#!/usr/bin/python # -*- coding: iso-8859-1 -*- # This script is used for the post processing of the results achieved by the spectral method. # As it reads in the data coming from "materialpoint_results", it can be adopted to the data # computed using the FEM solvers. Until now, its capable to handle elements with one IP in a regular order # written by M. Diehl, m.diehl@mpie.de import os,sys,re,array,struct,numpy, time class vector: x,y,z = [None,None,None] def __init__(self,coords): self.x = coords[0] self.y = coords[1] self.z = coords[2] class element: items = [] type = None def __init__(self,nodes,type): self.items = nodes self.type = type class element_scalar: id = None value = None def __init__(self,node,value): self.id = node self.value = value class MPIEspectral_result: file = None dataOffset = 0 N_elemental_scalars = 0 resolution = [0,0,0] dimension = [0.0,0.0,0.0] theTitle = '' wd = '' extrapolate = '' N_increments = 0 increment = 0 N_nodes = 0 N_node_scalars = 0 N_elements = 0 N_element_scalars = 0 N_element_tensors = 0 theNodes = [] theElements = [] def __init__(self,filename): self.file = open(filename, 'rb') self.title = self._keyedString('load') self.wd = self._keyedString('workingdir') self.geometry = self._keyedString('geometry') self.N_increments = self._keyedInt('increments') self.N_element_scalars = self._keyedInt('materialpoint_sizeResults') self.resolution = self._keyedPackedArray('resolution',3,'i') self.N_nodes = (self.resolution[0]+1)*(self.resolution[1]+1)*(self.resolution[2]+1) self.N_elements = self.resolution[0]*self.resolution[1]*self.resolution[2] self.dimension = self._keyedPackedArray('dimension',3,'d') a = self.resolution[0]+1 b = self.resolution[1]+1 c = self.resolution[2]+1 self.file.seek(0) self.dataOffset = self.file.read(2048).find('eoh')+7 def __str__(self): return '\n'.join([ 'title: %s'%self.title, 'workdir: %s'%self.wd, 'extrapolation: %s'%self.extrapolate, 'increments: %i'%self.N_increments, 'increment: %i'%self.increment, 'nodes: %i'%self.N_nodes, 'resolution: %s'%(','.join(map(str,self.resolution))), 'dimension: %s'%(','.join(map(str,self.dimension))), 'elements: %i'%self.N_elements, 'nodal_scalars: %i'%self.N_node_scalars, 'elemental scalars: %i'%self.N_element_scalars, 'end of header: %i'%self.dataOffset, ] ) def _keyedPackedArray(self,identifier,length = 3,type = 'd'): match = {'d': 8,'i': 4} self.file.seek(0) m = re.search('%s%s'%(identifier,'(.{%i})'%(match[type])*length),self.file.read(2048)) values = [] if m: for i in m.groups(): values.append(struct.unpack(type,i)[0]) return values def _keyedInt(self,identifier): value = None self.file.seek(0) m = re.search('%s%s'%(identifier,'(.{4})'),self.file.read(2048)) if m: value = struct.unpack('i',m.group(1))[0] return value def _keyedString(self,identifier): value = None self.file.seek(0) m = re.search(r'(.{4})%s(.*?)\1'%identifier,self.file.read(2048)) if m: value = m.group(2) return value def extrapolation(self,value): self.extrapolate = value def element_scalar(self,elem,idx): self.file.seek(self.dataOffset+(self.increment*(4+self.N_elements*self.N_element_scalars*8+4) + 4+(elem*self.N_element_scalars + idx)*8)) value = struct.unpack('d',self.file.read(8))[0] return [elemental_scalar(node,value) for node in self.theElements[elem].items] def readScalar(resolution,file,distance,startingPosition,offset): currentPosition = startingPosition+offset*8+4 - distance*8 # we add distance later on field = numpy.zeros([resolution[0],resolution[1],resolution[2]], 'd') for x in range(0,resolution[0]): for y in range(0,resolution[1]): for z in range(0,resolution[2]): currentPosition = currentPosition + distance*8 p.file.seek(currentPosition) field[x][y][z]=struct.unpack('d',p.file.read(8))[0] return field def readTensor(resolution,file,distance,startingPosition,offset): currentPosition = startingPosition+offset*8+4 - distance*8 # we add distance later on field = numpy.zeros([resolution[0],resolution[1],resolution[2],3,3], 'd') for x in range(0,resolution[0]): for y in range(0,resolution[1]): for z in range(0,resolution[2]): currentPosition = currentPosition + distance*8 p.file.seek(currentPosition) for i in range(0,3): for j in range(0,3): field[x][y][z][i][j]=struct.unpack('d',p.file.read(8))[0] return field #+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ def mesh(res,geomdim,defgrad_av,centroids): #+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ neighbor = numpy.array([[0, 0, 0], [1, 0, 0], [1, 1, 0], [0, 1, 0], [0, 0, 1], [1, 0, 1], [1, 1, 1], [0, 1, 1]]) wrappedCentroids = numpy.zeros([res[0]+2,res[1]+2,res[2]+2,3],'d') nodes = numpy.zeros([res[0]+1,res[1]+1,res[2]+1,3],'d') wrappedCentroids[1:-1,1:-1,1:-1] = centroids diag = numpy.ones(3,'i') shift = numpy.zeros(3,'i') lookup = numpy.zeros(3,'i') for k in range(res[2]+2): for j in range(res[1]+2): for i in range(res[0]+2): if (k==0 or k==res[2]+1 or \ j==0 or j==res[1]+1 or \ i==0 or i==res[0]+1 ): me = numpy.array([i,j,k],'i') shift = numpy.sign(res+diag-2*me)*(numpy.abs(res+diag-2*me)/(res+diag)) lookup = me-diag+shift*res wrappedCentroids[i,j,k] = centroids[lookup[0],lookup[1],lookup[2]]- \ numpy.dot(defgrad_av, shift*geomdim) for k in range(res[2]+1): for j in range(res[1]+1): for i in range(res[0]+1): for n in range(8): nodes[i,j,k] += wrappedCentroids[i+neighbor[n,0],j+neighbor[n,1],k+neighbor[n,2]] nodes[:,:,:] /=8.0 return nodes # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ def centroids(res,geomdimension,defgrad): # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ corner = numpy.array([[0, 0, 0], [1, 0, 0], [1, 1, 0], [0, 1, 0], [1, 1, 1], [0, 1, 1], [0, 0, 1], [1, 0, 1]]) step = numpy.array([[ 1, 1, 1], [-1, 1, 1], [-1,-1, 1], [ 1,-1, 1], [-1,-1,-1], [ 1,-1,-1], [ 1, 1,-1], [-1, 1,-1]]) order = numpy.array([[0, 1, 2], [0, 2, 1], [1, 0, 2], [1, 2, 0], [2, 0, 1], [2, 1, 0]]) cornerCoords = numpy.zeros([8,res[0],res[1],res[2],3], 'd') coord = numpy.zeros([8,6,res[0],res[1],res[2],3], 'd') centroids = numpy.zeros([res[0],res[1],res[2],3], 'd') myStep = numpy.zeros(3,'d') rear = numpy.zeros(3, 'i') init = numpy.zeros(3, 'i') oppo = numpy.zeros(3, 'i') me = numpy.zeros(3, 'i') ones = numpy.ones(3, 'i') fones = numpy.ones(3, 'd') defgrad_av=numpy.average(numpy.average(numpy.average(defgrad,0),0),0) for s in range(8):# corners init = corner[s]*(res-ones) oppo = corner[(s+4)%8]*(res-ones) for o in range(6): # orders for k in range(init[order[o,2]],oppo[order[o,2]]+step[s,order[o,2]],step[s,order[o,2]]): rear[order[o,1]] = init[order[o,1]] for j in range(init[order[o,1]],oppo[order[o,1]]+step[s,order[o,1]],step[s,order[o,1]]): rear[order[o,0]] = init[order[o,0]] for i in range(init[order[o,0]],oppo[order[o,0]]+step[s,order[o,0]],step[s,order[o,0]]): me[order[o,0]] = i me[order[o,1]] = j me[order[o,2]] = k if (numpy.all(me == init)): coord[s,o,me[0],me[1],me[2]] = geomdimension * (numpy.dot(defgrad_av,corner[s]) + \ numpy.dot(defgrad[me[0],me[1],me[2]],0.5*step[s]/res)) else: myStep = (me-rear)*geomdimension/res coord[s,o,me[0],me[1],me[2]] = coord[s,o,rear[0],rear[1],rear[2]]+ \ 0.5*numpy.dot(defgrad[me[0],me[1],me[2]] + \ defgrad[rear[0],rear[1],rear[2]],myStep) rear[:] = me[:] cornerCoords[s] = numpy.average(coord[s],0) for k in range(res[2]): for j in range(res[1]): for i in range(res[0]): parameter_coords=(2.0*numpy.array([i,j,k])-res+fones)/(res-fones) pos = (fones + parameter_coords) neg = (fones - parameter_coords) if(k<3 and j<3 and i<3): print i,j,k,':',pos, neg,'(',parameter_coords,')' centroids[i,j,k] = ( cornerCoords[0,i,j,k] *neg[0]*neg[1]*neg[2]\ + cornerCoords[1,i,j,k] *pos[0]*neg[1]*neg[2]\ + cornerCoords[2,i,j,k] *pos[0]*pos[1]*neg[2]\ + cornerCoords[3,i,j,k] *neg[0]*pos[1]*neg[2]\ + cornerCoords[4,i,j,k] *pos[0]*pos[1]*pos[2]\ + cornerCoords[5,i,j,k] *neg[0]*pos[1]*pos[2]\ + cornerCoords[6,i,j,k] *neg[0]*neg[1]*pos[2]\ + cornerCoords[7,i,j,k] *pos[0]*neg[1]*pos[2])*0.125 return centroids, defgrad_av # function writes scalar values to a mesh (geometry) def writeVtkAscii(filename,geometry,scalar,resolution): prodnn=(p.resolution[0]+1)*(p.resolution[1]+1)*(p.resolution[2]+1) vtk = open(filename, 'w') vtk.write('# vtk DataFile Version 3.1\n') # header vtk.write('just a test\n') # header vtk.write('ASCII\n') # header vtk.write('DATASET UNSTRUCTURED_GRID\n') # header vtk.write('POINTS ') # header vtk.write(str(prodnn)) # header vtk.write(' FLOAT\n') # header # nodes for k in range (resolution[2]+1): for j in range (resolution[1]+1): for i in range (resolution[0]+1): vtk.write('\t'.join(map(str,geometry[i,j,k]))+'\n') vtk.write('\n') vtk.write('CELLS ') vtk.write(str(resolution[0]*resolution[1]*resolution[2])) vtk.write('\t') vtk.write(str(resolution[0]*resolution[1]*resolution[2]*9)) vtk.write('\n') # elements for i in range (resolution[2]): for j in range (resolution[1]): for k in range (resolution[0]): vtk.write('8') vtk.write('\t') base = i*(resolution[1]+1)*(resolution[2]+1)+j*(resolution[1]+1)+k vtk.write(str(base)) vtk.write('\t') vtk.write(str(base+1)) vtk.write('\t') vtk.write(str(base+resolution[1]+2)) vtk.write('\t') vtk.write(str(base+resolution[1]+1)) vtk.write('\t') base = base + (resolution[1]+1)*(resolution[2]+1) vtk.write(str(base)) vtk.write('\t') vtk.write(str(base+1)) vtk.write('\t') vtk.write(str(base+resolution[1]+2)) vtk.write('\t') vtk.write(str(base+resolution[1]+1)) vtk.write('\n') vtk.write('\n') vtk.write('CELL_TYPES ') vtk.write('\t') vtk.write(str(resolution[0]*resolution[1]*resolution[2])) vtk.write('\n') for i in range (resolution[0]*resolution[1]*resolution[2]): vtk.write('12\n') vtk.write('\nCELL_DATA ') # header vtk.write(str(resolution[0]*resolution[1]*resolution[2])) # header vtk.write('\n') # header vtk.write('SCALARS HorizontalSpeed float\n') # header vtk.write('LOOKUP_TABLE default\n') # header for k in range (resolution[2]): for j in range (resolution[1]): for i in range (resolution[0]): vtk.write(str(scalar[i,j,k])) vtk.write('\n') return # function writes scalar values to a point field def writeVtkAsciiDots(filename,coordinates,scalar,resolution): prodnn=(p.resolution[0])*(p.resolution[1])*(p.resolution[2]) vtk = open(filename, 'w') vtk.write('# vtk DataFile Version 3.1\n') # header vtk.write('just a test\n') # header vtk.write('ASCII\n') # header vtk.write('DATASET UNSTRUCTURED_GRID\n') # header vtk.write('POINTS ') # header vtk.write(str(prodnn)) # header vtk.write(' FLOAT\n') # header # points for k in range (resolution[2]): for j in range (resolution[1]): for i in range (resolution[0]): vtk.write('\t'.join(map(str,coordinates[i,j,k]))+'\n') vtk.write('\n') vtk.write('CELLS ') vtk.write(str(prodnn)) vtk.write('\t') vtk.write(str(prodnn*2)) vtk.write('\n') for i in range(prodnn): vtk.write('1\t' + str(i) + '\n') vtk.write('CELL_TYPES ') vtk.write('\t') vtk.write(str(prodnn)) vtk.write('\n') for i in range (prodnn): vtk.write('1\n') vtk.write('\nPOINT_DATA ') # header vtk.write(str(prodnn)) # header vtk.write('\n') # header vtk.write('SCALARS HorizontalSpeed float\n') # header vtk.write('LOOKUP_TABLE default\n') # header for k in range (resolution[2]): for j in range (resolution[1]): for i in range (resolution[0]): vtk.write(str(scalar[i,j,k])) vtk.write('\n') return # functiongives the corner box for the average defgrad def writeVtkAsciidefgrad_av(filename,diag,defgrad): points = numpy.array([\ [0.0,0.0,0.0,],\ [diag[0],0.0,0.0,],\ [diag[0],diag[1],0.0,],\ [0.0,diag[1],0.0,],\ [0.0,0.0,diag[2],],\ [diag[0],0.0,diag[2],],\ [diag[0],diag[1],diag[2],],\ [0.0,diag[1],diag[2],]]\ ) vtk = open(filename, 'w') vtk.write('# vtk DataFile Version 3.1\n') # header vtk.write('just a test\n') # header vtk.write('ASCII\n') # header vtk.write('DATASET UNSTRUCTURED_GRID\n') # header vtk.write('POINTS 8') # header vtk.write(' FLOAT\n') # header # points for p in range (8): vtk.write('\t'.join(map(str,numpy.dot(defgrad_av,points[p])))+'\n') vtk.write('\n') vtk.write('CELLS 8 16\n') vtk.write('\n'.join(['1\t%i'%i for i in range(8)])+'\n') vtk.write('CELL_TYPES 8\n') vtk.write('\n'.join(['1']*8)+'\n') return print '*********************************************************************************' print 'Post Processing for Material subroutine for BVP solution using spectral method' print '*********************************************************************************\n' #reading in the header of the results file p = MPIEspectral_result('32x32x32x100.spectralOut') p.extrapolation('') print p # Ended reading of header res_x=p.resolution[0] res_y=p.resolution[1] res_z=p.resolution[2] for i in range(120,121): c_pos = p.dataOffset + i*(p.N_element_scalars*8*p.N_elements + 8) #8 accounts for header&footer defgrad = readTensor(p.resolution,p.file,p.N_element_scalars,c_pos,16) grain = readScalar(p.resolution,p.file,p.N_element_scalars,c_pos,7) centroids, defgrad_av = centroids(p.resolution,p.dimension,defgrad) print centroids.shape, defgrad_av.shape ms = mesh(p.resolution,p.dimension,defgrad_av,centroids) writeVtkAscii('mesh-%i.vtk'%i,ms,grain,p.resolution) writeVtkAsciidefgrad_av('box-%i.vtk'%i,p.dimension,defgrad_av) writeVtkAsciiDots('points-%i.vtk'%i,centroids,grain,p.resolution) sys.stdout.flush()