adopted same algorithm as in addEuclideanDistance
This commit is contained in:
Pratheek Shanthraj
parent
096204cd79
commit
0e93d51fed
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@ -1,12 +1,11 @@
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#!/usr/bin/env python
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# -*- coding: UTF-8 no BOM -*-
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import os,sys,string,re,numpy,skfmm
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from optparse import OptionParser, OptionGroup, Option, SUPPRESS_HELP
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import os,re,sys,math,numpy,string,damask
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from scipy import ndimage
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from optparse import OptionParser, Option
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# -----------------------------
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class extendedOption(Option):
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class extendableOption(Option):
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# -----------------------------
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# used for definition of new option parser action 'extend', which enables to take multiple option arguments
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# taken from online tutorial http://docs.python.org/library/optparse.html
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@ -24,73 +23,30 @@ class extendedOption(Option):
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Option.take_action(self, action, dest, opt, value, values, parser)
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def periodic_3Dpad(array, rimdim=(1,1,1)):
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def outStdout(cmd,locals):
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if cmd[0:3] == '(!)':
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exec(cmd[3:])
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elif cmd[0:3] == '(?)':
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cmd = eval(cmd[3:])
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print cmd
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else:
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print cmd
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return
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rimdim = numpy.array(rimdim,'i')
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size = numpy.array(array.shape,'i')
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padded = numpy.empty(size+2*rimdim,array.dtype)
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padded[rimdim[0]:rimdim[0]+size[0],
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rimdim[1]:rimdim[1]+size[1],
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rimdim[2]:rimdim[2]+size[2]] = array
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def outFile(cmd,locals):
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if cmd[0:3] == '(!)':
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exec(cmd[3:])
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elif cmd[0:3] == '(?)':
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cmd = eval(cmd[3:])
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locals['filepointer'].write(cmd+'\n')
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else:
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locals['filepointer'].write(cmd+'\n')
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return
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p = numpy.zeros(3,'i')
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for side in xrange(3):
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for p[(side+2)%3] in xrange(padded.shape[(side+2)%3]):
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for p[(side+1)%3] in xrange(padded.shape[(side+1)%3]):
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for p[side%3] in xrange(rimdim[side%3]):
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spot = (p-rimdim)%size
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padded[p[0],p[1],p[2]] = array[spot[0],spot[1],spot[2]]
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for p[side%3] in xrange(rimdim[side%3]+size[side%3],size[side%3]+2*rimdim[side%3]):
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spot = (p-rimdim)%size
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padded[p[0],p[1],p[2]] = array[spot[0],spot[1],spot[2]]
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return padded
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def output(cmds,locals,dest):
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for cmd in cmds:
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if isinstance(cmd,list):
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output(cmd,locals,dest)
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else:
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{\
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'File': outFile,\
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'Stdout': outStdout,\
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}[dest](str(cmd),locals)
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return
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# +++++++++++++++++++++++++++++++++++++++++++++++++++
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def vtk_writeASCII_mesh(dim,res,origin,data):
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# +++++++++++++++++++++++++++++++++++++++++++++++++++
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""" function writes data array defined on a rectilinear grid """
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N = res[0]*res[1]*res[2]
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cmds = [\
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'# vtk DataFile Version 3.1',
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string.replace('powered by $Id: spectral_geomCheck.py 1575 2012-06-26 18:07:38Z MPIE\p.eisenlohr $','\n','\\n'),
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'ASCII',
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'DATASET RECTILINEAR_GRID',
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'DIMENSIONS %i %i %i'%(res[0]+1,res[1]+1,res[2]+1),
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'X_COORDINATES %i float'%(res[0]+1),
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' '.join(map(str,[i*dim[0]/res[0]+origin[0] for i in range(res[0]+1)])),
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'Y_COORDINATES %i float'%(res[1]+1),
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' '.join(map(str,[i*dim[1]/res[1]+origin[1] for i in range(res[1]+1)])),
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'Z_COORDINATES %i float'%(res[2]+1),
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' '.join(map(str,[i*dim[2]/res[2]+origin[2] for i in range(res[2]+1)])),
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'CELL_DATA %i'%N,
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]
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for datatype in data:
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for item in data[datatype]:
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cmds += [\
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'%s %s float'%(datatype.upper()+{True:'',False:'S'}[datatype.lower().endswith('s')],item),
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'LOOKUP_TABLE default',
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[[['\t'.join(map(str,data[datatype][item][:,j,k]))] for j in range(res[1])] for k in range(res[2])]
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]
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return cmds
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# ----------------------- MAIN -------------------------------
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# --------------------------------------------------------------------
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# MAIN
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# --------------------------------------------------------------------
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identifiers = {
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'resolution': ['a','b','c'],
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@ -103,28 +59,108 @@ mappings = {
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'origin': lambda x: float(x),
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}
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parser = OptionParser(option_class=extendedOption, usage='%prog [geomfile[s]]', description = """
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Produce Euclidean distance map from geom description
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features = [ \
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{'aliens': 1, 'names': ['boundary','biplane'],},
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{'aliens': 2, 'names': ['tripleline',],},
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{'aliens': 3, 'names': ['quadruplepoint',],}
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]
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""" + string.replace('$Id: spectral_geomCheck.py 1575 2012-06-26 18:07:38Z MPIE\p.eisenlohr $','\n','\\n')
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neighborhoods = {
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'neumann':numpy.array([
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[-1, 0, 0],
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[ 1, 0, 0],
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[ 0,-1, 0],
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[ 0, 1, 0],
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[ 0, 0,-1],
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[ 0, 0, 1],
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]),
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'moore':numpy.array([
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[-1,-1,-1],
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[ 0,-1,-1],
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[ 1,-1,-1],
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[-1, 0,-1],
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[ 0, 0,-1],
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[ 1, 0,-1],
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[-1, 1,-1],
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[ 0, 1,-1],
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[ 1, 1,-1],
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[-1,-1, 0],
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[ 0,-1, 0],
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[ 1,-1, 0],
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[-1, 0, 0],
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#
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[ 1, 0, 0],
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[-1, 1, 0],
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[ 0, 1, 0],
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[ 1, 1, 0],
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[-1,-1, 1],
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[ 0,-1, 1],
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[ 1,-1, 1],
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[-1, 0, 1],
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[ 0, 0, 1],
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[ 1, 0, 1],
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[-1, 1, 1],
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[ 0, 1, 1],
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[ 1, 1, 1],
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])
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}
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parser = OptionParser(option_class=extendableOption, usage='%prog options [file[s]]', description = """
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Produce geom files containing Euclidean distance to grain structural features:
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boundaries, triple lines, and quadruple points.
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""" + string.replace('$Id: addEuclideanDistance.py 2039 2012-12-19 14:50:45Z MPIE\p.shanthraj $','\n','\\n')
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)
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(options, filenames) = parser.parse_args()
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parser.add_option('-t','--type', dest='type', action='extend', type='string', \
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help='feature type (%s)'%(', '.join(map(lambda x:', '.join(x['names']),features))))
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parser.add_option('-n','--neighborhood', dest='neigborhood', action='store', type='string', \
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help='type of neighborhood (%s)'%(', '.join(neighborhoods.keys())), \
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metavar='<int>')
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parser.add_option('-2', '--twodimensional', dest='twoD', action='store_true', \
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help='output geom file with two-dimensional data arrangement')
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parser.set_defaults(type = [])
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parser.set_defaults(neighborhood = 'neumann')
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parser.set_defaults(twoD = False)
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(options,filenames) = parser.parse_args()
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options.neighborhood = options.neighborhood.lower()
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if options.neighborhood not in neighborhoods:
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parser.error('unknown neighborhood %s!'%options.neighborhood)
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feature_list = []
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for i,feature in enumerate(features):
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for name in feature['names']:
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for type in options.type:
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if name.startswith(type):
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feature_list.append(i) # remember valid features
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break
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print feature_list
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# ------------------------------------------ setup file handles ---------------------------------------
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files = []
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if filenames == []:
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files.append({'name':'STDIN', 'input':sys.stdin})
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files.append({'name':'STDIN',
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'input':sys.stdin,
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'output':sys.stdout,
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'croak':sys.stderr,
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})
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else:
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for name in filenames:
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if os.path.exists(name):
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files.append({'name':name, 'input':open(name)})
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files.append({'name':name,
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'input':open(name),
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'output':[open(features[feature]['names'][0]+'_'+name,'w') for feature in feature_list],
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'croak':sys.stdout,
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})
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# ------------------------------------------ loop over input files ---------------------------------------
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for file in files:
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if file['name'] != 'STDIN': print file['name']
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if file['name'] != 'STDIN': file['croak'].write(file['name']+'\n')
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# get labels by either read the first row, or - if keyword header is present - the last line of the header
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@ -132,7 +168,7 @@ for file in files:
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m = re.search('(\d+)\s*head', firstline.lower())
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if m:
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headerlines = int(m.group(1))
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headers = [file['input'].readline() for i in range(headerlines)]
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headers = [firstline]+[file['input'].readline() for i in range(headerlines)]
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else:
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headerlines = 1
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headers = firstline
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@ -140,56 +176,110 @@ for file in files:
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content = file['input'].readlines()
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file['input'].close()
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info = {'resolution': [0,0,0],
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'dimension': [0.0,0.0,0.0],
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'origin': [0.0,0.0,0.0],
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info = {'resolution': numpy.array([0,0,0]),
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'dimension': numpy.array([0.0,0.0,0.0]),
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'origin': numpy.array([0.0,0.0,0.0]),
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'homogenization': 1,
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}
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new_header = []
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for header in headers:
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headitems = map(str.lower,header.split())
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if headitems[0] in mappings.keys():
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if headitems[0] in identifiers.keys():
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for i in xrange(len(identifiers[headitems[0]])):
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info[headitems[0]][i] = mappings[headitems[0]](headitems[headitems.index(identifiers[headitems[0]][i])+1])
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info[headitems[0]][i] = \
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mappings[headitems[0]](headitems[headitems.index(identifiers[headitems[0]][i])+1])
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else:
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info[headitems[0]] = mappings[headitems[0]](headitems[1])
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if info['resolution'] == [0,0,0]:
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print 'no resolution info found.'
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sys.exit(1)
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if info['dimension'] == [0.0,0.0,0.0]:
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print 'no dimension info found.'
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sys.exit(1)
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if numpy.all(info['resolution'] == 0):
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file['croak'].write('no resolution info found.\n')
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continue
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if numpy.all(info['dimension'] == 0.0):
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file['croak'].write('no dimension info found.\n')
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continue
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print 'resolution: %s'%(' x '.join(map(str,info['resolution'])))
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print 'dimension: %s'%(' x '.join(map(str,info['dimension'])))
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print 'origin: %s'%(' : '.join(map(str,info['origin'])))
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file['croak'].write('resolution: %s\n'%(' x '.join(map(str,info['resolution']))) + \
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'dimension: %s\n'%(' x '.join(map(str,info['dimension']))) + \
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'origin: %s\n'%(' : '.join(map(str,info['origin']))) + \
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'homogenization: %i\n'%info['homogenization'])
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dx = info['dimension'][0]/info['resolution'][0]
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new_header.append("resolution\ta %i\tb %i\tc %i\n"%(
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info['resolution'][0],
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info['resolution'][1],
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info['resolution'][2],))
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new_header.append("dimension\tx %f\ty %f\tz %f\n"%(
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info['dimension'][0],
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info['dimension'][1],
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info['dimension'][2],))
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new_header.append("origin\tx %f\ty %f\tz %f\n"%(
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info['origin'][0],
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info['origin'][1],
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info['origin'][2],))
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new_header.append("homogenization\t%i\n"%info['homogenization'])
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data = {'scalar':{'perimeter':numpy.zeros(info['resolution'],'i'),
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'distance':numpy.zeros(info['resolution'],'i')}}
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structure = numpy.zeros(info['resolution'],'i')
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i = 0
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for line in content:
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for item in map(int,line.split()):
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data['scalar']['perimeter'][i%info['resolution'][0],(i/info['resolution'][0])%info['resolution'][1],i/info['resolution'][0]/info['resolution'][1]] = item
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structure[i%info['resolution'][0],
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(i/info['resolution'][0])%info['resolution'][1],
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i/info['resolution'][0] /info['resolution'][1]] = item
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i += 1
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# data['scalar']['perimeter'] = numpy.where(ndimage.morphology.grey_dilation(data['scalar']['perimeter'],size=(3,3,3))-data['scalar']['perimeter']>0,0,1)
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neighborhood = neighborhoods[options.neighborhood]
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convoluted = numpy.empty([len(neighborhood)]+list(info['resolution']+2),'i')
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microstructure = periodic_3Dpad(structure)
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FDstencil_x = numpy.zeros([3,3,3])
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FDstencil_x[:,1,1] = [-1,0,1]
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FDstencil_y = numpy.zeros([3,3,3])
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FDstencil_y[1,:,1] = [-1,0,1]
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FDstencil_z = numpy.zeros([3,3,3])
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FDstencil_z[1,1,:] = [-1,0,1]
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data['scalar']['perimeter'] = numpy.where(numpy.abs(ndimage.convolve(data['scalar']['perimeter'], FDstencil_x)) + numpy.abs(ndimage.convolve(data['scalar']['perimeter'], FDstencil_y)) + numpy.abs(ndimage.convolve(data['scalar']['perimeter'], FDstencil_z))>0,0,1)
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data['scalar']['distance'] = skfmm.distance(data['scalar']['perimeter'], dx=dx)
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for i,p in enumerate(neighborhood):
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stencil = numpy.zeros((3,3,3),'i')
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stencil[1,1,1] = -1
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stencil[p[0]+1,
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p[1]+1,
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p[2]+1] = 1
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convoluted[i,:,:,:] = ndimage.convolve(microstructure,stencil)
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distance = numpy.ones((len(feature_list),info['resolution'][0],info['resolution'][1],info['resolution'][2]),'d')
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convoluted = numpy.sort(convoluted,axis=0)
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uniques = numpy.zeros(info['resolution'])
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check = numpy.empty(info['resolution'])
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check[:,:,:] = numpy.nan
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for i in xrange(len(neighborhood)):
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uniques += numpy.where(convoluted[i,1:-1,1:-1,1:-1] == check,0,1)
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check = convoluted[i,1:-1,1:-1,1:-1]
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for i,feature_id in enumerate(feature_list):
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distance[i,:,:,:] = numpy.where(uniques > features[feature_id]['aliens'],0.0,1.0)
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for i in xrange(len(feature_list)):
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distance[i,:,:,:] = ndimage.morphology.distance_transform_edt(distance[i,:,:,:])*[max(info['dimension']/info['resolution'])]*3
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for i,feature in enumerate(feature_list):
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formatwidth = int(math.floor(math.log10(distance[i,:,:,:].max())+1))
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# ------------------------------------------ assemble header ---------------------------------------
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output = '%i\theader\n'%(len(new_header))
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output += ''.join(new_header)
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# ------------------------------------- regenerate texture information ----------------------------------
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for z in xrange(info['resolution'][2]):
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for y in xrange(info['resolution'][1]):
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output += {True:' ',False:'\n'}[options.twoD].join(map(lambda x: ('%%%ii'%formatwidth)%(round(x)), distance[i,:,y,z])) + '\n'
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# ------------------------------------------ output result ---------------------------------------
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file['output'][i].write(output)
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if file['name'] != 'STDIN':
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file['output'][i].close()
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if file['name'] != 'STDIN':
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file['input'].close() # close input geom file
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out = {}
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out['mesh'] = vtk_writeASCII_mesh(info['dimension'],info['resolution'],info['origin'],data)
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for what in out.keys():
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if file['name'] == 'STDIN':
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output(out[what],{},'Stdout')
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else:
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(head,tail) = os.path.split(file['name'])
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vtk = open(os.path.join(head,what+'_'+os.path.splitext(tail)[0]+'.vtk'), 'w')
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output(out[what],{'filepointer':vtk},'File')
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vtk.close()
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