From b386dc73b22814aae891809a4fa3232d5d6eea0d Mon Sep 17 00:00:00 2001
From: Martin Diehl <m.diehl@mpie.de>
Date: Thu, 17 Oct 2019 07:46:20 +0200
Subject: [PATCH] enable to non-transposed tensor data

usually, we store per data per cell, i.e. len(shape(x)) == 3 means x is
a tensor.
Due to the use of transposed tensors (due to column-major storage order
in Fortran), we usually want to store the transpose of (3x3) tensors.
Now the default can be changed
---
 src/element.f90 |  2 +-
 src/results.f90 | 24 +++++++++++++++++++-----
 2 files changed, 20 insertions(+), 6 deletions(-)

diff --git a/src/element.f90 b/src/element.f90
index 8fb7d4c8b..02f5fb762 100644
--- a/src/element.f90
+++ b/src/element.f90
@@ -753,7 +753,7 @@ subroutine tElement_init(self,elemType)
        self%cell        = CELL10
    end select
 
-   self%NcellNodesPerCell = NCELLNODEPERCELL(self%cellType)
+   self%NcellnodesPerCell = NCELLNODEPERCELL(self%cellType)
   
    select case(self%cellType)
      case(1)
diff --git a/src/results.f90 b/src/results.f90
index 2498bf957..025f35602 100644
--- a/src/results.f90
+++ b/src/results.f90
@@ -296,21 +296,35 @@ end subroutine results_writeVectorDataset_real
 !--------------------------------------------------------------------------------------------------
 !> @brief stores a tensor dataset in a group
 !--------------------------------------------------------------------------------------------------
-subroutine results_writeTensorDataset_real(group,dataset,label,description,SIunit)
+subroutine results_writeTensorDataset_real(group,dataset,label,description,SIunit,transposed)
 
   character(len=*), intent(in)                   :: label,group,description
   character(len=*), intent(in), optional         :: SIunit
+  logical,          intent(in), optional         :: transposed
   real(pReal),      intent(in), dimension(:,:,:) :: dataset
   
   integer :: i 
+  logical :: T
   integer(HID_T) :: groupHandle
   real(pReal), dimension(:,:,:), allocatable :: dataset_transposed
 
+  
+  if(present(transposed)) then
+    T = transposed
+  else
+    T = .true.
+  endif
 
-  allocate(dataset_transposed,mold=dataset)
-  do i=1,size(dataset,3)
-    dataset_transposed(1:3,1:3,i) = transpose(dataset(1:3,1:3,i))
-  enddo
+  if(T) then
+    if(size(dataset_transposed,1) /= size(dataset_transposed,2)) &
+      call IO_error(0,ext_msg='transpose non-symmetric tensor')
+    allocate(dataset_transposed,mold=dataset)
+    do i=1,size(dataset_transposed,3)
+      dataset_transposed(:,:,i) = transpose(dataset(:,:,i))
+    enddo
+  else
+    allocate(dataset_transposed,source=dataset)
+  endif
 
   groupHandle = results_openGroup(group)