def decode_atom_string(atom_str, use_segids=False):
# Example:
# ' A 49 LEU HD11B'
if (not use_segids) or (len(atom_str) == 16):
return atom_info(chain_id=atom_str[0:2],
resseq=atom_str[2:6],
icode=atom_str[6],
resname=atom_str[7:10],
altloc=atom_str[15],
name=atom_str[11:15])
else:
return atom_info(chain_id=atom_str[0:4],
resseq=atom_str[4:8],
icode=atom_str[8],
resname=atom_str[9:12],
altloc=atom_str[17],
name=atom_str[13:17])
def decode_atom_string (atom_str, use_segids=False) :
# Example:
# ' A 49 LEU HD11B'
if (not use_segids) or (len(atom_str) == 16) :
return atom_info(
chain_id=atom_str[0:2],
resseq=atom_str[2:6],
icode=atom_str[6],
resname=atom_str[7:10],
altloc=atom_str[15],
name=atom_str[11:15])
else:
return atom_info(
chain_id=atom_str[0:4],
resseq=atom_str[4:8],
icode=atom_str[8],
resname=atom_str[9:12],
altloc=atom_str[17],
name=atom_str[13:17])
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_cart = xray_structure.sites_cart()
sites_frac = xray_structure.sites_frac()
sel_cache = pdb_hierarchy.atom_selection_cache()
water_sel = sel_cache.selection("resname HOH and name O")
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)
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 __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 __init__ (self, pdb_hierarchy, xray_structure, fmodel,
distance_cutoff=4.0, collect_all=True) :
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_cart = xray_structure.sites_cart()
sites_frac = xray_structure.sites_frac()
sel_cache = pdb_hierarchy.atom_selection_cache()
water_sel = sel_cache.selection("resname HOH and name O")
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)
