#!/usr/bin/env python
# -*- coding: UTF-8 no BOM -*-
import os,sys,string,math
import numpy as np
from optparse import OptionParser
import damask
scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
#--------------------------------------------------------------------------------------------------
def deformedCoordsFFT(F,undeformed=False):
#--------------------------------------------------------------------------------------------------
wgt = 1.0/grid.prod()
integrator = np.array([0.+1.j,0.+1.j,0.+1.j],'c16') * size/ 2.0 / math.pi
step = size/grid
F_fourier = np.fft.rfftn(F,axes=(0,1,2))
coords_fourier = np.zeros(F_fourier.shape[0:4],'c16')
if undeformed:
Favg=np.eye(3)
else:
Favg=np.real(F_fourier[0,0,0,:,:])*wgt
#--------------------------------------------------------------------------------------------------
# integration in Fourier space
k_s = np.zeros([3],'i')
for i in xrange(grid[2]):
k_s[2] = i
if(i > grid[2]//2 ): k_s[2] = k_s[2] - grid[2]
for j in xrange(grid[1]):
k_s[1] = j
if(j > grid[1]//2 ): k_s[1] = k_s[1] - grid[1]
for k in xrange(grid[0]//2+1):
k_s[0] = k
for m in xrange(3):
coords_fourier[i,j,k,m] = sum(F_fourier[i,j,k,m,0:3]*k_s*integrator)
if (any(k_s != 0)):
coords_fourier[i,j,k,0:3] /= -sum(k_s*k_s)
#--------------------------------------------------------------------------------------------------
# add average to scaled fluctuation and put (0,0,0) on (0,0,0)
coords = np.fft.irfftn(coords_fourier,F.shape[0:3],axes=(0,1,2))
offset_coords = np.dot(F[0,0,0,:,:],step/2.0) - scaling*coords[0,0,0,0:3]
for z in xrange(grid[2]):
for y in xrange(grid[1]):
for x in xrange(grid[0]):
coords[z,y,x,0:3] = scaling*coords[z,y,x,0:3] \
+ offset_coords \
+ np.dot(Favg,step*np.array([x,y,z]))
return coords
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options file[s]', description = """
Add deformed configuration of given initial coordinates.
Operates on periodic three-dimensional x,y,z-ordered data sets.
""", version = scriptID)
parser.add_option('-f', '--defgrad',dest='defgrad', metavar = 'string',
help='heading of deformation gradient columns [%default]')
parser.add_option('--reference', dest='undeformed', action='store_true',
help='map results to reference (undeformed) average configuration [%default]')
parser.add_option('--scaling', dest='scaling', action='extend', metavar = '<float LIST>',
help='scaling of fluctuation')
parser.add_option('-u', '--unitlength', dest='unitlength', type='float', metavar = 'float',
help='set unit length for 2D model [%default]')
parser.add_option('--coordinates', dest='coords', metavar='string',
help='column heading for coordinates [%default]')
parser.set_defaults(defgrad = 'f')
parser.set_defaults(coords = 'ipinitialcoord')
parser.set_defaults(scaling = [])
parser.set_defaults(undeformed = False)
parser.set_defaults(unitlength = 0.0)
(options,filenames) = parser.parse_args()
options.scaling += [1.0 for i in xrange(max(0,3-len(options.scaling)))]
scaling = map(float, options.scaling)
# --- loop over input files -------------------------------------------------------------------------
if filenames == []: filenames = [None]
for name in filenames:
try:
table = damask.ASCIItable(name = name,
buffered = False)
except: continue
damask.util.report(scriptName,name)
# ------------------------------------------ read header ------------------------------------------
table.head_read()
# ------------------------------------------ sanity checks ----------------------------------------
errors = []
remarks = []
if table.label_dimension(options.coords) != 3: errors.append('coordinates {} are not a vector.'.format(options.coords))
else: colCoord = table.label_index(options.coords)
if table.label_dimension(options.defgrad) != 9: errors.append('deformation gradient {} is not a tensor.'.format(options.defgrad))
else: colF = table.label_index(options.defgrad)
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()
coords = [np.unique(table.data[:,colCoord+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 equal 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
# ------------------------------------------ assemble header ---------------------------------------
table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
for coord in xrange(3):
label = '{}_{}_{}'.format(coord+1,options.defgrad,options.coords)
if np.any(scaling) != 1.0: label+='_{}_{}_{}'.format(scaling)
if options.undeformed: label+='_undeformed'
table.labels_append([label]) # extend ASCII header with new labels
table.head_write()
# ------------------------------------------ read deformation gradient field -----------------------
centroids = deformedCoordsFFT(table.data[:,colF:colF+9].reshape(grid[2],grid[1],grid[0],3,3),
options.undeformed)
# ------------------------------------------ process data ------------------------------------------
table.data_rewind()
for z in xrange(grid[2]):
for y in xrange(grid[1]):
for x in xrange(grid[0]):
table.data_read()
table.data_append(list(centroids[z,y,x,:]))
table.data_write()
# ------------------------------------------ output finalization -----------------------------------
table.close() # close ASCII tables