added options for laguerrre tessellation

This commit is contained in:
Tias Maiti 2015-05-02 07:41:14 +00:00
parent 58b3d017bd
commit ce0675f359
2 changed files with 106 additions and 25 deletions

View File

@ -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
if hasEulers:
labels += ['phi1','Phi','phi2']
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))
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 ---------------------------------------------------------------------
@ -208,6 +257,9 @@ 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]
if options.laguerre == False :
coords = (coords*info['size']).T
undeformed = np.vstack(map(np.ravel, meshgrid2(x, y, z)))
file['croak'].write('tessellating...\n')
@ -216,6 +268,9 @@ for file in files:
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:

View File

@ -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')