287 lines
12 KiB
Python
Executable File
287 lines
12 KiB
Python
Executable File
#!/usr/bin/env python
|
|
# -*- coding: UTF-8 no BOM -*-
|
|
|
|
import os,re,sys,math,numpy,string,damask
|
|
from scipy import ndimage
|
|
from optparse import OptionParser, Option
|
|
|
|
#--------------------------------------------------------------------------------------------------
|
|
class extendableOption(Option):
|
|
#--------------------------------------------------------------------------------------------------
|
|
# used for definition of new option parser action 'extend', which enables to take multiple option arguments
|
|
# taken from online tutorial http://docs.python.org/library/optparse.html
|
|
|
|
ACTIONS = Option.ACTIONS + ("extend",)
|
|
STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",)
|
|
TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",)
|
|
ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",)
|
|
|
|
def take_action(self, action, dest, opt, value, values, parser):
|
|
if action == "extend":
|
|
lvalue = value.split(",")
|
|
values.ensure_value(dest, []).extend(lvalue)
|
|
else:
|
|
Option.take_action(self, action, dest, opt, value, values, parser)
|
|
|
|
|
|
def periodic_3Dpad(array, rimdim=(1,1,1)):
|
|
|
|
rimdim = numpy.array(rimdim,'i')
|
|
size = numpy.array(array.shape,'i')
|
|
padded = numpy.empty(size+2*rimdim,array.dtype)
|
|
padded[rimdim[0]:rimdim[0]+size[0],
|
|
rimdim[1]:rimdim[1]+size[1],
|
|
rimdim[2]:rimdim[2]+size[2]] = array
|
|
|
|
p = numpy.zeros(3,'i')
|
|
for side in xrange(3):
|
|
for p[(side+2)%3] in xrange(padded.shape[(side+2)%3]):
|
|
for p[(side+1)%3] in xrange(padded.shape[(side+1)%3]):
|
|
for p[side%3] in xrange(rimdim[side%3]):
|
|
spot = (p-rimdim)%size
|
|
padded[p[0],p[1],p[2]] = array[spot[0],spot[1],spot[2]]
|
|
for p[side%3] in xrange(rimdim[side%3]+size[side%3],size[side%3]+2*rimdim[side%3]):
|
|
spot = (p-rimdim)%size
|
|
padded[p[0],p[1],p[2]] = array[spot[0],spot[1],spot[2]]
|
|
return padded
|
|
|
|
#--------------------------------------------------------------------------------------------------
|
|
# MAIN
|
|
#--------------------------------------------------------------------------------------------------
|
|
identifiers = {
|
|
'grid': ['a','b','c'],
|
|
'size': ['x','y','z'],
|
|
'origin': ['x','y','z'],
|
|
}
|
|
|
|
mappings = {
|
|
'grid': lambda x: int(x),
|
|
'size': lambda x: float(x),
|
|
'origin': lambda x: float(x),
|
|
'homogenization': lambda x: int(x),
|
|
'microstructures': lambda x: int(x),
|
|
}
|
|
|
|
features = [
|
|
{'aliens': 1, 'names': ['boundary, biplane'],},
|
|
{'aliens': 2, 'names': ['tripleline',],},
|
|
{'aliens': 3, 'names': ['quadruplepoint',],}
|
|
]
|
|
|
|
neighborhoods = {
|
|
'neumann':numpy.array([
|
|
[-1, 0, 0],
|
|
[ 1, 0, 0],
|
|
[ 0,-1, 0],
|
|
[ 0, 1, 0],
|
|
[ 0, 0,-1],
|
|
[ 0, 0, 1],
|
|
]),
|
|
'moore':numpy.array([
|
|
[-1,-1,-1],
|
|
[ 0,-1,-1],
|
|
[ 1,-1,-1],
|
|
[-1, 0,-1],
|
|
[ 0, 0,-1],
|
|
[ 1, 0,-1],
|
|
[-1, 1,-1],
|
|
[ 0, 1,-1],
|
|
[ 1, 1,-1],
|
|
[-1,-1, 0],
|
|
[ 0,-1, 0],
|
|
[ 1,-1, 0],
|
|
[-1, 0, 0],
|
|
#
|
|
[ 1, 0, 0],
|
|
[-1, 1, 0],
|
|
[ 0, 1, 0],
|
|
[ 1, 1, 0],
|
|
[-1,-1, 1],
|
|
[ 0,-1, 1],
|
|
[ 1,-1, 1],
|
|
[-1, 0, 1],
|
|
[ 0, 0, 1],
|
|
[ 1, 0, 1],
|
|
[-1, 1, 1],
|
|
[ 0, 1, 1],
|
|
[ 1, 1, 1],
|
|
])
|
|
}
|
|
|
|
parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """
|
|
Produce geom files containing Euclidean distance to grain structural features:
|
|
boundaries, triple lines, and quadruple points.
|
|
|
|
""" + string.replace('$Id$','\n','\\n')
|
|
)
|
|
|
|
parser.add_option('-t','--type', dest='type', action='extend', type='string', \
|
|
help='feature type (%s)'%(', '.join(map(lambda x:', '.join(x['names']),features))))
|
|
parser.add_option('-n','--neighborhood', dest='neigborhood', action='store', type='string', \
|
|
help='type of neighborhood (%s) [neumann]'%(', '.join(neighborhoods.keys())))
|
|
parser.add_option('-2', '--twodimensional', dest='twoD', action='store_true', \
|
|
help='output geom file with two-dimensional data arrangement [%default]')
|
|
|
|
parser.set_defaults(type = [])
|
|
parser.set_defaults(neighborhood = 'neumann')
|
|
parser.set_defaults(twoD = False)
|
|
|
|
(options,filenames) = parser.parse_args()
|
|
|
|
options.neighborhood = options.neighborhood.lower()
|
|
if options.neighborhood not in neighborhoods:
|
|
parser.error('unknown neighborhood %s!'%options.neighborhood)
|
|
|
|
feature_list = []
|
|
for i,feature in enumerate(features):
|
|
for name in feature['names']:
|
|
for myType in options.type:
|
|
if name.startswith(myType):
|
|
feature_list.append(i) # remember valid features
|
|
break
|
|
|
|
|
|
#--- setup file handles ---------------------------------------------------------------------------
|
|
files = []
|
|
if filenames == []:
|
|
files.append({'name':'STDIN',
|
|
'input':sys.stdin,
|
|
'output':sys.stdout,
|
|
'croak':sys.stderr,
|
|
})
|
|
else:
|
|
for name in filenames:
|
|
if os.path.exists(name):
|
|
files.append({'name':name,
|
|
'input':open(name),
|
|
'output':[open(features[feature]['names'][0]+'_'+name,'w') for feature in feature_list],
|
|
'croak':sys.stdout,
|
|
})
|
|
|
|
#--- loop over input files ------------------------------------------------------------------------
|
|
for file in files:
|
|
if file['name'] != 'STDIN': file['croak'].write(file['name']+'\n')
|
|
|
|
firstline = file['input'].readline()
|
|
m = re.search('(\d+)\s*head', firstline.lower())
|
|
if m:
|
|
headerlines = int(m.group(1))
|
|
headers = [file['input'].readline() for i in range(headerlines)]
|
|
else:
|
|
headerlines = 1
|
|
headers = firstline
|
|
|
|
content = file['input'].readlines()
|
|
file['input'].close()
|
|
|
|
#--- interpretate header --------------------------------------------------------------------------
|
|
info = {
|
|
'grid': numpy.array([0,0,0]),
|
|
'size': numpy.array([0.0,0.0,0.0]),
|
|
'origin': numpy.array([0.0,0.0,0.0]),
|
|
'microstructures': 0,
|
|
'homogenization': 0
|
|
}
|
|
|
|
newInfo = {
|
|
'microstructures': 0,
|
|
}
|
|
|
|
new_header = []
|
|
new_header.append('$Id$\n')
|
|
for header in headers:
|
|
headitems = map(str.lower,header.split())
|
|
if headitems[0] == 'resolution': headitems[0] = 'grid'
|
|
if headitems[0] == 'dimension': headitems[0] = 'size'
|
|
if headitems[0] in mappings.keys():
|
|
if headitems[0] in identifiers.keys():
|
|
for i in xrange(len(identifiers[headitems[0]])):
|
|
info[headitems[0]][i] = \
|
|
mappings[headitems[0]](headitems[headitems.index(identifiers[headitems[0]][i])+1])
|
|
else:
|
|
info[headitems[0]] = mappings[headitems[0]](headitems[1])
|
|
else:
|
|
new_header.append(header)
|
|
|
|
if numpy.all(info['grid'] == 0):
|
|
file['croak'].write('no grid info found.\n')
|
|
continue
|
|
if numpy.all(info['size'] == 0.0):
|
|
file['croak'].write('no size info found.\n')
|
|
continue
|
|
|
|
file['croak'].write('grid a b c: %s\n'%(' x '.join(map(str,info['grid']))) + \
|
|
'size x y z: %s\n'%(' x '.join(map(str,info['size']))) + \
|
|
'origin x y z: %s\n'%(' : '.join(map(str,info['origin']))) + \
|
|
'homogenization: %i\n'%info['homogenization'] + \
|
|
'microstructures: %i\n'%info['microstructures'])
|
|
|
|
new_header.append("grid\ta %i\tb %i\tc %i\n"%(info['grid'][0],info['grid'][1],info['grid'][2],))
|
|
new_header.append("size\tx %f\ty %f\tz %f\n"%(info['size'][0],info['size'][1],info['size'][2],))
|
|
new_header.append("origin\tx %f\ty %f\tz %f\n"%(info['origin'][0],info['origin'][1],info['origin'][2],))
|
|
new_header.append("homogenization\t%i\n"%info['homogenization'])
|
|
|
|
#--- process input --------------------------------------------------------------------------------
|
|
structure = numpy.zeros(info['grid'],'i')
|
|
i = 0
|
|
for line in content:
|
|
for item in map(int,line.split()):
|
|
structure[i%info['grid'][0],
|
|
(i/info['grid'][0])%info['grid'][1],
|
|
i/info['grid'][0] /info['grid'][1]] = item
|
|
i += 1
|
|
|
|
neighborhood = neighborhoods[options.neighborhood]
|
|
convoluted = numpy.empty([len(neighborhood)]+list(info['grid']+2),'i')
|
|
microstructure = periodic_3Dpad(structure)
|
|
|
|
for i,p in enumerate(neighborhood):
|
|
stencil = numpy.zeros((3,3,3),'i')
|
|
stencil[1,1,1] = -1
|
|
stencil[p[0]+1,
|
|
p[1]+1,
|
|
p[2]+1] = 1
|
|
|
|
convoluted[i,:,:,:] = ndimage.convolve(microstructure,stencil)
|
|
|
|
distance = numpy.ones((len(feature_list),info['grid'][0],info['grid'][1],info['grid'][2]),'d')
|
|
|
|
convoluted = numpy.sort(convoluted,axis=0)
|
|
uniques = numpy.zeros(info['grid'])
|
|
check = numpy.empty(info['grid'])
|
|
check[:,:,:] = numpy.nan
|
|
for i in xrange(len(neighborhood)):
|
|
uniques += numpy.where(convoluted[i,1:-1,1:-1,1:-1] == check,0,1)
|
|
check = convoluted[i,1:-1,1:-1,1:-1]
|
|
for i,feature_id in enumerate(feature_list):
|
|
distance[i,:,:,:] = numpy.where(uniques > features[feature_id]['aliens'],0.0,1.0)
|
|
|
|
for i in xrange(len(feature_list)):
|
|
distance[i,:,:,:] = ndimage.morphology.distance_transform_edt(distance[i,:,:,:])*\
|
|
[max(info['size']/info['grid'])]*3
|
|
for i,feature in enumerate(feature_list):
|
|
newInfo['microstructures'] = int(math.ceil(distance[i,:,:,:].max()))
|
|
formatwidth = int(math.floor(math.log10(distance[i,:,:,:].max())+1))
|
|
|
|
#--- assemble header and report changes -----------------------------------------------------------
|
|
output = '%i\theader\n'%(len(new_header)+1)
|
|
output += ''.join(new_header)
|
|
output += "microstructures\t%i\n"%newInfo['microstructures']
|
|
file['croak'].write('\n'+features[i]['names'][0]+'\n')
|
|
if (newInfo['microstructures'] != info['microstructures']):
|
|
file['croak'].write('--> microstructures: %i\n'%newInfo['microstructures'])
|
|
|
|
#--- write new data -------------------------------------------------------------------------------
|
|
for z in xrange(info['grid'][2]):
|
|
for y in xrange(info['grid'][1]):
|
|
output += {True:' ',False:'\n'}[options.twoD].join(map(lambda x: \
|
|
('%%%ii'%formatwidth)%(round(x)), distance[i,:,y,z])) + '\n'
|
|
file['output'][i].write(output)
|
|
|
|
if file['name'] != 'STDIN':
|
|
file['output'][i].close()
|
|
|
|
#--- output finalization --------------------------------------------------------------------------
|
|
if file['name'] != 'STDIN':
|
|
file['input'].close()
|