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DAMASK_EICMD
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Merge branch 'development' of magit1.mpie.de:damask/DAMASK into development

This commit is contained in:
Martin Diehl 2016-03-20 22:28:49 +01:00
parent 52ba6e19a0 a41cd3df40
commit 97b52f60e7
12 changed files with 263 additions and 89 deletions
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2
VERSION
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@ -1 +1 @@
v2.0.0-16-g344c6f6
v2.0.0-43-ge39441f

2
code/lattice.f90
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@ -2182,7 +2182,7 @@ pure function lattice_qDisorientation(Q1, Q2, struct)
real(pReal), dimension(4) :: lattice_qDisorientation
real(pReal), dimension(4), intent(in) :: &
Q1, & ! 1st orientation
Q2 ! 2nd orientation
Q2 ! 2nd orientation
integer(kind(LATTICE_undefined_ID)), optional, intent(in) :: & ! if given, symmetries between the two orientation will be considered
struct

26
lib/damask/asciitable.py
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@ -517,22 +517,28 @@ class ASCIItable():
# ------------------------------------------------------------------
def microstructure_read(self,
grid):
grid,
type = 'i',
strict = False):
"""read microstructure data (from .geom format)"""
N = grid.prod() # expected number of microstructure indices in data
microstructure = np.zeros(N,'i') # initialize as flat array
def datatype(item):
return int(item) if type.lower() == 'i' else float(item)
N = grid.prod() # expected number of microstructure indices in data
microstructure = np.zeros(N,type) # initialize as flat array
i = 0
while i < N and self.data_read():
items = self.data
if len(items) > 2:
if items[1].lower() == 'of': items = [int(items[2])]*int(items[0])
elif items[1].lower() == 'to': items = range(int(items[0]),1+int(items[2]))
else: items = map(int,items)
else: items = map(int,items)
if items[1].lower() == 'of': items = np.ones(datatype(items[0]))*datatype(items[2])
elif items[1].lower() == 'to': items = np.arange(datatype(items[0]),1+datatype(items[2]))
else: items = map(datatype,items)
else: items = map(datatype,items)
s = min(len(items), N-i) # prevent overflow of microstructure array
s = min(len(items), N-i) # prevent overflow of microstructure array
microstructure[i:i+s] = items[:s]
i += s
i += len(items)
return microstructure
return (microstructure, i == N and not self.data_read() if strict # check for proper point count and end of file
else microstructure)

3
lib/damask/util.py
View File

@ -104,7 +104,8 @@ class extendableOption(Option):
class backgroundMessage(threading.Thread):
"""reporting with animation to indicate progress"""
choices = {'bounce': ['_','o','O','°','¯','¯','°','O','o',],
choices = {'bounce': ['_', 'o', 'O', u'\u00B0',
u'\u203e',u'\u203e',u'\u00B0','O','o','_'],
'circle': [u'\u25f4',u'\u25f5',u'\u25f6',u'\u25f7'],
'hexagon': [u'\u2b22',u'\u2b23'],
'square': [u'\u2596',u'\u2598',u'\u259d',u'\u2597'],

44
processing/post/addCurl.py
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@ -10,40 +10,35 @@ scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
def curlFFT(geomdim,field):
N = grid.prod() # field size
n = np.array(np.shape(field)[3:]).prod() # data size
grid = np.array(np.shape(field)[2::-1])
N = grid.prod() # field size
n = np.array(np.shape(field)[3:]).prod() # data size
if n == 3:
dataType = 'vector'
elif n == 9:
dataType = 'tensor'
if n == 3: dataType = 'vector'
elif n == 9: dataType = 'tensor'
field_fourier = np.fft.fftpack.rfftn(field,axes=(0,1,2))
curl_fourier = np.zeros(field_fourier.shape,'c16')
# differentiation in Fourier space
k_s = np.zeros([3],'i')
TWOPIIMG = (0.0+2.0j*math.pi)
TWOPIIMG = 2.0j*math.pi
for i in xrange(grid[2]):
k_s[0] = i
if(grid[2]%2==0 and i == grid[2]//2): # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
k_s[0]=0
elif (i > grid[2]//2):
k_s[0] = k_s[0] - grid[2]
if grid[2]%2 == 0 and i == grid[2]//2: k_s[0] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
elif i > grid[2]//2: k_s[0] -= grid[2]
for j in xrange(grid[1]):
k_s[1] = j
if(grid[1]%2==0 and j == grid[1]//2): # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
k_s[1]=0
elif (j > grid[1]//2):
k_s[1] = k_s[1] - grid[1]
if grid[1]%2 == 0 and j == grid[1]//2: k_s[1] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
elif j > grid[1]//2: k_s[1] -= grid[1]
for k in xrange(grid[0]//2+1):
k_s[2] = k
if(grid[0]%2==0 and k == grid[0]//2): # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
k_s[2]=0
if grid[0]%2 == 0 and k == grid[0]//2: k_s[2] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
xi = (k_s/geomdim)[2::-1].astype('c16') # reversing the field input order
xi = np.array([k_s[2]/geomdim[2]+0.0j,k_s[1]/geomdim[1]+0.j,k_s[0]/geomdim[0]+0.j],'c16')
if dataType == 'tensor':
for l in xrange(3):
curl_fourier[i,j,k,0,l] = ( field_fourier[i,j,k,l,2]*xi[1]\
@ -100,10 +95,8 @@ if options.vector is None and options.tensor is None:
if filenames == []: filenames = [None]
for name in filenames:
try:
table = damask.ASCIItable(name = name,buffered = False)
except:
continue
try: table = damask.ASCIItable(name = name,buffered = False)
except: continue
damask.util.report(scriptName,name)
# ------------------------------------------ read header ------------------------------------------
@ -161,9 +154,10 @@ for name in filenames:
stack = [table.data]
for type, data in items.iteritems():
for i,label in enumerate(data['active']):
stack.append(curlFFT(size[::-1], # we need to reverse order here, because x
table.data[:,data['column'][i]:data['column'][i]+data['dim']]. # is fastest,ie rightmost, but leftmost in
reshape([grid[2],grid[1],grid[0]]+data['shape']))) # our x,y,z notation
# we need to reverse order here, because x is fastest,ie rightmost, but leftmost in our x,y,z notation
stack.append(curlFFT(size[::-1],
table.data[:,data['column'][i]:data['column'][i]+data['dim']].
reshape([grid[2],grid[1],grid[0]]+data['shape'])))
# ------------------------------------------ output result -----------------------------------------

49
processing/post/addDivergence.py
View File

@ -10,39 +10,35 @@ scriptName = os.path.splitext(os.path.basename(__file__))[0]
scriptID = ' '.join([scriptName,damask.version])
def divFFT(geomdim,field):
N = grid.prod() # field size
n = np.array(np.shape(field)[3:]).prod() # data size
grid = np.array(np.shape(field)[2::-1])
N = grid.prod() # field size
n = np.array(np.shape(field)[3:]).prod() # data size
field_fourier = np.fft.fftpack.rfftn(field,axes=(0,1,2))
div_fourier = np.zeros(field_fourier.shape[0:len(np.shape(field))-1],'c16') # size depents on whether tensor or vector
div_fourier = np.zeros(field_fourier.shape[0:len(np.shape(field))-1],'c16') # size depents on whether tensor or vector
# differentiation in Fourier space
k_s=np.zeros([3],'i')
TWOPIIMG = (0.0+2.0j*math.pi)
TWOPIIMG = 2.0j*math.pi
for i in xrange(grid[2]):
k_s[0] = i
if(grid[2]%2==0 and i == grid[2]//2): # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
k_s[0]=0
elif (i > grid[2]//2):
k_s[0] = k_s[0] - grid[2]
if grid[2]%2 == 0 and i == grid[2]//2: k_s[0] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
elif i > grid[2]//2: k_s[0] -= grid[2]
for j in xrange(grid[1]):
k_s[1] = j
if(grid[1]%2==0 and j == grid[1]//2): # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
k_s[1]=0
elif (j > grid[1]//2):
k_s[1] = k_s[1] - grid[1]
if grid[1]%2 == 0 and j == grid[1]//2: k_s[1] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
elif j > grid[1]//2: k_s[1] -= grid[1]
for k in xrange(grid[0]//2+1):
k_s[2] = k
if(grid[0]%2==0 and k == grid[0]//2): # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
k_s[2]=0
if grid[0]%2 == 0 and k == grid[0]//2: k_s[2] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
xi=np.array([k_s[2]/geomdim[2]+0.0j,k_s[1]/geomdim[1]+0.j,k_s[0]/geomdim[0]+0.j],'c16')
if n == 9: # tensor, 3x3 -> 3
xi = (k_s/geomdim)[2::-1].astype('c16') # reversing the field input order
if n == 9: # tensor, 3x3 -> 3
for l in xrange(3):
div_fourier[i,j,k,l] = sum(field_fourier[i,j,k,l,0:3]*xi) *TWOPIIMG
elif n == 3: # vector, 3 -> 1
elif n == 3: # vector, 3 -> 1
div_fourier[i,j,k] = sum(field_fourier[i,j,k,0:3]*xi) *TWOPIIMG
return np.fft.fftpack.irfftn(div_fourier,axes=(0,1,2)).reshape([N,n/3])
@ -80,15 +76,13 @@ parser.set_defaults(coords = 'ipinitialcoord',
if options.vector is None and options.tensor is None:
parser.error('no data column specified.')
# --- loop over input files -------------------------------------------------------------------------
# --- loop over input files ------------------------------------------------------------------------
if filenames == []: filenames = [None]
for name in filenames:
try:
table = damask.ASCIItable(name = name,buffered = False)
except:
continue
try: table = damask.ASCIItable(name = name,buffered = False)
except: continue
damask.util.report(scriptName,name)
# ------------------------------------------ read header ------------------------------------------
@ -140,16 +134,17 @@ for name in filenames:
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
size = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1])) # spacing for grid==1 equal to smallest among other ones
# ------------------------------------------ process value field -----------------------------------
stack = [table.data]
for type, data in items.iteritems():
for i,label in enumerate(data['active']):
stack.append(divFFT(size[::-1], # we need to reverse order here, because x
table.data[:,data['column'][i]:data['column'][i]+data['dim']]. # is fastest,ie rightmost, but leftmost in
reshape([grid[2],grid[1],grid[0]]+data['shape']))) # our x,y,z notation
# we need to reverse order here, because x is fastest,ie rightmost, but leftmost in our x,y,z notation
stack.append(divFFT(size[::-1],
table.data[:,data['column'][i]:data['column'][i]+data['dim']].
reshape([grid[2],grid[1],grid[0]]+data['shape'])))
# ------------------------------------------ output result -----------------------------------------
@ -158,4 +153,4 @@ for name in filenames:
# ------------------------------------------ output finalization -----------------------------------
table.close() # close input ASCII table (works for stdin)
table.close() # close input ASCII table (works for stdin)

158
processing/post/addGradient.py Executable file
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@ -0,0 +1,158 @@
#!/usr/bin/env python
# -*- coding: UTF-8 no BOM -*-
import os,sys,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 gradFFT(geomdim,field):
grid = np.array(np.shape(field)[2::-1])
N = grid.prod() # field size
n = np.array(np.shape(field)[3:]).prod() # data size
if n == 3: dataType = 'vector'
elif n == 1: dataType = 'scalar'
field_fourier = np.fft.fftpack.rfftn(field,axes=(0,1,2))
grad_fourier = np.zeros(field_fourier.shape+(3,),'c16')
# differentiation in Fourier space
k_s = np.zeros([3],'i')
TWOPIIMG = 2.0j*math.pi
for i in xrange(grid[2]):
k_s[0] = i
if grid[2]%2 == 0 and i == grid[2]//2: k_s[0] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
elif i > grid[2]//2: k_s[0] -= grid[2]
for j in xrange(grid[1]):
k_s[1] = j
if grid[1]%2 == 0 and j == grid[1]//2: k_s[1] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
elif j > grid[1]//2: k_s[1] -= grid[1]
for k in xrange(grid[0]//2+1):
k_s[2] = k
if grid[0]%2 == 0 and k == grid[0]//2: k_s[2] = 0 # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
xi = (k_s/geomdim)[2::-1].astype('c16') # reversing the field order
grad_fourier[i,j,k,0,:] = field_fourier[i,j,k,0]*xi *TWOPIIMG # vector field from scalar data
if dataType == 'vector':
grad_fourier[i,j,k,1,:] = field_fourier[i,j,k,1]*xi *TWOPIIMG # tensor field from vector data
grad_fourier[i,j,k,2,:] = field_fourier[i,j,k,2]*xi *TWOPIIMG
return np.fft.fftpack.irfftn(grad_fourier,axes=(0,1,2)).reshape([N,3*n])
# --------------------------------------------------------------------
# MAIN
# --------------------------------------------------------------------
parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
Add column(s) containing gradient of requested column(s).
Operates on periodic ordered three-dimensional data sets.
Deals with both vector- and scalar fields.
""", version = scriptID)
parser.add_option('-c','--coordinates',
dest = 'coords',
type = 'string', metavar='string',
help = 'column heading for coordinates [%default]')
parser.add_option('-v','--vector',
dest = 'vector',
action = 'extend', metavar = '<string LIST>',
help = 'heading of columns containing vector field values')
parser.add_option('-s','--scalar',
dest = 'scalar',
action = 'extend', metavar = '<string LIST>',
help = 'heading of columns containing scalar field values')
parser.set_defaults(coords = 'ipinitialcoord',
)
(options,filenames) = parser.parse_args()
if options.vector is None and options.scalar is None:
parser.error('no data column specified.')
# --- 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 ----------------------------------------
items = {
'scalar': {'dim': 1, 'shape': [1], 'labels':options.scalar, 'active':[], 'column': []},
'vector': {'dim': 3, 'shape': [3], 'labels':options.vector, 'active':[], 'column': []},
}
errors = []
remarks = []
column = {}
if table.label_dimension(options.coords) != 3: errors.append('coordinates {} are not a vector.'.format(options.coords))
else: colCoord = table.label_index(options.coords)
for type, data in items.iteritems():
for what in (data['labels'] if data['labels'] is not None else []):
dim = table.label_dimension(what)
if dim != data['dim']: remarks.append('column {} is not a {}.'.format(what,type))
else:
items[type]['active'].append(what)
items[type]['column'].append(table.label_index(what))
if remarks != []: damask.util.croak(remarks)
if errors != []:
damask.util.croak(errors)
table.close(dismiss = True)
continue
# ------------------------------------------ assemble header --------------------------------------
table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
for type, data in items.iteritems():
for label in data['active']:
table.labels_append(['{}_gradFFT({})'.format(i+1,label) for i in xrange(3 * data['dim'])]) # extend ASCII header with new labels
table.head_write()
# --------------- 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]))
# ------------------------------------------ process value field -----------------------------------
stack = [table.data]
for type, data in items.iteritems():
for i,label in enumerate(data['active']):
# we need to reverse order here, because x is fastest,ie rightmost, but leftmost in our x,y,z notation
stack.append(gradFFT(size[::-1],
table.data[:,data['column'][i]:data['column'][i]+data['dim']].
reshape([grid[2],grid[1],grid[0]]+data['shape'])))
# ------------------------------------------ output result -----------------------------------------
if len(stack) > 1: table.data = np.hstack(tuple(stack))
table.data_writeArray('%.12g')
# ------------------------------------------ output finalization -----------------------------------
table.close() # close input ASCII table (works for stdin)

2
processing/post/filterTable.py
View File

@ -35,7 +35,7 @@ Filter rows according to condition and columns by either white or black listing.
Examples:
Every odd row if x coordinate is positive -- " #ip.x# >= 0.0 and #_row_#%2 == 1 ).
All rows where label 'foo' equals 'bar' -- " #foo# == \"bar\" "
All rows where label 'foo' equals 'bar' -- " #s#foo# == 'bar' "
""", version = scriptID)

2
processing/post/vtk_addRectilinearGridData.py
View File

@ -151,7 +151,7 @@ for name in filenames:
writer = vtk.vtkXMLRectilinearGridWriter()
writer.SetDataModeToBinary()
writer.SetCompressorTypeToZLib()
writer.SetFileName(os.path.splitext(options.vtk)[0]+('' if options.inplace else '_added.vtr'))
writer.SetFileName(os.path.splitext(options.vtk)[0]+('.vtr' if options.inplace else '_added.vtr'))
if vtk.VTK_MAJOR_VERSION <= 5: writer.SetInput(rGrid)
else: writer.SetInputData(rGrid)
writer.Write()

26
processing/pre/geom_canvas.py
View File

@ -28,24 +28,32 @@ parser.add_option('-o', '--offset',
help = 'a,b,c offset from old to new origin of grid [%default]')
parser.add_option('-f', '--fill',
dest = 'fill',
type = 'int', metavar = 'int',
type = 'float', metavar = 'float',
help = '(background) canvas grain index. "0" selects maximum microstructure index + 1 [%default]')
parser.add_option('--float',
dest = 'real',
action = 'store_true',
help = 'input data is float [%default]')
parser.set_defaults(grid = ['0','0','0'],
offset = (0,0,0),
fill = 0,
real = False,
)
(options, filenames) = parser.parse_args()
datatype = 'f' if options.real else 'i'
# --- loop over input files -------------------------------------------------------------------------
if filenames == []: filenames = [None]
for name in filenames:
try:
table = damask.ASCIItable(name = name,
buffered = False, labeled = False)
try: table = damask.ASCIItable(name = name,
buffered = False,
labeled = False)
except: continue
damask.util.report(scriptName,name)
@ -71,7 +79,7 @@ for name in filenames:
# --- read data ------------------------------------------------------------------------------------
microstructure = table.microstructure_read(info['grid']).reshape(info['grid'],order='F') # read microstructure
microstructure = table.microstructure_read(info['grid'],datatype).reshape(info['grid'],order='F') # read microstructure
# --- do work ------------------------------------------------------------------------------------
@ -85,8 +93,8 @@ for name in filenames:
else int(n) for o,n in zip(info['grid'],options.grid)],'i')
newInfo['grid'] = np.where(newInfo['grid'] > 0, newInfo['grid'],info['grid'])
microstructure_cropped = np.zeros(newInfo['grid'],'i')
microstructure_cropped.fill(options.fill if options.fill > 0 else microstructure.max()+1)
microstructure_cropped = np.zeros(newInfo['grid'],datatype)
microstructure_cropped.fill(options.fill if options.real or options.fill > 0 else microstructure.max()+1)
xindex = list(set(xrange(options.offset[0],options.offset[0]+newInfo['grid'][0])) & \
set(xrange(info['grid'][0])))
yindex = list(set(xrange(options.offset[1],options.offset[1]+newInfo['grid'][1])) & \
@ -152,9 +160,9 @@ for name in filenames:
# --- write microstructure information ------------------------------------------------------------
formatwidth = int(math.floor(math.log10(microstructure_cropped.max())+1))
format = '%g' if options.real else '%{}i'.format(int(math.floor(math.log10(microstructure_cropped.max())+1)))
table.data = microstructure_cropped.reshape((newInfo['grid'][0],newInfo['grid'][1]*newInfo['grid'][2]),order='F').transpose()
table.data_writeArray('%%%ii'%(formatwidth),delimiter=' ')
table.data_writeArray(format,delimiter=' ')
# --- output finalization --------------------------------------------------------------------------

27
processing/pre/geom_check.py
View File

@ -54,12 +54,25 @@ for name in filenames:
errors = []
if np.any(info['grid'] < 1): errors.append('invalid grid a b c.')
if np.any(info['size'] <= 0.0): errors.append('invalid size x y z.')
#--- read microstructure information --------------------------------------------------------------
if options.data:
microstructure,ok = table.microstructure_read(info['grid'],strict = True) # read microstructure
if ok:
structure = vtk.vtkIntArray()
structure.SetName('Microstructures')
for idx in microstructure: structure.InsertNextValue(idx)
else: errors.append('mismatch between data and grid dimension.')
if errors != []:
damask.util.croak(errors)
table.close(dismiss = True)
continue
# --- generate VTK rectilinear grid --------------------------------------------------------------------------------
# --- generate VTK rectilinear grid ---------------------------------------------------------------
grid = vtk.vtkRectilinearGrid()
grid.SetDimensions([x+1 for x in info['grid']])
@ -72,18 +85,8 @@ for name in filenames:
elif i == 1: grid.SetYCoordinates(temp)
elif i == 2: grid.SetZCoordinates(temp)
#--- read microstructure information --------------------------------------------------------------
if options.data:
microstructure = table.microstructure_read(info['grid']) # read microstructure
structure = vtk.vtkIntArray()
structure.SetName('Microstructures')
for idx in microstructure:
structure.InsertNextValue(idx)
grid.GetCellData().AddArray(structure)
if options.data: grid.GetCellData().AddArray(structure)
# --- write data -----------------------------------------------------------------------------------
if name:

11
processing/pre/geom_unpack.py
View File

@ -18,6 +18,14 @@ Unpack geometry files containing ranges "a to b" and/or "n of x" multiples (excl
""", version = scriptID)
parser.add_option('-1', '--onedimensional',
dest = 'oneD',
action = 'store_true',
help = 'output geom file with one-dimensional data arrangement')
parser.set_defaults(oneD = False,
)
(options, filenames) = parser.parse_args()
# --- loop over input files -------------------------------------------------------------------------
@ -69,7 +77,8 @@ for name in filenames:
microstructure = table.microstructure_read(info['grid']) # read microstructure
formatwidth = int(math.floor(math.log10(microstructure.max())+1)) # efficient number printing format
table.data = microstructure.reshape((info['grid'][0],info['grid'][1]*info['grid'][2]),order='F').transpose()
table.data = microstructure if options.oneD else \
microstructure.reshape((info['grid'][0],info['grid'][1]*info['grid'][2]),order='F').transpose()
table.data_writeArray('%%%ii'%(formatwidth),delimiter = ' ')
#--- output finalization --------------------------------------------------------------------------