fully adopted code from addDisplacement
This commit is contained in:
Martin Diehl
parent
c949f407e5
commit
745c012088
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@ -1,9 +1,9 @@
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#!/usr/bin/env python2
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# -*- coding: UTF-8 no BOM -*-
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import os,sys
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import numpy as np
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import os
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import math
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import numpy as np
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import scipy.ndimage
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from optparse import OptionParser
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import damask
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@ -18,7 +18,7 @@ def cell2node(cellData,grid):
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datalen = np.array(cellData.shape[3:]).prod()
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for i in xrange(datalen):
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node = scipy.ndimage.convolve(cellData.reshape(tuple(grid)+(datalen,))[...,i],
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node = scipy.ndimage.convolve(cellData.reshape(tuple(grid[::-1])+(datalen,))[...,i],
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np.ones((2,2,2))/8., # 2x2x2 neighborhood of cells
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mode = 'wrap',
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origin = -1, # offset to have cell origin as center
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@ -32,26 +32,26 @@ def cell2node(cellData,grid):
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return nodeData
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#--------------------------------------------------------------------------------------------------
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def displacementAvgFFT(F,grid,size,nodal=False,transformed=False):
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"""calculate average cell center (or nodal) displacement for deformation gradient field specified in each grid cell"""
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def deformationAvgFFT(F,grid,size,nodal=False,transformed=False):
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"""calculate average cell center (or nodal) deformation for deformation gradient field specified in each grid cell"""
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if nodal:
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x, y, z = np.meshgrid(np.linspace(0,size[0],1+grid[0]),
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x, y, z = np.meshgrid(np.linspace(0,size[2],1+grid[2]),
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np.linspace(0,size[1],1+grid[1]),
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np.linspace(0,size[2],1+grid[2]),
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np.linspace(0,size[0],1+grid[0]),
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indexing = 'ij')
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else:
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x, y, z = np.meshgrid(np.linspace(0,size[0],grid[0],endpoint=False),
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np.linspace(0,size[1],grid[1],endpoint=False),
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np.linspace(0,size[2],grid[2],endpoint=False),
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x, y, z = np.meshgrid(np.linspace(size[2]/grid[2]/2.,size[2]-size[2]/grid[2]/2.,grid[2]),
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np.linspace(size[1]/grid[1]/2.,size[1]-size[1]/grid[1]/2.,grid[1]),
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np.linspace(size[0]/grid[0]/2.,size[0]-size[0]/grid[0]/2.,grid[0]),
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indexing = 'ij')
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origCoords = np.concatenate((z[:,:,:,None],y[:,:,:,None],x[:,:,:,None]),axis = 3)
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F_fourier = F if transformed else np.fft.rfftn(F,axes=(0,1,2)) # transform or use provided data
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Favg = np.real(F_fourier[0,0,0,:,:])/grid.prod() # take zero freq for average
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avgDisplacement = np.einsum('ml,ijkl->ijkm',Favg-np.eye(3),origCoords) # dX = Favg.X
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avgDeformation = np.einsum('ml,ijkl->ijkm',Favg,origCoords) # dX = Favg.X
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return avgDisplacement
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return avgDeformation
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#--------------------------------------------------------------------------------------------------
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def displacementFluctFFT(F,grid,size,nodal=False,transformed=False):
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@ -69,7 +69,7 @@ def displacementFluctFFT(F,grid,size,nodal=False,transformed=False):
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#--------------------------------------------------------------------------------------------------
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# integration in Fourier space
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displacement_fourier = +np.einsum('ijkml,ijkl,l->ijkm',
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displacement_fourier = -np.einsum('ijkml,ijkl,l->ijkm',
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F if transformed else np.fft.rfftn(F,axes=(0,1,2)),
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k_s,
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integrator,
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@ -78,7 +78,7 @@ def displacementFluctFFT(F,grid,size,nodal=False,transformed=False):
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#--------------------------------------------------------------------------------------------------
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# backtransformation to real space
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displacement = np.fft.irfftn(displacement_fourier,grid,axes=(0,1,2))
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displacement = np.fft.irfftn(displacement_fourier,grid[::-1],axes=(0,1,2))
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return cell2node(displacement,grid) if nodal else displacement
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@ -137,7 +137,7 @@ def volumeMismatch(size,F,nodes):
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(compatible) cube and determinant of defgrad at the FP
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"""
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coords = np.empty([8,3])
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vMismatch = np.empty(grid)
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vMismatch = np.empty(grid[::-1])
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volInitial = size.prod()/grid.prod()
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#--------------------------------------------------------------------------------------------------
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@ -145,23 +145,22 @@ def volumeMismatch(size,F,nodes):
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for k in xrange(grid[2]):
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for j in xrange(grid[1]):
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for i in xrange(grid[0]):
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coords[0,0:3] = nodes[i, j, k ,0:3]
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coords[1,0:3] = nodes[i+1,j, k ,0:3]
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coords[2,0:3] = nodes[i+1,j+1,k ,0:3]
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coords[3,0:3] = nodes[i, j+1,k ,0:3]
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coords[4,0:3] = nodes[i, j, k+1,0:3]
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coords[5,0:3] = nodes[i+1,j, k+1,0:3]
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coords[6,0:3] = nodes[i+1,j+1,k+1,0:3]
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coords[7,0:3] = nodes[i, j+1,k+1,0:3]
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vMismatch[i,j,k] = \
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abs(volTetrahedron([coords[6,0:3],coords[0,0:3],coords[7,0:3],coords[3,0:3]])) \
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coords[0,0:3] = nodes[k, j, i ,0:3]
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coords[1,0:3] = nodes[k ,j, i+1,0:3]
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coords[2,0:3] = nodes[k ,j+1,i+1,0:3]
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coords[3,0:3] = nodes[k, j+1,i ,0:3]
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coords[4,0:3] = nodes[k+1,j, i ,0:3]
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coords[5,0:3] = nodes[k+1,j, i+1,0:3]
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coords[6,0:3] = nodes[k+1,j+1,i+1,0:3]
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coords[7,0:3] = nodes[k+1,j+1,i ,0:3]
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vMismatch[k,j,i] = \
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( abs(volTetrahedron([coords[6,0:3],coords[0,0:3],coords[7,0:3],coords[3,0:3]])) \
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+ abs(volTetrahedron([coords[6,0:3],coords[0,0:3],coords[7,0:3],coords[4,0:3]])) \
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+ abs(volTetrahedron([coords[6,0:3],coords[0,0:3],coords[2,0:3],coords[3,0:3]])) \
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+ abs(volTetrahedron([coords[6,0:3],coords[0,0:3],coords[2,0:3],coords[1,0:3]])) \
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+ abs(volTetrahedron([coords[6,0:3],coords[4,0:3],coords[1,0:3],coords[5,0:3]])) \
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+ abs(volTetrahedron([coords[6,0:3],coords[4,0:3],coords[1,0:3],coords[0,0:3]]))
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vMismatch[i,j,k] = vMismatch[i,j,k]/np.linalg.det(F[i,j,k,0:3,0:3])
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+ abs(volTetrahedron([coords[6,0:3],coords[4,0:3],coords[1,0:3],coords[0,0:3]]))) \
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/np.linalg.det(F[k,j,i,0:3,0:3])
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return vMismatch/volInitial
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@ -175,7 +174,7 @@ def shapeMismatch(size,F,nodes,centres):
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the initial volume element with the current deformation gradient
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"""
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coordsInitial = np.empty([8,3])
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sMismatch = np.empty(grid)
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sMismatch = np.empty(grid[::-1])
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#--------------------------------------------------------------------------------------------------
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# initial positions
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@ -194,15 +193,15 @@ def shapeMismatch(size,F,nodes,centres):
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for k in xrange(grid[2]):
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for j in xrange(grid[1]):
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for i in xrange(grid[0]):
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sMismatch[i,j,k] = \
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+ np.linalg.norm(nodes[i, j, k,0:3] - centres[i,j,k,0:3] - np.dot(F[i,j,k,:,:], coordsInitial[0,0:3]))\
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+ np.linalg.norm(nodes[i+1,j, k,0:3] - centres[i,j,k,0:3] - np.dot(F[i,j,k,:,:], coordsInitial[1,0:3]))\
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+ np.linalg.norm(nodes[i+1,j+1,k ,0:3] - centres[i,j,k,0:3] - np.dot(F[i,j,k,:,:], coordsInitial[2,0:3]))\
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+ np.linalg.norm(nodes[i, j+1,k ,0:3] - centres[i,j,k,0:3] - np.dot(F[i,j,k,:,:], coordsInitial[3,0:3]))\
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+ np.linalg.norm(nodes[i, j, k+1,0:3] - centres[i,j,k,0:3] - np.dot(F[i,j,k,:,:], coordsInitial[4,0:3]))\
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+ np.linalg.norm(nodes[i+1,j, k+1,0:3] - centres[i,j,k,0:3] - np.dot(F[i,j,k,:,:], coordsInitial[5,0:3]))\
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+ np.linalg.norm(nodes[i+1,j+1,k+1,0:3] - centres[i,j,k,0:3] - np.dot(F[i,j,k,:,:], coordsInitial[6,0:3]))\
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+ np.linalg.norm(nodes[i, j+1,k+1,0:3] - centres[i,j,k,0:3] - np.dot(F[i,j,k,:,:], coordsInitial[7,0:3]))
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sMismatch[k,j,i] = \
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+ np.linalg.norm(nodes[k, j, i ,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[0,0:3]))\
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+ np.linalg.norm(nodes[k, j, i+1,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[1,0:3]))\
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+ np.linalg.norm(nodes[k, j+1,i+1,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[2,0:3]))\
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+ np.linalg.norm(nodes[k, j+1,i ,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[3,0:3]))\
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+ np.linalg.norm(nodes[k+1,j, i ,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[4,0:3]))\
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+ np.linalg.norm(nodes[k+1,j, i+1,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[5,0:3]))\
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+ np.linalg.norm(nodes[k+1,j+1,i+1,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[6,0:3]))\
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+ np.linalg.norm(nodes[k+1,j+1,i ,0:3] - centres[k,j,i,0:3] - np.dot(F[k,j,i,:,:], coordsInitial[7,0:3]))
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return sMismatch
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@ -307,38 +306,32 @@ for name in filenames:
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# -----------------------------process data and assemble header -------------------------------------
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F_fourier = np.fft.rfftn(table.data[:,:9].reshape(grid[2],grid[1],grid[0],3,3),axes=(0,1,2)) # perform transform only once...
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nodes = np.vstack(np.meshgrid(np.linspace(0.0,size[0],grid[0]+1),
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np.linspace(0.0,size[1],grid[1]+1),
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np.linspace(0.0,size[2],grid[2]+1))).reshape([3,17,17,17]).T\
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+ displacementFluctFFT(F_fourier,grid,size,True,transformed=True)\
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+ displacementAvgFFT (F_fourier,grid,size,True,transformed=True)
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nodes = displacementFluctFFT(F_fourier,grid,size,True,transformed=True)\
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+ deformationAvgFFT (F_fourier,grid,size,True,transformed=True)
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if options.shape:
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table.labels_append(['shapeMismatch({})'.format(options.defgrad)])
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centres = np.vstack(np.meshgrid(np.linspace(size[0]/grid[0]*.5,size[0]-size[0]/grid[0]*.5,grid[0]),
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np.linspace(size[1]/grid[1]*.5,size[1]-size[1]/grid[1]*.5,grid[1]),
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np.linspace(size[2]/grid[2]*.5,size[2]-size[2]/grid[2]*.5,grid[2]))).reshape([3,16,16,16]).T\
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+ displacementFluctFFT(F_fourier,grid,size,False,transformed=True)\
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+ displacementAvgFFT (F_fourier,grid,size,False,transformed=True)
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centres = displacementFluctFFT(F_fourier,grid,size,False,transformed=True)\
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+ deformationAvgFFT (F_fourier,grid,size,False,transformed=True)
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if options.volume:
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table.labels_append(['volMismatch({})'.format(options.defgrad)])
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table.head_write()
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if options.shape: shapeMismatch = shapeMismatch( size,table.data[:,:9].reshape(grid[2],grid[1],grid[0],3,3),nodes,centres)
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if options.volume: volumeMismatch = volumeMismatch(size,table.data[:,:9].reshape(grid[2],grid[1],grid[0],3,3),nodes)
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if options.shape:
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shapeMismatch = shapeMismatch( size,table.data[:,:9].reshape(grid[2],grid[1],grid[0],3,3),nodes,centres)
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if options.volume:
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volumeMismatch = volumeMismatch(size,table.data[:,:9].reshape(grid[2],grid[1],grid[0],3,3),nodes)
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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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if options.shape: table.data_append( shapeMismatch[x,y,z])
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if options.volume: table.data_append(volumeMismatch[x,y,z])
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outputAlive = table.data_write()
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# ------------------------------------------ output data -------------------------------------------
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for i in xrange(grid[2]):
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for j in xrange(grid[1]):
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for k in xrange(grid[0]):
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table.data_read()
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if options.shape: table.data_append(shapeMismatch[i,j,k])
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if options.volume: table.data_append(volumeMismatch[i,j,k])
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table.data_write()
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# ------------------------------------------ output finalization -----------------------------------
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table.close()
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table.close() # close ASCII tables
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