trying to get the last things work without the core module
This commit is contained in:
Martin Diehl
parent
21cfe09412
commit
8307a4a9ab
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@ -3,12 +3,85 @@
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import os,sys
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import os,sys
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import numpy as np
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import numpy as np
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import math
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import scipy.ndimage
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from optparse import OptionParser
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from optparse import OptionParser
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import damask
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import damask
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scriptName = os.path.splitext(os.path.basename(__file__))[0]
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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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scriptID = ' '.join([scriptName,damask.version])
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#--------------------------------------------------------------------------------------------------
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def cell2node(cellData,grid):
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nodeData = 0.0
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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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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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) # now averaged at cell origins
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node = np.append(node,node[np.newaxis,0,:,:,...],axis=0) # wrap along z
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node = np.append(node,node[:,0,np.newaxis,:,...],axis=1) # wrap along y
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node = np.append(node,node[:,:,0,np.newaxis,...],axis=2) # wrap along x
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nodeData = node[...,np.newaxis] if i==0 else np.concatenate((nodeData,node[...,np.newaxis]),axis=-1)
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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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if nodal:
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x, y, z = np.meshgrid(np.linspace(0,size[0],1+grid[0]),
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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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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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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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return avgDisplacement
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#--------------------------------------------------------------------------------------------------
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def displacementFluctFFT(F,grid,size,nodal=False,transformed=False):
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"""calculate cell center (or nodal) displacement for deformation gradient field specified in each grid cell"""
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integrator = 0.5j * size / math.pi
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kk, kj, ki = np.meshgrid(np.where(np.arange(grid[2])>grid[2]//2,np.arange(grid[2])-grid[2],np.arange(grid[2])),
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np.where(np.arange(grid[1])>grid[1]//2,np.arange(grid[1])-grid[1],np.arange(grid[1])),
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np.arange(grid[0]//2+1),
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indexing = 'ij')
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k_s = np.concatenate((ki[:,:,:,None],kj[:,:,:,None],kk[:,:,:,None]),axis = 3)
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k_sSquared = np.einsum('...l,...l',k_s,k_s)
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k_sSquared[0,0,0] = 1.0 # ignore global average frequency
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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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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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) / k_sSquared[...,np.newaxis]
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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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return cell2node(displacement,grid) if nodal else displacement
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def volTetrahedron(coords):
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def volTetrahedron(coords):
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"""
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"""
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@ -188,13 +261,16 @@ for name in filenames:
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errors = []
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errors = []
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remarks = []
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remarks = []
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if table.label_dimension(options.pos) != 3:
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errors.append('coordinates "{}" are not a vector.'.format(options.pos))
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else: colCoord = table.label_index(options.pos)
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if table.label_dimension(options.defgrad) != 9:
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if table.label_dimension(options.defgrad) != 9:
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errors.append('deformation gradient "{}" is not a tensor.'.format(options.defgrad))
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errors.append('deformation gradient "{}" is not a 3x3 tensor.'.format(options.defgrad))
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else: colF = table.label_index(options.defgrad)
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coordDim = table.label_dimension(options.pos)
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if not 3 >= coordDim >= 1:
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errors.append('coordinates "{}" need to have one, two, or three dimensions.'.format(options.pos))
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elif coordDim < 3:
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remarks.append('appending {} dimension{} to coordinates "{}"...'.format(3-coordDim,
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's' if coordDim < 2 else '',
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options.pos))
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if remarks != []: damask.util.croak(remarks)
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if remarks != []: damask.util.croak(remarks)
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if errors != []:
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if errors != []:
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@ -202,52 +278,54 @@ for name in filenames:
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table.close(dismiss=True)
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table.close(dismiss=True)
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continue
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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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if options.shape: table.labels_append('shapeMismatch({})'.format(options.defgrad))
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if options.volume: table.labels_append('volMismatch({})'.format(options.defgrad))
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# --------------- figure out size and grid ---------------------------------------------------------
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# --------------- figure out size and grid ---------------------------------------------------------
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table.data_readArray()
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table.data_readArray([options.defgrad,options.pos])
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table.data_rewind()
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coords = [np.unique(table.data[:,colCoord+i]) for i in xrange(3)]
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if len(table.data.shape) < 2: table.data.shape += (1,) # expand to 2D shape
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if table.data[:,9:].shape[1] < 3:
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table.data = np.hstack((table.data,
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np.zeros((table.data.shape[0],
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3-table.data[:,9:].shape[1]),dtype='f'))) # fill coords up to 3D with zeros
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coords = [np.unique(table.data[:,9+i]) for i in xrange(3)]
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mincorner = np.array(map(min,coords))
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mincorner = np.array(map(min,coords))
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maxcorner = np.array(map(max,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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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 = 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])) # grid==1 spacing set to smallest among other ones
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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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N = grid.prod()
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# --------------- figure out columns to process ---------------------------------------------------
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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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key = '1_'+options.defgrad
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if errors != []:
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if table.label_index(key) == -1:
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damask.util.croak(errors)
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damask.util.croak('column "{}" not found...'.format(key))
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table.close(dismiss = True)
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continue
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continue
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else:
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column = table.label_index(key) # remember columns of requested data
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# ------------------------------------------ assemble header ---------------------------------------
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# -----------------------------process data and assemble header -------------------------------------
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if options.shape: table.labels_append(['shapeMismatch({})'.format(options.defgrad)])
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if options.volume: table.labels_append(['volMismatch({})'.format(options.defgrad)])
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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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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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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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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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# ------------------------------------------ read deformation gradient field -----------------------
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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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table.data_rewind()
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F = np.zeros(N*9,'d').reshape([3,3]+list(grid))
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idx = 0
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while table.data_read():
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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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F[0:3,0:3,x,y,z] = np.array(map(float,table.data[column:column+9]),'d').reshape(3,3)
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Favg = damask.core.math.tensorAvg(F)
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centres = damask.core.mesh.deformedCoordsFFT(size,F,Favg,[1.0,1.0,1.0])
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nodes = damask.core.mesh.nodesAroundCentres(size,Favg,centres)
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if options.shape: shapeMismatch = shapeMismatch( size,F,nodes,centres)
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if options.volume: volumeMismatch = volumeMismatch(size,F,nodes)
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# ------------------------------------------ process data ------------------------------------------
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# ------------------------------------------ process data ------------------------------------------
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table.data_rewind()
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table.data_rewind()
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@ -262,4 +340,5 @@ for name in filenames:
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# ------------------------------------------ output finalization -----------------------------------
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# ------------------------------------------ output finalization -----------------------------------
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table.close() # close ASCII tables
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table.close()
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