several improvements
- more error checking - order of points can be arbitrary also for microstructure input - grouping of same orientation/phase combinations
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@ -54,12 +54,14 @@ parser.set_defaults(homogenization = 1,
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(options,filenames) = parser.parse_args()
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input = [ options.quaternion is not None,
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input = [options.quaternion is not None,
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options.microstructure is not None,
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]
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if np.sum(input) != 1:
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parser.error('need either microstructure label or exactly one orientation input format.')
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parser.error('need either microstructure or quaternion (and optionally phase) as input.')
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if options.microstructure is not None and options.phase is not None:
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parser.error('need either microstructure or phase (and mandatory quaternion) as input.')
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if options.axes is not None and not set(options.axes).issubset(set(['x','+x','-x','y','+y','-y','z','+z','-z'])):
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parser.error('invalid axes {} {} {}.'.format(*options.axes))
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@ -106,72 +108,46 @@ for name in filenames:
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origin = mincorner - 0.5*size/grid # shift from cell center to corner
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# ------------------------------------------ process data ------------------------------------------
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colOri = table.label_index(label)+(3-coordDim) # column(s) of orientation data followed by 3 coordinates
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indices = np.lexsort((table.data[:,0],table.data[:,1],table.data[:,2])) # indices of position when sorting x fast, z slow
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microstructure = np.empty(grid,dtype = int) # initialize empty microstructure
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i = 0
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if inputtype == 'microstructure':
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for z in range(grid[2]):
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for y in range(grid[1]):
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for x in range(grid[0]):
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microstructure[x,y,z] = table.data[indices[i],3]
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i+=1
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grain = table.data[:,colOri]
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nGrains = len(np.unique(grain))
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config_header = []
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elif inputtype == 'quaternion':
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colPhase = -1 # column of phase data comes last
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index = np.lexsort((table.data[:,0],table.data[:,1],table.data[:,2])) # index of position when sorting x fast, z slow
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grain = -np.ones(grid.prod(),dtype = int) # initialize empty microstructure
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orientations = [] # orientations
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multiplicity = [] # orientation multiplicity (number of group members)
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phases = [] # phase info
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nGrains = 0 # counter for detected grains
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existingGrains = np.arange(nGrains)
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myPos = 0 # position (in list) of current grid point
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unique,unique_inverse = np.unique(table.data[:,3:8],return_inverse=True,axis=0)
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for z in range(grid[2]):
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for y in range(grid[1]):
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for x in range(grid[0]):
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microstructure[x,y,z] = unique_inverse[indices[i]]+1
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i+=1
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myData = table.data[index[myPos]] # read data for current grid point
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myPhase = int(myData[colPhase])
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o = damask.Rotation(myData[colOri:colOri+4])
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grain[myPos] = nGrains # assign new grain to me ...
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nGrains += 1 # ... and update counter
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orientations.append(o) # store new orientation for future comparison
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multiplicity.append(1) # having single occurrence so far
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phases.append(myPhase) # store phase info for future reporting
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existingGrains = np.arange(nGrains) # update list of existing grains
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myPos += 1
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grain += 1 # offset from starting index 0 to 1
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formatwidth = 1+int(np.log10(nGrains))
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if inputtype == 'microstructure':
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config_header = []
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else:
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config_header = ['<microstructure>']
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for i,phase in enumerate(phases):
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config_header += ['[Grain%s]'%(str(i+1).zfill(formatwidth)),
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for i,data in enumerate(unique):
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config_header += ['[Grain{}]'.format(i+1),
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'crystallite 1',
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'(constituent)\tphase %i\ttexture %s\tfraction 1.0'%(phase,str(i+1).rjust(formatwidth)),
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'(constituent)\tphase {}\ttexture {}\tfraction 1.0'.format(int(data[4]),i+1),
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]
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config_header += ['<texture>']
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for i,orientation in enumerate(orientations):
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config_header += ['[Grain%s]'%(str(i+1).zfill(formatwidth)),
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'(gauss)\tphi1 %g\tPhi %g\tphi2 %g'%tuple(orientation.asEulers(degrees = True)),
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for i,data in enumerate(unique):
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ori = damask.Rotation(data[0:4])
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config_header += ['[Grain{}]'.format(i+1),
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'(gauss)\tphi1 {:g}\tPhi {:g}\tphi2 {:g}'.format(*ori.asEulers(degrees = True)),
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]
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if options.axes is not None: config_header += ['axes\t{} {} {}'.format(*options.axes)]
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header = [scriptID + ' ' + ' '.join(sys.argv[1:])] + config_header + ['origin x {} y {} z {}'.format(*origin)]
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geom = damask.Geom(grain.reshape(grid,order='F'),size,
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header = [scriptID + ' ' + ' '.join(sys.argv[1:])]\
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+ config_header
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geom = damask.Geom(microstructure,size,origin,
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homogenization=options.homogenization,comments=header)
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damask.util.croak(geom)
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