# DOF permutations and transformations¶

When using high degree finite elements on general meshes, adjustments may need to be made to correct for differences in the orientation of mesh entities on the mesh and on the reference cell. For example, in a degree 4 Lagrange element on a triangle, there are 3 degrees of freedom (DOFs) associated with each edge. If two neighbouring cells in a mesh disagree on the direction of the edge, they could put an incorrectly combine the local basis functions to give the wrong global basis function.

This issue and the use of permutations and transformations to correct it is discussed in detail in Construction of arbitrary order finite element degree-of-freedom maps on polygonal and polyhedral cell meshes (Scroggs, Dokken, Richardons, Wells, 2021).

Functions to permute and transform high degree elements are provided by Basix. In this demo, we show how these can be used.

First, we import Basix and Numpy.

import basix
import numpy as np
from basix import ElementFamily, CellType, LagrangeVariant, LatticeType


## Degree 5 Lagrange element¶

We create a degree 5 Lagrange element on a triangle, then print the values of the attributes dof_transformations_are_identity and dof_transformations_are_permutations.

The value of dof_transformations_are_identity is False: this tells us that permutations or transformations are needed for this element.

The value of dof_transformations_are_permutations is True: this tells us that for this element, all the corrections we need to apply permutations. This is the simpler case, and means we make the orientation corrections by applying permutations when creating the DOF map.

lagrange = basix.create_element(
ElementFamily.P, CellType.triangle, 5, LagrangeVariant.equispaced)
print(lagrange.dof_transformations_are_identity)
print(lagrange.dof_transformations_are_permutations)


We can apply permutations by using the matrices returned by the method base_transformations. This method will return one matrix for each edge of the cell (for 2D and 3D cells), and two matrices for each face of the cell (for 3D cells). These describe the effect of reversing the edge or reflecting and rotating the face.

For this element, we know that the base transformations will be permutation matrices.

print(lagrange.base_transformations())


The matrices returned by base_transformations are quite large, and are equal to the identity matrix except for a small block of the matrix. It is often easier and more efficient to use the matrices returned by the method entity_transformations instead.

entity_transformations returns a dictionary that maps the type of entity (“interval”, “triangle”, “quadrilateral”) to a matrix describing the effect of permuting that entity on the DOFs on that entity.

For this element, we see that this method returns one matrix for an interval: this matrix reverses the order of the four DOFs associated with that edge.

print(lagrange.entity_transformations())


In orders to work out which DOFs are associated with each edge, we use the attribute entity_dofs. For example, the following can be used to see which DOF numbers are associated with edge (dim 1) number 2:

print(lagrange.entity_dofs)


## Degree 2 Lagrange element¶

For a degree 2 Lagrange element, no permutations or transformations are needed. We can verify this by checking that dof_transformations_are_identity is True. To confirm that the transformations are identity matrices, we also print the base transformations.

lagrange_degree_2 = basix.create_element(
ElementFamily.P, CellType.triangle, 2, LagrangeVariant.equispaced)
print(lagrange_degree_2.dof_transformations_are_identity)
print(lagrange_degree_2.base_transformations())


## Degree 2 Nédélec element¶

For a degree 2 Nédélec (first kind) element on a tetrahedron, the corrections are not all permutations, so both dof_transformations_are_identity and dof_transformations_are_permutations are False.

nedelec = basix.create_element(ElementFamily.N1E, CellType.tetrahedron, 2)
print(nedelec.dof_transformations_are_identity)
print(nedelec.dof_transformations_are_permutations)


For this element, entity_transformations returns a dictionary with two entries: a matrix for an interval that describes the effect of reversing the edge; and an array of two matrices for a triangle. The first matrix for the triangle describes the effect of rotating the triangle. The second matrix describes the effect of reflecting the triangle.

For this element, the matrix describing the effect of rotating the triangle is

$\begin{split}\left(\begin{array}{cc}-1&-1\\1&0\end{array}\right).\end{split}$

This is not a permutation, so this must be applied when assembling a form and cannot be applied to the DOF numbering in the DOF map.

print(nedelec.entity_transformations())


To demonstrate how these transformations can be used, we create a lattice of points where we will tabulate the element.

points = basix.create_lattice(
CellType.tetrahedron, 5, LatticeType.equispaced, True)


If (for example) the direction of edge 2 in the physical cell does not match its direction on the reference, then we need to adjust the tabulated data.

As the cell sub-entity that we are correcting is an interval, we get the “interval” item from the entity transformations dictionary. We use entity_dofs (1 is the dimension of an edge, 2 is the index of the edge we are reversing) to find out which dofs are on our edge.

To adjust the tabulated data, we loop over each point in the lattice and over the value size. For each of these values, we apply the transformation matrix to the relevant DOFs.

data = nedelec.tabulate(0, points)

transformation = nedelec.entity_transformations()["interval"]
dofs = nedelec.entity_dofs

for point in range(data.shape):
for dim in range(data.shape):
data[0, point, dofs, dim] = np.dot(transformation, data[0, point, dofs, dim])

print(data)


More efficient functions that apply the transformations and permutations directly to data can be used via Basix’s C++ interface.

## C++ demo¶

The following C++ code runs the same demo using Basix’s C++ interface:

// ====================================
// DOF permutations and transformations
// ====================================

// When using high degree finite elements on general meshes, adjustments
// may need to be made to correct for differences in the orientation of
// mesh entities on the mesh and on the reference cell. For example, in
// a degree 4 Lagrange element on a triangle, there are 3 degrees of
// freedom (DOFs) associated with each edge. If two neighbouring cells in
// a mesh disagree on the direction of the edge, they could put an
// incorrectly combine the local basis functions to give the wrong global
// basis function.

// This issue and the use of permutations and transformations to correct
// it is discussed in detail in Construction of arbitrary order finite
// element degree-of-freedom maps on polygonal and polyhedral cell
// meshes (Scroggs, Dokken, Richardons, Wells,
// 2021) <https://arxiv.org/abs/2102.11901>_.

// Functions to permute and transform high degree elements are
// provided by Basix. In this demo, we show how these can be used from C++.

#include <basix/finite-element.h>
#include <basix/lattice.h>
#include <iomanip>
#include <xtensor/xio.hpp>

static const std::map<basix::cell::type, std::string> type_to_name
= {{basix::cell::type::point, "point"},
{basix::cell::type::interval, "interval"},
{basix::cell::type::triangle, "triangle"},
{basix::cell::type::tetrahedron, "tetrahedron"},
{basix::cell::type::pyramid, "pyramid"},
{basix::cell::type::prism, "prism"},
{basix::cell::type::hexahedron, "hexahedron"}};

int main(int argc, char* argv[])
{
// Degree 5 Lagrange element
// =========================
{
std::cout << "Degree 5 Lagrange element \n";

// Create a degree 5 Lagrange element on a triangle
auto family = basix::element::family::P;
auto cell_type = basix::cell::type::triangle;
int degree = 5;
auto variant = basix::element::lagrange_variant::equispaced;

// Create the lagrange element
basix::FiniteElement lagrange
= basix::create_element(family, cell_type, degree, variant);

// Print bools as true/false instead of 0/1
std::cout << std::boolalpha;

// The value of dof_transformations_are_identity is false: this tells
// us that permutations or transformations are needed for this element.
std::cout << "Dof transformations are identity: "
<< lagrange.dof_transformations_are_identity() << "\n";

// The value of dof_transformations_are_permutations is true: this
// tells us that for this element, all the corrections we need to apply
// permutations. This is the simpler case, and means we make the
// orientation corrections by applying permutations when creating the
// DOF map.
std::cout << "Dof transformations are permutations: "
<< lagrange.dof_transformations_are_permutations() << "\n";

// We can apply permutations by using the matrices returned by the
// method base_transformations. This method will return one matrix
// for each edge of the cell (for 2D and 3D cells), and two matrices
// for each face of the cell (for 3D cells). These describe the effect
// of reversing the edge or reflecting and rotating the face.

// For this element, we know that the base transformations will be
// permutation matrices.
std::cout << "\nBase transformations: \n";
std::cout << lagrange.base_transformations() << "\n";

// The matrices returned by base_transformations are quite large, and
// are equal to the identity matrix except for a small block of the
// matrix. It is often easier and more efficient to use the matrices
// returned by the method entity_transformations instead.

// entity_transformations returns a dictionary that maps the type
// of entity ("interval", "triangle", "quadrilateral") to a
// matrix describing the effect of permuting that entity on the DOFs
// on that entity.
std::map<basix::cell::type, xt::xtensor<double, 3>> entity__transformation
= lagrange.entity_transformations();

std::cout << "\nEntity transformations: \n";
for (auto const& [cell, transformation] : entity__transformation)
std::cout << " -" << type_to_name.at(cell) << ":\n"
<< transformation << std::endl;

// For this element, we see that this method returns one matrix for
// an interval: this matrix reverses the order of the four DOFs
// associated with that edge.

// In orders to work out which DOFs are associated with each edge,
// we use the attribute entity_dofs. For example, the following can
// be used to see which DOF numbers are associated with edge (dim 1)
// number 2:
int dim = 1;
int edge_num = 2;
std::vector<int> entity_dofs = lagrange.entity_dofs()[dim][edge_num];
std::cout << "\n Entity dofs of Edge number 2: ";
for (const auto dof : entity_dofs)
std::cout << dof << " ";
}
// Degree 2 Lagrange element
// =========================
{
// For a degree 2 Lagrange element, no permutations or transformations
// are needed.
std::cout << "\n\nDegree 2 Lagrange element \n";
auto family = basix::element::family::P;
auto cell_type = basix::cell::type::triangle;
int degree = 2;
auto variant = basix::element::lagrange_variant::equispaced;

// Create the lagrange element
auto lagrange = basix::create_element(family, cell_type, degree, variant);

// We can verify this by checking thatdof_transformations_are_identity is
// True. To confirm that the transformations are identity matrices, we
// also print the base transformations.
std::cout << "Dof transformations are identity: "
<< lagrange.dof_transformations_are_identity() << "\n";

std::cout << "Dof transformations are permutations: "
<< lagrange.dof_transformations_are_permutations() << "\n";
}

// Degree 2 Nédélec element
// ========================
{
std::cout << "\n\nDegree 2 Nedelec element \n";
// For a degree 2 Nédélec (first kind) element on a tetrahedron, the
// corrections are not all permutations, so both
// dof_transformations_are_identity and
// dof_transformations_are_permutations are False.

auto family = basix::element::family::N1E;
auto cell_type = basix::cell::type::tetrahedron;
int degree = 2;
auto nedelec = basix::create_element(family, cell_type, degree);

std::cout << "Dof transformations are identity: "
<< nedelec.dof_transformations_are_identity() << "\n";
std::cout << "Dof transformations are permutations: "
<< nedelec.dof_transformations_are_permutations() << "\n";

// For this element, entity_transformations returns a map
// with two entries: a matrix for an interval that describes
// the effect of reversing the edge; and an array of two matrices
// for a triangle. The first matrix for the triangle describes
// the effect of rotating the triangle. The second matrix describes
// the effect of reflecting the triangle.

// For this element, the matrix describing the effect of rotating
// the triangle is

// .. math::
//    \left(\begin{array}{cc}-1&-1\\1&0\end{array}\right).

// This is not a permutation, so this must be applied when assembling
// a form and cannot be applied to the DOF numbering in the DOF map.
std::map<basix::cell::type, xt::xtensor<double, 3>> entity__transformation
= nedelec.entity_transformations();

std::cout << "\nEntity transformations: \n";
for (auto const& [cell, transformation] : entity__transformation)
std::cout << " -" << type_to_name.at(cell) << ":\n"
<< transformation << std::endl;

// To demonstrate how these transformations can be used, we create a
// lattice of points where we will tabulate the element.

xt::xtensor<double, 2> points = basix::lattice::create(
cell_type, 5, basix::lattice::type::equispaced, true);
int num_points = points.shape(0);

// If (for example) the direction of edge 2 in the physical cell does
// not match its direction on the reference, then we need to adjust the
// tabulated data.

xt::xtensor<double, 4> original_data = nedelec.tabulate(0, points);
xt::xtensor<double, 4> mod_data = nedelec.tabulate(0, points);
xtl::span<double> data(mod_data.data(), mod_data.size());

// If the direction of edge 2 in the physical cell is reflected, it has
// cell permutation info ....000010 so (from right to left):
//      - edge 0 is not permuted (0)
//      - edge 1 is reflected (1)
//      - edge 2 is not permuted (0)
//      - edge 3 is not permuted (0)
//      - edge 4 is not permuted (0)
//      - edge 5 is not permuted (0)

int cell_info = 0b000010;
nedelec.apply_dof_transformation(data, num_points, cell_info);

std::cout << "\n Tabulated data is equal: "
<< xt::allclose(original_data, mod_data) << std::endl;
}

return 0;
}