// Jacobian on the unit cell. Then j' = phi' k'/k^2 = j k' j^2.
template <int dim, typename Number>
Tensor<1, dim *(dim + 1) / 2, Tensor<1, dim, Number>>
- process_jacobian_gradient(const Tensor<2, dim, Number> &inv_jac_permut,
+ process_jacobian_gradient(const Tensor<2, dim, Number> &inv_jac_permutation,
const Tensor<2, dim, Number> &inv_jac,
const Tensor<3, dim, Number> &jac_grad)
{
Number inv_jac_grad[dim][dim][dim];
- // compute: inv_jac_grad = inv_jac_permut * grad_unit(jac)
+ // compute: inv_jac_grad = inv_jac_permutation * grad_unit(jac)
for (unsigned int d = 0; d < dim; ++d)
for (unsigned int e = 0; e < dim; ++e)
for (unsigned int f = 0; f < dim; ++f)
{
inv_jac_grad[f][e][d] =
- (inv_jac_permut[f][0] * jac_grad[d][e][0]);
+ (inv_jac_permutation[f][0] * jac_grad[d][e][0]);
for (unsigned int g = 1; g < dim; ++g)
inv_jac_grad[f][e][d] +=
- (inv_jac_permut[f][g] * jac_grad[d][e][g]);
+ (inv_jac_permutation[f][g] * jac_grad[d][e][g]);
}
- // compute: transpose (-inv_jac_permut * inv_jac_grad[d] * inv_jac)
+ // compute: transpose (-inv_jac_permutation * inv_jac_grad[d] * inv_jac)
Number tmp[dim];
Number grad_jac_inv[dim][dim][dim];
for (unsigned int d = 0; d < dim; ++d)
// needed for non-diagonal part of Jacobian grad
for (unsigned int f = 0; f < dim; ++f)
{
- grad_jac_inv[f][d][e] = inv_jac_permut[f][0] * tmp[0];
+ grad_jac_inv[f][d][e] = inv_jac_permutation[f][0] * tmp[0];
for (unsigned int g = 1; g < dim; ++g)
- grad_jac_inv[f][d][e] += inv_jac_permut[f][g] * tmp[g];
+ grad_jac_inv[f][d][e] += inv_jac_permutation[f][g] * tmp[g];
}
}
unsigned int q,
Tensor<2, dim, VectorizedDouble> inv_jac,
FEEvaluationData<dim, VectorizedDouble, true> &eval) {
- Tensor<2, dim, VectorizedDouble> inv_transp_jac_permut;
+ Tensor<2, dim, VectorizedDouble> inv_transp_jac_permutation;
for (unsigned int d = 0; d < dim; ++d)
for (unsigned int e = 0; e < dim; ++e)
{
const unsigned int ee =
ExtractFaceHelper::reorder_face_derivative_indices<
dim>(face_no, e);
- inv_transp_jac_permut[d][e] = inv_jac[ee][d];
+ inv_transp_jac_permutation[d][e] = inv_jac[ee][d];
}
Tensor<2, dim, VectorizedDouble> jacobi;
for (unsigned int e = 0; e < dim; ++e)
eval.begin_hessians()[q + (d * hess_dim + c) *
n_q_points];
const auto inv_jac_grad =
- process_jacobian_gradient(inv_transp_jac_permut,
+ process_jacobian_gradient(inv_transp_jac_permutation,
inv_transp_jac,
jac_grad);
for (unsigned int e = 0; e < dim; ++e)