further improvements on the conversion, seems to work quite good for the 2D case now
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@ -93,19 +93,24 @@ parser.add_option('--defgrad', dest='defgrad', type='string', \
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help='label of deformation gradient in ASCII table')
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parser.add_option('-n','--normal', dest='normal', type='float', nargs=3, \
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help='normal of slices to visualize')
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parser.add_option('-s','--size', dest='size', type='float', nargs=3, \
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help='physical size of ang file')
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parser.add_option('-u','--up', dest='up', type='float', nargs=3,
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help='up direction of slices to visualize')
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parser.add_option('-r','--resolution', dest='res', type='int', nargs=3,
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help='up direction of slices to visualize')
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parser.add_option('-r','--resolution', dest='res', type='float',
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help='scaling factor for resolution')
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parser.add_option('--hexagonal', dest='hex', action='store_true',
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help='use in plane hexagonal grid')
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parser.add_option('-c','--center', dest='center', type='float', nargs=3,
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help='center of ang file in cube, negative for center')
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parser.set_defaults(coords = 'coords')
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parser.set_defaults(eulerangles = 'eulerangles')
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parser.set_defaults(defgrad = 'f')
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parser.set_defaults(normal = ['0.0','0.0','1.0'])
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parser.set_defaults(up = ['1.0','0.0','0.0'])
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parser.set_defaults(center = ['-1.0','-1.0','-1.0'])
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parser.set_defaults(res = ['16','16','1'])
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parser.set_defaults(normal = [0.0,0.0,1.0])
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parser.set_defaults(size = [1.0,1.0,0.0])
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parser.set_defaults(up = [1.0,0.0,0.0])
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parser.set_defaults(center = [-1.0,-1.0,-1.0])
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parser.set_defaults(res = 1.0)
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(options,filenames) = parser.parse_args()
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datainfo = {
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@ -119,10 +124,6 @@ datainfo['vector']['label'].append(options.coords)
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datainfo['vector']['label'].append(options.eulerangles)
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datainfo['tensor']['label'].append(options.defgrad)
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print options.res[0]
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print options.res[1]
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print options.res[2]
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# ------------------------------------------ setup file handles ---------------------------------------
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files = []
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@ -169,7 +170,8 @@ for file in files:
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N = resolution.prod()
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print '\t%s @ %s'%(dimension,resolution)
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# --------------- figure out columns to process
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# --------------- figure out columns to process
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active = {}
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column = {}
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values = {}
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@ -201,55 +203,69 @@ for file in files:
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values[datatype][label][begin:end]= numpy.array(map(float,table.data[column[datatype][label]:
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column[datatype][label]+datainfo[datatype]['len']]),'d')
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idx+=1
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hexagonal = True
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if hexagonal:
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scale = math.sin(1.0/3.0*math.pi)
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else:
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scale = 1.0
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res0 = int(float(options.res[0])/scale)
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print 'res0', res0
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print 'res 1', options.res[1]
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stepSize = 0.0
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for i in xrange(3): stepSize+=dimension[i]/resolution[i]/3.0/options.res
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print 'step size', stepSize
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hexagonal = False
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if hexagonal:
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NpointsSlice = res0//2*(int(options.res[1])-1)+(res0-res0//2)*int(options.res[1])
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else:
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NpointsSlice = res0*int(options.res[1])
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stepSize0 = stepSize * math.sin(1.0/3.0*math.pi)
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else:
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stepSize0 = stepSize
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print 'step Size in x direction', stepSize0
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angRes = int(options.size[0]/stepSize0),\
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int(options.size[1]/stepSize),\
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max(int(options.size[2]/stepSize),1)
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print 'resolution of ang file', angRes
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if hexagonal:
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NpointsSlice = angRes[0]//2*(angRes[1]-1)+(angRes[0]-angRes[0]//2)*angRes[1]
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else:
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NpointsSlice = angRes[0]*angRes[1]
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print NpointsSlice
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z = numpy.array(options.normal,dtype='float')
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z = z/numpy.linalg.norm(z)
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x = numpy.array(options.up,dtype='float')
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x = x/numpy.linalg.norm(x)
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y = numpy.cross(z,x)
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x = numpy.cross(y,z)
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x = x/numpy.linalg.norm(x)
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print 'x unit vector', x, 'with norm ', numpy.linalg.norm(x)
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print 'y unit vector', y, 'with norm ', numpy.linalg.norm(y)
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print 'z unit vector', z, 'with norm ', numpy.linalg.norm(z)
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Favg = damask.core.math.tensorAvg(values['tensor']['%s'%(options.defgrad)].\
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reshape(resolution[0],resolution[1],resolution[2],3,3))
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coordTransform = numpy.array([x,y,z])
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print 'rotation matrix', coordTransform
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Favg = damask.core.math.tensorAvg(values['tensor']['%s'%(options.defgrad)].reshape(resolution[0],resolution[1],resolution[2],3,3))
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mySlice = numpy.zeros(NpointsSlice*3)
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eulerangles = values['vector']['%s'%options.eulerangles].reshape([3,N],order='F')
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for i in xrange(int(options.res[2])):
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offset = ((dimension - options.size)/2.0 + (dimension/angRes)/2.0)/options.res
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print 'offset', offset
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# 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]]
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for i in xrange(angRes[2]):
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idx = 0
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shift = 0
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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]]
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for j in xrange(res0):
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for j in xrange(angRes[0]):
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if hexagonal:
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res1=int(options.res[1])-j%2
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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]]
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res1=angRes[1]-j%2
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#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]]
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myOffset = offset +float(j%2)* numpy.array([0.0,0.5*stepSize,0.0],dtype='float')
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else:
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res1=int(options.res[1])
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res1=angRes[1]
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myOffset = offset
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for k in xrange(res1):
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mySlice[idx*3:idx*3+3] = numpy.dot(numpy.array([x,y,z],dtype='float'),
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numpy.array([j,k,i],dtype='float'))/[float(res0),float(options.res[0]),float(options.res[2])]*[dimension[0],dimension[1],dimension[2]]\
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+ myOffset
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mySlice[idx*3:idx*3+3] = numpy.dot(coordTransform,[j*stepSize0,k*stepSize,i*stepSize]+myOffset)
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#print mySlice[idx*3:idx*3+3]
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idx+=1
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mySlice = mySlice.reshape([3,NpointsSlice],order='F')
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indices=damask.core.math.math_nearestNeighborSearch(3,Favg,numpy.array(
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dimension,dtype='float'),NpointsSlice,N,mySlice,values['vector']['%s'%options.coords].reshape([3,N],order='F'))/27
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fileOut=open(os.path.join(os.path.dirname(name),os.path.splitext(os.path.basename(name))[0]+'_%s.ang'%i),'w')
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for line in getHeader(res0,res1,1.0):
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fileOut=open(os.path.join(os.path.dirname(name),os.path.splitext(os.path.basename(name))[0]+'_%s.ang'%(angRes[2]-i-1)),'w')
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for line in getHeader(angRes[0],angRes[1],angRes[2]):
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fileOut.write(line + '\n')
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# write data
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