def run(args):
assert len(args) == 1
# Read file into pdb_input class
inp = iotbx.pdb.input(file_name=args[0])
# create a model manager
# Catch Sorry about MTRIX here.
model = mmtbx.model.manager(
model_input=inp,
restraint_objects=
None, # these are ligands if any [('fname', cif_object), ()]
log=null_out(),
)
print("=" * 80)
print("number of atoms with MTRIX multiplication:",
model.get_number_of_atoms())
show_ss_counts(model)
# Expand with BIOMT if needed. MTRIX are already expanded by default
# Catch case when both MTRIX and BIOMT present, or other Sorry raised by
# BIOMT handling.
# LIMITATION: this should be done before any selections made on model.manager
double_counter = 0
try:
model.expand_with_BIOMT_records()
except Sorry as e:
if str(e).startswith("Model has been already expanded"):
double_counter += 1
print("=" * 80)
print("number of atoms with BIOMT multiplication:",
model.get_number_of_atoms())
show_ss_counts(model)
# Get default params
pdb_int_params = mmtbx.model.manager.get_default_pdb_interpretation_params(
)
# Set whatever you want
pdb_int_params.pdb_interpretation.secondary_structure.protein.enabled = True
pdb_int_params.pdb_interpretation.ncs_search.enabled = True
pdb_int_params.pdb_interpretation.ncs_search.residue_match_radius = 999
pdb_int_params.pdb_interpretation.clash_guard.nonbonded_distance_threshold = None
#pdb_int_params.pdb_interpretation.nonbonded_weight = None
# set the params. Note, that GRM would be dropped, even if it was already
# constructed. In this example it is not yet constructed.
model.set_pdb_interpretation_params(params=pdb_int_params)
grm = model.get_restraints_manager()
# Not clear which one should be used at the moment
gs = model.geometry_statistics()
gs.show()
# The second way
msi = model.get_model_statistics_info()
msi.show_remark_3()
def exercise_mtrix():
inp = iotbx.pdb.input(lines=mtrix_txt+ss_txt+atoms_txt, source_info=None)
model = mmtbx.model.manager(
model_input = inp)
assert model.get_number_of_atoms() == 900, model.get_number_of_atoms()
assert model.get_hierarchy().atoms_size() == 900
assert model.get_xray_structure().scatterers().size() == 900
ss_ann = model.get_ss_annotation()
# print ss_ann.as_pdb_str()
assert ss_ann.get_n_helices() == 6
assert ss_ann.get_n_sheets() == 3
def exercise_08():
"""
Test for MTRIX record when copies already present in file
"""
pdb_inp = pdb.input(source_info=None, lines=pdb_str_8)
model = mmtbx.model.manager(pdb_inp)
assert model.get_number_of_atoms() == 7
def exercise_set_sites_cart_no_ncs():
inp = iotbx.pdb.input(lines=pdb_str_5, source_info=None)
model = mmtbx.model.manager(model_input=inp, expand_with_mtrix=False)
model.search_for_ncs()
nrgl = model.get_ncs_groups()
nrgl._show()
print('n model atoms:', model.get_number_of_atoms())
print('n master atoms:', model.get_master_selection().count(True))
print('n master atoms:', model.get_master_selection().iselection().size())
print('n master atoms:', model.get_master_hierarchy().atoms_size())
assert model.get_master_selection().count(True) ==\
model.get_master_selection().iselection().size() ==\
model.get_master_hierarchy().atoms_size()
h = model.get_hierarchy()
# Warning: here here mh is not deep-copy, therefore when we change atom coords
# they are changing in model.get_hierarchy() as well
mh = model.get_master_hierarchy()
new_sites_cart = flex.vec3_double([(1.0, 1.0, 1.0)] * 42)
mh.atoms().set_xyz(new_sites_cart)
model.set_sites_cart_from_hierarchy(multiply_ncs=True)
h = model.get_hierarchy()
new_xyz = h.atoms().extract_xyz()
# print('h sites:', list(new_xyz))
# checking if setting went as supposed:
for j in range(42):
assert approx_equal(new_xyz[j], (1.0, 1.0, 1.0), eps=1e-4)
def run(args):
assert len(args) == 1
# Read file into pdb_input class
inp = iotbx.pdb.input(file_name=args[0])
# create a model manager
model = mmtbx.model.manager(model_input=inp)
# get number of atoms in the input model
n_atoms = model.get_number_of_atoms()
# extract atom coordinates
old_sites_cart = model.get_sites_cart()
# generate random additions
random_addition = flex.vec3_double(
flex.random_double(size=n_atoms * 3) - 0.5)
# actually add them to old coordinates
new_xyz = old_sites_cart + random_addition
# Update coordinates in model manager
model.set_sites_cart(sites_cart=new_xyz)
# get xray structure
xrs = model.get_xray_structure()
# reset B-factors (min=1, max=20)
# generate array of new B-factors
new_b = flex.random_double(size=n_atoms, factor=19) + 1
# set them in xray structure
xrs.set_b_iso(values=new_b)
# update model manager with this xray structure
model.set_xray_structure(xrs)
# output result in PDB format to the screen
print model.model_as_pdb()
print "END"
def exercise_biomt():
inp = iotbx.pdb.input(lines=biomt_txt+ss_txt+atoms_txt, source_info=None)
model = mmtbx.model.manager(
model_input = inp)
assert model.get_number_of_atoms() == 300, model.get_number_of_atoms()
assert model.get_hierarchy().atoms_size() == 300
assert model.get_xray_structure().scatterers().size() == 300
ss_ann = model.get_ss_annotation()
assert ss_ann.get_n_helices() == 2
assert ss_ann.get_n_sheets() == 1
model.expand_with_BIOMT_records()
assert model.get_number_of_atoms() == 900, model.get_number_of_atoms()
assert model.get_hierarchy().atoms_size() == 900
assert model.get_xray_structure().scatterers().size() == 900, model.get_xray_structure().scatterers().size()
ss_ann = model.get_ss_annotation()
assert ss_ann.get_n_helices() == 6
assert ss_ann.get_n_sheets() == 3
def exercise_dihedral_edits_change():
edits = """\
geometry_restraints.edits {
dihedral {
action = *change
atom_selection_1 = resid 1 and name CA
atom_selection_2 = resid 1 and name C
atom_selection_3 = resid 2 and name N
atom_selection_4 = resid 2 and name CA
angle_ideal = 100.00
alt_angle_ideals = 90,110
sigma = 2
periodicity = 2
}
}"""
def_params = mmtbx.model.manager.get_default_pdb_interpretation_scope()
edits_phil = iotbx.phil.parse(edits)
working_phil = def_params.fetch(edits_phil)
params = working_phil.extract()
inp = iotbx.pdb.input(lines=raw_records2, source_info=None)
model = mmtbx.model.manager(model_input=inp)
model.process(make_restraints=True)
grm = model.get_restraints_manager().geometry
assert grm.dihedral_proxies.size() == 9
dih1 = grm.dihedral_proxies.proxy_select(n_seq=model.get_number_of_atoms(),
iselection=flex.size_t(
[1, 2, 5, 6]))
assert dih1.size() == 1
dp1 = dih1[0]
assert approx_equal(dp1.angle_ideal, 180)
assert dp1.alt_angle_ideals == None
assert dp1.origin_id == 0
assert dp1.periodicity == 0
assert dp1.slack == 0
assert not dp1.top_out
assert approx_equal(dp1.weight, 0.04)
# Now with modifications
inp = iotbx.pdb.input(lines=raw_records2, source_info=None)
model2 = mmtbx.model.manager(model_input=inp)
model2.process(pdb_interpretation_params=params, make_restraints=True)
grm2 = model2.get_restraints_manager().geometry
assert grm2.dihedral_proxies.size() == 9
dih2 = grm2.dihedral_proxies.proxy_select(
n_seq=model2.get_number_of_atoms(),
iselection=flex.size_t([1, 2, 5, 6]))
assert dih2.size() == 1
dp2 = dih2[0]
assert approx_equal(dp2.angle_ideal, 100)
assert dp2.alt_angle_ideals == (90, 110)
assert dp2.origin_id == origin_ids.get_origin_id('edits')
assert dp2.periodicity == 2
assert dp2.slack == 0
assert not dp2.top_out
assert approx_equal(dp2.weight, 0.25)
def exercise_1():
inp = iotbx.pdb.input(source_info=None, lines=pdb_str_1)
model = mmtbx.model.manager(model_input=inp, log=null_out())
model.process(make_restraints=True)
assert model.get_number_of_atoms() == 21, model.get_number_of_atoms()
assert model.get_hierarchy().atoms_size() == 21
assert model.get_xray_structure().scatterers().size() == 21
ss = model.get_ss_annotation()
# print ss.as_pdb_str()
# STOP()
assert ss.get_n_helices() == 3
# because the second strand contains chain B which is not in ATOM records
# whole sheet got discarded.
assert ss.get_n_sheets() == 0
rm = model.get_restraints_manager()
assert rm.geometry.pair_proxies().bond_proxies.simple.size() == 6
# since No NCS was set, these functions return the whole thing and no
# master selection
assert model.get_master_hierarchy().atoms_size() == 21
assert model.get_master_selection().size() == 0
# print model.model_as_pdb()
# print "="*40
# Here we set NCS constraints
inp = iotbx.pdb.input(source_info=None, lines=pdb_str_1)
pdb_int_params = mmtbx.model.manager.get_default_pdb_interpretation_params(
)
pdb_int_params.pdb_interpretation.ncs_search.enabled = True
model = mmtbx.model.manager(model_input=inp, log=null_out())
model.process(pdb_interpretation_params=pdb_int_params)
# model.get_xray_structure()
assert not model.ncs_constraints_present()
assert model.get_ncs_obj() is not None
model.setup_ncs_constraints_groups()
# print model.get_ncs_obj()
assert model.ncs_constraints_present()
assert model.get_master_hierarchy().atoms_size() == 7
# print model.get_master_hierarchy().as_pdb_string()
# print list(model.get_master_selection())
assert list(model.get_master_selection()).count(True) == 7
def test_1():
inp = iotbx.pdb.input(source_info=None, lines=pdb_str_0)
model = mmtbx.model.manager(model_input=inp)
model.expand_with_BIOMT_records()
model = shift_and_box_model(model)
sel = model.selection("chain '0' or chain 'C' or chain 'F' or chain 'I' or chain 'L' or chain 'O' or chain 'R' or chain 'U' or chain 'X'")
model = model.select(sel)
model.search_for_ncs()
model.setup_ncs_constraints_groups(filter_groups=True)
n1 = model.get_number_of_atoms()
assert n1 == 648, n1
assert model.ncs_constraints_present()
nrgl = model.get_ncs_groups()
assert len(nrgl[0].master_iselection) == 72
assert len(nrgl[0].copies) == 8
# nrgl._show()
# print (model.can_be_unique_with_biomt())
cif_txt = model.model_as_mmcif(try_unique_with_biomt=True)
# print (cif_txt)
assert_lines_in_text(cif_txt, """
loop_
_pdbx_struct_assembly_gen.assembly_id
_pdbx_struct_assembly_gen.oper_expression
_pdbx_struct_assembly_gen.asym_id_list
1 (1-9) A""")
assert_lines_in_text(cif_txt, """
loop_
_pdbx_struct_assembly.id
_pdbx_struct_assembly.details
_pdbx_struct_assembly.method_details
_pdbx_struct_assembly.oligomeric_details
_pdbx_struct_assembly.oligomeric_count
1 'Symmetry assembly' ? ? ? """)
assert_lines_in_text(cif_txt, """
_pdbx_struct_oper_list.vector[1]
_pdbx_struct_oper_list.vector[2]
_pdbx_struct_oper_list.vector[3]
1 'point symmetry operation' ? ? 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0""")
inp = iotbx.pdb.input(source_info=None, lines=cif_txt)
m2 = mmtbx.model.manager(model_input=inp)
n2_1 = m2.get_number_of_atoms()
assert n2_1 == 72
m2.expand_with_BIOMT_records()
n2_2 = m2.get_number_of_atoms()
# print (n1, n2)
assert n1 == n2_2, "%d, %d" % (n1, n2)
def tst_1(prefix="gm_ncs_constr_tst1"):
log = sys.stdout
pdb_in = iotbx.pdb.input(source_info=None, lines=pdb_string1.split('\n'))
# print dir(pdb_in)
pdb_int_params = mmtbx.model.manager.get_default_pdb_interpretation_params(
)
pdb_int_params.pdb_interpretation.ncs_search.enabled = True
model = mmtbx.model.manager(model_input=pdb_in,
pdb_interpretation_params=pdb_int_params,
build_grm=True)
ncs_obj = iotbx.ncs.input(hierarchy=model.get_hierarchy())
original_ncs_transform = ncs_obj.ncs_transform
ncs_restraints_group_list = ncs_obj.get_ncs_restraints_group_list()
ncs_obj.show(format='phil')
grm = model.get_restraints_manager()
tmp_xrs = model.get_xray_structure().deep_copy_scatterers()
refine_selection = flex.size_t(xrange(model.get_number_of_atoms()))
# print "refining sites"
cycle = 0
tfg_obj = mmtbx.refinement.minimization_ncs_constraints.\
target_function_and_grads_geometry_minimization(
xray_structure=tmp_xrs,
ncs_restraints_group_list=ncs_restraints_group_list,
refine_selection=refine_selection,
restraints_manager=grm.geometry,
refine_sites=True,
refine_transformations=False,
)
minimized = mmtbx.refinement.minimization_ncs_constraints.lbfgs(
target_and_grads_object=tfg_obj,
xray_structure=tmp_xrs,
ncs_restraints_group_list=ncs_restraints_group_list,
refine_selection=refine_selection,
finite_grad_differences_test=False,
max_iterations=100,
refine_sites=True,
refine_transformations=False)
refined_pdb_h = model.get_hierarchy().deep_copy()
refined_pdb_h.adopt_xray_structure(tmp_xrs)
refined_pdb_h.write_pdb_file("refined_%d.pdb" % cycle)
new_ncs_obj = iotbx.ncs.input(hierarchy=refined_pdb_h)
new_ncs_transform = new_ncs_obj.ncs_transform
spec = new_ncs_obj.get_ncs_info_as_spec()
for k, v in original_ncs_transform.iteritems():
assert approx_equal(v.r.elems, new_ncs_transform[k].r.elems)
assert approx_equal(v.t, new_ncs_transform[k].t)
overall_rmsd_after = spec.overall_rmsd()
assert overall_rmsd_after < 1e-6
def exercise_set_sites_cart_ncs():
"""
No extra atoms
"""
inp = iotbx.pdb.input(lines=pdb_str_5, source_info=None)
model = mmtbx.model.manager(model_input=inp)
model.search_for_ncs()
nrgl = model.get_ncs_groups()
nrgl._show()
print('n model atoms:', model.get_number_of_atoms())
print('n master atoms:', model.get_master_selection().count(True))
print('n master atoms:', model.get_master_selection().iselection().size())
print('n master atoms:', model.get_master_hierarchy().atoms_size())
assert model.get_master_selection().count(True) ==\
model.get_master_selection().iselection().size() ==\
model.get_master_hierarchy().atoms_size()
h = model.get_hierarchy()
# print('h sites:', list(h.atoms().extract_xyz()))
# Warning: here here mh is not deep-copy, therefore when we change atom coords
# they are changing in model.get_hierarchy() as well
mh = model.get_master_hierarchy()
new_sites_cart = flex.vec3_double([(1.0, 1.0, 1.0)] * 42)
mh.atoms().set_xyz(new_sites_cart)
model.set_sites_cart_from_hierarchy(multiply_ncs=True)
h = model.get_hierarchy()
new_xyz = h.atoms().extract_xyz()
# print('h sites:', list(new_xyz))
# checking if setting went as supposed:
assert approx_equal(new_xyz[0], (1.0, 1.0, 1.0), eps=1e-4)
assert approx_equal(
new_xyz[42],
(-0.6420293330506949, 1.2600792663765976, 7.999997229451341),
eps=1e-4)
assert approx_equal(
new_xyz[84],
(-1.396802536808536, -0.22123285934616377, 1.000000038694047),
eps=1e-4)
for i in range(3):
for j in range(42):
assert approx_equal(new_xyz[42 * i + j], new_xyz[42 * i], eps=1e-4)
def exercise_2(eps = 1.e-6):
###> Get started from PDB
mon_lib_srv = monomer_library.server.server()
ener_lib = monomer_library.server.ener_lib()
pdb_file = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/phe_abc_tlsanl_out_geometry_minimized.pdb",
test=os.path.isfile)
model = mmtbx.model.manager(
model_input=iotbx.pdb.input(file_name=pdb_file),
build_grm=True)
model.setup_scattering_dictionaries(scattering_table="wk1995")
model.get_xray_structure().convert_to_isotropic()
u_iso_start = model.get_xray_structure().extract_u_iso_or_u_equiv()
model.get_xray_structure().convert_to_anisotropic()
selections = []
selection_strings = ["chain A", "chain B", "chain C"]
for string in selection_strings:
selections.append(model.selection(string = string))
################
selection = flex.bool(model.get_number_of_atoms(), True)
class refinement_flags: pass
refinement_flags.adp_tls = selections
model.set_refinement_flags(refinement_flags)
model.determine_tls_groups(selection_strings=selections, generate_tlsos=selections)
model.set_refinement_flags(refinement_flags)
xray_structure = model.get_xray_structure()
################
###> Get TLS <-> Ucart
T_initial = []
L_initial = []
S_initial = []
T_initial.append([0.11,0.22,0.33,0.12,0.13,0.23])
L_initial.append([1.11,1.22,1.33,1.12,1.13,1.23])
S_initial.append([0.11,0.12,0.13,0.21,0.22,0.23,0.31,0.32,-0.33])
T_initial.append([0.22,0.44,0.66,0.24,0.26,0.46])
L_initial.append([2.22,2.44,2.66,2.24,2.26,2.46])
S_initial.append([0.22,0.24,0.26,0.42,0.44,0.46,0.62,0.64,-0.66])
T_initial.append([0.33,0.66,0.99,0.36,0.39,0.69])
L_initial.append([2.33,2.66,2.99,2.36,2.39,2.69])
S_initial.append([0.22,0.24,0.26,0.42,0.44,0.46,0.62,0.64,-0.66])
tlsosA = tools.generate_tlsos(selections = selections,
xray_structure = xray_structure,
T = T_initial,
L = L_initial,
S = S_initial)
tlsos = tools.generate_tlsos(selections = selections,
xray_structure = xray_structure,
T = T_initial,
L = L_initial,
S = S_initial)
tlsos = tools.make_tlso_compatible_with_u_positive_definite(
tlsos = tlsos,
xray_structure = xray_structure.deep_copy_scatterers(),
selections = selections,
max_iterations = 50,
number_of_u_nonpositive_definite = 0,
eps = eps,
number_of_macro_cycles_for_tls_from_uanisos = 30)
u_cart_answer = tools.u_cart_from_tls(sites_cart = xray_structure.sites_cart(),
selections = selections,
tlsos = tlsos)
xray_structure.scatterers().set_u_cart(xray_structure.unit_cell(),
u_cart_answer)
assert approx_equal(u_cart_answer,
xray_structure.scatterers().extract_u_cart(xray_structure.unit_cell()))
tools.show_tls(tlsos = tlsos, text = "ANSWER")
###> Set up fmodel
sfg_params = mmtbx.f_model.sf_and_grads_accuracy_master_params.extract()
sfg_params.algorithm = "direct"
sfg_params.cos_sin_table = False
dummy = xray_structure.structure_factors(algorithm = sfg_params.algorithm,
d_min = 2.0).f_calc()
f_obs = abs(dummy.structure_factors_from_scatterers(
xray_structure = xray_structure,
algorithm = sfg_params.algorithm,
cos_sin_table = sfg_params.cos_sin_table).f_calc())
flags = f_obs.generate_r_free_flags(fraction=0.01, max_free=2000)
fmodel = mmtbx.f_model.manager(xray_structure = xray_structure,
f_obs = f_obs,
r_free_flags = flags,
target_name = "ls_wunit_k1",
sf_and_grads_accuracy_params = sfg_params)
fmodel.info(free_reflections_per_bin=250, max_number_of_bins=30).show_all()
xray_structure.convert_to_isotropic()
xray_structure.set_b_iso(value = 25.0)
fmodel.update_xray_structure(xray_structure = xray_structure,
update_f_calc = True)
fmodel.info(free_reflections_per_bin=250, max_number_of_bins=30).show_all()
print("*"*80)
###> TLS refinement against xray data
if (not "--comprehensive" in sys.argv[1:]):
number_of_macro_cycles = 1
max_number_of_iterations = 3
else:
number_of_macro_cycles = 100
max_number_of_iterations = 50
for start_tls_value in [None]:#[0.0, tlsosA, None]:
#for start_tls_value in [None]:
print(" \n "+str(start_tls_value) + " \n ")
fmodel_cp = fmodel.deep_copy()
#for sc in fmodel_cp.xray_structure.scatterers():
# sc.flags.set_use_u_aniso(True)
fmodel_cp.xray_structure.convert_to_anisotropic()
if(start_tls_value is None):
run_finite_differences_test = True
else: run_finite_differences_test = False
model.set_xray_structure(fmodel_cp.xray_structure)
tls_refinement_manager = tools.tls_refinement(
fmodel = fmodel_cp,
model = model,
selections = selections,
selections_1d = None,
refine_T = 1,
refine_L = 1,
refine_S = 1,
number_of_macro_cycles = number_of_macro_cycles,
max_number_of_iterations = max_number_of_iterations,
start_tls_value = start_tls_value,
run_finite_differences_test = run_finite_differences_test,
eps = eps)
u_cart = tls_refinement_manager.fmodel.xray_structure.scatterers().extract_u_cart(
xray_structure.unit_cell())
if("--comprehensive" in sys.argv[1:]):
format = "%10.6f %10.6f %10.6f %10.6f %10.6f %10.6f"
counter = 0
if(start_tls_value == tlsosA): tolerance = 1.e-6
else: tolerance = 0.02
for m1,m2 in zip(u_cart_answer, u_cart):
counter += 1
if(counter < 10):
print("1=" + format % (m1[0],m1[1],m1[2],m1[3],m1[4],m1[5]))
print("2=" + format % (m2[0],m2[1],m2[2],m2[3],m2[4],m2[5]))
assert approx_equal(m1,m2, tolerance)
def run(args, command_name="phenix.tls"):
if (len(args) == 0): args = ["--help"]
usage_fmt = "%s pdb_file [parameters: file or command line string]"
des_fmt = "Example: %s model.pdb fit_tls_to.selection='%s' fit_tls_to.selection='%s'"
command_line = (iotbx_option_parser(
usage=usage_fmt % command_name, description=banner).option(
"--show_defaults",
action="store_true",
help="Do not output to the screen (except errors).").option(
"--silent",
action="store_true",
help="Suppress output to the screen.")).process(args=args)
#
log = sys.stdout
if (not command_line.options.silent):
utils.print_header("TLS tools", out=log)
if (command_line.options.show_defaults):
master_params.show(out=log)
print(file=log)
return
if (not command_line.options.silent):
print(banner, file=log)
#
processed_args = utils.process_command_line_args(
args=command_line.args, master_params=master_params, log=log)
reflection_files = processed_args.reflection_files
if (processed_args.crystal_symmetry is None):
raise Sorry("No crystal symmetry found.")
if (len(processed_args.pdb_file_names) == 0):
raise Sorry("No PDB file found.")
params = processed_args.params
if (not command_line.options.silent):
utils.print_header("Input parameters", out=log)
params.show(out=log)
params = params.extract()
#
if (processed_args.crystal_symmetry.unit_cell() is None
or processed_args.crystal_symmetry.space_group() is None):
raise Sorry("No CRYST1 record found.")
pdb_combined = iotbx.pdb.combine_unique_pdb_files(
file_names=processed_args.pdb_file_names)
pdb_combined.report_non_unique(out=log)
if (len(pdb_combined.unique_file_names) == 0):
raise Sorry("No coordinate file given.")
raw_records = pdb_combined.raw_records
try:
pdb_inp = iotbx.pdb.input(source_info=None,
lines=flex.std_string(raw_records))
except ValueError as e:
raise Sorry("Model format (PDB or mmCIF) error:\n%s" % str(e))
model = mmtbx.model.manager(
model_input=pdb_inp,
restraint_objects=processed_args.cif_objects,
crystal_symmetry=processed_args.crystal_symmetry,
log=log)
if (not command_line.options.silent):
utils.print_header("TLS groups from PDB file header", out=log)
pdb_inp_tls = mmtbx.tls.tools.tls_from_pdb_inp(
remark_3_records=model._model_input.extract_remark_iii_records(3),
pdb_hierarchy=model.get_hierarchy())
#
tls_groups = []
if (pdb_inp_tls.tls_present):
if (pdb_inp_tls.error_string is not None):
raise Sorry(pdb_inp_tls.error_string)
pdb_tls = mmtbx.tls.tools.extract_tls_from_pdb(pdb_inp_tls=pdb_inp_tls,
model=model)
tls_groups = pdb_tls.pdb_inp_tls.tls_params
#
tls_selections_strings = []
#
if (len(tls_groups) == 0 and not command_line.options.silent):
print("No TLS groups found in PDB file header.", file=log)
else:
for i_seq, tls_group in enumerate(tls_groups):
tls_selections_strings.append(tls_group.selection_string)
if (not command_line.options.silent):
print("TLS group %d: %s" %
(i_seq + 1, tls_group.selection_string),
file=log)
mmtbx.tls.tools.show_tls_one_group(tlso=tls_group, out=log)
print(file=log)
#
if (len(tls_selections_strings) > 0 and len(params.selection) > 0):
raise Sorry(
"Two TLS selection sources found: PDB file header and parameters.")
if (len(params.selection) > 0):
tls_selections_strings = params.selection
if ([params.combine_tls, params.extract_tls].count(True) > 1):
raise Sorry(
"Cannot simultaneously pereform: combine_tls and extract_tls")
if ([params.combine_tls, params.extract_tls].count(True) > 0):
if (len(tls_selections_strings) == 0):
raise Sorry("No TLS selections found.")
#
if (len(tls_selections_strings)):
if (not command_line.options.silent):
utils.print_header("TLS groups selections", out=log)
selections = utils.get_atom_selections(
model=model, selection_strings=tls_selections_strings)
if (not command_line.options.silent):
print("Number of TLS groups: ", len(selections), file=log)
print("Number of atoms: %d" % model.get_number_of_atoms(),
file=log)
n_atoms_in_tls = 0
for sel_a in selections:
n_atoms_in_tls += sel_a.size()
if (not command_line.options.silent):
print("Number of atoms in TLS groups: %d" % n_atoms_in_tls,
file=log)
print(file=log)
assert len(tls_selections_strings) == len(selections)
if (not command_line.options.silent):
for sel_a, sel_s in zip(selections, tls_selections_strings):
print("Selection string:\n%s" % sel_s, file=log)
print("selects %d atoms." % sel_a.size(), file=log)
print(file=log)
print("Ready-to-use in phenix.refine:\n", file=log)
for sel_a, sel_s in zip(selections, tls_selections_strings):
print(sel_s, file=log)
#
ofn = params.output_file_name
if (ofn is None):
ofn = os.path.splitext(
os.path.basename(processed_args.pdb_file_names[0]))[0]
if (len(processed_args.pdb_file_names) > 1):
ofn = ofn + "_el_al"
if (params.combine_tls):
ofn = ofn + "_combine_tls.pdb"
elif (params.extract_tls):
ofn = ofn + "_extract_tls.pdb"
else:
ofn = None
if (ofn is not None):
ofo = open(ofn, "w")
#
if (params.extract_tls):
utils.print_header(
"Fit TLS matrices to B-factors of selected sets of atoms", out=log)
tlsos = mmtbx.tls.tools.generate_tlsos(
selections=selections,
xray_structure=model.get_xray_structure(),
value=0.0)
for rt, rl, rs in [[1, 0, 1], [1, 1, 1], [0, 1, 1], [1, 0, 0],
[0, 1, 0], [0, 0, 1], [1, 1, 1], [0, 0, 1]] * 10:
tlsos = mmtbx.tls.tools.tls_from_uanisos(
xray_structure=model.get_xray_structure(),
selections=selections,
tlsos_initial=tlsos,
number_of_macro_cycles=10,
max_iterations=100,
refine_T=rt,
refine_L=rl,
refine_S=rs,
enforce_positive_definite_TL=params.
enforce_positive_definite_TL,
verbose=-1,
out=log)
mmtbx.tls.tools.show_tls(tlsos=tlsos, out=log)
u_cart_from_tls = mmtbx.tls.tools.u_cart_from_tls(
sites_cart=model.get_sites_cart(),
selections=selections,
tlsos=tlsos)
unit_cell = model.get_xray_structure().unit_cell()
for i_seq, sc in enumerate(model.get_xray_structure().scatterers()):
if (u_cart_from_tls[i_seq] != (0, 0, 0, 0, 0, 0)):
u_star_tls = adptbx.u_cart_as_u_star(
unit_cell, tuple(u_cart_from_tls[i_seq]))
sc.u_star = tuple(
flex.double(sc.u_star) - flex.double(u_star_tls))
for sel in selections:
model.get_xray_structure().convert_to_isotropic(selection=sel)
mmtbx.tls.tools.remark_3_tls(tlsos=tlsos,
selection_strings=tls_selections_strings,
out=ofo)
#
if (params.combine_tls):
utils.print_header("Combine B_tls with B_residual", out=log)
mmtbx.tls.tools.combine_tls_and_u_local(
xray_structure=model.get_xray_structure(),
tls_selections=selections,
tls_groups=tls_groups)
print("All done.", file=log)
#
if (ofn is not None):
utils.print_header("Write output PDB file %s" % ofn, out=log)
model.set_sites_cart_from_xrs()
pdb_str = model.model_as_pdb()
ofo.write(pdb_str)
ofo.close()
print("All done.", file=log)
def run(
pdb_filename=None,
raw_records=None,
return_formal_charges=False,
verbose=False,
):
if pdb_filename:
# Read file into pdb_input class
inp = iotbx.pdb.input(file_name=pdb_filename)
elif raw_records:
inp = iotbx.pdb.input(lines=raw_records, source_info='lines from PDB')
else:
assert 0
# create a model manager
from io import StringIO
log = StringIO()
default_scope = mmtbx.model.manager.get_default_pdb_interpretation_scope()
working_params = default_scope.extract()
# optional???
working_params.pdb_interpretation.automatic_linking.link_metals = True
model = mmtbx.model.manager(
model_input=inp,
log=log,
)
model.process(make_restraints=True,
pdb_interpretation_params=working_params)
# get xray structure
xrs = model.get_xray_structure()
grm = model.get_restraints_manager()
t0 = time.time()
atom_valences = electron_distribution(
model.get_hierarchy(), # needs to be altloc free
model.get_restraints_manager().geometry,
verbose=verbose,
)
if verbose: print(atom_valences)
total_charge = atom_valences.get_total_charge()
#print 'total_charge',total_charge
#print 'time %0.1f' % (time.time()-t0)
rc = atom_valences.validate_atomic_formal_charges()
if return_formal_charges: return atom_valences
return total_charge
# get number of atoms in the input model
n_atoms = model.get_number_of_atoms()
# extract atom coordinates
old_sites_cart = model.get_sites_cart()
# generate random additions
random_addition = flex.vec3_double(
flex.random_double(size=n_atoms * 3) - 0.5)
# actually add them to old coordinates
new_xyz = old_sites_cart + random_addition
# Update coordinates in model manager
model.set_sites_cart(sites_cart=new_xyz)
# reset B-factors (min=1, max=20)
# generate array of new B-factors
new_b = flex.random_double(size=n_atoms, factor=19) + 1
# set them in xray structure
xrs.set_b_iso(values=new_b)
# update model manager with this xray structure
model.set_xray_structure(xrs)
# output result in PDB format to the screen
print(model.model_as_pdb())
print("END")
tls_selections_strings = params.selection
if ([params.combine_tls, params.extract_tls].count(True) > 1):
raise Sorry(
"Cannot simultaneously pereform: combine_tls and extract_tls")
if ([params.combine_tls, params.extract_tls].count(True) > 0):
if (len(tls_selections_strings) == 0):
raise Sorry("No TLS selections found.")
#
if (len(tls_selections_strings)):
if (not command_line.options.silent):
utils.print_header("TLS groups selections", out=log)
selections = utils.get_atom_selections(
model=model, selection_strings=tls_selections_strings)
if (not command_line.options.silent):
print >> log, "Number of TLS groups: ", len(selections)
print >> log, "Number of atoms: %d" % model.get_number_of_atoms()
n_atoms_in_tls = 0
for sel_a in selections:
n_atoms_in_tls += sel_a.size()
if (not command_line.options.silent):
print >> log, "Number of atoms in TLS groups: %d" % n_atoms_in_tls
print >> log
assert len(tls_selections_strings) == len(selections)
if (not command_line.options.silent):
for sel_a, sel_s in zip(selections, tls_selections_strings):
print >> log, "Selection string:\n%s" % sel_s
print >> log, "selects %d atoms." % sel_a.size()
print >> log
print >> log, "Ready-to-use in phenix.refine:\n"
for sel_a, sel_s in zip(selections, tls_selections_strings):
print >> log, sel_s
def exercise_set_sites_cart_ncs_with_extra_atoms():
inp = iotbx.pdb.input(lines=test_pdb_6, source_info=None)
model = mmtbx.model.manager(model_input=inp)
model.search_for_ncs()
nrgl = model.get_ncs_groups()
nrgl._show(brief=False)
print('n model atoms:', model.get_number_of_atoms())
print('n master atoms:', model.get_master_selection().count(True))
print('n master atoms:', model.get_master_selection().iselection().size())
print('n master isel:', list(model.get_master_selection().iselection()))
print('n master atoms:', model.get_master_hierarchy().atoms_size())
print('n master hierarchy:\n',
model.get_master_hierarchy().as_pdb_string())
# Note that "HETATM 32 C2 NDG H" and "HETATM 35 C2 NDG L"
# don't belong to any master/copy
assert not show_diff(
model.get_master_hierarchy().as_pdb_string(), """\
ATOM 1 N ASP H 5 91.286 -31.834 73.572 1.00 77.83 N
ATOM 2 CA ASP H 5 90.511 -32.072 72.317 1.00 78.04 C
ATOM 3 C ASP H 5 90.136 -30.762 71.617 1.00 77.70 C
ATOM 4 O ASP H 5 89.553 -29.857 72.225 1.00 77.56 O
ATOM 5 N THR H 6 91.286 -31.834 73.572 1.00 77.83 N
ATOM 6 CA THR H 6 90.511 -32.072 72.317 1.00 78.04 C
TER
ATOM 7 N GLY I 501 91.286 -31.834 73.572 1.00 77.83 N
ATOM 8 CA GLY I 501 90.511 -32.072 72.317 1.00 78.04 C
ATOM 9 C GLY I 501 90.136 -30.762 71.617 1.00 77.70 C
ATOM 10 O GLY I 501 89.553 -29.857 72.225 1.00 77.56 O
TER
HETATM 31 C1 NDG H 640 91.286 -31.834 73.572 1.00 77.83 C
HETATM 32 C2 NDG H 640 91.286 -31.834 73.572 1.00 77.83 C
HETATM 35 C2 NDG L 646 61.028 -14.273 81.262 1.00 69.80 C
""")
mh = model.get_master_hierarchy()
# Note that atoms outside NCS are getting 2.0 as xyz
new_sites_cart = flex.vec3_double(
[(1.0, 1.0, 1.0), (1.0, 1.0, 1.0), (1.0, 1.0, 1.0), (1.0, 1.0, 1.0),
(1.0, 1.0, 1.0), (1.0, 1.0, 1.0)] + [(3.0, 3.0, 3.0)] * 4 +
[
(1.0, 1.0, 1.0), # <--- Note this atom belongs the first NCS group
(2.0, 2.0, 2.0),
(2.0, 2.0, 2.0)
])
mh.atoms().set_xyz(new_sites_cart)
# print('='*80)
# print (mh.as_pdb_string())
model.set_sites_cart_from_hierarchy(multiply_ncs=True)
h = model.get_hierarchy()
new_xyz = h.atoms().extract_xyz()
# print(model.model_as_pdb())
# print (list(new_xyz))
assert approx_equal(new_xyz[31], (2.0, 2.0, 2.0), eps=1e-4)
assert approx_equal(new_xyz[34], (2.0, 2.0, 2.0), eps=1e-4)
assert approx_equal(new_xyz[0], (1.0, 1.0, 1.0), eps=1e-4)
assert approx_equal(new_xyz[5], (1.0, 1.0, 1.0), eps=1e-4)
assert approx_equal(new_xyz[6], (3.0, 3.0, 3.0), eps=1e-4)
assert approx_equal(new_xyz[9], (3.0, 3.0, 3.0), eps=1e-4)
assert nrgl.check_for_max_rmsd(sites_cart=new_xyz, chain_max_rmsd=0.0)
for i in [[0, 1, 2, 3, 4, 5, 30], [10, 11, 12, 13, 14, 15, 32],
[20, 21, 22, 23, 24, 25, 33]]:
for j in i:
assert approx_equal(new_xyz[j], new_xyz[i[0]], eps=1e-4)
for i in [[6, 7, 8, 9], [16, 17, 18, 19], [26, 27, 28, 29]]:
for j in i:
assert approx_equal(new_xyz[j], new_xyz[i[0]], eps=1e-4)
