r7825 - /branches/multi_processor_merge/specific_fns/model_free/mf_minimise.py -- October 19, 2008 - 17:09

Author: bugman
Date: Sun Oct 19 17:09:26 2008
New Revision: 7825

URL: http://svn.gna.org/viewcvs/relax?rev=7825&view=rev
Log:
Commented the new model-free minimisation code.


Modified:
    branches/multi_processor_merge/specific_fns/model_free/mf_minimise.py

Modified: 
branches/multi_processor_merge/specific_fns/model_free/mf_minimise.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/multi_processor_merge/specific_fns/model_free/mf_minimise.py?rev=7825&r1=7824&r2=7825&view=diff
==============================================================================
--- branches/multi_processor_merge/specific_fns/model_free/mf_minimise.py 
(original)
+++ branches/multi_processor_merge/specific_fns/model_free/mf_minimise.py Sun 
Oct 19 17:09:26 2008
@@ -1109,43 +1109,63 @@
             processor_box = Processor_box() 
             processor = processor_box.processor
 
+            # Parallelised grid search for the diffusion parameter space.
             #FIXME??? strange contraints
             if match('^[Gg]rid', min_algor) and model_type == 'diff' :
+                # Determine the number of processors.
                 processors = processor.processor_size()
+
+                # Split up the grid into chunks for each processor.
                 full_grid_info = Grid_info(min_options)
                 sub_grid_list = 
full_grid_info.sub_divide(processor.processor_size())
+
+                # Set up the constrained super grid memo.
                 if constraints:
                     super_grid_memo = MF_super_grid_memo(model_free=self, 
index=index, sim_index=sim_index, model_type=model_type, scaling=scaling, 
scaling_matrix=scaling_matrix, full_output=True, verbosity=verbosity, 
print_prefix="", grid_size=self.grid_size, A=A, b=b)
+
+                # Set up the unconstrained super grid memo.
                 else:
                     super_grid_memo = MF_super_grid_memo(model_free=self, 
index=index, sim_index=sim_index, model_type=model_type, scaling=scaling, 
scaling_matrix=scaling_matrix, full_output=True, verbosity=verbosity, 
print_prefix="", grid_size=self.grid_size)
 
+                # Loop over each grid sub-division.
                 for sub_grid_index, sub_grid_info in 
enumerate(sub_grid_list):
+                    # Grid search initialisation.
                     command = MF_grid_command()
                     command.set_mf(init_params=param_vector, 
model_type=model_type, diff_type=diff_type, diff_params=diff_params, 
scaling_matrix=scaling_matrix, num_spins=num_spins, equations=equations, 
param_types=param_types, param_values=param_values, relax_data=relax_data, 
errors=relax_error, bond_length=r, csa=csa, num_frq=num_frq, frq=frq, 
num_ri=num_ri, remap_table=remap_table, noe_r1_table=noe_r1_table, 
ri_labels=ri_labels, gx=gx, gh=gh, h_bar=h_bar, mu0=mu0, 
num_params=num_params, vectors=xh_unit_vectors)
+
+                    # Constrained optimisation.
                     if constraints:
                         command.set_minimise(args=(), x0=param_vector, 
min_algor=min_algor, min_options=min_options, func_tol=func_tol, 
grad_tol=grad_tol, maxiter=max_iterations, A=A, b=b, full_output=True, 
verbosity=verbosity)
+
+                    # Unconstrained optimisation.
                     else:
                         command.set_minimise(args=(), x0=param_vector, 
min_algor=min_algor, min_options=min_options, func_tol=func_tol, 
grad_tol=grad_tol, maxiter=max_iterations, full_output=True, 
verbosity=verbosity)
 
-
+                    # Set up the model-free memo and add it to the processor 
queue.
                     memo = MF_grid_memo(super_grid_memo)
                     processor.add_to_queue(command, memo)
 
-            else:
+            # Minimisation of all other model types.
+            else:
+                # Minimisation initialisation.
                 command = MF_minimise_command()
                 command.set_mf(init_params=param_vector, 
model_type=model_type, diff_type=diff_type, diff_params=diff_params, 
scaling_matrix=scaling_matrix, num_spins=num_spins, equations=equations, 
param_types=param_types, param_values=param_values, relax_data=relax_data, 
errors=relax_error, bond_length=r, csa=csa, num_frq=num_frq, frq=frq, 
num_ri=num_ri, remap_table=remap_table, noe_r1_table=noe_r1_table, 
ri_labels=ri_labels, gx=gx, gh=gh, h_bar=h_bar, mu0=mu0, 
num_params=num_params, vectors=xh_unit_vectors)
 
+                # Back calculation.
                 #FIXME could be neater?
                 if min_algor == 'back_calc':
                     return command.build_mf().calc_ri()
 
+                # Constrained optimisation.
                 if constraints:
                     command.set_minimise(args=(), x0=param_vector, 
min_algor=min_algor, min_options=min_options, func_tol=func_tol, 
grad_tol=grad_tol, maxiter=max_iterations, A=A, b=b, full_output=True, 
verbosity=verbosity)
+
+                # Unconstrained optimisation.
                 else:
                     command.set_minimise(args=(), x0=param_vector, 
min_algor=min_algor, min_options=min_options, func_tol=func_tol, 
grad_tol=grad_tol, maxiter=max_iterations, full_output=True, 
verbosity=verbosity)
 
+                # Set up the model-free memo and add it to the processor 
queue.
                 memo = MF_memo(model_free=self, spin=spin, 
sim_index=sim_index, model_type=model_type, scaling=scaling, 
scaling_matrix=scaling_matrix)
-
                 processor.add_to_queue(command, memo)