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stopping criteria on generations

This commit is contained in:
Konstantinos Katrioplas 2018-05-03 12:12:30 +02:00
parent 7f23b19f30
commit 319c8079ad
2 changed files with 30 additions and 12 deletions
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7
Optimal_bounding_box/include/CGAL/Optimal_bounding_box/fitness_function.h
View File

@ -106,6 +106,13 @@ struct Fitness_map // -> a free function
}
double get_best_fitness_value(const Matrix& data)
{
Matrix best_mat = get_best();
return compute_fitness(best_mat, data);
}
const Matrix points;
Population<Matrix> pop;
};

35
Optimal_bounding_box/include/CGAL/Optimal_bounding_box/obb.h
View File

@ -46,7 +46,7 @@ namespace Optimal_bounding_box {
template <typename Matrix>
void evolution(Matrix& R, Matrix& points, std::size_t generations) // todo: points is const
void evolution(Matrix& R, Matrix& points, std::size_t max_generations) // todo: points is const
{
CGAL_assertion(points.rows() >= 3);
@ -59,12 +59,12 @@ void evolution(Matrix& R, Matrix& points, std::size_t generations) // todo: poin
Population<Matrix> pop(50);
//std::cout << "initial pop" << std::endl;
//pop.show_population();
//std::cout << std::endl;
//std::cin.get();
double prev_fit_value = 0;
double new_fit_value = 0;
double tolerance = 1e-2;
int stale = 0;
for(std::size_t t = 0; t < generations; ++t)
for(std::size_t t = 0; t < max_generations; ++t)
{
genetic_algorithm(pop, points);
@ -73,7 +73,6 @@ void evolution(Matrix& R, Matrix& points, std::size_t generations) // todo: poin
// std::cout << std::endl;
//std::cin.get();
for(std::size_t s = 0; s < pop.size(); ++s)
nelder_mead(pop[s], points, nelder_mead_iterations);
@ -82,7 +81,6 @@ void evolution(Matrix& R, Matrix& points, std::size_t generations) // todo: poin
//std::cout << std::endl;
//std::cin.get();
// debugging
/*
Fitness_map<Matrix> fitness_map(pop, points);
@ -90,13 +88,23 @@ void evolution(Matrix& R, Matrix& points, std::size_t generations) // todo: poin
std::cout << "det= " << R_now.determinant() << std::endl;
*/
// stopping criteria
Fitness_map<Matrix> fitness_map(pop, points);
new_fit_value = fitness_map.get_best_fitness_value(points);
double difference = new_fit_value - prev_fit_value;
if(abs(difference) < tolerance * new_fit_value)
stale++;
if(stale == 5)
break;
prev_fit_value = new_fit_value;
}
// compute fitness of entire population
Fitness_map<Matrix> fitness_map(pop, points);
R = fitness_map.get_best();
}
@ -152,8 +160,11 @@ void fill_matrix(std::vector<Point>& v_points, Matrix& points_mat)
}
}
/// @param points point coordinates of the input mesh
/// @param points point coordinates of the input mesh.
/// @param obb_points the 8 points of the obb.
/// @param use convex hull or not.
///
/// todo named parameters: max iterations
template <typename Point>
void find_obb(std::vector<Point>& points, std::vector<Point>& obb_points, bool use_ch)
{
@ -186,8 +197,8 @@ void find_obb(std::vector<Point>& points, std::vector<Point>& obb_points, bool u
}
MatrixXf R(3, 3);
std::size_t generations = 10;
CGAL::Optimal_bounding_box::evolution(R, points_mat, generations);
std::size_t max_generations = 100;
CGAL::Optimal_bounding_box::evolution(R, points_mat, max_generations);
MatrixXf obb(8, 3);
CGAL::Optimal_bounding_box::post_processing(points_mat, R, obb);