added options for laguerrre tessellation
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Tias Maiti
parent
58b3d017bd
commit
ce0675f359
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@ -30,6 +30,45 @@ def meshgrid2(*arrs):
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ans.insert(0,arr2)
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return tuple(ans)
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def laguerreTessellation(undeformed, coords):
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bestdist = np.ones(len(undeformed)) * np.finfo('d').max
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bestseed = np.zeros(len(undeformed))
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for i,seed in enumerate(coords):
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for copy in np.array([[1, 0, 0, ],
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[0, 1, 0, ],
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[0, 0, 1, ],
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[-1, 0, 0, ],
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[0, -1, 0, ],
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[0, 0, -1, ],
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[1, 1, 0, ],
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[1, 0, 1, ],
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[0, 1, 1, ],
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[-1, 1, 0, ],
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[-1, 0, 1, ],
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[0, -1, 1, ],
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[-1, -1, 0, ],
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[-1, 0, -1, ],
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[0, -1, -1, ],
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[1, -1, 0, ],
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[1, 0, -1, ],
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[0, 1, -1, ],
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[1, 1, 1, ],
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[-1, 1, 1, ],
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[1, -1, 1, ],
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[1, 1, -1, ],
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[-1, -1, -1, ],
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[1, -1, -1, ],
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[-1, 1, -1, ],
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[-1, -1, 1, ]]).astype(float):
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diff = undeformed - np.repeat((seed+info['size']*copy).reshape(3,1),len(undeformed),axis=1).T
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dist = np.sum(diff*diff,axis=1) - weights[i]
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bestseed = np.where(dist < bestdist, np.ones(len(undeformed))*(i+1),bestseed)
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bestdist = np.where(dist < bestdist, dist,bestdist)
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return bestseed
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# --------------------------------------------------------------------
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# MAIN
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@ -68,6 +107,9 @@ parser.add_option('-c', '--configuration', dest='config', action='store_true',
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help='output material configuration [%default]')
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parser.add_option('--secondphase', type='float', dest='secondphase', metavar= 'float',
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help='volume fraction of randomly distribute second phase [%default]')
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parser.add_option('--laguerre', dest='laguerre', action='store_true',
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help='for weighted voronoi (Laguerre) tessellation [%default]')
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parser.set_defaults(grid = (0,0,0))
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parser.set_defaults(size = (0.0,0.0,0.0))
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@ -77,6 +119,7 @@ parser.set_defaults(phase = 1)
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parser.set_defaults(crystallite = 1)
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parser.set_defaults(secondphase = 0.0)
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parser.set_defaults(config = False)
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parser.set_defaults(laguerre = False)
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(options,filenames) = parser.parse_args()
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@ -105,22 +148,29 @@ for file in files:
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table = damask.ASCIItable(file['input'],file['output'],buffered = False)
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table.head_read()
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coordsCol = table.labels_index('1_coords')
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if coordsCol < 0:
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coordsCol = table.labels_index('x') # try if file is in legacy format
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if coordsCol < 0:
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file['croak'].write('column 1_coords/x not found...\n')
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continue
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labels = []
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if np.any(table.labels_index(['1_coords','2_coords','3_coords'])) == -1:
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parser.error("missing seed coordinate column")
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else:
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labels += ['1_coords','2_coords','3_coords']
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eulerCol = table.labels_index('phi1')
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hasEulers = np.all(table.labels_index(['phi1','Phi','phi2'])) != -1
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grainCol = table.labels_index('microstructure')
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hasGrains = grainCol != -1
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table.data_readArray()
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coords = table.data[:,coordsCol:coordsCol+3]
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eulers = table.data[:,eulerCol:eulerCol+3] if hasEulers else np.zeros(3*len(coords))
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grain = table.data[:,grainCol] if hasGrains else 1+np.arange(len(eulers))
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if hasEulers:
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labels += ['phi1','Phi','phi2']
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hasGrains = table.labels_index('microstructure') != -1
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if hasGrains:
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labels += ['microstructure']
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hasWeight = table.labels_index('weight') != -1
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if hasWeight:
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labels += ['weight']
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table.data_readArray(labels)
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coords = table.data[:,table.labels_index(['1_coords','2_coords','3_coords'])]
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eulers = table.data[:,table.labels_index(['phi1','Phi','phi2'])] if hasEulers else np.zeros(3*len(coords))
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grain = table.data[:,table.labels_index('microstructure')] if hasGrains else 1+np.arange(len(coords))
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weights = table.data[:,table.labels_index('weight')] if hasWeight else np.zeros(len(coords))
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grainIDs = np.unique(grain).astype('i')
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@ -179,7 +229,6 @@ for file in files:
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continue
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#--- prepare data ---------------------------------------------------------------------------------
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coords = (coords*info['size']).T
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eulers = eulers.T
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#--- switch according to task ---------------------------------------------------------------------
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@ -208,14 +257,20 @@ for file in files:
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x = (np.arange(info['grid'][0])+0.5)*info['size'][0]/info['grid'][0]
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y = (np.arange(info['grid'][1])+0.5)*info['size'][1]/info['grid'][1]
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z = (np.arange(info['grid'][2])+0.5)*info['size'][2]/info['grid'][2]
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undeformed = np.vstack(map(np.ravel, meshgrid2(x, y, z)))
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file['croak'].write('tessellating...\n')
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indices = damask.core.math.periodicNearestNeighbor(\
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info['size'],\
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np.eye(3),\
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undeformed,coords)//3**3 + 1 # floor division to kill periodic images
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indices = grain[indices-1]
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if options.laguerre == False :
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coords = (coords*info['size']).T
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undeformed = np.vstack(map(np.ravel, meshgrid2(x, y, z)))
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file['croak'].write('tessellating...\n')
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indices = damask.core.math.periodicNearestNeighbor(\
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info['size'],\
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np.eye(3),\
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undeformed,coords)//3**3 + 1 # floor division to kill periodic images
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indices = grain[indices-1]
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else :
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undeformed = np.vstack(np.meshgrid(x, y, z)).reshape(3,-1).T
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indices = laguerreTessellation(undeformed, coords)
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newInfo['microstructures'] = info['microstructures']
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for i in grainIDs:
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@ -25,14 +25,28 @@ parser.add_option('-g','--grid', dest='grid', type='int', nargs=3, metavar='int
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help='min a,b,c grid of hexahedral box %default')
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parser.add_option('-r', '--rnd', dest='randomSeed', type='int', metavar='int', \
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help='seed of random number generator [%default]')
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parser.add_option('-w', '--weights', dest='weights', action='store_true',
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help = 'assign random weigts (Gaussian Distribution) to seed points for laguerre tessellation [%default]')
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parser.add_option('--mean', dest='mean', type='float', metavar='float', \
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help='mean of Gaussian Distribution for weights [%default]')
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parser.add_option('--sigma', dest='sigma', type='float', metavar='float', \
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help='standard deviation of Gaussian Distribution for weights [%default]')
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parser.set_defaults(randomSeed = None)
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parser.set_defaults(grid = (16,16,16))
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parser.set_defaults(N = 20)
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parser.set_defaults(weights=False)
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parser.set_defaults(mean = 0.0)
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parser.set_defaults(sigma = 1.0)
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(options,filename) = parser.parse_args()
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options.grid = np.array(options.grid)
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labels = "1_coords\t2_coords\t3_coords\tphi1\tPhi\tphi2"
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# ------------------------------------------ setup file handle -------------------------------------
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if filename == []:
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file = {'output':sys.stdout, 'croak':sys.stderr}
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@ -48,6 +62,8 @@ if options.N > gridSize:
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options.N = gridSize
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if options.randomSeed == None:
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options.randomSeed = int(os.urandom(4).encode('hex'), 16)
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np.random.seed(options.randomSeed) # init random generators
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random.seed(options.randomSeed)
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@ -76,14 +92,24 @@ seeds[1,:] = (np.mod(seedpoints// options.grid[0] ,options.grid[
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seeds[2,:] = (np.mod(seedpoints//(options.grid[1]*options.grid[0]),options.grid[2])\
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+np.random.random())/options.grid[2]
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table = np.transpose(np.concatenate((seeds,grainEuler),axis = 0))
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if options.weights :
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weight = np.random.normal(loc=options.mean, scale=options.sigma, size=options.N)
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weight /= np.sum(weight)
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table = np.append(table, weight.reshape(options.N,1), axis=1)
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labels += "\tweight"
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header = ["5\theader",
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scriptID + " " + " ".join(sys.argv[1:]),
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"grid\ta {}\tb {}\tc {}".format(options.grid[0],options.grid[1],options.grid[2]),
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"microstructures\t{}".format(options.N),
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"randomSeed\t{}".format(options.randomSeed),
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"1_coords\t2_coords\t3_coords\tphi1\tPhi\tphi2",
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"%s"%labels,
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]
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for line in header:
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file['output'].write(line+"\n")
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np.savetxt(file['output'],np.transpose(np.concatenate((seeds,grainEuler),axis = 0)),fmt='%10.6f',delimiter='\t')
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np.savetxt(file['output'], table, fmt='%10.6f', delimiter='\t')
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