def get_cas_from_three(three):
cas = []
for residue in three:
for atom in residue.atoms():
if atom.name == " CA ":
cas.append(atom)
break
else:
cas.append(None)
return cas
def __init__ (self, pdb_hierarchy,
outliers_only=False,
out=sys.stdout,
collect_ideal=False,
quiet=False) :
validation.__init__(self)
self._outlier_i_seqs = flex.size_t()
self.beta_ideal = {}
relevant_atom_names = {
" CA ": None, " N ": None, " C ": None, " CB ": None} # FUTURE: set
output_list = []
from mmtbx.validation import utils
use_segids = utils.use_segids_in_place_of_chainids(
hierarchy=pdb_hierarchy)
for model in pdb_hierarchy.models():
for chain in model.chains():
if use_segids:
chain_id = utils.get_segid_as_chainid(chain=chain)
else:
chain_id = chain.id
for rg in chain.residue_groups():
for i_cf,cf in enumerate(rg.conformers()):
for i_residue,residue in enumerate(cf.residues()):
if (residue.resname == "GLY") :
continue
is_first = (i_cf == 0)
is_alt_conf = False
relevant_atoms = {}
for atom in residue.atoms():
if (atom.name in relevant_atom_names):
relevant_atoms[atom.name] = atom
if (len(atom.parent().altloc) != 0):
is_alt_conf = True
if ((is_first or is_alt_conf) and len(relevant_atoms) == 4):
result = calculate_ideal_and_deviation(
relevant_atoms=relevant_atoms,
resname=residue.resname)
dev = result.deviation
dihedralNABB = result.dihedral
betaxyz = result.ideal
if (dev is None) : continue
if(dev >=0.25 or outliers_only==False):
if(dev >=0.25):
self.n_outliers+=1
self._outlier_i_seqs.append(atom.i_seq)
if (is_alt_conf):
altchar = cf.altloc
else:
altchar = " "
res=residue.resname.lower()
sub=chain.id
if(len(sub)==1):
sub=" "+sub
resCB = relevant_atoms[" CB "]
result = cbeta(
chain_id=chain_id,
resname=residue.resname,
resseq=residue.resseq,
icode=residue.icode,
altloc=altchar,
xyz=resCB.xyz,
occupancy=resCB.occ,
deviation=dev,
dihedral_NABB=dihedralNABB,
ideal_xyz=betaxyz,
outlier=(dev >= 0.25))
self.results.append(result)
key = result.id_str()
if (collect_ideal) :
self.beta_ideal[key] = betaxyz
def get_center (residue):
for atom in residue.atoms():
if atom.name == " CA ":
return atom.xyz
return residue.atoms().extract_xyz().mean()
def __init__(self,
pdb_hierarchy,
outliers_only=False,
out=sys.stdout,
collect_ideal=False,
quiet=False):
validation.__init__(self)
self._outlier_i_seqs = flex.size_t()
self.beta_ideal = {}
relevant_atom_names = {
" CA ": None,
" N ": None,
" C ": None,
" CB ": None
} # FUTURE: set
output_list = []
self.stats = group_args(n_results=0,
n_weighted_results=0,
n_weighted_outliers=0)
from mmtbx.validation import utils
use_segids = utils.use_segids_in_place_of_chainids(
hierarchy=pdb_hierarchy)
for model in pdb_hierarchy.models():
for chain in model.chains():
if use_segids:
chain_id = utils.get_segid_as_chainid(chain=chain)
else:
chain_id = chain.id
for rg in chain.residue_groups():
for i_cf, cf in enumerate(rg.conformers()):
for i_residue, residue in enumerate(cf.residues()):
if (residue.resname == "GLY"):
continue
is_first = (i_cf == 0)
is_alt_conf = False
relevant_atoms = {}
for atom in residue.atoms():
if (atom.name in relevant_atom_names):
relevant_atoms[atom.name] = atom
if (len(atom.parent().altloc) != 0):
is_alt_conf = True
if ((is_first or is_alt_conf)
and len(relevant_atoms) == 4):
result = calculate_ideal_and_deviation(
relevant_atoms=relevant_atoms,
resname=residue.resname)
dev = result.deviation
dihedralNABB = result.dihedral
betaxyz = result.ideal
if (dev is None): continue
resCB = relevant_atoms[" CB "]
self.stats.n_results += 1
self.stats.n_weighted_results += resCB.occ
if (dev >= 0.25 or outliers_only == False):
if (dev >= 0.25):
self.n_outliers += 1
self.stats.n_weighted_outliers += resCB.occ
self._outlier_i_seqs.append(atom.i_seq)
if (is_alt_conf):
altchar = cf.altloc
else:
altchar = " "
res = residue.resname.lower()
sub = chain.id
if (len(sub) == 1):
sub = " " + sub
result = cbeta(chain_id=chain_id,
resname=residue.resname,
resseq=residue.resseq,
icode=residue.icode,
altloc=altchar,
xyz=resCB.xyz,
occupancy=resCB.occ,
deviation=dev,
dihedral_NABB=dihedralNABB,
ideal_xyz=betaxyz,
outlier=(dev >= 0.25))
self.results.append(result)
key = result.id_str()
if (collect_ideal):
self.beta_ideal[key] = betaxyz
def __init__(self,
pdb_hierarchy,
outliers_only=False,
out=sys.stdout,
collect_ideal=False,
apply_phi_psi_correction=False,
display_phi_psi_correction=False,
quiet=False):
validation.__init__(self)
self._outlier_i_seqs = flex.size_t()
self.beta_ideal = {}
output_list = []
self.stats = group_args(n_results=0,
n_weighted_results=0,
n_weighted_outliers=0)
if apply_phi_psi_correction:
phi_psi_angles = get_phi_psi_dict(pdb_hierarchy)
new_outliers = 0
outliers_removed = 0
total_residues = 0
from mmtbx.validation import utils
use_segids = utils.use_segids_in_place_of_chainids(
hierarchy=pdb_hierarchy)
for model in pdb_hierarchy.models():
for chain in model.chains():
if use_segids:
chain_id = utils.get_segid_as_chainid(chain=chain)
else:
chain_id = chain.id
for rg in chain.residue_groups():
for i_cf, cf in enumerate(rg.conformers()):
for i_residue, residue in enumerate(cf.residues()):
if (residue.resname == "GLY"):
continue
is_first = (i_cf == 0)
is_alt_conf = False
relevant_atoms = {}
for atom in residue.atoms():
if (atom.name in relevant_atom_names):
relevant_atoms[atom.name] = atom
if (len(atom.parent().altloc) != 0):
is_alt_conf = True
if ((is_first or is_alt_conf)
and len(relevant_atoms) == 4):
result = calculate_ideal_and_deviation(
relevant_atoms=relevant_atoms,
resname=residue.resname)
dev = result.deviation
dihedralNABB = result.dihedral
betaxyz = result.ideal
if (dev is None): continue
resCB = relevant_atoms[" CB "]
self.stats.n_results += 1
self.stats.n_weighted_results += resCB.occ
if (is_alt_conf):
altchar = cf.altloc
else:
altchar = " "
if apply_phi_psi_correction:
total_residues += 1
id_str = '|%s:%s|' % (residue.id_str(),
altchar)
phi_psi = phi_psi_angles.get(id_str, None)
if phi_psi:
rc = cbd_utils.get_phi_psi_correction(
result,
residue,
phi_psi,
display_phi_psi_correction=
display_phi_psi_correction,
)
if rc:
dev, dihedralNABB, start, finish = rc
if start and not finish:
outliers_removed += 1
elif not start and finish:
new_outliers += 1
if (dev >= 0.25 or outliers_only == False):
if (dev >= 0.25):
self.n_outliers += 1
self.stats.n_weighted_outliers += resCB.occ
self._outlier_i_seqs.append(atom.i_seq)
res = residue.resname.lower()
sub = chain.id
if (len(sub) == 1):
sub = " " + sub
result = cbeta(chain_id=chain_id,
resname=residue.resname,
resseq=residue.resseq,
icode=residue.icode,
altloc=altchar,
xyz=resCB.xyz,
occupancy=resCB.occ,
deviation=dev,
dihedral_NABB=dihedralNABB,
ideal_xyz=betaxyz,
outlier=(dev >= 0.25))
self.results.append(result)
key = result.id_str()
if (collect_ideal):
self.beta_ideal[key] = betaxyz
if apply_phi_psi_correction:
print('''
Outliers removed : %5d
New outliers : %5d
Num. of outliers : %5d
Num. of residues : %5d
''' % (
outliers_removed,
new_outliers,
self.n_outliers,
total_residues,
))
def get_center(residue):
for atom in residue.atoms():
if atom.name == " CA ":
return atom.xyz
return None
def get_center(residue):
for atom in residue.atoms():
if atom.name == " CA ":
return atom.xyz
return None
