Author: bugman
Date: Thu Oct 16 00:15:01 2008
New Revision: 7732
URL: http://svn.gna.org/viewcvs/relax?rev=7732&view=rev
Log:
Merged all that could be merged from r3266.
The 2 commands used were:
svn merge -r3265:3266
svn+ssh://bugman@xxxxxxxxxxx/svn/relax/branches/multi_processor .
svn merge -r3265:3266
svn+ssh://bugman@xxxxxxxxxxx/svn/relax/branches/multi_processor/specific_fns/model_free.py
specific_fns/model_free/mf_minimise.py
The grid search code was skipped as it is in minfx
(https://gna.org/projects/minfx/).
.....
r3266 | varioustoxins | 2007-04-12 18:48:28 +0200 (Thu, 12 Apr 2007) | 2
lines
Changed paths:
M /branches/multi_processor/minimise/grid.py
M /branches/multi_processor/multi/commands.py
M /branches/multi_processor/specific_fns/model_free.py
partial integration of distributed grid code (everything broken)
.....
Modified:
branches/multi_processor_merge/multi/commands.py
branches/multi_processor_merge/specific_fns/model_free/mf_minimise.py
Modified: branches/multi_processor_merge/multi/commands.py
URL:
http://svn.gna.org/viewcvs/relax/branches/multi_processor_merge/multi/commands.py?rev=7732&r1=7731&r2=7732&view=diff
==============================================================================
--- branches/multi_processor_merge/multi/commands.py (original)
+++ branches/multi_processor_merge/multi/commands.py Thu Oct 16 00:15:01 2008
@@ -50,6 +50,8 @@
msg = processor.get_name()
result = Result_string(msg,completed)
processor.return_object(result)
+
+
#not quite a momento so a memo
class MF_memo(Memo):
@@ -63,10 +65,23 @@
self.scaling=scaling
self.scaling_matrix=scaling_matrix
+OFFSET_XK=0
+OFFSET_FK=1
+OFFSET_K=2
+OFFSET_F_COUNT=3
+OFFSET_G_COUNT=4
+OFFSET_H_COUNT=5
+OFFSET_WARNING=6
+
+OFFSET_SHORT_MIN_PARAMS=0
+OFFSET_SHORT_FK=1
+OFFSET_SHORT_K=2
+
+
class MF_result_command(Result_command):
def __init__(self,memo_id,param_vector, func, iter, fc, gc, hc,
warning,completed):
-
super(MF_result_command,self).__init__(completed=completed,memo_id=memo_id)
+ super(MF_result_command,self).__init__(completed=completed)
self.memo_id=memo_id
self.param_vector=param_vector
self.func=func
@@ -87,6 +102,12 @@
gc=self.gc,hc=self.hc, warning=self.warning,
run=memo.run, index=memo.index,
sim_index=memo.sim_index,
param_set=memo.param_set,
scaling=memo.scaling, scaling_matrix=memo.scaling_matrix)
+
+
+
+
+
+
class MF_minimise_command(Slave_command):
@@ -197,12 +218,20 @@
if match('^[Gg]rid', m_m['min_algor']):
print "Unconstrained grid search size: " +
`i_m['grid_size']` + " (constraints may decrease this size).\n"
+ def process_results(self,results,processor,completed):
+ param_vector, func, iter, fc, gc, hc, warning = results
+
+ result_string = sys.stdout.getvalue() + sys.stderr.getvalue()
+ processor.return_object(Result_string(result_string,completed=False))
+ processor.return_object(MF_result_command(self.memo_id,param_vector,
func, iter, fc, gc, hc, warning,completed=completed))
+
def run(self,processor, completed):
#FIXME: move to processor startup
save_stdout = sys.stdout
save_stderr = sys.stderr
pre_string = processor.rank_format_string() % processor.rank()
+ # add debug flag or extra channels that output immediately
sys.stdout = PrependStringIO(pre_string + ' S> ')
sys.stderr = PrependStringIO(pre_string + ' E> ')
@@ -211,14 +240,110 @@
self.do_feedback()
results = generic_minimise(func=self.mf.func, dfunc=self.mf.dfunc,
d2func=self.mf.d2func, **self.minimise_map)
- param_vector, func, iter, fc, gc, hc, warning = results
-
- result_string = sys.stdout.getvalue() + sys.stderr.getvalue()
- processor.return_object(Result_string(result_string,completed=False))
- processor.return_object(MF_result_command(self.memo_id,param_vector,
func, iter, fc, gc, hc, warning,completed=completed))
+ self.process_results(results,processor,completed)
#FIXME: move to processor startup
sys.stdout.close()
sys.stderr.close()
sys.stdout = save_stdout
sys.stderr = save_stderr
+
+class MF_grid_command(MF_minimise_command):
+ def __init__(self):
+ super(MF_grid_command,self).__init__()
+
+ def process_results(self,results,processor,completed):
+ param_vector, func, iter, fc, gc, hc, warning = results
+
+ result_string = sys.stdout.getvalue() + sys.stderr.getvalue()
+ processor.return_object(Result_string(result_string,completed=False))
+
processor.return_object(MF_grid_result_command(self.memo_id,param_vector,
func, iter, fc, gc, hc, warning,completed=completed))
+
+def MF_grid_memo(memo):
+ def __init__(self,super_grid_memo):
+ super(MF_grid_memo,self).__init__()
+ self.super_grid_memo = super_grid_memo
+
+
+ def add_results(self,results):
+ self.super_grid_memo.add_result(results)
+
+class MF_super_grid_memo(MF_memo):
+ def
__init__(self,model_free,index,sim_index,run,param_set,scaling,scaling_matrix):
+
super(MF_super_grid_memo,self).__init__(model_free,index,sim_index,run,param_set,scaling,scaling_matrix)
+ self.sub_memos = []
+ self.completed = False
+
+ # aggregated results
+ # min_params, f_min, k
+ short_result=[None, None, 0]
+ self.xk = None
+ self.fk = None
+ self.k = 0
+ self.f_count = 0
+ self.g_count = 0
+ self.h_count = 0
+ self.warning = []
+
+
+
+
+ def add_sub_memo(self):
+ self.sub_memos.append(memo)
+
+ def add_result(self,sub_memo,results,full_output):
+ if 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]
+ self.warning.append(results[WARNING_OFFSET])
+
+ else:
+ if results[OFFSET_SHORT_FK] < 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]
+ self.short_result[OFFSET_SHORT_K] += results[OFFSET_SHORT_K]
+ self.sub_memos.remove(sub_memo)
+
+ if len(self.sub_memos) < 1:
+ self.completed = True
+
+class MF_grid_result_command(Result_command):
+ def __init__(self,memo_id,param_vector, func, iter, fc, gc, hc,
warning,completed):
+ super(MF_grid_result_command,self).__init__(completed=completed)
+ self.memo_id=memo_id
+ self.param_vector=param_vector
+ self.func=func
+ self.iter=iter
+ self.fc=fc
+ self.gc=gc
+ self.hc=hc
+ self.warning=warning
+
+ def run(self,relax,processor,memo):
+
+ # FIXME: Check against full result
+ # FIXME: names not consistent in memo
+ # FIXME too much repacking
+ results =
(self.param_vector,self.func,self.iter,self.fc,self.gc,self.hc, self.warning)
+ memo.add_result(results,full_result=True)
+
+ sgm = memo.super_grid_memo
+ if sgm.completed:
+
+
+
+ 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
+ #raise Exception()
+
m_f.disassemble_result(param_vector=sgm.xk,func=sgm.fk,iter=sgm.k,fc=sgm.fc,
+ gc=sgm.gc,hc=sgm.hc, warning=sgm.warning,
+ run=memo.run, index=memo.index,
sim_index=memo.sim_index,
+ param_set=memo.param_set,
scaling=memo.scaling, scaling_matrix=memo.scaling_matrix)
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=7732&r1=7731&r2=7732&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
Oct 16 00:15:01 2008
@@ -33,7 +33,7 @@
from generic_fns.mol_res_spin import count_spins, exists_mol_res_spin_data,
return_spin_from_index, spin_loop
from maths_fns.mf import Mf
from minfx.generic import generic_minimise
-from multi.commands import MF_minimise_command,MF_memo
+from multi.commands import MF_grid_command,MF_super_grid_memo,MF_grid_memo
from physical_constants import h_bar, mu0, return_gyromagnetic_ratio
from relax_errors import RelaxError, RelaxInfError, RelaxLenError,
RelaxNaNError, RelaxNoModelError, RelaxNoPdbError, RelaxNoResError,
RelaxNoSequenceError, RelaxNoTensorError, RelaxNoValueError,
RelaxNoVectorsError, RelaxNucleusError, RelaxProtonTypeError,
RelaxSpinTypeError
@@ -940,8 +940,6 @@
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)
- 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)
#test.assert_mf_equivalent(self.mf)
##self.mf=test.mf
# Setup the minimisation algorithm when constraints are present.
@@ -983,14 +981,37 @@
# Minimisation.
###############
#FIXME??? strange contraints
- 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=1,
print_flag=verbosity)
- else:
- 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=verbosity)
-
- memo =
MF_memo(model_free=self,index=index,sim_index=sim_index,run=self.run,param_set=self.param_set,scaling=scaling,
scaling_matrix=scaling_matrix)
-
- self.relax.processor.add_to_queue(command,memo)
+ if match('^[Gg]rid', min_algor):
+ processors = self.relax.processor.processor_size()
+ full_grid_info = Grid_info(min_options)
+ sub_grid_list =
full_grid_info.sub_divide(self.relax.processor.processor_size())
+ super_grid_memo =
MF_super_grid_memo(model_free=self,index=index,sim_index=sim_index,run=self.run,param_set=self.param_set,
+
scaling=scaling,scaling_matrix=self.scaling_matrix)
+
+ for sub_grid_index,sub_grid_info in enumerate(sub_grid_list):
+
+ 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)
+ 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=1,
print_flag=verbosity)
+ else:
+ 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=verbosity)
+
+
+ memo = MF_grid_memo(super_grid_memo)
+ self.relax.processor.add_to_queue(command,memo)
+
+ else:
+ 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)
+ 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=1,
print_flag=verbosity)
+ else:
+ 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=verbosity)
+
+ memo =
MF_memo(model_free=self,index=index,sim_index=sim_index,run=self.run,param_set=self.param_set,scaling=scaling,
scaling_matrix=scaling_matrix)
+
+ self.relax.processor.add_to_queue(command,memo)
#raise Exception('test')
#self.relax.processor.run_queue()
r7732 - in /branches/multi_processor_merge: multi/commands.py specific_fns/model_free/mf_minimise.py