def IsotropicADPDataSmoother(chain, num_smooth = 1):
"""Experimental data smoothing of temperature factors.
"""
console.endln()
console.stdoutln("SMOOTHING CHAIN %s ADPs" % (chain.chain_id))
console.kvformat("SMOOTH WINDOW", 2 * num_smooth + 1)
num_frags = len(chain)
smooth_uiso = dict()
ifrag_start = num_smooth
ifrag_end = num_frags - num_smooth - 1
for ifrag in xrange(ifrag_start, ifrag_end + 1):
smooth_frag = chain[ifrag]
frag1 = chain[ifrag - num_smooth]
frag2 = chain[ifrag + num_smooth]
IT, IL, IS, IOrigin = IsotropicFitSegmentOutlierRejection(
chain, frag1.fragment_id, frag2.fragment_id)
for atm, uiso in TLS.iter_itls_uiso(smooth_frag.iter_all_atoms(),
IT, IL, IS, IOrigin):
smooth_uiso[atm] = uiso
if ifrag == ifrag_start:
for i in range(ifrag_start):
smooth_frag = chain[i]
for atm, uiso in TLS.iter_itls_uiso(smooth_frag.iter_all_atoms(),
IT, IL, IS, IOrigin):
smooth_uiso[atm] = uiso
elif ifrag == ifrag_end:
for i in range(ifrag_end + 1, num_frags):
smooth_frag = chain[i]
for atm, uiso in TLS.iter_itls_uiso(smooth_frag.iter_all_atoms(),
IT, IL, IS, IOrigin):
smooth_uiso[atm] = uiso
for atm, uiso in smooth_uiso.iteritems():
atm.temp_factor = Constants.U2B * uiso
atm.U = numpy.identity(3, float) * uiso
def IsotropicADPDataSmoother(chain, num_smooth=1):
"""Experimental data smoothing of temperature factors
"""
console.endln()
console.stdoutln("SMOOTHING CHAIN %s ADPs" % (chain.chain_id))
conesole.kvformat("SMOOTH WINDOW", 2 * num_smooth + 1)
num_frags = len(chain)
smooth_uiso = dict()
ifrag_start = num_smooth
ifrag_end = num_frags - num_smooth - 1
for ifrag in xrange(ifrag_start, ifrag_end + 1):
smooth_frag = chain[ifrag]
frag1 = chain[ifrag - num_smooth]
frag2 = chain[ifrag + num_smooth]
IT, IL, IS, IOrigin = IsotropicFitSegmentOutlierRejection(
chain, frag1.fragment_id, frag2.fragment_id)
for atm, uiso in TLS.iter_itls_uiso(smooth_frag.iter_all_atoms(), IT,
IL, IS, IOrigin):
smooth_uiso[atm] = uiso
if ifrag == ifrag_start:
for i in range(ifrag_start):
smooth_frag = chain[i]
for atm, uiso in TLS.iter_itls_uiso(
smooth_frag.iter_all_atoms(), IT, IL, IS, IOrigin):
smooth_uiso[atm] = uiso
elif ifrag == ifrag_end:
for i in range(ifrag_end + 1, num_frags):
smooth_frag = chain[i]
for atm, uiso in TLS.iter_itls_uiso(
smooth_frag.iter_all_atoms(), IT, IL, IS, IOrigin):
smooth_uiso[atm] = uiso
for atm, uiso in smooth_uiso.iteritems():
atm.temp_factor = Constants.U2B * uiso
atm.U = numpy.identity(3, float) * uiso
def ResidualInfo(chain, range, tlsdict):
IT, IL, IS, IO = tls_calcs.isotlsdict2tensors(tlsdict)
num_atoms = 0
weight_sum = 0.0
msd_sum = 0.0
atomiter = iter_fragment_atoms(chain.iter_fragments(*range))
for atm, uiso_tls in TLS.iter_itls_uiso(atomiter, IT, IL, IS, IO):
num_atoms += 1
delta = atm.temp_factor - (Constants.U2B * uiso_tls)
msd_sum += atm.occupancy * delta**2
weight_sum += atm.occupancy
msd = msd_sum / weight_sum
return msd
def ResidualInfo(chain, range, tlsdict):
IT, IL, IS, IO = tls_calcs.isotlsdict2tensors(tlsdict)
num_atoms = 0
weight_sum = 0.0
msd_sum = 0.0
atomiter = iter_fragment_atoms(chain.iter_fragments(*range))
for atm, uiso_tls in TLS.iter_itls_uiso(atomiter, IT, IL, IS, IO):
num_atoms += 1
delta = atm.temp_factor - (Constants.U2B * uiso_tls)
msd_sum += atm.occupancy * delta**2
weight_sum += atm.occupancy
msd = msd_sum / weight_sum
return msd
def calc_rmsd_tls_biso(tls_group):
"""Calculate the RMSD of the tls_group using the isotropic TLS model.
"""
T = tls_group.itls_T
L = tls_group.itls_L
S = tls_group.itls_S
O = tls_group.origin
msd_sum = 0.0
for atm, uiso_tls in TLS.iter_itls_uiso(iter(tls_group), T, L, S, O):
msd_sum += (Constants.U2B*uiso_tls - atm.temp_factor)**2
if len(tls_group)>0:
msd = msd_sum / len(tls_group)
rmsd = math.sqrt(msd)
else:
rmsd = 0.0
return rmsd
def IsotropicFitSegmentOutlierRejection(chain, frag_id1, frag_id2):
segment = chain[frag_id1:frag_id2]
atoms = list(segment.iter_all_atoms())
orig_num_atoms = len(atoms)
rejected = 0
while True:
tls_analyzer = tlsmdmodule.TLSModelAnalyzer()
xlist = atom_selection.chain_to_xmlrpc_list(iter(atoms))
tls_analyzer.set_xmlrpc_chain(xlist)
tlsdict = tls_analyzer.isotropic_fit_segment(frag_id1, frag_id2)
IT, IL, IS, IOrigin = tls_calcs.isotlsdict2tensors(tlsdict)
num_atoms = 0
msd_sum = 0.0
atm_deltab = []
for atm, uiso in TLS.iter_itls_uiso(iter(atoms), IT, IL, IS, IOrigin):
num_atoms += 1
deltab = atm.temp_factor - (Constants.U2B * uiso)
msd_sum += deltab**2
atm_deltab.append((deltab, atm))
sigma = math.sqrt((msd_sum / num_atoms))
sigma2 = 2.0 * sigma
outliers = 0
for deltab, atm in atm_deltab:
if abs(deltab) > sigma2:
atoms.remove(atm)
outliers += 1
rejected += outliers
if outliers == 0 or (num_atoms - outliers) < 10:
console.stdoutln("SEGMENT %s-%s %d->%d" %
(frag_id1, frag_id2, orig_num_atoms,
orig_num_atoms - rejected))
return IT, IL, IS, IOrigin
def IsotropicFitSegmentOutlierRejection(chain, frag_id1, frag_id2):
segment = chain[frag_id1:frag_id2]
atoms = list(segment.iter_all_atoms())
orig_num_atoms = len(atoms)
rejected = 0
while True:
tls_analyzer = tlsmdmodule.TLSModelAnalyzer()
xlist = atom_selection.chain_to_xmlrpc_list(iter(atoms))
tls_analyzer.set_xmlrpc_chain(xlist)
tlsdict = tls_analyzer.isotropic_fit_segment(frag_id1, frag_id2)
IT, IL, IS, IOrigin = tls_calcs.isotlsdict2tensors(tlsdict)
num_atoms = 0
msd_sum = 0.0
atm_deltab = []
for atm, uiso in TLS.iter_itls_uiso(iter(atoms), IT, IL, IS, IOrigin):
num_atoms += 1;
deltab = atm.temp_factor - (Constants.U2B * uiso)
msd_sum += deltab**2
atm_deltab.append((deltab, atm))
sigma = math.sqrt((msd_sum / num_atoms))
sigma2 = 2.0 * sigma
outliers = 0
for deltab, atm in atm_deltab:
if abs(deltab) > sigma2:
atoms.remove(atm)
outliers += 1
rejected += outliers
if outliers == 0 or (num_atoms - outliers) < 10:
console.stdoutln("SEGMENT %s-%s %d->%d" % (
frag_id1, frag_id2, orig_num_atoms, orig_num_atoms - rejected))
return IT, IL, IS, IOrigin
