Author: varioustoxins
Date: Tue Mar 27 17:04:02 2007
New Revision: 3242
URL: http://svn.gna.org/viewcvs/relax?rev=3242&view=rev
Log:
changes to add minimise command processing for multiprocessing
Modified:
branches/multi_processor/specific_fns/model_free.py
Modified: branches/multi_processor/specific_fns/model_free.py
URL:
http://svn.gna.org/viewcvs/relax/branches/multi_processor/specific_fns/model_free.py?rev=3242&r1=3241&r2=3242&view=diff
==============================================================================
--- branches/multi_processor/specific_fns/model_free.py (original)
+++ branches/multi_processor/specific_fns/model_free.py Tue Mar 27 17:04:02
2007
@@ -28,11 +28,14 @@
from re import match, search
from string import replace, split
import sys
+import cStringIO #FIXME: temporary for pickle tests
+import marshal #FIXME: temporary for pickle tests
from base_class import Common_functions
from maths_fns.mf import Mf
from minimise.generic import generic_minimise
-from float import isNaN,isInf
+from float import isNaN,isInf
+from multi.mpi4py_processor import MF_minimise_command
class Model_free(Common_functions):
@@ -2325,12 +2328,84 @@
- # Initialise the function to minimise.
- ######################################
-
- self.mf = Mf(init_params=self.param_vector,
param_set=self.param_set, diff_type=diff_type, diff_params=diff_params,
scaling_matrix=self.scaling_matrix, num_res=num_res, 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=self.relax.data.gx, gh=self.relax.data.gh,
g_ratio=self.relax.data.g_ratio, h_bar=self.relax.data.h_bar,
mu0=self.relax.data.mu0, num_params=num_params, vectors=xh_unit_vectors)
-
-
+# # Initialise the function to minimise.
+# ######################################
+# print 'initialise Mf'
+# print 'init_params',self.param_vector
+# print 'param_se',self.param_set
+# print 'diff_type',diff_type
+# print 'diff_params',diff_params
+# print 'scaling_matrix',self.scaling_matrix
+# print 'num_res',num_res
+# print 'equations',equations
+# print 'param_types',param_types
+# print 'param_values',param_values
+# print 'relax_data',relax_data
+# print 'errors',relax_error
+# print 'bond_length',r
+# print 'csa=',csa
+# print 'num_frq',num_frq
+# print 'frq',frq
+# print 'num_ri',num_ri
+# print 'remap_table',remap_table
+# print 'noe_r1_table',noe_r1_table
+# print 'ri_labels',ri_labels
+# print 'gx',self.relax.data.gx
+# print 'gh',self.relax.data.gh
+# print 'g_ratio',self.relax.data.g_ratio
+# print 'h_bar',self.relax.data.h_bar
+# print 'mu0',self.relax.data.mu0
+# print 'num_params',num_params
+# print 'vectors',xh_unit_vectors
+#
+# data_list = [ 'initialise Mf',
+# 'init_params',self.param_vector,
+# 'param_set',self.param_set,
+# 'diff_type',diff_type,
+# 'diff_params',diff_params,
+# 'scaling_matrix',self.scaling_matrix,
+# 'num_res',num_res,
+# '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',self.relax.data.gx,
+# 'gh',self.relax.data.gh,\
+# 'g_ratio',self.relax.data.g_ratio,
+# 'h_bar',self.relax.data.h_bar,
+# 'mu0',self.relax.data.mu0,
+# 'num_params',num_params,
+# 'vectors',xh_unit_vectors]
+# for elem in data_list:
+# marshal.loads(marshal.dumps(elem))
+# self.mf = Mf(init_params=self.param_vector,
param_set=self.param_set, diff_type=diff_type,
+# diff_params=diff_params,
scaling_matrix=self.scaling_matrix, num_res=num_res,
+# 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=self.relax.data.gx,
gh=self.relax.data.gh,
+# g_ratio=self.relax.data.g_ratio,
h_bar=self.relax.data.h_bar,
+# mu0=self.relax.data.mu0, num_params=num_params,
vectors=xh_unit_vectors)
+ command=MF_minimise_command()
+ command.set_mf(init_params=self.param_vector,
param_set=self.param_set, diff_type=diff_type,
+ diff_params=diff_params,
scaling_matrix=self.scaling_matrix, num_res=num_res,
+ 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=self.relax.data.gx,
gh=self.relax.data.gh,
+ g_ratio=self.relax.data.g_ratio,
h_bar=self.relax.data.h_bar,
+ mu0=self.relax.data.mu0, num_params=num_params,
vectors=xh_unit_vectors)
+ #test.assert_mf_equivalent(self.mf)
+ ##self.mf=test.mf
# Setup the minimisation algorithm when constraints are present.
################################################################
@@ -2362,20 +2437,32 @@
# Back-calculation.
###################
+ #FIXME could be neater?
if min_algor == 'back_calc':
- return self.mf.calc_ri()
+ return command.build_mf().calc_ri()
# Minimisation.
###############
-
+ #FIXME remove old version
+# if constraints:
+# results = generic_minimise(func=self.mf.func,
dfunc=self.mf.dfunc, d2func=self.mf.d2func, args=(), x0=self.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=1,
print_flag=print_flag)
+# else:
+# results = generic_minimise(func=self.mf.func,
dfunc=self.mf.dfunc, d2func=self.mf.d2func, args=(), x0=self.param_vector,
min_algor=min_algor, min_options=min_options, func_tol=func_tol,
grad_tol=grad_tol, maxiter=max_iterations, full_output=1,
print_flag=print_flag)
+# if results == None:
+# return
+ #FIXME??? strange contraints
if constraints:
- results = generic_minimise(func=self.mf.func,
dfunc=self.mf.dfunc, d2func=self.mf.d2func, args=(), x0=self.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=1,
print_flag=print_flag)
+ command.set_minimise(args=(), x0=self.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=1,
+ print_flag=print_flag)
else:
- results = generic_minimise(func=self.mf.func,
dfunc=self.mf.dfunc, d2func=self.mf.d2func, args=(), x0=self.param_vector,
min_algor=min_algor, min_options=min_options, func_tol=func_tol,
grad_tol=grad_tol, maxiter=max_iterations, full_output=1,
print_flag=print_flag)
- if results == None:
- return
- self.param_vector, self.func, iter, fc, gc, hc, self.warning =
results
+ command.set_minimise(args=(), x0=self.param_vector,
min_algor=min_algor, min_options=min_options,
+ func_tol=func_tol, grad_tol=grad_tol,
maxiter=max_iterations, full_output=1,
+ print_flag=print_flag)
+ command.run(None)
+
+ self.param_vector, self.func, iter, fc, gc, hc, self.warning =
command.results
self.iter_count = self.iter_count + iter
self.f_count = self.f_count + fc
self.g_count = self.g_count + gc
r3242 - /branches/multi_processor/specific_fns/model_free.py