def parallelRun(self):
'''
Runs Sampler in parallel and collects solns
Input: none
Output: none
'''
self.outq=sque() #to dump (nRun,soln) in
ps=[]
wantprocs = self.input_file('Problem/numprocs',1)
self.numprocs = min(wantprocs,multiprocessing.cpu_count())
trackThousand = 0
trials = int(self.sampler.totalSamples)
print '\nRunning %1.0e samples in parallel...' %trials
ps=[]
self.numPs=0
self.done=False
self.histories={}
self.histories['varNames']=self.varDict.keys()
self.histories['vars']=self.varDict.values()
self.histories['varPaths']=[]
for var in self.varDict.values():
#need to preset these so they can be filled with nRun?
self.histories['varPaths'].append(var.path)
self.histories['varVals']=[]
print ' ...uncertain variables:',self.histories['varNames'],'...'
if not self.restart:
self.total_runs = -1
trialsLeft = trials
trialsAtRestart = 0
#tempOutFile = file('solns.out','w')
else: #start from restart
print '\nStarting from restart...'
print ' Starting after run',self.total_runs
trialsAtRestart = self.total_runs
trialsLeft = trials - self.total_runs
print ' ...using',self.numprocs,'processors...'
printFreq = self.input_file('Sampler/MC/printfreq',1000)
print ' ...print frequency is',printFreq,'...'
trialsPerProc = int(trials/float(self.numprocs))
trialsPerProc = min(trialsPerProc,int(ceil(printFreq/4)))
if trialsPerProc > 1000:
trialsPerProc = 1000
mesh_size = self.input_file('Problem/mesh_factor',1)
self.done=False
runDict={}
starttime=time.time()
rcvProc=0
lastPrint=0
doAPrint = False
thrown=0
print '\nFinished Run | Time Elapsed | Est. Remaining',
print '| Number Discarded Solutions'
while not self.done:
#remove dead processses
for p,proc in enumerate(ps):
if not proc.is_alive():
proc.join()
del ps[p]
rcvProc+=1
while not self.outq.empty():
slns,newthrown = list(self.outq.get())
thrown+=newthrown
lastPrint+=len(slns)
if lastPrint >= printFreq:
self.backends['PDF'].addToBins(slns,True)
doAPrint=True
lastPrint=0
else:
self.backends['PDF'].addToBins(slns)
self.savestate(self.backends['PDF'].savedict())
if rcvProc==self.numprocs:
rcvProc=0
if doAPrint:
doAPrint = False
lastPrint=0
#print progress
#FIXME fix for restart case
finished = trials-trialsLeft
totDone = finished + trialsAtRestart
if self.restart:
finished -= trialsAtRestart
elapTime = time.time()-starttime
dpdt = float(finished)/float(elapTime)
toGo = dt.timedelta(seconds=(int(trialsLeft/dpdt)))
elapTime = dt.timedelta(seconds=int(elapTime))
print '%12i | %12s | %12s | %9i' %(totDone,elapTime,toGo,thrown),
print ' \r',
if trialsLeft > 0:
while len(ps)<self.numprocs and not self.done:
if trialsLeft > trialsPerProc: newtrials = trialsPerProc
else: newtrials = trialsLeft
trialsLeft -= newtrials
self.numPs+=1
runDict['fileChange']={}
runDict['fileChange']['Mesh/nx_per_reg']=mesh_size
runDict['fileChange']['Mesh/ny_per_reg']=mesh_size
ps.append(multiprocessing.Process(\
target = self.runSample,\
args=(trackThousand,newtrials,runDict)\
))
ps[-1].start()
trackThousand+=1
self.done = self.outq.empty() and len(ps)==0
print '\n'
def __init__(self,ords,case):
self.expOrds = ords
self.case = case
self.coeffs={}
self.outq=sque()
def parallelRun(self):
'''
Runs Sampler in parallel and collects solns
Input: none
Output: none
'''
self.outq=sque() #to dump (nRun,soln) in
ps=[]
wantprocs = self.input_file('Problem/numprocs',1)
self.numprocs = min(wantprocs,multiprocessing.cpu_count())
if not self.restart:
print '\nRunning samples in parallel...'
self.total_runs = -1
ps=[]
self.done=False
self.histories={}
self.histories['varNames']=self.varDict.keys()
self.histories['vars']=self.varDict.values()
self.histories['varPaths']=[]
for var in self.varDict.values():
#need to preset these so they can be filled with nRun?
self.histories['varPaths'].append(var.path)
self.histories['varVals']=[]
self.histories['nRun']=[]
self.histories['soln']=[]
print ' ...uncertain variables:',self.histories['varNames']
tempOutFile = file('solns.out','w')
else: #start from restart
print '\nStarting from restart...'
print ' Starting after run',self.total_runs
trialsAtRestart = self.total_runs
print ' ...using',self.numprocs,'processors...'
self.numPs=0
finished=0
while not self.done:
#remove dead processses
for p,proc in enumerate(ps):
if not proc.is_alive():
proc.join()
while not self.outq.empty():
n,sln = self.outq.get()
self.histories['soln'][n]=sln
finished+=1
print 'Runs finished:',finished,
del ps[p]
#save state
if not self.sampler.converged:
while len(ps)<self.numprocs and not self.sampler.converged:
self.numPs+=1
self.total_runs+=1
#TODO print single line, started/finished runs
print 'Runs started:',self.total_runs,'\r',
try:
tot1 = self.backends['PDF'].tot1
tot2 = self.backends['PDF'].tot2
N = self.backends['PDF'].N
runDict = self.sampler.giveSample([N,tot1,tot2])
except KeyError:
runDict = self.sampler.giveSample()
self.histories['nRun'].append(self.total_runs)
self.histories['soln'].append(0) #placeholder
#print self.sampler.type
for key in runDict.keys():
try: self.histories[key].append(runDict[key])
except KeyError:
self.histories[key]=[runDict[key]]
# print ' ',key,self.histories[key][-1]
#add flux output identifier to change dict
#TODO this expects the same output block for everything!
runDict['fileChange']={}
outFileName='run.out'+str(self.total_runs)
runDict['fileChange']['Output/file']=outFileName
mesh_size = self.input_file('Problem/mesh_factor',1)
runDict['fileChange']['Mesh/nx_per_reg']=mesh_size
runDict['fileChange']['Mesh/ny_per_reg']=mesh_size
inp_file = self.ie.writeInput(self.templateFile,
self.inputDir,
self.histories['varPaths'],
runDict['varVals'],
runDict['fileChange'],
self.total_runs)
ps.append(multiprocessing.Process(\
target = self.runSample,\
args=(self.total_runs,inp_file,outFileName))\
)
ps[-1].start()
self.done = (len(ps)==0) and self.sampler.converged
def parallelRun(self):
'''
Runs Sampler in parallel and collects solns
Input: none
Output: none
'''
self.outq=sque() #to dump (nRun,soln) in
ps=[]
wantprocs = self.input_file('Problem/numprocs',1)
self.numprocs = min(wantprocs,multiprocessing.cpu_count())
trackThousand = 0
trials = int(self.sampler.totalSamples)
print '\nRunning %1.0e samples in parallel...' %trials
ps=[]
self.numPs=0
self.done=False
self.histories={}
self.histories['varNames']=self.varDict.keys()
self.histories['vars']=self.varDict.values()
self.histories['varPaths']=[]
for var in self.varDict.values():
#need to preset these so they can be filled with nRun?
self.histories['varPaths'].append(var.path)
self.histories['varVals']=[]
print ' ...uncertain variables:',self.histories['varNames'],'...'
if not self.restart:
self.total_runs = -1
trialsLeft = trials
trialsAtRestart = 0
#tempOutFile = file('solns.out','w')
else: #start from restart
print '\nStarting from restart...'
print ' Starting after run',self.total_runs
trialsAtRestart = self.total_runs
trialsLeft = trials - self.total_runs
print ' ...using',self.numprocs,'processors...'
printFreq = self.input_file('Sampler/MC/printfreq',1000)
print ' ...print frequency is',printFreq,'...'
trialsPerProc = int(trials/float(self.numprocs))
trialsPerProc = min(trialsPerProc,int(ceil(printFreq/4)))
if trialsPerProc > 1000:
trialsPerProc = 1000
mesh_size = self.input_file('Problem/mesh_factor',1)
self.done=False
runDict={}
starttime=time.time()
rcvProc=0
lastPrint=0
doAPrint = False
thrown=0
print '\nFinished Run | Time Elapsed | Est. Remaining',
print '| Number Discarded Solutions'
while not self.done:
#remove dead processses
for p,proc in enumerate(ps):
if not proc.is_alive():
proc.join()
del ps[p]
rcvProc+=1
while not self.outq.empty():
slns,newthrown = list(self.outq.get())
thrown+=newthrown
lastPrint+=len(slns)
if lastPrint >= printFreq:
self.backends['PDF'].addToBins(slns,True)
doAPrint=True
lastPrint=0
else:
self.backends['PDF'].addToBins(slns)
self.savestate(self.backends['PDF'].savedict())
if rcvProc==self.numprocs:
rcvProc=0
if doAPrint:
doAPrint = False
lastPrint=0
#print progress
#FIXME fix for restart case
finished = trials-trialsLeft
totDone = finished + trialsAtRestart
if self.restart:
finished -= trialsAtRestart
elapTime = time.time()-starttime
dpdt = float(finished)/float(elapTime)
toGo = dt.timedelta(seconds=(int(trialsLeft/dpdt)))
elapTime = dt.timedelta(seconds=int(elapTime))
print '%12i | %12s | %12s | %9i' %(totDone,elapTime,toGo,thrown),
print ' \r',
if trialsLeft > 0:
while len(ps)<self.numprocs and not self.done:
if trialsLeft > trialsPerProc: newtrials = trialsPerProc
else: newtrials = trialsLeft
trialsLeft -= newtrials
self.numPs+=1
runDict['fileChange']={}
runDict['fileChange']['Mesh/nx_per_reg']=mesh_size
runDict['fileChange']['Mesh/ny_per_reg']=mesh_size
ps.append(multiprocessing.Process(\
target = self.runSample,\
args=(trackThousand,newtrials,runDict)\
))
ps[-1].start()
trackThousand+=1
self.done = self.outq.empty() and len(ps)==0
print '\n'
def parallelRun(self):
'''
Runs Sampler in parallel and collects solns
Input: none
Output: none
'''
self.outq=sque() #to dump (nRun,soln) in
ps=[]
wantprocs = self.input_file('Problem/numprocs',1)
self.numprocs = min(wantprocs,multiprocessing.cpu_count())
if not self.restart:
print '\nRunning samples in parallel...'
self.total_runs = -1
ps=[]
self.done=False
self.histories={}
self.histories['varNames']=self.varDict.keys()
self.histories['vars']=self.varDict.values()
self.histories['varPaths']=[]
for var in self.varDict.values():
#need to preset these so they can be filled with nRun?
self.histories['varPaths'].append(var.path)
self.histories['varVals']=[]
self.histories['nRun']=[]
self.histories['soln']=[]
print ' ...uncertain variables:',self.histories['varNames']
tempOutFile = file('solns.out','w')
else: #start from restart
print '\nStarting from restart...'
print ' Starting after run',self.total_runs
trialsAtRestart = self.total_runs
print ' ...using',self.numprocs,'processors...'
self.numPs=0
finished=0
while not self.done:
#remove dead processses
for p,proc in enumerate(ps):
if not proc.is_alive():
proc.join()
while not self.outq.empty():
n,sln = self.outq.get()
self.histories['soln'][n]=sln
finished+=1
print 'Runs finished:',finished,
del ps[p]
#save state
if not self.sampler.converged:
while len(ps)<self.numprocs and not self.sampler.converged:
self.numPs+=1
self.total_runs+=1
#TODO print single line, started/finished runs
print 'Runs started:',self.total_runs,'\r',
try:
tot1 = self.backends['PDF'].tot1
tot2 = self.backends['PDF'].tot2
N = self.backends['PDF'].N
runDict = self.sampler.giveSample([N,tot1,tot2])
except KeyError:
runDict = self.sampler.giveSample()
self.histories['nRun'].append(self.total_runs)
self.histories['soln'].append(0) #placeholder
#print self.sampler.type
for key in runDict.keys():
try: self.histories[key].append(runDict[key])
except KeyError:
self.histories[key]=[runDict[key]]
# print ' ',key,self.histories[key][-1]
#add flux output identifier to change dict
#TODO this expects the same output block for everything!
runDict['fileChange']={}
outFileName='run.out'+str(self.total_runs)
runDict['fileChange']['Output/file']=outFileName
mesh_size = self.input_file('Problem/mesh_factor',1)
runDict['fileChange']['Mesh/nx_per_reg']=mesh_size
runDict['fileChange']['Mesh/ny_per_reg']=mesh_size
inp_file = self.ie.writeInput(self.templateFile,
self.inputDir,
self.histories['varPaths'],
runDict['varVals'],
runDict['fileChange'],
self.total_runs)
ps.append(multiprocessing.Process(\
target = self.runSample,\
args=(self.total_runs,inp_file,outFileName))\
)
ps[-1].start()
self.done = (len(ps)==0) and self.sampler.converged
def __init__(self, ords, case):
self.expOrds = ords
self.case = case
self.coeffs = {}
self.outq = sque()
def __init__(self,ords):
self.coeffs={}
self.ords = ords
self.outq=sque()
def __init__(self, ords):
self.coeffs = {}
self.ords = ords
self.outq = sque()