269 lines
12 KiB
Python
Executable File
269 lines
12 KiB
Python
Executable File
#!/usr/bin/env python3
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import threading
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import time
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import os
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import sys
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import random
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from optparse import OptionParser
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from io import StringIO
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import numpy as np
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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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"""Perturb 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 class with thread ID."""
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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 nMaterials
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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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#--- 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.seek(0)
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myBestSeedsVFile.close()
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myBestSeedsVFile = StringIO()
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i=0
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myBestSeedsVFile.writelines(bestSeedsVFile.readlines())
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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 range(NmoveGrains):
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selectedMs.append(random.randrange(1,nMaterials))
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direction.append((np.random.random()-0.5)*delta)
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perturbedSeedsVFile.close() # reset virtual file
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perturbedSeedsVFile = StringIO()
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myBestSeedsVFile.seek(0)
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perturbedSeedsTable = damask.Table.load(myBestSeedsVFile)
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coords = perturbedSeedsTable.get('pos')
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i = 0
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for ms,coord in enumerate(coords):
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if ms in selectedMs:
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newCoords=coord+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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coords[i]=newCoords
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direction[i]*=2.
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i+= 1
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perturbedSeedsTable.set('pos',coords).save(perturbedSeedsVFile,legacy=True)
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#--- do tesselation with perturbed seed file ------------------------------------------------------
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perturbedGeom = damask.Grid.from_Voronoi_tessellation(options.grid,np.ones(3),coords)
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#--- evaluate current seeds file ------------------------------------------------------------------
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myNmaterials = len(np.unique(perturbedGeom.material))
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currentData = np.bincount(perturbedGeom.material.ravel())[1:]/points
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currentError=[]
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currentHist=[]
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for i in range(nMaterials): # 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 range(nMaterials):
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if currentError[i] > 0.0: break
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myMatch = i+1
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if myNmaterials == nMaterials:
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for i in range(min(nMaterials,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 {:d}: Better match ({:d} bins, {:6.4f} --> {:6.4f})'\
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.format(self.threadID,i+1,target[i]['error'],currentError[i]))
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damask.util.croak(' target: '+np.array_str(target[i]['histogram']))
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damask.util.croak(' best: '+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.seek(0)
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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 range(nMaterials): # 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 {:d} cleared'.format(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(nMaterials,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.seek(0)
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bestSeedsVFile.close()
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bestSeedsVFile = StringIO()
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bestSeedsVFile.writelines(perturbedSeedsVFile.readlines())
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for j in range(nMaterials):
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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 {:d}: Material mismatch ({:d} material indices mapped)'\
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.format(self.threadID,myNmaterials))
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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(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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grid = (64,64,64),
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threads = 2,
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randomSeed = None,
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target = 'geom',
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threshold = 20,
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bins = 15,
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scale = 1.0,
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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).hex(),16)
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damask.util.croak(options.randomSeed)
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delta = options.scale/np.array(options.grid)
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baseFile = os.path.splitext(os.path.basename(options.seedFile))[0]
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points = np.array(options.grid).prod().astype('float')
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# ----------- calculate target distribution and bin edges
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targetGeom = damask.Grid.load_ASCII(os.path.splitext(os.path.basename(options.target))[0]+'.geom')
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nMaterials = len(np.unique(targetGeom.material))
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targetVolFrac = np.bincount(targetGeom.material.flatten())/targetGeom.cells.prod().astype(np.float)
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target = []
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for i in range(1,nMaterials+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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initial_seeds = damask.Table.load(os.path.splitext(options.seedFile)[0]+'.seeds').get('pos')
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else:
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initial_seeds = damask.seeds.from_random(np.ones(3),nMaterials,options.grid,options.randomSeed)
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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.seek(0)
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initialGeom = damask.Grid.from_Voronoi_tessellation(options.grid,np.ones(3),initial_seeds)
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if len(np.unique(targetGeom.material)) != nMaterials:
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damask.util.croak('error. Material count mismatch')
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initialData = np.bincount(initialGeom.material.flatten())/points
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for i in range(nMaterials):
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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 range(nMaterials):
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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 = len(np.unique(initialGeom.material))
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else:
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maxSeeds = options.maxseeds
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if match >0: damask.util.croak('Stage {:d} cleared'.format(match))
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sys.stdout.flush()
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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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