Author: bugman
Date: Thu Mar 17 13:31:59 2011
New Revision: 12812
URL: http://svn.gna.org/viewcvs/relax?rev=12812&view=rev
Log:
Alphabetical arrangement of the methods.
Modified:
1.3/specific_fns/model_free/bmrb.py
Modified: 1.3/specific_fns/model_free/bmrb.py
URL:
http://svn.gna.org/viewcvs/relax/1.3/specific_fns/model_free/bmrb.py?rev=12812&r1=12811&r2=12812&view=diff
==============================================================================
--- 1.3/specific_fns/model_free/bmrb.py (original)
+++ 1.3/specific_fns/model_free/bmrb.py Thu Mar 17 13:31:59 2011
@@ -93,6 +93,199 @@
raise RelaxError("The BMRB model-free model '%s' is unknown." %
name)
+ def _sf_model_free_read(self, star, sample_conditions=None):
+ """Fill the spin containers with the model-free data from the
saveframe records.
+
+ @param star: The NMR-STAR dictionary object.
+ @type star: NMR_STAR instance
+ @keyword sample_conditions: The sample condition label to read.
Only one sample condition can be read per data pipe.
+ @type sample_conditions: None or str
+ """
+
+ # The list of model-free parameters (both bmrblib names and relax
names).
+ mf_bmrb_key = ['bond_length', 'local_tm', 's2', 's2f', 's2s', 'te',
'tf', 'ts', 'rex', 'chi2']
+ mf_params = ['r', 'local_tm', 's2', 's2f', 's2s', 'te', 'tf',
'ts', 'rex', 'chi2']
+
+ # Get the entities.
+ for data in star.model_free.loop():
+ # Store the keys.
+ keys = data.keys()
+
+ # Sample conditions do not match (remove the $ sign).
+ if 'sample_cond_list_label' in keys and sample_conditions and
string.replace(data['sample_cond_list_label'], '$', '') != sample_conditions:
+ continue
+
+ # Global data.
+ if 'global_chi2' in keys:
+ setattr(cdp, 'chi2', data['global_chi2'])
+
+ # The number of spins.
+ N = bmrb.num_spins(data)
+
+ # No data in the saveframe.
+ if N == 0:
+ continue
+
+ # The molecule names.
+ mol_names = bmrb.molecule_names(data, N)
+
+ # Missing atom names.
+ if 'atom_names' not in keys or data['atom_names'] == None:
+ data['atom_names'] = [None] * N
+
+ # Generate the sequence if needed.
+ bmrb.generate_sequence(N, spin_names=data['atom_names'],
res_nums=data['res_nums'], res_names=data['res_names'], mol_names=mol_names)
+
+ # Correlation time scaling.
+ table = {'s': 1.0,
+ 'ns': 1e-9,
+ 'ps': 1e-12}
+ te_scale = 1.0
+ if data['te_units']:
+ te_scale = table[data['te_units']]
+
+ # Fast correlation time scaling.
+ if data['tf_units']:
+ tf_scale = table[data['tf_units']]
+ else:
+ tf_scale = te_scale
+
+ # Slow correlation time scaling.
+ if data['ts_units']:
+ ts_scale = table[data['ts_units']]
+ else:
+ ts_scale = te_scale
+
+ # Rex scaling.
+ rex_scale = 1.0
+ if hasattr(cdp, 'frq') and len(cdp.frq):
+ rex_scale = 1.0 / (2.0*pi*cdp.frq[cdp.ri_ids[0]])**2
+
+ # Loop over the spins.
+ for i in range(N):
+ # Generate a spin ID.
+ spin_id =
mol_res_spin.generate_spin_id(mol_name=mol_names[i],
res_name=data['res_names'][i], res_num=data['res_nums'][i],
spin_name=data['atom_names'][i])
+
+ # Obtain the spin.
+ spin = mol_res_spin.return_spin(spin_id)
+
+ # No spin?!?
+ if spin == None:
+ raise(RelaxError("The spin '%s' does not exist." %
spin_id))
+
+ # Loop over and set the model-free parameters.
+ for j in range(len(mf_params)):
+ # The parameter.
+ param = mf_params[j]
+
+ # No parameter.
+ if not mf_bmrb_key[j] in keys:
+ continue
+
+ # The parameter and its value.
+ if data[mf_bmrb_key[j]] != None:
+ # The value.
+ value = data[mf_bmrb_key[j]][i]
+
+ # A te value which should be ts!
+ if param == 'te' and not hasattr(spin, 'te'):
+ if (data['s2s'] and data['s2s'][i] != None) or
(data['s2f'] and data['s2f'][i] != None):
+ # Change the parameter name of te to ts.
+ param = 'ts'
+
+ # Set the te and te_err values to None.
+ spin.te = None
+ spin.te_err = None
+
+ # Parameter scaling.
+ if value != None:
+ if param == 'te':
+ value = value * te_scale
+ elif param == 'tf':
+ value = value * tf_scale
+ elif param == 'ts':
+ value = value * ts_scale
+ elif param == 'rex':
+ value = value * rex_scale
+
+ # No parameter value.
+ else:
+ value = None
+
+ # Set the parameter.
+ setattr(spin, param, value)
+
+ # The error.
+ mf_bmrb_key_err = mf_bmrb_key[j] + '_err'
+ error = None
+ if mf_bmrb_key_err in keys and data[mf_bmrb_key_err] !=
None:
+ error = data[mf_bmrb_key_err][i]
+
+ # Error scaling.
+ if error != None:
+ if param == 'te':
+ error = error * te_scale
+ elif param == 'tf':
+ error = error * tf_scale
+ elif param == 'ts':
+ error = error * ts_scale
+ elif param == 'rex':
+ error = error * rex_scale
+
+ # Set the error.
+ mf_param_err = param + '_err'
+ if mf_bmrb_key_err in keys and data[mf_bmrb_key_err] !=
None:
+ setattr(spin, mf_param_err, error)
+
+ # The model.
+ if data['model_fit'] != None and data['model_fit'][i] !=
None:
+ model = self._from_bmrb_model(data['model_fit'][i])
+ setattr(spin, 'model', model)
+
+ # The equation and parameters.
+ equation, params = self._model_map(model)
+ setattr(spin, 'equation', equation)
+ setattr(spin, 'params', params)
+
+ # The element.
+ if'atom_types' in keys and data['atom_types'] != None:
+ setattr(spin, 'element', data['atom_types'][i])
+
+ # Heteronucleus type.
+ if'atom_types' in keys and data['atom_types'] != None and
data['atom_types'][i] != None and 'isotope' in keys and data['isotope'] !=
None:
+ # The isotope number.
+ iso_num = data['isotope'][i]
+
+ # No isotope number.
+ iso_table = {'C': 13, 'N': 15}
+ if not data['isotope'][i]:
+ iso_num = iso_table[data['atom_types'][i]]
+
+ # Set the type.
+ setattr(spin, 'heteronuc_type', str(iso_num) +
data['atom_types'][i])
+
+
+ def _sf_csa_read(self, star):
+ """Place the CSA data from the saveframe records into the spin
container.
+
+ @param star: The NMR-STAR dictionary object.
+ @type star: NMR_STAR instance
+ """
+
+ # Get the entities.
+ for data in star.chem_shift_anisotropy.loop():
+ # Loop over the spins.
+ for i in range(len(data['data_ids'])):
+ # Generate a spin ID.
+ spin_id =
mol_res_spin.generate_spin_id(res_num=data['res_nums'][i],
spin_name=data['atom_names'][i])
+
+ # Obtain the spin.
+ spin = mol_res_spin.return_spin(spin_id)
+
+ # The CSA value (converted from ppm).
+ setattr(spin, 'csa', data['csa'][i] * 1e-6)
+
+
def _to_bmrb_model(self, name=None):
"""Convert the model-free model name to the BMRB name.
@@ -133,199 +326,6 @@
return map[name]
- def _sf_model_free_read(self, star, sample_conditions=None):
- """Fill the spin containers with the model-free data from the
saveframe records.
-
- @param star: The NMR-STAR dictionary object.
- @type star: NMR_STAR instance
- @keyword sample_conditions: The sample condition label to read.
Only one sample condition can be read per data pipe.
- @type sample_conditions: None or str
- """
-
- # The list of model-free parameters (both bmrblib names and relax
names).
- mf_bmrb_key = ['bond_length', 'local_tm', 's2', 's2f', 's2s', 'te',
'tf', 'ts', 'rex', 'chi2']
- mf_params = ['r', 'local_tm', 's2', 's2f', 's2s', 'te', 'tf',
'ts', 'rex', 'chi2']
-
- # Get the entities.
- for data in star.model_free.loop():
- # Store the keys.
- keys = data.keys()
-
- # Sample conditions do not match (remove the $ sign).
- if 'sample_cond_list_label' in keys and sample_conditions and
string.replace(data['sample_cond_list_label'], '$', '') != sample_conditions:
- continue
-
- # Global data.
- if 'global_chi2' in keys:
- setattr(cdp, 'chi2', data['global_chi2'])
-
- # The number of spins.
- N = bmrb.num_spins(data)
-
- # No data in the saveframe.
- if N == 0:
- continue
-
- # The molecule names.
- mol_names = bmrb.molecule_names(data, N)
-
- # Missing atom names.
- if 'atom_names' not in keys or data['atom_names'] == None:
- data['atom_names'] = [None] * N
-
- # Generate the sequence if needed.
- bmrb.generate_sequence(N, spin_names=data['atom_names'],
res_nums=data['res_nums'], res_names=data['res_names'], mol_names=mol_names)
-
- # Correlation time scaling.
- table = {'s': 1.0,
- 'ns': 1e-9,
- 'ps': 1e-12}
- te_scale = 1.0
- if data['te_units']:
- te_scale = table[data['te_units']]
-
- # Fast correlation time scaling.
- if data['tf_units']:
- tf_scale = table[data['tf_units']]
- else:
- tf_scale = te_scale
-
- # Slow correlation time scaling.
- if data['ts_units']:
- ts_scale = table[data['ts_units']]
- else:
- ts_scale = te_scale
-
- # Rex scaling.
- rex_scale = 1.0
- if hasattr(cdp, 'frq') and len(cdp.frq):
- rex_scale = 1.0 / (2.0*pi*cdp.frq[cdp.ri_ids[0]])**2
-
- # Loop over the spins.
- for i in range(N):
- # Generate a spin ID.
- spin_id =
mol_res_spin.generate_spin_id(mol_name=mol_names[i],
res_name=data['res_names'][i], res_num=data['res_nums'][i],
spin_name=data['atom_names'][i])
-
- # Obtain the spin.
- spin = mol_res_spin.return_spin(spin_id)
-
- # No spin?!?
- if spin == None:
- raise(RelaxError("The spin '%s' does not exist." %
spin_id))
-
- # Loop over and set the model-free parameters.
- for j in range(len(mf_params)):
- # The parameter.
- param = mf_params[j]
-
- # No parameter.
- if not mf_bmrb_key[j] in keys:
- continue
-
- # The parameter and its value.
- if data[mf_bmrb_key[j]] != None:
- # The value.
- value = data[mf_bmrb_key[j]][i]
-
- # A te value which should be ts!
- if param == 'te' and not hasattr(spin, 'te'):
- if (data['s2s'] and data['s2s'][i] != None) or
(data['s2f'] and data['s2f'][i] != None):
- # Change the parameter name of te to ts.
- param = 'ts'
-
- # Set the te and te_err values to None.
- spin.te = None
- spin.te_err = None
-
- # Parameter scaling.
- if value != None:
- if param == 'te':
- value = value * te_scale
- elif param == 'tf':
- value = value * tf_scale
- elif param == 'ts':
- value = value * ts_scale
- elif param == 'rex':
- value = value * rex_scale
-
- # No parameter value.
- else:
- value = None
-
- # Set the parameter.
- setattr(spin, param, value)
-
- # The error.
- mf_bmrb_key_err = mf_bmrb_key[j] + '_err'
- error = None
- if mf_bmrb_key_err in keys and data[mf_bmrb_key_err] !=
None:
- error = data[mf_bmrb_key_err][i]
-
- # Error scaling.
- if error != None:
- if param == 'te':
- error = error * te_scale
- elif param == 'tf':
- error = error * tf_scale
- elif param == 'ts':
- error = error * ts_scale
- elif param == 'rex':
- error = error * rex_scale
-
- # Set the error.
- mf_param_err = param + '_err'
- if mf_bmrb_key_err in keys and data[mf_bmrb_key_err] !=
None:
- setattr(spin, mf_param_err, error)
-
- # The model.
- if data['model_fit'] != None and data['model_fit'][i] !=
None:
- model = self._from_bmrb_model(data['model_fit'][i])
- setattr(spin, 'model', model)
-
- # The equation and parameters.
- equation, params = self._model_map(model)
- setattr(spin, 'equation', equation)
- setattr(spin, 'params', params)
-
- # The element.
- if'atom_types' in keys and data['atom_types'] != None:
- setattr(spin, 'element', data['atom_types'][i])
-
- # Heteronucleus type.
- if'atom_types' in keys and data['atom_types'] != None and
data['atom_types'][i] != None and 'isotope' in keys and data['isotope'] !=
None:
- # The isotope number.
- iso_num = data['isotope'][i]
-
- # No isotope number.
- iso_table = {'C': 13, 'N': 15}
- if not data['isotope'][i]:
- iso_num = iso_table[data['atom_types'][i]]
-
- # Set the type.
- setattr(spin, 'heteronuc_type', str(iso_num) +
data['atom_types'][i])
-
-
- def _sf_csa_read(self, star):
- """Place the CSA data from the saveframe records into the spin
container.
-
- @param star: The NMR-STAR dictionary object.
- @type star: NMR_STAR instance
- """
-
- # Get the entities.
- for data in star.chem_shift_anisotropy.loop():
- # Loop over the spins.
- for i in range(len(data['data_ids'])):
- # Generate a spin ID.
- spin_id =
mol_res_spin.generate_spin_id(res_num=data['res_nums'][i],
spin_name=data['atom_names'][i])
-
- # Obtain the spin.
- spin = mol_res_spin.return_spin(spin_id)
-
- # The CSA value (converted from ppm).
- setattr(spin, 'csa', data['csa'][i] * 1e-6)
-
-
def bmrb_read(self, file_path, version=None, sample_conditions=None):
"""Read the model-free results from a BMRB NMR-STAR v3.1 formatted
file.
r12812 - /1.3/specific_fns/model_free/bmrb.py