223 lines
10 KiB
Python
Executable File
223 lines
10 KiB
Python
Executable File
#!/usr/bin/env python2
|
|
# -*- coding: UTF-8 no BOM -*-
|
|
|
|
import os,sys,math
|
|
import numpy as np
|
|
import scipy.ndimage
|
|
from optparse import OptionParser
|
|
import damask
|
|
|
|
scriptName = os.path.splitext(os.path.basename(__file__))[0]
|
|
scriptID = ' '.join([scriptName,damask.version])
|
|
|
|
|
|
#--------------------------------------------------------------------------------------------------
|
|
def cell2node(cellData,grid):
|
|
|
|
nodeData = 0.0
|
|
datalen = np.array(cellData.shape[3:]).prod()
|
|
|
|
for i in xrange(datalen):
|
|
node = scipy.ndimage.convolve(cellData.reshape(tuple(grid)+(datalen,))[...,i],
|
|
np.ones((2,2,2))/8., # 2x2x2 neighborhood of cells
|
|
mode = 'wrap',
|
|
origin = -1, # offset to have cell origin as center
|
|
) # now averaged at cell origins
|
|
node = np.append(node,node[np.newaxis,0,:,:,...],axis=0) # wrap along z
|
|
node = np.append(node,node[:,0,np.newaxis,:,...],axis=1) # wrap along y
|
|
node = np.append(node,node[:,:,0,np.newaxis,...],axis=2) # wrap along x
|
|
|
|
nodeData = node[...,np.newaxis] if i==0 else np.concatenate((nodeData,node[...,np.newaxis]),axis=-1)
|
|
|
|
return nodeData
|
|
|
|
#--------------------------------------------------------------------------------------------------
|
|
def displacementAvgFFT(F,grid,size,nodal=False,transformed=False):
|
|
"""calculate average cell center (or nodal) displacement for deformation gradient field specified in each grid cell"""
|
|
if nodal:
|
|
x, y, z = np.meshgrid(np.linspace(0,size[0],1+grid[0]),
|
|
np.linspace(0,size[1],1+grid[1]),
|
|
np.linspace(0,size[2],1+grid[2]),
|
|
indexing = 'ij')
|
|
else:
|
|
x, y, z = np.meshgrid(np.linspace(0,size[0],grid[0],endpoint=False),
|
|
np.linspace(0,size[1],grid[1],endpoint=False),
|
|
np.linspace(0,size[2],grid[2],endpoint=False),
|
|
indexing = 'ij')
|
|
|
|
origCoords = np.concatenate((z[:,:,:,None],y[:,:,:,None],x[:,:,:,None]),axis = 3)
|
|
|
|
F_fourier = F if transformed else np.fft.rfftn(F,axes=(0,1,2)) # transform or use provided data
|
|
Favg = np.real(F_fourier[0,0,0,:,:])/grid.prod() # take zero freq for average
|
|
avgDisplacement = np.einsum('ml,ijkl->ijkm',Favg-np.eye(3),origCoords) # dX = Favg.X
|
|
|
|
return avgDisplacement
|
|
|
|
#--------------------------------------------------------------------------------------------------
|
|
def displacementFluctFFT(F,grid,size,nodal=False,transformed=False):
|
|
"""calculate cell center (or nodal) displacement for deformation gradient field specified in each grid cell"""
|
|
integrator = 0.5j * size / math.pi
|
|
|
|
kk, kj, ki = np.meshgrid(np.where(np.arange(grid[2])>grid[2]//2,np.arange(grid[2])-grid[2],np.arange(grid[2])),
|
|
np.where(np.arange(grid[1])>grid[1]//2,np.arange(grid[1])-grid[1],np.arange(grid[1])),
|
|
np.arange(grid[0]//2+1),
|
|
indexing = 'ij')
|
|
k_s = np.concatenate((ki[:,:,:,None],kj[:,:,:,None],kk[:,:,:,None]),axis = 3)
|
|
k_sSquared = np.einsum('...l,...l',k_s,k_s)
|
|
k_sSquared[0,0,0] = 1.0 # ignore global average frequency
|
|
|
|
#--------------------------------------------------------------------------------------------------
|
|
# integration in Fourier space
|
|
|
|
displacement_fourier = -np.einsum('ijkml,ijkl,l->ijkm',
|
|
F if transformed else np.fft.rfftn(F,axes=(0,1,2)),
|
|
k_s,
|
|
integrator,
|
|
) / k_sSquared[...,np.newaxis]
|
|
|
|
#--------------------------------------------------------------------------------------------------
|
|
# backtransformation to real space
|
|
|
|
displacement = np.fft.irfftn(displacement_fourier,grid,axes=(0,1,2))
|
|
|
|
return cell2node(displacement,grid) if nodal else displacement
|
|
|
|
|
|
# --------------------------------------------------------------------
|
|
# MAIN
|
|
# --------------------------------------------------------------------
|
|
|
|
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options file[s]', description = """
|
|
Add displacments resulting from deformation gradient field.
|
|
Operates on periodic three-dimensional x,y,z-ordered data sets.
|
|
Outputs at cell centers or cell nodes (into separate file).
|
|
|
|
""", version = scriptID)
|
|
|
|
parser.add_option('-f',
|
|
'--defgrad',
|
|
dest = 'defgrad',
|
|
metavar = 'string',
|
|
help = 'column label of deformation gradient [%default]')
|
|
parser.add_option('-p',
|
|
'--pos', '--position',
|
|
dest = 'pos',
|
|
metavar = 'string',
|
|
help = 'label of coordinates [%default]')
|
|
parser.add_option('--nodal',
|
|
dest = 'nodal',
|
|
action = 'store_true',
|
|
help = 'output nodal (instad of cell-centered) displacements')
|
|
|
|
parser.set_defaults(defgrad = 'f',
|
|
pos = 'pos',
|
|
nodal = False,
|
|
)
|
|
|
|
(options,filenames) = parser.parse_args()
|
|
|
|
# --- loop over input files -------------------------------------------------------------------------
|
|
|
|
if filenames == []: filenames = [None]
|
|
|
|
for name in filenames:
|
|
outname = (os.path.splitext(name)[0] +
|
|
'_nodal' +
|
|
os.path.splitext(name)[1]) if (options.nodal and name) else None
|
|
try: table = damask.ASCIItable(name = name,
|
|
outname = outname,
|
|
buffered = False)
|
|
except: continue
|
|
damask.util.report(scriptName,'{}{}'.format(name,' --> {}'.format(outname) if outname else ''))
|
|
|
|
# ------------------------------------------ read header ------------------------------------------
|
|
|
|
table.head_read()
|
|
|
|
# ------------------------------------------ sanity checks ----------------------------------------
|
|
|
|
errors = []
|
|
remarks = []
|
|
|
|
if table.label_dimension(options.defgrad) != 9:
|
|
errors.append('deformation gradient "{}" is not a 3x3 tensor.'.format(options.defgrad))
|
|
|
|
coordDim = table.label_dimension(options.pos)
|
|
if not 3 >= coordDim >= 1:
|
|
errors.append('coordinates "{}" need to have one, two, or three dimensions.'.format(options.pos))
|
|
elif coordDim < 3:
|
|
remarks.append('appending {} dimension{} to coordinates "{}"...'.format(3-coordDim,
|
|
's' if coordDim < 2 else '',
|
|
options.pos))
|
|
|
|
if remarks != []: damask.util.croak(remarks)
|
|
if errors != []:
|
|
damask.util.croak(errors)
|
|
table.close(dismiss=True)
|
|
continue
|
|
|
|
# --------------- figure out size and grid ---------------------------------------------------------
|
|
|
|
table.data_readArray([options.defgrad,options.pos])
|
|
table.data_rewind()
|
|
|
|
if len(table.data.shape) < 2: table.data.shape += (1,) # expand to 2D shape
|
|
if table.data[:,9:].shape[1] < 3:
|
|
table.data = np.hstack((table.data,
|
|
np.zeros((table.data.shape[0],
|
|
3-table.data[:,9:].shape[1]),dtype='f'))) # fill coords up to 3D with zeros
|
|
|
|
coords = [np.unique(table.data[:,9+i]) for i in xrange(3)]
|
|
mincorner = np.array(map(min,coords))
|
|
maxcorner = np.array(map(max,coords))
|
|
grid = np.array(map(len,coords),'i')
|
|
size = grid/np.maximum(np.ones(3,'d'), grid-1.0) * (maxcorner-mincorner) # size from edge to edge = dim * n/(n-1)
|
|
size = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1])) # spacing for grid==1 set to smallest among other spacings
|
|
|
|
N = grid.prod()
|
|
|
|
if N != len(table.data): errors.append('data count {} does not match grid {}x{}x{}.'.format(N,*grid))
|
|
if errors != []:
|
|
damask.util.croak(errors)
|
|
table.close(dismiss = True)
|
|
continue
|
|
|
|
# ------------------------------------------ process data ------------------------------------------
|
|
|
|
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...
|
|
|
|
displacement = displacementFluctFFT(F_fourier,grid,size,options.nodal,transformed=True)
|
|
avgDisplacement = displacementAvgFFT (F_fourier,grid,size,options.nodal,transformed=True)
|
|
|
|
# ------------------------------------------ assemble header ---------------------------------------
|
|
|
|
if options.nodal:
|
|
table.info_clear()
|
|
table.labels_clear()
|
|
|
|
table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
|
|
table.labels_append((['{}_pos' .format(i+1) for i in xrange(3)] if options.nodal else []) +
|
|
['{}_avg({}).{}' .format(i+1,options.defgrad,options.pos) for i in xrange(3)] +
|
|
['{}_fluct({}).{}'.format(i+1,options.defgrad,options.pos) for i in xrange(3)] )
|
|
table.head_write()
|
|
|
|
# ------------------------------------------ output data -------------------------------------------
|
|
|
|
zrange = np.linspace(0,size[2],1+grid[2]) if options.nodal else xrange(grid[2])
|
|
yrange = np.linspace(0,size[1],1+grid[1]) if options.nodal else xrange(grid[1])
|
|
xrange = np.linspace(0,size[0],1+grid[0]) if options.nodal else xrange(grid[0])
|
|
|
|
for i,z in enumerate(zrange):
|
|
for j,y in enumerate(yrange):
|
|
for k,x in enumerate(xrange):
|
|
if options.nodal: table.data_clear()
|
|
else: table.data_read()
|
|
table.data_append([x,y,z] if options.nodal else [])
|
|
table.data_append(list(avgDisplacement[i,j,k,:]))
|
|
table.data_append(list( displacement[i,j,k,:]))
|
|
table.data_write()
|
|
|
|
# ------------------------------------------ output finalization -----------------------------------
|
|
|
|
table.close() # close ASCII tables
|