DAMASK_EICMD/processing/pre/seeds_fromDistribution.py

283 lines
13 KiB
Python
Executable File

#!/usr/bin/env python3
import threading
import time
import os
import sys
import random
from optparse import OptionParser
from io import StringIO
import numpy as np
import damask
scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
mismatch = None
currentSeedsName = None
#---------------------------------------------------------------------------------------------------
class myThread (threading.Thread):
"""Perturb seed in seed file, performes Voronoi tessellation, evaluates, and updates best match."""
def __init__(self, threadID):
"""Threading class with thread ID."""
threading.Thread.__init__(self)
self.threadID = threadID
def run(self):
global bestSeedsUpdate
global bestSeedsVFile
global nMaterials
global delta
global points
global target
global match
global baseFile
global maxSeeds
s.acquire()
bestMatch = match
s.release()
random.seed(options.randomSeed+self.threadID) # initializes to given seeds
knownSeedsUpdate = bestSeedsUpdate -1.0 # trigger update of local best seeds
randReset = True # aquire new direction
myBestSeedsVFile = StringIO() # store local copy of best seeds file
perturbedSeedsVFile = StringIO() # perturbed best seeds file
perturbedGeomVFile = StringIO() # tessellated geom file
#--- still not matching desired bin class ----------------------------------------------------------
while bestMatch < options.threshold:
s.acquire() # ensure only one thread acces global data
if bestSeedsUpdate > knownSeedsUpdate: # write best fit to virtual file
knownSeedsUpdate = bestSeedsUpdate
bestSeedsVFile.seek(0)
myBestSeedsVFile.close()
myBestSeedsVFile = StringIO()
i=0
myBestSeedsVFile.writelines(bestSeedsVFile.readlines())
s.release()
if randReset: # new direction because current one led to worse fit
randReset = False
NmoveGrains = random.randrange(1,maxSeeds)
selectedMs = []
direction = []
for i in range(NmoveGrains):
selectedMs.append(random.randrange(1,nMaterials))
direction.append((np.random.random()-0.5)*delta)
perturbedSeedsVFile.close() # reset virtual file
perturbedSeedsVFile = StringIO()
myBestSeedsVFile.seek(0)
perturbedSeedsTable = damask.Table.load(myBestSeedsVFile)
coords = perturbedSeedsTable.get('pos')
i = 0
for ms,coord in enumerate(coords):
if ms in selectedMs:
newCoords=coord+direction[i]
newCoords=np.where(newCoords>=1.0,newCoords-1.0,newCoords) # ensure that the seeds remain in the box
newCoords=np.where(newCoords <0.0,newCoords+1.0,newCoords)
coords[i]=newCoords
direction[i]*=2.
i+= 1
perturbedSeedsTable.set('pos',coords).save(perturbedSeedsVFile,legacy=True)
#--- do tesselation with perturbed seed file ------------------------------------------------------
perturbedGeomVFile.close()
perturbedGeomVFile = StringIO()
perturbedSeedsVFile.seek(0)
perturbedGeomVFile.write(damask.util.execute('geom_fromVoronoiTessellation '+
' -g '+' '.join(list(map(str, options.grid))),streamIn=perturbedSeedsVFile)[0])
perturbedGeomVFile.seek(0)
#--- evaluate current seeds file ------------------------------------------------------------------
perturbedGeom = damask.Geom.load_ASCII(perturbedGeomVFile)
myNmaterials = len(np.unique(perturbedGeom.material))
currentData = np.bincount(perturbedGeom.material.ravel())[1:]/points
currentError=[]
currentHist=[]
for i in range(nMaterials): # calculate the deviation in all bins per histogram
currentHist.append(np.histogram(currentData,bins=target[i]['bins'])[0])
currentError.append(np.sqrt(np.square(np.array(target[i]['histogram']-currentHist[i])).sum()))
# as long as not all grains are within the range of the target, use the deviation to left and right as error
if currentError[0]>0.0:
currentError[0] *=((target[0]['bins'][0]-np.min(currentData))**2.0+
(target[0]['bins'][1]-np.max(currentData))**2.0)**0.5 # norm of deviations by number of usual bin deviation
s.acquire() # do the evaluation serially
bestMatch = match
#--- count bin classes with no mismatch ----------------------------------------------------------------------
myMatch=0
for i in range(nMaterials):
if currentError[i] > 0.0: break
myMatch = i+1
if myNmaterials == nMaterials:
for i in range(min(nMaterials,myMatch+options.bins)):
if currentError[i] > target[i]['error']: # worse fitting, next try
randReset = True
break
elif currentError[i] < target[i]['error']: # better fit
bestSeedsUpdate = time.time() # save time of better fit
damask.util.croak('Thread {:d}: Better match ({:d} bins, {:6.4f} --> {:6.4f})'\
.format(self.threadID,i+1,target[i]['error'],currentError[i]))
damask.util.croak(' target: '+np.array_str(target[i]['histogram']))
damask.util.croak(' best: '+np.array_str(currentHist[i]))
currentSeedsName = baseFile+'_'+str(bestSeedsUpdate).replace('.','-') # name of new seed file (use time as unique identifier)
perturbedSeedsVFile.seek(0)
bestSeedsVFile.close()
bestSeedsVFile = StringIO()
sys.stdout.flush()
with open(currentSeedsName+'.seeds','w') as currentSeedsFile: # write to new file
for line in perturbedSeedsVFile:
currentSeedsFile.write(line)
bestSeedsVFile.write(line)
for j in range(nMaterials): # save new errors for all bins
target[j]['error'] = currentError[j]
if myMatch > match: # one or more new bins have no deviation
damask.util.croak( 'Stage {:d} cleared'.format(myMatch))
match=myMatch
sys.stdout.flush()
break
if i == min(nMaterials,myMatch+options.bins)-1: # same quality as before: take it to keep on moving
bestSeedsUpdate = time.time()
perturbedSeedsVFile.seek(0)
bestSeedsVFile.close()
bestSeedsVFile = StringIO()
bestSeedsVFile.writelines(perturbedSeedsVFile.readlines())
for j in range(nMaterials):
target[j]['error'] = currentError[j]
randReset = True
else: #--- not all grains are tessellated
damask.util.croak('Thread {:d}: Material mismatch ({:d} material indices mapped)'\
.format(self.threadID,myNmaterials))
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.add_option('--maxseeds', dest='maxseeds', type='int', metavar='int',
help='maximum number of seeds to move simulateneously [number of seeds]')
parser.set_defaults(seedFile = 'seeds',
grid = (64,64,64),
threads = 2,
randomSeed = None,
target = 'geom',
threshold = 20,
bins = 15,
scale = 1.0,
maxseeds = 0)
options = parser.parse_args()[0]
damask.util.report(scriptName,options.seedFile)
if options.randomSeed is None:
options.randomSeed = int(os.urandom(4).hex(),16)
damask.util.croak(options.randomSeed)
delta = options.scale/np.array(options.grid)
baseFile = os.path.splitext(os.path.basename(options.seedFile))[0]
points = np.array(options.grid).prod().astype('float')
# ----------- calculate target distribution and bin edges
targetGeom = damask.Geom.load_ASCII(os.path.splitext(os.path.basename(options.target))[0]+'.geom')
nMaterials = len(np.unique(targetGeom.material))
targetVolFrac = np.bincount(targetGeom.material.flatten())/targetGeom.grid.prod().astype(np.float)
target = []
for i in range(1,nMaterials+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(damask.util.execute('seeds_fromRandom'+\
' -g '+' '.join(list(map(str, options.grid)))+\
' -r {:d}'.format(options.randomSeed)+\
' -N '+str(nMaterials))[0])
bestSeedsUpdate = time.time()
# ----------- tessellate initial seed file to get and evaluate geom file
bestSeedsVFile.seek(0)
initialGeomVFile = StringIO()
initialGeomVFile.write(damask.util.execute('geom_fromVoronoiTessellation '+
' -g '+' '.join(list(map(str, options.grid))),bestSeedsVFile)[0])
initialGeomVFile.seek(0)
initialGeom = damask.Geom.load_ASCII(initialGeomVFile)
if len(np.unique(targetGeom.material)) != nMaterials:
damask.util.croak('error. Material count mismatch')
initialData = np.bincount(initialGeom.material.flatten())/points
for i in range(nMaterials):
initialHist = np.histogram(initialData,bins=target[i]['bins'])[0]
target[i]['error']=np.sqrt(np.square(np.array(target[i]['histogram']-initialHist)).sum())
# as long as not all grain sizes are within the range, the error is the deviation to left and right
if target[0]['error'] > 0.0:
target[0]['error'] *=((target[0]['bins'][0]-np.min(initialData))**2.0+
(target[0]['bins'][1]-np.max(initialData))**2.0)**0.5
match=0
for i in range(nMaterials):
if target[i]['error'] > 0.0: break
match = i+1
if options.maxseeds < 1:
maxSeeds = len(np.unique(initialGeom.material))
else:
maxSeeds = options.maxseeds
if match >0: damask.util.croak('Stage {:d} cleared'.format(match))
sys.stdout.flush()
initialGeomVFile.close()
# 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()