Author: bugman
Date: Thu Jan 7 17:59:00 2010
New Revision: 10144
URL: http://svn.gna.org/viewcvs/relax?rev=10144&view=rev
Log:
Simplification of the model-free target function class initialisation.
This has been shifted back into specific_fns/model_free/mf_minimise.py! This
does not need to be
done by the multi-processing code. Silencing can be performed later by
modifying the 'verbosity'
variable in this class.
Modified:
branches/multi_processor_merge/specific_fns/model_free/mf_minimise.py
branches/multi_processor_merge/specific_fns/model_free/multi_processor_commands.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=10144&r1=10143&r2=10144&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 Thu
Jan 7 17:59:00 2010
@@ -1542,6 +1542,12 @@
relax_data, relax_error, equations, param_types, param_values,
r, csa, num_frq, frq, num_ri, remap_table, noe_r1_table, ri_labels, gx, gh,
num_params, xh_unit_vectors, diff_type, diff_params =
self._minimise_data_setup(model_type, min_algor, num_data_sets, min_options,
spin=spin, sim_index=sim_index)
+ # Initialise the function to minimise.
+ ######################################
+
+ self.mf = 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)
+
+
# Setup the minimisation algorithm when constraints are present.
################################################################
@@ -1606,15 +1612,14 @@
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)
+ command.set_minimise(mf=self.mf,
model_type=model_type, 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)
+ command.set_minimise(mf=self.mf,
model_type=model_type, 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)
@@ -1625,11 +1630,8 @@
# Minimisation initialisation.
command = MF_minimise_command()
- # Set up the model-free data.
- 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)
-
# Set up for optimisation.
- 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, spin_id=spin_id,
sim_index=sim_index, full_output=True, print_flag=verbosity)
+ command.set_minimise(mf=self.mf, model_type=model_type,
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,
spin_id=spin_id, sim_index=sim_index, full_output=True, print_flag=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)
Modified:
branches/multi_processor_merge/specific_fns/model_free/multi_processor_commands.py
URL:
http://svn.gna.org/viewcvs/relax/branches/multi_processor_merge/specific_fns/model_free/multi_processor_commands.py?rev=10144&r1=10143&r2=10144&view=diff
==============================================================================
---
branches/multi_processor_merge/specific_fns/model_free/multi_processor_commands.py
(original)
+++
branches/multi_processor_merge/specific_fns/model_free/multi_processor_commands.py
Thu Jan 7 17:59:00 2010
@@ -163,11 +163,8 @@
# The minimisation map containing the minimisation information.
self.minimise_map = {'args':(), 'x0':None, 'min_algor':None,
'min_options':None, 'func_tol':1e-25, 'grad_tol':None, 'maxiter':1e6,
'A':None, 'b':None, 'l':None, 'u':None, 'c':None, 'dc':None, 'd2c':None,
'dc':None, 'd2c':None, 'full_output':0, 'print_flag':0, 'print_prefix':""}
- # The map containing the model-free information.
- self.mf_map = {'init_params':None, 'model_type':None,
'diff_type':None, 'diff_params':None, 'scaling_matrix':None,
'num_spins':None, 'equations':None, 'param_types':None, 'param_values':None,
'relax_data':None, 'errors':None, 'bond_length':None, 'csa':None,
'num_frq':0, 'frq':None, 'num_ri':None, 'remap_table':None,
'noe_r1_table':None, 'ri_labels':None, 'gx':0, 'gh':0, 'h_bar':0, 'mu0':0,
'num_params':None, 'vectors':None}
-
# A map containing generic information.
- self.info_map = {'spin_id':None, 'sim_index':None, 'grid_size':1}
+ self.info_map = {'mf':None, 'model_type':None, 'spin_id':None,
'sim_index':None, 'grid_size':1}
# A flag for silencing output.
self.silence = False
@@ -183,7 +180,7 @@
print('Simulation '+ repr(self.info_map['sim_index'])+ '\n')
# Individual spin print out.
- if self.mf_map['model_type'] == 'mf' or
self.mf_map['model_type'] == 'local_tm':
+ if self.model_type == 'mf' or self.model_type == 'local_tm':
if self.minimise_map['print_flag'] >= 2:
print("\n\n")
string = "Fitting to spin: " + self.info_map['spin_id']
@@ -220,9 +217,6 @@
# Initial print outs.
self.initial_printout()
- # Initialise the function to minimise.
- self.mf = Mf(**self.mf_map)
-
# Minimisation.
results = generic_minimise(func=self.mf.func,
dfunc=self.mf.dfunc, d2func=self.mf.d2func, **self.minimise_map)
@@ -237,16 +231,16 @@
raise Capturing_exception(rank=processor.rank(),
name=processor.get_name())
- #FIXME: bad names
- def set_mf(self, **kwargs):
- """Place the model-free information into the mf_map."""
-
- # Fill out the mf_map using the keyword args.
- self.mf_map.update(kwargs)
-
-
def set_minimise(self, **kwargs):
"""Place the minimisation and other information into the appropriate
maps."""
+
+ # The optimisation class.
+ self.mf = kwargs['mf']
+ del kwargs['mf']
+
+ # The model type.
+ self.model_type = kwargs['model_type']
+ del kwargs['model_type']
# Strip out and store special arguments into the info_map.
if 'spin_id' in kwargs:
r10144 - in /branches/multi_processor_merge/specific_fns/model_free: mf_minimise.py multi_processor_commands.py