def read_range(self):
condition = self.condition_menu.condition()
residue_range = (pyutil.string_to_int(self.range_variables[0].get()),
pyutil.string_to_int(self.range_variables[1].get()))
if residue_range[0] == None or residue_range[1] == None:
self.progress_report('Must select residue range.')
return 0
reslist = self.range_resonances(condition, residue_range)
if len(reslist) == 0:
self.progress_report('No residues in selected range.')
return 0
seq = sequence.molecule_sequence(condition.molecule)
if seq == None:
self.progress_report('Molecule sequence unknown.')
return 0
self.residue_range = residue_range
self.resonances = reslist
self.sequence = seq
return 1
def read_range(self):
condition = self.condition_menu.condition()
residue_range = (pyutil.string_to_int(self.range_variables[0].get()),
pyutil.string_to_int(self.range_variables[1].get()))
if residue_range[0] == None or residue_range[1] == None:
self.progress_report('Must select residue range.')
return 0
reslist = self.range_resonances(condition, residue_range)
if len(reslist) == 0:
self.progress_report('No residues in selected range.')
return 0
seq = sequence.molecule_sequence(condition.molecule)
if seq == None:
self.progress_report('Molecule sequence unknown.')
return 0
self.residue_range = residue_range
self.resonances = reslist
self.sequence = seq
# Compute global ncIDP-based random coil chemical shifts
self.RC_prediction = shiftstats_ncIDP.resonance_statistics(reslist)
return 1
def write_spectrum_table(self, asys, molecule, tolerances, temp_directory):
table_path = os.path.join(temp_directory, 'table.aat')
f = open(table_path, 'w')
f.write('#\n' +
'# %s table file for AutoAssign\n' % molecule.name +
'#\n')
f.write('Protein: %s\n' % molecule.name)
f.write('\n')
seq = sequence.molecule_sequence(molecule)
f.write('Sequence: %d %s*\n' % (seq.first_residue_number,
seq.one_letter_codes))
f.write('\n')
toltext = ''
for atom_name in ('HN', 'N15', 'CA', 'CB', 'HA', 'CO'):
toltext = toltext + ' %s %.3f' % (atom_name, tolerances[atom_name])
f.write('Tolerances: %s\n' % toltext)
f.write('\n')
f.write('Spectra:\n')
for asp in asys.assignable_spectra:
self.write_spectrum_table_entry(asp, f)
f.write('$\n')
f.close()
def read_range(self):
condition = self.condition_menu.condition()
residue_range = (pyutil.string_to_int(self.range_variables[0].get()),
pyutil.string_to_int(self.range_variables[1].get()))
if residue_range[0] == None or residue_range[1] == None:
self.progress_report('Must select residue range.')
return 0
reslist = self.range_resonances(condition, residue_range)
if len(reslist) == 0:
self.progress_report('No residues in selected range.')
return 0
seq = sequence.molecule_sequence(condition.molecule)
if seq == None:
self.progress_report('Molecule sequence unknown.')
return 0
self.residue_range = residue_range
self.resonances = reslist
self.sequence = seq
return 1
def single_resonance_statistics(r):
"""
Compute global, sequence-specific ncIDP-based chemical shifts using resonance list
"""
seq = sequence.molecule_sequence(r.condition.molecule).one_letter_codes
path = get_sparky_home()+'/Python'
prediction = compute_RC(path+'/ncIDP-cs.tab', path+'/ncIDP-dev.tab', seq)
return prediction
def assignable_spectrum_from_pattern(spectrum, tolerances,
pattern_name, pattern_axes, stoppable):
remember_pattern(spectrum, pattern_name, pattern_axes)
seq = sequence.molecule_sequence(spectrum.molecule)
pattern_list = expected_peak_descriptions[pattern_name]
epeaks = []
for pat in pattern_list:
stoppable.progress_report(pattern_name + ' pattern ' + pat)
patpeaks = expected_peaks_from_pattern(pat, pattern_axes, seq)
epeaks = epeaks + patpeaks
asp = assignable_spectrum(spectrum, seq, epeaks, tolerances)
asp.expected_peak_pattern_name = pattern_name
asp.pattern_axis_order = pattern_axes
return asp