#!/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, OptionGroup, Option, SUPPRESS_HELP
scriptID = '$Id$'
scriptName = scriptID.split()[1]
#--------------------------------------------------------------------------------------------------
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(scriptID,'\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', choices=neighborhoods.keys(), \
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()
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(string.split(''.join((features[feature]['names'])),sep='(')[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('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n')
else: file['croak'].write('\033[1m'+scriptName+'\033[0m\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()
#--- interprete header ----------------------------------------------------------------------------
info = {
'grid': numpy.zeros(3,'i'),
'size': numpy.zeros(3,'d'),
'origin': numpy.zeros(3,'d'),
'microstructures': 0,
'homogenization': 0
}
newInfo = {
'microstructures': 0,
}
new_header = []
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)
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'])
if numpy.any(info['grid'] < 1):
file['croak'].write('invalid grid a b c.\n')
sys.exit()
if numpy.any(info['size'] <= 0.0):
file['croak'].write('invalid size x y z.\n')
sys.exit()
new_header.append(scriptID+'\n')
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)+''.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()