#!/usr/bin/env python import os,re,sys,math,string,damask,numpy from optparse import OptionParser, Option # ----------------------------- class extendableOption(Option): # ----------------------------- # used for definition of new option parser action 'extend', which enables to take multiple option arguments # taken from online tutorial http://docs.python.org/library/optparse.html ACTIONS = Option.ACTIONS + ("extend",) STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",) TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",) ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",) def take_action(self, action, dest, opt, value, values, parser): if action == "extend": lvalue = value.split(",") values.ensure_value(dest, []).extend(lvalue) else: Option.take_action(self, action, dest, opt, value, values, parser) def integerFactorization(i): j = int(math.floor(math.sqrt(float(i)))) while (j>1 and int(i)%j != 0): j -= 1 return j def positiveRadians(angle): angle = math.radians(float(angle)) while angle < 0.0: angle += 2.0*math.pi return angle def getHeader(sizeX,sizeY,step): return [ \ '# TEM_PIXperUM 1.000000', \ '# x-star 0.509548', \ '# y-star 0.795272', \ '# z-star 0.611799', \ '# WorkingDistance 18.000000', \ '#', \ '# Phase 1', \ '# MaterialName Al', \ '# Formula Fe', \ '# Info', \ '# Symmetry 43', \ '# LatticeConstants 2.870 2.870 2.870 90.000 90.000 90.000', \ '# NumberFamilies 4', \ '# hklFamilies 1 1 0 1 0.000000 1', \ '# hklFamilies 2 0 0 1 0.000000 1', \ '# hklFamilies 2 1 1 1 0.000000 1', \ '# hklFamilies 3 1 0 1 0.000000 1', \ '# Categories 0 0 0 0 0 ', \ '#', \ '# GRID: SquareGrid', \ '# XSTEP: ' + str(step), \ '# YSTEP: ' + str(step), \ '# NCOLS_ODD: ' + str(sizeX), \ '# NCOLS_EVEN: ' + str(sizeX), \ '# NROWS: ' + str(sizeY), \ '#', \ '# OPERATOR: ODFsammpling', \ '#', \ '# SAMPLEID: ', \ '#', \ '# SCANID: ', \ '#', \ ] # -------------------------------------------------------------------- # MAIN # -------------------------------------------------------------------- parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """ Builds an ang file out of ASCII table. """ + string.replace('$Id$','\n','\\n') ) parser.add_option('--coords', dest='coords', type='string', \ help='label of coords in ASCII table') parser.add_option('--eulerangles', dest='eulerangles', type='string', \ help='label of euler angles in ASCII table') parser.add_option('--defgrad', dest='defgrad', type='string', \ help='label of deformation gradient in ASCII table') parser.add_option('-n','--normal', dest='normal', type='float', nargs=3, \ help='normal of slices to visualize') parser.add_option('-s','--size', dest='size', type='float', nargs=3, \ help='physical size of ang file') parser.add_option('-u','--up', dest='up', type='float', nargs=3, help='up direction of slices to visualize') parser.add_option('-r','--resolution', dest='res', type='float', help='scaling factor for resolution') parser.add_option('--hexagonal', dest='hex', action='store_true', help='use in plane hexagonal grid') parser.add_option('-c','--center', dest='center', type='float', nargs=3, help='center of ang file in cube, negative for center') parser.set_defaults(coords = 'coords') parser.set_defaults(eulerangles = 'eulerangles') parser.set_defaults(defgrad = 'f') parser.set_defaults(normal = [0.0,0.0,1.0]) parser.set_defaults(size = [1.0,1.0,0.0]) parser.set_defaults(up = [1.0,0.0,0.0]) parser.set_defaults(center = [-1.0,-1.0,-1.0]) parser.set_defaults(res = 1.0) (options,filenames) = parser.parse_args() datainfo = { 'vector': {'len':3, 'label':[]}, 'tensor': {'len':9, 'label':[]} } datainfo['vector']['label'].append(options.coords) datainfo['vector']['label'].append(options.eulerangles) datainfo['tensor']['label'].append(options.defgrad) # ------------------------------------------ setup file handles --------------------------------------- files = [] if filenames == []: files.append({'name':'STDIN', 'input':sys.stdin, 'output':sys.stdout}) else: for name in filenames: if os.path.exists(name): files.append({'name':name, 'input':open(name)}) # ------------------------------------------ loop over input files --------------------------------------- for file in files: if file['name'] != 'STDIN': print file['name'] table = damask.ASCIItable(file['input']) # open ASCII_table for reading table.head_read() # read ASCII header info # --------------- figure out dimension and resolution try: locationCol = table.labels.index('ip.x') # columns containing location data except ValueError: print 'no coordinate data found...' continue grid = [{},{},{}] while table.data_read(): # read next data line of ASCII table for j in xrange(3): grid[j][str(table.data[locationCol+j])] = True # remember coordinate along x,y,z resolution = numpy.array([len(grid[0]),\ len(grid[1]),\ len(grid[2]),],'i') # resolution is number of distinct coordinates found dimension = resolution/numpy.maximum(numpy.ones(3,'d'),resolution-1.0)* \ numpy.array([max(map(float,grid[0].keys()))-min(map(float,grid[0].keys())),\ max(map(float,grid[1].keys()))-min(map(float,grid[1].keys())),\ max(map(float,grid[2].keys()))-min(map(float,grid[2].keys())),\ ],'d') # dimension from bounding box, corrected for cell-centeredness if resolution[2] == 1: dimension[2] = min(dimension[:2]/resolution[:2]) N = resolution.prod() print '\t%s @ %s'%(dimension,resolution) # --------------- figure out columns to process active = {} column = {} values = {} head = [] for datatype,info in datainfo.items(): for label in info['label']: key = {True :'1_%s', False:'%s' }[info['len']>1]%label if key not in table.labels: sys.stderr.write('column %s not found...\n'%key) else: if datatype not in active: active[datatype] = [] if datatype not in column: column[datatype] = {} if datatype not in values: values[datatype] = {} active[datatype].append(label) column[datatype][label] = table.labels.index(key) # remember columns of requested data values[datatype][label] = numpy.array([0.0 for i in xrange(N*datainfo[datatype]['len'])]) # ------------------------------------------ read value field --------------------------------------- table.data_rewind() idx = 0 while table.data_read(): # read next data line of ASCII table for datatype,labels in active.items(): # loop over vector,tensor for label in labels: # loop over all requested curls begin = idx*datainfo[datatype]['len'] end = begin + datainfo[datatype]['len'] values[datatype][label][begin:end]= numpy.array(map(float,table.data[column[datatype][label]: column[datatype][label]+datainfo[datatype]['len']]),'d') idx+=1 stepSize = 0.0 for i in xrange(3): stepSize+=dimension[i]/resolution[i]/3.0/options.res print 'step size', stepSize hexagonal = False if hexagonal: stepSize0 = stepSize * math.sin(1.0/3.0*math.pi) else: stepSize0 = stepSize print 'step Size in x direction', stepSize0 angRes = int(options.size[0]/stepSize0),\ int(options.size[1]/stepSize),\ max(int(options.size[2]/stepSize),1) print 'resolution of ang file', angRes if hexagonal: NpointsSlice = angRes[0]//2*(angRes[1]-1)+(angRes[0]-angRes[0]//2)*angRes[1] else: NpointsSlice = angRes[0]*angRes[1] z = numpy.array(options.normal,dtype='float') z = z/numpy.linalg.norm(z) x = numpy.array(options.up,dtype='float') x = x/numpy.linalg.norm(x) y = numpy.cross(z,x) x = numpy.cross(y,z) print 'x unit vector', x, 'with norm ', numpy.linalg.norm(x) print 'y unit vector', y, 'with norm ', numpy.linalg.norm(y) print 'z unit vector', z, 'with norm ', numpy.linalg.norm(z) Favg = damask.core.math.tensorAvg(values['tensor']['%s'%(options.defgrad)].\ reshape(resolution[0],resolution[1],resolution[2],3,3)) coordTransform = numpy.array([x,y,z]) print 'rotation matrix', coordTransform mySlice = numpy.zeros(NpointsSlice*3) eulerangles = values['vector']['%s'%options.eulerangles].reshape([3,N],order='F') offset = ((dimension - options.size)/2.0 + (dimension/angRes)/2.0)/options.res print 'offset', offset # offset = numpy.array([0.5,0.5,0.5],dtype='float')/[float(options.res[0]),float(options.res[1]),float(options.res[2])]*[dimension[0],dimension[1],dimension[2]] for i in xrange(angRes[2]): idx = 0 for j in xrange(angRes[0]): if hexagonal: res1=angRes[1]-j%2 #myOffset = offset +float(j%2)* numpy.array([0.0,0.5,0.0],dtype='float')/[float(options.res[0]),float(options.res[1]),float(options.res[2])]*[dimension[0],dimension[1],dimension[2]] myOffset = offset +float(j%2)* numpy.array([0.0,0.5*stepSize,0.0],dtype='float') else: res1=angRes[1] myOffset = offset for k in xrange(res1): mySlice[idx*3:idx*3+3] = numpy.dot(coordTransform,[j*stepSize0,k*stepSize,i*stepSize]+myOffset) #print mySlice[idx*3:idx*3+3] idx+=1 mySlice = mySlice.reshape([3,NpointsSlice],order='F') indices=damask.core.math.math_nearestNeighborSearch(3,Favg,numpy.array( dimension,dtype='float'),NpointsSlice,N,mySlice,values['vector']['%s'%options.coords].reshape([3,N],order='F'))/27 fileOut=open(os.path.join(os.path.dirname(name),os.path.splitext(os.path.basename(name))[0]+'_%s.ang'%(angRes[2]-i-1)),'w') for line in getHeader(angRes[0],angRes[1],angRes[2]): fileOut.write(line + '\n') # write data for idx in xrange(NpointsSlice): fileOut.write(''.join(['%10.5f'%positiveRadians(angle) for angle in eulerangles[:,indices[idx]]])+ ' %10.5f %10.5f'%(mySlice[1,idx],mySlice[0,idx])+ ' 100.0 1.0 0 1 1.0\n') fileOut.close()