def run(args):
if len(args) == 0:
show_usage()
return
inp_fn = args[0]
import time
t0 = time.time()
pdb_input = iotbx.pdb.input(file_name=inp_fn,
source_info=None,
raise_sorry_if_format_error=True)
t0 = time.time()
model = mmtbx.model.manager(model_input=pdb_input)
pdb_h = model.get_hierarchy()
info = pdb_h.flip_symmetric_amino_acids()
print(info)
model.set_sites_cart_from_hierarchy()
out_fn_prefix = inp_fn
if inp_fn.endswith(".pdb") or inp_fn.endswith(".cif"):
out_fn_prefix = inp_fn[:-4]
out_fn = out_fn_prefix + "_iupac.pdb"
if model.input_model_format_cif():
out_fn = out_fn_prefix + "_iupac.cif"
txt = model.model_as_mmcif()
else:
out_fn = out_fn_prefix + "_iupac.cif"
txt = model.model_as_pdb()
with open(out_fn, 'w') as f:
f.write(txt)
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 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(tolerance=0.01):
for use_neutron_distances in [True, False]:
mon_lib_srv = monomer_library.server.server()
ener_lib = monomer_library.server.ener_lib()
inp = iotbx.pdb.input(lines=pdb_str.splitlines(), source_info=None)
params = iotbx.phil.parse(input_string=grand_master_phil_str,
process_includes=True).extract()
params.pdb_interpretation.use_neutron_distances = use_neutron_distances
model = mmtbx.model.manager(model_input=inp)
model.process(pdb_interpretation_params=params, make_restraints=True)
ph = model.get_hierarchy()
ph.write_pdb_file(file_name="input.pdb")
m = geometry_minimization.run2(
restraints_manager=model.get_restraints_manager(),
pdb_hierarchy=ph,
correct_special_position_tolerance=1.0,
bond=True,
nonbonded=True,
angle=True,
dihedral=True,
chirality=True,
planarity=True)
model.set_sites_cart_from_hierarchy()
suffix = "X"
if (use_neutron_distances): suffix = "N"
ph.write_pdb_file(file_name="output_%s.pdb" % suffix)
# check X-H distances: x-ray
cntr = 0
awl = iotbx.pdb.input(file_name="output_X.pdb").atoms_with_labels()
for a1 in awl:
n1 = a1.name.strip()
for a2 in awl:
n2 = a2.name.strip()
if ([n1, n2] == ["CD1", "HD1"] or [n1, n2] == ["CD2", "HD2"]
or [n1, n2] == ["CE1", "HE1"]
or [n1, n2] == ["CE2", "HE2"]):
assert approx_equal(dist(a1.xyz, a2.xyz), 0.93, tolerance)
cntr += 1
if (n1 == "OH" and n2 in ["HH", "DH"]):
assert approx_equal(dist(a1.xyz, a2.xyz), 0.84, tolerance)
cntr += 1
if ([n1, n2] == ["CB", "HB2"] or [n1, n2] == ["CB", "HB3"]
or [n1, n2] == ["CA", "HA"]):
assert approx_equal(dist(a1.xyz, a2.xyz), 0.97, tolerance)
cntr += 1
if (n1 == "O" and n2 in ["D1", "D2"] and a1.resname == "HOH"):
assert approx_equal(dist(a1.xyz, a2.xyz), 0.85, tolerance)
cntr += 1
assert cntr == 11, cntr
# check X-H distances: neutron
cntr = 0
awl = iotbx.pdb.input(file_name="output_N.pdb").atoms_with_labels()
for a1 in awl:
n1 = a1.name.strip()
for a2 in awl:
n2 = a2.name.strip()
if ([n1, n2] == ["CD1", "HD1"] or [n1, n2] == ["CD2", "HD2"]
or [n1, n2] == ["CE1", "HE1"]
or [n1, n2] == ["CE2", "HE2"]):
assert approx_equal(dist(a1.xyz, a2.xyz), 1.08, tolerance), """
dist(a1.xyz, a2.xyz) : %f
tolerance : %f
""" % (
dist(a1.xyz, a2.xyz),
tolerance,
)
cntr += 1
if (n1 == "OH" and n2 in ["HH", "DH"]):
assert approx_equal(dist(a1.xyz, a2.xyz), 0.98, tolerance)
cntr += 1
if ([n1, n2] == ["CB", "HB2"] or [n1, n2] == ["CB", "HB3"]
or [n1, n2] == ["CA", "HA"]):
assert approx_equal(dist(a1.xyz, a2.xyz), 1.09, tolerance)
cntr += 1
if (n1 == "O" and n2 in ["D1", "D2"] and a1.resname == "HOH"):
assert approx_equal(dist(a1.xyz, a2.xyz), 0.98, tolerance)
cntr += 1
assert cntr == 11, cntr
def __init__(self,
model,
target_map,
refine_ncs_operators=False,
number_of_cycles=1,
cycles_to_converge=2,
log=None):
# completely new way of doing this. using RSR macro-cycle
# for test compatibility:
print("Minimizing using reference map...", file=log)
if model.ncs_constraints_present():
print(" Minimizing... (NCS)", file=log)
else:
print(" Minimizing...", file=log)
from phenix.refinement.macro_cycle_real_space import run as rsr_mc_run
import scitbx.math
from phenix.command_line.real_space_refine import extract_rigid_body_selections
from phenix.command_line.real_space_refine import master_params as rsr_master_params
from mmtbx.refinement.real_space.utils import target_map as rsr_target_map
import mmtbx.idealized_aa_residues.rotamer_manager
sin_cos_table = scitbx.math.sin_cos_table(n=10000)
params = rsr_master_params().extract()
params.pdb_interpretation = model._pdb_interpretation_params.pdb_interpretation
params.refinement.run = "minimization_global+local_grid_search"
params.refine_ncs_operators = False
params.output.write_all_states = True
rotamer_manager = mmtbx.idealized_aa_residues.rotamer_manager.load(
rotamers="favored")
rigid_body_selections = extract_rigid_body_selections(
params=params,
ncs_groups=model.get_ncs_groups(),
pdb_hierarchy=model.get_hierarchy())
rsr_tm = rsr_target_map(map_data=target_map,
xray_structure=model.get_xray_structure(),
d_min=3.8,
atom_radius=params.refinement.atom_radius)
res = rsr_mc_run(params=params,
model=model,
target_map=rsr_tm,
log=log,
ncs_groups=model.get_ncs_groups(),
rotamer_manager=rotamer_manager,
sin_cos_table=sin_cos_table,
rigid_body_selections=rigid_body_selections)
model.set_sites_cart_from_hierarchy(res.model.get_hierarchy())
res.structure_monitor.states_collector.write(
file_name="rsr_all_states.pdb")
return
# end ===================================================
from mmtbx.refinement.geometry_minimization import add_rotamer_restraints
from mmtbx.refinement.minimization_monitor import minimization_monitor
self.model = model
self.log = log
print("Minimizing using reference map...", file=self.log)
self.log.flush()
# copy-paste from cctbx_project/mmtbx/refinement/geometry_minimization.py:
# minimize_wrapper_for_ramachandran
self.model.get_restraints_manager().geometry.pair_proxies(
sites_cart=self.model.get_sites_cart())
ncs_restraints_group_list = self.model.get_ncs_groups()
if ncs_restraints_group_list is None:
ncs_restraints_group_list = []
ncs_groups = None
if len(ncs_restraints_group_list) > 0:
ncs_groups = ncs_restraints_group_list
min_monitor = minimization_monitor(
number_of_cycles=number_of_cycles,
max_number_of_cycles=20,
cycles_to_converge=cycles_to_converge,
mode="no_outliers")
selection_real_space = None
import mmtbx.refinement.real_space.weight
self.w = 1
print("number_of_cycles", number_of_cycles, file=log)
print("Stats before minimization:", file=log)
ms = self.model.geometry_statistics()
ms.show(log=log)
while min_monitor.need_more_cycles():
print("Cycle number",
min_monitor.get_current_cycle_n(),
file=self.log)
self.model.get_restraints_manager().geometry.\
update_ramachandran_restraints_phi_psi_targets(
hierarchy=self.model.get_hierarchy())
print(" Updating rotamer restraints...", file=self.log)
add_rotamer_restraints(
pdb_hierarchy=self.model.get_hierarchy(),
restraints_manager=self.model.get_restraints_manager(),
selection=None,
sigma=5,
mode="fix_outliers",
accept_allowed=False,
mon_lib_srv=self.model.get_mon_lib_srv(),
rotamer_manager=self.model.get_rotamer_manager())
self.model.set_sites_cart_from_hierarchy()
if min_monitor.need_weight_optimization():
# if self.w is None:
print(" Determining weight...", file=self.log)
self.log.flush()
self.weight = mmtbx.refinement.real_space.weight.run(
map_data=target_map,
xray_structure=self.model.get_xray_structure(),
pdb_hierarchy=self.model.get_hierarchy(),
geometry_restraints_manager=self.model.
get_restraints_manager(),
rms_bonds_limit=0.015,
rms_angles_limit=1.0,
ncs_groups=ncs_groups)
# division is to put more weight onto restraints. Checked. Works.
self.w = self.weight.weight / 3.0
# self.w = self.weight.weight/15.0
# self.w = 0
# self.w = self.weight.weight
for s in self.weight.msg_strings:
print(s, file=self.log)
if ncs_restraints_group_list is None or len(
ncs_restraints_group_list) == 0:
#No NCS
print(" Minimizing...", file=self.log)
print(" with weight %f" % self.w, file=self.log)
self.log.flush()
refine_object = simple(
target_map=target_map,
selection=None,
max_iterations=150,
geometry_restraints_manager=self.model.
get_restraints_manager().geometry,
selection_real_space=selection_real_space,
states_accumulator=None,
ncs_groups=ncs_groups)
refine_object.refine(
weight=self.w,
xray_structure=self.model.get_xray_structure())
self.rmsd_bonds_final, self.rmsd_angles_final = refine_object.rmsds(
)
print("RMSDS:",
self.rmsd_bonds_final,
self.rmsd_angles_final,
file=log)
# print >> log, "sizes:", len(refine_object.sites_cart()), len(self.xrs.scatterers())
self.model.set_sites_cart(refine_object.sites_cart(),
update_grm=True)
# print >> log, "sizes", self.xrs.scatterers()
else:
# Yes NCS
# copy-paste from macro_cycle_real_space.py
# !!! Don't rearrange NCS groups here because master was just fixed!
# import mmtbx.ncs.ncs_utils as nu
# nu.get_list_of_best_ncs_copy_map_correlation(
# ncs_groups = ncs_restraints_group_list,
# xray_structure = self.model.get_xray_structure(),
# map_data = target_map,
# d_min = 3)
print(" Minimizing... (NCS)", file=self.log)
tfg_obj = mmtbx.refinement.minimization_ncs_constraints.\
target_function_and_grads_real_space(
map_data = target_map,
xray_structure = self.model.get_xray_structure(),
ncs_restraints_group_list = ncs_restraints_group_list,
refine_selection = None,
real_space_gradients_delta = 1,
restraints_manager = self.model.get_restraints_manager(),
data_weight = self.w,
refine_sites = True)
minimized = mmtbx.refinement.minimization_ncs_constraints.lbfgs(
target_and_grads_object=tfg_obj,
xray_structure=self.model.get_xray_structure(),
ncs_restraints_group_list=ncs_restraints_group_list,
refine_selection=None,
finite_grad_differences_test=False,
max_iterations=100,
refine_sites=True)
self.model.set_sites_cart(tfg_obj.xray_structure.sites_cart())
ncs_restraints_group_list.recalculate_ncs_transforms(
self.model.get_sites_cart())
ms = self.model.geometry_statistics()
min_monitor.save_cycle_results(geometry=ms)
ms.show(log=log)
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)