using central functionality
This commit is contained in:
Martin Diehl
parent
e006e0ebec
commit
9ad8743396
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@ -2,10 +2,10 @@
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import os
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import os
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import sys
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import sys
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from io import StringIO
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from optparse import OptionParser
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from optparse import OptionParser
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import numpy as np
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import numpy as np
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import scipy.ndimage
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import damask
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import damask
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@ -14,79 +14,6 @@ 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 range(datalen):
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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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) # 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[2],1+grid[2]),
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np.linspace(0,size[1],1+grid[1]),
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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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delta = size/grid*0.5
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x, y, z = np.meshgrid(np.linspace(delta[2],size[2]-delta[2],grid[2]),
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np.linspace(delta[1],size[1]-delta[1],grid[1]),
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np.linspace(delta[0],size[0]-delta[0],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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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 / np.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[::-1],axes=(0,1,2))
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return cell2node(displacement,grid) if nodal else displacement
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# --------------------------------------------------------------------
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# --------------------------------------------------------------------
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# MAIN
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# MAIN
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# --------------------------------------------------------------------
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# --------------------------------------------------------------------
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@ -100,7 +27,7 @@ Outputs at cell centers or cell nodes (into separate file).
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parser.add_option('-f',
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parser.add_option('-f',
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'--defgrad',
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'--defgrad',
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dest = 'defgrad',
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dest = 'f',
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metavar = 'string',
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metavar = 'string',
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help = 'label of deformation gradient [%default]')
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help = 'label of deformation gradient [%default]')
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parser.add_option('-p',
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parser.add_option('-p',
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@ -113,108 +40,35 @@ parser.add_option('--nodal',
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action = 'store_true',
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action = 'store_true',
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help = 'output nodal (instead of cell-centered) displacements')
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help = 'output nodal (instead of cell-centered) displacements')
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parser.set_defaults(defgrad = 'f',
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parser.set_defaults(f = 'f',
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pos = 'pos',
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pos = 'pos',
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)
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)
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(options,filenames) = parser.parse_args()
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(options,filenames) = parser.parse_args()
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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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for name in filenames:
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outname = (os.path.splitext(name)[0] +
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damask.util.report(scriptName,name)
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'_nodal' +
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os.path.splitext(name)[1]) if (options.nodal and name) else None
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try: table = damask.ASCIItable(name = name,
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outname = outname,
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buffered = False)
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except: continue
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damask.util.report(scriptName,'{}{}'.format(name if name else '',
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' --> {}'.format(outname) if outname else ''))
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# ------------------------------------------ read header ------------------------------------------
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table = damask.Table.from_ASCII(StringIO(''.join(sys.stdin.read())) if name is None else name)
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grid,size = damask.util.coordGridAndSize(table.get_array(options.pos))
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table.head_read()
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F = table.get_array(options.f).reshape(np.append(grid[::-1],(3,3)))
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# ------------------------------------------ sanity checks ----------------------------------------
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if options.nodal:
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table = damask.Table(damask.grid_filters.coord0_node(grid[::-1],size[::-1]).reshape((-1,3)),
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errors = []
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{'pos':(3,)})
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remarks = []
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table.add_array('avg({}).{}'.format(options.f,options.pos),
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damask.grid_filters.displacement_avg_node(size[::-1],F).reshape((-1,3)),
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if table.label_dimension(options.defgrad) != 9:
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scriptID+' '+' '.join(sys.argv[1:]))
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errors.append('deformation gradient "{}" is not a 3x3 tensor.'.format(options.defgrad))
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table.add_array('fluct({}).{}'.format(options.f,options.pos),
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damask.grid_filters.displacement_fluct_node(size[::-1],F).reshape((-1,3)),
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coordDim = table.label_dimension(options.pos)
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scriptID+' '+' '.join(sys.argv[1:]))
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if not 3 >= coordDim >= 1:
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table.to_ASCII(sys.stdout if name is None else os.path.splitext(name)[0]+'_nodal.txt')
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errors.append('coordinates "{}" need to have one, two, or three dimensions.'.format(options.pos))
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else:
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elif coordDim < 3:
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table.add_array('avg({}).{}'.format(options.f,options.pos),
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remarks.append('appending {} dimension{} to coordinates "{}"...'.format(3-coordDim,
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damask.grid_filters.displacement_avg_cell(size[::-1],F).reshape((-1,3)),
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's' if coordDim < 2 else '',
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scriptID+' '+' '.join(sys.argv[1:]))
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options.pos))
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table.add_array('fluct({}).{}'.format(options.f,options.pos),
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damask.grid_filters.displacement_fluct_cell(size[::-1],F).reshape((-1,3)),
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if remarks != []: damask.util.croak(remarks)
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scriptID+' '+' '.join(sys.argv[1:]))
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if errors != []:
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damask.util.croak(errors)
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table.to_ASCII(sys.stdout if name is None else name)
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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([options.defgrad,options.pos])
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table.data_rewind()
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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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grid,size = damask.util.coordGridAndSize(table.data[:,9:12])
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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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# ------------------------------------------ process data ------------------------------------------
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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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fluctDisplacement = displacementFluctFFT(F_fourier,grid,size,options.nodal,transformed=True)
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avgDisplacement = displacementAvgFFT (F_fourier,grid,size,options.nodal,transformed=True)
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# ------------------------------------------ assemble header ---------------------------------------
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if options.nodal:
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table.info_clear()
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table.labels_clear()
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table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
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table.labels_append((['{}_pos' .format(i+1) for i in range(3)] if options.nodal else []) +
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['{}_avg({}).{}' .format(i+1,options.defgrad,options.pos) for i in range(3)] +
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['{}_fluct({}).{}'.format(i+1,options.defgrad,options.pos) for i in range(3)] )
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table.head_write()
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# ------------------------------------------ output data -------------------------------------------
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Zrange = np.linspace(0,size[2],1+grid[2]) if options.nodal else range(grid[2])
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Yrange = np.linspace(0,size[1],1+grid[1]) if options.nodal else range(grid[1])
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Xrange = np.linspace(0,size[0],1+grid[0]) if options.nodal else range(grid[0])
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for i,z in enumerate(Zrange):
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for j,y in enumerate(Yrange):
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for k,x in enumerate(Xrange):
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if options.nodal: table.data_clear()
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else: table.data_read()
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table.data_append([x,y,z] if options.nodal else [])
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table.data_append(list( avgDisplacement[i,j,k,:]))
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table.data_append(list(fluctDisplacement[i,j,k,:]))
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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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@ -102,14 +102,21 @@ def displacement_fluct_node(size,F):
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def displacement_avg_node(size,F):
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def displacement_avg_node(size,F):
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F_avg = np.average(F,axis=(0,1,2))
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F_avg = np.average(F,axis=(0,1,2))
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return np.einsum('ml,ijkl->ijkm',F_avg-np.eye(3),coord0_node(F.shape[0:3],size))
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return np.einsum('ml,ijkl->ijkm',F_avg-np.eye(3),coord0_node(F.shape[:3],size))
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def cell_2_node(cell_data):
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def cell_2_node(cell_data):
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"""Interpolate cell data to nodal data."""
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"""Interpolate cell data to nodal data."""
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n = ( cell_data + np.roll(cell_data,1,(0,1,2))
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n = ( cell_data + np.roll(cell_data,1,(0,1,2))
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+ np.roll(cell_data,1,(0,)) + np.roll(cell_data,1,(1,)) + np.roll(cell_data,1,(2,))
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+ np.roll(cell_data,1,(0,)) + np.roll(cell_data,1,(1,)) + np.roll(cell_data,1,(2,))
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+ np.roll(cell_data,1,(0,1)) + np.roll(cell_data,1,(1,2)) + np.roll(cell_data,1,(2,0))) *0.125
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+ np.roll(cell_data,1,(0,1)) + np.roll(cell_data,1,(1,2)) + np.roll(cell_data,1,(2,0)))*0.125
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return np.pad(n,((0,1),(0,1),(0,1))+((0,0),)*len(cell_data.shape[3:]),mode='wrap')
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return np.pad(n,((0,1),(0,1),(0,1))+((0,0),)*len(cell_data.shape[3:]),mode='wrap')
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def node_2_cell(node_data):
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"""Interpolate nodal data to cell data."""
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c = ( node_data + np.roll(node_data,1,(0,1,2))
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+ np.roll(node_data,1,(0,)) + np.roll(node_data,1,(1,)) + np.roll(node_data,1,(2,))
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+ np.roll(node_data,1,(0,1)) + np.roll(node_data,1,(1,2)) + np.roll(node_data,1,(2,0)))*0.125
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return c[:-1,:-1,:-1]
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