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-rw-r--r--src/Coxeter_triangulation/include/gudhi/Functions/Function_lemniscate_revolution_in_R3.h12
1 files changed, 5 insertions, 7 deletions
diff --git a/src/Coxeter_triangulation/include/gudhi/Functions/Function_lemniscate_revolution_in_R3.h b/src/Coxeter_triangulation/include/gudhi/Functions/Function_lemniscate_revolution_in_R3.h
index f36ccd3c..beb41e00 100644
--- a/src/Coxeter_triangulation/include/gudhi/Functions/Function_lemniscate_revolution_in_R3.h
+++ b/src/Coxeter_triangulation/include/gudhi/Functions/Function_lemniscate_revolution_in_R3.h
@@ -14,8 +14,6 @@
#include <cstdlib> // for std::size_t
#include <cmath> // for std::sqrt
-#include <gudhi/Functions/Function.h>
-
#include <Eigen/Dense>
namespace Gudhi {
@@ -27,12 +25,12 @@ namespace coxeter_triangulation {
* \brief A class that encodes the function, the zero-set of which is a surface of revolution
* around the x axis based on the lemniscate of Bernoulli embedded in R^3.
*/
-struct Function_lemniscate_revolution_in_R3 : public Function {
+struct Function_lemniscate_revolution_in_R3 {
/**
* \brief Value of the function at a specified point.
* @param[in] p The input point. The dimension needs to coincide with the ambient dimension.
*/
- virtual Eigen::VectorXd operator()(const Eigen::VectorXd& p) const override {
+ Eigen::VectorXd operator()(const Eigen::VectorXd& p) const {
double x = p(0) - off_[0], y = p(1) - off_[1], z = p(2) - off_[2];
Eigen::VectorXd result(cod_d());
double x2 = x * x, y2 = y * y, z2 = z * z, a2 = a_ * a_;
@@ -42,16 +40,16 @@ struct Function_lemniscate_revolution_in_R3 : public Function {
}
/** \brief Returns the (ambient) domain dimension.*/
- virtual std::size_t amb_d() const override { return 3; };
+ std::size_t amb_d() const { return 3; };
/** \brief Returns the codomain dimension. */
- virtual std::size_t cod_d() const override { return 1; };
+ std::size_t cod_d() const { return 1; };
/** \brief Returns a point on the surface. This seed point is only one of
* two necessary seed points for the manifold tracing algorithm.
* See the method seed2() for the other point.
*/
- virtual Eigen::VectorXd seed() const override {
+ Eigen::VectorXd seed() const {
Eigen::Vector3d result(std::sqrt(2 * a_) + off_[0], off_[1], off_[2]);
return result;
}