#!/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')
    #print self.resolution
    #self.resolution = numpy.array([10,10,10],'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 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
  
#+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++   
def calculateVonMises(tensor,res):
#+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ 
  vonMises = numpy.zeros([res[0],res[1],res[2]],'d')
  deviator = numpy.zeros([3,3],'d')
  delta = numpy.zeros([3,3],'d')
  delta[0,0] = 1.0
  delta[1,1] = 1.0
  delta[2,2] = 1.0
  for z in range(res[2]):
    for y in range(res[1]):
      for x in range(res[0]): 
       deviator = tensor[x,y,z] - 1.0/3.0*tensor[x,y,z,0,0]*tensor[x,y,z,1,1]*tensor[x,y,z,2,2]*delta
       J_2 = deviator[0,0]*deviator[1,1]\
           + deviator[1,1]*deviator[2,2]\
           + deviator[0,0]*deviator[2,2]\
           - (deviator[0,1])**2\
           - (deviator[1,2])**2\
           - (deviator[0,2])**2
       vonMises[x,y,z] = numpy.sqrt(3*J_2)
  return vonMises
  
#+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ 
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)
        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
name = 'dipl32'
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)))

    

for i in range(40,46):
  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)         
  p_stress = readTensor(p.resolution,p.file,p.N_element_scalars,c_pos,52)         
  #c_stress = calculateCauchyStress(p_stress,defgrad,p.resolution)
  #grain = calculateVonMises(c_stress,p.resolution)
  centroids_coord, defgrad_av = centroids(p.resolution,p.dimension,defgrad)
  ms = mesh(p.resolution,p.dimension,defgrad_av,centroids_coord)
  writeVtkAscii(name+'-mesh-%i.vtk'%i,ms,p_stress[:,:,:,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()