]> https://gitweb.dealii.org/ - dealii-svn.git/commitdiff
Use standard naming for fields.
authorbangerth <bangerth@0785d39b-7218-0410-832d-ea1e28bc413d>
Fri, 18 May 2012 14:53:32 +0000 (14:53 +0000)
committerbangerth <bangerth@0785d39b-7218-0410-832d-ea1e28bc413d>
Fri, 18 May 2012 14:53:32 +0000 (14:53 +0000)
git-svn-id: https://svn.dealii.org/branches/branch_higher_derivatives@25520 0785d39b-7218-0410-832d-ea1e28bc413d

deal.II/include/deal.II/fe/mapping_q1.h
deal.II/source/fe/mapping_q.cc
deal.II/source/fe/mapping_q1.cc

index befd17bb2df84f36bfefa02ff3bc398fd15da32e..ce1754e52027ea135d41cc4e3fbf24f2a4c4ab61 100644 (file)
@@ -169,14 +169,14 @@ class MappingQ1 : public Mapping<dim,spacedim>
                                           * vertices must be reordered
                                           * to obtain transformation.
                                           */
-        double shape (const unsigned int qpoint,
+        double shape_value (const unsigned int qpoint,
                       const unsigned int shape_nr) const;
 
                                          /**
                                           * Shape function at quadrature
                                           * point. See above.
                                           */
-        double &shape (const unsigned int qpoint,
+        double &shape_value (const unsigned int qpoint,
                        const unsigned int shape_nr);
 
                                          /**
@@ -184,7 +184,7 @@ class MappingQ1 : public Mapping<dim,spacedim>
                                           * in quadrature point. See
                                           * above.
                                           */
-        Tensor<1,dim> derivative (const unsigned int qpoint,
+        Tensor<1,dim> shape_grad (const unsigned int qpoint,
                                   const unsigned int shape_nr) const;
 
                                          /**
@@ -192,7 +192,7 @@ class MappingQ1 : public Mapping<dim,spacedim>
                                           * in quadrature point. See
                                           * above.
                                           */
-        Tensor<1,dim> &derivative (const unsigned int qpoint,
+        Tensor<1,dim> &shape_grad (const unsigned int qpoint,
                                    const unsigned int shape_nr);
 
                                          /**
@@ -200,7 +200,7 @@ class MappingQ1 : public Mapping<dim,spacedim>
                                           * function in quadrature
                                           * point. See above.
                                           */
-        Tensor<2,dim> second_derivative (const unsigned int qpoint,
+        Tensor<2,dim> shape_hessian (const unsigned int qpoint,
                                          const unsigned int shape_nr) const;
 
                                          /**
@@ -208,7 +208,7 @@ class MappingQ1 : public Mapping<dim,spacedim>
                                           * function in quadrature
                                           * point. See above.
                                           */
-        Tensor<2,dim> &second_derivative (const unsigned int qpoint,
+        Tensor<2,dim> &shape_hessian (const unsigned int qpoint,
                                           const unsigned int shape_nr);
 
                                          /**
@@ -235,7 +235,7 @@ class MappingQ1 : public Mapping<dim,spacedim>
                                           *
                                           * Computed once.
                                           */
-        std::vector<Tensor<1,dim> > shape_derivatives;
+        std::vector<Tensor<1,dim> > shape_grads;
 
                                          /**
                                           * Values of shape function
@@ -245,7 +245,7 @@ class MappingQ1 : public Mapping<dim,spacedim>
                                           *
                                           * Computed once.
                                           */
-        std::vector<Tensor<2,dim> > shape_second_derivatives;
+        std::vector<Tensor<2,dim> > shape_hessians;
 
                                          /**
                                           * Tensors of covariant
@@ -279,7 +279,7 @@ class MappingQ1 : public Mapping<dim,spacedim>
                                           *
                                           * Computed on each cell.
                                           */
-        std::vector< DerivativeForm<1,dim,spacedim> > contravariant;
+        std::vector<DerivativeForm<1,dim,spacedim> > contravariant;
 
                                          /**
                                           * Unit tangential vectors. Used
@@ -802,7 +802,7 @@ struct StaticMappingQ1
 template<int dim, int spacedim>
 inline
 double
-MappingQ1<dim,spacedim>::InternalData::shape (const unsigned int qpoint,
+MappingQ1<dim,spacedim>::InternalData::shape_value (const unsigned int qpoint,
                                      const unsigned int shape_nr) const
 {
   Assert(qpoint*n_shape_functions + shape_nr < shape_values.size(),
@@ -816,7 +816,7 @@ MappingQ1<dim,spacedim>::InternalData::shape (const unsigned int qpoint,
 template<int dim, int spacedim>
 inline
 double &
-MappingQ1<dim,spacedim>::InternalData::shape (const unsigned int qpoint,
+MappingQ1<dim,spacedim>::InternalData::shape_value (const unsigned int qpoint,
                                      const unsigned int shape_nr)
 {
   Assert(qpoint*n_shape_functions + shape_nr < shape_values.size(),
@@ -829,13 +829,13 @@ MappingQ1<dim,spacedim>::InternalData::shape (const unsigned int qpoint,
 template<int dim, int spacedim>
 inline
 Tensor<1,dim>
-MappingQ1<dim,spacedim>::InternalData::derivative (const unsigned int qpoint,
+MappingQ1<dim,spacedim>::InternalData::shape_grad (const unsigned int qpoint,
                                           const unsigned int shape_nr) const
 {
-  Assert(qpoint*n_shape_functions + shape_nr < shape_derivatives.size(),
+  Assert(qpoint*n_shape_functions + shape_nr < shape_grads.size(),
          ExcIndexRange(qpoint*n_shape_functions + shape_nr, 0,
-                       shape_derivatives.size()));
-  return shape_derivatives [qpoint*n_shape_functions + shape_nr];
+                       shape_grads.size()));
+  return shape_grads[qpoint*n_shape_functions + shape_nr];
 }
 
 
@@ -843,26 +843,26 @@ MappingQ1<dim,spacedim>::InternalData::derivative (const unsigned int qpoint,
 template<int dim, int spacedim>
 inline
 Tensor<1,dim> &
-MappingQ1<dim,spacedim>::InternalData::derivative (const unsigned int qpoint,
+MappingQ1<dim,spacedim>::InternalData::shape_grad (const unsigned int qpoint,
                                           const unsigned int shape_nr)
 {
-  Assert(qpoint*n_shape_functions + shape_nr < shape_derivatives.size(),
+  Assert(qpoint*n_shape_functions + shape_nr < shape_grads.size(),
          ExcIndexRange(qpoint*n_shape_functions + shape_nr, 0,
-                       shape_derivatives.size()));
-  return shape_derivatives [qpoint*n_shape_functions + shape_nr];
+                       shape_grads.size()));
+  return shape_grads[qpoint*n_shape_functions + shape_nr];
 }
 
 
 template <int dim, int spacedim>
 inline
 Tensor<2,dim>
-MappingQ1<dim,spacedim>::InternalData::second_derivative (const unsigned int qpoint,
+MappingQ1<dim,spacedim>::InternalData::shape_hessian (const unsigned int qpoint,
                                                           const unsigned int shape_nr) const
 {
-  Assert(qpoint*n_shape_functions + shape_nr < shape_second_derivatives.size(),
+  Assert(qpoint*n_shape_functions + shape_nr < shape_hessians.size(),
          ExcIndexRange(qpoint*n_shape_functions + shape_nr, 0,
-                       shape_second_derivatives.size()));
-  return shape_second_derivatives [qpoint*n_shape_functions + shape_nr];
+                       shape_hessians.size()));
+  return shape_hessians[qpoint*n_shape_functions + shape_nr];
 }
 
 
@@ -870,13 +870,13 @@ MappingQ1<dim,spacedim>::InternalData::second_derivative (const unsigned int qpo
 template <int dim, int spacedim>
 inline
 Tensor<2,dim> &
-MappingQ1<dim,spacedim>::InternalData::second_derivative (const unsigned int qpoint,
+MappingQ1<dim,spacedim>::InternalData::shape_hessian(const unsigned int qpoint,
                                                  const unsigned int shape_nr)
 {
-  Assert(qpoint*n_shape_functions + shape_nr < shape_second_derivatives.size(),
+  Assert(qpoint*n_shape_functions + shape_nr < shape_hessians.size(),
          ExcIndexRange(qpoint*n_shape_functions + shape_nr, 0,
-                       shape_second_derivatives.size()));
-  return shape_second_derivatives [qpoint*n_shape_functions + shape_nr];
+                       shape_hessians.size()));
+  return shape_hessians[qpoint*n_shape_functions + shape_nr];
 }
 
 
index 73817630e1be958e4d650d394beb0330982626dc..407c6871f6df807f3b79b86447e0cb3263dcd2ac 100644 (file)
@@ -203,39 +203,39 @@ MappingQ<dim,spacedim>::compute_shapes_virtual (const std::vector<Point<dim> > &
              ExcInternalError());
       values.resize(n_shape_functions);
     }
-  if (data.shape_derivatives.size()!=0)
+  if (data.shape_grads.size()!=0)
     {
-      Assert(data.shape_derivatives.size()==n_shape_functions*n_points,
+      Assert(data.shape_grads.size()==n_shape_functions*n_points,
              ExcInternalError());
       grads.resize(n_shape_functions);
     }
 
 //                                 // dummy variable of size 0
   std::vector<Tensor<2,dim> > grad2;
-  if (data.shape_second_derivatives.size()!=0)
+  if (data.shape_hessians.size()!=0)
     {
-      Assert(data.shape_second_derivatives.size()==n_shape_functions*n_points,
+      Assert(data.shape_hessians.size()==n_shape_functions*n_points,
              ExcInternalError());
       grad2.resize(n_shape_functions);
     }
 
 
-  if (data.shape_values.size()!=0 || data.shape_derivatives.size()!=0)
+  if (data.shape_values.size()!=0 || data.shape_grads.size()!=0)
     for (unsigned int point=0; point<n_points; ++point)
       {
         tensor_pols->compute(unit_points[point], values, grads, grad2);
 
         if (data.shape_values.size()!=0)
           for (unsigned int i=0; i<n_shape_functions; ++i)
-            data.shape(point,renumber[i]) = values[i];
+            data.shape_value(point,renumber[i]) = values[i];
 
-        if (data.shape_derivatives.size()!=0)
+        if (data.shape_grads.size()!=0)
           for (unsigned int i=0; i<n_shape_functions; ++i)
-            data.derivative(point,renumber[i]) = grads[i];
+            data.shape_grad(point,renumber[i]) = grads[i];
 
-        if (data.shape_second_derivatives.size()!=0)
+        if (data.shape_hessians.size()!=0)
           for (unsigned int i=0; i<n_shape_functions; ++i)
-            data.second_derivative(point,renumber[i]) = grad2[i];
+            data.shape_hessian(point,renumber[i]) = grad2[i];
       }
 }
 
@@ -781,7 +781,7 @@ MappingQ<dim,spacedim>::compute_laplace_vector(Table<2,double> &lvs) const
   const unsigned int n_q_points=quadrature.size();
 
   InternalData quadrature_data(n_shape_functions);
-  quadrature_data.shape_derivatives.resize(n_shape_functions * n_q_points);
+  quadrature_data.shape_grads.resize(n_shape_functions * n_q_points);
   this->compute_shapes(quadrature.get_points(), quadrature_data);
 
                                    // Compute the stiffness matrix of
@@ -790,8 +790,8 @@ MappingQ<dim,spacedim>::compute_laplace_vector(Table<2,double> &lvs) const
   for (unsigned int point=0; point<n_q_points; ++point)
     for (unsigned int i=0; i<n_inner; ++i)
       for (unsigned int j=0; j<n_inner; ++j)
-        S(i,j) += contract(quadrature_data.derivative(point, n_outer+i),
-                           quadrature_data.derivative(point, n_outer+j))
+        S(i,j) += contract(quadrature_data.shape_grad(point, n_outer+i),
+                           quadrature_data.shape_grad(point, n_outer+j))
                   * quadrature.weight(point);
 
                                    // Compute the components of T to be the
@@ -801,8 +801,8 @@ MappingQ<dim,spacedim>::compute_laplace_vector(Table<2,double> &lvs) const
   for (unsigned int point=0; point<n_q_points; ++point)
     for (unsigned int i=0; i<n_inner; ++i)
       for (unsigned int k=0; k<n_outer; ++k)
-        T(i,k) += contract(quadrature_data.derivative(point, n_outer+i),
-                           quadrature_data.derivative(point, k))
+        T(i,k) += contract(quadrature_data.shape_grad(point, n_outer+i),
+                           quadrature_data.shape_grad(point, k))
                   *quadrature.weight(point);
 
   FullMatrix<double> S_1(n_inner);
index b3d683b0b54441afa6732db83b4b6b1b22dd2263..59b35b5e48235ab2d34ed8108571099acd51eef6 100644 (file)
@@ -54,7 +54,8 @@ MappingQ1<dim,spacedim>::InternalData::memory_consumption () const
 {
   return (Mapping<dim,spacedim>::InternalDataBase::memory_consumption() +
           MemoryConsumption::memory_consumption (shape_values) +
-          MemoryConsumption::memory_consumption (shape_derivatives) +
+          MemoryConsumption::memory_consumption (shape_grads) +
+          MemoryConsumption::memory_consumption (shape_hessians) +
           MemoryConsumption::memory_consumption (covariant) +
           MemoryConsumption::memory_consumption (contravariant) +
           MemoryConsumption::memory_consumption (unit_tangentials) +
@@ -107,26 +108,26 @@ namespace internal
             {
               Assert(data.shape_values.size()==n_shape_functions*n_points,
                      ExcInternalError());
-              data.shape(k,0) = 1.-x;
-              data.shape(k,1) = x;
+              data.shape_value(k,0) = 1.-x;
+              data.shape_value(k,1) = x;
             }
-          if (data.shape_derivatives.size()!=0)
+          if (data.shape_grads.size()!=0)
             {
-              Assert(data.shape_derivatives.size()==n_shape_functions*n_points,
+              Assert(data.shape_grads.size()==n_shape_functions*n_points,
                      ExcInternalError());
-              data.derivative(k,0)[0] = -1.;
-              data.derivative(k,1)[0] = 1.;
+              data.shape_grad(k,0)[0] = -1.;
+              data.shape_grad(k,1)[0] = 1.;
             }
-          if (data.shape_second_derivatives.size()!=0)
+          if (data.shape_hessians.size()!=0)
             {
                                                // the following may or may not
                                                // work if dim != spacedim
               Assert (spacedim == 1, ExcNotImplemented());
 
-              Assert(data.shape_second_derivatives.size()==n_shape_functions*n_points,
+              Assert(data.shape_hessians.size()==n_shape_functions*n_points,
                      ExcInternalError());
-              data.second_derivative(k,0)[0][0] = 0;
-              data.second_derivative(k,1)[0][0] = 0;
+              data.shape_hessian(k,0)[0][0] = 0;
+              data.shape_hessian(k,1)[0][0] = 0;
             }
         }
     }
@@ -148,44 +149,44 @@ namespace internal
             {
               Assert(data.shape_values.size()==n_shape_functions*n_points,
                      ExcInternalError());
-              data.shape(k,0) = (1.-x)*(1.-y);
-              data.shape(k,1) = x*(1.-y);
-              data.shape(k,2) = (1.-x)*y;
-              data.shape(k,3) = x*y;
+              data.shape_value(k,0) = (1.-x)*(1.-y);
+              data.shape_value(k,1) = x*(1.-y);
+              data.shape_value(k,2) = (1.-x)*y;
+              data.shape_value(k,3) = x*y;
             }
-          if (data.shape_derivatives.size()!=0)
+          if (data.shape_grads.size()!=0)
             {
-              Assert(data.shape_derivatives.size()==n_shape_functions*n_points,
+              Assert(data.shape_grads.size()==n_shape_functions*n_points,
                      ExcInternalError());
-              data.derivative(k,0)[0] = (y-1.);
-              data.derivative(k,1)[0] = (1.-y);
-              data.derivative(k,2)[0] = -y;
-              data.derivative(k,3)[0] = y;
-              data.derivative(k,0)[1] = (x-1.);
-              data.derivative(k,1)[1] = -x;
-              data.derivative(k,2)[1] = (1.-x);
-              data.derivative(k,3)[1] = x;
+              data.shape_grad(k,0)[0] = (y-1.);
+              data.shape_grad(k,1)[0] = (1.-y);
+              data.shape_grad(k,2)[0] = -y;
+              data.shape_grad(k,3)[0] = y;
+              data.shape_grad(k,0)[1] = (x-1.);
+              data.shape_grad(k,1)[1] = -x;
+              data.shape_grad(k,2)[1] = (1.-x);
+              data.shape_grad(k,3)[1] = x;
             }
-          if (data.shape_second_derivatives.size()!=0)
+          if (data.shape_hessians.size()!=0)
             {
-              Assert(data.shape_second_derivatives.size()==n_shape_functions*n_points,
+              Assert(data.shape_hessians.size()==n_shape_functions*n_points,
                      ExcInternalError());
-              data.second_derivative(k,0)[0][0] = 0;
-              data.second_derivative(k,1)[0][0] = 0;
-              data.second_derivative(k,2)[0][0] = 0;
-              data.second_derivative(k,3)[0][0] = 0;
-              data.second_derivative(k,0)[0][1] = 1.;
-              data.second_derivative(k,1)[0][1] = -1.;
-              data.second_derivative(k,2)[0][1] = -1.;
-              data.second_derivative(k,3)[0][1] = 1.;
-              data.second_derivative(k,0)[1][0] = 1.;
-              data.second_derivative(k,1)[1][0] = -1.;
-              data.second_derivative(k,2)[1][0] = -1.;
-              data.second_derivative(k,3)[1][0] = 1.;
-              data.second_derivative(k,0)[1][1] = 0;
-              data.second_derivative(k,1)[1][1] = 0;
-              data.second_derivative(k,2)[1][1] = 0;
-              data.second_derivative(k,3)[1][1] = 0;
+              data.shape_hessian(k,0)[0][0] = 0;
+              data.shape_hessian(k,1)[0][0] = 0;
+              data.shape_hessian(k,2)[0][0] = 0;
+              data.shape_hessian(k,3)[0][0] = 0;
+              data.shape_hessian(k,0)[0][1] = 1.;
+              data.shape_hessian(k,1)[0][1] = -1.;
+              data.shape_hessian(k,2)[0][1] = -1.;
+              data.shape_hessian(k,3)[0][1] = 1.;
+              data.shape_hessian(k,0)[1][0] = 1.;
+              data.shape_hessian(k,1)[1][0] = -1.;
+              data.shape_hessian(k,2)[1][0] = -1.;
+              data.shape_hessian(k,3)[1][0] = 1.;
+              data.shape_hessian(k,0)[1][1] = 0;
+              data.shape_hessian(k,1)[1][1] = 0;
+              data.shape_hessian(k,2)[1][1] = 0;
+              data.shape_hessian(k,3)[1][1] = 0;
             }
         }
     }
@@ -209,127 +210,127 @@ namespace internal
             {
               Assert(data.shape_values.size()==n_shape_functions*n_points,
                      ExcInternalError());
-              data.shape(k,0) = (1.-x)*(1.-y)*(1.-z);
-              data.shape(k,1) = x*(1.-y)*(1.-z);
-              data.shape(k,2) = (1.-x)*y*(1.-z);
-              data.shape(k,3) = x*y*(1.-z);
-              data.shape(k,4) = (1.-x)*(1.-y)*z;
-              data.shape(k,5) = x*(1.-y)*z;
-              data.shape(k,6) = (1.-x)*y*z;
-              data.shape(k,7) = x*y*z;
+              data.shape_value(k,0) = (1.-x)*(1.-y)*(1.-z);
+              data.shape_value(k,1) = x*(1.-y)*(1.-z);
+              data.shape_value(k,2) = (1.-x)*y*(1.-z);
+              data.shape_value(k,3) = x*y*(1.-z);
+              data.shape_value(k,4) = (1.-x)*(1.-y)*z;
+              data.shape_value(k,5) = x*(1.-y)*z;
+              data.shape_value(k,6) = (1.-x)*y*z;
+              data.shape_value(k,7) = x*y*z;
             }
-          if (data.shape_derivatives.size()!=0)
+          if (data.shape_grads.size()!=0)
             {
-              Assert(data.shape_derivatives.size()==n_shape_functions*n_points,
+              Assert(data.shape_grads.size()==n_shape_functions*n_points,
                      ExcInternalError());
-              data.derivative(k,0)[0] = (y-1.)*(1.-z);
-              data.derivative(k,1)[0] = (1.-y)*(1.-z);
-              data.derivative(k,2)[0] = -y*(1.-z);
-              data.derivative(k,3)[0] = y*(1.-z);
-              data.derivative(k,4)[0] = (y-1.)*z;
-              data.derivative(k,5)[0] = (1.-y)*z;
-              data.derivative(k,6)[0] = -y*z;
-              data.derivative(k,7)[0] = y*z;
-              data.derivative(k,0)[1] = (x-1.)*(1.-z);
-              data.derivative(k,1)[1] = -x*(1.-z);
-              data.derivative(k,2)[1] = (1.-x)*(1.-z);
-              data.derivative(k,3)[1] = x*(1.-z);
-              data.derivative(k,4)[1] = (x-1.)*z;
-              data.derivative(k,5)[1] = -x*z;
-              data.derivative(k,6)[1] = (1.-x)*z;
-              data.derivative(k,7)[1] = x*z;
-              data.derivative(k,0)[2] = (x-1)*(1.-y);
-              data.derivative(k,1)[2] = x*(y-1.);
-              data.derivative(k,2)[2] = (x-1.)*y;
-              data.derivative(k,3)[2] = -x*y;
-              data.derivative(k,4)[2] = (1.-x)*(1.-y);
-              data.derivative(k,5)[2] = x*(1.-y);
-              data.derivative(k,6)[2] = (1.-x)*y;
-              data.derivative(k,7)[2] = x*y;
+              data.shape_grad(k,0)[0] = (y-1.)*(1.-z);
+              data.shape_grad(k,1)[0] = (1.-y)*(1.-z);
+              data.shape_grad(k,2)[0] = -y*(1.-z);
+              data.shape_grad(k,3)[0] = y*(1.-z);
+              data.shape_grad(k,4)[0] = (y-1.)*z;
+              data.shape_grad(k,5)[0] = (1.-y)*z;
+              data.shape_grad(k,6)[0] = -y*z;
+              data.shape_grad(k,7)[0] = y*z;
+              data.shape_grad(k,0)[1] = (x-1.)*(1.-z);
+              data.shape_grad(k,1)[1] = -x*(1.-z);
+              data.shape_grad(k,2)[1] = (1.-x)*(1.-z);
+              data.shape_grad(k,3)[1] = x*(1.-z);
+              data.shape_grad(k,4)[1] = (x-1.)*z;
+              data.shape_grad(k,5)[1] = -x*z;
+              data.shape_grad(k,6)[1] = (1.-x)*z;
+              data.shape_grad(k,7)[1] = x*z;
+              data.shape_grad(k,0)[2] = (x-1)*(1.-y);
+              data.shape_grad(k,1)[2] = x*(y-1.);
+              data.shape_grad(k,2)[2] = (x-1.)*y;
+              data.shape_grad(k,3)[2] = -x*y;
+              data.shape_grad(k,4)[2] = (1.-x)*(1.-y);
+              data.shape_grad(k,5)[2] = x*(1.-y);
+              data.shape_grad(k,6)[2] = (1.-x)*y;
+              data.shape_grad(k,7)[2] = x*y;
             }
-          if (data.shape_second_derivatives.size()!=0)
+          if (data.shape_hessians.size()!=0)
             {
                                                // the following may or may not
                                                // work if dim != spacedim
               Assert (spacedim == 3, ExcNotImplemented());
 
-              Assert(data.shape_second_derivatives.size()==n_shape_functions*n_points,
+              Assert(data.shape_hessians.size()==n_shape_functions*n_points,
                      ExcInternalError());
-              data.second_derivative(k,0)[0][0] = 0;
-              data.second_derivative(k,1)[0][0] = 0;
-              data.second_derivative(k,2)[0][0] = 0;
-              data.second_derivative(k,3)[0][0] = 0;
-              data.second_derivative(k,4)[0][0] = 0;
-              data.second_derivative(k,5)[0][0] = 0;
-              data.second_derivative(k,6)[0][0] = 0;
-              data.second_derivative(k,7)[0][0] = 0;
-              data.second_derivative(k,0)[1][1] = 0;
-              data.second_derivative(k,1)[1][1] = 0;
-              data.second_derivative(k,2)[1][1] = 0;
-              data.second_derivative(k,3)[1][1] = 0;
-              data.second_derivative(k,4)[1][1] = 0;
-              data.second_derivative(k,5)[1][1] = 0;
-              data.second_derivative(k,6)[1][1] = 0;
-              data.second_derivative(k,7)[1][1] = 0;
-              data.second_derivative(k,0)[2][2] = 0;
-              data.second_derivative(k,1)[2][2] = 0;
-              data.second_derivative(k,2)[2][2] = 0;
-              data.second_derivative(k,3)[2][2] = 0;
-              data.second_derivative(k,4)[2][2] = 0;
-              data.second_derivative(k,5)[2][2] = 0;
-              data.second_derivative(k,6)[2][2] = 0;
-              data.second_derivative(k,7)[2][2] = 0;
-
-              data.second_derivative(k,0)[0][1] = (1.-z);
-              data.second_derivative(k,1)[0][1] = -(1.-z);
-              data.second_derivative(k,2)[0][1] = -(1.-z);
-              data.second_derivative(k,3)[0][1] = (1.-z);
-              data.second_derivative(k,4)[0][1] = z;
-              data.second_derivative(k,5)[0][1] = -z;
-              data.second_derivative(k,6)[0][1] = -z;
-              data.second_derivative(k,7)[0][1] = z;
-              data.second_derivative(k,0)[1][0] = (1.-z);
-              data.second_derivative(k,1)[1][0] = -(1.-z);
-              data.second_derivative(k,2)[1][0] = -(1.-z);
-              data.second_derivative(k,3)[1][0] = (1.-z);
-              data.second_derivative(k,4)[1][0] = z;
-              data.second_derivative(k,5)[1][0] = -z;
-              data.second_derivative(k,6)[1][0] = -z;
-              data.second_derivative(k,7)[1][0] = z;
-
-              data.second_derivative(k,0)[0][2] = (1.-y);
-              data.second_derivative(k,1)[0][2] = -(1.-y);
-              data.second_derivative(k,2)[0][2] = y;
-              data.second_derivative(k,3)[0][2] = -y;
-              data.second_derivative(k,4)[0][2] = -(1.-y);
-              data.second_derivative(k,5)[0][2] = (1.-y);
-              data.second_derivative(k,6)[0][2] = -y;
-              data.second_derivative(k,7)[0][2] = y;
-              data.second_derivative(k,0)[2][0] = (1.-y);
-              data.second_derivative(k,1)[2][0] = -(1.-y);
-              data.second_derivative(k,2)[2][0] = y;
-              data.second_derivative(k,3)[2][0] = -y;
-              data.second_derivative(k,4)[2][0] = -(1.-y);
-              data.second_derivative(k,5)[2][0] = (1.-y);
-              data.second_derivative(k,6)[2][0] = -y;
-              data.second_derivative(k,7)[2][0] = y;
-
-              data.second_derivative(k,0)[1][2] = (1.-x);
-              data.second_derivative(k,1)[1][2] = x;
-              data.second_derivative(k,2)[1][2] = -(1.-x);
-              data.second_derivative(k,3)[1][2] = -x;
-              data.second_derivative(k,4)[1][2] = -(1.-x);
-              data.second_derivative(k,5)[1][2] = -x;
-              data.second_derivative(k,6)[1][2] = (1.-x);
-              data.second_derivative(k,7)[1][2] = x;
-              data.second_derivative(k,0)[2][1] = (1.-x);
-              data.second_derivative(k,1)[2][1] = x;
-              data.second_derivative(k,2)[2][1] = -(1.-x);
-              data.second_derivative(k,3)[2][1] = -x;
-              data.second_derivative(k,4)[2][1] = -(1.-x);
-              data.second_derivative(k,5)[2][1] = -x;
-              data.second_derivative(k,6)[2][1] = (1.-x);
-              data.second_derivative(k,7)[2][1] = x;
+              data.shape_hessian(k,0)[0][0] = 0;
+              data.shape_hessian(k,1)[0][0] = 0;
+              data.shape_hessian(k,2)[0][0] = 0;
+              data.shape_hessian(k,3)[0][0] = 0;
+              data.shape_hessian(k,4)[0][0] = 0;
+              data.shape_hessian(k,5)[0][0] = 0;
+              data.shape_hessian(k,6)[0][0] = 0;
+              data.shape_hessian(k,7)[0][0] = 0;
+              data.shape_hessian(k,0)[1][1] = 0;
+              data.shape_hessian(k,1)[1][1] = 0;
+              data.shape_hessian(k,2)[1][1] = 0;
+              data.shape_hessian(k,3)[1][1] = 0;
+              data.shape_hessian(k,4)[1][1] = 0;
+              data.shape_hessian(k,5)[1][1] = 0;
+              data.shape_hessian(k,6)[1][1] = 0;
+              data.shape_hessian(k,7)[1][1] = 0;
+              data.shape_hessian(k,0)[2][2] = 0;
+              data.shape_hessian(k,1)[2][2] = 0;
+              data.shape_hessian(k,2)[2][2] = 0;
+              data.shape_hessian(k,3)[2][2] = 0;
+              data.shape_hessian(k,4)[2][2] = 0;
+              data.shape_hessian(k,5)[2][2] = 0;
+              data.shape_hessian(k,6)[2][2] = 0;
+              data.shape_hessian(k,7)[2][2] = 0;
+
+              data.shape_hessian(k,0)[0][1] = (1.-z);
+              data.shape_hessian(k,1)[0][1] = -(1.-z);
+              data.shape_hessian(k,2)[0][1] = -(1.-z);
+              data.shape_hessian(k,3)[0][1] = (1.-z);
+              data.shape_hessian(k,4)[0][1] = z;
+              data.shape_hessian(k,5)[0][1] = -z;
+              data.shape_hessian(k,6)[0][1] = -z;
+              data.shape_hessian(k,7)[0][1] = z;
+              data.shape_hessian(k,0)[1][0] = (1.-z);
+              data.shape_hessian(k,1)[1][0] = -(1.-z);
+              data.shape_hessian(k,2)[1][0] = -(1.-z);
+              data.shape_hessian(k,3)[1][0] = (1.-z);
+              data.shape_hessian(k,4)[1][0] = z;
+              data.shape_hessian(k,5)[1][0] = -z;
+              data.shape_hessian(k,6)[1][0] = -z;
+              data.shape_hessian(k,7)[1][0] = z;
+
+              data.shape_hessian(k,0)[0][2] = (1.-y);
+              data.shape_hessian(k,1)[0][2] = -(1.-y);
+              data.shape_hessian(k,2)[0][2] = y;
+              data.shape_hessian(k,3)[0][2] = -y;
+              data.shape_hessian(k,4)[0][2] = -(1.-y);
+              data.shape_hessian(k,5)[0][2] = (1.-y);
+              data.shape_hessian(k,6)[0][2] = -y;
+              data.shape_hessian(k,7)[0][2] = y;
+              data.shape_hessian(k,0)[2][0] = (1.-y);
+              data.shape_hessian(k,1)[2][0] = -(1.-y);
+              data.shape_hessian(k,2)[2][0] = y;
+              data.shape_hessian(k,3)[2][0] = -y;
+              data.shape_hessian(k,4)[2][0] = -(1.-y);
+              data.shape_hessian(k,5)[2][0] = (1.-y);
+              data.shape_hessian(k,6)[2][0] = -y;
+              data.shape_hessian(k,7)[2][0] = y;
+
+              data.shape_hessian(k,0)[1][2] = (1.-x);
+              data.shape_hessian(k,1)[1][2] = x;
+              data.shape_hessian(k,2)[1][2] = -(1.-x);
+              data.shape_hessian(k,3)[1][2] = -x;
+              data.shape_hessian(k,4)[1][2] = -(1.-x);
+              data.shape_hessian(k,5)[1][2] = -x;
+              data.shape_hessian(k,6)[1][2] = (1.-x);
+              data.shape_hessian(k,7)[1][2] = x;
+              data.shape_hessian(k,0)[2][1] = (1.-x);
+              data.shape_hessian(k,1)[2][1] = x;
+              data.shape_hessian(k,2)[2][1] = -(1.-x);
+              data.shape_hessian(k,3)[2][1] = -x;
+              data.shape_hessian(k,4)[2][1] = -(1.-x);
+              data.shape_hessian(k,5)[2][1] = -x;
+              data.shape_hessian(k,6)[2][1] = (1.-x);
+              data.shape_hessian(k,7)[2][1] = x;
             }
         }
     }
@@ -468,7 +469,7 @@ MappingQ1<dim,spacedim>::compute_data (const UpdateFlags      update_flags,
     data.shape_values.resize(data.n_shape_functions * n_q_points);
 
   if (flags & update_transformation_gradients)
-    data.shape_derivatives.resize(data.n_shape_functions * n_q_points);
+    data.shape_grads.resize(data.n_shape_functions * n_q_points);
 
   if (flags & update_covariant_transformation)
     data.covariant.resize(n_original_q_points);
@@ -480,7 +481,7 @@ MappingQ1<dim,spacedim>::compute_data (const UpdateFlags      update_flags,
     data.volume_elements.resize(n_original_q_points);
 
   if (flags & update_jacobian_grads)
-    data.shape_second_derivatives.resize(data.n_shape_functions * n_q_points);
+    data.shape_hessians.resize(data.n_shape_functions * n_q_points);
 
   compute_shapes (q.get_points(), data);
 }
@@ -637,7 +638,7 @@ MappingQ1<dim,spacedim>::compute_fill (const typename Triangulation<dim,spacedim
 
       for (unsigned int point=0; point<n_q_points; ++point)
         {
-          const double * shape = &data.shape(point+data_set,0);
+          const double * shape = &data.shape_value(point+data_set,0);
           Point<spacedim> result = (shape[0] *
                                     data.mapping_support_points[0]);
           for (unsigned int k=1; k<data.n_shape_functions; ++k)
@@ -667,7 +668,7 @@ MappingQ1<dim,spacedim>::compute_fill (const typename Triangulation<dim,spacedim
           for (unsigned int point=0; point<n_q_points; ++point)
             {
               const Tensor<1,dim> * data_derv =
-                &data.derivative(point+data_set, 0);
+                &data.shape_grad(point+data_set, 0);
 
               double result [spacedim][dim];
 
@@ -870,7 +871,7 @@ MappingQ1<dim,spacedim>::fill_fe_values (
           for (unsigned int point=0; point<n_q_points; ++point)
             {
               const Tensor<2,dim> * second =
-                &data.second_derivative(point+data_set, 0);
+                &data.shape_hessian(point+data_set, 0);
               double result [spacedim][dim][dim];
               for (unsigned int i=0; i<spacedim; ++i)
                 for (unsigned int j=0; j<dim; ++j)
@@ -1463,7 +1464,7 @@ transform_unit_to_real_cell_internal (const InternalData &data) const
                                    // compute the point in real space.
   Point<spacedim> p_real;
   for (unsigned int i=0; i<data.mapping_support_points.size(); ++i)
-    p_real += data.mapping_support_points[i] * data.shape(0,i);
+    p_real += data.mapping_support_points[i] * data.shape_value(0,i);
 
   return p_real;
 }
@@ -1677,7 +1678,7 @@ transform_real_to_unit_cell_internal
 {
   const unsigned int n_shapes=mdata.shape_values.size();
   Assert(n_shapes!=0, ExcInternalError());
-  AssertDimension (mdata.shape_derivatives.size(), n_shapes);
+  AssertDimension (mdata.shape_grads.size(), n_shapes);
 
   std::vector<Point<spacedim> > &points=mdata.mapping_support_points;
   AssertDimension (points.size(), n_shapes);
@@ -1713,7 +1714,7 @@ transform_real_to_unit_cell_internal
       Tensor<2,spacedim> df;
       for (unsigned int k=0; k<mdata.n_shape_functions; ++k)
         {
-          const Tensor<1,dim> &grad_transform=mdata.derivative(0,k);
+          const Tensor<1,dim> &grad_transform=mdata.shape_grad(0,k);
           const Point<spacedim> &point=points[k];
 
           for (unsigned int i=0; i<spacedim; ++i)
@@ -1831,8 +1832,8 @@ transform_real_to_unit_cell_internal_codim1
 
   const unsigned int n_shapes=mdata.shape_values.size();
   Assert(n_shapes!=0, ExcInternalError());
-  Assert(mdata.shape_derivatives.size()==n_shapes, ExcInternalError());
-  Assert(mdata.shape_second_derivatives.size()==n_shapes, ExcInternalError());
+  Assert(mdata.shape_grads.size()==n_shapes, ExcInternalError());
+  Assert(mdata.shape_hessians.size()==n_shapes, ExcInternalError());
 
   std::vector<Point<spacedim1> > &points=mdata.mapping_support_points;
   Assert(points.size()==n_shapes, ExcInternalError());
@@ -1849,8 +1850,8 @@ transform_real_to_unit_cell_internal_codim1
   compute_shapes(std::vector<Point<dim1> > (1, p_unit), mdata);
   for (unsigned int k=0; k<mdata.n_shape_functions; ++k)
     {
-      const Tensor<1,dim1>   &grad_phi_k = mdata.derivative(0,k);
-      const Tensor<2,dim1>   &hessian_k  = mdata.second_derivative(0,k);
+      const Tensor<1,dim1>   &grad_phi_k = mdata.shape_grad(0,k);
+      const Tensor<2,dim1>   &hessian_k  = mdata.shape_hessian(0,k);
       const Point<spacedim1> &point_k = points[k];
 
       for (unsigned int j=0; j<dim1; ++j)
@@ -1901,8 +1902,8 @@ transform_real_to_unit_cell_internal_codim1
       compute_shapes(std::vector<Point<dim1> > (1, p_unit), mdata);
       for (unsigned int k=0; k<mdata.n_shape_functions; ++k)
         {
-          const Tensor<1,dim1>   &grad_phi_k = mdata.derivative(0,k);
-          const Tensor<2,dim1>   &hessian_k  = mdata.second_derivative(0,k);
+          const Tensor<1,dim1>   &grad_phi_k = mdata.shape_grad(0,k);
+          const Tensor<2,dim1>   &hessian_k  = mdata.shape_hessian(0,k);
           const Point<spacedim1> &point_k = points[k];
 
           for (unsigned int j=0; j<dim1; ++j)

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