Author: bugman
Date: Thu Jan 7 15:58:38 2010
New Revision: 10133
URL: http://svn.gna.org/viewcvs/relax?rev=10133&view=rev
Log:
Some clean ups of the model-free code for multi-processing.
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=10133&r1=10132&r2=10133&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 15:58:38 2010
@@ -1544,8 +1544,6 @@
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)
- #test.assert_mf_equivalent(self.mf)
- ##self.mf=test.mf
# Setup the minimisation algorithm when constraints are present.
################################################################
@@ -1577,6 +1575,12 @@
# Back-calculation.
###################
+ if min_algor == 'back_calc':
+ # Initialise the model-free class.
+ 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)
+
+ # Return the back-calculated Ri data.
+ return self.mf.calc_ri()
# Minimisation.
@@ -1587,11 +1591,7 @@
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())
@@ -1626,20 +1626,12 @@
else:
# 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)
- # 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, spin_id=spin_id,
sim_index=sim_index, full_output=True, print_flag=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, spin_id=spin_id,
sim_index=sim_index, full_output=True, print_flag=verbosity)
+ # 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)
# 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=10133&r1=10132&r2=10133&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 15:58:38 2010
@@ -33,19 +33,6 @@
from maths_fns.mf import Mf
from minfx.generic import generic_minimise
from multi.processor import Capturing_exception, Memo, Result_command,
Result_string, Slave_command
-
-
-OFFSET_XK = 0 # The array of minimised parameter values
-OFFSET_FK = 1 # The minimised function value,
-OFFSET_K = 2 # The number of iterations,
-OFFSET_F_COUNT = 3 # The number of function calls,
-OFFSET_G_COUNT = 4 # The number of gradient calls,
-OFFSET_H_COUNT = 5 # The number of Hessian calls,
-OFFSET_WARNING = 6 # The warning string.
-
-OFFSET_SHORT_MIN_PARAMS = 0
-OFFSET_SHORT_FK = 1
-OFFSET_SHORT_K = 2
class MF_grid_memo(Memo):
@@ -128,13 +115,14 @@
print(print_prefix + "Parameter values: " +
repr(sgm.short_results))
print("")
- m_f = sgm.model_free
- m_f.iter_count = 0
- m_f.f_count = 0
- m_f.g_count = 0
- m_f.h_count = 0
- #raise Exception()
- m_f.disassemble_result(param_vector=sgm.xk, func=sgm.fk,
iter=sgm.k, fc=sgm.f_count, gc=sgm.g_count, hc=sgm.h_count,
warning=sgm.warning, spin=sgm.spin, sim_index=sgm.sim_index,
model_type=sgm.model_type, scaling=sgm.scaling,
scaling_matrix=sgm.scaling_matrix)
+ # Initialise the iteration counter and function, gradient, and
Hessian call counters.
+ sgm.model_free.iter_count = 0
+ sgm.model_free.f_count = 0
+ sgm.model_free.g_count = 0
+ sgm.model_free.h_count = 0
+
+ # Disassemble the results.
+ sgm.model_free._disassemble_result(param_vector=sgm.xk,
func=sgm.fk, iter=sgm.k, fc=sgm.f_count, gc=sgm.g_count, hc=sgm.h_count,
warning=sgm.warning, spin=sgm.spin, sim_index=sgm.sim_index,
model_type=sgm.model_type, scaling=sgm.scaling,
scaling_matrix=sgm.scaling_matrix)
class MF_memo(Memo):
@@ -232,6 +220,9 @@
def run(self, processor, completed):
+ """Execute the model-free optimisation."""
+
+ # Run catching all errors.
try:
self.pre_run(processor)
self.pre_command_feed_back(processor)
@@ -239,6 +230,8 @@
self.post_command_feedback(results, processor)
self.process_results(results, processor, completed)
self.post_run(processor)
+
+ # An error occurred.
except Exception, e :
if isinstance(e, Capturing_exception):
raise e
@@ -315,12 +308,22 @@
def run(self, processor, memo):
- m_f = memo.model_free
- m_f.iter_count = 0
- m_f.f_count = 0
- m_f.g_count = 0
- m_f.h_count = 0
- m_f._disassemble_result(param_vector=self.param_vector,
func=self.func, iter=self.iter, fc=self.fc, gc=self.gc, hc=self.hc,
warning=self.warning, spin=memo.spin, sim_index=memo.sim_index,
model_type=memo.model_type, scaling=memo.scaling,
scaling_matrix=memo.scaling_matrix)
+ """Disassemble the model-free optimisation results.
+
+ @param processor: Unused!
+ @type processor: None
+ @param memo: The model-free memo.
+ @type memo: memo
+ """
+
+ # Initialise the iteration counter and function, gradient, and
Hessian call counters.
+ memo.model_free.iter_count = 0
+ memo.model_free.f_count = 0
+ memo.model_free.g_count = 0
+ memo.model_free.h_count = 0
+
+ # Disassemble the results.
+ memo.model_free._disassemble_result(param_vector=self.param_vector,
func=self.func, iter=self.iter, fc=self.fc, gc=self.gc, hc=self.hc,
warning=self.warning, spin=memo.spin, sim_index=memo.sim_index,
model_type=memo.model_type, scaling=memo.scaling,
scaling_matrix=memo.scaling_matrix)
class MF_super_grid_memo(MF_memo):
@@ -337,7 +340,6 @@
self.grid_size = grid_size
# aggregated results
# min_params, f_min, k
- short_result = [None, None, 0]
self.xk = None
self.fk = 1e300
self.k = 0
@@ -349,20 +351,29 @@
def add_result(self, sub_memo, results):
+
+ # Normal minimisation.
if self.full_output:
- if results[OFFSET_FK] < self.fk:
- self.xk = results[OFFSET_XK]
- self.fk = results[OFFSET_FK]
- self.k += results[OFFSET_K]
- self.f_count += results[OFFSET_F_COUNT]
-
- self.g_count += results[OFFSET_G_COUNT]
- self.h_count += results[OFFSET_H_COUNT]
- if results[OFFSET_WARNING] != None:
- self.warning.append(results[OFFSET_WARNING])
-
+ # Unpack the results.
+ param_vector, func, iter, fc, gc, hc, warning = results
+
+ if func < self.fk:
+ self.xk = param_vector
+ self.fk = func
+ self.k += iter
+ self.f_count += fc
+
+ self.g_count += gc
+ self.h_count += hc
+ if warning != None:
+ self.warning.append(warning)
+
+ # Grid search.
#FIXME: TESTME: do we use short results?
else:
+ # Unpack the results.
+ param_vector, func, iter, warning = results
+
if results[OFFSET_SHORT_FK] < self.short_result[OFFSET_SHORT_FK]:
self.short_result[OFFSET_SHORT_MIN_PARAMS] =
results[OFFSET_SHORT_MIN_PARAMS]
self.short_result[OFFSET_SHORT_FK] = results[OFFSET_SHORT_FK]
r10133 - in /branches/multi_processor_merge/specific_fns/model_free: mf_minimise.py multi_processor_commands.py