#!/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(hexagonal = False)
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
if options.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 options.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 options.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()