Author: bugman
Date: Sun Mar 23 01:55:05 2008
New Revision: 5173
URL: http://svn.gna.org/viewcvs/relax?rev=5173&view=rev
Log:
Shifted all the setting up of data for model-free minimisation into its own
function.
Modified:
1.3/specific_fns/model_free/mf_minimise.py
Modified: 1.3/specific_fns/model_free/mf_minimise.py
URL:
http://svn.gna.org/viewcvs/relax/1.3/specific_fns/model_free/mf_minimise.py?rev=5173&r1=5172&r2=5173&view=diff
==============================================================================
--- 1.3/specific_fns/model_free/mf_minimise.py (original)
+++ 1.3/specific_fns/model_free/mf_minimise.py Sun Mar 23 01:55:05 2008
@@ -872,140 +872,6 @@
g_count = 0
h_count = 0
- # Initialise the data structures for the model-free function.
- relax_data = []
- relax_error = []
- equations = []
- param_types = []
- param_values = None
- r = []
- csa = []
- num_frq = []
- frq = []
- num_ri = []
- remap_table = []
- noe_r1_table = []
- ri_labels = []
- num_params = []
- xh_unit_vectors = []
- if param_set == 'local_tm':
- mf_params = []
- elif param_set == 'diff':
- param_values = []
-
- # Set up the data for the back_calc function.
- if min_algor == 'back_calc':
- # The data.
- relax_data = [0.0]
- relax_error = [0.000001]
- equations = [spin.equation]
- param_types = [spin.params]
- r = [spin.r]
- csa = [spin.csa]
- num_frq = [1]
- frq = [[min_options[3]]]
- num_ri = [1]
- remap_table = [[0]]
- noe_r1_table = [[None]]
- ri_labels = [[min_options[1]]]
- if param_set != 'local_tm' and cdp.diff_tensor.type !=
'sphere':
- xh_unit_vectors = [spin.xh_vect]
- else:
- xh_unit_vectors = [None]
-
- # Count the number of model-free parameters for the spin
index.
- num_params = [len(spin.params)]
-
- # Loop over the number of data sets.
- for j in xrange(num_data_sets):
- # Set the spin index and get the spin, if not already set.
- if param_set == 'diff' or param_set == 'all':
- spin_index = j
- spin = return_spin_from_index(global_index=spin_index)
-
- # Skip deselected spins.
- if not spin.select:
- continue
-
- # Skip spins where there is no data or errors.
- if not hasattr(spin, 'relax_data') or not hasattr(spin,
'relax_error'):
- continue
-
- # Make sure that the errors are strictly positive numbers.
- for k in xrange(len(spin.relax_error)):
- if spin.relax_error[k] == 0.0:
- raise RelaxError, "Zero error for spin '" +
`spin.num` + " " + spin.name + "', minimisation not possible."
- elif spin.relax_error[k] < 0.0:
- raise RelaxError, "Negative error for spin '" +
`spin.num` + " " + spin.name + "', minimisation not possible."
-
- # Repackage the data.
- if sim_index == None:
- relax_data.append(spin.relax_data)
- else:
- relax_data.append(spin.relax_sim_data[sim_index])
- relax_error.append(spin.relax_error)
- equations.append(spin.equation)
- param_types.append(spin.params)
- num_frq.append(spin.num_frq)
- frq.append(spin.frq)
- num_ri.append(spin.num_ri)
- remap_table.append(spin.remap_table)
- noe_r1_table.append(spin.noe_r1_table)
- ri_labels.append(spin.ri_labels)
- if sim_index == None or param_set == 'diff':
- r.append(spin.r)
- csa.append(spin.csa)
- else:
- r.append(spin.r_sim[sim_index])
- csa.append(spin.csa_sim[sim_index])
-
- # Model-free parameter values.
- if param_set == 'local_tm':
- pass
-
- # Vectors.
- if param_set != 'local_tm' and cdp.diff_tensor.type !=
'sphere':
- xh_unit_vectors.append(spin.xh_vect)
- else:
- xh_unit_vectors.append(None)
-
- # Count the number of model-free parameters for the spin
index.
- num_params.append(len(spin.params))
-
- # Repackage the parameter values for minimising just the
diffusion tensor parameters.
- if param_set == 'diff':
-
param_values.append(self.assemble_param_vector(param_set='mf'))
-
- # Convert to numpy arrays.
- for k in xrange(len(relax_data)):
- relax_data[k] = array(relax_data[k], float64)
- relax_error[k] = array(relax_error[k], float64)
-
- # Diffusion tensor type.
- if param_set == 'local_tm':
- diff_type = 'sphere'
- else:
- diff_type = cdp.diff_tensor.type
-
- # Package the diffusion tensor parameters.
- diff_params = None
- if param_set == 'mf':
- # Spherical diffusion.
- if diff_type == 'sphere':
- diff_params = [cdp.diff_tensor.tm]
-
- # Spheroidal diffusion.
- elif diff_type == 'spheroid':
- diff_params = [cdp.diff_tensor.tm, cdp.diff_tensor.Da,
cdp.diff_tensor.theta, cdp.diff_tensor.phi]
-
- # Ellipsoidal diffusion.
- elif diff_type == 'ellipsoid':
- diff_params = [cdp.diff_tensor.tm, cdp.diff_tensor.Da,
cdp.diff_tensor.Dr, cdp.diff_tensor.alpha, cdp.diff_tensor.beta,
cdp.diff_tensor.gamma]
- elif min_algor == 'back_calc' and param_set == 'local_tm':
- # Spherical diffusion.
- diff_params = [spin.local_tm]
-
-
# Initialise the function to minimise.
######################################
@@ -1163,6 +1029,153 @@
cdp.warning = warning
+ def minimise_data_setup():
+ """Set up all the data required for minimisation.
+
+ @return: An insane tuple. The full tuple is (relax_data,
relax_error, equations,
+ param_types, param_values, r, csa, num_frq, frq,
num_ri, remap_table,
+ noe_r1_table, ri_labels, num_params,
xh_unit_vectors, diff_type,
+ diff_params)
+ @rtype: tuple
+ """
+
+ # Initialise the data structures for the model-free function.
+ relax_data = []
+ relax_error = []
+ equations = []
+ param_types = []
+ param_values = None
+ r = []
+ csa = []
+ num_frq = []
+ frq = []
+ num_ri = []
+ remap_table = []
+ noe_r1_table = []
+ ri_labels = []
+ num_params = []
+ xh_unit_vectors = []
+ if param_set == 'local_tm':
+ mf_params = []
+ elif param_set == 'diff':
+ param_values = []
+
+ # Set up the data for the back_calc function.
+ if min_algor == 'back_calc':
+ # The data.
+ relax_data = [0.0]
+ relax_error = [0.000001]
+ equations = [spin.equation]
+ param_types = [spin.params]
+ r = [spin.r]
+ csa = [spin.csa]
+ num_frq = [1]
+ frq = [[min_options[3]]]
+ num_ri = [1]
+ remap_table = [[0]]
+ noe_r1_table = [[None]]
+ ri_labels = [[min_options[1]]]
+ if param_set != 'local_tm' and cdp.diff_tensor.type != 'sphere':
+ xh_unit_vectors = [spin.xh_vect]
+ else:
+ xh_unit_vectors = [None]
+
+ # Count the number of model-free parameters for the spin index.
+ num_params = [len(spin.params)]
+
+ # Loop over the number of data sets.
+ for j in xrange(num_data_sets):
+ # Set the spin index and get the spin, if not already set.
+ if param_set == 'diff' or param_set == 'all':
+ spin_index = j
+ spin = return_spin_from_index(global_index=spin_index)
+
+ # Skip deselected spins.
+ if not spin.select:
+ continue
+
+ # Skip spins where there is no data or errors.
+ if not hasattr(spin, 'relax_data') or not hasattr(spin,
'relax_error'):
+ continue
+
+ # Make sure that the errors are strictly positive numbers.
+ for k in xrange(len(spin.relax_error)):
+ if spin.relax_error[k] == 0.0:
+ raise RelaxError, "Zero error for spin '" + `spin.num` +
" " + spin.name + "', minimisation not possible."
+ elif spin.relax_error[k] < 0.0:
+ raise RelaxError, "Negative error for spin '" +
`spin.num` + " " + spin.name + "', minimisation not possible."
+
+ # Repackage the data.
+ if sim_index == None:
+ relax_data.append(spin.relax_data)
+ else:
+ relax_data.append(spin.relax_sim_data[sim_index])
+ relax_error.append(spin.relax_error)
+ equations.append(spin.equation)
+ param_types.append(spin.params)
+ num_frq.append(spin.num_frq)
+ frq.append(spin.frq)
+ num_ri.append(spin.num_ri)
+ remap_table.append(spin.remap_table)
+ noe_r1_table.append(spin.noe_r1_table)
+ ri_labels.append(spin.ri_labels)
+ if sim_index == None or param_set == 'diff':
+ r.append(spin.r)
+ csa.append(spin.csa)
+ else:
+ r.append(spin.r_sim[sim_index])
+ csa.append(spin.csa_sim[sim_index])
+
+ # Model-free parameter values.
+ if param_set == 'local_tm':
+ pass
+
+ # Vectors.
+ if param_set != 'local_tm' and cdp.diff_tensor.type != 'sphere':
+ xh_unit_vectors.append(spin.xh_vect)
+ else:
+ xh_unit_vectors.append(None)
+
+ # Count the number of model-free parameters for the spin index.
+ num_params.append(len(spin.params))
+
+ # Repackage the parameter values for minimising just the
diffusion tensor parameters.
+ if param_set == 'diff':
+
param_values.append(self.assemble_param_vector(param_set='mf'))
+
+ # Convert to numpy arrays.
+ for k in xrange(len(relax_data)):
+ relax_data[k] = array(relax_data[k], float64)
+ relax_error[k] = array(relax_error[k], float64)
+
+ # Diffusion tensor type.
+ if param_set == 'local_tm':
+ diff_type = 'sphere'
+ else:
+ diff_type = cdp.diff_tensor.type
+
+ # Package the diffusion tensor parameters.
+ diff_params = None
+ if param_set == 'mf':
+ # Spherical diffusion.
+ if diff_type == 'sphere':
+ diff_params = [cdp.diff_tensor.tm]
+
+ # Spheroidal diffusion.
+ elif diff_type == 'spheroid':
+ diff_params = [cdp.diff_tensor.tm, cdp.diff_tensor.Da,
cdp.diff_tensor.theta, cdp.diff_tensor.phi]
+
+ # Ellipsoidal diffusion.
+ elif diff_type == 'ellipsoid':
+ diff_params = [cdp.diff_tensor.tm, cdp.diff_tensor.Da,
cdp.diff_tensor.Dr, cdp.diff_tensor.alpha, cdp.diff_tensor.beta,
cdp.diff_tensor.gamma]
+ elif min_algor == 'back_calc' and param_set == 'local_tm':
+ # Spherical diffusion.
+ diff_params = [spin.local_tm]
+
+ # Return all the data.
+ return relax_data, relax_error, equations, param_types,
param_values, r, csa, num_frq, frq, num_ri, remap_table, noe_r1_table,
ri_labels, num_params, xh_unit_vectors, diff_type, diff_params
+
+
def test_grid_size(min_options):
"""Test the size of the grid search.
r5173 - /1.3/specific_fns/model_free/mf_minimise.py