Merge branch 'development' into CCodeUse

VERSION

@@ -1 +1 @@
-v2.0.0-15-g3898fb2
+v2.0.0-43-ge39441f

code/crystallite.f90

@@ -3569,11 +3569,7 @@ logical function crystallite_integrateStress(&
                                      maxticks
 
  external :: &
-#if(FLOAT==8)
    dgesv
-#elif(FLOAT==4)
-   sgesv
-#endif
 
  !* be pessimistic
  crystallite_integrateStress = .false.
@@ -3756,11 +3752,7 @@ logical function crystallite_integrateStress(&
                      - math_Plain3333to99(math_mul3333xx3333(math_mul3333xx3333(dLp_dT3333,dT_dFe3333),dFe_dLp3333))
        dRLp_dLp2   = dRLp_dLp                                                                         ! will be overwritten in first call to LAPACK routine
        work = math_plain33to9(residuumLp)
-#if(FLOAT==8)
        call dgesv(9,1,dRLp_dLp2,9,ipiv,work,9,ierr)                                                   ! solve dRLp/dLp * delta Lp = -res for delta Lp
-#elif(FLOAT==4)
-       call sgesv(9,1,dRLp_dLp2,9,ipiv,work,9,ierr)                                                   ! solve dRLp/dLp * delta Lp = -res for delta Lp
-#endif
        if (ierr /= 0_pInt) then
 #ifndef _OPENMP
          if (iand(debug_level(debug_crystallite), debug_levelBasic) /= 0_pInt) then
@@ -3849,11 +3841,7 @@ logical function crystallite_integrateStress(&
                                                                    math_mul3333xx3333(dT_dFi3333, dFi_dLi3333)))  &
                - math_Plain3333to99(math_mul3333xx3333(dLi_dFi3333, dFi_dLi3333))
      work = math_plain33to9(residuumLi)
-#if(FLOAT==8)
      call dgesv(9,1,dRLi_dLi,9,ipiv,work,9,ierr)                                                    ! solve dRLi/dLp * delta Li = -res for delta Li
-#elif(FLOAT==4)
-     call sgesv(9,1,dRLi_dLi,9,ipiv,work,9,ierr)                                                    ! solve dRLi/dLp * delta Li = -res for delta Li
-#endif
      if (ierr /= 0_pInt) then
 #ifndef _OPENMP
        if (iand(debug_level(debug_crystallite), debug_levelBasic) /= 0_pInt) then

code/math.f90

@@ -186,10 +186,6 @@ module math
    halton_seed_set, &
    i_to_halton, &
    prime
- external :: &
-   dsyev, &
-   dgetrf, &
-   dgetri
 
 contains
 
@@ -811,15 +807,13 @@ function math_invSym3333(A)
  integer(pInt), dimension(6)   :: ipiv6
  real(pReal),   dimension(6,6) :: temp66_Real
  real(pReal),   dimension(6)   :: work6
+ external :: &
+  dgetrf, &
+  dgetri
 
  temp66_real = math_Mandel3333to66(A)
-#if(FLOAT==8)
  call dgetrf(6,6,temp66_real,6,ipiv6,ierr)
  call dgetri(6,temp66_real,6,ipiv6,work6,6,ierr)
-#elif(FLOAT==4)
- call sgetrf(6,6,temp66_real,6,ipiv6,ierr)
- call sgetri(6,temp66_real,6,ipiv6,work6,6,ierr)
-#endif
  if (ierr == 0_pInt) then
    math_invSym3333 = math_Mandel66to3333(temp66_real)
  else
@@ -847,13 +841,8 @@ subroutine math_invert(myDim,A, InvA, error)
  logical, intent(out) :: error
  
  invA = A 
-#if(FLOAT==8)
  call dgetrf(myDim,myDim,invA,myDim,ipiv,ierr)
  call dgetri(myDim,InvA,myDim,ipiv,work,myDim,ierr)
-#elif(FLOAT==4)
- call sgetrf(myDim,myDim,invA,myDim,ipiv,ierr)
- call sgetri(myDim,InvA,myDim,ipiv,work,myDim,ierr)
-#endif
  error = merge(.true.,.false., ierr /= 0_pInt)                                                      ! http://fortraninacworld.blogspot.de/2012/12/ternary-operator.html
  
 end subroutine math_invert
@@ -1937,16 +1926,13 @@ subroutine math_eigenValuesVectorsSym(m,values,vectors,error)
  real(pReal), dimension(size(m,1)),            intent(out) :: values
  real(pReal), dimension(size(m,1),size(m,1)),  intent(out) :: vectors
  logical, intent(out) :: error
-
  integer(pInt) :: info
  real(pReal), dimension((64+2)*size(m,1)) :: work                                                    ! block size of 64 taken from http://www.netlib.org/lapack/double/dsyev.f
+ external :: &
+  dsyev
 
  vectors = m                                                                                         ! copy matrix to input (doubles as output) array
-#if(FLOAT==8)
  call dsyev('V','U',size(m,1),vectors,size(m,1),values,work,(64+2)*size(m,1),info)
-#elif(FLOAT==4)
- call ssyev('V','U',size(m,1),vectors,size(m,1),values,work,(64+2)*size(m,1),info)
-#endif
  error = (info == 0_pInt)
 
 end subroutine math_eigenValuesVectorsSym
@@ -2135,16 +2121,13 @@ function math_eigenvaluesSym(m)
  real(pReal), dimension(:,:),                  intent(in)  :: m
  real(pReal), dimension(size(m,1))                         :: math_eigenvaluesSym
  real(pReal), dimension(size(m,1),size(m,1))               :: vectors
-
  integer(pInt) :: info
  real(pReal), dimension((64+2)*size(m,1)) :: work                                                    ! block size of 64 taken from http://www.netlib.org/lapack/double/dsyev.f
+ external :: &
+  dsyev
 
  vectors = m                                                                                         ! copy matrix to input (doubles as output) array
-#if(FLOAT==8)
  call dsyev('N','U',size(m,1),vectors,size(m,1),math_eigenvaluesSym,work,(64+2)*size(m,1),info)
-#elif(FLOAT==4)
- call ssyev('N','U',size(m,1),vectors,size(m,1),math_eigenvaluesSym,work,(64+2)*size(m,1),info)
-#endif
  if (info /= 0_pInt) math_eigenvaluesSym = DAMASK_NaN
 
 end function math_eigenvaluesSym

code/prec.f90

@@ -4,9 +4,9 @@
 !> @author   Christoph Kords, Max-Planck-Institut für Eisenforschung GmbH
 !> @author   Martin Diehl, Max-Planck-Institut für Eisenforschung GmbH
 !> @author   Luv Sharma, Max-Planck-Institut für Eisenforschung GmbH
-!> @brief    setting precision for real and int type depending on makros "FLOAT" and "INT"
+!> @brief    setting precision for real and int type
 !> @details  setting precision for real and int type and for DAMASK_NaN. Definition is made 
-!!           depending on makros "FLOAT" and "INT" defined during compilation
+!!           depending on makro "INT" defined during compilation
 !!           for details on NaN see https://software.intel.com/en-us/forums/topic/294680
 !--------------------------------------------------------------------------------------------------
 module prec
@@ -18,18 +18,7 @@ module prec
 
  implicit none
  private 
-#if (FLOAT==4)
+#if (FLOAT==8)
-#if defined(Spectral) || defined(FEM)
- SPECTRAL SOLVER AND OWN FEM DO NOT SUPPORT SINGLE PRECISION, STOPPING COMPILATION
-#endif
- integer,     parameter, public :: pReal = 4                                                        !< floating point single precition (was selected_real_kind(6,37), number with 6 significant digits, up to 1e+-37)
-#ifdef __INTEL_COMPILER
- real(pReal), parameter, public :: DAMASK_NaN = Z'7F800001'                                         !< quiet NaN for single precision (from http://www.hpc.unimelb.edu.au/doc/f90lrm/dfum_035.html, copy can be found in documentation/Code/Fortran)
-#endif
-#ifdef __GFORTRAN__
- real(pReal), parameter, public :: DAMASK_NaN = real(Z'7F800001', pReal)                            !< quiet NaN for single precision (from http://www.hpc.unimelb.edu.au/doc/f90lrm/dfum_035.html, copy can be found in documentation/Code/Fortran)
-#endif
-#elif (FLOAT==8)
  integer,     parameter, public :: pReal = 8                                                        !< floating point double precision (was selected_real_kind(15,300), number with 15 significant digits, up to 1e+-300)
 #ifdef __INTEL_COMPILER
  real(pReal), parameter, public :: DAMASK_NaN = Z'7FF8000000000000'                                 !< quiet NaN for double precision (from http://www.hpc.unimelb.edu.au/doc/f90lrm/dfum_035.html, copy can be found in documentation/Code/Fortran)
@@ -172,9 +161,9 @@ end subroutine prec_init
 
 !--------------------------------------------------------------------------------------------------
 !> @brief figures out if a floating point number is NaN
-! basically just a small wrapper, because gfortran < 4.9 does not have the IEEE module
+! basically just a small wrapper, because gfortran < 5.0 does not have the IEEE module
 !--------------------------------------------------------------------------------------------------
-logical elemental function prec_isNaN(a)
+logical elemental pure function prec_isNaN(a)
 
  implicit none
  real(pReal), intent(in) :: a
@@ -187,4 +176,30 @@ logical elemental function prec_isNaN(a)
 #endif
 end function prec_isNaN
 
+
+!--------------------------------------------------------------------------------------------------
+!> @brief equality comparison for double precision
+! replaces "==" but for certain (relative) tolerance. Counterpart to dNeq
+! http://www.cygnus-software.com/papers/comparingfloats/comparingfloats.htm
+!--------------------------------------------------------------------------------------------------
+logical elemental pure function dEq(a,b,tol)
+  real(pReal), intent(in) :: a,b
+  real(pReal), intent(in), optional :: tol
+  real(pReal), parameter  :: eps = 2.2204460492503131E-16                                           ! DBL_EPSILON in C
+  dEq = merge(.True., .False.,abs(a-b) <= merge(tol,eps,present(tol))*maxval(abs([a,b])))
+end function dEq
+
+
+!--------------------------------------------------------------------------------------------------
+!> @brief inequality comparison for double precision
+! replaces "!=" but for certain (relative) tolerance. Counterpart to dEq
+! http://www.cygnus-software.com/papers/comparingfloats/comparingfloats.htm
+!--------------------------------------------------------------------------------------------------
+logical elemental pure function dNeq(a,b,tol)
+  real(pReal), intent(in)           :: a,b
+  real(pReal), intent(in), optional :: tol
+  real(pReal), parameter  :: eps = 2.2204460492503131E-16                                           ! DBL_EPSILON in C
+  dNeq = merge(.False., .True.,abs(a-b) <= merge(tol,eps,present(tol))*maxval(abs([a,b])))
+end function dNeq
+
 end module prec

lib/damask/asciitable.py

@@ -517,22 +517,27 @@ class ASCIItable():
 
 # ------------------------------------------------------------------
   def microstructure_read(self,
-                          grid):
+                          grid,
+                          type = 'i',
+                          strict = False):
     """read microstructure data (from .geom format)"""
+    def datatype(item):
+      return int(item) if type.lower() == 'i' else float(item)
+      
     N = grid.prod()                                                                       # expected number of microstructure indices in data
-    microstructure = np.zeros(N,'i')                                                # initialize as flat array
+    microstructure = np.zeros(N,type)                                                     # initialize as flat array
 
     i = 0
     while i < N and self.data_read():
       items = self.data
       if len(items) > 2:
-        if   items[1].lower() == 'of': items = [int(items[2])]*int(items[0])
+        if   items[1].lower() == 'of': items = np.ones(datatype(items[0]))*datatype(items[2])
-        elif items[1].lower() == 'to': items = range(int(items[0]),1+int(items[2]))
+        elif items[1].lower() == 'to': items = np.arange(datatype(items[0]),1+datatype(items[2]))
-        else:                          items = map(int,items)
+        else:                          items = map(datatype,items)
-      else:                            items = map(int,items)
+      else:                            items = map(datatype,items)
 
       s = min(len(items), N-i)                                                            # prevent overflow of microstructure array
       microstructure[i:i+s] = items[:s]
-      i += s
+      i += len(items)
 
-    return microstructure
+    return (microstructure, i == N and not self.data_read()) if strict else microstructure  # check for proper point count and end of file

lib/damask/test/test.py

@@ -62,7 +62,7 @@ class Test():
           if not self.compare(variant):
             return variant+1                                                   # return culprit
         except Exception as e :
-          logging.critical('\nWARNING:\n %s\n'%e)
+          logging.critical('\nWARNING:\n {}\n'.format(e))
           return variant+1                                                     # return culprit
       return 0
     else:
@@ -79,7 +79,7 @@ class Test():
           elif not (self.options.accept or self.compare(variant)):             # no update, do comparison
             return variant+1                                                   # return culprit
         except Exception as e :
-          logging.critical('\nWARNING:\n %s\n'%e)
+          logging.critical('\nWARNING:\n {}\n'.format(e))
           return variant+1                                                     # return culprit
       return 0
   
@@ -94,13 +94,13 @@ class Test():
     try:
       shutil.rmtree(self.dirCurrent())
     except:
-      logging.warning('removal of directory "%s" not possible...'%(self.dirCurrent()))
+      logging.warning('removal of directory "{}" not possible...'.format(self.dirCurrent()))
       status = status and False
 
     try:
       os.mkdir(self.dirCurrent())
     except:
-      logging.critical('creation of directory "%s" failed...'%(self.dirCurrent()))
+      logging.critical('creation of directory "{}" failed...'.format(self.dirCurrent()))
       status = status and False
 
     return status
@@ -193,19 +193,19 @@ class Test():
       try:
         shutil.copy2(self.fileInReference(file),self.fileInCurrent(targetfiles[i]))  
       except:
-        logging.critical('Reference2Current: Unable to copy file %s'%file)
+        logging.critical('Reference2Current: Unable to copy file "{}"'.format(file))
 
  
   def copy_Base2Current(self,sourceDir,sourcefiles=[],targetfiles=[]):
     
-    source=os.path.normpath(os.path.join(self.dirBase,'../../../'+sourceDir))
+    source=os.path.normpath(os.path.join(self.dirBase,'../../..',sourceDir))
     if len(targetfiles) == 0: targetfiles = sourcefiles
     for i,file in enumerate(sourcefiles):
       try:
         shutil.copy2(os.path.join(source,file),self.fileInCurrent(targetfiles[i]))  
       except:
         logging.error(os.path.join(source,file))
-        logging.critical('Base2Current: Unable to copy file %s'%file)
+        logging.critical('Base2Current: Unable to copy file "{}"'.format(file))
 
 
   def copy_Current2Reference(self,sourcefiles=[],targetfiles=[]):
@@ -215,7 +215,7 @@ class Test():
       try:
         shutil.copy2(self.fileInCurrent(file),self.fileInReference(targetfiles[i]))  
       except:
-        logging.critical('Current2Reference: Unable to copy file %s'%file)
+        logging.critical('Current2Reference: Unable to copy file "{}"'.format(file))
 
         
   def copy_Proof2Current(self,sourcefiles=[],targetfiles=[]):
@@ -225,7 +225,7 @@ class Test():
       try:
         shutil.copy2(self.fileInProof(file),self.fileInCurrent(targetfiles[i]))  
       except:
-        logging.critical('Proof2Current: Unable to copy file %s'%file)
+        logging.critical('Proof2Current: Unable to copy file "{}"'.format(file))
 
         
   def copy_Current2Current(self,sourcefiles=[],targetfiles=[]):
@@ -234,7 +234,7 @@ class Test():
       try:
         shutil.copy2(self.fileInReference(file),self.fileInCurrent(targetfiles[i]))  
       except:
-        logging.critical('Current2Current: Unable to copy file %s'%file)
+        logging.critical('Current2Current: Unable to copy file "{}"'.format(file))
 
 
   def execute_inCurrentDir(self,cmd,streamIn=None):
@@ -252,7 +252,7 @@ class Test():
   def compare_Array(self,File1,File2):
 
     import numpy as np
-    logging.info('comparing\n '+File1+'\n '+File2)
+    logging.info('\n '.join(['comparing',File1,File2]))
     table1 = damask.ASCIItable(name=File1,readonly=True)
     table1.head_read()
     len1=len(table1.info)+2
@@ -270,8 +270,9 @@ class Test():
       max_loc=np.argmax(abs(refArrayNonZero[curArray.nonzero()]/curArray[curArray.nonzero()]-1.))
       refArrayNonZero = refArrayNonZero[curArray.nonzero()]
       curArray = curArray[curArray.nonzero()]
-      print(' ********\n * maximum relative error %e for %e and %e\n ********'
+      print(' ********\n * maximum relative error {} between {} and {}\n ********'.format(max_err,
-                  %(max_err, refArrayNonZero[max_loc],curArray[max_loc]))
+                                                                                          refArrayNonZero[max_loc],
+                                                                                          curArray[max_loc]))
       return max_err
     else:
        raise Exception('mismatch in array size to compare')
@@ -295,7 +296,7 @@ class Test():
                                      absoluteTolerance=False,perLine=False,skipLines=[]):
     
     import numpy as np
-    logging.info('comparing ASCII Tables\n %s \n %s'%(file0,file1))
+    logging.info('\n '.join(['comparing ASCII Tables',file0,file1]))
     if normHeadings == '': normHeadings = headings0
 
 # check if comparison is possible and determine lenght of columns
@@ -315,7 +316,7 @@ class Test():
 
       for i in xrange(dataLength):
         if headings0[i]['shape'] != headings1[i]['shape']: 
-          raise Exception('shape mismatch when comparing %s with %s '%(headings0[i]['label'],headings1[i]['label']))
+          raise Exception('shape mismatch between {} and {} '.format(headings0[i]['label'],headings1[i]['label']))
         shape[i] = headings0[i]['shape']
         for j in xrange(np.shape(shape[i])[0]):
           length[i] *= shape[i][j]
@@ -323,7 +324,9 @@ class Test():
         for j in xrange(np.shape(normShape[i])[0]):
           normLength[i] *= normShape[i][j]
     else:
-      raise Exception('trying to compare %i with %i normed by %i data sets'%(len(headings0),len(headings1),len(normHeadings)))
+      raise Exception('trying to compare {} with {} normed by {} data sets'.format(len(headings0),
+                                                                                   len(headings1),
+                                                                                   len(normHeadings)))
 
     table0 = damask.ASCIItable(name=file0,readonly=True)
     table0.head_read()
@@ -331,22 +334,19 @@ class Test():
     table1.head_read()   
 
     for i in xrange(dataLength):
-      key0 =    {True :'1_%s',
+      key0    = ('1_' if     length[i]>1 else '') +    headings0[i]['label']
-                 False:'%s'   }[length[i]>1]%headings0[i]['label']
+      key1    = ('1_' if     length[i]>1 else '') +    headings1[i]['label']
-      key1 =    {True :'1_%s',
+      normKey = ('1_' if normLength[i]>1 else '') + normHeadings[i]['label']
-                 False:'%s'   }[length[i]>1]%headings1[i]['label']
-      normKey = {True :'1_%s',
-                 False:'%s'   }[normLength[i]>1]%normHeadings[i]['label']
       if key0 not in table0.labels:
-        raise Exception('column %s not found in 1. table...\n'%key0)
+        raise Exception('column {} not found in 1. table...\n'.format(key0))
       elif key1 not in table1.labels:
-        raise Exception('column %s not found in 2. table...\n'%key1)
+        raise Exception('column {} not found in 2. table...\n'.format(key1))
       elif normKey not in table0.labels:
-        raise Exception('column %s not found in 1. table...\n'%normKey)
+        raise Exception('column {} not found in 1. table...\n'.format(normKey))
       else:
-        column[0][i]  = table0.labels.index(key0)                                  # remember columns of requested data
+        column[0][i]  = table0.labels.index(key0)
-        column[1][i]  = table1.labels.index(key1)                                  # remember columns of requested data in second column
+        column[1][i]  = table1.labels.index(key1)
-        normColumn[i] = table0.labels.index(normKey)                               # remember columns of requested data in second column
+        normColumn[i] = table0.labels.index(normKey)
     
     line0 = 0
     while table0.data_read():                                                  # read next data line of ASCII table
@@ -361,7 +361,7 @@ class Test():
             norm[i] = np.append(norm[i],np.max(np.abs(normData)))
           else:
             norm[i] = np.append(norm[i],np.linalg.norm(np.reshape(normData,normShape[i]),normType))
-      line0 +=1
+      line0 += 1
     
     for i in xrange(dataLength):
       if not perLine: norm[i] = [np.max(norm[i]) for j in xrange(line0-len(skipLines))]
@@ -370,9 +370,9 @@ class Test():
         norm[i] = [1.0 for j in xrange(line0-len(skipLines))]
         absTol[i] = True
         if perLine:
-          logging.warning('At least one norm of %s in 1. table is 0.0, using absolute tolerance'%headings0[i]['label'])
+          logging.warning('At least one norm of {} in 1. table is 0.0, using absolute tolerance'.format(headings0[i]['label']))
         else:
-          logging.warning('Maximum norm of %s in 1. table is 0.0, using absolute tolerance'%headings0[i]['label'])
+          logging.warning('Maximum norm of {} in 1. table is 0.0, using absolute tolerance'.format(headings0[i]['label']))
 
     line1 = 0
     while table1.data_read():                                                  # read next data line of ASCII table
@@ -384,14 +384,18 @@ class Test():
                                                                                    norm[i][line1-len(skipLines)])
       line1 +=1
 
-    if (line0 != line1): raise Exception('found %s lines in 1. table and %s in 2. table'%(line0,line1))
+    if (line0 != line1): raise Exception('found {} lines in 1. table but {} in 2. table'.format(line0,line1))
 
     logging.info(' ********')
     for i in xrange(dataLength):
       if absTol[i]:
-        logging.info(' * maximum absolute error %e for %s and %s'%(maxError[i],headings0[i]['label'],headings1[i]['label']))
+        logging.info(' * maximum absolute error {} between {} and {}'.format(maxError[i],
+                                                                             headings0[i]['label'],
+                                                                             headings1[i]['label']))
       else:
-        logging.info(' * maximum relative error %e for %s and %s'%(maxError[i],headings0[i]['label'],headings1[i]['label']))
+        logging.info(' * maximum relative error {} between {} and {}'.format(maxError[i],
+                                                                             headings0[i]['label'],
+                                                                             headings1[i]['label']))
     logging.info(' ********')
     return maxError
 
@@ -443,8 +447,8 @@ class Test():
       normedDelta = np.where(normBy>preFilter,delta/normBy,0.0)
       mean = np.amax(np.abs(np.mean(normedDelta,0)))
       std = np.amax(np.std(normedDelta,0))
-      logging.info('mean: %f'%mean)
+      logging.info('mean: {:f}'.format(mean))
-      logging.info('std: %f'%std)
+      logging.info('std: {:f}'.format(std))
     
     return (mean<meanTol) & (std < stdTol)
 
@@ -495,7 +499,7 @@ class Test():
       table.close()
     
     maximum /= len(tables)
-    maximum = np.where(maximum >0.0, maximum, 1)                                                 # do not devide by zero for empty columns
+    maximum = np.where(maximum >0.0, maximum, 1)                               # avoid div by zero for empty columns
     for i in xrange(len(data)):
       data[i] /= maximum
     
@@ -511,8 +515,8 @@ class Test():
         t0 = np.where(mask,0.0,data[i-1])
         t1 = np.where(mask,0.0,data[i  ])
         j = np.argmin(np.abs(t1)*rtol+atol-np.abs(t0-t1))
-        logging.info('%f'%np.amax(np.abs(t0-t1)/(np.abs(t1)*rtol+atol)))
+        logging.info('{:f}'.format(np.amax(np.abs(t0-t1)/(np.abs(t1)*rtol+atol))))
-        logging.info('%f %f'%((t0*maximum).flatten()[j],(t1*maximum).flatten()[j]))
+        logging.info('{:f} {:f}'.format((t0*maximum).flatten()[j],(t1*maximum).flatten()[j]))
       allclose &= np.allclose(np.where(mask,0.0,data[i-1]),
                               np.where(mask,0.0,data[i  ]),rtol,atol)          # accumulate "pessimism"
 
@@ -543,14 +547,13 @@ class Test():
   def report_Success(self,culprit):
     
     if culprit == 0:
-      logging.critical('%s passed.'%({False: 'The test',
+      logging.critical(('The test' if len(self.variants) == 1 else 'All {} tests'.format(len(self.variants))) + ' passed')
-                         True: 'All %i tests'%(len(self.variants))}[len(self.variants) > 1]))
       logging.critical('\n!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n')
       return 0
     if culprit == -1:
       logging.warning('Warning: Could not start test')
       return 0
     else:
-      logging.critical(' ********\n * Test %i failed...\n ********'%(culprit))
+      logging.critical(' ********\n * Test {} failed...\n ********'.format(culprit))
       logging.critical('\n!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n')
       return culprit

lib/damask/util.py

@@ -58,6 +58,24 @@ def emph(what):
   """emphasizes string on screen"""
   return bcolors.BOLD+srepr(what)+bcolors.ENDC
 
+# -----------------------------
+def execute(cmd,
+            streamIn = None,
+            wd = './'):
+  """executes a command in given directory and returns stdout and stderr for optional stdin"""
+  initialPath = os.getcwd()
+  os.chdir(wd)
+  process = subprocess.Popen(shlex.split(cmd),
+                             stdout = subprocess.PIPE,
+                             stderr = subprocess.PIPE,
+                             stdin  = subprocess.PIPE)
+  out,error = [i.replace("\x08","") for i in (process.communicate() if streamIn is None 
+                                         else process.communicate(streamIn.read()))]
+  os.chdir(initialPath)
+  if process.returncode != 0: raise RuntimeError('{} failed with returncode {}'.format(cmd,process.returncode))
+  return out,error
+
+
 # -----------------------------
 # Matlab like trigonometric functions that take and return angles in degrees.
 # -----------------------------
@@ -104,7 +122,9 @@ class extendableOption(Option):
 class backgroundMessage(threading.Thread):
   """reporting with animation to indicate progress"""
 
-  choices = {'bounce':   ['_','o','O','°','¯','¯','°','O','o',],
+  choices = {'bounce':   ['_',      'o',      'O',      u'\u00B0',
+                          u'\u203e',u'\u203e',u'\u00B0','O','o','_'],
+             'spin':     [u'\u25dc',u'\u25dd',u'\u25de',u'\u25df'],
              'circle':   [u'\u25f4',u'\u25f5',u'\u25f6',u'\u25f7'],
              'hexagon':  [u'\u2b22',u'\u2b23'],
              'square':   [u'\u2596',u'\u2598',u'\u259d',u'\u2597'],
@@ -228,7 +248,7 @@ def leastsqBound(func, x0, args=(), bounds=None, Dfun=None, full_output=0,
     return shape(res), dt
   
   def _int2extGrad(p_int, bounds):
-    """Calculate the gradients of transforming the internal (unconstrained) to external (constained) parameter."""
+    """Calculate the gradients of transforming the internal (unconstrained) to external (constrained) parameter."""
     grad = np.empty_like(p_int)
     for i, (x, bound) in enumerate(zip(p_int, bounds)):
         lower, upper = bound
@@ -430,22 +450,4 @@ def curve_fit_bound(f, xdata, ydata, p0=None, sigma=None, bounds=None, **kw):
     else:
         pcov = np.inf
 
-    if return_full:
+    return (popt, pcov, infodict, errmsg, ier) if return_full else (popt, pcov)
-        return popt, pcov, infodict, errmsg, ier
-    else:
-        return popt, pcov
-
-        
-def execute(cmd,streamIn=None,wd='./'):
-  """executes a command in given directory and returns stdout and stderr for optional stdin"""
-  initialPath=os.getcwd()
-  os.chdir(wd)
-  process = subprocess.Popen(shlex.split(cmd),stdout=subprocess.PIPE,stderr = subprocess.PIPE,stdin=subprocess.PIPE)
-  if streamIn is not None:
-    out,error = [i.replace("\x08","") for i in process.communicate(streamIn.read())]
-  else:
-    out,error =[i.replace("\x08","") for i in process.communicate()]
-  os.chdir(initialPath)
-  if process.returncode !=0: raise RuntimeError(cmd+' failed with returncode '+str(process.returncode))
-  return out,error
-

processing/post/addCurl.py

@@ -10,40 +10,35 @@ scriptName = os.path.splitext(os.path.basename(__file__))[0]
 scriptID   = ' '.join([scriptName,damask.version])
 
 def curlFFT(geomdim,field):
+ grid = np.array(np.shape(field)[2::-1])
  N = grid.prod()                                                                          # field size
  n = np.array(np.shape(field)[3:]).prod()                                                 # data size
 
- if   n == 3:
+ if   n == 3:   dataType = 'vector'
-   dataType = 'vector'
+ elif n == 9:   dataType = 'tensor'
- elif n == 9:
-   dataType = 'tensor'
 
  field_fourier = np.fft.fftpack.rfftn(field,axes=(0,1,2))
  curl_fourier  = np.zeros(field_fourier.shape,'c16')
 
 # differentiation in Fourier space
  k_s = np.zeros([3],'i')
- TWOPIIMG = (0.0+2.0j*math.pi)
+ TWOPIIMG = 2.0j*math.pi
  for i in xrange(grid[2]):
    k_s[0] = i
-   if(grid[2]%2==0 and i == grid[2]//2):                                                            # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
+   if grid[2]%2 == 0 and i == grid[2]//2:  k_s[0] = 0                                     # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
-     k_s[0]=0
+   elif i > grid[2]//2:                    k_s[0] -= grid[2]
-   elif (i > grid[2]//2): 
-     k_s[0] = k_s[0] - grid[2]
 
    for j in xrange(grid[1]):
      k_s[1] = j
-     if(grid[1]%2==0 and j == grid[1]//2):                                                          # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
+     if grid[1]%2 == 0 and j == grid[1]//2: k_s[1] = 0                                    # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
-       k_s[1]=0
+     elif j > grid[1]//2:                   k_s[1] -= grid[1]
-     elif (j > grid[1]//2): 
-       k_s[1] = k_s[1] - grid[1]
 
      for k in xrange(grid[0]//2+1):
        k_s[2] = k
-       if(grid[0]%2==0 and k == grid[0]//2):                                                        # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
+       if grid[0]%2 == 0 and k == grid[0]//2: k_s[2] = 0                                  # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
-         k_s[2]=0
+
+       xi = (k_s/geomdim)[2::-1].astype('c16')                                            # reversing the field input order
 
-       xi = np.array([k_s[2]/geomdim[2]+0.0j,k_s[1]/geomdim[1]+0.j,k_s[0]/geomdim[0]+0.j],'c16')
        if dataType == 'tensor': 
          for l in xrange(3):
            curl_fourier[i,j,k,0,l] = ( field_fourier[i,j,k,l,2]*xi[1]\
@@ -100,10 +95,8 @@ if options.vector is None and options.tensor is None:
 if filenames == []: filenames = [None]
 
 for name in filenames:
-  try:
+  try:    table = damask.ASCIItable(name = name,buffered = False)
-    table = damask.ASCIItable(name = name,buffered = False)
+  except: continue
-  except:
-    continue
   damask.util.report(scriptName,name)
 
 # ------------------------------------------ read header ------------------------------------------
@@ -161,9 +154,10 @@ for name in filenames:
   stack = [table.data]
   for type, data in items.iteritems():
     for i,label in enumerate(data['active']):
-      stack.append(curlFFT(size[::-1],                                                              # we need to reverse order here, because x 
+      # we need to reverse order here, because x is fastest,ie rightmost, but leftmost in our x,y,z notation
-                           table.data[:,data['column'][i]:data['column'][i]+data['dim']].           # is fastest,ie rightmost, but leftmost in 
+      stack.append(curlFFT(size[::-1],
-                           reshape([grid[2],grid[1],grid[0]]+data['shape'])))                       # our x,y,z notation
+                           table.data[:,data['column'][i]:data['column'][i]+data['dim']].
+                           reshape([grid[2],grid[1],grid[0]]+data['shape'])))
 
 # ------------------------------------------ output result -----------------------------------------
 

processing/post/addDivergence.py

@@ -10,6 +10,7 @@ scriptName = os.path.splitext(os.path.basename(__file__))[0]
 scriptID   = ' '.join([scriptName,damask.version])
 
 def divFFT(geomdim,field):
+ grid = np.array(np.shape(field)[2::-1])
  N = grid.prod()                                                                          # field size
  n = np.array(np.shape(field)[3:]).prod()                                                 # data size
 
@@ -18,27 +19,22 @@ def divFFT(geomdim,field):
 
 # differentiation in Fourier space
  k_s=np.zeros([3],'i')
- TWOPIIMG = (0.0+2.0j*math.pi)
+ TWOPIIMG = 2.0j*math.pi
  for i in xrange(grid[2]):
    k_s[0] = i
-   if(grid[2]%2==0 and i == grid[2]//2):                                                            # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
+   if grid[2]%2 == 0 and i == grid[2]//2:  k_s[0] = 0                                     # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
-     k_s[0]=0
+   elif i > grid[2]//2:                    k_s[0] -= grid[2]
-   elif (i > grid[2]//2): 
-     k_s[0] = k_s[0] - grid[2]
 
    for j in xrange(grid[1]):
      k_s[1] = j
-     if(grid[1]%2==0 and j == grid[1]//2):                                                          # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
+     if grid[1]%2 == 0 and j == grid[1]//2: k_s[1] = 0                                    # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
-       k_s[1]=0
+     elif j > grid[1]//2:                   k_s[1] -= grid[1]
-     elif (j > grid[1]//2): 
-       k_s[1] = k_s[1] - grid[1]
 
      for k in xrange(grid[0]//2+1):
        k_s[2] = k
-       if(grid[0]%2==0 and k == grid[0]//2):                                                        # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
+       if grid[0]%2 == 0 and k == grid[0]//2: k_s[2] = 0                                  # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
-         k_s[2]=0
 
-       xi=np.array([k_s[2]/geomdim[2]+0.0j,k_s[1]/geomdim[1]+0.j,k_s[0]/geomdim[0]+0.j],'c16')
+       xi = (k_s/geomdim)[2::-1].astype('c16')                                            # reversing the field input order
        if n == 9:                                                                         # tensor, 3x3 -> 3
          for l in xrange(3):
            div_fourier[i,j,k,l] = sum(field_fourier[i,j,k,l,0:3]*xi) *TWOPIIMG
@@ -80,15 +76,13 @@ parser.set_defaults(coords = 'ipinitialcoord',
 if options.vector is None and options.tensor is None:
   parser.error('no data column specified.')
 
-# --- loop over input files -------------------------------------------------------------------------
+# --- loop over input files ------------------------------------------------------------------------
 
 if filenames == []: filenames = [None]
 
 for name in filenames:
-  try:
+  try:    table = damask.ASCIItable(name = name,buffered = False)
-    table = damask.ASCIItable(name = name,buffered = False)
+  except: continue
-  except:
-    continue
   damask.util.report(scriptName,name)
 
 # ------------------------------------------ read header ------------------------------------------
@@ -140,16 +134,17 @@ for name in filenames:
   maxcorner = np.array(map(max,coords))
   grid   = np.array(map(len,coords),'i')
   size   = grid/np.maximum(np.ones(3,'d'), grid-1.0) * (maxcorner-mincorner)                        # size from edge to edge = dim * n/(n-1) 
-  size   = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1]))                             # spacing for grid==1 set to smallest among other spacings
+  size   = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1]))                             # spacing for grid==1 equal to smallest among other ones
 
 # ------------------------------------------ process value field -----------------------------------
 
   stack = [table.data]
   for type, data in items.iteritems():
     for i,label in enumerate(data['active']):
-      stack.append(divFFT(size[::-1],                                                               # we need to reverse order here, because x
+      # we need to reverse order here, because x is fastest,ie rightmost, but leftmost in our x,y,z notation
-                          table.data[:,data['column'][i]:data['column'][i]+data['dim']].            # is fastest,ie rightmost, but leftmost in 
+      stack.append(divFFT(size[::-1],
-                          reshape([grid[2],grid[1],grid[0]]+data['shape'])))                        # our x,y,z notation
+                          table.data[:,data['column'][i]:data['column'][i]+data['dim']].
+                          reshape([grid[2],grid[1],grid[0]]+data['shape'])))
 
 # ------------------------------------------ output result -----------------------------------------
 

processing/post/addGradient.py

@@ -0,0 +1,158 @@
+#!/usr/bin/env python
+# -*- coding: UTF-8 no BOM -*-
+
+import os,sys,math
+import numpy as np
+from optparse import OptionParser
+import damask
+
+scriptName = os.path.splitext(os.path.basename(__file__))[0]
+scriptID   = ' '.join([scriptName,damask.version])
+
+def gradFFT(geomdim,field):
+ grid = np.array(np.shape(field)[2::-1])
+ N = grid.prod()                                                                          # field size
+ n = np.array(np.shape(field)[3:]).prod()                                                 # data size
+ if   n == 3:   dataType = 'vector'
+ elif n == 1:   dataType = 'scalar'
+
+ field_fourier = np.fft.fftpack.rfftn(field,axes=(0,1,2))
+ grad_fourier   = np.zeros(field_fourier.shape+(3,),'c16')
+
+# differentiation in Fourier space
+ k_s = np.zeros([3],'i')
+ TWOPIIMG = 2.0j*math.pi
+ for i in xrange(grid[2]):
+   k_s[0] = i
+   if grid[2]%2 == 0 and i == grid[2]//2:  k_s[0] = 0                                     # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
+   elif i > grid[2]//2:                    k_s[0] -= grid[2]
+
+   for j in xrange(grid[1]):
+     k_s[1] = j
+     if grid[1]%2 == 0 and j == grid[1]//2: k_s[1] = 0                                    # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
+     elif j > grid[1]//2:                   k_s[1] -= grid[1]
+
+     for k in xrange(grid[0]//2+1):
+       k_s[2] = k
+       if grid[0]%2 == 0 and k == grid[0]//2: k_s[2] = 0                                  # for even grid, set Nyquist freq to 0 (Johnson, MIT, 2011)
+
+       xi = (k_s/geomdim)[2::-1].astype('c16')                                            # reversing the field order
+       
+       grad_fourier[i,j,k,0,:] = field_fourier[i,j,k,0]*xi *TWOPIIMG                      # vector field from scalar data
+
+       if dataType == 'vector':
+         grad_fourier[i,j,k,1,:] = field_fourier[i,j,k,1]*xi *TWOPIIMG                    # tensor field from vector data
+         grad_fourier[i,j,k,2,:] = field_fourier[i,j,k,2]*xi *TWOPIIMG
+
+ return np.fft.fftpack.irfftn(grad_fourier,axes=(0,1,2)).reshape([N,3*n])
+
+
+# --------------------------------------------------------------------
+#                                MAIN
+# --------------------------------------------------------------------
+
+parser = OptionParser(option_class=damask.extendableOption, usage='%prog options [file[s]]', description = """
+Add column(s) containing gradient of requested column(s).
+Operates on periodic ordered three-dimensional data sets.
+Deals with both vector- and scalar fields.
+
+""", version = scriptID)
+
+parser.add_option('-c','--coordinates',
+                  dest = 'coords',
+                  type = 'string', metavar='string',
+                  help = 'column heading for coordinates [%default]')
+parser.add_option('-v','--vector',
+                  dest = 'vector',
+                  action = 'extend', metavar = '<string LIST>',
+                  help = 'heading of columns containing vector field values')
+parser.add_option('-s','--scalar',
+                  dest = 'scalar',
+                  action = 'extend', metavar = '<string LIST>',
+                  help = 'heading of columns containing scalar field values')
+
+parser.set_defaults(coords = 'ipinitialcoord',
+                   )
+
+(options,filenames) = parser.parse_args()
+
+if options.vector is None and options.scalar is None:
+  parser.error('no data column specified.')
+
+# --- loop over input files ------------------------------------------------------------------------
+
+if filenames == []: filenames = [None]
+
+for name in filenames:
+  try:    table = damask.ASCIItable(name = name,buffered = False)
+  except: continue
+  damask.util.report(scriptName,name)
+
+# ------------------------------------------ read header ------------------------------------------
+
+  table.head_read()
+
+# ------------------------------------------ sanity checks ----------------------------------------
+
+  items = {
+            'scalar': {'dim': 1, 'shape': [1], 'labels':options.scalar, 'active':[], 'column': []},
+            'vector': {'dim': 3, 'shape': [3],   'labels':options.vector, 'active':[], 'column': []},
+          }
+  errors  = []
+  remarks = []
+  column = {}
+  
+  if table.label_dimension(options.coords) != 3: errors.append('coordinates {} are not a vector.'.format(options.coords))
+  else: colCoord = table.label_index(options.coords)
+
+  for type, data in items.iteritems():
+    for what in (data['labels'] if data['labels'] is not None else []):
+      dim = table.label_dimension(what)
+      if dim != data['dim']: remarks.append('column {} is not a {}.'.format(what,type))
+      else:
+        items[type]['active'].append(what)
+        items[type]['column'].append(table.label_index(what))
+
+  if remarks != []: damask.util.croak(remarks)
+  if errors  != []:
+    damask.util.croak(errors)
+    table.close(dismiss = True)
+    continue
+
+# ------------------------------------------ assemble header --------------------------------------
+
+  table.info_append(scriptID + '\t' + ' '.join(sys.argv[1:]))
+  for type, data in items.iteritems():
+    for label in data['active']:
+      table.labels_append(['{}_gradFFT({})'.format(i+1,label) for i in xrange(3 * data['dim'])])        # extend ASCII header with new labels
+  table.head_write()
+
+# --------------- figure out size and grid ---------------------------------------------------------
+
+  table.data_readArray()
+
+  coords = [np.unique(table.data[:,colCoord+i]) for i in xrange(3)]
+  mincorner = np.array(map(min,coords))
+  maxcorner = np.array(map(max,coords))
+  grid   = np.array(map(len,coords),'i')
+  size   = grid/np.maximum(np.ones(3,'d'), grid-1.0) * (maxcorner-mincorner)                        # size from edge to edge = dim * n/(n-1) 
+  size   = np.where(grid > 1, size, min(size[grid > 1]/grid[grid > 1]))     
+
+# ------------------------------------------ process value field -----------------------------------
+
+  stack = [table.data]
+  for type, data in items.iteritems():
+    for i,label in enumerate(data['active']):
+      # we need to reverse order here, because x is fastest,ie rightmost, but leftmost in our x,y,z notation
+      stack.append(gradFFT(size[::-1],
+                           table.data[:,data['column'][i]:data['column'][i]+data['dim']].
+                           reshape([grid[2],grid[1],grid[0]]+data['shape'])))
+
+# ------------------------------------------ output result -----------------------------------------
+
+  if len(stack) > 1: table.data = np.hstack(tuple(stack))
+  table.data_writeArray('%.12g')
+
+# ------------------------------------------ output finalization -----------------------------------
+
+  table.close()                                                                                     # close input ASCII table (works for stdin)

processing/post/filterTable.py

@@ -35,7 +35,7 @@ Filter rows according to condition and columns by either white or black listing.
 
 Examples:
 Every odd row if x coordinate is positive -- " #ip.x# >= 0.0 and #_row_#%2 == 1 ).
-All rows where label 'foo' equals 'bar' -- " #foo# == \"bar\" "
+All rows where label 'foo' equals 'bar' -- " #s#foo# == 'bar' "
 
 """, version = scriptID)
 

processing/post/vtk_addRectilinearGridData.py

@@ -151,7 +151,7 @@ for name in filenames:
   writer = vtk.vtkXMLRectilinearGridWriter()
   writer.SetDataModeToBinary()
   writer.SetCompressorTypeToZLib()
-  writer.SetFileName(os.path.splitext(options.vtk)[0]+('' if options.inplace else '_added.vtr'))
+  writer.SetFileName(os.path.splitext(options.vtk)[0]+('.vtr' if options.inplace else '_added.vtr'))
   if vtk.VTK_MAJOR_VERSION <= 5: writer.SetInput(rGrid)
   else:                          writer.SetInputData(rGrid)
   writer.Write()

processing/pre/geom_canvas.py

@@ -28,24 +28,32 @@ parser.add_option('-o', '--offset',
                   help = 'a,b,c offset from old to new origin of grid [%default]')
 parser.add_option('-f', '--fill',
                   dest = 'fill',
-                  type = 'int', metavar = 'int',
+                  type = 'float', metavar = 'float',
                   help = '(background) canvas grain index. "0" selects maximum microstructure index + 1 [%default]')
+parser.add_option('--float',
+                  dest = 'real',
+                  action = 'store_true',
+                  help = 'input data is float [%default]')
 
 parser.set_defaults(grid = ['0','0','0'],
                     offset = (0,0,0),
                     fill = 0,
+                    real = False,
                    )
 
 (options, filenames) = parser.parse_args()
 
+datatype = 'f' if options.real else 'i'
+
+
 # --- loop over input files -------------------------------------------------------------------------
 
 if filenames == []: filenames = [None]
 
 for name in filenames:
-  try:
+  try: table = damask.ASCIItable(name = name,
-    table = damask.ASCIItable(name = name,
+                                 buffered = False,
-                              buffered = False, labeled = False)
+                                 labeled = False)
   except: continue
   damask.util.report(scriptName,name)
 
@@ -71,7 +79,7 @@ for name in filenames:
 
 # --- read data ------------------------------------------------------------------------------------
 
-  microstructure = table.microstructure_read(info['grid']).reshape(info['grid'],order='F')          # read microstructure
+  microstructure = table.microstructure_read(info['grid'],datatype).reshape(info['grid'],order='F')          # read microstructure
 
 # --- do work ------------------------------------------------------------------------------------
  
@@ -85,8 +93,8 @@ for name in filenames:
                                                                    else int(n) for o,n in zip(info['grid'],options.grid)],'i')
   newInfo['grid'] = np.where(newInfo['grid'] > 0, newInfo['grid'],info['grid'])
 
-  microstructure_cropped = np.zeros(newInfo['grid'],'i')
+  microstructure_cropped = np.zeros(newInfo['grid'],datatype)
-  microstructure_cropped.fill(options.fill if options.fill > 0 else microstructure.max()+1)
+  microstructure_cropped.fill(options.fill if options.real or options.fill > 0 else microstructure.max()+1)
   xindex = list(set(xrange(options.offset[0],options.offset[0]+newInfo['grid'][0])) & \
                                                                set(xrange(info['grid'][0])))
   yindex = list(set(xrange(options.offset[1],options.offset[1]+newInfo['grid'][1])) & \
@@ -152,9 +160,9 @@ for name in filenames:
 
 # --- write microstructure information ------------------------------------------------------------
 
-  formatwidth = int(math.floor(math.log10(microstructure_cropped.max())+1))
+  format = '%g' if options.real else '%{}i'.format(int(math.floor(math.log10(microstructure_cropped.max())+1)))
   table.data = microstructure_cropped.reshape((newInfo['grid'][0],newInfo['grid'][1]*newInfo['grid'][2]),order='F').transpose()
-  table.data_writeArray('%%%ii'%(formatwidth),delimiter=' ')
+  table.data_writeArray(format,delimiter=' ')
     
 # --- output finalization --------------------------------------------------------------------------
 

processing/pre/geom_check.py

@@ -54,12 +54,25 @@ for name in filenames:
   errors = []
   if np.any(info['grid'] < 1):    errors.append('invalid grid a b c.')
   if np.any(info['size'] <= 0.0): errors.append('invalid size x y z.')
+
+#--- read microstructure information --------------------------------------------------------------
+
+  if options.data:
+    microstructure,ok = table.microstructure_read(info['grid'],strict = True)                                 # read microstructure
+
+    if ok:
+      structure = vtk.vtkIntArray()
+      structure.SetName('Microstructures')
+      for idx in microstructure: structure.InsertNextValue(idx)
+
+    else:                           errors.append('mismatch between data and grid dimension.')
+
   if errors != []:
     damask.util.croak(errors)
     table.close(dismiss = True)
     continue
 
-# --- generate VTK rectilinear grid --------------------------------------------------------------------------------
+# --- generate VTK rectilinear grid ---------------------------------------------------------------
 
   grid = vtk.vtkRectilinearGrid()
   grid.SetDimensions([x+1 for x in info['grid']])
@@ -72,18 +85,8 @@ for name in filenames:
     elif i == 1: grid.SetYCoordinates(temp)
     elif i == 2: grid.SetZCoordinates(temp)
 
-#--- read microstructure information --------------------------------------------------------------
 
-  if options.data:
+  if options.data: grid.GetCellData().AddArray(structure)
-    microstructure = table.microstructure_read(info['grid'])                                        # read microstructure
-
-    structure = vtk.vtkIntArray()
-    structure.SetName('Microstructures')
-
-    for idx in microstructure:
-      structure.InsertNextValue(idx)
-
-    grid.GetCellData().AddArray(structure)
 
 # --- write data -----------------------------------------------------------------------------------
   if name:

processing/pre/geom_unpack.py

@@ -18,6 +18,14 @@ Unpack geometry files containing ranges "a to b" and/or "n of x" multiples (excl
 
 """, version = scriptID)
 
+parser.add_option('-1', '--onedimensional',
+                  dest   = 'oneD',
+                  action = 'store_true',
+                  help   = 'output geom file with one-dimensional data arrangement')
+
+parser.set_defaults(oneD = False,
+                   )
+
 (options, filenames) = parser.parse_args()
 
 # --- loop over input files -------------------------------------------------------------------------
@@ -69,7 +77,8 @@ for name in filenames:
 
   microstructure = table.microstructure_read(info['grid'])                                          # read microstructure
   formatwidth = int(math.floor(math.log10(microstructure.max())+1))                                 # efficient number printing format
-  table.data = microstructure.reshape((info['grid'][0],info['grid'][1]*info['grid'][2]),order='F').transpose()
+  table.data = microstructure if options.oneD else \
+               microstructure.reshape((info['grid'][0],info['grid'][1]*info['grid'][2]),order='F').transpose()
   table.data_writeArray('%%%ii'%(formatwidth),delimiter = ' ')
     
 #--- output finalization --------------------------------------------------------------------------