diff --git a/processing/pre/geom_fromVoronoiTessellation.py b/processing/pre/geom_fromVoronoiTessellation.py index 84f915292..4c07e69e2 100755 --- a/processing/pre/geom_fromVoronoiTessellation.py +++ b/processing/pre/geom_fromVoronoiTessellation.py @@ -30,6 +30,45 @@ def meshgrid2(*arrs): ans.insert(0,arr2) return tuple(ans) +def laguerreTessellation(undeformed, coords): + bestdist = np.ones(len(undeformed)) * np.finfo('d').max + bestseed = np.zeros(len(undeformed)) + + for i,seed in enumerate(coords): + for copy in np.array([[1, 0, 0, ], + [0, 1, 0, ], + [0, 0, 1, ], + [-1, 0, 0, ], + [0, -1, 0, ], + [0, 0, -1, ], + [1, 1, 0, ], + [1, 0, 1, ], + [0, 1, 1, ], + [-1, 1, 0, ], + [-1, 0, 1, ], + [0, -1, 1, ], + [-1, -1, 0, ], + [-1, 0, -1, ], + [0, -1, -1, ], + [1, -1, 0, ], + [1, 0, -1, ], + [0, 1, -1, ], + [1, 1, 1, ], + [-1, 1, 1, ], + [1, -1, 1, ], + [1, 1, -1, ], + [-1, -1, -1, ], + [1, -1, -1, ], + [-1, 1, -1, ], + [-1, -1, 1, ]]).astype(float): + + diff = undeformed - np.repeat((seed+info['size']*copy).reshape(3,1),len(undeformed),axis=1).T + dist = np.sum(diff*diff,axis=1) - weights[i] + + bestseed = np.where(dist < bestdist, np.ones(len(undeformed))*(i+1),bestseed) + bestdist = np.where(dist < bestdist, dist,bestdist) + return bestseed + # -------------------------------------------------------------------- # MAIN @@ -68,6 +107,9 @@ parser.add_option('-c', '--configuration', dest='config', action='store_true', help='output material configuration [%default]') parser.add_option('--secondphase', type='float', dest='secondphase', metavar= 'float', help='volume fraction of randomly distribute second phase [%default]') +parser.add_option('--laguerre', dest='laguerre', action='store_true', + help='for weighted voronoi (Laguerre) tessellation [%default]') + parser.set_defaults(grid = (0,0,0)) parser.set_defaults(size = (0.0,0.0,0.0)) @@ -77,6 +119,7 @@ parser.set_defaults(phase = 1) parser.set_defaults(crystallite = 1) parser.set_defaults(secondphase = 0.0) parser.set_defaults(config = False) +parser.set_defaults(laguerre = False) (options,filenames) = parser.parse_args() @@ -105,22 +148,29 @@ for file in files: table = damask.ASCIItable(file['input'],file['output'],buffered = False) table.head_read() - coordsCol = table.labels_index('1_coords') - if coordsCol < 0: - coordsCol = table.labels_index('x') # try if file is in legacy format - if coordsCol < 0: - file['croak'].write('column 1_coords/x not found...\n') - continue + labels = [] + if np.any(table.labels_index(['1_coords','2_coords','3_coords'])) == -1: + parser.error("missing seed coordinate column") + else: + labels += ['1_coords','2_coords','3_coords'] - eulerCol = table.labels_index('phi1') hasEulers = np.all(table.labels_index(['phi1','Phi','phi2'])) != -1 - grainCol = table.labels_index('microstructure') - hasGrains = grainCol != -1 - - table.data_readArray() - coords = table.data[:,coordsCol:coordsCol+3] - eulers = table.data[:,eulerCol:eulerCol+3] if hasEulers else np.zeros(3*len(coords)) - grain = table.data[:,grainCol] if hasGrains else 1+np.arange(len(eulers)) + if hasEulers: + labels += ['phi1','Phi','phi2'] + + hasGrains = table.labels_index('microstructure') != -1 + if hasGrains: + labels += ['microstructure'] + + hasWeight = table.labels_index('weight') != -1 + if hasWeight: + labels += ['weight'] + + table.data_readArray(labels) + coords = table.data[:,table.labels_index(['1_coords','2_coords','3_coords'])] + eulers = table.data[:,table.labels_index(['phi1','Phi','phi2'])] if hasEulers else np.zeros(3*len(coords)) + grain = table.data[:,table.labels_index('microstructure')] if hasGrains else 1+np.arange(len(coords)) + weights = table.data[:,table.labels_index('weight')] if hasWeight else np.zeros(len(coords)) grainIDs = np.unique(grain).astype('i') @@ -179,7 +229,6 @@ for file in files: continue #--- prepare data --------------------------------------------------------------------------------- - coords = (coords*info['size']).T eulers = eulers.T #--- switch according to task --------------------------------------------------------------------- @@ -208,14 +257,20 @@ for file in files: x = (np.arange(info['grid'][0])+0.5)*info['size'][0]/info['grid'][0] y = (np.arange(info['grid'][1])+0.5)*info['size'][1]/info['grid'][1] z = (np.arange(info['grid'][2])+0.5)*info['size'][2]/info['grid'][2] - undeformed = np.vstack(map(np.ravel, meshgrid2(x, y, z))) - - file['croak'].write('tessellating...\n') - indices = damask.core.math.periodicNearestNeighbor(\ - info['size'],\ - np.eye(3),\ - undeformed,coords)//3**3 + 1 # floor division to kill periodic images - indices = grain[indices-1] + + if options.laguerre == False : + coords = (coords*info['size']).T + undeformed = np.vstack(map(np.ravel, meshgrid2(x, y, z))) + + file['croak'].write('tessellating...\n') + indices = damask.core.math.periodicNearestNeighbor(\ + info['size'],\ + np.eye(3),\ + undeformed,coords)//3**3 + 1 # floor division to kill periodic images + indices = grain[indices-1] + else : + undeformed = np.vstack(np.meshgrid(x, y, z)).reshape(3,-1).T + indices = laguerreTessellation(undeformed, coords) newInfo['microstructures'] = info['microstructures'] for i in grainIDs: diff --git a/processing/pre/seeds_fromRandom.py b/processing/pre/seeds_fromRandom.py index 8272db468..fb181613a 100755 --- a/processing/pre/seeds_fromRandom.py +++ b/processing/pre/seeds_fromRandom.py @@ -25,14 +25,28 @@ parser.add_option('-g','--grid', dest='grid', type='int', nargs=3, metavar='int help='min a,b,c grid of hexahedral box %default') parser.add_option('-r', '--rnd', dest='randomSeed', type='int', metavar='int', \ help='seed of random number generator [%default]') +parser.add_option('-w', '--weights', dest='weights', action='store_true', + help = 'assign random weigts (Gaussian Distribution) to seed points for laguerre tessellation [%default]') +parser.add_option('--mean', dest='mean', type='float', metavar='float', \ + help='mean of Gaussian Distribution for weights [%default]') +parser.add_option('--sigma', dest='sigma', type='float', metavar='float', \ + help='standard deviation of Gaussian Distribution for weights [%default]') + + parser.set_defaults(randomSeed = None) parser.set_defaults(grid = (16,16,16)) parser.set_defaults(N = 20) +parser.set_defaults(weights=False) +parser.set_defaults(mean = 0.0) +parser.set_defaults(sigma = 1.0) + (options,filename) = parser.parse_args() options.grid = np.array(options.grid) +labels = "1_coords\t2_coords\t3_coords\tphi1\tPhi\tphi2" + # ------------------------------------------ setup file handle ------------------------------------- if filename == []: file = {'output':sys.stdout, 'croak':sys.stderr} @@ -48,6 +62,8 @@ if options.N > gridSize: options.N = gridSize if options.randomSeed == None: options.randomSeed = int(os.urandom(4).encode('hex'), 16) + + np.random.seed(options.randomSeed) # init random generators random.seed(options.randomSeed) @@ -76,14 +92,24 @@ seeds[1,:] = (np.mod(seedpoints// options.grid[0] ,options.grid[ seeds[2,:] = (np.mod(seedpoints//(options.grid[1]*options.grid[0]),options.grid[2])\ +np.random.random())/options.grid[2] +table = np.transpose(np.concatenate((seeds,grainEuler),axis = 0)) + +if options.weights : + weight = np.random.normal(loc=options.mean, scale=options.sigma, size=options.N) + weight /= np.sum(weight) + table = np.append(table, weight.reshape(options.N,1), axis=1) + labels += "\tweight" + + + header = ["5\theader", scriptID + " " + " ".join(sys.argv[1:]), "grid\ta {}\tb {}\tc {}".format(options.grid[0],options.grid[1],options.grid[2]), "microstructures\t{}".format(options.N), "randomSeed\t{}".format(options.randomSeed), - "1_coords\t2_coords\t3_coords\tphi1\tPhi\tphi2", + "%s"%labels, ] for line in header: file['output'].write(line+"\n") -np.savetxt(file['output'],np.transpose(np.concatenate((seeds,grainEuler),axis = 0)),fmt='%10.6f',delimiter='\t') +np.savetxt(file['output'], table, fmt='%10.6f', delimiter='\t')