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-rw-r--r--internal/ceres/loss_function.cc34
1 files changed, 17 insertions, 17 deletions
diff --git a/internal/ceres/loss_function.cc b/internal/ceres/loss_function.cc
index b948f28..4ad01e3 100644
--- a/internal/ceres/loss_function.cc
+++ b/internal/ceres/loss_function.cc
@@ -39,8 +39,8 @@ namespace ceres {
void TrivialLoss::Evaluate(double s, double rho[3]) const {
rho[0] = s;
- rho[1] = 1;
- rho[2] = 0;
+ rho[1] = 1.0;
+ rho[2] = 0.0;
}
void HuberLoss::Evaluate(double s, double rho[3]) const {
@@ -48,32 +48,32 @@ void HuberLoss::Evaluate(double s, double rho[3]) const {
// Outlier region.
// 'r' is always positive.
const double r = sqrt(s);
- rho[0] = 2 * a_ * r - b_;
- rho[1] = a_ / r;
- rho[2] = - rho[1] / (2 * s);
+ rho[0] = 2.0 * a_ * r - b_;
+ rho[1] = std::max(std::numeric_limits<double>::min(), a_ / r);
+ rho[2] = - rho[1] / (2.0 * s);
} else {
// Inlier region.
rho[0] = s;
- rho[1] = 1;
- rho[2] = 0;
+ rho[1] = 1.0;
+ rho[2] = 0.0;
}
}
void SoftLOneLoss::Evaluate(double s, double rho[3]) const {
- const double sum = 1 + s * c_;
+ const double sum = 1.0 + s * c_;
const double tmp = sqrt(sum);
// 'sum' and 'tmp' are always positive, assuming that 's' is.
- rho[0] = 2 * b_ * (tmp - 1);
- rho[1] = 1 / tmp;
- rho[2] = - (c_ * rho[1]) / (2 * sum);
+ rho[0] = 2.0 * b_ * (tmp - 1.0);
+ rho[1] = std::max(std::numeric_limits<double>::min(), 1.0 / tmp);
+ rho[2] = - (c_ * rho[1]) / (2.0 * sum);
}
void CauchyLoss::Evaluate(double s, double rho[3]) const {
- const double sum = 1 + s * c_;
- const double inv = 1 / sum;
+ const double sum = 1.0 + s * c_;
+ const double inv = 1.0 / sum;
// 'sum' and 'inv' are always positive, assuming that 's' is.
rho[0] = b_ * log(sum);
- rho[1] = inv;
+ rho[1] = std::max(std::numeric_limits<double>::min(), inv);
rho[2] = - c_ * (inv * inv);
}
@@ -82,8 +82,8 @@ void ArctanLoss::Evaluate(double s, double rho[3]) const {
const double inv = 1 / sum;
// 'sum' and 'inv' are always positive.
rho[0] = a_ * atan2(s, a_);
- rho[1] = inv;
- rho[2] = -2 * s * b_ * (inv * inv);
+ rho[1] = std::max(std::numeric_limits<double>::min(), inv);
+ rho[2] = -2.0 * s * b_ * (inv * inv);
}
TolerantLoss::TolerantLoss(double a, double b)
@@ -108,7 +108,7 @@ void TolerantLoss::Evaluate(double s, double rho[3]) const {
} else {
const double e_x = exp(x);
rho[0] = b_ * log(1.0 + e_x) - c_;
- rho[1] = e_x / (1.0 + e_x);
+ rho[1] = std::max(std::numeric_limits<double>::min(), e_x / (1.0 + e_x));
rho[2] = 0.5 / (b_ * (1.0 + cosh(x)));
}
}