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Replace std::pow(x,2) by CGAL::square(x)

This commit is contained in:
Simon Giraudot 2021-03-23 13:14:41 +01:00
parent 91de37ec3a
commit ab14acff77
8 changed files with 13 additions and 13 deletions
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2
Generator/include/CGAL/random_convex_hull_in_disc_2.h
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@ -192,7 +192,7 @@ void random_convex_hull_in_disc_2(std::size_t n, double radius, std::list<typena
(simulated_points < n)); // initialization such that 0 in P_n
std::size_t T = n;
if (!fast) T = static_cast<std::size_t>(std::floor(n / std::pow(std::log(static_cast<double>(n)), 2)));
if (!fast) T = static_cast<std::size_t>(std::floor(n / CGAL::square(std::log(static_cast<double>(n)))));
while (simulated_points < n) {
// l is a list coming from a convex hull operation. we are moving the

4
Point_set_processing_3/include/CGAL/bilateral_smooth_point_set.h
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@ -90,7 +90,7 @@ compute_denoise_projection(
Vector normal_sum = CGAL::NULL_VECTOR;
FT cos_sigma = cos(sharpness_angle * CGAL_PI / 180.0);
FT sharpness_bandwidth = std::pow((CGAL::max)(1e-8, 1 - cos_sigma), 2);
FT sharpness_bandwidth = CGAL::square((CGAL::max)(1e-8, 1 - cos_sigma));
for (typename PointRange::iterator it : neighbor_pwns)
{
@ -101,7 +101,7 @@ compute_denoise_projection(
if (dist2 < radius2)
{
FT theta = std::exp(dist2 * iradius16);
FT psi = std::exp(-std::pow(1 - get(normal_map, vt) * nn, 2)
FT psi = std::exp(-CGAL::square(1 - get(normal_map, vt) * nn)
/ sharpness_bandwidth);
weight = theta * psi;

4
Point_set_processing_3/include/CGAL/edge_aware_upsample_point_set.h
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@ -212,7 +212,7 @@ update_new_point(
for (unsigned int j = 0; j < candidate_num; j++)
{
FT psi = std::exp(-std::pow(FT(1) - normal_cadidate[j] * t.normal, FT(2))
FT psi = std::exp(-CGAL::square(FT(1) - normal_cadidate[j] * t.normal)
/ sharpness_bandwidth);
FT project_diff_t_v = (t.pt - new_v.pt) * t.normal;
FT weight = psi * theta;
@ -437,7 +437,7 @@ edge_aware_upsample_point_set(
//
FT cos_sigma = static_cast<FT>(std::cos(FT(CGAL::to_double(sharpness_angle))
/ FT(180) * FT(CGAL_PI)));
FT sharpness_bandwidth = static_cast<FT>(std::pow((CGAL::max)((FT)1e-8, (FT)1.0 - cos_sigma), 2));
FT sharpness_bandwidth = CGAL::square((CGAL::max)((FT)1e-8, (FT)1.0 - cos_sigma));
FT sum_density = 0.0;
unsigned int count_density = 1;

2
Point_set_processing_3/include/CGAL/wlop_simplify_and_regularize_point_set.h
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@ -185,7 +185,7 @@ compute_update_sample_point(
if (dist2 < 1e-10) continue;
FT dist = std::sqrt(dist2);
weight = std::exp(dist2 * iradius16) * std::pow(FT(1.0) / dist, 2); // L1
weight = std::exp(dist2 * iradius16) * CGAL::square(FT(1.0) / dist); // L1
if (!is_sample_densities_empty)
{

2
Surface_mesh_segmentation/include/CGAL/internal/Surface_mesh_segmentation/Disk_samplers.h
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@ -88,7 +88,7 @@ public:
for(std::size_t i = 0; i < number_of_points; ++i) {
double Q = i * golden_ratio * CGAL_PI;
double R = std::sqrt(static_cast<double>(i) / number_of_points);
double weight = exp(-0.5 * (std::pow(R / CGAL_ANGLE_ST_DEV_DIVIDER, 2)));
double weight = exp(-0.5 * (CGAL::square(R / CGAL_ANGLE_ST_DEV_DIVIDER)));
*out_it++ = Tuple(R * cos(Q), R * sin(Q), weight);
}
} else {

4
Surface_mesh_segmentation/include/CGAL/internal/Surface_mesh_segmentation/Expectation_maximization.h
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@ -75,7 +75,7 @@ private:
return x == mean ? 1.0 : 0.0;
}
double e_over = -0.5 * std::pow((x - mean) / deviation, 2);
double e_over = -0.5 * CGAL::square((x - mean) / deviation);
return exp(e_over) / deviation;
}
/**
@ -289,7 +289,7 @@ private:
double new_deviation = 0.0;
for(std::size_t point_i = 0; point_i < points.size(); ++point_i) {
double membership = responsibility_matrix[center_i][point_i];
new_deviation += membership * std::pow(points[point_i] - new_mean, 2);
new_deviation += membership * CGAL::square(points[point_i] - new_mean);
}
new_deviation = std::sqrt(new_deviation/total_membership);

4
Surface_mesh_segmentation/include/CGAL/internal/Surface_mesh_segmentation/Filters.h
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@ -92,7 +92,7 @@ public:
double deviation = 0.0;
for(typename std::map<face_descriptor, std::size_t>::iterator it =
neighbors.begin(); it != neighbors.end(); ++it) {
deviation += std::pow(get(values, it->first) - current_sdf_value, 2);
deviation += CGAL::square(get(values, it->first) - current_sdf_value);
}
deviation = std::sqrt(deviation / neighbors.size());
if(deviation == 0.0) {
@ -133,7 +133,7 @@ public:
private:
/** Gaussian function for weighting. */
double gaussian_function(double value, double deviation) const {
return exp(-0.5 * (std::pow(value / deviation, 2)));
return exp(-0.5 * (CGAL::square(value / deviation)));
}
};

4
Surface_mesh_segmentation/include/CGAL/internal/Surface_mesh_segmentation/K_means_clustering.h
View File

@ -123,7 +123,7 @@ public:
double cumulative_distance_square = 0.0;
// distance_square holds closest distance that points have, so just test new coming center (i.e. centers.back())
for(std::size_t j = 0; j < points.size(); ++j) {
double new_distance = std::pow(centers.back() - points[j], 2);
double new_distance = CGAL::square(centers.back() - points[j]);
if(new_distance < distance_square[j]) {
distance_square[j] = new_distance;
}
@ -422,7 +422,7 @@ private:
double sum = 0.0;
for(std::vector<K_means_point>::const_iterator point_it = points.begin();
point_it != points.end(); ++point_it) {
sum += std::pow(centers[point_it->center_id].mean - point_it->data, 2);
sum += CGAL::square(centers[point_it->center_id].mean - point_it->data);
}
return sum;
}