DAMASK_EICMD/processing/pre/seeds_fromDistribution.py

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#!/usr/bin/python
# -*- coding: UTF-8 no BOM -*-
import threading,time,os,subprocess,shlex,string,sys,random
import numpy as np
from optparse import OptionParser
from operator import mul
from cStringIO import StringIO
import damask
scriptID = string.replace('$Id$','\n','\\n')
scriptName = os.path.splitext(scriptID.split()[1])[0]
mismatch = None
currentSeedsName = None
def execute(cmd,streamIn=None,dir='./'):
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'''
executes a command in given directory and returns stdout and stderr for optional stdin
'''
initialPath=os.getcwd()
os.chdir(dir)
process = subprocess.Popen(shlex.split(cmd),stdout=subprocess.PIPE,stderr = subprocess.PIPE,stdin=subprocess.PIPE)
if streamIn != None:
out,error = process.communicate(streamIn.read())
else:
out,error = process.communicate()
os.chdir(initialPath)
return out,error
#---------------------------------------------------------------------------------------------------
class myThread (threading.Thread):
#---------------------------------------------------------------------------------------------------
'''
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perturbes seed in seed file, performes Voronoi tessellation, evaluates, and updates best match
'''
def __init__(self, threadID):
threading.Thread.__init__(self)
self.threadID = threadID
def run(self):
global bestSeedsUpdate
global bestSeedsVFile
global nMicrostructures
global delta
global points
global target
global match
global baseFile
s.acquire()
bestMatch = match
s.release()
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random.seed(options.randomSeed+self.threadID) # initializes to given seeds
knownSeedsUpdate = bestSeedsUpdate -1.0 # trigger update of local best seeds (time when the best seed file was found known to thread)
randReset = True # aquire new direction
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myBestSeedsVFile = StringIO() # in-memory file to store local copy of best seeds file
perturbedSeedsVFile = StringIO() # in-memory file for perturbed best seeds file
perturbedGeomVFile = StringIO() # in-memory file for tessellated geom file
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#--- still not matching desired bin class ----------------------------------------------------------
while bestMatch < options.threshold:
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s.acquire() # accessing global data, ensure only one thread does it per time
if bestSeedsUpdate > knownSeedsUpdate: # if a newer best seed file exist, read it into a virtual file
knownSeedsUpdate = bestSeedsUpdate
bestSeedsVFile.reset()
myBestSeedsVFile.close()
myBestSeedsVFile = StringIO()
i=0
for line in bestSeedsVFile:
myBestSeedsVFile.write(line)
s.release()
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if randReset: # new direction because current one led to worse fit
selectedMs = random.randrange(1,nMicrostructures)
direction = np.array(((random.random()-0.5)*delta[0],
(random.random()-0.5)*delta[1],
(random.random()-0.5)*delta[2]))
randReset = False
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perturbedSeedsVFile.close() # reset virtual file
perturbedSeedsVFile = StringIO()
myBestSeedsVFile.reset()
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perturbedSeedsTable = damask.ASCIItable(myBestSeedsVFile,perturbedSeedsVFile,labels=True) # read current best fitting seed file and to perturbed seed file
perturbedSeedsTable.head_read()
perturbedSeedsTable.head_write()
outputAlive=True
ms = 1
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while outputAlive and perturbedSeedsTable.data_read(): # perturbe selecte microstructure
if ms == selectedMs:
direction+=direction
newCoords=np.array(tuple(map(float,perturbedSeedsTable.data[0:3]))+direction)
newCoords=np.where(newCoords>=1.0,newCoords-1.0,newCoords)
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newCoords=np.where(newCoords <0.0,newCoords+1.0,newCoords)
perturbedSeedsTable.data[0:3]=[format(f, '8.6f') for f in newCoords]
ms+=1
perturbedSeedsTable.data_write()
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#--- do tesselation with perturbed seed file ----------------------------------------------------------
perturbedGeomVFile.close()
perturbedGeomVFile = StringIO()
perturbedSeedsVFile.reset()
perturbedGeomVFile.write(execute('geom_fromVoronoiTessellation '+
' -g '+' '.join(map(str, options.grid)),streamIn=perturbedSeedsVFile)[0])
perturbedGeomVFile.reset()
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#--- evaluate current seeds file ----------------------------------------------------------------------
perturbedGeomTable = damask.ASCIItable(perturbedGeomVFile,labels=False)
perturbedGeomTable.head_read()
for i in perturbedGeomTable.info:
if i.startswith('microstructures'): myNmicrostructures = int(i.split('\t')[1])
perturbedGeomTable.data_readArray()
perturbedGeomTable.output_flush()
currentData=np.bincount(perturbedGeomTable.data.astype(int).ravel())[1:]/points
currentError=[]
currentHist=[]
for i in xrange(nMicrostructures):
currentHist.append(np.histogram(currentData,bins=target[i]['bins'])[0])
currentError.append(np.sqrt(np.square(np.array(target[i]['histogram']-currentHist[i])).sum()))
s.acquire()
bestMatch = match
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#--- count bin classes with no mismatch ----------------------------------------------------------------------
myMatch=0
for i in xrange(nMicrostructures):
if currentError[i] > 0.0: break
myMatch = i+1
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if myNmicrostructures == nMicrostructures:
for i in xrange(min(nMicrostructures,myMatch+options.bins)):
if currentError[i] > target[i]['error']:
randReset = True
break
elif currentError[i] < target[i]['error']:
bestSeedsUpdate = time.time()
print 'Thread %i: Better match (%i bins, %6.4f --> %6.4f)'%(self.threadID,i+1,target[i]['error'],currentError[i])
print ' target: ',target[i]['histogram']
print ' best: ',currentHist[i]
currentSeedsName = baseFile+'_'+str(bestSeedsUpdate).replace('.','-')
perturbedSeedsVFile.reset()
bestSeedsVFile.close()
bestSeedsVFile = StringIO()
sys.stdout.flush()
with open(currentSeedsName+'.seeds','w') as currentSeedsFile:
for line in perturbedSeedsVFile:
currentSeedsFile.write(line)
bestSeedsVFile.write(line)
for j in xrange(nMicrostructures):
target[j]['error'] = currentError[j]
if myMatch > match:
print 'Stage %i cleared'%(myMatch)
match=myMatch
sys.stdout.flush()
break
if i == min(nMicrostructures,myMatch+options.bins)-1:
bestSeedsUpdate = time.time()
perturbedSeedsVFile.reset()
bestSeedsVFile.close()
bestSeedsVFile = StringIO()
for line in perturbedSeedsVFile:
bestSeedsVFile.write(line)
for j in xrange(nMicrostructures):
target[j]['error'] = currentError[j]
randReset = True
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else: #--- not all grains are tessellated
print 'Thread %i: Microstructure mismatch (%i microstructures mapped)'%(self.threadID,myNmicrostructures)
randReset = True
s.release()
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
Monte Carlo simulation to produce seed file that gives same size distribution like given geometry file.
""", version = scriptID)
parser.add_option('-s','--seeds', dest='seedFile', metavar='string',
help='name of the intial seed file. If not found, a new one is created [%default]')
parser.add_option('-g','--grid', dest='grid', type='int', nargs=3, metavar='int int int',
help='a,b,c grid of hexahedral box [%default]')
parser.add_option('-t','--threads', dest='threads', type='int', metavar='int',
help='number of parallel executions [%default]')
parser.add_option('-r', '--rnd', dest='randomSeed', type='int', metavar='int',
help='seed of random number generator [%default]')
parser.add_option('--target', dest='target', metavar='string',
help='name of the geom file with target distribution [%default]')
parser.add_option('--tolerance', dest='threshold', type='int', metavar='int',
help='stopping criterion (bin number) [%default]')
parser.add_option('--scale', dest='scale',type='float', metavar='float',
help='maximum moving distance of perturbed seed in pixel [%default]')
parser.add_option('--bins', dest='bins', type='int', metavar='int',
help='bins to sort beyond current best fit [%default]')
parser.set_defaults(seedFile = 'seeds')
parser.set_defaults(grid = (64,64,64))
parser.set_defaults(threads = 2)
parser.set_defaults(randomSeed = None)
parser.set_defaults(target = 'geom')
parser.set_defaults(threshold = 20)
parser.set_defaults(bins = 15)
parser.set_defaults(scale = 1.0)
options = parser.parse_args()[0]
if options.randomSeed == None:
options.randomSeed = int(os.urandom(4).encode('hex'), 16)
print 'random seed', options.randomSeed
delta = (options.scale/options.grid[0],options.scale/options.grid[1],options.scale/options.grid[2])
baseFile=os.path.splitext(os.path.basename(options.seedFile))[0]
points = float(reduce(mul,options.grid))
# ----------- calculate target distribution and bin edges
with open(os.path.splitext(os.path.basename(options.target))[0]+'.geom') as targetGeomFile:
targetGeomTable = damask.ASCIItable(targetGeomFile,labels=False)
targetGeomTable.head_read()
for i in targetGeomTable.info:
if i.startswith('microstructures'): nMicrostructures = int(i.split()[1])
if i.startswith('grid'): targetPoints = np.array(map(float,i.split()[2:7:2])).prod()
targetGeomTable.data_readArray()
targetVolFrac = np.bincount(targetGeomTable.data.astype(int).ravel())[1:nMicrostructures+1]/targetPoints
target=[]
for i in xrange(1,nMicrostructures+1):
targetHist,targetBins = np.histogram(targetVolFrac,bins=i) #bin boundaries
target.append({'histogram':targetHist,'bins':targetBins})
# ----------- create initial seed file or open existing one
bestSeedsVFile = StringIO()
if os.path.isfile(os.path.splitext(options.seedFile)[0]+'.seeds'):
with open(os.path.splitext(options.seedFile)[0]+'.seeds') as initialSeedFile:
for line in initialSeedFile: bestSeedsVFile.write(line)
else:
bestSeedsVFile.write(execute('seeds_fromRandom'+\
' -g '+' '.join(map(str, options.grid))+\
' -r %i'%options.randomSeed+\
' -N '+str(nMicrostructures))[0])
bestSeedsUpdate = time.time()
# ----------- tessellate initial seed file to get and evaluate geom file
bestSeedsVFile.reset()
initialGeomVFile = StringIO()
initialGeomVFile.write(execute('geom_fromVoronoiTessellation '+
' -g '+' '.join(map(str, options.grid)),bestSeedsVFile)[0])
initialGeomVFile.reset()
initialGeomTable = damask.ASCIItable(initialGeomVFile,labels=False)
initialGeomTable.head_read()
for i in initialGeomTable.info:
if i.startswith('microstructures'): initialMicrostructures = int(i.split('\t')[1])
if initialMicrostructures != nMicrostructures: print 'error. Microstructure count mismatch'
initialGeomTable.data_readArray()
initialData = np.bincount(initialGeomTable.data.astype(int).ravel())[1:]/points
for i in xrange(nMicrostructures):
initialHist = np.histogram(initialData,bins=target[i]['bins'])[0]
target[i]['error']=np.sqrt(np.square(np.array(target[i]['histogram']-initialHist)).sum())
match=0
for i in xrange(nMicrostructures):
if target[i]['error'] > 0.0: break
match = i+1
print 'Stage %i cleared'%match
sys.stdout.flush()
initialGeomVFile.close()
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# start mulithreaded monte carlo simulation
threads=[]
s=threading.Semaphore(1)
for i in range(options.threads):
threads.append(myThread(i))
threads[i].start()
for i in range(options.threads):
threads[i].join()