".find(z) < 0):
raise RuntimeError(
"Cannot determine lattice centring type given space group symbol"
" %s" % show_string(space_group_symbol))
if (z == "P"):
return sgtbx.space_group_info(group=space_group_from_ops)
if (z == "H"):
space_group_symbol = "R" + space_group_symbol[1:] + ":H"
z = "R"
elif (z == "R" and not space_group_symbol.endswith(":H")):
if (space_group_symbol.endswith(":R")):
z = None
else:
for s in space_group_from_ops:
r_info = s.r().info()
if (abs(r_info.type()) == 3):
if (r_info.ev() == (0,0,1)):
space_group_symbol = "R" + space_group_symbol[1:] + ":H"
break
elif (r_info.ev() == (1,1,1)):
space_group_symbol += ":R"
z = None
break
space_group_exp = sgtbx.space_group(space_group_from_ops)
if (z is not None):
try:
space_group_exp.expand_conventional_centring_type(z)
except RuntimeError:
space_group_exp = None
if (space_group_exp is not None):
try:
space_group_from_symbol = sgtbx.space_group_info(
symbol=space_group_symbol).group()
except RuntimeError:
space_group_from_symbol = None
if ( space_group_exp is None
or space_group_from_symbol is None
or space_group_exp != space_group_from_symbol):
if space_group_from_symbol:
warnings.warn("""
WARNING:
Symmetry operations in input file are for space group %(space_group_exp)s
However space group symbol is: %(space_group_symbol)s
This may be a format error in the Scalepack file!
Using %(space_group_symbol)s
""" % {"space_group_exp" : str(space_group_exp.info()),
"space_group_symbol" : show_string(space_group_symbol), },
UserWarning, stacklevel=10)
space_group_exp = space_group_from_symbol
else:
raise RuntimeError(
"Symmetry operations in unmerged SCALEPACK file incompatible with"
" space group symbol %s"
% show_string(space_group_symbol))
return sgtbx.space_group_info(group=space_group_exp)
def get_all_axes(space_group_symbol=None, space_group_info=None, extension=0):
assert space_group_symbol is None or space_group_info is None
shift_range = 1 # RWGK Works for the 230 reference settings; it is not
# RWGK clear to me (rwgk) what value is needed in general.
if (space_group_symbol is not None):
space_group_info = sgtbx.space_group_info(symbol=space_group_symbol)
#space_group_info.show_summary()
axes_dict = {}
for smx in space_group_info.group():
r = smx.r()
t = smx.t()
shift = [0,0,0]
for shift[0] in range(-shift_range,shift_range+1):
for shift[1] in range(-shift_range,shift_range+1):
for shift[2] in range(-shift_range,shift_range+1):
ts = t.plus(sgtbx.tr_vec(shift, 1)).new_denominator(t.den())
m = sgtbx.rt_mx(r, ts)
#print m
rtmxanal = rlc_RTMxAnalysis(m)
#print r, t, shift, ts, m
if rtmxanal:
#print rtmxanal
axes_dict[rtmxanal] = 0
axes_list = axes_dict.keys()
axes_list.sort()
# reject nonenantiomorphic space groups
if len(axes_list) > 0 and not re.compile("[A-z]").search(space_group_symbol[1:]):
try:
sgtbx.space_group_info(space_group_symbol).show_summary(),
#print len(axes_list), space_group_symbol
except:
print space_group, space_group_symbol
print
sys.exit(1)
axes = []
for a in axes_list:
if len(a) == 3 and len(a[1]) == 3 and len(a[2]) == 3:
tmp_dict = {}
print "%4s %7.4f %7.4f %7.4f %7.4f %7.4f %7.4f " % (a[0],a[1][0],a[1][1],a[1][2],a[2][0],a[2][1],a[2][2])
tmp_dict['symb'] = a[0]
start_array = N.asarray(a[1])
end_array = N.asarray(a[2])
start_vec = start_array - (end_array - start_array)*extension
end_vec = end_array + (end_array - start_array)*extension
tmp_dict['start'] = start_vec
tmp_dict['end'] = end_vec
#rlc# tmp_dict['start'] = a[1]
#rlc# tmp_dict['end'] = a[2]
axes.append(tmp_dict)
else:
print a
else:
return None
return axes
def exercise () :
m = iotbx.symmetry.manager(prefer_pdb_space_group=True)
(uc_mismatch, sg_mismatch) = m.add_reflections_file(
file_name="data.mtz",
space_group=sgtbx.space_group_info("P222"),
unit_cell=uctbx.unit_cell("50 60 70 90 90 90"))
assert (m.get_current_as_strings() == ('P 2 2 2', '50 60 70 90 90 90'))
(uc_mismatch, sg_mismatch) = m.add_pdb_file(
file_name="model.pdb",
space_group=sgtbx.space_group_info("P212121"),
unit_cell=uctbx.unit_cell("50 60 70 90 90 90"))
assert (not (uc_mismatch or sg_mismatch))
(uc_mismatch, sg_mismatch) = m.add_pdb_file(
file_name="reference_model.pdb",
space_group=sgtbx.space_group_info("P63"),
unit_cell=uctbx.unit_cell("40 40 75 90 90 120"))
assert ((uc_mismatch, sg_mismatch) == (True, True))
assert (m.get_current_as_strings() == ('P 21 21 21', '50 60 70 90 90 90'))
(uc_mismatch, sg_mismatch) = m.add_reflections_file(
file_name="data_neutron.mtz",
space_group=sgtbx.space_group_info("P222"),
unit_cell=uctbx.unit_cell("50.1 60 70.1 90 90 90"))
assert (not (uc_mismatch or sg_mismatch))
(uc_mismatch, sg_mismatch) = m.add_reflections_file(
file_name="data_rfree.hkl",
space_group=None,
unit_cell=None)
assert (not (uc_mismatch or sg_mismatch))
assert (m.get_current_as_strings() == ('P 21 21 21', '50 60 70 90 90 90'))
assert (m.check_cell_compatibility("phenix.refine"))
symm_choices = m.get_symmetry_choices()
assert (symm_choices.space_group_files == [('model.pdb', 'P 21 21 21'),
('reference_model.pdb', 'P 63'), ('data.mtz', 'P 2 2 2'),
('data_neutron.mtz', 'P 2 2 2')])
assert (symm_choices.unit_cell_files == [
('model.pdb', '(50, 60, 70, 90, 90, 90)'),
('reference_model.pdb', '(40, 40, 75, 90, 90, 120)'),
('data.mtz', '(50, 60, 70, 90, 90, 90)'),
('data_neutron.mtz', '(50.1, 60, 70.1, 90, 90, 90)')])
m.set_current_as_strings("P63", "50 60 70 90 90 90")
try :
m.check_cell_compatibility(
program_name="phenix.refine",
raise_error_if_incomplete=True)
except Sorry :
pass
else :
raise Exception_expected
out = StringIO()
m.show(out=out)
assert (out.getvalue() == """\
model.pdb: (50, 60, 70, 90, 90, 90) P 21 21 21
reference_model.pdb: (40, 40, 75, 90, 90, 120) P 63
data.mtz: (50, 60, 70, 90, 90, 90) P 2 2 2
data_neutron.mtz: (50.1, 60, 70.1, 90, 90, 90) P 2 2 2
data_rfree.hkl: None None
""")
def digest(self,add_inv=False):
return '#'.join([
'%.5f'%self['max_angular_difference'],
self.pretty_cb_op(),
self['bravais'],
sgtbx.space_group_info(group=self['reduced_group']).type().lookup_symbol(),
sgtbx.space_group_info(group=self['best_group']).type().lookup_symbol(),
' '.join([str(int(x)) for x in self['constraints']]),
])
def run_00():
time_aniso_u_scaler = 0
for symbol in sgtbx.bravais_types.acentric + sgtbx.bravais_types.centric:
#print symbol, "-"*50
space_group_info = sgtbx.space_group_info(symbol = symbol)
xrs = random_structure.xray_structure(
space_group_info = space_group_info,
elements = ["N"]*100,
volume_per_atom = 50.0,
random_u_iso = True)
# XXX ad a method to adptbx to do this
point_group = sgtbx.space_group_info(
symbol=symbol).group().build_derived_point_group()
adp_constraints = sgtbx.tensor_rank_2_constraints(
space_group=point_group,
reciprocal_space=True)
u_star = adptbx.u_cart_as_u_star(xrs.unit_cell(),
adptbx.random_u_cart(u_scale=1,u_min=0.1))
u_indep = adp_constraints.independent_params(all_params=u_star)
u_star = adp_constraints.all_params(independent_params=u_indep)
b_cart_start=adptbx.u_as_b(adptbx.u_star_as_u_cart(xrs.unit_cell(), u_star))
#
tr = (b_cart_start[0]+b_cart_start[1]+b_cart_start[2])/3
b_cart_start = [b_cart_start[0]-tr,b_cart_start[1]-tr,b_cart_start[2]-tr,
b_cart_start[3],b_cart_start[4],b_cart_start[5]]
tr = (b_cart_start[0]+b_cart_start[1]+b_cart_start[2])/3
#
#print "Input b_cart :", " ".join(["%8.4f"%i for i in b_cart_start]), "tr:", tr
F = xrs.structure_factors(d_min = 2.0).f_calc()
u_star = adptbx.u_cart_as_u_star(
F.unit_cell(), adptbx.b_as_u(b_cart_start))
fbc = mmtbx.f_model.ext.k_anisotropic(F.indices(), u_star)
fc = F.structure_factors_from_scatterers(xray_structure=xrs).f_calc()
f_obs = F.customized_copy(data = flex.abs(fc.data()*fbc))
t0 = time.time()
#
obj = bulk_solvent.aniso_u_scaler(
f_model_abs = flex.abs(fc.data()),
f_obs = f_obs.data(),
miller_indices = f_obs.indices(),
adp_constraint_matrix = adp_constraints.gradient_sum_matrix())
time_aniso_u_scaler += (time.time()-t0)
b_cart_final = adptbx.u_as_b(adptbx.u_star_as_u_cart(f_obs.unit_cell(),
adp_constraints.all_params(tuple(obj.u_star_independent))))
#
obj = bulk_solvent.aniso_u_scaler(
f_model_abs = flex.abs(fc.data()),
f_obs = f_obs.data(),
miller_indices = f_obs.indices())
b_cart_final2 = adptbx.u_as_b(adptbx.u_star_as_u_cart(f_obs.unit_cell(),
tuple(obj.u_star)))
#
assert approx_equal(b_cart_final, b_cart_final2)
#print "Output b_cart:", " ".join(["%8.4f"%i for i in b_cart_final])
assert approx_equal(b_cart_start, b_cart_final, 1.e-4)
print "Time (aniso_u_scaler only): %6.4f"%time_aniso_u_scaler
def is_subgroup(self, g, h):
tst_group = str( sgtbx.space_group_info(group=g) )
tst_group = sgtbx.space_group_info( tst_group ).group()
h = [s for s in h]
for s in h:
tst_group.expand_smx( s )
if str(sgtbx.space_group_info(group=tst_group)) == str( sgtbx.space_group_info(group=g) ):
return True
else:
return False
def exercise_writer () :
from iotbx import file_reader
from cctbx import uctbx, sgtbx
from scitbx.array_family import flex
file_name = libtbx.env.find_in_repositories(
relative_path="phenix_regression/wizards/partial_refine_001_map_coeffs.mtz",
test=os.path.isfile)
if file_name is None :
print "Can't find map coefficients file, skipping."
return
mtz_in = file_reader.any_file(file_name, force_type="hkl").file_object
miller_arrays = mtz_in.as_miller_arrays()
map_coeffs = miller_arrays[0]
fft_map = map_coeffs.fft_map(resolution_factor=1/3.0)
fft_map.apply_sigma_scaling()
fft_map.as_ccp4_map(file_name="2mFo-DFc.map")
m = iotbx.ccp4_map.map_reader(file_name="2mFo-DFc.map")
real_map = fft_map.real_map_unpadded()
mmm = flex.double(list(real_map)).min_max_mean()
assert approx_equal(m.unit_cell_parameters,
map_coeffs.unit_cell().parameters())
assert approx_equal(mmm.min, m.header_min)
assert approx_equal(mmm.max, m.header_max)
#assert approx_equal(mmm.mean, m.header_mean)
# random small maps of different sizes
for nxyz in flex.nested_loop((1,1,1),(4,4,4)):
mt = flex.mersenne_twister(0)
grid = flex.grid(nxyz)
map = mt.random_double(size=grid.size_1d())
map.reshape(grid)
real_map = fft_map.real_map_unpadded()
iotbx.ccp4_map.write_ccp4_map(
file_name="random.map",
unit_cell=uctbx.unit_cell((1,1,1,90,90,90)),
space_group=sgtbx.space_group_info("P1").group(),
gridding_first=(0,0,0),
gridding_last=tuple(fft_map.n_real()),
map_data=real_map,
labels=flex.std_string(["iotbx.ccp4_map.tst"]))
m = iotbx.ccp4_map.map_reader(file_name="random.map")
mmm = flex.double(list(real_map)).min_max_mean()
assert approx_equal(m.unit_cell_parameters, (1,1,1,90,90,90))
assert approx_equal(mmm.min, m.header_min)
assert approx_equal(mmm.max, m.header_max)
#
gridding_first = (0,0,0)
gridding_last = tuple(fft_map.n_real())
map_box = maptbx.copy(map, gridding_first, gridding_last)
map_box.reshape(flex.grid(map_box.all()))
iotbx.ccp4_map.write_ccp4_map(
file_name="random_box.map",
unit_cell=uctbx.unit_cell((1,1,1,90,90,90)),
space_group=sgtbx.space_group_info("P1").group(),
map_data=map_box,
labels=flex.std_string(["iotbx.ccp4_map.tst"]))
def exercise_combine_symmetry () :
"""
Test the extraction of symmetry from both a PDB file and an MTZ file.
"""
from mmtbx.regression import model_1yjp
import mmtbx.command_line
import iotbx.pdb.hierarchy
from cctbx import sgtbx
from cctbx import uctbx
# 1yjp, as usual
pdb_in = iotbx.pdb.hierarchy.input(pdb_string=model_1yjp)
xrs = pdb_in.input.xray_structure_simple()
f = open("tst_combine_symmetry.pdb", "w")
f.write(pdb_in.hierarchy.as_pdb_string(crystal_symmetry=xrs))
f.close()
f_calc = abs(xrs.structure_factors(d_min=1.5).f_calc())
# Make up slightly more exact unit cell, but set SG to P2
f_calc = f_calc.customized_copy(
crystal_symmetry=f_calc.crystal_symmetry().customized_copy(
space_group_info=sgtbx.space_group_info("P2"),
unit_cell=uctbx.unit_cell((21.9371, 4.8659, 23.4774, 90.0, 107.0832,
90.00))))
flags = f_calc.generate_r_free_flags()
mtz = f_calc.as_mtz_dataset(column_root_label="F")
mtz.add_miller_array(flags, column_root_label="FreeR_flag")
mtz.mtz_object().write("tst_combine_symmetry.mtz")
cmdline = mmtbx.command_line.load_model_and_data(
args=["tst_combine_symmetry.pdb", "tst_combine_symmetry.mtz"],
master_phil=mmtbx.command_line.generate_master_phil_with_inputs(""),
process_pdb_file=False,
create_fmodel=True,
out=null_out())
symm = cmdline.xray_structure.crystal_symmetry()
assert (approx_equal(symm.unit_cell().parameters(),
(21.9371, 4.8659, 23.4774, 90.0, 107.0832, 90.0)))
assert (str(symm.space_group_info()) == "P 1 21 1")
# Part 2: incompatible space groups
f_calc_2 = f_calc.customized_copy(
crystal_symmetry=f_calc.crystal_symmetry().customized_copy(
space_group_info=sgtbx.space_group_info("P1")))
flags_2 = f_calc_2.generate_r_free_flags()
mtz = f_calc_2.as_mtz_dataset(column_root_label="F")
mtz.add_miller_array(flags_2, column_root_label="FreeR_flag")
mtz.mtz_object().write("tst_combine_symmetry_2.mtz")
try :
cmdline = mmtbx.command_line.load_model_and_data(
args=["tst_combine_symmetry.pdb", "tst_combine_symmetry_2.mtz"],
master_phil=mmtbx.command_line.generic_simple_input_phil(),
process_pdb_file=False,
create_fmodel=True,
out=null_out())
except Sorry, s :
assert ("Incompatible space groups" in str(s))
def tst_find_best_cell():
uc_array=[ uctbx.unit_cell( '40, 50, 60, 90, 90, 90' ),
uctbx.unit_cell( '40, 60, 50, 90, 90, 90' ),
uctbx.unit_cell( '50, 40, 60, 90, 90, 90' ),
uctbx.unit_cell( '50, 60, 40, 90, 90, 90' ),
uctbx.unit_cell( '60, 40, 50, 90, 90, 90' ),
uctbx.unit_cell( '60, 50, 40, 90, 90, 90' ) ]
uc_correct = [ uctbx.unit_cell( '40, 50, 60, 90, 90, 90' ),
uctbx.unit_cell( '40, 60, 50, 90, 90, 90' ),
uctbx.unit_cell( '40, 50, 60, 90, 90, 90' ),
uctbx.unit_cell( '50, 60, 40, 90, 90, 90' ),
uctbx.unit_cell( '40, 60, 50, 90, 90, 90' ),
uctbx.unit_cell( '50, 60, 40, 90, 90, 90' ) ]
sg_info = sgtbx.space_group_info( 'P 21 21 2' )
sg_info_2 = sgtbx.space_group_info( 'I 21 21 21' )
sg = sg_info.group()
sg_2 = sg_info_2.group()
for uc, correct in zip(uc_array,uc_correct):
best_cell_finder = fbc( uc, sg )
assert approx_equal( correct.parameters(),
best_cell_finder.return_best_cell().parameters() )
cb_op = best_cell_finder.return_change_of_basis_op_to_best_cell()
xs = crystal.symmetry( uc, space_group=sg)
assert approx_equal( correct.parameters(),
xs.change_basis(cb_op).unit_cell().parameters() )
best_cell_finder = fbc( uc, sg_2 )
assert approx_equal( uc_array[0].parameters(),
best_cell_finder.return_best_cell().parameters() )
xs = crystal.symmetry( uc, space_group=sg_2)
cb_op = best_cell_finder.return_change_of_basis_op_to_best_cell()
assert approx_equal( uc_array[0].parameters(),
xs.change_basis(cb_op).unit_cell().parameters() )
# test with incomming sg not in reference setting
uc = uctbx.unit_cell( '60, 40, 30, 90, 90, 90' )
sg_info_3 = sgtbx.space_group_info( 'P 1 1 21' )
sg_3 = sg_info_3.group()
best_cell_finder = fbc( uc, sg_3 )
xs_best = best_cell_finder.return_best_xs()
uc_correct = uctbx.unit_cell( '40, 30, 60, 90, 90, 90' )
sg_correct = sgtbx.space_group_info( 'P 1 21 1' ).group()
assert approx_equal( xs_best.unit_cell().parameters(),
uc_correct.parameters() )
assert sg_correct == xs_best.space_group()
def exercise_monoclinic_cell_choices_core(space_group_number, verbose):
# transformation matrices for cell choices
# columns are basis vectors "new in terms of old"
# see Int. Tab. Vol. A, p. 22, Fig. 2.2.6.4.
b1 = (1, 0, 0,
0, 1, 0,
0, 0, 1)
b2 = (-1, 0, 1,
0, 1, 0,
-1, 0, 0)
b3 = (0, 0, -1,
0, 1, 0,
1, 0, -1)
flip = (0, 0, 1,
0, -1, 0,
1, 0, 0)
p3s = sgtbx.space_group("P 3*")
done = {}
ref = sgtbx.space_group_info(number=space_group_number)
ref_uhm = ref.type().universal_hermann_mauguin_symbol()
for i_fl,fl in enumerate([b1, flip]):
rfl = sgtbx.rot_mx(fl)
cfl = sgtbx.change_of_basis_op(sgtbx.rt_mx(rfl))
for i_rt,rt in enumerate(p3s):
rp3 = rt.r()
cp3 = sgtbx.change_of_basis_op(sgtbx.rt_mx(rp3))
for i_cs,cs in enumerate([b1,b2,b3]):
rcs = sgtbx.rot_mx(cs).inverse()
ccs = sgtbx.change_of_basis_op(sgtbx.rt_mx(rcs))
cb_all = cp3 * cfl * ccs
refcb = ref.change_basis(cb_all)
refcb2 = sgtbx.space_group_info(symbol=ref_uhm+"("+str(cb_all.c())+")")
assert refcb2.group() == refcb.group()
s = sgtbx.space_group_symbols(str(refcb))
q = s.qualifier()
hm = str(refcb)
if (0 or verbose): print hm, q, cb_all.c()
if (i_fl == 0):
assert q[0] == "bca"[i_rt]
if (len(q) == 2): assert q[1] == "123"[i_cs]
elif (q[0] == "-"):
assert q[1] == "bca"[i_rt]
if (len(q) == 3): assert q[2] == "123"[i_cs]
else:
assert q[0] == "bca"[i_rt]
if (len(q) == 2 and q[1] != "123"[i_cs]):
assert done[hm] == 1
done.setdefault(hm, 0)
done[hm] += 1
assert len(done) in [3, 9, 18]
assert done.values() == [18/len(done)]*len(done)
if (0 or verbose): print
return done
def exercise():
from cctbx import sgtbx
import sys
for symbol in acentric + centric:
space_group_info = sgtbx.space_group_info(symbol=symbol)
assert str(space_group_info) == symbol
assert space_group_info.is_reference_setting()
if ("--Verbose" in sys.argv[1:]):
for symbol in centric:
print "/* %s */ %d," % (
symbol, sgtbx.space_group_info(symbol=symbol).type().number())
assert tst_bravais_types(verbose=("--Verbose" in sys.argv[1:]))
print "OK"
def exercise_quick():
for space_group_symbol in ("P-1",
"P2/m",
"C2/m",
"Pmmm",
"Cmmm",
"Fmmm",
"Immm",
"P4/mmm",
"I4/mmm",
"R-3m",
"P6/mmm",
"Pm-3m",
"Im-3m",
"Fm-3m"):
parent_group_info = sgtbx.space_group_info(space_group_symbol)
non_centric = sgtbx.space_group()
for i_ltr in xrange(parent_group_info.group().n_ltr()):
for i_smx in xrange(parent_group_info.group().n_smx()):
s = parent_group_info.group()(i_ltr,0,i_smx)
non_centric.expand_smx(s)
assert non_centric.f_inv() == 1
assert non_centric.order_z() * 2 == parent_group_info.group().order_z()
non_centric_info = sgtbx.space_group_info(group=non_centric)
unit_cell = non_centric_info.any_compatible_unit_cell(volume=1000)
crystal_symmetry = crystal.symmetry(
unit_cell=unit_cell,
space_group_info=non_centric_info)
minimum_symmetry = crystal_symmetry.minimum_cell()
lattice_group = lattice_symmetry.group(
minimum_symmetry.unit_cell(), max_delta=0.5)
lattice_group_info = sgtbx.space_group_info(group=lattice_group)
assert lattice_group_info.group() == minimum_symmetry.space_group()
subgrs = subgroups.subgroups(lattice_group_info).groups_parent_setting()
for group in subgrs:
subsym = crystal.symmetry(
unit_cell=minimum_symmetry.unit_cell(),
space_group=group,
assert_is_compatible_unit_cell=False)
assert subsym.unit_cell().is_similar_to(minimum_symmetry.unit_cell())
assert lattice_symmetry.find_max_delta(
reduced_cell=minimum_symmetry.unit_cell(),
space_group=group) < 0.6
minimum_symmetry = crystal.symmetry(
unit_cell="106.04, 181.78, 110.12, 90, 90, 90",
space_group_symbol="P 1").minimum_cell()
for max_delta in xrange(10,100,10):
lattice_group = lattice_symmetry.group(
minimum_symmetry.unit_cell(), max_delta=max_delta)
lattice_group_info = sgtbx.space_group_info(group=lattice_group)
assert str(lattice_group_info) == "P 4 2 2"
def show(self, out=None):
if out == None:
out=sys.stdout
print >> out, "Input space group : ", sgtbx.space_group_info(
group=self.x_sg)
print >> out, "Input unit cell : ", self.x_uc.parameters()
print >> out, "Likely point group : ", sgtbx.space_group_info(
group=self.lpg)
print >> out
print >> out, "Possible crystal symmetries: "
for sx_cb in self.allowed_under_pg_and_sys_abs:
sx_cb.show(out)
print >> out
def tst_build_reticular_twin_laws():
sg1 = construct_rational_point_group( sgtbx.space_group_info( "P 2 2 2" ).group() )
sg2 = construct_rational_point_group( sgtbx.space_group_info( "P 4 2 2 (a,b,2c)").group() )
result = build_reticular_twin_laws(sg1, sg2)
assert len(result)==1
for ii in result:
assert as_hkl(ii.transpose() )=="k,-h,l"
sg1 = construct_rational_point_group( sgtbx.space_group_info( "P 2 2 2" ).group() )
sg2 = construct_rational_point_group( sgtbx.space_group_info( "P 4 2 2").group() )
result = build_reticular_twin_laws(sg1, sg2)
assert len(result)==1
for ii in result:
assert as_hkl(ii.transpose() )=="k,-h,l"
def exercise_orthorhombic_hm_qualifier_as_cb_symbol():
cb_symbols = {
"cab": ["c,a,b", "z,x,y"],
"a-cb": ["a,-c,b", "x,-z,y"],
"-cba": ["-c,b,a", "-z,y,x"],
"bca": ["b,c,a", "y,z,x"],
"ba-c": ["b,a,-c", "y,x,-z"]}
for sgsyms1 in sgtbx.space_group_symbol_iterator():
n = sgsyms1.number()
if (n < 16 or n > 74): continue
q = sgsyms1.qualifier()
if (len(q) == 0): continue
e = sgsyms1.extension()
if (e == "\0"): e = ""
ehm = sgtbx.space_group_symbols(
space_group_number=n, extension=e).universal_hermann_mauguin()
cabc, cxyz = cb_symbols[q]
assert sgtbx.change_of_basis_op(cxyz).as_abc() == cabc
assert sgtbx.change_of_basis_op(cabc).as_xyz() == cxyz
uhm_xyz = ehm + " ("+cxyz+")"
sgsyms2 = sgtbx.space_group_symbols(symbol=uhm_xyz)
assert sgsyms2.change_of_basis_symbol() == cxyz
assert sgsyms2.extension() == sgsyms1.extension()
assert sgsyms2.universal_hermann_mauguin() == uhm_xyz
g1 = sgtbx.space_group(space_group_symbols=sgsyms1)
g2 = sgtbx.space_group(space_group_symbols=sgsyms2)
assert g2 == g1
g2 = sgtbx.space_group(
sgtbx.space_group_symbols(symbol=ehm)).change_basis(
sgtbx.change_of_basis_op(sgtbx.rt_mx(cxyz)))
assert g2 == g1
for c in [cxyz, cabc]:
g2 = sgtbx.space_group_info(
group=sgtbx.space_group(
sgtbx.space_group_symbols(symbol=ehm))).change_basis(c).group()
assert g2 == g1
cit = sgtbx.rt_mx(cxyz).r().inverse().transpose()
cit_xyz = cit.as_xyz()
g2 = sgtbx.space_group_info(
group=sgtbx.space_group(
sgtbx.space_group_symbols(symbol=ehm))).change_basis(cit_xyz).group()
assert g2 == g1
assert cit.as_xyz(False, "abc") == cabc
uhm_abc = ehm + " ("+cabc+")"
sgsyms2 = sgtbx.space_group_symbols(symbol=uhm_abc)
assert sgsyms2.change_of_basis_symbol() == cxyz
assert sgsyms2.extension() == sgsyms1.extension()
assert sgsyms2.universal_hermann_mauguin() == uhm_xyz
g2 = sgtbx.space_group(space_group_symbols=sgsyms2)
assert g2 == g1
def exercise_ss_continuous_shifts_are_principal():
for i in xrange(1, 231):
sgi = sgtbx.space_group_info(number=i)
ss = sgi.structure_seminvariants()
assert ss.continuous_shifts_are_principal()
for symbols in sgtbx.space_group_symbol_iterator():
sgi = sgtbx.space_group_info(group=sgtbx.space_group(
space_group_symbols=symbols))
ss = sgi.structure_seminvariants()
if (not ss.continuous_shifts_are_principal()):
assert symbols.universal_hermann_mauguin() in [
"R 3 :R",
"R 3 m :R",
"R 3 c :R"]
def run(args):
if (len(args) == 0):
from libtbx.utils import Usage
import libtbx.load_env
raise Usage(
"%s all|list-of-space-group-symbols-or-numbers"
% libtbx.env.dispatcher_name)
from cctbx.sgtbx import space_group_info
from cctbx.sgtbx.subgroups import show
if (args == ["all"]):
for space_group_number in xrange(1,231):
show(parent_group_info=space_group_info(space_group_number))
else:
for arg in args:
show(parent_group_info=space_group_info(symbol=arg))
def tst_groups():
cb_ops = sub_lattice_tools.generate_cb_op_up_to_order(7)
mats = sub_lattice_tools.generate_matrix_up_to_order(7)
base_group = sgtbx.space_group_info( "P 2 2 2" ).group()
for cb_op, mat in zip(cb_ops, mats):
rat_cb_op = mat
extended_group=None
try:
extended_group = sgtbx.space_group_info( "P 2 2 2 (%s)"%cb_op ).group()
except Exception: pass
rbg = construct_rational_point_group( base_group, rat_cb_op )
reg = None
if extended_group is not None:
reg = construct_rational_point_group( extended_group )
assert compare_groups(reg, rbg)
def make_new_xs(self, mat, cb_op, to_reference=True):
# make new lattice
new_basis = self.basis * mat.as_float()
new_uc = uctbx.unit_cell(orthogonalization_matrix=new_basis)
tmp_xs = crystal.symmetry(
unit_cell=new_uc,
space_group=sgtbx.lattice_symmetry.group(new_uc, self.max_delta),
assert_is_compatible_unit_cell=False,
)
extra_cb_op = tmp_xs.change_of_basis_op_to_reference_setting()
self.extra_cb_op.append(extra_cb_op)
#
new_sg = None
try:
new_sg = sgtbx.space_group_info(group=self.basic_xs_n.space_group()).change_basis(cb_op)
except Exception:
pass
if to_reference:
tmp_xs = tmp_xs.change_basis(extra_cb_op)
try:
new_sg = new_sg.change_basis(extra_cb_op)
except Exception:
pass
self.xs_list.append(tmp_xs)
self.sg_list.append(new_sg)
from __future__ import print_function
from cctbx import crystal, sgtbx, uctbx
from cctbx.sgtbx import lattice_symmetry
from cctbx.sgtbx.bravais_types import bravais_lattice
sg = sgtbx.space_group_info("C2").group()
uc = uctbx.unit_cell(
parameters="102.965614947,79.2397736681,77.45579668,90.0,139.074859178,90.0"
)
cs = crystal.symmetry(unit_cell=uc, space_group=sg)
print("Input cell:")
cs.show_summary()
print()
print("Best cell:")
cs.best_cell().show_summary()
print()
print("Reference settings:")
print("Best cell -> reference setting")
cs.best_cell().as_reference_setting().show_summary()
print("Input -> reference setting")
cs.as_reference_setting().show_summary()
print("Input -> primitive setting -> reference setting")
cs.primitive_setting().as_reference_setting().show_summary()
print("Best cell -> primitive setting -> reference setting")
print()
print("Primitive settings:")
cs.best_cell().primitive_setting().as_reference_setting().show_summary()
print("Best cell -> primitive setting")
def from_words(self, words, master):
symbol = libtbx.phil.str_from_words(words)
if (symbol is None): return None
if (symbol is Auto): return Auto
return sgtbx.space_group_info(symbol=str(symbol))
def spacegroup_number_to_name(spg_num):
"""Convert a spacegroup number to a more readable name."""
return sgtbx.space_group_info(number=spg_num).type().lookup_symbol()
try:
from crys3d.qttbx.xray_structure_viewer import display
except IOError:
def display(*args, **kwds): pass
# then use it
#display(xray_structure=xs)
# Let's look at symmetries
info = xs.space_group_info()
info.show_summary()
print "Hall: %s" % info.type().hall_symbol()
# List of all symmetries
print "Symmetries:"
for rt in info.group():
print rt.as_xyz()
# The mathematical object representing the group
g = info.group()
print "Inversion at origin:%s" % ('no', 'yes')[g.is_origin_centric()]
# Let's triple the cell
from cctbx import sgtbx
g.expand_ltr(sgtbx.tr_vec((1,0,1),3).new_denominator(g.t_den()))
g.expand_ltr(sgtbx.tr_vec((2,0,2),3).new_denominator(g.t_den()))
tripled_info = sgtbx.space_group_info(group=g)
tripled_info.show_summary()
print tripled_info.type().hall_symbol()
# Let's change the space group of the structure now
xs.as_cif_simple(open('03srv209x3.cif', 'w'))
def CheckFormat(self, value):
if len(value) == 0:
return ""
from cctbx import sgtbx
sg = str(sgtbx.space_group_info(symbol=str(value)))
return sg
def __init__(
self,
intensities,
normalisation="ml_aniso",
lattice_symmetry_max_delta=2.0,
d_min=libtbx.Auto,
min_i_mean_over_sigma_mean=4,
min_cc_half=0.6,
relative_length_tolerance=None,
absolute_angle_tolerance=None,
best_monoclinic_beta=True,
):
u"""Initialise a symmetry_base object.
Args:
intensities (cctbx.miller.array): The intensities on which to perform
symmetry anaylsis.
normalisation (str): The normalisation method to use. Possible choices are
'kernel', 'quasi', 'ml_iso' and 'ml_aniso'. Set to None to switch off
normalisation altogether.
lattice_symmetry_max_delta (float): The maximum value of delta for
determining the lattice symmetry using the algorithm of Le Page (1982).
d_min (float): Optional resolution cutoff to be applied to the input
intensities. If set to :data:`libtbx.Auto` then d_min will be
automatically determined according to the parameters
``min_i_mean_over_sigma_mean`` and ``min_cc_half``.
min_i_mean_over_sigma_mean (float): minimum value of |I|/|sigma(I)| for
automatic determination of resolution cutoff.
min_cc_half (float): minimum value of CC½ for automatic determination of
resolution cutoff.
relative_length_tolerance (float): Relative length tolerance in checking
consistency of input unit cells against the median unit cell.
absolute_angle_tolerance (float): Absolute angle tolerance in checking
consistency of input unit cells against the median unit cell.
best_monoclinic_beta (bool): If True, then for monoclinic centered cells, I2
will be preferred over C2 if it gives a more oblique cell (i.e. smaller
beta angle).
"""
self.input_intensities = intensities
uc_params = [flex.double() for i in range(6)]
for d in self.input_intensities:
for i, p in enumerate(d.unit_cell().parameters()):
uc_params[i].append(p)
self.median_unit_cell = uctbx.unit_cell(
parameters=[flex.median(p) for p in uc_params])
self._check_unit_cell_consistency(relative_length_tolerance,
absolute_angle_tolerance)
self.intensities = self.input_intensities[0]
self.dataset_ids = flex.double(self.intensities.size(), 0)
for i, d in enumerate(self.input_intensities[1:]):
self.intensities = self.intensities.concatenate(
d, assert_is_similar_symmetry=False)
self.dataset_ids.extend(flex.double(d.size(), i + 1))
self.intensities = self.intensities.customized_copy(
unit_cell=self.median_unit_cell)
self.intensities.set_observation_type_xray_intensity()
sys_absent_flags = self.intensities.sys_absent_flags(
integral_only=True).data()
self.intensities = self.intensities.select(~sys_absent_flags)
self.dataset_ids = self.dataset_ids.select(~sys_absent_flags)
self.lattice_symmetry_max_delta = lattice_symmetry_max_delta
self.subgroups = metric_subgroups(
self.intensities.crystal_symmetry(),
max_delta=self.lattice_symmetry_max_delta,
bravais_types_only=False,
best_monoclinic_beta=best_monoclinic_beta,
)
self.cb_op_inp_min = self.subgroups.cb_op_inp_minimum
self.intensities = (self.intensities.change_basis(
self.cb_op_inp_min).customized_copy(
space_group_info=sgtbx.space_group_info(
"P1")).map_to_asu().set_info(self.intensities.info()))
self.lattice_group = (self.subgroups.result_groups[0]
["subsym"].space_group().make_tidy())
self.patterson_group = (
self.lattice_group.build_derived_patterson_group().make_tidy())
logger.info("Patterson group: %s" % self.patterson_group.info())
sel = self.patterson_group.epsilon(self.intensities.indices()) == 1
self.intensities = self.intensities.select(sel)
self.dataset_ids = self.dataset_ids.select(sel)
# Correct SDs by "typical" SD factors
self._correct_sigmas(sd_fac=2.0, sd_b=0.0, sd_add=0.03)
self._normalise(normalisation)
self._resolution_filter(d_min, min_i_mean_over_sigma_mean, min_cc_half)
def infer_unit_cell_from_symmetry(params, space_group):
# XXX exercised by iotbx/kriber/tst_strudat.py
# XXX TODO: add to uctbx tests
from cctbx import sgtbx
error_msg = "Cannot interpret unit cell parameters."
#
laue_group = str(sgtbx.space_group_info(
group=space_group.build_derived_laue_group())).replace(" ", "")
#
if (len(params) == 6):
return unit_cell(params)
else:
crystal_system = space_group.crystal_system()
if (crystal_system == "Cubic"):
if len(params) == 1:
a = params[0]
elif len(params) == 3:
a,b,c = params
assert a==b==c
else:
raise RuntimeError(error_msg)
unit_cell_ = unit_cell((a,a,a,90,90,90))
elif (crystal_system in ("Hexagonal", "Trigonal")):
is_rhombohedral = False
if (crystal_system == "Trigonal"):
if (laue_group in ("R-3m:R", "R-3:R")):
is_rhombohedral = True
if (is_rhombohedral):
if len(params) != 2: raise RuntimeError(error_msg)
a = params[0]
angle = params[1]
unit_cell_ = unit_cell((a,a,a,angle,angle,angle))
else:
if len(params) == 2:
a = params[0]
c = params[1]
elif len(params) == 3:
a,b,c = params
assert a == b
elif len(params) == 4:
a,b,c,angle = params
assert a == b
assert angle == 120
else:
raise RuntimeError(error_msg)
unit_cell_ = unit_cell((a,a,c,90,90,120))
elif (crystal_system == "Tetragonal"):
if len(params) == 2:
a = params[0]
c = params[1]
unit_cell_ = unit_cell((a,a,c,90,90,90))
elif len(params) == 3:
a,b,c = params[:3]
assert a == b
unit_cell_ = unit_cell((a,a,c,90,90,90))
else:
raise RuntimeError(error_msg)
elif (crystal_system == "Orthorhombic"):
if len(params) != 3: raise RuntimeError(error_msg)
a = params[0]
b = params[1]
c = params[2]
unit_cell_ = unit_cell((a,b,c,90,90,90))
elif (crystal_system == "Monoclinic"):
if len(params) != 4: raise RuntimeError(error_msg)
a = params[0]
b = params[1]
c = params[2]
angle = params[3]
if (laue_group == "P12/m1"):
unit_cell_ = unit_cell((a,b,c,90,angle,90))
elif (laue_group == "P112/m"):
unit_cell_ = unit_cell((a,b,c,90,90,angle))
elif (laue_group == "P2/m11"):
unit_cell_ = unit_cell((a,b,c,angle,90,90))
elif (crystal_system == "Triclinic"):
raise RuntimeError(error_msg)
return unit_cell_
def exercise_lex_parse_build():
exercise_parser(cif.reader, cif.builders.cif_model_builder)
cm = cif.reader(input_string=cif_quoted_string).model()
assert cm['global']['_a'] == 'a"b'
assert cm['global']['_b'] == "a dog's life"
stdout = sys.stdout
s = StringIO()
sys.stdout = s
try:
cif.reader(input_string=cif_invalid_missing_value)
except CifParserError:
pass
else:
raise Exception_expected
r = cif.reader(input_string=cif_invalid_missing_value,
raise_if_errors=False)
assert r.error_count() == 1
try:
cif.reader(input_string=cif_invalid_string)
except CifParserError:
pass
else:
raise Exception_expected
a = cif.reader(input_string=cif_cod)
assert a.error_count() == 0
try:
cif.reader(input_string=cif_invalid_semicolon_text_field)
except CifParserError:
pass
else:
raise Exception_expected
d = cif.reader(input_string=cif_valid_semicolon_text_field)
assert d.error_count() == 0
assert d.model()['1']['_a'] == '\n1\n'
e = cif.reader(input_string=cif_unquoted_string_semicolon)
assert not show_diff(
str(e.model()), """\
data_1
_a ;1
_b ;
_c 2
""")
cif_str_1 = """\
data_1
_a 1
"""
cif_str_2 = """\
data_2
_b 2
"""
cm = cif.reader(input_string=cif_str_1).model()
assert list(cm.keys()) == ['1']
cif.reader(input_string=cif_str_2, cif_object=cm).model()
assert list(cm.keys()) == ['1', '2']
try:
cm = cif.reader(input_string=cif_invalid_loop).model()
except CifParserError:
pass
else:
raise Exception_expected
try:
cm = cif.reader(input_string=cif_invalid_loop_2).model()
except CifParserError:
pass
else:
raise Exception_expected
sys.stdout = stdout
arrays = miller.array.from_cif(file_object=StringIO(
cif_miller_array_template %
('_refln_F_calc', '_refln_F_meas', '_refln_F_sigma')),
data_block_name='global')
assert sorted(arrays.keys()) == ['_refln_F_calc', '_refln_F_meas']
assert arrays['_refln_F_calc'].sigmas() is None
assert isinstance(arrays['_refln_F_meas'].sigmas(), flex.double)
arrays = miller.array.from_cif(file_object=StringIO(
cif_miller_array_template %
('_refln_A_calc', '_refln_B_calc', '_refln_F_meas')),
data_block_name='global')
assert sorted(arrays.keys()) == ['_refln_A_calc', '_refln_F_meas']
assert arrays['_refln_A_calc'].is_complex_array()
arrays = miller.array.from_cif(file_object=StringIO(
cif_miller_array_template %
('_refln_A_meas', '_refln_B_meas', '_refln_F_meas')),
data_block_name='global')
assert sorted(arrays.keys()) == ['_refln_A_meas', '_refln_F_meas']
assert arrays['_refln_A_meas'].is_complex_array()
arrays = miller.array.from_cif(
file_object=StringIO(cif_miller_array_template %
('_refln_intensity_calc', '_refln_intensity_meas',
'_refln_intensity_sigma')),
data_block_name='global')
assert sorted(
arrays.keys()) == ['_refln_intensity_calc', '_refln_intensity_meas']
arrays = miller.array.from_cif(file_object=StringIO(
cif_miller_array_template %
('_refln_F_calc', '_refln_phase_calc', '_refln_F_sigma')),
data_block_name='global')
assert arrays['_refln_F_calc'].is_complex_array()
for data_block_name in (None, "global"):
miller_arrays = cif.reader(
file_object=StringIO(cif_miller_array_template %
('_refln_F_calc', '_refln_F_meas',
'_refln_F_sigma'))).as_miller_arrays(
data_block_name=data_block_name)
assert " ".join(sorted([str(ma.info()) for ma in miller_arrays])) \
== "cif:global,_refln_F_calc cif:global,_refln_F_meas,_refln_F_sigma"
f = open_tmp_file(suffix="cif")
f.write(cif_miller_array_template %
('_refln_F_calc', '_refln_F_meas', '_refln_F_sigma'))
f.close()
miller_arrays = any_reflection_file(file_name=f.name).as_miller_arrays()
assert len(miller_arrays) == 2
cs = crystal.symmetry(space_group_info=sgtbx.space_group_info("P1"))
miller_arrays = any_reflection_file(file_name=f.name).as_miller_arrays(
crystal_symmetry=cs, force_symmetry=True, anomalous=True)
assert miller_arrays[0].anomalous_flag() is True
assert miller_arrays[0].crystal_symmetry().space_group() == cs.space_group(
)
def create_all_subgroups( sg1,show_all=True, reverse=False ):
sg_high = sgtbx.space_group_info( sg1 ).group()
sg_low = sgtbx.space_group_info( "p1" ).group()
graph_object = pointgroup_tools.point_group_graph( sg_low, sg_high, False,True)
highest_sg = str( sgtbx.space_group_info( sg1 ) )
rev_dict = reverse_dict( graph_object.graph.o )
maximal_subgroups = get_maximal_subgroup( highest_sg, rev_dict )
if show_all:
print "Subgroups of input space groups which can be constructed by introducing one single operator (and group completion) in the subgroup:"
for sg in rev_dict[ highest_sg ]:
line = " "
line += sg+(30-len(sg))*" "+str(graph_object.graph.edge_objects[ sg ][highest_sg])+(90-len( str(graph_object.graph.edge_objects[ sg ][highest_sg]) ))*" "
print line
print
print "Maximal subgroup detected in the full sub-group-graph: "
for sg in maximal_subgroups:
line = " "
line += sg
print line
print
print
print
print " Cosets for each maximal sub-group and the input space group are listed:"
for sg in maximal_subgroups:
print "-----------------------------------------------------------------"
show_cosets.run( sg,highest_sg )
print "-----------------------------------------------------------------"
print
print
print
print
else:
print "Maximal subgroups of %s: "%(sg1)
for sg in maximal_subgroups:
line = " "
line += sg
print line
print
print
print
if reverse:
print "Minimal supergroups generated by the sub-groups of the input space group:"
tmp_sg = sgtbx.space_group_info( sg1 )
for sg in maximal_subgroups:
tmp_sgsg = sgtbx.space_group_info( sg )
cb_op = tmp_sgsg.change_of_basis_op_to_reference_setting()
okai=False
try:
new_sg = tmp_sg.change_basis( cb_op )
okai=True
print new_sg ," is a minimal supergroup of ", tmp_sgsg.change_basis(cb_op)
except Exception: pass
if not okai:
print "%s (%s) is a minimal supergroup of %s [*]"%(tmp_sg,cb_op, tmp_sgsg.change_basis(cb_op))
print
print
print
def exercise():
flex.set_random_seed(123456)
random.seed(123456)
base = "tst_table_one"
pdb_in = iotbx.pdb.hierarchy.input(pdb_string=model_1yjp)
xrs = pdb_in.xray_structure_simple()
xrs.set_inelastic_form_factors(photon=1.54, table="sasaki")
fc = abs(xrs.structure_factors(d_min=1.5).f_calc()).average_bijvoet_mates()
fc.set_observation_type_xray_amplitude()
flags = fc.generate_r_free_flags()
mtz = fc.as_mtz_dataset(column_root_label="F", wavelength=1.54)
mtz.add_miller_array(flags, column_root_label="FreeR_flag")
mtz.mtz_object().write(base + ".mtz")
xrs_p1 = xrs.expand_to_p1()
xrs_p1.shake_sites_in_place(rms_difference=0.1)
fc_p1 = xrs_p1.structure_factors(d_min=1.4).f_calc()
fc_p1_extra = fc_p1.randomize_amplitude_and_phase(amplitude_error=1.0,
phase_error_deg=0,
random_seed=123456)
fc_p1 = abs(
fc_p1.concatenate(other=fc_p1_extra)).sort(by_value="packed_indices")
fc_p1.set_observation_type_xray_amplitude()
sg_p2 = sgtbx.space_group_info("P2")
ic = fc_p1.f_as_f_sq().customized_copy(space_group_info=sg_p2,
sigmas=flex.double(
fc_p1.size(), 10.0))
ic.export_as_scalepack_unmerged(file_name=base + ".sca")
open(base + ".pdb", "w").write(model_1yjp)
args = [
base + ".mtz",
base + ".pdb",
"unmerged_data=%s.sca" % base,
"prefix=tst_table_one_1",
]
table_one.run(args=args,
out=null_out(),
use_current_directory_if_not_specified=True)
# now with unmerged data in SHELX format
f = open(base + ".hkl", "w")
ic.export_as_shelx_hklf(file_object=f)
f.close()
args = [
base + ".mtz",
base + ".pdb",
"unmerged_data=%s.hkl=hklf4" % base,
"prefix=tst_table_one_2",
]
table_one.run(args=args,
out=null_out(),
use_current_directory_if_not_specified=True)
# now with phil file
f = open("tst_table_one_3.eff", "w")
f.write("""\
table_one {
structure {
name = %(base)s
pdb_file = %(base)s.pdb
mtz_file = %(base)s.mtz
unmerged_data = %(base)s.hkl=hklf4
}
output {
directory = os.getcwd()
base_name = %(base)s_3
}
}""" % {"base": base})
args = ["tst_table_one_3.eff"]
table_one.run(args=args,
out=null_out(),
use_current_directory_if_not_specified=True)
def exercise_miller_arrays_as_cif_block():
from iotbx.cif import reader
cif_model = reader(input_string=cif_miller_array,
builder=cif.builders.cif_model_builder()).model()
ma_builder = cif.builders.miller_array_builder(cif_model['global'])
ma1 = ma_builder.arrays()['_refln_F_squared_meas']
mas_as_cif_block = cif.miller_arrays_as_cif_block(ma1,
array_type='meas',
format="corecif")
mas_as_cif_block.add_miller_array(
ma1.array(data=flex.complex_double([1 - 1j] * ma1.size())),
array_type='calc')
mas_as_cif_block.add_miller_array(
ma1.array(data=flex.complex_double([1 - 2j] * ma1.size())),
column_names=['_refln_A_calc', '_refln_B_calc'])
for key in ('_refln_F_squared_meas', '_refln_F_squared_sigma',
'_refln_F_calc', '_refln_phase_calc', '_refln_A_calc',
'_refln_A_calc'):
assert (key in mas_as_cif_block.cif_block.keys()), key
#
mas_as_cif_block = cif.miller_arrays_as_cif_block(ma1,
array_type='meas',
format="mmcif")
mas_as_cif_block.add_miller_array(
ma1.array(data=flex.complex_double([1 - 1j] * ma1.size())),
array_type='calc')
for key in ('_refln.F_squared_meas', '_refln.F_squared_sigma',
'_refln.F_calc', '_refln.phase_calc',
'_space_group_symop.operation_xyz', '_cell.length_a',
'_refln.index_h'):
assert key in mas_as_cif_block.cif_block.keys()
#
mas_as_cif_block = cif.miller_arrays_as_cif_block(
ma1,
column_names=[
'_diffrn_refln_intensity_net', '_diffrn_refln_intensity_sigma'
],
miller_index_prefix='_diffrn_refln')
mas_as_cif_block.add_miller_array(
ma1.array(data=flex.std_string(ma1.size(), 'om')),
column_name='_diffrn_refln_intensity_u')
for key in ('_diffrn_refln_intensity_net', '_diffrn_refln_intensity_sigma',
'_diffrn_refln_intensity_u'):
assert key in list(mas_as_cif_block.cif_block.keys())
#
try:
reader(input_string=cif_global)
except CifParserError as e:
pass
else:
raise Exception_expected
cif_model = reader(input_string=cif_global, strict=False).model()
assert not show_diff(
str(cif_model), """\
data_1
_c 3
_d 4
""")
# exercise adding miller arrays with non-matching indices
cs = crystal.symmetry(unit_cell=uctbx.unit_cell((10, 10, 10, 90, 90, 90)),
space_group_info=sgtbx.space_group_info(symbol="P1"))
mi = flex.miller_index(((1, 0, 0), (1, 2, 3), (2, 3, 4)))
ms1 = miller.set(cs, mi)
ma1 = miller.array(ms1, data=flex.double((1, 2, 3)))
mas_as_cif_block = cif.miller_arrays_as_cif_block(
ma1, column_name="_refln.F_meas_au")
ms2 = miller.set(cs, mi[:2])
ma2 = miller.array(ms2, data=flex.complex_double([1 - 2j] * ms2.size()))
mas_as_cif_block.add_miller_array(ma2,
column_names=("_refln.F_calc_au",
"_refln.phase_calc")),
ms3 = miller.set(cs, flex.miller_index(((1, 0, 0), (5, 6, 7), (2, 3, 4))))
ma3 = miller.array(ms3, data=flex.double((4, 5, 6)))
mas_as_cif_block.add_miller_array(ma3, column_name="_refln.F_squared_meas")
ms4 = miller.set(
cs,
flex.miller_index(
((1, 2, 3), (5, 6, 7), (1, 1, 1), (1, 0, 0), (2, 3, 4))))
ma4 = ms4.d_spacings()
mas_as_cif_block.add_miller_array(ma4, column_name="_refln.d_spacing")
# extract arrays from cif block and make sure we get back what we started with
arrays = cif.builders.miller_array_builder(
mas_as_cif_block.cif_block).arrays()
recycled_arrays = (arrays['_refln.F_meas_au'], arrays['_refln.F_calc_au'],
arrays['_refln.F_squared_meas'],
arrays['_refln.d_spacing'])
for orig, recycled in zip((ma1, ma2, ma3, ma4), recycled_arrays):
assert orig.size() == recycled.size()
recycled = recycled.customized_copy(
anomalous_flag=orig.anomalous_flag())
orig, recycled = orig.common_sets(recycled)
assert orig.indices().all_eq(recycled.indices())
assert approx_equal(orig.data(), recycled.data(), eps=1e-5)
#
cif_model = reader(input_string=r3adrsf,
builder=cif.builders.cif_model_builder()).model()
cs = cif.builders.crystal_symmetry_builder(
cif_model["r3adrsf"]).crystal_symmetry
ma_builder = cif.builders.miller_array_builder(
cif_model['r3adrAsf'],
base_array_info=miller.array_info(crystal_symmetry_from_file=cs))
miller_arrays = list(ma_builder.arrays().values())
assert len(miller_arrays) == 4
mas_as_cif_block = cif.miller_arrays_as_cif_block(
miller_arrays[0].map_to_asu(),
column_names=miller_arrays[0].info().labels,
format="corecif")
for array in miller_arrays[1:]:
labels = array.info().labels
if len(labels) > 1:
for label in labels:
if label.startswith("wavelength_id"):
labels.remove(label)
mas_as_cif_block.add_miller_array(array=array.map_to_asu(),
column_names=array.info().labels)
s = StringIO()
print(mas_as_cif_block.refln_loop, file=s)
assert not show_diff(
s.getvalue(), """\
loop_
_refln_index_h
_refln_index_k
_refln_index_l
_refln.crystal_id
_refln.wavelength_id
_refln.scale_group_code
_refln.pdbx_I_plus
_refln.pdbx_I_plus_sigma
_refln.pdbx_I_minus
_refln.pdbx_I_minus_sigma
-87 5 46 1 3 1 40.2 40.4 6.7 63.9
-87 5 45 1 3 1 47.8 29.7 35.1 30.5
-87 5 44 1 3 1 18.1 33.2 0.5 34.6
-87 5 43 1 3 1 6.1 45.4 12.9 51.6
-87 5 42 1 3 1 -6.6 45.6 -15.5 55.8
-87 7 37 1 3 1 6.3 43.4 ? ?
-87 7 36 1 3 1 -67.2 55.4 ? ?
-88 2 44 1 3 1 0 -1 35 38.5
-88 2 43 1 3 1 0 -1 57.4 41.5
-88 4 45 1 3 1 -1 46.1 -9.1 45.6
-88 4 44 1 3 1 -19.8 49.2 0.3 34.7
-88 6 44 1 3 1 -1.8 34.8 ? ?
""")
def simple(fmodel, pdb_hierarchy, params=None, log=None, show_results=False):
if (params is None): params = master_params().extract()
if (log is None): log = sys.stdout
crystal_gridding = None
unit_cell = None
d_min = 1.0
map_1 = None
map_2 = None
# compute map_1 and map_2 if given F_obs (fmodel exists)
if ((params.map_file_name is None)
and (params.map_coefficients_file_name is None)
and (fmodel is not None)):
e_map_obj = fmodel.electron_density_map()
coeffs_2 = e_map_obj.map_coefficients(
map_type=params.map_2.type,
fill_missing=params.map_2.fill_missing_reflections,
isotropize=params.map_2.isotropize)
fft_map_2 = coeffs_2.fft_map(
resolution_factor=params.resolution_factor)
crystal_gridding = fft_map_2
fft_map_2.apply_sigma_scaling()
map_2 = fft_map_2.real_map_unpadded()
coeffs_1 = e_map_obj.map_coefficients(
map_type=params.map_1.type,
fill_missing=params.map_1.fill_missing_reflections,
isotropize=params.map_1.isotropize)
fft_map_1 = miller.fft_map(crystal_gridding=crystal_gridding,
fourier_coefficients=coeffs_1)
fft_map_1.apply_sigma_scaling()
map_1 = fft_map_1.real_map_unpadded()
unit_cell = fmodel.xray_structure.unit_cell()
d_min = fmodel.f_obs().d_min()
# or read map coefficents
elif (params.map_coefficients_file_name is not None):
map_handle = any_file(params.map_coefficients_file_name)
crystal_symmetry = get_crystal_symmetry(map_handle)
unit_cell = crystal_symmetry.unit_cell()
d_min = get_d_min(map_handle)
crystal_gridding = maptbx.crystal_gridding(
crystal_symmetry.unit_cell(),
d_min=d_min,
resolution_factor=params.resolution_factor,
space_group_info=crystal_symmetry.space_group_info())
coeffs_2 = map_handle.file_server.get_miller_array(
params.map_coefficients_label)
fft_map_2 = miller.fft_map(crystal_gridding=crystal_gridding,
fourier_coefficients=coeffs_2)
fft_map_2.apply_sigma_scaling()
map_2 = fft_map_2.real_map_unpadded()
# or read CCP4 map
else:
map_handle = any_file(params.map_file_name)
unit_cell = map_handle.file_object.unit_cell()
sg_info = space_group_info(map_handle.file_object.space_group_number)
n_real = map_handle.file_object.unit_cell_grid
crystal_gridding = maptbx.crystal_gridding(
unit_cell, space_group_info=sg_info, pre_determined_n_real=n_real)
map_2 = map_handle.file_object.map_data()
# check for origin shift
# modified from phenix.command_line.real_space_refine
# plan to centralize functionality in another location
# -------------------------------------------------------------------------
shift_manager = mmtbx.utils.shift_origin(
map_data=map_2,
pdb_hierarchy=pdb_hierarchy,
crystal_symmetry=map_handle.crystal_symmetry())
if (shift_manager.shift_cart is not None):
print("Map origin is not at (0,0,0): shifting the map and model.",
file=log)
pdb_hierarchy = shift_manager.pdb_hierarchy
map_2 = shift_manager.map_data
# -------------------------------------------------------------------------
# compute map_1 (Fc) if given a map (fmodel does not exist)
if (map_1 is None):
xray_structure = pdb_hierarchy.extract_xray_structure(
crystal_symmetry=crystal_gridding.crystal_symmetry())
fft_map_1 = compute_map_from_model(d_min,
None,
xray_structure,
crystal_gridding=crystal_gridding)
fft_map_1.apply_sigma_scaling()
map_1 = fft_map_1.real_map_unpadded()
# compute cc
assert ((map_1 is not None) and (map_2 is not None))
broadcast(m="Map correlation and map values", log=log)
overall_cc = flex.linear_correlation(x=map_1.as_1d(),
y=map_2.as_1d()).coefficient()
print(" Overall map cc(%s,%s): %6.4f" %
(params.map_1.type, params.map_2.type, overall_cc),
file=log)
detail, atom_radius = params.detail, params.atom_radius
detail, atom_radius = set_detail_level_and_radius(detail=detail,
atom_radius=atom_radius,
d_min=d_min)
use_hydrogens = params.use_hydrogens
if (use_hydrogens is None):
if (params.scattering_table == "neutron" or d_min <= 1.2):
use_hydrogens = True
else:
use_hydrogens = False
hydrogen_atom_radius = params.hydrogen_atom_radius
if (hydrogen_atom_radius is None):
if (params.scattering_table == "neutron"):
hydrogen_atom_radius = atom_radius
else:
hydrogen_atom_radius = 1
results = compute(pdb_hierarchy=pdb_hierarchy,
unit_cell=unit_cell,
fft_n_real=map_1.focus(),
fft_m_real=map_1.all(),
map_1=map_1,
map_2=map_2,
detail=detail,
atom_radius=atom_radius,
use_hydrogens=use_hydrogens,
hydrogen_atom_radius=hydrogen_atom_radius)
if (show_results):
show(log=log, results=results, params=params, detail=detail)
return overall_cc, results
def exercise_floating_origin_dynamic_weighting(verbose=False):
from cctbx import covariance
import scitbx.math
worst_condition_number_acceptable = 10
# light elements only
xs0 = random_structure.xray_structure(elements=['C', 'C', 'C', 'O', 'N'],
use_u_aniso=True)
msg = "light elements in %s ..." % (
xs0.space_group_info().type().hall_symbol())
if verbose:
print(msg, end=' ')
fo_sq = xs0.structure_factors(d_min=0.8).f_calc().norm()
fo_sq = fo_sq.customized_copy(sigmas=flex.double(fo_sq.size(), 1.))
xs = xs0.deep_copy_scatterers()
xs.shake_adp()
xs.shake_sites_in_place(rms_difference=0.1)
for sc in xs.scatterers():
sc.flags.set_grad_site(True).set_grad_u_aniso(True)
ls = least_squares.crystallographic_ls(
fo_sq.as_xray_observations(),
constraints.reparametrisation(
structure=xs,
constraints=[],
connectivity_table=smtbx.utils.connectivity_table(xs)),
weighting_scheme=least_squares.unit_weighting(),
origin_fixing_restraints_type=
origin_fixing_restraints.atomic_number_weighting)
ls.build_up()
lambdas = eigensystem.real_symmetric(
ls.normal_matrix_packed_u().matrix_packed_u_as_symmetric()).values()
# assert the restrained L.S. problem is not too ill-conditionned
cond = math.log10(lambdas[0]/lambdas[-1])
if verbose:
print("normal matrix condition: %.1f" % cond)
assert cond < worst_condition_number_acceptable, msg
# one heavy element
xs0 = random_structure.xray_structure(
space_group_info=sgtbx.space_group_info('hall: P 2yb'),
elements=['Zn', 'C', 'C', 'C', 'O', 'N'],
use_u_aniso=True)
msg = "one heavy element + light elements (synthetic data) in %s ..." % (
xs0.space_group_info().type().hall_symbol())
if verbose:
print(msg, end=' ')
fo_sq = xs0.structure_factors(d_min=0.8).f_calc().norm()
fo_sq = fo_sq.customized_copy(sigmas=flex.double(fo_sq.size(), 1.))
xs = xs0.deep_copy_scatterers()
xs.shake_adp()
xs.shake_sites_in_place(rms_difference=0.1)
for sc in xs.scatterers():
sc.flags.set_grad_site(True).set_grad_u_aniso(True)
ls = least_squares.crystallographic_ls(
fo_sq.as_xray_observations(),
constraints.reparametrisation(
structure=xs,
constraints=[],
connectivity_table=smtbx.utils.connectivity_table(xs)),
weighting_scheme=least_squares.mainstream_shelx_weighting(),
origin_fixing_restraints_type=
origin_fixing_restraints.atomic_number_weighting)
ls.build_up()
lambdas = eigensystem.real_symmetric(
ls.normal_matrix_packed_u().matrix_packed_u_as_symmetric()).values()
# assert the restrained L.S. problem is not too ill-conditionned
cond = math.log10(lambdas[0]/lambdas[-1])
if verbose:
print("normal matrix condition: %.1f" % cond)
assert cond < worst_condition_number_acceptable, msg
# are esd's for x,y,z coordinates of the same order of magnitude?
var_cart = covariance.orthogonalize_covariance_matrix(
ls.covariance_matrix(),
xs.unit_cell(),
xs.parameter_map())
var_site_cart = covariance.extract_covariance_matrix_for_sites(
flex.size_t_range(len(xs.scatterers())),
var_cart,
xs.parameter_map())
site_esds = var_site_cart.matrix_packed_u_diagonal()
indicators = flex.double()
for i in xrange(0, len(site_esds), 3):
stats = scitbx.math.basic_statistics(site_esds[i:i+3])
indicators.append(stats.bias_corrected_standard_deviation/stats.mean)
assert indicators.all_lt(2)
# especially troublesome structure with one heavy element
# (contributed by Jonathan Coome)
xs0 = xray.structure(
crystal_symmetry=crystal.symmetry(
unit_cell=(8.4519, 8.4632, 18.7887, 90, 96.921, 90),
space_group_symbol="hall: P 2yb"),
scatterers=flex.xray_scatterer([
xray.scatterer( #0
label="ZN1",
site=(-0.736683, -0.313978, -0.246902),
u=(0.000302, 0.000323, 0.000054,
0.000011, 0.000015, -0.000004)),
xray.scatterer( #1
label="N3B",
site=(-0.721014, -0.313583, -0.134277),
u=(0.000268, 0.000237, 0.000055,
-0.000027, 0.000005, 0.000006)),
xray.scatterer( #2
label="N3A",
site=(-0.733619, -0.290423, -0.357921),
u=(0.000229, 0.000313, 0.000053,
0.000022, 0.000018, -0.000018)),
xray.scatterer( #3
label="C9B",
site=(-1.101537, -0.120157, -0.138063),
u=(0.000315, 0.000345, 0.000103,
0.000050, 0.000055, -0.000017)),
xray.scatterer( #4
label="N5B",
site=(-0.962032, -0.220345, -0.222045),
u=(0.000274, 0.000392, 0.000060,
-0.000011, -0.000001, -0.000002)),
xray.scatterer( #5
label="N1B",
site=(-0.498153, -0.402742, -0.208698),
u=(0.000252, 0.000306, 0.000063,
0.000000, 0.000007, 0.000018)),
xray.scatterer( #6
label="C3B",
site=(-0.322492, -0.472610, -0.114594),
u=(0.000302, 0.000331, 0.000085,
0.000016, -0.000013, 0.000037)),
xray.scatterer( #7
label="C4B",
site=(-0.591851, -0.368163, -0.094677),
u=(0.000262, 0.000255, 0.000073,
-0.000034, 0.000027, -0.000004)),
xray.scatterer( #8
label="N4B",
site=(-0.969383, -0.204624, -0.150014),
u=(0.000279, 0.000259, 0.000070,
-0.000009, 0.000039, 0.000000)),
xray.scatterer( #9
label="N2B",
site=(-0.470538, -0.414572, -0.135526),
u=(0.000277, 0.000282, 0.000065,
0.000003, 0.000021, -0.000006)),
xray.scatterer( #10
label="C8A",
site=(-0.679889, -0.158646, -0.385629),
u=(0.000209, 0.000290, 0.000078,
0.000060, 0.000006, 0.000016)),
xray.scatterer( #11
label="N5A",
site=(-0.649210, -0.075518, -0.263412),
u=(0.000307, 0.000335, 0.000057,
-0.000002, 0.000016, -0.000012)),
xray.scatterer( #12
label="C6B",
site=(-0.708620, -0.325965, 0.011657),
u=(0.000503, 0.000318, 0.000053,
-0.000058, 0.000032, -0.000019)),
xray.scatterer( #13
label="C10B",
site=(-1.179332, -0.083184, -0.202815),
u=(0.000280, 0.000424, 0.000136,
0.000094, 0.000006, 0.000013)),
xray.scatterer( #14
label="N1A",
site=(-0.838363, -0.532191, -0.293213),
u=(0.000312, 0.000323, 0.000060,
0.000018, 0.000011, -0.000008)),
xray.scatterer( #15
label="C3A",
site=(-0.915414, -0.671031, -0.393826),
u=(0.000319, 0.000384, 0.000078,
-0.000052, -0.000001, -0.000020)),
xray.scatterer( #16
label="C1A",
site=(-0.907466, -0.665419, -0.276011),
u=(0.000371, 0.000315, 0.000079,
0.000006, 0.000036, 0.000033)),
xray.scatterer( #17
label="C1B",
site=(-0.365085, -0.452753, -0.231927),
u=(0.000321, 0.000253, 0.000087,
-0.000024, 0.000047, -0.000034)),
xray.scatterer( #18
label="C11A",
site=(-0.598622, 0.053343, -0.227354),
u=(0.000265, 0.000409, 0.000084,
0.000088, -0.000018, -0.000030)),
xray.scatterer( #19
label="C2A",
site=(-0.958694, -0.755645, -0.337016),
u=(0.000394, 0.000350, 0.000106,
-0.000057, 0.000027, -0.000005)),
xray.scatterer( #20
label="C4A",
site=(-0.784860, -0.407601, -0.402050),
u=(0.000238, 0.000296, 0.000064,
0.000002, 0.000011, -0.000016)),
xray.scatterer( #21
label="C5A",
site=(-0.784185, -0.399716, -0.475491),
u=(0.000310, 0.000364, 0.000062,
0.000044, -0.000011, -0.000017)),
xray.scatterer( #22
label="N4A",
site=(-0.630284, -0.043981, -0.333143),
u=(0.000290, 0.000275, 0.000074,
0.000021, 0.000027, 0.000013)),
xray.scatterer( #23
label="C10A",
site=(-0.545465, 0.166922, -0.272829),
u=(0.000369, 0.000253, 0.000117,
0.000015, -0.000002, -0.000008)),
xray.scatterer( #24
label="C9A",
site=(-0.567548, 0.102272, -0.339923),
u=(0.000346, 0.000335, 0.000103,
-0.000016, 0.000037, 0.000023)),
xray.scatterer( #25
label="C11B",
site=(-1.089943, -0.146930, -0.253779),
u=(0.000262, 0.000422, 0.000102,
-0.000018, -0.000002, 0.000029)),
xray.scatterer( #26
label="N2A",
site=(-0.843385, -0.537780, -0.366515),
u=(0.000273, 0.000309, 0.000055,
-0.000012, -0.000005, -0.000018)),
xray.scatterer( #27
label="C7A",
site=(-0.674021, -0.136086, -0.457790),
u=(0.000362, 0.000378, 0.000074,
0.000043, 0.000034, 0.000016)),
xray.scatterer( #28
label="C8B",
site=(-0.843625, -0.264182, -0.102023),
u=(0.000264, 0.000275, 0.000072,
-0.000025, 0.000019, -0.000005)),
xray.scatterer( #29
label="C6A",
site=(-0.726731, -0.261702, -0.502366),
u=(0.000339, 0.000472, 0.000064,
0.000062, -0.000003, 0.000028)),
xray.scatterer( #30
label="C5B",
site=(-0.577197, -0.376753, -0.020800),
u=(0.000349, 0.000353, 0.000066,
-0.000082, -0.000022, 0.000014)),
xray.scatterer( #31
label="C2B",
site=(-0.252088, -0.497338, -0.175057),
u=(0.000251, 0.000342, 0.000119,
0.000020, 0.000034, -0.000018)),
xray.scatterer( #32
label="C7B",
site=(-0.843956, -0.268811, -0.028080),
u=(0.000344, 0.000377, 0.000078,
-0.000029, 0.000059, -0.000007)),
xray.scatterer( #33
label="F4B",
site=(-0.680814, -0.696808, -0.115056),
u=(0.000670, 0.000408, 0.000109,
-0.000099, 0.000139, -0.000031)),
xray.scatterer( #34
label="F1B",
site=(-0.780326, -0.921249, -0.073962),
u=(0.000687, 0.000357, 0.000128,
-0.000152, -0.000011, 0.000021)),
xray.scatterer( #35
label="B1B",
site=(-0.795220, -0.758128, -0.075955),
u=(0.000413, 0.000418, 0.000075,
0.000054, 0.000045, 0.000023)),
xray.scatterer( #36
label="F2B",
site=(-0.945140, -0.714626, -0.105820),
u=(0.000584, 0.001371, 0.000108,
0.000420, 0.000067, 0.000134)),
xray.scatterer( #37
label="F3B",
site=(-0.768914, -0.701660, -0.005161),
u=(0.000678, 0.000544, 0.000079,
-0.000000, 0.000090, -0.000021)),
xray.scatterer( #38
label="F1A",
site=(-0.109283, -0.252334, -0.429288),
u=(0.000427, 0.001704, 0.000125,
0.000407, 0.000041, 0.000035)),
xray.scatterer( #39
label="F4A",
site=(-0.341552, -0.262864, -0.502023),
u=(0.000640, 0.000557, 0.000081,
-0.000074, 0.000042, -0.000052)),
xray.scatterer( #40
label="F3A",
site=(-0.324533, -0.142292, -0.393215),
u=(0.000471, 0.001203, 0.000134,
0.000333, -0.000057, -0.000220)),
xray.scatterer( #41
label="F2A",
site=(-0.312838, -0.405405, -0.400231),
u=(0.002822, 0.000831, 0.000092,
-0.000648, 0.000115, 0.000027)),
xray.scatterer( #42
label="B1A",
site=(-0.271589, -0.268874, -0.430724),
u=(0.000643, 0.000443, 0.000079,
0.000040, 0.000052, -0.000034)),
xray.scatterer( #43
label="H5B",
site=(-0.475808, -0.413802, 0.004402),
u=0.005270),
xray.scatterer( #44
label="H6B",
site=(-0.699519, -0.326233, 0.062781),
u=0.019940),
xray.scatterer( #45
label="H3B",
site=(-0.283410, -0.484757, -0.063922),
u=0.029990),
xray.scatterer( #46
label="H1B",
site=(-0.357103, -0.451819, -0.284911),
u=0.031070),
xray.scatterer( #47
label="H10A",
site=(-0.495517, 0.268296, -0.256187),
u=0.027610),
xray.scatterer( #48
label="H2B",
site=(-0.147129, -0.535141, -0.174699),
u=0.017930),
xray.scatterer( #49
label="H7A",
site=(-0.643658, -0.031387, -0.475357),
u=0.020200),
xray.scatterer( #50
label="H1A",
site=(-0.912757, -0.691043, -0.227554),
u=0.033320),
xray.scatterer( #51
label="H7B",
site=(-0.933670, -0.241189, -0.010263),
u=0.021310),
xray.scatterer( #52
label="H11B",
site=(-1.107736, -0.155470, -0.311996),
u=0.041500),
xray.scatterer( #53
label="H9A",
site=(-0.539908, 0.139753, -0.382281),
u=0.007130),
xray.scatterer( #54
label="H10B",
site=(-1.265944, -0.029610, -0.212398),
u=0.030910),
xray.scatterer( #55
label="H3A",
site=(-0.934728, -0.691149, -0.450551),
u=0.038950),
xray.scatterer( #56
label="H5A",
site=(-0.833654, -0.487479, -0.508239),
u=0.031150),
xray.scatterer( #57
label="H6A",
site=(-0.742871, -0.242269, -0.558157),
u=0.050490),
xray.scatterer( #58
label="H9B",
site=(-1.120150, -0.093752, -0.090706),
u=0.039310),
xray.scatterer( #59
label="H11A",
site=(-0.593074, 0.054973, -0.180370),
u=0.055810),
xray.scatterer( #60
label="H2A",
site=(-0.999576, -0.842158, -0.340837),
u=0.057030)
]))
fo_sq = xs0.structure_factors(d_min=0.8).f_calc().norm()
fo_sq = fo_sq.customized_copy(sigmas=flex.double(fo_sq.size(), 1.))
for hydrogen_flag in (True, False):
xs = xs0.deep_copy_scatterers()
if not hydrogen_flag:
xs.select_inplace(~xs.element_selection('H'))
xs.shake_adp()
xs.shake_sites_in_place(rms_difference=0.1)
for sc in xs.scatterers():
sc.flags.set_grad_site(True).set_grad_u_aniso(False)
ls = least_squares.crystallographic_ls(
fo_sq.as_xray_observations(),
constraints.reparametrisation(
structure=xs,
constraints=[],
connectivity_table=smtbx.utils.connectivity_table(xs)),
weighting_scheme=least_squares.unit_weighting(),
origin_fixing_restraints_type=
origin_fixing_restraints.atomic_number_weighting)
ls.build_up()
lambdas = eigensystem.real_symmetric(
ls.normal_matrix_packed_u().matrix_packed_u_as_symmetric()).values()
# assert the restrained L.S. problem is not too ill-conditionned
cond = math.log10(lambdas[0]/lambdas[-1])
msg = ("one heavy element + light elements (real data) %s Hydrogens: %.1f"
% (['without', 'with'][hydrogen_flag], cond))
if verbose: print(msg)
assert cond < worst_condition_number_acceptable, msg
# are esd's for x,y,z coordinates of the same order of magnitude?
var_cart = covariance.orthogonalize_covariance_matrix(
ls.covariance_matrix(),
xs.unit_cell(),
xs.parameter_map())
var_site_cart = covariance.extract_covariance_matrix_for_sites(
flex.size_t_range(len(xs.scatterers())),
var_cart,
xs.parameter_map())
site_esds = var_site_cart.matrix_packed_u_diagonal()
indicators = flex.double()
for i in xrange(0, len(site_esds), 3):
stats = scitbx.math.basic_statistics(site_esds[i:i+3])
indicators.append(stats.bias_corrected_standard_deviation/stats.mean)
assert indicators.all_lt(1)
def exercise_space_group_info():
i = sgtbx.space_group_info("P 1")
assert i.type().number() == 1
i = sgtbx.space_group_info("P -1")
assert i.type().number() == 2
i = sgtbx.space_group_info("P 2", "I", space_group_t_den=24)
assert str(i) == "P 1 1 2"
assert i.group().t_den() == 24
i = sgtbx.space_group_info("P32 (a,b,3c)", space_group_t_den=36)
assert str(i) == "P 32 (a,b,3*c)"
assert i.group().t_den() == 36
i = sgtbx.space_group_info("P 2", "I")
assert str(i) == "P 1 1 2"
i = sgtbx.space_group_info("P 2", "a")
assert str(i) == "P 1 2 1"
assert i.group() == i.type().group()
assert i.reciprocal_space_asu().reference_as_string() \
== "k>=0 and (l>0 or (l==0 and h>=0))"
assert str(i.brick()) == "0<=x<=1/2; 0<=y<1; 0<=z<1"
assert i.wyckoff_table().space_group_type().group() == i.type().group()
assert len(i.structure_seminvariants().vectors_and_moduli()) == 3
assert i.number_of_continuous_allowed_origin_shifts() == 1
for sg_number in (1, 3, 15, 75, 143, 195):
assert approx_equal(
sgtbx.space_group_info(sg_number).any_compatible_unit_cell(
100).volume(), 100)
s = pickle.dumps(i)
j = pickle.loads(s)
assert str(i) == str(j)
i = sgtbx.space_group_info("B 2", "i")
assert not i.is_reference_setting()
assert str(i.change_of_basis_op_to_reference_setting().c()) == "-x,z,y"
assert str(i.reference_setting()) == "C 1 2 1"
assert str(i.as_reference_setting()) == "C 1 2 1"
assert str(i.primitive_setting()) == "C 1 2 1 (-x+y,z,x+y)"
asu = i.direct_space_asu()
assert len(asu.cuts) == 6
assert sgtbx.space_group(asu.hall_symbol) == i.group()
j = i.primitive_setting()
asu = j.direct_space_asu()
assert len(asu.cuts) == 6
assert sgtbx.space_group(asu.hall_symbol) == j.group()
i = sgtbx.space_group_info(number=19)
assert [
str(sgtbx.space_group_info(group=group))
for group in i.reflection_intensity_equivalent_groups()
] == [
"P 2 2 2", "P 2 2 21", "P 21 2 2", "P 2 21 2", "P 21 21 2",
"P 2 21 21", "P 21 2 21", "P 21 21 21"
]
assert len(i.reflection_intensity_equivalent_groups(anomalous_flag=False)) \
== 127
#
i = sgtbx.space_group_info(symbol="C 1 2 1")
assert str(i.change_of_basis_op_to_reference_setting().c()) == "x,y,z"
assert approx_equal(
i.subtract_continuous_allowed_origin_shifts(
translation_frac=[1, 2, 3]), [1, 0, 3])
i = sgtbx.space_group_info(symbol="B 2 1 1")
assert str(i.change_of_basis_op_to_reference_setting().c()) == "z,x,y"
assert approx_equal(
i.subtract_continuous_allowed_origin_shifts(
translation_frac=[1, 2, 3]), [0, 2, 3])
#
for space_group_symbol, addl_smx, uhm in [
("P 21 21 21", "x+1/2,y+1/2,z", "C 2 2 21 (a-1/4,b,c)"),
("C 1 2 1", "x,y+1/2,z", "P 1 2 1 (2*a,2*b,c)")
]:
for f in range(1, 12 + 1):
sg_t_den = sgtbx.sg_t_den * f
cb_r_den = sgtbx.cb_r_den * f
cb_t_den = sgtbx.cb_t_den * f
#
sg_i = sgtbx.space_group_info(symbol=space_group_symbol)
t = sg_i.type()
assert sg_i.type(tidy_cb_op=True) is t
assert sg_i.type(tidy_cb_op=False) is not t
if (f != 1):
t = sg_i.type()
c = t.cb_op().c()
assert c.r().den() == sgtbx.cb_r_den
assert c.t().den() == sgtbx.cb_t_den
for t_den in [cb_t_den, None]:
if (t_den is not None):
tt = sg_i.type(t_den=t_den)
assert tt is not t
else:
assert sg_i.type(t_den=t_den) is tt
c = tt.cb_op().c()
assert c.r().den() == sgtbx.cb_r_den
assert c.t().den() == cb_t_den
for r_den in [cb_r_den, None]:
if (r_den is not None):
tr = sg_i.type(r_den=r_den)
assert tr is not tt
else:
sg_i.type(r_den=r_den) is tr
c = tr.cb_op().c()
assert c.r().den() == cb_r_den
assert c.t().den() == cb_t_den
#
sg_i = sgtbx.space_group_info(symbol=space_group_symbol,
space_group_t_den=sg_t_den)
sgx = sgtbx.space_group(sg_i.group())
rt_mx = sgtbx.rt_mx(addl_smx)
rt_mx = rt_mx.new_denominators(sgx.r_den(), sgx.t_den())
sgx.expand_smx(rt_mx)
sgx_i = sgx.info()
assert str(sgx_i) == uhm
t = sgx_i.type()
c = t.cb_op().c()
assert c.r().den() == cb_r_den
assert c.t().den() == cb_t_den
for r_den, t_den in [(None, None), (cb_r_den, None),
(None, cb_t_den), (cb_r_den, cb_t_den)]:
assert sgx_i.type(r_den=r_den, t_den=t_den) is t
assert sgx_i.type(tidy_cb_op=False, r_den=r_den,
t_den=t_den) is not t
for i, op in enumerate(sgx_i.group()):
assert sgx_i.cif_symmetry_code(op) == "%i" % (i + 1)
assert sgx_i.cif_symmetry_code(op, full_code=True,
sep=" ") == "%i 555" % (i + 1)
tr = [random.randint(-4, 4) for j in range(3)]
rt_mx = sgtbx.rt_mx(
op.r(),
op.t().plus(
sgtbx.tr_vec(tr,
tr_den=1).new_denominator(op.t().den())))
assert sgx_i.cif_symmetry_code(rt_mx, full_code=True) \
== "%i_%i%i%i" %(i+1, 5+tr[0], 5+tr[1], 5+tr[2])
def refined_settings_factory_from_refined_triclinic(params,
experiments,
reflections,
i_setting=None,
lepage_max_delta=5.0,
nproc=1,
refiner_verbosity=0):
assert len(experiments.crystals()) == 1
crystal = experiments.crystals()[0]
used_reflections = copy.deepcopy(reflections)
UC = crystal.get_unit_cell()
from rstbx.dps_core.lepage import iotbx_converter
Lfat = refined_settings_list()
for item in iotbx_converter(UC, lepage_max_delta):
Lfat.append(bravais_setting(item))
supergroup = Lfat.supergroup()
triclinic = Lfat.triclinic()
triclinic_miller = used_reflections['miller_index']
# assert no transformation between indexing and bravais list
assert str(triclinic['cb_op_inp_best']) == "a,b,c"
Nset = len(Lfat)
for j in xrange(Nset):
Lfat[j].setting_number = Nset - j
from cctbx.crystal_orientation import crystal_orientation
from cctbx import sgtbx
from scitbx import matrix
for j in xrange(Nset):
cb_op = Lfat[j]['cb_op_inp_best'].c().as_double_array()[0:9]
orient = crystal_orientation(crystal.get_A(), True)
orient_best = orient.change_basis(matrix.sqr(cb_op).transpose())
constrain_orient = orient_best.constrain(Lfat[j]['system'])
bravais = Lfat[j]["bravais"]
cb_op_best_ref = Lfat[j][
'best_subsym'].change_of_basis_op_to_reference_setting()
space_group = sgtbx.space_group_info(
number=bravais_lattice_to_lowest_symmetry_spacegroup_number[
bravais]).group()
space_group = space_group.change_basis(cb_op_best_ref.inverse())
bravais = str(bravais_types.bravais_lattice(group=space_group))
Lfat[j]["bravais"] = bravais
Lfat[j].unrefined_crystal = dials_crystal_from_orientation(
constrain_orient, space_group)
args = []
for subgroup in Lfat:
args.append((params, subgroup, used_reflections, experiments,
refiner_verbosity))
results = easy_mp.parallel_map(func=refine_subgroup,
iterable=args,
processes=nproc,
method="multiprocessing",
preserve_order=True,
asynchronous=True,
preserve_exception_message=True)
for i, result in enumerate(results):
Lfat[i] = result
identify_likely_solutions(Lfat)
return Lfat
def run(args, out=sys.stdout, validated=False):
show_citation(out=out)
if (len(args) == 0):
master_phil.show(out=out)
print('\nUsage: phenix.map_comparison <CCP4> <CCP4>\n',\
' phenix.map_comparison <CCP4> <MTZ> mtz_label_1=<label>\n',\
' phenix.map_comparison <MTZ 1> mtz_label_1=<label 1> <MTZ 2> mtz_label_2=<label 2>\n', file=out)
sys.exit()
# process arguments
params = None
input_attributes = ['map_1', 'mtz_1', 'map_2', 'mtz_2']
try: # automatic parsing
params = phil.process_command_line_with_files(
args=args, master_phil=master_phil).work.extract()
except Exception: # map_file_def only handles one map phil
from libtbx.phil.command_line import argument_interpreter
arg_int = argument_interpreter(master_phil=master_phil)
command_line_args = list()
map_files = list()
for arg in args:
if (os.path.isfile(arg)):
map_files.append(arg)
else:
command_line_args.append(arg_int.process(arg))
params = master_phil.fetch(sources=command_line_args).extract()
# check if more files are necessary
n_defined = 0
for attribute in input_attributes:
if (getattr(params.input, attribute) is not None):
n_defined += 1
# matches files to phil scope, stops once there is sufficient data
for map_file in map_files:
if (n_defined < 2):
current_map = file_reader.any_file(map_file)
if (current_map.file_type == 'ccp4_map'):
n_defined += 1
if (params.input.map_1 is None):
params.input.map_1 = map_file
elif (params.input.map_2 is None):
params.input.map_2 = map_file
elif (current_map.file_type == 'hkl'):
n_defined += 1
if (params.input.mtz_1 is None):
params.input.mtz_1 = map_file
elif (params.input.mtz_2 is None):
params.input.mtz_2 = map_file
else:
print('WARNING: only the first two files are used', file=out)
break
# validate arguments (GUI sets validated to true, no need to run again)
assert (params is not None)
if (not validated):
validate_params(params)
# ---------------------------------------------------------------------------
# check if maps need to be generated from mtz
n_maps = 0
maps = list()
map_names = list()
for attribute in input_attributes:
filename = getattr(params.input, attribute)
if (filename is not None):
map_names.append(filename)
current_map = file_reader.any_file(filename)
maps.append(current_map)
if (current_map.file_type == 'ccp4_map'):
n_maps += 1
# construct maps, if necessary
crystal_gridding = None
m1 = None
m2 = None
# 1 map, 1 mtz file
if (n_maps == 1):
for current_map in maps:
if (current_map.file_type == 'ccp4_map'):
uc = current_map.file_object.unit_cell()
sg_info = space_group_info(
current_map.file_object.space_group_number)
n_real = current_map.file_object.unit_cell_grid
crystal_gridding = maptbx.crystal_gridding(
uc, space_group_info=sg_info, pre_determined_n_real=n_real)
m1 = current_map.file_object.map_data()
if (crystal_gridding is not None):
label = None
for attribute in [('mtz_1', 'mtz_label_1'),
('mtz_2', 'mtz_label_2')]:
filename = getattr(params.input, attribute[0])
label = getattr(params.input, attribute[1])
if ((filename is not None) and (label is not None)):
break
# labels will match currently open mtz file
for current_map in maps:
if (current_map.file_type == 'hkl'):
m2 = miller.fft_map(
crystal_gridding=crystal_gridding,
fourier_coefficients=current_map.file_server.
get_miller_array(
label)).apply_sigma_scaling().real_map_unpadded()
else:
raise Sorry('Gridding is not defined.')
# 2 mtz files
elif (n_maps == 0):
crystal_symmetry = get_crystal_symmetry(maps[0])
d_min = min(get_d_min(maps[0]), get_d_min(maps[1]))
crystal_gridding = maptbx.crystal_gridding(
crystal_symmetry.unit_cell(),
d_min=d_min,
resolution_factor=params.options.resolution_factor,
space_group_info=crystal_symmetry.space_group_info())
m1 = miller.fft_map(
crystal_gridding=crystal_gridding,
fourier_coefficients=maps[0].file_server.get_miller_array(
params.input.mtz_label_1)).apply_sigma_scaling(
).real_map_unpadded()
m2 = miller.fft_map(
crystal_gridding=crystal_gridding,
fourier_coefficients=maps[1].file_server.get_miller_array(
params.input.mtz_label_2)).apply_sigma_scaling(
).real_map_unpadded()
# 2 maps
else:
m1 = maps[0].file_object.map_data()
m2 = maps[1].file_object.map_data()
# ---------------------------------------------------------------------------
# analyze maps
assert ((m1 is not None) and (m2 is not None))
# show general statistics
s1 = maptbx.more_statistics(m1)
s2 = maptbx.more_statistics(m2)
show_overall_statistics(out=out, s=s1, header="Map 1 (%s):" % map_names[0])
show_overall_statistics(out=out, s=s2, header="Map 2 (%s):" % map_names[1])
cc_input_maps = flex.linear_correlation(x=m1.as_1d(),
y=m2.as_1d()).coefficient()
print("CC, input maps: %6.4f" % cc_input_maps, file=out)
# compute CCpeak
cc_peaks = list()
m1_he = maptbx.volume_scale(map=m1, n_bins=10000).map_data()
m2_he = maptbx.volume_scale(map=m2, n_bins=10000).map_data()
cc_quantile = flex.linear_correlation(x=m1_he.as_1d(),
y=m2_he.as_1d()).coefficient()
print("CC, quantile rank-scaled (histogram equalized) maps: %6.4f" % \
cc_quantile, file=out)
print("Peak correlation:", file=out)
print(" cutoff CCpeak", file=out)
cutoffs = [i / 100.
for i in range(1, 90)] + [i / 1000 for i in range(900, 1000)]
for cutoff in cutoffs:
cc_peak = maptbx.cc_peak(map_1=m1_he, map_2=m2_he, cutoff=cutoff)
print(" %3.2f %7.4f" % (cutoff, cc_peak), file=out)
cc_peaks.append((cutoff, cc_peak))
# compute discrepancy function (D-function)
discrepancies = list()
cutoffs = flex.double(cutoffs)
df = maptbx.discrepancy_function(map_1=m1_he, map_2=m2_he, cutoffs=cutoffs)
print("Discrepancy function:", file=out)
print(" cutoff D", file=out)
for c, d in zip(cutoffs, df):
print(" %3.2f %7.4f" % (c, d), file=out)
discrepancies.append((c, d))
# compute and output histograms
h1 = maptbx.histogram(map=m1, n_bins=10000)
h2 = maptbx.histogram(map=m2, n_bins=10000)
print("Map histograms:", file=out)
print("Map 1 (%s) Map 2 (%s)"%\
(params.input.map_1,params.input.map_2), file=out)
print("(map_value,cdf,frequency) <> (map_value,cdf,frequency)", file=out)
for a1, c1, v1, a2, c2, v2 in zip(h1.arguments(), h1.c_values(),
h1.values(), h2.arguments(),
h2.c_values(), h2.values()):
print("(%9.5f %9.5f %9.5f) <> (%9.5f %9.5f %9.5f)"%\
(a1,c1,v1, a2,c2,v2), file=out)
# store results
s1_dict = create_statistics_dict(s=s1)
s2_dict = create_statistics_dict(s=s2)
results = dict()
inputs = list()
for attribute in input_attributes:
filename = getattr(params.input, attribute)
if (filename is not None):
inputs.append(filename)
assert (len(inputs) == 2)
results['map_files'] = inputs
results['map_statistics'] = (s1_dict, s2_dict)
results['cc_input_maps'] = cc_input_maps
results['cc_quantile'] = cc_quantile
results['cc_peaks'] = cc_peaks
results['discrepancies'] = discrepancies
# TODO, verify h1,h2 are not dicts, e.g. .values is py2/3 compat. I assume it is here
results['map_histograms'] = ((h1.arguments(), h1.c_values(), h1.values()),
(h2.arguments(), h2.c_values(), h2.values()))
return results
def metric_supergroup(group):
return sgtbx.space_group_info(
group=group).type().expand_addl_generators_of_euclidean_normalizer(
True, True).build_derived_acentric_group()
raise
except Exception:
pass
fullprof_out = easy_run.fully_buffered(command="fp2k "+os.path.split(pcrfile)[1]) \
.raise_if_errors() \
.stdout_lines
if (0 or verbose):
for l in fullprof_out:
print(l)
f = open(pcrfile + ".out", "r")
fullprof_out = f.readlines()
f.close()
sys.stderr.flush()
if (0 or verbose):
for l in fullprof_out:
print(l[:-1])
sys.stdout.flush()
os.chdir(old_cwd)
if __name__ == '__main__':
# just a little test for debugging
from cctbx import sgtbx
from cctbx.development import random_structure
xrs = random_structure.xray_structure(
space_group_info=sgtbx.space_group_info(number=1),
elements=["C"] * 10,
u_iso=0.005)
print(list(simulate_powder_pattern(xrs)
[0])) #, filename="/tmp/test.pcr", keep_results=True))
def _mosflm_refine_cell(self, idxr, set_spacegroup=None):
'''Perform the refinement of the unit cell. This will populate
all of the information needed to perform the integration.'''
# FIXME this will die after #1285
#if not self.get_integrater_indexer():
#Debug.write('Replacing indexer of %s with self at %d' % \
#(str(self.get_integrater_indexer()), __line__))
#self.set_integrater_indexer(self)
#idxr = self.get_integrater_indexer()
if not idxr.get_indexer_payload('mosflm_orientation_matrix'):
raise RuntimeError('unexpected situation in indexing')
lattice = idxr.get_indexer_lattice()
mosaic = idxr.get_indexer_mosaic()
cell = idxr.get_indexer_cell()
beam_centre = idxr.get_indexer_beam_centre()
# bug # 3174 - if mosaic is very small (here defined to be
# 0.25 x osc_width) then set to this minimum value.
phi_width = idxr.get_phi_width()
if mosaic < 0.25 * phi_width:
mosaic = 0.25 * phi_width
if idxr.get_indexer_payload('mosflm_beam_centre'):
beam_centre = idxr.get_indexer_payload('mosflm_beam_centre')
distance = idxr.get_indexer_distance()
matrix = idxr.get_indexer_payload('mosflm_orientation_matrix')
integration_params = idxr.get_indexer_payload(
'mosflm_integration_parameters')
if integration_params is None:
integration_params = {}
if integration_params:
if 'separation' in integration_params:
self.set_refiner_parameter(
'mosflm', 'separation',
'%f %f' % tuple(integration_params['separation']))
if 'raster' in integration_params:
self.set_refiner_parameter(
'mosflm', 'raster',
'%d %d %d %d %d' % tuple(integration_params['raster']))
idxr.set_indexer_payload('mosflm_integration_parameters', None)
spacegroup_number = lattice_to_spacegroup(lattice)
# copy these into myself for later reference, if indexer
# is not myself - everything else is copied via the
# cell refinement process...
from cctbx import sgtbx
from dxtbx.model import Crystal
from dxtbx.model.detector_helpers import set_mosflm_beam_centre
experiment = idxr.get_indexer_experiment_list()[0]
set_mosflm_beam_centre(experiment.detector, experiment.beam,
beam_centre)
space_group = sgtbx.space_group_info(number=spacegroup_number).group()
a, b, c = experiment.crystal.get_real_space_vectors()
experiment.crystal = Crystal(a, b, c, space_group=space_group)
# FIXME surely these have been assigned further up?!
if not self._mosflm_cell_ref_images:
self._mosflm_cell_ref_images = self._refine_select_images(mosaic)
f = open(
os.path.join(self.get_working_directory(),
'xiaindex-%s.mat' % lattice), 'w')
for m in matrix:
f.write(m)
f.close()
# then start the cell refinement
refiner = MosflmRefineCell()
refiner.set_working_directory(self.get_working_directory())
auto_logfiler(refiner)
if self._mosflm_gain:
refiner.set_gain(self._mosflm_gain)
refiner.set_template(os.path.basename(idxr.get_template()))
refiner.set_directory(idxr.get_directory())
refiner.set_input_mat_file('xiaindex-%s.mat' % lattice)
refiner.set_output_mat_file('xiarefine.mat')
refiner.set_beam_centre(beam_centre)
refiner.set_unit_cell(cell)
refiner.set_distance(distance)
if set_spacegroup:
refiner.set_space_group_number(set_spacegroup)
else:
refiner.set_space_group_number(spacegroup_number)
# FIXME 18/JUN/08 - it may help to have an overestimate
# of the mosaic spread in here as it *may* refine down
# better than up... - this is not a good idea as it may
# also not refine at all! - 12972 # integration failed
# Bug # 3103
if self._mosflm_cell_ref_double_mosaic:
mosaic *= 2.0
refiner.set_mosaic(mosaic)
# if set, use the resolution for cell refinement - see
# bug # 2078...
if self._mosflm_cell_ref_resolution:
refiner.set_resolution(self._mosflm_cell_ref_resolution)
refiner.set_fix_mosaic(self._mosflm_postref_fix_mosaic)
# note well that the beam centre is coming from indexing so
# should be already properly handled
#if idxr.get_wavelength_prov() == 'user':
#refiner.set_wavelength(idxr.get_wavelength())
# belt + braces mode - only to be used when considering failover,
# will run an additional step of autoindexing prior to cell
# refinement, to be used only after proving that not going it
# will result in cell refinement failure - will use the first
# wedge... N.B. this is only useful if the indexer is Labelit
# not Mosflm...
refiner.set_add_autoindex(self._mosflm_cell_ref_add_autoindex)
# get all of the stored parameter values
parameters = self.get_refiner_parameters('mosflm')
refiner.update_parameters(parameters)
detector = idxr.get_detector()
detector_width, detector_height = detector[0].get_image_size_mm()
lim_x = 0.5 * detector_width
lim_y = 0.5 * detector_height
Debug.write('Scanner limits: %.1f %.1f' % (lim_x, lim_y))
refiner.set_limits(lim_x, lim_y)
refiner.set_images(self._mosflm_cell_ref_images)
failover = PhilIndex.params.xia2.settings.failover
if failover and not self._mosflm_cell_ref_add_autoindex:
refiner.set_ignore_cell_refinement_failure(True)
refiner.run()
# then look to see if the cell refinement worked ok - if it
# didn't then this may indicate that the lattice was wrongly
# selected.
cell_refinement_ok = refiner.cell_refinement_ok()
if not cell_refinement_ok:
Debug.write('Repeating cell refinement...')
self.set_integrater_prepare_done(False)
self._mosflm_cell_ref_add_autoindex = True
return [0.0], [0.0]
rms_values = refiner.get_rms_values()
background_residual = refiner.get_background_residual()
self._refinr_cell = refiner.get_refined_unit_cell()
distance = refiner.get_refined_distance2()
experiment = idxr.get_indexer_experiment_list()[0]
from xia2.Wrappers.Mosflm.AutoindexHelpers import set_distance
set_distance(experiment.detector, distance)
self.set_refiner_parameter('mosflm', 'distortion yscale',
refiner.get_refined_distortion_yscale())
self.set_refiner_parameter('mosflm', 'raster', refiner.get_raster())
#integration_params['distortion yscale'] \
#= refiner.get_refined_distortion_yscale()
#integration_params['raster'] = refiner.get_raster()
separation = refiner.get_separation()
if separation is not None:
self.set_refiner_parameter('mosflm', 'separation',
'%s %s' % refiner.get_separation())
#integration_params['separation'] = refiner.get_separation()
self.set_refiner_parameter('mosflm', 'beam',
'%s %s' % refiner.get_refined_beam_centre())
self.set_refiner_parameter('mosflm', 'distance',
refiner.get_refined_distance())
self.set_refiner_parameter('mosflm', 'distortion tilt',
refiner.get_refined_distortion_tilt())
self.set_refiner_parameter('mosflm', 'distortion twist',
refiner.get_refined_distortion_twist())
integration_params['beam'] = tuple(
float(b) for b in refiner.get_refined_beam_centre())
integration_params['distance'] = refiner.get_refined_distance()
integration_params[
'distortion tilt'] = refiner.get_refined_distortion_tilt()
integration_params[
'distortion twist'] = refiner.get_refined_distortion_twist()
idxr._indxr_mosaic = refiner.get_refined_mosaic()
idxr.set_indexer_payload(
'mosflm_orientation_matrix',
open(os.path.join(self.get_working_directory(), 'xiarefine.mat'),
'r').readlines())
self.set_refiner_payload(
'mosflm_orientation_matrix',
idxr.get_indexer_payload('mosflm_orientation_matrix'))
self.set_refiner_payload('mosaic', refiner.get_refined_mosaic())
self.set_refiner_payload('beam', integration_params['beam'])
self.set_refiner_payload('distance', integration_params['distance'])
from xia2.Wrappers.Mosflm.AutoindexHelpers import crystal_model_from_mosflm_mat
# make a dxtbx crystal_model object from the mosflm matrix
experiment = idxr.get_indexer_experiment_list()[0]
crystal_model = crystal_model_from_mosflm_mat(
idxr._indxr_payload['mosflm_orientation_matrix'],
unit_cell=refiner.get_refined_unit_cell(),
space_group=experiment.crystal.get_space_group())
experiment.crystal = crystal_model
#self.set_refiner_payload(
#'mosflm_integration_parameters', integration_params)
self._refinr_refined_experiment_list = ExperimentList([experiment])
return rms_values, background_residual
fill_missing=False)
crystal_gridding = fmodel.f_obs().crystal_gridding(
d_min=fmodel.f_obs().d_min(),
symmetry_flags=maptbx.use_space_group_symmetry,
resolution_factor=1. / 3)
# compute OMIT map
r = cfom.run(crystal_gridding=crystal_gridding,
fmodel=fmodel.deep_copy(),
full_resolution_map=False,
max_boxes=70,
neutral_volume_box_cushion_width=0,
box_size_as_fraction=0.3,
log=False)
ccs = get_cc(mc1=mc1, mc2=r.map_coefficients(filter_noise=False), xrs=xrs)
assert flex.mean(ccs) > 0.8
print " CC(min/max,mean)", ccs.min_max_mean().as_tuple()
def run_call_back(flags, space_group_info):
run(space_group_info)
if (__name__ == "__main__"):
t0 = time.time()
debug_utils.parse_options_loop_space_groups(sys.argv[1:],
run_call_back,
symbols_to_stdout=True,
symbols_to_stderr=False)
run(sgtbx.space_group_info("R3:R"))
print "Time: %6.4f" % (time.time() - t0)
def run(args,
command_name="phenix.reflection_file_converter",
simply_return_all_miller_arrays=False):
command_line = (option_parser(
usage="%s [options] reflection_file ..." % command_name,
description="Example: %s w1.sca --mtz ." % command_name
).enable_symmetry_comprehensive().option(
None,
"--weak_symmetry",
action="store_true",
default=False,
help="symmetry on command line is weaker than symmetry found in files"
).enable_resolutions().option(
None,
"--label",
action="store",
type="string",
help="Substring of reflection data label or number",
metavar="STRING"
).option(
None,
"--non_anomalous",
action="store_true",
default=False,
help="Averages Bijvoet mates to obtain a non-anomalous array"
).option(
None,
"--r_free_label",
action="store",
type="string",
help="Substring of reflection data label or number",
metavar="STRING"
).option(
None,
"--r_free_test_flag_value",
action="store",
type="int",
help="Value in R-free array indicating assignment to free set.",
metavar="FLOAT"
).option(
None,
"--generate_r_free_flags",
action="store_true",
default=False,
help="Generates a new array of random R-free flags"
" (MTZ and CNS output only)."
).option(
None,
"--use_lattice_symmetry_in_r_free_flag_generation",
dest="use_lattice_symmetry_in_r_free_flag_generation",
action="store_true",
default=True,
help="group twin/pseudo symmetry related reflections together"
" in r-free set (this is the default)."
).option(
None,
"--no_lattice_symmetry_in_r_free_flag_generation",
dest="use_lattice_symmetry_in_r_free_flag_generation",
action="store_false",
help="opposite of --use-lattice-symmetry-in-r-free-flag-generation"
).option(
None,
"--r_free_flags_fraction",
action="store",
default=0.10,
type="float",
help="Target fraction free/work reflections (default: 0.10).",
metavar="FLOAT"
).option(
None,
"--r_free_flags_max_free",
action="store",
default=2000,
type="int",
help="Maximum number of free reflections (default: 2000).",
metavar="INT"
).option(
None,
"--r_free_flags_format",
choices=(
"cns", "ccp4",
"shelx"),
default="cns",
help="Convention for generating R-free flags",
metavar="cns|ccp4"
).option(
None,
"--output_r_free_label",
action="store",
type="string",
help=
"Label for newly generated R-free flags (defaults to R-free-flags)",
default="R-free-flags",
metavar="STRING"
).option(
None,
"--random_seed",
action="store",
type="int",
help="Seed for random number generator (affects generation of"
" R-free flags).",
metavar="INT"
).option(
None,
"--change_of_basis",
action="store",
type="string",
help="Change-of-basis operator: h,k,l or x,y,z"
" or to_reference_setting, to_primitive_setting, to_niggli_cell,"
" to_inverse_hand",
metavar="STRING"
).option(
None,
"--eliminate_invalid_indices",
action="store_true",
default=False,
help="Remove indices which are invalid given the change of basis desired"
).option(
None,
"--expand_to_p1",
action="store_true",
default=False,
help="Generates all symmetrically equivalent reflections."
" The space group symmetry is reset to P1."
" May be used in combination with --change_to_space_group to"
" lower the symmetry."
).option(
None,
"--change_to_space_group",
action="store",
type="string",
help="Changes the space group and merges equivalent reflections"
" if necessary",
metavar="SYMBOL|NUMBER"
).option(
None,
"--write_mtz_amplitudes",
action="store_true",
default=False,
help="Converts intensities to amplitudes before writing MTZ format;"
" requires --mtz_root_label"
).option(
None,
"--write_mtz_intensities",
action="store_true",
default=False,
help="Converts amplitudes to intensities before writing MTZ format;"
" requires --mtz_root_label"
).option(
None,
"--remove_negatives",
action="store_true",
default=False,
help="Remove negative intensities or amplitudes from the data set"
).option(
None,
"--massage_intensities",
action="store_true",
default=False,
help="'Treat' negative intensities to get a positive amplitude."
" |Fnew| = sqrt((Io+sqrt(Io**2 +2sigma**2))/2.0). Requires"
" intensities as input and the flags --mtz,"
" --write_mtz_amplitudes and --mtz_root_label."
).option(
None,
"--scale_max",
action="store",
type="float",
help="Scales data such that the maximum is equal to the given value",
metavar="FLOAT"
).option(
None,
"--scale_factor",
action="store",
type="float",
help="Multiplies data with the given factor",
metavar="FLOAT"
).option(
None,
"--sca",
action="store",
type="string",
help=
"write data to Scalepack FILE ('--sca .' copies name of input file)",
metavar="FILE"
).option(
None,
"--mtz",
action="store",
type="string",
help="write data to MTZ FILE ('--mtz .' copies name of input file)",
metavar="FILE"
).option(
None,
"--mtz_root_label",
action="store",
type="string",
help="Root label for MTZ file (e.g. Fobs)",
metavar="STRING"
).option(
None,
"--cns",
action="store",
type="string",
help="write data to CNS FILE ('--cns .' copies name of input file)",
metavar="FILE"
).option(
None,
"--shelx",
action="store",
type="string",
help="write data to SHELX FILE ('--shelx .' copies name of input file)",
metavar="FILE")).process(args=args)
co = command_line.options
if (co.random_seed is not None):
random.seed(co.random_seed)
flex.set_random_seed(value=co.random_seed)
if (co.write_mtz_amplitudes and co.write_mtz_intensities):
print()
print("--write_mtz_amplitudes and --write_mtz_intensities" \
" are mutually exclusive.")
print()
return None
if (co.write_mtz_amplitudes or co.write_mtz_intensities):
if (co.mtz_root_label is None):
print()
print("--write_mtz_amplitudes and --write_mtz_intensities" \
" require --mtz_root_label.")
print()
return None
if (co.scale_max is not None and co.scale_factor is not None):
print()
print("--scale_max and --scale_factor are mutually exclusive.")
print()
return None
if (len(command_line.args) == 0):
command_line.parser.show_help()
return None
all_miller_arrays = reflection_file_reader.collect_arrays(
file_names=command_line.args,
crystal_symmetry=None,
force_symmetry=False,
merge_equivalents=False,
discard_arrays=False,
verbose=1)
if (simply_return_all_miller_arrays):
return all_miller_arrays
if (len(all_miller_arrays) == 0):
print()
print("No reflection data found in input file%s." %
(plural_s(len(command_line.args))[1]))
print()
return None
label_table = reflection_file_utils.label_table(
miller_arrays=all_miller_arrays)
selected_array = label_table.select_array(label=co.label,
command_line_switch="--label")
if (selected_array is None): return None
r_free_flags = None
r_free_info = None
if (co.r_free_label is not None):
r_free_flags = label_table.match_data_label(
label=co.r_free_label, command_line_switch="--r_free_label")
if (r_free_flags is None):
return None
r_free_info = str(r_free_flags.info())
if (not r_free_flags.is_bool_array()):
test_flag_value = reflection_file_utils.get_r_free_flags_scores(
miller_arrays=[r_free_flags],
test_flag_value=co.r_free_test_flag_value).test_flag_values[0]
if (test_flag_value is None):
if (co.r_free_test_flag_value is None):
raise Sorry(
"Cannot automatically determine r_free_test_flag_value."
" Please use --r_free_test_flag_value to specify a value."
)
else:
raise Sorry("Invalid --r_free_test_flag_value.")
r_free_flags = r_free_flags.customized_copy(
data=(r_free_flags.data() == test_flag_value))
print("Selected data:")
print(" ", selected_array.info())
print(" Observation type:", selected_array.observation_type())
print()
if (r_free_info is not None):
print("R-free flags:")
print(" ", r_free_info)
print()
processed_array = selected_array.customized_copy(
crystal_symmetry=selected_array.join_symmetry(
other_symmetry=command_line.symmetry,
force=not co.weak_symmetry)).set_observation_type(
selected_array.observation_type())
if (r_free_flags is not None):
r_free_flags = r_free_flags.customized_copy(
crystal_symmetry=processed_array)
print("Input crystal symmetry:")
crystal.symmetry.show_summary(processed_array, prefix=" ")
print()
if (processed_array.unit_cell() is None):
command_line.parser.show_help()
print(
"Unit cell parameters unknown. Please use --symmetry or --unit_cell."
)
print()
return None
if (processed_array.space_group_info() is None):
command_line.parser.show_help()
print("Space group unknown. Please use --symmetry or --space_group.")
print()
return None
if (r_free_flags is not None):
r_free_flags = r_free_flags.customized_copy(
crystal_symmetry=processed_array)
if (co.change_of_basis is not None):
processed_array, cb_op = processed_array.apply_change_of_basis(
change_of_basis=co.change_of_basis,
eliminate_invalid_indices=co.eliminate_invalid_indices)
if (r_free_flags is not None):
r_free_flags = r_free_flags.change_basis(cb_op=cb_op)
if (not processed_array.is_unique_set_under_symmetry()):
print("Merging symmetry-equivalent values:")
merged = processed_array.merge_equivalents()
merged.show_summary(prefix=" ")
print()
processed_array = merged.array()
del merged
processed_array.show_comprehensive_summary(prefix=" ")
print()
if (r_free_flags is not None
and not r_free_flags.is_unique_set_under_symmetry()):
print("Merging symmetry-equivalent R-free flags:")
merged = r_free_flags.merge_equivalents()
merged.show_summary(prefix=" ")
print()
r_free_flags = merged.array()
del merged
r_free_flags.show_comprehensive_summary(prefix=" ")
print()
if (co.expand_to_p1):
print("Expanding symmetry and resetting space group to P1:")
if (r_free_flags is not None):
raise Sorry(
"--expand_to_p1 not supported for arrays of R-free flags.")
processed_array = processed_array.expand_to_p1()
processed_array.show_comprehensive_summary(prefix=" ")
print()
if (co.change_to_space_group is not None):
if (r_free_flags is not None):
raise Sorry(
"--change_to_space_group not supported for arrays of R-free flags."
)
new_space_group_info = sgtbx.space_group_info(
symbol=co.change_to_space_group)
print("Change to space group:", new_space_group_info)
new_crystal_symmetry = crystal.symmetry(
unit_cell=processed_array.unit_cell(),
space_group_info=new_space_group_info,
assert_is_compatible_unit_cell=False)
if (not new_crystal_symmetry.unit_cell().is_similar_to(
processed_array.unit_cell())):
print(" *************")
print(" W A R N I N G")
print(" *************")
print(
" Unit cell parameters adapted to new space group symmetry are"
)
print(" significantly different from input unit cell parameters:")
print(" Input unit cell parameters:", \
processed_array.unit_cell())
print(" Adapted unit cell parameters:", \
new_crystal_symmetry.unit_cell())
processed_array = processed_array.customized_copy(
crystal_symmetry=new_crystal_symmetry)
print()
if (not processed_array.is_unique_set_under_symmetry()):
print(" Merging values symmetry-equivalent under new symmetry:")
merged = processed_array.merge_equivalents()
merged.show_summary(prefix=" ")
print()
processed_array = merged.array()
del merged
processed_array.show_comprehensive_summary(prefix=" ")
print()
if (processed_array.anomalous_flag() and co.non_anomalous):
print("Converting data array from anomalous to non-anomalous.")
if (not processed_array.is_xray_intensity_array()):
processed_array = processed_array.average_bijvoet_mates()
else:
processed_array = processed_array.average_bijvoet_mates()
processed_array.set_observation_type_xray_intensity()
if (r_free_flags is not None and r_free_flags.anomalous_flag()
and co.non_anomalous):
print("Converting R-free flags from anomalous to non-anomalous.")
r_free_flags = r_free_flags.average_bijvoet_mates()
d_max = co.low_resolution
d_min = co.resolution
if (d_max is not None or d_min is not None):
if (d_max is not None):
print("Applying low resolution cutoff: d_max=%.6g" % d_max)
if (d_min is not None):
print("Applying high resolution cutoff: d_min=%.6g" % d_min)
processed_array = processed_array.resolution_filter(d_max=d_max,
d_min=d_min)
print("Number of reflections:", processed_array.indices().size())
print()
if (co.scale_max is not None):
print("Scaling data such that the maximum value is: %.6g" %
co.scale_max)
processed_array = processed_array.apply_scaling(
target_max=co.scale_max)
print()
if (co.scale_factor is not None):
print("Multiplying data with the factor: %.6g" % co.scale_factor)
processed_array = processed_array.apply_scaling(factor=co.scale_factor)
print()
if (([co.remove_negatives, co.massage_intensities]).count(True) == 2):
raise Sorry("It is not possible to use --remove_negatives and"
" --massage_intensities at the same time.")
if (co.remove_negatives):
if processed_array.is_real_array():
print("Removing negatives items")
processed_array = processed_array.select(
processed_array.data() > 0)
if processed_array.sigmas() is not None:
processed_array = processed_array.select(
processed_array.sigmas() > 0)
else:
raise Sorry(
"--remove_negatives not applicable to complex data arrays.")
if (co.massage_intensities):
if processed_array.is_real_array():
if processed_array.is_xray_intensity_array():
if (co.mtz is not None):
if (co.write_mtz_amplitudes):
print(
"The supplied intensities will be used to estimate"
)
print(" amplitudes in the following way: ")
print(
" Fobs = Sqrt[ (Iobs + Sqrt(Iobs**2 + 2sigmaIobs**2))/2 ]"
)
print(" Sigmas are estimated in a similar manner.")
print()
processed_array = processed_array.enforce_positive_amplitudes(
)
else:
raise Sorry(
"--write_mtz_amplitudes has to be specified when using"
" --massage_intensities")
else:
raise Sorry(
"--mtz has to be used when using --massage_intensities"
)
else:
raise Sorry(
"Intensities must be supplied when using the option"
" --massage_intensities")
else:
raise Sorry(
"--massage_intensities not applicable to complex data arrays.")
if (not co.generate_r_free_flags):
if (r_free_flags is None):
r_free_info = []
else:
if (r_free_flags.anomalous_flag() !=
processed_array.anomalous_flag()):
if (processed_array.anomalous_flag()): is_not = ("", " not")
else: is_not = (" not", "")
raise Sorry(
"The data array is%s anomalous but the R-free array is%s.\n"
% is_not + " Please try --non_anomalous.")
r_free_info = ["R-free flags source: " + r_free_info]
if (not r_free_flags.indices().all_eq(processed_array.indices())):
processed_array = processed_array.map_to_asu()
r_free_flags = r_free_flags.map_to_asu().common_set(
processed_array)
n_missing_r_free_flags = processed_array.indices().size() \
- r_free_flags.indices().size()
if (n_missing_r_free_flags != 0):
raise Sorry(
"R-free flags not compatible with data array:"
" missing flag for %d reflections selected for output."
% n_missing_r_free_flags)
else:
if (r_free_flags is not None):
raise Sorry(
"--r_free_label and --generate_r_free_flags are mutually exclusive."
)
print("Generating a new array of R-free flags:")
r_free_flags = processed_array.generate_r_free_flags(
fraction=co.r_free_flags_fraction,
max_free=co.r_free_flags_max_free,
use_lattice_symmetry=co.
use_lattice_symmetry_in_r_free_flag_generation,
format=co.r_free_flags_format)
test_flag_value = True
if (co.r_free_flags_format == "ccp4"):
test_flag_value = 0
elif (co.r_free_flags_format == "shelx"):
test_flag_value = -1
r_free_as_bool = r_free_flags.customized_copy(
data=r_free_flags.data() == test_flag_value)
r_free_info = ["R-free flags generated by %s:" % command_name]
r_free_info.append(" " + date_and_time())
r_free_info.append(" fraction: %.6g" % co.r_free_flags_fraction)
r_free_info.append(" max_free: %s" % str(co.r_free_flags_max_free))
r_free_info.append(" size of work set: %d" %
r_free_as_bool.data().count(False))
r_free_info.append(" size of free set: %d" %
r_free_as_bool.data().count(True))
r_free_info_str = StringIO()
r_free_as_bool.show_r_free_flags_info(prefix=" ", out=r_free_info_str)
if (co.r_free_flags_format == "ccp4"):
r_free_info.append(" convention: CCP4 (test=0, work=1-%d)" %
flex.max(r_free_flags.data()))
elif (co.r_free_flags_format == "shelx"):
r_free_info.append(" convention: SHELXL (test=-1, work=1)")
else:
r_free_info.append(" convention: CNS/X-PLOR (test=1, work=0)")
print("\n".join(r_free_info[2:4]))
print(r_free_info[-1])
print(r_free_info_str.getvalue())
print()
n_output_files = 0
if (co.sca is not None):
if (co.generate_r_free_flags):
raise Sorry("Cannot write R-free flags to Scalepack file.")
file_name = reflection_file_utils.construct_output_file_name(
input_file_names=[selected_array.info().source],
user_file_name=co.sca,
file_type_label="Scalepack",
file_extension="sca")
print("Writing Scalepack file:", file_name)
iotbx.scalepack.merge.write(file_name=file_name,
miller_array=processed_array)
n_output_files += 1
print()
if (co.mtz is not None):
file_name = reflection_file_utils.construct_output_file_name(
input_file_names=[selected_array.info().source],
user_file_name=co.mtz,
file_type_label="MTZ",
file_extension="mtz")
print("Writing MTZ file:", file_name)
mtz_history_buffer = flex.std_string()
mtz_history_buffer.append(date_and_time())
mtz_history_buffer.append("> program: %s" % command_name)
mtz_history_buffer.append(
"> input file name: %s" %
os.path.basename(selected_array.info().source))
mtz_history_buffer.append(
"> input directory: %s" %
os.path.dirname(os.path.abspath(selected_array.info().source)))
mtz_history_buffer.append("> input labels: %s" %
selected_array.info().label_string())
mtz_output_array = processed_array
if (co.write_mtz_amplitudes):
if (not mtz_output_array.is_xray_amplitude_array()):
print(" Converting intensities to amplitudes.")
mtz_output_array = mtz_output_array.f_sq_as_f()
mtz_history_buffer.append(
"> Intensities converted to amplitudes.")
elif (co.write_mtz_intensities):
if (not mtz_output_array.is_xray_intensity_array()):
print(" Converting amplitudes to intensities.")
mtz_output_array = mtz_output_array.f_as_f_sq()
mtz_history_buffer.append(
"> Amplitudes converted to intensities.")
column_root_label = co.mtz_root_label
if (column_root_label is None):
# XXX 2013-03-29: preserve original root label by default
# XXX 2014-12-16: skip trailing "(+)" in root_label if anomalous
column_root_label = selected_array.info().labels[0]
column_root_label = remove_anomalous_suffix_if_necessary(
miller_array=selected_array, column_root_label=column_root_label)
mtz_dataset = mtz_output_array.as_mtz_dataset(
column_root_label=column_root_label)
del mtz_output_array
if (r_free_flags is not None):
mtz_dataset.add_miller_array(
miller_array=r_free_flags,
column_root_label=co.output_r_free_label)
for line in r_free_info:
mtz_history_buffer.append("> " + line)
mtz_history_buffer.append("> output file name: %s" %
os.path.basename(file_name))
mtz_history_buffer.append("> output directory: %s" %
os.path.dirname(os.path.abspath(file_name)))
mtz_object = mtz_dataset.mtz_object()
mtz_object.add_history(mtz_history_buffer)
mtz_object.write(file_name=file_name)
n_output_files += 1
print()
if (co.cns is not None):
file_name = reflection_file_utils.construct_output_file_name(
input_file_names=[selected_array.info().source],
user_file_name=co.cns,
file_type_label="CNS",
file_extension="cns")
print("Writing CNS file:", file_name)
processed_array.export_as_cns_hkl(
file_object=open(file_name, "w"),
file_name=file_name,
info=["source of data: " + str(selected_array.info())] +
r_free_info,
r_free_flags=r_free_flags)
n_output_files += 1
print()
if (co.shelx is not None):
if (co.generate_r_free_flags):
raise Sorry("Cannot write R-free flags to SHELX file.")
file_name = reflection_file_utils.construct_output_file_name(
input_file_names=[selected_array.info().source],
user_file_name=co.shelx,
file_type_label="SHELX",
file_extension="shelx")
print("Writing SHELX file:", file_name)
processed_array.as_amplitude_array().export_as_shelx_hklf(
open(file_name, "w"))
n_output_files += 1
print()
if (n_output_files == 0):
command_line.parser.show_help()
print("Please specify at least one output file format,", end=' ')
print("e.g. --mtz, --sca, etc.")
print()
return None
return processed_array
def OnChangeSpaceGroup(self, event):
sg_sel = str(self.sg_ctrl.GetStringSelection())
if (sg_sel != self._last_sg_sel):
from cctbx import sgtbx
sg_info = sgtbx.space_group_info(sg_sel)
self.parent.set_space_group(sg_info)
"P-1", # space groups for all 14 Bravais lattices
"P2/m",
"C2/m",
"Pmmm",
"Cmmm",
"Fmmm",
"Immm",
"P4/mmm",
"I4/mmm",
"R-3m",
"P6/mmm",
"Pm-3m",
"Im-3m",
"Fm-3m",
):
sgi = sgtbx.space_group_info(symbol=sg)
cs = sgi.any_compatible_crystal_symmetry(volume=1000)
ms = cs.build_miller_set(anomalous_flag=False, d_min=dmin)
#ms.show_summary()
spcg = ("%s" % ms.space_group_info()).split(':')[0]
print(spcg)
fp.write("'%s': [\n" % spcg)
fp.write("%s ,\n" % ms.unit_cell())
hkllist = {}
for hkl, d in ms.d_spacings():
if hkllist.has_key(d):
hkllist[d].append(hkl)
print(hkllist[d])
else:
hkllist[d] = [
hkl,
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 parse(self, int_lp):
re_im = re.compile(
"^ (.....) 0 +([0-9\.]+) +([0-9]+) +([0-9]+) +([0-9]+) +([0-9]+) +([0-9]+) +([0-9\.]+) +([0-9\.]+)"
)
re_cell = re.compile(
"^ UNIT CELL PARAMETERS *([0-9\.]+) *([0-9\.]+) *([0-9\.]+) *([0-9\.]+) *([0-9\.]+) *([0-9\.]+)"
)
re_rotation = re.compile(
"^ CRYSTAL ROTATION OFF FROM INITIAL ORIENTATION *([-0-9\.]+) *([-0-9\.]+) *([-0-9\.]+)"
) #
re_mosaicity = re.compile(
"^ CRYSTAL MOSAICITY \(DEGREES\) *([0-9\.]+)") #
re_axis = re.compile(
"^ LAB COORDINATES OF ROTATION AXIS *([-0-9\.]+) *([-0-9\.]+) *([-0-9\.]+)"
) #
re_beam = re.compile(
"^ DIRECT BEAM COORDINATES \(REC\. ANGSTROEM\) *([-0-9\.]+) *([-0-9\.]+) *([-0-9\.]+)"
) #
re_dist = re.compile(
"^ CRYSTAL TO DETECTOR DISTANCE \(mm\) *([-0-9\.]+)")
re_dev_spot = re.compile(
"^ STANDARD DEVIATION OF SPOT POSITION \(PIXELS\) *([0-9\.]+)")
re_dev_spindle = re.compile(
"^ STANDARD DEVIATION OF SPINDLE POSITION \(DEGREES\) *([0-9\.]+)")
re_orig = re.compile(
"^ DETECTOR ORIGIN \(PIXELS\) AT *([0-9\.]+) *([0-9\.]+)")
images = [] # as key of params
self.cell_changes = []
self.blockparams = collections.OrderedDict()
clear_flag = False
self.frames = []
self.scales, self.overloads, self.strongs, self.rejecteds, self.sigmads, self.sigmars = [], [], [], [], [], []
self.space_group = None
# Read INTEGRATE.LP file
for l in open(int_lp):
r_im = re_im.search(l)
r_cell = re_cell.search(l)
r_rotation = re_rotation.search(l)
r_dist = re_dist.search(l)
r_spot = re_dev_spot.search(l)
r_spindle = re_dev_spindle.search(l)
r_orig = re_orig.search(l)
if l.startswith(" SPACE_GROUP_NUMBER="):
sgnum = int(l.strip().split()[-1])
if sgnum > 0:
self.space_group = sgtbx.space_group_info(sgnum).group()
if r_im:
if clear_flag:
images = []
clear_flag = False
image, scale, nbkg, novl, newald, nstrong, nrej, sigmad, sigmar = r_im.groups(
)
images.append(int(image))
# for plot
self.frames.append(int(image))
self.scales.append(scale)
self.overloads.append(int(novl))
self.strongs.append(int(nstrong))
self.rejecteds.append(int(nrej))
self.sigmads.append(sigmad)
self.sigmars.append(sigmar)
if r_cell:
#a, b, c, alpha, beta, gamma = r_cell.groups()
self.blockparams.setdefault(tuple(images),
{})["cell"] = r_cell.groups()
self.cell_changes.append((images, r_cell.groups()))
clear_flag = True
if r_rotation:
self.blockparams.setdefault(
tuple(images), {})["rotation"] = r_rotation.groups()
misset = rotations_to_missetting_angles(
map(float, r_rotation.groups()))
self.blockparams.setdefault(tuple(images), {})["misset"] = map(
lambda x: "%.2f" % x, misset)
clear_flag = True
if r_dist:
self.blockparams.setdefault(tuple(images),
{})["dist"] = r_dist.group(1)
clear_flag = True
if r_spot:
self.blockparams.setdefault(tuple(images),
{})["spot"] = r_spot.group(1)
clear_flag = True
if r_spindle:
self.blockparams.setdefault(tuple(images),
{})["spindle"] = r_spindle.group(1)
clear_flag = True
if r_orig:
self.blockparams.setdefault(tuple(images),
{})["orig"] = r_orig.groups()
clear_flag = True
if l.startswith(" SIGMAB (degree)"):
self.blockparams.setdefault(
tuple(images), {})["sigmab9"] = l.strip().split()[-9:]
clear_flag = True
if l.startswith(" SIGMAR (degree)"):
self.blockparams.setdefault(
tuple(images), {})["sigmar9"] = l.strip().split()[-9:]
clear_flag = True
def exercise_restrained_refinement(options):
import random
random.seed(1)
flex.set_random_seed(1)
xs0 = smtbx.development.random_xray_structure(
sgtbx.space_group_info('P1'),
n_scatterers=options.n_scatterers,
elements="random")
for sc in xs0.scatterers():
sc.flags.set_grad_site(True)
sc0 = xs0.scatterers()
uc = xs0.unit_cell()
mi = xs0.build_miller_set(anomalous_flag=False, d_min=options.resolution)
fo_sq = mi.structure_factors_from_scatterers(
xs0, algorithm="direct").f_calc().norm()
fo_sq = fo_sq.customized_copy(sigmas=flex.double(fo_sq.size(), 1))
i, j, k, l = random.sample(range(options.n_scatterers), 4)
bond_proxies = geometry_restraints.shared_bond_simple_proxy()
w = 1e9
d_ij = uc.distance(sc0[i].site, sc0[j].site)*0.8
bond_proxies.append(geom.bond_simple_proxy(
i_seqs=(i, j),
distance_ideal=d_ij,
weight=w))
d_jk = uc.distance(sc0[j].site, sc0[k].site)*0.85
bond_proxies.append(geom.bond_simple_proxy(
i_seqs=(j, k),
distance_ideal=d_jk,
weight=w))
d_ki = min(uc.distance(sc0[k].site, sc0[i].site)*0.9, (d_ij + d_jk)*0.8)
bond_proxies.append(geom.bond_simple_proxy(
i_seqs=(k, i),
distance_ideal=d_ki,
weight=w))
d_jl = uc.distance(sc0[j].site, sc0[l].site)*0.9
bond_proxies.append(geom.bond_simple_proxy(
i_seqs=(j, l),
distance_ideal=d_jl,
weight=w))
d_lk = min(uc.distance(sc0[l].site, sc0[k].site)*0.8, 0.75*(d_jk + d_jl))
bond_proxies.append(geom.bond_simple_proxy(
i_seqs=(l, k),
distance_ideal=d_jl,
weight=w))
restraints_manager = restraints.manager(bond_proxies=bond_proxies)
xs1 = xs0.deep_copy_scatterers()
xs1.shake_sites_in_place(rms_difference=0.1)
def ls_problem():
xs = xs1.deep_copy_scatterers()
reparametrisation = constraints.reparametrisation(
structure=xs,
constraints=[],
connectivity_table=smtbx.utils.connectivity_table(xs),
temperature=20)
return least_squares.crystallographic_ls(
fo_sq.as_xray_observations(),
reparametrisation=reparametrisation,
restraints_manager=restraints_manager)
gradient_threshold, step_threshold = 1e-6, 1e-6
eps = 5e-3
ls = ls_problem()
t = wall_clock_time()
cycles = normal_eqns_solving.naive_iterations(
ls,
gradient_threshold=gradient_threshold,
step_threshold=step_threshold,
track_all=True)
if options.verbose:
print("%i %s steps in %.6f s" % (cycles.n_iterations, cycles, t.elapsed()))
sc = ls.xray_structure.scatterers()
for p in bond_proxies:
d = uc.distance(*[ sc[i_pair].site for i_pair in p.i_seqs ])
assert approx_equal(d, p.distance_ideal, eps)
ls = ls_problem()
t = wall_clock_time()
cycles = normal_eqns_solving.levenberg_marquardt_iterations(
ls,
gradient_threshold=gradient_threshold,
step_threshold=step_threshold,
tau=1e-3,
track_all=True)
if options.verbose:
print("%i %s steps in %.6f s" % (cycles.n_iterations, cycles, t.elapsed()))
sc = ls.xray_structure.scatterers()
sc = ls.xray_structure.scatterers()
for p in bond_proxies:
d = uc.distance(*[ sc[i].site for i in p.i_seqs ])
assert approx_equal(d, p.distance_ideal, eps)
class process_command_line_with_files(object):
def __init__(self,
args,
master_phil=None,
master_phil_string=None,
pdb_file_def=None,
reflection_file_def=None,
map_file_def=None,
cif_file_def=None,
seq_file_def=None,
pickle_file_def=None,
ncs_file_def=None,
directory_def=None,
integer_def=None,
float_def=None,
space_group_def=None,
unit_cell_def=None,
usage_string=None):
assert (master_phil is not None) or (master_phil_string is not None)
if (master_phil_string is not None):
assert (master_phil is None)
import iotbx.phil
master_phil = iotbx.phil.parse(input_string=master_phil_string,
process_includes=True)
if (usage_string is not None):
if (len(args) == 0) or ("--help" in args):
raise Usage("""
%s
Full parameters:
%s""" % (usage_string, master_phil.as_str(prefix=" ", attributes_level=1)))
self.master = master_phil
self.pdb_file_def = pdb_file_def
self.reflection_file_def = reflection_file_def
self.cif_file_def = cif_file_def
self.map_file_def = map_file_def
self.seq_file_def = seq_file_def
self.pickle_file_def = pickle_file_def
self.ncs_file_def = ncs_file_def
self.directory_def = directory_def
self.integer_def = integer_def
self.float_def = float_def
self.space_group_def = space_group_def
self.unit_cell_def = unit_cell_def
self._type_counts = {}
self._cache = {}
cai = libtbx.phil.command_line.argument_interpreter(
master_phil=self.master)
self.unused_args = []
self.work = cai.process_and_fetch(args=args, custom_processor=self)
def get_file_type_count(self, file_type):
return self._type_counts.get(file_type, 0)
def __call__(self, arg):
file_arg = None
is_shelx_file = False
if (os.path.isfile(arg)):
file_arg = arg
# handle SHELX format hack
elif (arg.endswith("=hklf3") or arg.endswith("=hklf4")
or arg.endswith("=amplitudes") or arg.endswith("=intensities")):
base_arg = "".join(arg.split("=")[:-1])
if (base_arg != "") and os.path.isfile(base_arg):
file_arg = arg
is_shelx_file = True
if (file_arg is not None):
from iotbx import file_reader
f = file_reader.any_file(os.path.abspath(file_arg),
raise_sorry_if_not_expected_format=True)
if (f.file_type is not None):
if (not f.file_type in self._type_counts):
self._type_counts[f.file_type] = 0
self._type_counts[f.file_type] += 1
self._cache[f.file_name] = f
file_def_name = None
if (f.file_type == "pdb") and (self.pdb_file_def is not None):
file_def_name = self.pdb_file_def
elif (f.file_type == "hkl") and (self.reflection_file_def
is not None):
file_def_name = self.reflection_file_def
elif (f.file_type == "ccp4_map") and (self.map_file_def
is not None):
file_def_name = self.map_file_def
elif (f.file_type == "cif") and (self.cif_file_def is not None):
file_def_name = self.cif_file_def
elif (f.file_type == "seq") and (self.seq_file_def is not None):
file_def_name = self.seq_file_def
elif (f.file_type == "ncs") and (self.ncs_file_def is not None):
file_def_name = self.ncs_file_def
elif (f.file_type == "pkl") and (self.pickle_file_def is not None):
file_def_name = self.pickle_file_def
if (file_def_name is not None):
file_name = f.file_name
if (is_shelx_file):
file_name = file_arg
return libtbx.phil.parse("%s=%s" % (file_def_name, file_name))
else:
return False
elif (os.path.isdir(arg)):
if (self.directory_def is not None):
return libtbx.phil.parse("%s=%s" % (self.directory_def, arg))
else:
int_value = float_value = None
if (self.integer_def is not None):
try:
int_value = int(arg)
except ValueError, e:
pass
else:
return libtbx.phil.parse("%s=%d" %
(self.integer_def, int_value))
if (self.float_def is not None):
try:
float_value = float(arg)
except ValueError, e:
pass
else:
return libtbx.phil.parse("%s=%g" %
(self.float_def, float_value))
if (self.space_group_def is not None):
try:
space_group_info = sgtbx.space_group_info(arg)
except RuntimeError: # XXX should really be ValueError
pass
else:
return libtbx.phil.parse(
"%s=%s" % (self.space_group_def, space_group_info))
if (self.unit_cell_def is not None) and (arg.count(",") >= 2):
try:
uc_params = tuple([float(x) for x in arg.split(",")])
unit_cell = uctbx.unit_cell(uc_params)
except Exception: # XXX should really be ValueError
pass
else:
return libtbx.phil.parse(
"%s=%s" % (self.unit_cell_def, ",".join(
["%g" % x for x in unit_cell.parameters()])))
def run(args):
assert len(args) == 0
from cctbx import miller
import cctbx.miller.reindexing
from cctbx import uctbx
from cctbx import sgtbx
from cctbx.array_family import flex
uc = uctbx.unit_cell((11, 11, 11, 81, 81, 81))
ms = uc.complete_miller_set_with_lattice_symmetry(anomalous_flag=True,
d_min=3)
ra = miller.reindexing.assistant(
lattice_group=ms.space_group(),
intensity_group=sgtbx.space_group_info(symbol="P 1").group(),
miller_indices=ms.expand_to_p1().indices())
mt = flex.mersenne_twister(seed=0)
def check_cb_op_perm(cb_op, perm):
mi_cb = cb_op.apply(ra.miller_indices)
miis = flex.random_permutation(size=ra.miller_indices.size())[:2]
k = cb_op.apply(ra.miller_indices.select(miis))
matches = miller.match_indices(k, ra.miller_indices)
pairs = matches.pairs()
assert pairs.column(0).all_eq(flex.size_t_range(k.size()))
miis_cb = pairs.column(1)
assert perm.select(miis).all_eq(miis_cb)
def check_ra():
for cb_op, perm, inv_perm in zip(ra.cb_ops, ra.perms, ra.inv_perms):
check_cb_op_perm(cb_op, perm)
check_cb_op_perm(cb_op.inverse(), inv_perm)
check_ra()
assert ra.i_j_multiplication_table == [[0, 1, 2, 3, 4, 5],
[1, 2, 0, 4, 5, 3],
[2, 0, 1, 5, 3, 4],
[3, 5, 4, 0, 2, 1],
[4, 3, 5, 1, 0, 2],
[5, 4, 3, 2, 1, 0]]
assert ra.i_inv_j_multiplication_table == [[0, 1, 2, 3, 4, 5],
[2, 0, 1, 5, 3, 4],
[1, 2, 0, 4, 5, 3],
[3, 5, 4, 0, 2, 1],
[4, 3, 5, 1, 0, 2],
[5, 4, 3, 2, 1, 0]]
assert ra.i_j_inv_multiplication_table == [[0, 2, 1, 3, 4, 5],
[1, 0, 2, 4, 5, 3],
[2, 1, 0, 5, 3, 4],
[3, 4, 5, 0, 2, 1],
[4, 5, 3, 1, 0, 2],
[5, 3, 4, 2, 1, 0]]
from libtbx.test_utils import show_diff
from six.moves import cStringIO as StringIO
sio = StringIO()
assert ra.show_summary(out=sio, prefix=": ") is ra
assert not show_diff(
sio.getvalue(), """\
: Lattice symmetry: R 3 2 :R (No. 155)
: Intensity symmetry: P 1 (No. 1)
:
: Indexing ambiguities:
: k,l,h 3-fold invariants: 4
: l,h,k 3-fold invariants: 4
: -k,-h,-l 2-fold invariants: 4
: -l,-k,-h 2-fold invariants: 4
: -h,-l,-k 2-fold invariants: 4
""")
#
ra = miller.reindexing.assistant(lattice_group=ms.space_group(),
intensity_group=ms.space_group(),
miller_indices=ra.miller_indices)
check_ra()
sio = StringIO()
assert ra.show_summary(out=sio) is ra
assert not show_diff(
sio.getvalue(), """\
Lattice symmetry: R 3 2 :R (No. 155)
Intensity symmetry: R 3 2 :R (No. 155)
No indexing ambiguity.
""")
assert ra.i_j_multiplication_table == [[0]]
assert ra.i_inv_j_multiplication_table == [[0]]
assert ra.i_j_inv_multiplication_table == [[0]]
#
ra = miller.reindexing.assistant(
lattice_group=ms.space_group(),
intensity_group=sgtbx.space_group_info(symbol="R 3 :R").group(),
miller_indices=ra.miller_indices)
check_ra()
sio = StringIO()
assert ra.show_summary(out=sio) is ra
assert not show_diff(
sio.getvalue(), """\
Lattice symmetry: R 3 2 :R (No. 155)
Intensity symmetry: R 3 :R (No. 146)
Indexing ambiguity:
-h,-l,-k 2-fold invariants: 4
""")
assert ra.i_j_multiplication_table == [[0, 1], [1, 0]]
assert ra.i_inv_j_multiplication_table == [[0, 1], [1, 0]]
assert ra.i_j_inv_multiplication_table == [[0, 1], [1, 0]]
#
import math
ta = math.acos(-1 / 3) * 180 / math.pi
uc = uctbx.unit_cell((11, 11, 11, ta, ta, ta))
ms = uc.complete_miller_set_with_lattice_symmetry(anomalous_flag=True,
d_min=3)
ra = miller.reindexing.assistant(
lattice_group=ms.space_group(),
intensity_group=sgtbx.space_group_info(
symbol="I 4 (y+z,x+z,x+y)").group(),
miller_indices=ms.expand_to_p1().indices())
check_ra()
sio = StringIO()
assert ra.show_summary(out=sio) is ra
assert not show_diff(
sio.getvalue(), """\
Lattice symmetry: I 4 3 2 (y+z,x+z,x+y) (No. 211)
Intensity symmetry: I 4 (y+z,x+z,x+y) (No. 79)
Indexing ambiguities:
k,l,h 3-fold invariants: 2
-l,-k,-h 2-fold invariants: 4
-h,-l,-k 2-fold invariants: 4
l,h,k 3-fold invariants: 2
-k,-h,-l 2-fold invariants: 4
""")
assert ra.i_j_multiplication_table == [[0, 1, 2, 3, 4, 5],
[1, 4, 3, 5, 0, 2],
[2, 5, 0, 4, 3, 1],
[3, 2, 1, 0, 5, 4],
[4, 0, 5, 2, 1, 3],
[5, 3, 4, 1, 2, 0]]
assert ra.i_inv_j_multiplication_table == [[0, 1, 2, 3, 4, 5],
[4, 0, 5, 2, 1, 3],
[2, 5, 0, 4, 3, 1],
[3, 2, 1, 0, 5, 4],
[1, 4, 3, 5, 0, 2],
[5, 3, 4, 1, 2, 0]]
assert ra.i_j_inv_multiplication_table == [[0, 4, 2, 3, 1, 5],
[1, 0, 3, 5, 4, 2],
[2, 3, 0, 4, 5, 1],
[3, 5, 1, 0, 2, 4],
[4, 1, 5, 2, 0, 3],
[5, 2, 4, 1, 3, 0]]
#
print("OK")
def __init__(self,
pdb_hierarchy,
xray_structure,
fmodel,
distance_cutoff=4.0,
collect_all=True,
molprobity_map_params=None):
validation.__init__(self)
from mmtbx.real_space_correlation import extract_map_stats_for_single_atoms
from cctbx import adptbx
from scitbx.matrix import col
self.n_bad = 0
self.n_heavy = 0
pdb_atoms = pdb_hierarchy.atoms()
if (len(pdb_atoms) > 1):
assert (not pdb_atoms.extract_i_seq().all_eq(0))
unit_cell = xray_structure.unit_cell()
pair_asu_table = xray_structure.pair_asu_table(
distance_cutoff=distance_cutoff)
asu_mappings = pair_asu_table.asu_mappings()
asu_table = pair_asu_table.table()
u_isos = xray_structure.extract_u_iso_or_u_equiv()
occupancies = xray_structure.scatterers().extract_occupancies()
sites_frac = xray_structure.sites_frac()
sel_cache = pdb_hierarchy.atom_selection_cache()
water_sel = sel_cache.selection("water")
if (molprobity_map_params is not None):
# assume parameters have been validated (symmetry of pdb and map matches)
two_fofc_map = None
fc_map = None
d_min = None
crystal_gridding = None
# read two_fofc_map
if (molprobity_map_params.map_file_name is not None):
f = any_file(molprobity_map_params.map_file_name)
two_fofc_map = f.file_object.map_data()
d_min = molprobity_map_params.d_min
crystal_gridding = maptbx.crystal_gridding(
f.file_object.unit_cell(),
space_group_info=space_group_info(
f.file_object.space_group_number),
pre_determined_n_real=f.file_object.unit_cell_grid)
pdb_atoms = pdb_hierarchy.atoms()
xray_structure = pdb_hierarchy.extract_xray_structure(
crystal_symmetry=f.crystal_symmetry())
unit_cell = xray_structure.unit_cell()
# check for origin shift
# ---------------------------------------------------------------------
soin = maptbx.shift_origin_if_needed(
map_data=two_fofc_map,
sites_cart=xray_structure.sites_cart(),
crystal_symmetry=xray_structure.crystal_symmetry())
two_fofc_map = soin.map_data
xray_structure.set_sites_cart(soin.sites_cart)
# ---------------------------------------------------------------------
pair_asu_table = xray_structure.pair_asu_table(
distance_cutoff=distance_cutoff)
asu_mappings = pair_asu_table.asu_mappings()
asu_table = pair_asu_table.table()
u_isos = xray_structure.extract_u_iso_or_u_equiv()
occupancies = xray_structure.scatterers().extract_occupancies()
sites_frac = xray_structure.sites_frac()
sel_cache = pdb_hierarchy.atom_selection_cache()
water_sel = sel_cache.selection("water")
elif (molprobity_map_params.map_coefficients_file_name
is not None):
f = any_file(molprobity_map_params.map_coefficients_file_name)
fourier_coefficients = f.file_server.get_miller_array(
molprobity_map_params.map_coefficients_label)
crystal_symmetry = fourier_coefficients.crystal_symmetry()
d_min = fourier_coefficients.d_min()
crystal_gridding = maptbx.crystal_gridding(
crystal_symmetry.unit_cell(),
d_min,
resolution_factor=0.25,
space_group_info=crystal_symmetry.space_group_info())
two_fofc_map = miller.fft_map(
crystal_gridding=crystal_gridding,
fourier_coefficients=fourier_coefficients).apply_sigma_scaling().\
real_map_unpadded()
# calculate fc_map
assert ((d_min is not None) and (crystal_gridding is not None))
f_calc = xray_structure.structure_factors(d_min=d_min).f_calc()
fc_map = miller.fft_map(crystal_gridding=crystal_gridding,
fourier_coefficients=f_calc)
fc_map = fc_map.apply_sigma_scaling().real_map_unpadded()
map_stats = extract_map_stats_for_single_atoms(
pdb_atoms=pdb_atoms,
xray_structure=xray_structure,
fmodel=None,
selection=water_sel,
fc_map=fc_map,
two_fofc_map=two_fofc_map)
else:
map_stats = extract_map_stats_for_single_atoms(
pdb_atoms=pdb_atoms,
xray_structure=xray_structure,
fmodel=fmodel,
selection=water_sel)
waters = []
for i_seq, atom in enumerate(pdb_atoms):
if (water_sel[i_seq]):
rt_mx_i_inv = asu_mappings.get_rt_mx(i_seq, 0).inverse()
self.n_total += 1
asu_dict = asu_table[i_seq]
nearest_atom = nearest_contact = None
for j_seq, j_sym_groups in asu_dict.items():
atom_j = pdb_atoms[j_seq]
site_j = sites_frac[j_seq]
# Filter out hydrogens
if atom_j.element.upper().strip() in ["H", "D"]:
continue
for j_sym_group in j_sym_groups:
rt_mx = rt_mx_i_inv.multiply(
asu_mappings.get_rt_mx(j_seq, j_sym_group[0]))
site_ji = rt_mx * site_j
site_ji_cart = xray_structure.unit_cell(
).orthogonalize(site_ji)
vec_i = col(atom.xyz)
vec_ji = col(site_ji_cart)
dxyz = abs(vec_i - vec_ji)
if (nearest_contact is None) or (dxyz <
nearest_contact):
nearest_contact = dxyz
nearest_atom = atom_info(pdb_atom=atom_j,
symop=rt_mx)
w = water(pdb_atom=atom,
b_iso=adptbx.u_as_b(u_isos[i_seq]),
occupancy=occupancies[i_seq],
nearest_contact=nearest_contact,
nearest_atom=nearest_atom,
score=map_stats.two_fofc_ccs[i_seq],
fmodel=map_stats.fmodel_values[i_seq],
two_fofc=map_stats.two_fofc_values[i_seq],
fofc=map_stats.fofc_values[i_seq],
anom=map_stats.anom_values[i_seq],
n_hbonds=None) # TODO
if (w.is_bad_water()):
w.outlier = True
self.n_bad += 1
elif (w.is_heavy_atom()):
w.outlier = True
self.n_heavy += 1
if (w.outlier) or (collect_all):
self.results.append(w)
self.n_outliers = len(self.results)
def _compute_scaler_statistics(self,
scaled_unmerged_mtz,
selected_band=None,
wave=None):
''' selected_band = (d_min, d_max) with None for automatic determination. '''
# mapping of expected dictionary names to iotbx.merging_statistics attributes
key_to_var = {
'I/sigma': 'i_over_sigma_mean',
'Completeness': 'completeness',
'Low resolution limit': 'd_max',
'Multiplicity': 'mean_redundancy',
'Rmerge(I)': 'r_merge',
#'Wilson B factor':,
'Rmeas(I)': 'r_meas',
'High resolution limit': 'd_min',
'Total observations': 'n_obs',
'Rpim(I)': 'r_pim',
'CC half': 'cc_one_half',
'Total unique': 'n_uniq',
}
anom_key_to_var = {
'Rmerge(I+/-)': 'r_merge',
'Rpim(I+/-)': 'r_pim',
'Rmeas(I+/-)': 'r_meas',
'Anomalous completeness': 'anom_completeness',
'Anomalous correlation': 'anom_half_corr',
'Anomalous multiplicity': 'mean_redundancy',
}
stats = {}
select_result, select_anom_result = None, None
# don't call self.get_scaler_likely_spacegroups() since that calls
# self.scale() which introduced a subtle bug
from cctbx import sgtbx
sg = sgtbx.space_group_info(str(
self._scalr_likely_spacegroups[0])).group()
from xia2.Handlers.Environment import Environment
log_directory = Environment.generate_directory('LogFiles')
merging_stats_file = os.path.join(
log_directory, '%s_%s%s_merging-statistics.txt' %
(self._scalr_pname, self._scalr_xname,
'' if wave is None else '_%s' % wave))
merging_stats_json = os.path.join(
log_directory, '%s_%s%s_merging-statistics.json' %
(self._scalr_pname, self._scalr_xname,
'' if wave is None else '_%s' % wave))
result, select_result, anom_result, select_anom_result = None, None, None, None
n_bins = PhilIndex.params.xia2.settings.merging_statistics.n_bins
import iotbx.merging_statistics
while result is None:
try:
result = self._iotbx_merging_statistics(scaled_unmerged_mtz,
anomalous=False,
n_bins=n_bins)
result.as_json(file_name=merging_stats_json)
with open(merging_stats_file, 'w') as fh:
result.show(out=fh)
four_column_output = selected_band and any(selected_band)
if four_column_output:
select_result = self._iotbx_merging_statistics(
scaled_unmerged_mtz,
anomalous=False,
d_min=selected_band[0],
d_max=selected_band[1],
n_bins=n_bins)
if sg.is_centric():
anom_result = None
anom_key_to_var = {}
else:
anom_result = self._iotbx_merging_statistics(
scaled_unmerged_mtz, anomalous=True, n_bins=n_bins)
stats['Anomalous slope'] = [anom_result.anomalous_np_slope]
if four_column_output:
select_anom_result = self._iotbx_merging_statistics(
scaled_unmerged_mtz,
anomalous=True,
d_min=selected_band[0],
d_max=selected_band[1],
n_bins=n_bins)
except iotbx.merging_statistics.StatisticsErrorNoReflectionsInRange:
# Too few reflections for too many bins. Reduce number of bins and try again.
result = None
n_bins = n_bins - 3
if n_bins > 5:
continue
else:
raise
from six.moves import cStringIO as StringIO
result_cache = StringIO()
result.show(out=result_cache)
for d, r, s in ((key_to_var, result, select_result),
(anom_key_to_var, anom_result, select_anom_result)):
for k, v in d.iteritems():
if four_column_output:
values = (getattr(s.overall, v), getattr(s.bins[0], v),
getattr(s.bins[-1], v), getattr(r.overall, v))
else:
values = (getattr(r.overall,
v), getattr(r.bins[0],
v), getattr(r.bins[-1], v))
if 'completeness' in v:
values = [v_ * 100 for v_ in values]
if values[0] is not None:
stats[k] = values
return stats