fixed error in file handling
This commit is contained in:
Martin Diehl
parent
69857cc608
commit
1ff38b98af
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@ -1,34 +1,16 @@
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#!/usr/bin/env python
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# -*- coding: UTF-8 no BOM -*-
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import os,sys,string,re,math,numpy,itertools
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import damask
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from optparse import OptionParser, OptionGroup, Option, SUPPRESS_HELP
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import os,sys,string,re,math,itertools
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import numpy as np
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from optparse import OptionParser
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from scipy import ndimage
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from multiprocessing import Pool
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import damask
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scriptID = '$Id$'
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scriptName = scriptID.split()[1]
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#--------------------------------------------------------------------------------------------------
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class extendedOption(Option):
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#--------------------------------------------------------------------------------------------------
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# used for definition of new option parser action 'extend', which enables to take multiple option arguments
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# taken from online tutorial http://docs.python.org/library/optparse.html
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ACTIONS = Option.ACTIONS + ("extend",)
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STORE_ACTIONS = Option.STORE_ACTIONS + ("extend",)
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TYPED_ACTIONS = Option.TYPED_ACTIONS + ("extend",)
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ALWAYS_TYPED_ACTIONS = Option.ALWAYS_TYPED_ACTIONS + ("extend",)
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def take_action(self, action, dest, opt, value, values, parser):
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if action == "extend":
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lvalue = value.split(",")
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values.ensure_value(dest, []).extend(lvalue)
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else:
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Option.take_action(self, action, dest, opt, value, values, parser)
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#--------------------------------------------------------------------------------------------------
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# MAIN
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#--------------------------------------------------------------------------------------------------
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@ -49,7 +31,7 @@ mappings = {
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'microstructures': lambda x: int(x),
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}
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parser = OptionParser(option_class=extendedOption, usage='%prog options [file[s]]', description = """
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parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
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Smoothens out interface roughness by simulated curvature flow.
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This is achieved by the diffusion of each initially sharply bounded grain volume within the periodic domain
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up to a given distance 'd' voxels.
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@ -102,9 +84,9 @@ for file in files:
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#--- interpret header ----------------------------------------------------------------------------
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info = {
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'grid': numpy.zeros(3,'i'),
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'size': numpy.zeros(3,'d'),
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'origin': numpy.zeros(3,'d'),
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'grid': np.zeros(3,'i'),
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'size': np.zeros(3,'d'),
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'origin': np.zeros(3,'d'),
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'homogenization': 0,
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'microstructures': 0,
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}
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@ -134,15 +116,15 @@ for file in files:
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'homogenization: %i\n'%info['homogenization'] + \
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'microstructures: %i\n'%info['microstructures'])
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if numpy.any(info['grid'] < 1):
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if np.any(info['grid'] < 1):
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file['croak'].write('invalid grid a b c.\n')
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continue
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if numpy.any(info['size'] <= 0.0):
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if np.any(info['size'] <= 0.0):
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file['croak'].write('invalid size x y z.\n')
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continue
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#--- read data ------------------------------------------------------------------------------------
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microstructure = numpy.zeros(numpy.prod([2 if i == 1 else i for i in info['grid']]),'i') # 2D structures do not work
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microstructure = np.zeros(np.prod([2 if i == 1 else i for i in info['grid']]),'i') # 2D structures do not work
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i = 0
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while theTable.data_read(): # read next data line of ASCII table
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@ -159,47 +141,47 @@ for file in files:
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#--- reshape, if 2D make copy ---------------------------------------------------------------------
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microstructure = numpy.tile(microstructure.reshape(info['grid'],order='F'),
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numpy.where(info['grid'] == 1, 2,1)) # make one copy along dimensions with grid == 1
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grid = numpy.array(microstructure.shape)
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microstructure = np.tile(microstructure.reshape(info['grid'],order='F'),
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np.where(info['grid'] == 1, 2,1)) # make one copy along dimensions with grid == 1
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grid = np.array(microstructure.shape)
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#--- initialize support data -----------------------------------------------------------------------
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periodic_microstructure = numpy.tile(microstructure,(3,3,3))[grid[0]/2:-grid[0]/2,
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periodic_microstructure = np.tile(microstructure,(3,3,3))[grid[0]/2:-grid[0]/2,
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grid[1]/2:-grid[1]/2,
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grid[2]/2:-grid[2]/2] # periodically extend the microstructure
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microstructure_original = numpy.copy(microstructure) # store a copy the initial microstructure to find locations of immutable indices
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microstructure_original = np.copy(microstructure) # store a copy the initial microstructure to find locations of immutable indices
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X,Y,Z = numpy.mgrid[0:grid[0],0:grid[1],0:grid[2]]
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gauss = numpy.exp(-(X*X + Y*Y + Z*Z)/(2.0*options.d*options.d))/math.pow(2.0*numpy.pi*options.d*options.d,1.5)
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X,Y,Z = np.mgrid[0:grid[0],0:grid[1],0:grid[2]]
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gauss = np.exp(-(X*X + Y*Y + Z*Z)/(2.0*options.d*options.d))/math.pow(2.0*np.pi*options.d*options.d,1.5)
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gauss[:,:,grid[2]/2::] = gauss[:,:,round(grid[2]/2.)-1::-1] # trying to cope with uneven (odd) grid size
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gauss[:,grid[1]/2::,:] = gauss[:,round(grid[1]/2.)-1::-1,:]
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gauss[grid[0]/2::,:,:] = gauss[round(grid[0]/2.)-1::-1,:,:]
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gauss = numpy.fft.rfftn(gauss)
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gauss = np.fft.rfftn(gauss)
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interfacialEnergy = lambda A,B: (A*B != 0)*(A != B)*1.0
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struc = ndimage.generate_binary_structure(3,1) # 3D von Neumann neighborhood
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for smoothIter in xrange(options.N):
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boundary = numpy.zeros(microstructure.shape)
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boundary = np.zeros(microstructure.shape)
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for i in (-1,0,1):
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for j in (-1,0,1):
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for k in (-1,0,1):
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interfaceEnergy = numpy.maximum(boundary,
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interfacialEnergy(microstructure,numpy.roll(numpy.roll(numpy.roll(
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interfaceEnergy = np.maximum(boundary,
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interfacialEnergy(microstructure,np.roll(np.roll(np.roll(
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microstructure,i,axis=0), j,axis=1), k,axis=2))) # assign interfacial energy to all voxels that have a differing neighbor (in Moore neighborhood)
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periodic_interfaceEnergy = numpy.tile(interfaceEnergy,(3,3,3))[grid[0]/2:-grid[0]/2,
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periodic_interfaceEnergy = np.tile(interfaceEnergy,(3,3,3))[grid[0]/2:-grid[0]/2,
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grid[1]/2:-grid[1]/2,
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grid[2]/2:-grid[2]/2] # periodically extend interfacial energy array by half a grid size in positive and negative directions
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index = ndimage.morphology.distance_transform_edt(periodic_interfaceEnergy == 0., # transform bulk volume (i.e. where interfacial energy is zero)
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return_distances = False,
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return_indices = True) # want array index of nearest voxel on periodically extended boundary
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# boundaryExt = boundaryExt[index[0].flatten(),index[1].flatten(),index[2].flatten()].reshape(boundaryExt.shape) # fill bulk with energy of nearest interface | question PE: what "flatten" for?
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# boundaryExt = boundaryExt[index[0].flatten(),index[1].flatten(),index[2].flatten()].reshape(boundaryExt.shape) # fill bulk with energy of nearest interface | question PE: what "flatten" for?
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periodic_bulkEnergy = periodic_interfaceEnergy[index[0],
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index[1],
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index[2]].reshape(2*grid) # fill bulk with energy of nearest interface
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diffusedEnergy = numpy.fft.irfftn(numpy.fft.rfftn(numpy.where(ndimage.morphology.binary_dilation(interfaceEnergy > 0.,
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diffusedEnergy = np.fft.irfftn(np.fft.rfftn(np.where(ndimage.morphology.binary_dilation(interfaceEnergy > 0.,
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structure = struc,
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iterations = options.d/2 + 1), # fat boundary | question PE: why 2d - 1? I would argue for d/2 + 1 !!
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periodic_bulkEnergy[grid[0]/2:-grid[0]/2, # retain filled energy on fat boundary...
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@ -207,7 +189,7 @@ for file in files:
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grid[2]/2:-grid[2]/2], # ...and zero everywhere else
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0.)\
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)*gauss)
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periodic_diffusedEnergy = numpy.tile(diffusedEnergy,(3,3,3))[grid[0]/2:-grid[0]/2,
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periodic_diffusedEnergy = np.tile(diffusedEnergy,(3,3,3))[grid[0]/2:-grid[0]/2,
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grid[1]/2:-grid[1]/2,
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grid[2]/2:-grid[2]/2] # periodically extend the smoothed bulk energy
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index = ndimage.morphology.distance_transform_edt(periodic_diffusedEnergy >= 0.5, # transform voxels close to interface region | question PE: what motivates 1/2 (could be any small number, or)?
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@ -219,21 +201,21 @@ for file in files:
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grid[1]/2:-grid[1]/2,
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grid[2]/2:-grid[2]/2] # extent grains into interface region
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immutable = numpy.zeros(microstructure.shape, dtype=bool)
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immutable = np.zeros(microstructure.shape, dtype=bool)
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for micro in options.immutable:
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immutable += numpy.logical_or(microstructure == micro, microstructure_original == micro) # find locations where immutable microstructures have been or are now
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immutable += np.logical_or(microstructure == micro, microstructure_original == micro) # find locations where immutable microstructures have been or are now
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microstructure = numpy.where(immutable, microstructure_original,microstructure) # undo any changes involving immutable microstructures
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microstructure = np.where(immutable, microstructure_original,microstructure) # undo any changes involving immutable microstructures
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# --- renumber to sequence 1...Ngrains if requested ------------------------------------------------
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# http://stackoverflow.com/questions/10741346/numpy-frequency-counts-for-unique-values-in-an-array
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# http://stackoverflow.com/questions/10741346/np-frequency-counts-for-unique-values-in-an-array
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if options.renumber:
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newID = 0
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for microstructureID,count in enumerate(numpy.bincount(microstructure.flatten())):
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for microstructureID,count in enumerate(np.bincount(microstructure.flatten())):
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if count != 0:
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newID += 1
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microstructure = numpy.where(microstructure == microstructureID, newID, microstructure)
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microstructure = np.where(microstructure == microstructureID, newID, microstructure)
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# --- assemble header -----------------------------------------------------------------------------
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newInfo['microstructures'] = microstructure[0:info['grid'][0],0:info['grid'][1],0:info['grid'][2]].max()
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@ -257,11 +239,11 @@ for file in files:
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# --- write microstructure information ------------------------------------------------------------
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formatwidth = int(math.floor(math.log10(microstructure.max())+1))
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theTable.data = microstructure[0:info['grid'][0],0:info['grid'][1],0:info['grid'][2]].reshape(numpy.prod(info['grid']),order='F').transpose() # question PE: this assumes that only the Z dimension can be 1!
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theTable.data = microstructure[0:info['grid'][0],0:info['grid'][1],0:info['grid'][2]].reshape(np.prod(info['grid']),order='F').transpose() # question PE: this assumes that only the Z dimension can be 1!
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theTable.data_writeArray('%%%ii'%(formatwidth),delimiter=' ')
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#--- output finalization --------------------------------------------------------------------------
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if file['name'] != 'STDIN':
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theTable.input_close()
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theTable.output_close()
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theTable.__IO__['in'].close()
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theTable.__IO__['out'].close()
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os.rename(file['name']+'_tmp',file['name'])
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