store microstructure as integers
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3caad0bdf4
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0f45559271
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@ -64,8 +64,8 @@ for name in filenames:
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damask.util.croak('poking {} x {} x {} in box {} {} {}...'.format(Nx,Ny,Nz,*box))
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damask.util.croak('poking {} x {} x {} in box {} {} {}...'.format(Nx,Ny,Nz,*box))
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seeds = np.zeros((Nx*Ny*Nz,4),'d')
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seeds = np.zeros((Nx*Ny*Nz,4))
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g = np.zeros(3,'i')
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g = np.zeros(3,dtype=np.int)
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n = 0
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n = 0
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for i in range(Nx):
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for i in range(Nx):
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@ -84,12 +84,13 @@ for name in filenames:
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comments = geom.comments \
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comments = geom.comments \
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+ [scriptID + ' ' + ' '.join(sys.argv[1:]),
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+ [scriptID + ' ' + ' '.join(sys.argv[1:]),
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"poking\ta {}\tb {}\tc {}".format(Nx,Ny,Nz),
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'poking\ta {}\tb {}\tc {}'.format(Nx,Ny,Nz),
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"grid\ta {}\tb {}\tc {}".format(*geom.grid),
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'grid\ta {}\tb {}\tc {}'.format(*geom.grid),
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"size\tx {}\ty {}\tz {}".format(*geom.size),
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'size\tx {}\ty {}\tz {}'.format(*geom.size),
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"origin\tx {}\ty {}\tz {}".format(*geom.origin),
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'origin\tx {}\ty {}\tz {}'.format(*geom.origin),
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"homogenization\t{}".format(geom.homogenization)]
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'homogenization\t{}'.format(geom.homogenization)]
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table = damask.Table(seeds,{'pos':(3,),'microstructure':(1,)},comments)
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table = damask.Table(seeds,{'pos':(3,),'microstructure':(1,)},comments)
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table.set('microstructure',table.get('microstructure').astype(np.int))
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table.to_ASCII(sys.stdout if name is None else \
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table.to_ASCII(sys.stdout if name is None else \
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os.path.splitext(name)[0]+'_poked_{}.seeds'.format(options.N))
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os.path.splitext(name)[0]+'_poked_{}.seeds'.format(options.N))
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@ -145,19 +145,17 @@ for name in filenames:
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eulers = np.random.rand(options.N,3) # create random Euler triplets
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eulers = np.random.rand(options.N,3) # create random Euler triplets
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eulers[:,0] *= 360.0 # phi_1 is uniformly distributed
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eulers[:,0] *= 360.0 # phi_1 is uniformly distributed
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eulers[:,1] = np.degrees(np.arccos(2*eulers[:,1]-1)) # cos(Phi) is uniformly distributed
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eulers[:,1] = np.degrees(np.arccos(2*eulers[:,1]-1.0)) # cos(Phi) is uniformly distributed
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eulers[:,2] *= 360.0 # phi_2 is uniformly distributed
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eulers[:,2] *= 360.0 # phi_2 is uniformly distributed
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if not options.selective:
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if not options.selective:
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n = np.maximum(np.ones(3),np.array(grid*fraction),dtype=int,casting='unsafe') # find max grid indices within fraction
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n = np.maximum(np.ones(3),np.array(grid*fraction),dtype=int,casting='unsafe') # find max grid indices within fraction
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meshgrid = np.meshgrid(*map(np.arange,n),indexing='ij') # create a meshgrid within fraction
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meshgrid = np.meshgrid(*map(np.arange,n),indexing='ij') # create a meshgrid within fraction
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coords = np.vstack((meshgrid[0],meshgrid[1],meshgrid[2])).reshape(n.prod(),3) # assemble list of 3D coordinates
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coords = np.vstack((meshgrid[0],meshgrid[1],meshgrid[2])).reshape(n.prod(),3) # assemble list of 3D coordinates
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seeds = (random.sample(coords.tolist(),options.N)+np.random.rand(options.N,3))\
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seeds = (random.sample(coords.tolist(),options.N)+np.random.rand(options.N,3))/(n/fraction) # pick options.N of those, rattle position,
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/ \
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(n/fraction) # pick options.N of those, rattle position,
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# and rescale to fall within fraction
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# and rescale to fall within fraction
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else:
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else: # and rescale to fall within fraction
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seeds = np.zeros((options.N,3)) # seed positions array
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seeds = np.empty((options.N,3)) # seed positions array
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seeds[0] = np.random.random(3)*grid/max(grid)
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seeds[0] = np.random.random(3)*grid/max(grid)
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i = 1 # start out with one given point
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i = 1 # start out with one given point
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if i%(options.N/100.) < 1: damask.util.croak('.',False)
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if i%(options.N/100.) < 1: damask.util.croak('.',False)
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