364 lines
20 KiB
Python
364 lines
20 KiB
Python
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#!/usr/bin/env python
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import os,sys,string,itertools,re,time,copy,operator,threading
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import numpy as np
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import damask
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from scipy import spatial
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from collections import defaultdict
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from optparse import OptionParser, OptionGroup, Option, SUPPRESS_HELP
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scriptID = string.replace('$Id: addGrainID.py 2549 2013-07-10 09:13:21Z MPIE\p.eisenlohr $','\n','\\n')
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scriptName = os.path.splitext(scriptID.split()[1])[0]
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#--------------------------------------------------------------------------------------------------
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class extendedOption(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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ACTIONS = Option.ACTIONS + ("extend",)
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STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",)
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TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",)
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ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",)
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def take_action(self, action, dest, opt, value, values, parser):
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if action == "extend":
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lvalue = value.split(",")
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values.ensure_value(dest, []).extend(lvalue)
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else:
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Option.take_action(self, action, dest, opt, value, values, parser)
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# -----------------------------
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class backgroundMessage(threading.Thread):
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# -----------------------------
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def __init__(self):
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threading.Thread.__init__(self)
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self.message = ''
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self.new_message = ''
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self.counter = 0
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self.symbols = ['- ', '\ ', '| ', '/ ',]
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self.waittime = 0.5
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def __quit__(self):
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length = len(self.message) + len(self.symbols[self.counter])
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sys.stderr.write(chr(8)*length + ' '*length + chr(8)*length)
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sys.stderr.write('')
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def run(self):
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while not threading.enumerate()[0]._Thread__stopped:
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time.sleep(self.waittime)
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self.update_message()
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self.__quit__()
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def set_message(self, new_message):
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self.new_message = new_message
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self.print_message()
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def print_message(self):
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length = len(self.message) + len(self.symbols[self.counter])
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sys.stderr.write(chr(8)*length + ' '*length + chr(8)*length) # delete former message
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sys.stderr.write(self.symbols[self.counter] + self.new_message) # print new message
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self.message = self.new_message
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def update_message(self):
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self.counter = (self.counter + 1)%len(self.symbols)
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self.print_message()
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parser = OptionParser(option_class=extendedOption, usage='%prog options [file[s]]', description = """
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Add grain index based on similiarity of crystal lattice orientation.
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""" + string.replace(scriptID,'\n','\\n')
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)
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parser.add_option('-r', '--radius', dest='radius', type='float',
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help = 'search radius')
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parser.add_option('-d', '--disorientation', dest='disorientation', type='float', metavar='ANGLE',
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help = 'disorientation threshold per grain [%default] (degrees)')
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parser.add_option('-s', '--symmetry', dest='symmetry', type='string',
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help = 'crystal symmetry [%default]')
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parser.add_option('-e', '--eulers', dest='eulers', type='string', metavar='LABEL',
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help = 'Euler angles')
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parser.add_option( '--degrees', dest='degrees', action='store_true',
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help = 'Euler angles are given in degrees [%default]')
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parser.add_option('-m', '--matrix', dest='matrix', type='string', metavar='LABEL',
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help = 'orientation matrix')
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parser.add_option('-a', dest='a', type='string', metavar='LABEL',
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help = 'crystal frame a vector')
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parser.add_option('-b', dest='b', type='string', metavar='LABEL',
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help = 'crystal frame b vector')
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parser.add_option('-c', dest='c', type='string', metavar='LABEL',
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help = 'crystal frame c vector')
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parser.add_option('-q', '--quaternion', dest='quaternion', type='string', metavar='LABEL',
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help = 'quaternion')
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parser.add_option('-p', '--position', dest='position', type='string', metavar='LABEL',
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help = 'spatial position of voxel [%default]')
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parser.set_defaults(symmetry = 'cubic')
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parser.set_defaults(position = 'pos')
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parser.set_defaults(degrees = False)
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(options, filenames) = parser.parse_args()
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if options.radius == None:
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parser.error('no radius specified.')
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datainfo = { # list of requested labels per datatype
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'tensor': {'len':9,
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'label':[]},
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'vector': {'len':3,
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'label':[]},
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'quaternion': {'len':4,
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'label':[]},
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}
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if options.eulers != None: datainfo['vector']['label'] += [options.eulers]; input = 'eulers'
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if options.a != None and \
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options.b != None and \
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options.c != None: datainfo['vector']['label'] += [options.a,options.b,options.c]; input = 'frame'
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if options.matrix != None: datainfo['tensor']['label'] += [options.matrix]; input = 'matrix'
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if options.quaternion != None: datainfo['quaternion']['label'] += [options.quaternion]; input = 'quaternion'
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datainfo['vector']['label'] += [options.position]
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toRadians = np.pi/180.0 if options.degrees else 1.0 # rescale degrees to radians
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cos_disorientation = np.cos(options.disorientation/2.0*toRadians)
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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',
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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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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,
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'input':open(name),
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'output':open(name+'_tmp','w'),
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'croak':sys.stderr})
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#--- loop over input files ------------------------------------------------------------------------
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for file in files:
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if file['name'] != 'STDIN': file['croak'].write('\033[1m'+scriptName+'\033[0m: '+file['name']+'\n')
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else: file['croak'].write('\033[1m'+scriptName+'\033[0m\n')
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table = damask.ASCIItable(file['input'],file['output'],buffered = False) # make unbuffered ASCII_table
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table.head_read() # read ASCII header info
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# --------------- figure out columns to process
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column = {}
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missingColumns = False
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for datatype,info in datainfo.items():
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for label in info['label']:
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key = list(set([label, '1_'+label]) & set(table.labels)) # check for intersection with table labels
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if key == []:
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file['croak'].write('column %s not found...\n'%label)
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missingColumns = True # break if label not found
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else:
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column[label] = table.labels.index(key[0]) # remember columns of requested data
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if missingColumns:
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continue
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table.labels_append('grainID_%g'%options.disorientation)
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# ------------------------------------------ assemble header ---------------------------------------
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table.info_append(string.replace(scriptID,'\n','\\n') + '\t' + ' '.join(sys.argv[1:]))
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table.head_write()
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# ------------------------------------------ process data ---------------------------------------
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# ------------------------------------------ build KD tree ---------------------------------------
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# --- start background messaging
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bg = backgroundMessage()
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bg.start()
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bg.set_message('reading positions...')
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backup_readSize = table.__IO__['validReadSize'] # bad hack to circumvent overwriting by readArray...
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backup_labels = table.labels # bad hack...
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table.data_rewind()
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table.data_readArray(range(column[options.position],
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column[options.position]+datainfo['vector']['len'])) # read position vectors
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# file['croak'].write('%i\n'%(len(table.data)))
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grainID = -np.ones(len(table.data),dtype=int)
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start = tick = time.clock()
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bg.set_message('building KD tree...')
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kdtree = spatial.KDTree(copy.deepcopy(table.data))
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# neighborhood = kdtree.query_ball_tree(kdtree,options.radius)
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# file['croak'].write('%.2f seconds\n'%(time.clock()-tick))
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# file['croak'].write('%i points\n'%(len(neighborhood)))
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# ------------------------------------------ assign grain IDs ---------------------------------------
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orientations = [] # quaternions found for grain
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memberCounts = [] # number of voxels in grain
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table.data_rewind()
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table.__IO__['validReadSize'] = backup_readSize # bad hack to circumvent overwriting by readArray...
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table.labels = backup_labels # bad hack...
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p = 0 # point counter
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g = 0 # grain counter
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matchedID = -1
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lastDistance = np.dot(kdtree.data[-1]-kdtree.data[0],kdtree.data[-1]-kdtree.data[0]) # (arbitrarily) use diagonal of cloud
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tick = time.clock()
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while table.data_read(): # read next data line of ASCII table
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if p > 0 and p % 1000 == 0:
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time_delta = (time.clock()-tick) * (len(grainID) - p) / p
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bg.set_message('(%02i:%02i:%02i) processing point %i of %i (grain count %i)...'%(time_delta//3600,time_delta%3600//60,time_delta%60,p,len(grainID),len(orientations)))
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if input == 'eulers':
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o = damask.Orientation(Eulers=toRadians*\
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np.array(map(float,table.data[column[options.eulers]:\
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column[options.eulers]+datainfo['vector']['len']])),
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symmetry=options.symmetry).reduced()
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elif input == 'matrix':
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o = damask.Orientation(matrix=\
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np.array([map(float,table.data[column[options.matrix]:\
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column[options.matrix]+datainfo['tensor']['len']])]).reshape(np.sqrt(datainfo['tensor']['len']),
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np.sqrt(datainfo['tensor']['len'])).transpose(),
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symmetry=options.symmetry).reduced()
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elif input == 'frame':
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o = damask.Orientation(matrix=\
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np.array([map(float,table.data[column[options.a]:\
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column[options.a]+datainfo['vector']['len']] + \
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table.data[column[options.b]:\
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column[options.b]+datainfo['vector']['len']] + \
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table.data[column[options.c]:\
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column[options.c]+datainfo['vector']['len']]
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)]).reshape(3,3),
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symmetry=options.symmetry).reduced()
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elif input == 'quaternion':
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o = damask.Orientation(quaternion=\
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np.array(map(float,table.data[column[options.quaternion]:\
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column[options.quaternion]+datainfo['quaternion']['len']])),
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symmetry=options.symmetry).reduced()
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matched = False
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# check against last matched needs to be really picky. best would be to exclude jumps across the poke (checking distance between last and me?)
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# when walking through neighborhood first check whether grainID of that point has already been tested, if yes, skip!
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if matchedID != -1: # has matched before?
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matched = (o.quaternion.conjugated() * orientations[matchedID].quaternion).w > cos_disorientation
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# if matchedID > 0: # has matched before?
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# thisDistance = np.dot(kdtree.data[p]-kdtree.data[p-1],kdtree.data[p]-kdtree.data[p-1],)
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# if thisDistance < 4.*lastDistance: # about as close as last point pair?
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# disorientation = o.disorientation(orientations[matchedID-1]).quaternion.w # check whether former grainID matches now again
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# matched = disorientation > cos_disorientation
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# lastDistance = thisDistance
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#
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if not matched:
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alreadyChecked = {}
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bestDisorientation = damask.Orientation(quaternion=np.array([0,0,0,1]),symmetry = options.symmetry) # initialize to 180 deg rotation as worst case
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for i in kdtree.query_ball_point(kdtree.data[p],options.radius): # check all neighboring points
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gID = grainID[i]
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if gID != -1 and gID not in alreadyChecked: # an already indexed point belonging to a grain not yet tested?
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alreadyChecked[gID] = True # remember not to check again
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disorientation = o.disorientation(orientations[gID]) # compare against that grain's orientation
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if disorientation.quaternion.w > cos_disorientation and \
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disorientation.quaternion.w >= bestDisorientation.quaternion.w: # within disorientation threshold and better than current best?
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matched = True
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matchedID = gID # remember that grain
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# file['croak'].write('%i %f '%(matchedID,disorientation.quaternion.w))
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bestDisorientation = disorientation
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if not matched: # no match -> new grain found
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memberCounts += [1] # start new membership counter
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orientations += [o] # initialize with current orientation
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matchedID = g
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g += 1 # increment grain counter
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# file['croak'].write('+')
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else: # did match existing grain
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memberCounts[matchedID] += 1
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# file['croak'].write('got back %s is close by %f to %s\n'%(np.degrees(bestQ.asEulers()),np.degrees(2*np.arccos(bestDisorientation.quaternion.w)),np.degrees(bestFormerQ.asEulers())))
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# file['croak'].write('.%i %s'%(matchedID, orientations[matchedID-1].quaternion))
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# M = (1. - 1./memberCounts[matchedID-1]) * bestFormerQ.asM() + 1./memberCounts[matchedID-1] * bestQ.asM() # 4x4 matrix holding weighted quaternion outer products per grain
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# w,v = np.linalg.eigh(M)
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# avgQ = damask.Orientation(quaternion=v[:,w.argmax()],symmetry=options.symmetry)
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# file['croak'].write('new avg has misori of %f\n'%np.degrees(2*np.arccos(orientations[matchedID-1].disorientation(avgQ)[0].quaternion.w)))
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# orientations[matchedID-1].quaternion = damask.Quaternion(v[:,w.argmax()])
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# orientations[matchedID-1] = damask.Orientation(quaternion = bestDisorientation.quaternion**(1./memberCounts[matchedID-1]) \
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# * orientations[matchedID-1].quaternion,
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# symmetry = options.symmetry) # adjust average orientation taking newest member into account
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# file['croak'].write(' stored --> %s\n'%(np.degrees(orientations[matchedID-1].quaternion.asEulers())))
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# file['croak'].write('.')
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grainID[p] = matchedID # remember grain index assigned to point
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p += 1 # increment point
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bg.set_message('identifying similar orientations among %i grains...'%(len(orientations)))
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memberCounts = np.array(memberCounts)
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similarOrientations = [[] for i in xrange(len(orientations))]
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for i,orientation in enumerate(orientations): # compare each identified orientation...
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for j in xrange(i+1,len(orientations)): # ...against all others that were defined afterwards
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if orientation.disorientation(orientations[j]).quaternion.w > cos_disorientation: # similar orientations in both grainIDs?
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similarOrientations[i].append(j) # remember in upper triangle...
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similarOrientations[j].append(i) # ...and lower triangle of matrix
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|
|
if similarOrientations[i] != []:
|
||
|
|
bg.set_message('grainID %i is as: %s'%(i,' '.join(map(lambda x:str(x),similarOrientations[i]))))
|
||
|
|
|
||
|
|
stillShifting = True
|
||
|
|
while stillShifting:
|
||
|
|
stillShifting = False
|
||
|
|
tick = time.clock()
|
||
|
|
|
||
|
|
for p,gID in enumerate(grainID): # walk through all points
|
||
|
|
if p > 0 and p % 1000 == 0:
|
||
|
|
|
||
|
|
time_delta = (time.clock()-tick) * (len(grainID) - p) / p
|
||
|
|
bg.set_message('(%02i:%02i:%02i) shifting ID of point %i out of %i (grain count %i)...'%(time_delta//3600,time_delta%3600//60,time_delta%60,p,len(grainID),len(orientations)))
|
||
|
|
if similarOrientations[gID] != []: # orientation of my grainID is similar to someone else?
|
||
|
|
similarNeighbors = defaultdict(int) # dict holding frequency of neighboring grainIDs that share my orientation (freq info not used...)
|
||
|
|
for i in kdtree.query_ball_point(kdtree.data[p],options.radius): # check all neighboring points
|
||
|
|
if grainID[i] in similarOrientations[gID]: # neighboring point shares my orientation?
|
||
|
|
similarNeighbors[grainID[i]] += 1 # remember its grainID
|
||
|
|
if similarNeighbors != {}: # found similar orientation(s) in neighborhood
|
||
|
|
candidates = np.array([gID]+similarNeighbors.keys()) # possible replacement grainIDs for me
|
||
|
|
grainID[p] = candidates[np.argsort(memberCounts[candidates])[-1]] # adopt ID that is most frequent in overall dataset
|
||
|
|
memberCounts[gID] -= 1 # my former ID loses one fellow
|
||
|
|
memberCounts[grainID[p]] += 1 # my new ID gains one fellow
|
||
|
|
bg.set_message('%i:%i --> %i'%(p,gID,grainID[p])) # report switch of grainID
|
||
|
|
stillShifting = True
|
||
|
|
|
||
|
|
table.data_rewind()
|
||
|
|
p = 0
|
||
|
|
while table.data_read(): # read next data line of ASCII table
|
||
|
|
table.data_append(1+grainID[p]) # add grain ID
|
||
|
|
table.data_write() # output processed line
|
||
|
|
p += 1
|
||
|
|
|
||
|
|
bg.set_message('done after %i seconds'%(time.clock()-start))
|
||
|
|
|
||
|
|
# for i,o in enumerate(orientations): # croak about average grain orientations
|
||
|
|
# file['croak'].write('%i: %s\n'%(i,' '.join(map(str,o.quaternion.asEulers()))))
|
||
|
|
|
||
|
|
# ------------------------------------------ output result ---------------------------------------
|
||
|
|
|
||
|
|
table.output_flush() # just in case of buffered ASCII table
|
||
|
|
table.close() # close ASCII tables
|
||
|
|
if file['name'] != 'STDIN':
|
||
|
|
os.rename(file['name']+'_tmp',file['name']) # overwrite old one with tmp new
|