295 lines
15 KiB
Python
Executable File
295 lines
15 KiB
Python
Executable File
#!/usr/bin/python
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# -*- coding: UTF-8 no BOM -*-
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import threading,time,os,sys,random
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import numpy as np
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from optparse import OptionParser
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from operator import mul
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from cStringIO import StringIO
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import damask
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scriptName = os.path.splitext(os.path.basename(__file__))[0]
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scriptID = ' '.join([scriptName,damask.version])
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mismatch = None
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currentSeedsName = None
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#---------------------------------------------------------------------------------------------------
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class myThread (threading.Thread):
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"""perturbes seed in seed file, performes Voronoi tessellation, evaluates, and updates best match"""
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def __init__(self, threadID):
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threading.Thread.__init__(self)
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self.threadID = threadID
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def run(self):
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global bestSeedsUpdate
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global bestSeedsVFile
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global nMicrostructures
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global delta
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global points
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global target
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global match
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global baseFile
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global maxSeeds
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s.acquire()
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bestMatch = match
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s.release()
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random.seed(options.randomSeed+self.threadID) # initializes to given seeds
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knownSeedsUpdate = bestSeedsUpdate -1.0 # trigger update of local best seeds
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randReset = True # aquire new direction
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myBestSeedsVFile = StringIO() # store local copy of best seeds file
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perturbedSeedsVFile = StringIO() # perturbed best seeds file
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perturbedGeomVFile = StringIO() # tessellated geom file
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#--- still not matching desired bin class ----------------------------------------------------------
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while bestMatch < options.threshold:
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s.acquire() # ensure only one thread acces global data
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if bestSeedsUpdate > knownSeedsUpdate: # write best fit to virtual file
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knownSeedsUpdate = bestSeedsUpdate
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bestSeedsVFile.reset()
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myBestSeedsVFile.close()
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myBestSeedsVFile = StringIO()
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i=0
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for line in bestSeedsVFile:
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myBestSeedsVFile.write(line)
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s.release()
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if randReset: # new direction because current one led to worse fit
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randReset = False
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NmoveGrains = random.randrange(1,maxSeeds)
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selectedMs = []
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direction = []
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for i in xrange(NmoveGrains):
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selectedMs.append(random.randrange(1,nMicrostructures))
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direction.append(np.array(((random.random()-0.5)*delta[0],
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(random.random()-0.5)*delta[1],
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(random.random()-0.5)*delta[2])))
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perturbedSeedsVFile.close() # reset virtual file
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perturbedSeedsVFile = StringIO()
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myBestSeedsVFile.reset()
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perturbedSeedsTable = damask.ASCIItable(myBestSeedsVFile,perturbedSeedsVFile,labeled=True) # write best fit to perturbed seed file
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perturbedSeedsTable.head_read()
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perturbedSeedsTable.head_write()
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outputAlive=True
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ms = 1
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i = 0
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while outputAlive and perturbedSeedsTable.data_read(): # perturbe selected microstructure
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if ms in selectedMs:
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newCoords=np.array(tuple(map(float,perturbedSeedsTable.data[0:3]))+direction[i])
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newCoords=np.where(newCoords>=1.0,newCoords-1.0,newCoords) # ensure that the seeds remain in the box
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newCoords=np.where(newCoords <0.0,newCoords+1.0,newCoords)
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perturbedSeedsTable.data[0:3]=[format(f, '8.6f') for f in newCoords]
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direction[i]*=2.
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i+= 1
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ms+=1
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perturbedSeedsTable.data_write()
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#--- do tesselation with perturbed seed file ----------------------------------------------------------
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perturbedGeomVFile.close()
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perturbedGeomVFile = StringIO()
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perturbedSeedsVFile.reset()
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perturbedGeomVFile.write(damask.util.execute('geom_fromVoronoiTessellation '+
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' -g '+' '.join(map(str, options.grid)),streamIn=perturbedSeedsVFile)[0])
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perturbedGeomVFile.reset()
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#--- evaluate current seeds file ----------------------------------------------------------------------
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perturbedGeomTable = damask.ASCIItable(perturbedGeomVFile,None,labeled=False,readonly=True)
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perturbedGeomTable.head_read()
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for i in perturbedGeomTable.info:
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if i.startswith('microstructures'): myNmicrostructures = int(i.split('\t')[1])
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perturbedGeomTable.data_readArray()
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perturbedGeomTable.output_flush()
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currentData=np.bincount(perturbedGeomTable.data.astype(int).ravel())[1:]/points
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currentError=[]
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currentHist=[]
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for i in xrange(nMicrostructures): # calculate the deviation in all bins per histogram
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currentHist.append(np.histogram(currentData,bins=target[i]['bins'])[0])
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currentError.append(np.sqrt(np.square(np.array(target[i]['histogram']-currentHist[i])).sum()))
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# as long as not all grains are within the range of the target, use the deviation to left and right as error
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if currentError[0]>0.0:
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currentError[0] *=((target[0]['bins'][0]-np.min(currentData))**2.0+
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(target[0]['bins'][1]-np.max(currentData))**2.0)**0.5 # norm of deviations by number of usual bin deviation
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s.acquire() # do the evaluation serially
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bestMatch = match
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#--- count bin classes with no mismatch ----------------------------------------------------------------------
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myMatch=0
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for i in xrange(nMicrostructures):
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if currentError[i] > 0.0: break
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myMatch = i+1
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if myNmicrostructures == nMicrostructures:
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for i in xrange(min(nMicrostructures,myMatch+options.bins)):
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if currentError[i] > target[i]['error']: # worse fitting, next try
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randReset = True
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break
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elif currentError[i] < target[i]['error']: # better fit
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bestSeedsUpdate = time.time() # save time of better fit
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damask.util.croak('Thread %i: Better match (%i bins, %6.4f --> %6.4f)'
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%(self.threadID,i+1,target[i]['error'],currentError[i]))
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damask.util.croak(' target: %s'%np.array_str(target[i]['histogram']))
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damask.util.croak(' best: %s'%np.array_str(currentHist[i]))
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currentSeedsName = baseFile+'_'+str(bestSeedsUpdate).replace('.','-') # name of new seed file (use time as unique identifier)
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perturbedSeedsVFile.reset()
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bestSeedsVFile.close()
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bestSeedsVFile = StringIO()
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sys.stdout.flush()
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with open(currentSeedsName+'.seeds','w') as currentSeedsFile: # write to new file
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for line in perturbedSeedsVFile:
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currentSeedsFile.write(line)
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bestSeedsVFile.write(line)
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for j in xrange(nMicrostructures): # save new errors for all bins
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target[j]['error'] = currentError[j]
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if myMatch > match: # one or more new bins have no deviation
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damask.util.croak( 'Stage %i cleared'%(myMatch))
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match=myMatch
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sys.stdout.flush()
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break
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if i == min(nMicrostructures,myMatch+options.bins)-1: # same quality as before: take it to keep on moving
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bestSeedsUpdate = time.time()
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perturbedSeedsVFile.reset()
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bestSeedsVFile.close()
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bestSeedsVFile = StringIO()
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for line in perturbedSeedsVFile:
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bestSeedsVFile.write(line)
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for j in xrange(nMicrostructures):
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target[j]['error'] = currentError[j]
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randReset = True
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else: #--- not all grains are tessellated
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damask.util.croak('Thread %i: Microstructure mismatch (%i microstructures mapped)'
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%(self.threadID,myNmicrostructures))
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randReset = True
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s.release()
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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
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Monte Carlo simulation to produce seed file that gives same size distribution like given geometry file.
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""", version = scriptID)
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parser.add_option('-s','--seeds', dest='seedFile', metavar='string',
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help='name of the intial seed file. If not found, a new one is created [%default]')
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parser.add_option('-g','--grid', dest='grid', type='int', nargs=3, metavar='int int int',
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help='a,b,c grid of hexahedral box [%default]')
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parser.add_option('-t','--threads', dest='threads', type='int', metavar='int',
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help='number of parallel executions [%default]')
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parser.add_option('-r', '--rnd', dest='randomSeed', type='int', metavar='int',
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help='seed of random number generator [%default]')
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parser.add_option('--target', dest='target', metavar='string',
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help='name of the geom file with target distribution [%default]')
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parser.add_option('--tolerance', dest='threshold', type='int', metavar='int',
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help='stopping criterion (bin number) [%default]')
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parser.add_option('--scale', dest='scale',type='float', metavar='float',
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help='maximum moving distance of perturbed seed in pixel [%default]')
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parser.add_option('--bins', dest='bins', type='int', metavar='int',
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help='bins to sort beyond current best fit [%default]')
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parser.add_option('--maxseeds', dest='maxseeds', type='int', metavar='int',
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help='maximum number of seeds to move simulateneously [number of seeds]')
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parser.set_defaults(seedFile = 'seeds')
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parser.set_defaults(grid = (64,64,64))
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parser.set_defaults(threads = 2)
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parser.set_defaults(randomSeed = None)
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parser.set_defaults(target = 'geom')
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parser.set_defaults(threshold = 20)
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parser.set_defaults(bins = 15)
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parser.set_defaults(scale = 1.0)
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parser.set_defaults(maxseeds = 0)
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options = parser.parse_args()[0]
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damask.util.report(scriptName,options.seedFile)
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if options.randomSeed is None:
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options.randomSeed = int(os.urandom(4).encode('hex'), 16)
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damask.util.croak(options.randomSeed)
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delta = (options.scale/options.grid[0],options.scale/options.grid[1],options.scale/options.grid[2])
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baseFile=os.path.splitext(os.path.basename(options.seedFile))[0]
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points = float(reduce(mul,options.grid))
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# ----------- calculate target distribution and bin edges
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targetGeomFile = os.path.splitext(os.path.basename(options.target))[0]+'.geom'
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targetGeomTable = damask.ASCIItable(targetGeomFile,None,labeled=False,readonly=True)
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targetGeomTable.head_read()
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info,devNull = targetGeomTable.head_getGeom()
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nMicrostructures = info['microstructures']
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targetVolFrac = np.bincount(targetGeomTable.microstructure_read(info['grid']))[1:nMicrostructures+1]/\
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float(info['grid'].prod())
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target=[]
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for i in xrange(1,nMicrostructures+1):
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targetHist,targetBins = np.histogram(targetVolFrac,bins=i) #bin boundaries
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target.append({'histogram':targetHist,'bins':targetBins})
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# ----------- create initial seed file or open existing one
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bestSeedsVFile = StringIO()
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if os.path.isfile(os.path.splitext(options.seedFile)[0]+'.seeds'):
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with open(os.path.splitext(options.seedFile)[0]+'.seeds') as initialSeedFile:
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for line in initialSeedFile: bestSeedsVFile.write(line)
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else:
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bestSeedsVFile.write(damask.util.execute('seeds_fromRandom'+\
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' -g '+' '.join(map(str, options.grid))+\
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' -r %i'%options.randomSeed+\
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' -N '+str(nMicrostructures))[0])
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bestSeedsUpdate = time.time()
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# ----------- tessellate initial seed file to get and evaluate geom file
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bestSeedsVFile.reset()
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initialGeomVFile = StringIO()
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initialGeomVFile.write(damask.util.execute('geom_fromVoronoiTessellation '+
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' -g '+' '.join(map(str, options.grid)),bestSeedsVFile)[0])
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initialGeomVFile.reset()
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initialGeomTable = damask.ASCIItable(initialGeomVFile,None,labeled=False,readonly=True)
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initialGeomTable.head_read()
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info,devNull = initialGeomTable.head_getGeom()
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if info['microstructures'] != nMicrostructures: damask.util.croak('error. Microstructure count mismatch')
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initialData = np.bincount(initialGeomTable.microstructure_read(info['grid']))/points
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for i in xrange(nMicrostructures):
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initialHist = np.histogram(initialData,bins=target[i]['bins'])[0]
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target[i]['error']=np.sqrt(np.square(np.array(target[i]['histogram']-initialHist)).sum())
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# as long as not all grain sizes are within the range, the error is the deviation to left and right
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if target[0]['error'] > 0.0:
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target[0]['error'] *=((target[0]['bins'][0]-np.min(initialData))**2.0+
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(target[0]['bins'][1]-np.max(initialData))**2.0)**0.5
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match=0
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for i in xrange(nMicrostructures):
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if target[i]['error'] > 0.0: break
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match = i+1
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if options.maxseeds < 1:
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maxSeeds = info['microstructures']
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else:
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maxSeeds = options.maxseeds
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if match >0: damask.util.croak('Stage %i cleared'%match)
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sys.stdout.flush()
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initialGeomVFile.close()
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# start mulithreaded monte carlo simulation
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threads=[]
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s=threading.Semaphore(1)
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for i in range(options.threads):
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threads.append(myThread(i))
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threads[i].start()
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for i in range(options.threads):
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threads[i].join()
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