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-rw-r--r--extern/ceres/include/ceres/loss_function.h85
1 files changed, 44 insertions, 41 deletions
diff --git a/extern/ceres/include/ceres/loss_function.h b/extern/ceres/include/ceres/loss_function.h
index 0512c135143..7aabf7dfce1 100644
--- a/extern/ceres/include/ceres/loss_function.h
+++ b/extern/ceres/include/ceres/loss_function.h
@@ -1,5 +1,5 @@
// Ceres Solver - A fast non-linear least squares minimizer
-// Copyright 2015 Google Inc. All rights reserved.
+// Copyright 2019 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
// Redistribution and use in source and binary forms, with or without
@@ -57,7 +57,7 @@
// anything special (i.e. if we used a basic quadratic loss), the
// residual for the erroneous measurement will result in extreme error
// due to the quadratic nature of squared loss. This results in the
-// entire solution getting pulled away from the optimimum to reduce
+// entire solution getting pulled away from the optimum to reduce
// the large error that would otherwise be attributed to the wrong
// measurement.
//
@@ -75,11 +75,11 @@
#ifndef CERES_PUBLIC_LOSS_FUNCTION_H_
#define CERES_PUBLIC_LOSS_FUNCTION_H_
-#include "glog/logging.h"
-#include "ceres/internal/macros.h"
-#include "ceres/internal/scoped_ptr.h"
-#include "ceres/types.h"
+#include <memory>
+
#include "ceres/internal/disable_warnings.h"
+#include "ceres/types.h"
+#include "glog/logging.h"
namespace ceres {
@@ -119,7 +119,6 @@ class CERES_EXPORT LossFunction {
// Note: in the region of interest (i.e. s < 3) we have:
// TrivialLoss >= HuberLoss >= SoftLOneLoss >= CauchyLoss
-
// This corresponds to no robustification.
//
// rho(s) = s
@@ -131,7 +130,7 @@ class CERES_EXPORT LossFunction {
// thing.
class CERES_EXPORT TrivialLoss : public LossFunction {
public:
- virtual void Evaluate(double, double*) const;
+ void Evaluate(double, double*) const override;
};
// Scaling
@@ -174,8 +173,8 @@ class CERES_EXPORT TrivialLoss : public LossFunction {
// http://en.wikipedia.org/wiki/Huber_Loss_Function
class CERES_EXPORT HuberLoss : public LossFunction {
public:
- explicit HuberLoss(double a) : a_(a), b_(a * a) { }
- virtual void Evaluate(double, double*) const;
+ explicit HuberLoss(double a) : a_(a), b_(a * a) {}
+ void Evaluate(double, double*) const override;
private:
const double a_;
@@ -187,11 +186,11 @@ class CERES_EXPORT HuberLoss : public LossFunction {
//
// rho(s) = 2 (sqrt(1 + s) - 1).
//
-// At s = 0: rho = [0, 1, -1/2].
+// At s = 0: rho = [0, 1, -1 / (2 * a^2)].
class CERES_EXPORT SoftLOneLoss : public LossFunction {
public:
- explicit SoftLOneLoss(double a) : b_(a * a), c_(1 / b_) { }
- virtual void Evaluate(double, double*) const;
+ explicit SoftLOneLoss(double a) : b_(a * a), c_(1 / b_) {}
+ void Evaluate(double, double*) const override;
private:
// b = a^2.
@@ -204,11 +203,11 @@ class CERES_EXPORT SoftLOneLoss : public LossFunction {
//
// rho(s) = log(1 + s).
//
-// At s = 0: rho = [0, 1, -1].
+// At s = 0: rho = [0, 1, -1 / a^2].
class CERES_EXPORT CauchyLoss : public LossFunction {
public:
- explicit CauchyLoss(double a) : b_(a * a), c_(1 / b_) { }
- virtual void Evaluate(double, double*) const;
+ explicit CauchyLoss(double a) : b_(a * a), c_(1 / b_) {}
+ void Evaluate(double, double*) const override;
private:
// b = a^2.
@@ -228,8 +227,8 @@ class CERES_EXPORT CauchyLoss : public LossFunction {
// At s = 0: rho = [0, 1, 0].
class CERES_EXPORT ArctanLoss : public LossFunction {
public:
- explicit ArctanLoss(double a) : a_(a), b_(1 / (a * a)) { }
- virtual void Evaluate(double, double*) const;
+ explicit ArctanLoss(double a) : a_(a), b_(1 / (a * a)) {}
+ void Evaluate(double, double*) const override;
private:
const double a_;
@@ -268,7 +267,7 @@ class CERES_EXPORT ArctanLoss : public LossFunction {
class CERES_EXPORT TolerantLoss : public LossFunction {
public:
explicit TolerantLoss(double a, double b);
- virtual void Evaluate(double, double*) const;
+ void Evaluate(double, double*) const override;
private:
const double a_, b_, c_;
@@ -277,16 +276,17 @@ class CERES_EXPORT TolerantLoss : public LossFunction {
// This is the Tukey biweight loss function which aggressively
// attempts to suppress large errors.
//
-// The term is computed as:
+// The term is computed as follows where the equations are scaled by a
+// factor of 2 because the cost function is given by 1/2 rho(s):
//
-// rho(s) = a^2 / 6 * (1 - (1 - s / a^2)^3 ) for s <= a^2,
-// rho(s) = a^2 / 6 for s > a^2.
+// rho(s) = a^2 / 3 * (1 - (1 - s / a^2)^3 ) for s <= a^2,
+// rho(s) = a^2 / 3 for s > a^2.
//
-// At s = 0: rho = [0, 0.5, -1 / a^2]
+// At s = 0: rho = [0, 1, -2 / a^2]
class CERES_EXPORT TukeyLoss : public ceres::LossFunction {
public:
- explicit TukeyLoss(double a) : a_squared_(a * a) { }
- virtual void Evaluate(double, double*) const;
+ explicit TukeyLoss(double a) : a_squared_(a * a) {}
+ void Evaluate(double, double*) const override;
private:
const double a_squared_;
@@ -297,13 +297,15 @@ class CERES_EXPORT TukeyLoss : public ceres::LossFunction {
// The loss functions must not be NULL.
class CERES_EXPORT ComposedLoss : public LossFunction {
public:
- explicit ComposedLoss(const LossFunction* f, Ownership ownership_f,
- const LossFunction* g, Ownership ownership_g);
+ explicit ComposedLoss(const LossFunction* f,
+ Ownership ownership_f,
+ const LossFunction* g,
+ Ownership ownership_g);
virtual ~ComposedLoss();
- virtual void Evaluate(double, double*) const;
+ void Evaluate(double, double*) const override;
private:
- internal::scoped_ptr<const LossFunction> f_, g_;
+ std::unique_ptr<const LossFunction> f_, g_;
const Ownership ownership_f_, ownership_g_;
};
@@ -329,21 +331,22 @@ class CERES_EXPORT ScaledLoss : public LossFunction {
// Constructs a ScaledLoss wrapping another loss function. Takes
// ownership of the wrapped loss function or not depending on the
// ownership parameter.
- ScaledLoss(const LossFunction* rho, double a, Ownership ownership) :
- rho_(rho), a_(a), ownership_(ownership) { }
+ ScaledLoss(const LossFunction* rho, double a, Ownership ownership)
+ : rho_(rho), a_(a), ownership_(ownership) {}
+ ScaledLoss(const ScaledLoss&) = delete;
+ void operator=(const ScaledLoss&) = delete;
virtual ~ScaledLoss() {
if (ownership_ == DO_NOT_TAKE_OWNERSHIP) {
rho_.release();
}
}
- virtual void Evaluate(double, double*) const;
+ void Evaluate(double, double*) const override;
private:
- internal::scoped_ptr<const LossFunction> rho_;
+ std::unique_ptr<const LossFunction> rho_;
const double a_;
const Ownership ownership_;
- CERES_DISALLOW_COPY_AND_ASSIGN(ScaledLoss);
};
// Sometimes after the optimization problem has been constructed, we
@@ -387,8 +390,10 @@ class CERES_EXPORT ScaledLoss : public LossFunction {
class CERES_EXPORT LossFunctionWrapper : public LossFunction {
public:
LossFunctionWrapper(LossFunction* rho, Ownership ownership)
- : rho_(rho), ownership_(ownership) {
- }
+ : rho_(rho), ownership_(ownership) {}
+
+ LossFunctionWrapper(const LossFunctionWrapper&) = delete;
+ void operator=(const LossFunctionWrapper&) = delete;
virtual ~LossFunctionWrapper() {
if (ownership_ == DO_NOT_TAKE_OWNERSHIP) {
@@ -396,13 +401,12 @@ class CERES_EXPORT LossFunctionWrapper : public LossFunction {
}
}
- virtual void Evaluate(double sq_norm, double out[3]) const {
+ void Evaluate(double sq_norm, double out[3]) const override {
if (rho_.get() == NULL) {
out[0] = sq_norm;
out[1] = 1.0;
out[2] = 0.0;
- }
- else {
+ } else {
rho_->Evaluate(sq_norm, out);
}
}
@@ -416,9 +420,8 @@ class CERES_EXPORT LossFunctionWrapper : public LossFunction {
}
private:
- internal::scoped_ptr<const LossFunction> rho_;
+ std::unique_ptr<const LossFunction> rho_;
Ownership ownership_;
- CERES_DISALLOW_COPY_AND_ASSIGN(LossFunctionWrapper);
};
} // namespace ceres
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