pre processing finished
This commit is contained in:
Martin Diehl
parent
93d7643875
commit
3ff3bb1a5b
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@ -129,7 +129,8 @@ def servoLink():
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])
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for i in range(nLinks):
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cmds.append([
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"*link_class servo *servo_ret_node %i %i"%(i+1,baseNode["%.8e"%linkCoord[i][0]]["%.8e"%linkCoord[i][1]]["%.8e"%linkCoord[i][2]]),
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"*link_class servo *servo_ret_node %i %i"\
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%(i+1,baseNode["%.8e"%linkCoord[i][0]]["%.8e"%linkCoord[i][1]]["%.8e"%linkCoord[i][2]]),
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"*link_class servo *servo_ret_dof %i %i"%(i+1,dof),
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"*link_class servo *servo_ret_coef %i 1"%(i+1),
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])
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@ -234,7 +234,8 @@ def rcbParser(content,M,size,tolerance,idcolumn,segmentcolumn):
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crappyData = False
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for pointId,point in enumerate(points):
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if len(point['segments']) < 2: # point marks a dead end!
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print "Dead end at segment %i (%f,%f)"%(1+point['segments'][0],boxX[0]+point['coords'][0]/scalePatch,boxY[0]+point['coords'][1]/scalePatch,)
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print "Dead end at segment %i (%f,%f)"\
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%(1+point['segments'][0],boxX[0]+point['coords'][0]/scalePatch,boxY[0]+point['coords'][1]/scalePatch,)
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crappyData = True
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grains = {'draw': [], 'legs': []}
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@ -367,7 +368,8 @@ def sample(size,aspect,n,xmargin,ymargin):
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def patch(a,n,mesh,rcData):
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cmds = []
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for l in range(len(rcData['point'])): # generate all points
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cmds.append("*add_points %f %f %f"%(rcData['point'][l][0]-a/2.0,rcData['point'][l][1]-a/rcData['dimension'][0]*rcData['dimension'][1]/2.0,0))
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cmds.append("*add_points %f %f %f"\
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%(rcData['point'][l][0]-a/2.0,rcData['point'][l][1]-a/rcData['dimension'][0]*rcData['dimension'][1]/2.0,0))
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cmds.append(["*set_curve_type line",
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"*set_curve_div_type_fix_ndiv",
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@ -891,7 +893,8 @@ if 'spectral' in options.output:
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(y+1)*fftdata['resolution'][0]]))+'\n') # grain indexes, x-row per line
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geomFile.close() # close geom file
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print('assigned %i out of %i (2D) Fourier points.'%(len(fftdata['fftpoints']), int(fftdata['resolution'][0])*int(fftdata['resolution'][1])))
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print('assigned %i out of %i (2D) Fourier points.'\
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%(len(fftdata['fftpoints']), int(fftdata['resolution'][0])*int(fftdata['resolution'][1])))
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# ----- write Mentat procedure -----
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@ -974,7 +977,8 @@ if 'mentat' in options.output or 'spectral' in options.output:
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for grain in rcData['grainMapping']:
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output += '\n[grain %i]\n'%grain + \
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'(gauss)\tphi1\t%f\tphi\t%f\tphi2\t%f\tscatter\t%f\tfraction\t1.0\n'\
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%(math.degrees(orientationData[grain-1][0]),math.degrees(orientationData[grain-1][1]),math.degrees(orientationData[grain-1][2]),options.scatter)
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%(math.degrees(orientationData[grain-1][0]),math.degrees(orientationData[grain-1][1]),\
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math.degrees(orientationData[grain-1][2]),options.scatter)
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if (options.xmargin > 0.0 or options.ymargin > 0.0):
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output += '\n[margin]\n' + \
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'(random)\t\tscatter\t0.0\tfraction\t1.0\n'
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@ -1,7 +1,7 @@
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#!/usr/bin/python
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# -*- coding: UTF-8 no BOM -*-
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import threading,time,os,subprocess,shlex,string,sys,random
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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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@ -16,10 +16,8 @@ currentSeedsName = None
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#---------------------------------------------------------------------------------------------------
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class myThread (threading.Thread):
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#---------------------------------------------------------------------------------------------------
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'''
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perturbes seed in seed file, performes Voronoi tessellation, evaluates, and updates best match
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'''
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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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@ -40,17 +38,17 @@ class myThread (threading.Thread):
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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 (time when the best seed file was found known to thread)
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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() # in-memory file to store local copy of best seeds file
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perturbedSeedsVFile = StringIO() # in-memory file for perturbed best seeds file
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perturbedGeomVFile = StringIO() # in-memory file for tessellated geom file
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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() # accessing global data, ensure only one thread does it per time
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if bestSeedsUpdate > knownSeedsUpdate: # if a newer best seed file exist, read it into a virtual file
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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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@ -78,7 +76,7 @@ class myThread (threading.Thread):
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perturbedSeedsVFile = StringIO()
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myBestSeedsVFile.reset()
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perturbedSeedsTable = damask.ASCIItable(myBestSeedsVFile,perturbedSeedsVFile,labeled=True) # read current best fitting seed file and to perturbed seed file
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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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@ -87,7 +85,7 @@ class myThread (threading.Thread):
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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 (move one side out, other side in)
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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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@ -115,8 +113,9 @@ class myThread (threading.Thread):
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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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if currentError[0]>0.0: # 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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# 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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@ -154,7 +153,7 @@ class myThread (threading.Thread):
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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 (for the considered bins): take it to keep on moving
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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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@ -215,7 +214,7 @@ options = parser.parse_args()[0]
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damask.util.report(scriptName,options.seedFile)
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if options.randomSeed == None:
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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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@ -122,10 +122,9 @@ for name in filenames:
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newInfo['microstructures'] = len(np.unique(seeds[:,3]))
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# --- report ---------------------------------------------------------------------------------------
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if (newInfo['microstructures'] != info['microstructures']):
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damask.util.croak(remarks.append('--> microstructures: %i'%newInfo['microstructures']))
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remarks = []
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if ( newInfo['microstructures'] != info['microstructures']): remarks.append('--> microstructures: %i'%newInfo['microstructures'])
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if remarks != []: damask.util.croak(remarks)
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# ------------------------------------------ assemble header ---------------------------------------
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table.info_clear()
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