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DAMASK_EICMD
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Polishing 

- keep microstructure as integer
- avoid constant reshape
- IMPORTANT: random order has changed!
This commit is contained in:
Martin Diehl 2020-03-20 00:36:48 +01:00
parent 0556827f29
commit 064dabe34b
2 changed files with 50 additions and 60 deletions
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2
PRIVATE

@ -1 +1 @@
Subproject commit 05ac971ce58fc399dd99be9151b7d61d049aec42
Subproject commit 1b08e028a6177d03a0d4202e5feed2ec29f91c19

44
processing/pre/seeds_fromRandom.py
View File

@ -128,7 +128,6 @@ random.seed(options.randomSeed)
for name in filenames:
damask.util.report(scriptName,name)
# --- sanity checks -------------------------------------------------------------------------
remarks = []
errors = []
if any(grid==0):
@ -144,29 +143,27 @@ for name in filenames:
damask.util.croak(errors)
sys.exit()
# --- do work ------------------------------------------------------------------------------------
grainEuler = np.random.rand(3,options.N) # create random Euler triplets
grainEuler[0,:] *= 360.0 # phi_1 is uniformly distributed
grainEuler[1,:] = np.degrees(np.arccos(2*grainEuler[1,:]-1)) # cos(Phi) is uniformly distributed
grainEuler[2,:] *= 360.0 # phi_2 is uniformly distributed
eulers = np.random.rand(options.N,3) # create random Euler triplets
eulers[:,0] *= 360.0 # phi_1 is uniformly distributed
eulers[:,1] = np.degrees(np.arccos(2*eulers[:,1]-1)) # cos(Phi) is uniformly distributed
eulers[:,2] *= 360.0 # phi_2 is uniformly distributed
if not options.selective:
n = np.maximum(np.ones(3),np.array(grid*fraction),
dtype=int,casting='unsafe') # find max grid indices within fraction
n = np.maximum(np.ones(3),np.array(grid*fraction),dtype=int,casting='unsafe') # find max grid indices within fraction
meshgrid = np.meshgrid(*map(np.arange,n),indexing='ij') # create a meshgrid within fraction
coords = np.vstack((meshgrid[0],meshgrid[1],meshgrid[2])).reshape(3,n.prod()).T # assemble list of 3D coordinates
seeds = ((random.sample(list(coords),options.N)+np.random.random(options.N*3).reshape(options.N,3))\
coords = np.vstack((meshgrid[0],meshgrid[1],meshgrid[2])).reshape(n.prod(),3) # assemble list of 3D coordinates
seeds = (random.sample(coords.tolist(),options.N)+np.random.rand(options.N,3))\
/ \
(n/fraction)).T # pick options.N of those, rattle position,
(n/fraction) # pick options.N of those, rattle position,
# and rescale to fall within fraction
else:
seeds = np.zeros((options.N,3),dtype=float) # seed positions array
seeds = np.zeros((options.N,3)) # seed positions array
seeds[0] = np.random.random(3)*grid/max(grid)
i = 1 # start out with one given point
if i%(options.N/100.) < 1: damask.util.croak('.',False)
while i < options.N:
candidates = np.random.random(options.numCandidates*3).reshape(options.numCandidates,3)
candidates = np.random.rand(options.numCandidates,3)
distances = kdtree_search(seeds[:i],candidates)
best = distances.argmax()
if distances[best] > options.distance: # require minimum separation
@ -175,26 +172,19 @@ for name in filenames:
if i%(options.N/100.) < 1: damask.util.croak('.',False)
damask.util.croak('')
seeds = seeds.T # prepare shape for stacking
if options.weights:
weights = [np.random.uniform(low = 0, high = options.max, size = options.N)] if options.max > 0.0 \
else [np.random.normal(loc = options.mean, scale = options.sigma, size = options.N)]
data = np.transpose(np.vstack(tuple([seeds,
grainEuler,
np.arange(options.microstructure,options.microstructure + options.N),
] + (weights if options.weights else [])
)))
comments = [scriptID + ' ' + ' '.join(sys.argv[1:]),
'grid\ta {}\tb {}\tc {}'.format(*grid),
'randomSeed\t{}'.format(options.randomSeed),
]
shapes = {'pos':(3,),'euler':(3,),'microstructure':(1,)}
if options.weights: shapes['weight'] = (1,)
table = damask.Table(np.hstack((seeds,eulers)),{'pos':(3,),'euler':(3,)},comments)
table.add('microstructure',np.arange(options.microstructure,options.microstructure + options.N,dtype=int))
if options.weights:
weights = np.random.uniform(low = 0, high = options.max, size = options.N) if options.max > 0.0 \
else np.random.normal(loc = options.mean, scale = options.sigma, size = options.N)
table.add('weight',weights)
table = damask.Table(data,shapes,comments)
table.to_ASCII(sys.stdout if name is None else name)