* 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);
/**
* 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;
/**
* 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);
/**
* 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;
/**
* 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);
/**
*
* Computed once.
*/
- std::vector<Tensor<1,dim> > shape_derivatives;
+ std::vector<Tensor<1,dim> > shape_grads;
/**
* Values of shape function
*
* Computed once.
*/
- std::vector<Tensor<2,dim> > shape_second_derivatives;
+ std::vector<Tensor<2,dim> > shape_hessians;
/**
* Tensors of covariant
*
* Computed on each cell.
*/
- std::vector< DerivativeForm<1,dim,spacedim> > contravariant;
+ std::vector<DerivativeForm<1,dim,spacedim> > contravariant;
/**
* Unit tangential vectors. Used
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(),
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(),
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];
}
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];
}
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];
}
{
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) +
{
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;
}
}
}
{
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;
}
}
}
{
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;
}
}
}
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);
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);
}
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)
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];
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)
// 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;
}
{
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);
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)
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());
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)
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)