DAMASK_EICMD/processing/post/spectral_post.py

354 lines
12 KiB
Python

#!/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, postprocessingMath
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),re.DOTALL)
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),re.DOTALL)
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),re.DOTALL)
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 z in range(0,resolution[2]):
for y in range(0,resolution[1]):
for x in range(0,resolution[0]):
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 z in range(0,resolution[2]):
for y in range(0,resolution[1]):
for x in range(0,resolution[0]):
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 calculateCauchyStress(p_stress,defgrad,res):
#+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
c_stress = numpy.zeros([res[0],res[1],res[2],3,3],'d')
for z in range(res[2]):
for y in range(res[1]):
for x in range(res[0]):
jacobi = numpy.linalg.det(defgrad[x,y,z])
c_stress[x,y,z] = numpy.dot(p_stress[x,y,z],numpy.transpose(defgrad[x,y,z]))/jacobi
return c_stress
# 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
name = 'dipl10'
p = MPIEspectral_result(name+'.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(1,3):
# print('new step')
# c_pos = p.dataOffset + i*(p.N_element_scalars*8*p.N_elements + 8) #8 accounts for header&footer
# for j in range(p.N_element_scalars):
# #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 z in range(0,resolution[2]):
# #for y in range(0,resolution[1]):
# #for x in range(0,resolution[0]):
# currentPosition = c_pos + j*8 +4
# p.file.seek(currentPosition)
# print(struct.unpack('d',p.file.read(8)))
ms=numpy.zeros([res_x,res_y,res_z,3], 'd')
for i in range(249,250):
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)
logstrain = postprocessingMath.logstrain_mat(res_x,res_y,res_z,defgrad)
logstrain2 = postprocessingMath.logstrain_spat(res_x,res_y,res_z,defgrad)
p_stress = readTensor(p.resolution,p.file,p.N_element_scalars,c_pos,58)
c_stress = postprocessingMath.calculate_cauchy(res_x,res_y,res_z,defgrad,p_stress)
vm = postprocessingMath.calculate_mises(res_x,res_y,res_z,c_stress)
defgrad_av=numpy.average(numpy.average(numpy.average(defgrad,0),0),0)
centroids_coord = postprocessingMath.deformed(res_x,res_y,res_z,p.dimension,defgrad,defgrad_av)
ms = postprocessingMath.mesh(p.resolution[0],p.resolution[1],p.resolution[2],p.dimension,defgrad_av,centroids_coord)
writeVtkAscii(name+'-mesh-1-%s.vtk'%i,ms,logstrain[:,:,:,1,2],p.resolution)
writeVtkAscii(name+'-mesh-2-%s.vtk'%i,ms,logstrain2[:,:,:,1,2],p.resolution)
#writeVtkAsciidefgrad_av(name+'-box-%i.vtk'%i,p.dimension,defgrad_av)
#writeVtkAsciiDots(name+'-points-%i.vtk'%i,centroids_coord,grain,p.resolution)
sys.stdout.flush()