not needed (Philip has different names)
This commit is contained in:
Martin Diehl
parent
573d10f1e1
commit
6aa6b418ea
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#!/usr/bin/env python
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# -*- coding: UTF-8 no BOM -*-
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import os,sys,math
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import numpy as np
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from optparse import OptionParser
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import damask
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scriptName = os.path.splitext(os.path.basename(__file__))[0]
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scriptID = ' '.join([scriptName,damask.version])
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#--------------------------------------------------------------------------------------------------
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def deformedCoordsFFT(F,undeformed=False):
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wgt = 1.0/grid.prod()
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integrator = np.array([0.+1.j,0.+1.j,0.+1.j],'c16') * size/ 2.0 / math.pi
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step = size/grid
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F_fourier = np.fft.rfftn(F,axes=(0,1,2))
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coords_fourier = np.zeros(F_fourier.shape[0:4],'c16')
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if undeformed:
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Favg=np.eye(3)
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else:
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Favg=np.real(F_fourier[0,0,0,:,:])*wgt
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#--------------------------------------------------------------------------------------------------
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# integration in Fourier space
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k_s = np.zeros([3],'i')
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for i in xrange(grid[2]):
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k_s[2] = i
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if(i > grid[2]//2 ): k_s[2] = k_s[2] - grid[2]
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for j in xrange(grid[1]):
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k_s[1] = j
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if(j > grid[1]//2 ): k_s[1] = k_s[1] - grid[1]
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for k in xrange(grid[0]//2+1):
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k_s[0] = k
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for m in xrange(3):
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coords_fourier[i,j,k,m] = sum(F_fourier[i,j,k,m,0:3]*k_s*integrator)
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if (any(k_s != 0)):
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coords_fourier[i,j,k,0:3] /= -sum(k_s*k_s)
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#--------------------------------------------------------------------------------------------------
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# add average to scaled fluctuation and put (0,0,0) on (0,0,0)
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coords = np.fft.irfftn(coords_fourier,F.shape[0:3],axes=(0,1,2))
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offset_coords = np.dot(F[0,0,0,:,:],step/2.0) - scaling*coords[0,0,0,0:3]
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for z in xrange(grid[2]):
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for y in xrange(grid[1]):
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for x in xrange(grid[0]):
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coords[z,y,x,0:3] = scaling*coords[z,y,x,0:3] \
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+ offset_coords \
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+ np.dot(Favg,step*np.array([x,y,z]))
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return coords
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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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parser = OptionParser(option_class=damask.extendableOption, usage='%prog options file[s]', description = """
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Add deformed configuration of given initial coordinates.
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Operates on periodic three-dimensional x,y,z-ordered data sets.
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""", version = scriptID)
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parser.add_option('-f', '--defgrad',dest='defgrad', metavar = 'string',
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help='heading of deformation gradient columns [%default]')
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parser.add_option('--reference', dest='undeformed', action='store_true',
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help='map results to reference (undeformed) average configuration [%default]')
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parser.add_option('--scaling', dest='scaling', action='extend', metavar = '<float LIST>',
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help='scaling of fluctuation')
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parser.add_option('-u', '--unitlength', dest='unitlength', type='float', metavar = 'float',
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help='set unit length for 2D model [%default]')
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parser.add_option('--coordinates', dest='coords', metavar='string',
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help='column heading for coordinates [%default]')
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parser.set_defaults(defgrad = 'f')
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parser.set_defaults(coords = 'ipinitialcoord')
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parser.set_defaults(scaling = [])
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parser.set_defaults(undeformed = False)
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parser.set_defaults(unitlength = 0.0)
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(options,filenames) = parser.parse_args()
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options.scaling += [1.0 for i in xrange(max(0,3-len(options.scaling)))]
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scaling = map(float, options.scaling)
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# --- loop over input files -------------------------------------------------------------------------
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if filenames == []: filenames = [None]
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for name in filenames:
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try:
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table = damask.ASCIItable(name = name,
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buffered = False)
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except: continue
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damask.util.report(scriptName,name)
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# ------------------------------------------ read header ------------------------------------------
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table.head_read()
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# ------------------------------------------ sanity checks ----------------------------------------
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errors = []
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remarks = []
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if table.label_dimension(options.coords) != 3: errors.append('coordinates {} are not a vector.'.format(options.coords))
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else: colCoord = table.label_index(options.coords)
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if table.label_dimension(options.defgrad) != 9: errors.append('deformation gradient {} is not a tensor.'.format(options.defgrad))
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else: colF = table.label_index(options.defgrad)
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if remarks != []: damask.util.croak(remarks)
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if errors != []:
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damask.util.croak(errors)
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table.close(dismiss = True)
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continue
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# --------------- figure out size and grid ---------------------------------------------------------
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table.data_readArray()
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coords = [np.unique(table.data[:,colCoord+i]) for i in xrange(3)]
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mincorner = np.array(map(min,coords))
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maxcorner = np.array(map(max,coords))
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grid = np.array(map(len,coords),'i')
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size = grid/np.maximum(np.ones(3,'d'), grid-1.0) * (maxcorner-mincorner) # size from edge to edge = dim * n/(n-1)
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size = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1])) # spacing for grid==1 set to smallest among other spacings
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N = grid.prod()
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if N != len(table.data): errors.append('data count {} does not match grid {}x{}x{}.'.format(N,*grid))
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if errors != []:
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damask.util.croak(errors)
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table.close(dismiss = True)
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continue
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# ------------------------------------------ assemble header ---------------------------------------
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table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
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for coord in xrange(3):
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label = '{}_{}_{}'.format(coord+1,options.defgrad,options.coords)
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if np.any(scaling) != 1.0: label+='_{}_{}_{}'.format(scaling)
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if options.undeformed: label+='_undeformed'
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table.labels_append([label]) # extend ASCII header with new labels
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table.head_write()
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# ------------------------------------------ read deformation gradient field -----------------------
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centroids = deformedCoordsFFT(table.data[:,colF:colF+9].reshape(grid[2],grid[1],grid[0],3,3),
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options.undeformed)
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# ------------------------------------------ process data ------------------------------------------
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table.data_rewind()
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for z in xrange(grid[2]):
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for y in xrange(grid[1]):
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for x in xrange(grid[0]):
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table.data_read()
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table.data_append(list(centroids[z,y,x,:]))
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table.data_write()
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# ------------------------------------------ output finalization -----------------------------------
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table.close() # close ASCII tables
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#!/usr/bin/env python
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# -*- coding: UTF-8 no BOM -*-
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import os,sys,math,string
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import numpy as np
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from optparse import OptionParser
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import damask
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scriptID = string.replace('$Id: addDeformedConfiguration.py 4500 2015-09-24 09:24:42Z MPIE\m.diehl $','\n','\\n')
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scriptName = os.path.splitext(scriptID.split()[1])[0]
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#--------------------------------------------------------------------------------------------------
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def nodesAroundCentres(gDim,Favg,centres):
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#--------------------------------------------------------------------------------------------------
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neighbor = np.array([0, 0, 0,
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1, 0, 0,
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1, 1, 0,
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0, 1, 0,
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0, 0, 1,
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1, 0, 1,
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1, 1, 1,
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0, 1, 1]).reshape(8,3)
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#--------------------------------------------------------------------------------------------------
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# building wrappedCentres = centroids + ghosts
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diag = np.ones([3])
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wrappedCentres = np.zeros([3,grid[0]+2,grid[1]+2,grid[2]+2])
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wrappedCentres[0:3,1:grid[0]+1,1:grid[1]+1,1:grid[2]+1] = centres
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for k in xrange(grid[2]+2):
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for j in xrange(grid[1]+2):
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for i in xrange(grid[0]+2):
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if (k in [0,grid[2]+1] or j in [0,grid[1]+1] or i in[0,grid[0]+1]):
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me = np.array([i,j,k],'i') # me on skin
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shift = abs(grid+np.ones([3],'i')-2*me)/(grid+np.ones([3],'i'))*\
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np.sign(grid+np.ones([3],'i')-2*me)
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lookup = np.array(me-diag+shift*grid,'i')
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wrappedCentres[0:3,i, j, k] = \
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centres[0:3,lookup[0],lookup[1],lookup[2]] - np.dot(Favg, shift*gDim)
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#--------------------------------------------------------------------------------------------------
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# averaging
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nodes = np.zeros([3,grid[0]+1,grid[1]+1,grid[2]+1])
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for k in xrange(grid[2]+1):
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for j in xrange(grid[1]+1):
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for i in xrange(grid[0]+1):
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for n in xrange(8):
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nodes[0:3,i,j,k] = \
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nodes[0:3,i,j,k] + wrappedCentres[0:3,i+neighbor[n,0],j+neighbor[n,1],k+neighbor[n,2] ]
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return nodes/8.0
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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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parser = OptionParser(option_class=damask.extendableOption, usage='%prog options file[s]', description = """
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Add deformed configuration of given initial coordinates.
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Operates on periodic three-dimensional x,y,z-ordered data sets.
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""", version = scriptID)
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parser.add_option('-f', '--defgrad',dest='defgrad', metavar = 'string',
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help='heading of deformation gradient columns [%default]')
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parser.add_option('-u', '--unitlength', dest='unitlength', type='float', metavar = 'float',
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help='set unit length for 2D model [%default]')
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parser.set_defaults(deformed = 'ipinitialcoord')
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parser.set_defaults(unitlength = 0.0)
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(options,filenames) = parser.parse_args()
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options.scaling += [1.0 for i in xrange(max(0,3-len(options.scaling)))]
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scaling = map(float, options.scaling)
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# --- loop over input files -------------------------------------------------------------------------
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if filenames == []: filenames = [None]
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for name in filenames:
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try:
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table = damask.ASCIItable(name = name,
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buffered = False)
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except: continue
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damask.util.report(scriptName,name)
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# ------------------------------------------ read header ------------------------------------------
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table.head_read()
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# ------------------------------------------ sanity checks ----------------------------------------
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errors = []
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remarks = []
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if table.label_dimension(options.coords) != 3: errors.append('coordinates {} are not a vector.'.format(options.coords))
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else: colCoord = table.label_index(options.coords)
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if table.label_dimension(options.defgrad) != 9: errors.append('deformation gradient {} is not a tensor.'.format(options.defgrad))
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else: colF = table.label_index(options.defgrad)
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if remarks != []: damask.util.croak(remarks)
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if errors != []:
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damask.util.croak(errors)
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table.close(dismiss = True)
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continue
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# --------------- figure out size and grid ---------------------------------------------------------
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table.data_readArray()
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coords = [np.unique(table.data[:,colCoord+i]) for i in xrange(3)]
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mincorner = np.array(map(min,coords))
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maxcorner = np.array(map(max,coords))
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grid = np.array(map(len,coords),'i')
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size = grid/np.maximum(np.ones(3,'d'), grid-1.0) * (maxcorner-mincorner) # size from edge to edge = dim * n/(n-1)
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size = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1])) # spacing for grid==1 equal to smallest among other spacings
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N = grid.prod()
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if N != len(table.data): errors.append('data count {} does not match grid {}x{}x{}.'.format(N,*grid))
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if errors != []:
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damask.util.croak(errors)
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table.close(dismiss = True)
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continue
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# ------------------------------------------ assemble header ---------------------------------------
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table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
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for coord in xrange(3):
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label = '{}_{}_{}'.format(coord+1,options.defgrad,options.coords)
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if np.any(scaling) != 1.0: label+='_{}_{}_{}'.format(scaling)
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if options.undeformed: label+='_undeformed'
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table.labels_append([label]) # extend ASCII header with new labels
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table.head_write()
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# ------------------------------------------ read deformation gradient field -----------------------
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centroids,Favg = deformedCoordsFFT(table.data[:,colF:colF+9].reshape(grid[0],grid[1],grid[2],3,3))
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# ------------------------------------------ process data ------------------------------------------
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table.data_rewind()
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idx = 0
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outputAlive = True
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while outputAlive and table.data_read(): # read next data line of ASCII table
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(x,y,z) = damask.util.gridLocation(idx,grid) # figure out (x,y,z) position from line count
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idx += 1
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table.data_append(list(centroids[z,y,x,:]))
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outputAlive = table.data_write()
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# ------------------------------------------ output finalization -----------------------------------
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table.close() # close ASCII tables
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