task for DREAM.3D if needed
pointwise takeover should not be a problem anymore as reading in takes no time (at least in comparison to addGrainID)
This commit is contained in:
Martin Diehl
parent
a8e8b75cc0
commit
9fa2553af4
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@ -1,176 +0,0 @@
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#!/usr/bin/env python3
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# -*- coding: UTF-8 no BOM -*-
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import os,sys,copy
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import numpy as np
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import damask
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from optparse import OptionParser
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from scipy import spatial
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scriptName = os.path.splitext(os.path.basename(__file__))[0]
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scriptID = ' '.join([scriptName,damask.version])
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parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [ASCIItable(s)]', description = """
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Add grain index based on similiarity of crystal lattice orientation.
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""", version = scriptID)
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parser.add_option('-r',
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'--radius',
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dest = 'radius',
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type = 'float', metavar = 'float',
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help = 'search radius')
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parser.add_option('-d',
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'--disorientation',
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dest = 'disorientation',
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type = 'float', metavar = 'float',
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help = 'disorientation threshold in degrees [%default]')
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parser.add_option('-s',
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'--symmetry',
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dest = 'symmetry', type = 'choice', choices = damask.Symmetry.lattices[1:],
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metavar = 'string',
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help = 'crystal symmetry [%default] {{{}}} '.format(', '.join(damask.Symmetry.lattices[1:])))
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parser.add_option('-o',
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'--orientation',
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dest = 'quaternion',
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metavar = 'string',
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help = 'label of crystal orientation given as unit quaternion [%default]')
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parser.add_option('-p',
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'--pos', '--position',
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dest = 'pos',
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metavar = 'string',
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help = 'label of coordinates [%default]')
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parser.add_option('--quiet',
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dest='verbose',
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action = 'store_false',
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help = 'hide status bar (useful when piping to file)')
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parser.set_defaults(disorientation = 5,
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verbose = True,
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quaternion = 'orientation',
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symmetry = damask.Symmetry.lattices[-1],
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pos = 'pos',
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)
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(options, filenames) = parser.parse_args()
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if options.radius is None:
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parser.error('no radius specified.')
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cos_disorientation = np.cos(np.radians(options.disorientation/2.)) # cos of half the disorientation angle
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# --- loop over input files -------------------------------------------------------------------------
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if filenames == []: filenames = [None]
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for name in filenames:
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try: table = damask.ASCIItable(name = name,
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buffered = False)
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except: continue
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damask.util.report(scriptName,name)
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# ------------------------------------------ read header -------------------------------------------
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table.head_read()
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# ------------------------------------------ sanity checks -----------------------------------------
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errors = []
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remarks = []
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if not 3 >= table.label_dimension(options.pos) >= 1:
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errors.append('coordinates "{}" need to have one, two, or three dimensions.'.format(options.pos))
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if not np.all(table.label_dimension(options.quaternion) == 4):
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errors.append('input "{}" does not have dimension 4.'.format(options.quaternion))
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else: column = table.label_index(options.quaternion)
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if remarks != []: damask.util.croak(remarks)
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if errors != []:
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damask.util.croak(errors)
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table.close(dismiss = True)
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continue
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# ------------------------------------------ assemble header ---------------------------------------
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table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
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table.labels_append('grainID_{}@{:g}'.format(options.quaternion,options.disorientation)) # report orientation source and disorientation
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table.head_write()
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# ------------------------------------------ build KD tree -----------------------------------------
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table.data_readArray(options.pos) # read position vectors
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grainID = -np.ones(len(table.data),dtype=int)
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Npoints = table.data.shape[0]
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kdtree = spatial.KDTree(copy.deepcopy(table.data))
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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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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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table.data_rewind()
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while table.data_read(): # read next data line of ASCII table
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if options.verbose and Npoints > 100 and p%(Npoints//100) == 0: # report in 1% steps if possible and avoid modulo by zero
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damask.util.progressBar(iteration=p,total=Npoints)
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o = damask.Orientation(quaternion = np.array(list(map(float,table.data[column:column+4]))),
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symmetry = options.symmetry).reduced()
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matched = False
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alreadyChecked = {}
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candidates = []
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bestDisorientation = damask.Quaternion([0,0,0,1]) # 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: # 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],SST = False)[0] # compare against other orientation
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if disorientation.quaternion.q > cos_disorientation: # within threshold ...
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candidates.append(gID) # remember as potential candidate
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if disorientation.quaternion.q >= bestDisorientation.q: # ... and better than current best?
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matched = True
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matchedID = gID # remember that grain
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bestDisorientation = disorientation.quaternion
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if matched: # did match existing grain
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memberCounts[matchedID] += 1
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if len(candidates) > 1: # ambiguity in grain identification?
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largestGrain = sorted(candidates,key=lambda x:memberCounts[x])[-1] # find largest among potential candidate grains
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matchedID = largestGrain
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for c in [c for c in candidates if c != largestGrain]: # loop over smaller candidates
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memberCounts[largestGrain] += memberCounts[c] # reassign member count of smaller to largest
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memberCounts[c] = 0
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grainID = np.where(np.in1d(grainID,candidates), largestGrain, grainID) # relabel grid points of smaller candidates as largest one
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else: # no match -> new grain found
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orientations += [o] # initialize with current orientation
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memberCounts += [1] # start new membership counter
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matchedID = g
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g += 1 # increment grain counter
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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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grainIDs = np.where(np.array(memberCounts) > 0)[0] # identify "live" grain identifiers
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packingMap = dict(zip(list(grainIDs),range(len(grainIDs)))) # map to condense into consecutive IDs
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table.data_rewind()
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outputAlive = True
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p = 0
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damask.util.progressBar(iteration=1,total=1)
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while outputAlive and table.data_read(): # read next data line of ASCII table
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table.data_append(1+packingMap[grainID[p]]) # add (condensed) grain ID
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outputAlive = table.data_write() # output processed line
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p += 1
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# ------------------------------------------ output finalization -----------------------------------
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table.close() # close ASCII tables
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