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Merge pull request #352 from borglab/fix/override_warnings 

fix/override_warnings
release/4.3a0
Frank Dellaert 2020-06-16 15:26:13 -04:00 committed by GitHub
parent 19c12c8f8f 7b92ae8bd3
commit ec34f9fdf5
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GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 26 additions and 23 deletions
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49
gtsam/slam/RegularImplicitSchurFactor.h
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@ -10,7 +10,11 @@
#include <gtsam/geometry/CameraSet.h>
#include <gtsam/linear/JacobianFactor.h>
#include <gtsam/linear/VectorValues.h>
#include <iosfwd>
#include <map>
#include <string>
#include <vector>
namespace gtsam {
@ -76,7 +80,7 @@ public:
/// print
void print(const std::string& s = "", const KeyFormatter& keyFormatter =
DefaultKeyFormatter) const {
DefaultKeyFormatter) const override {
std::cout << " RegularImplicitSchurFactor " << std::endl;
Factor::print(s);
for (size_t pos = 0; pos < size(); ++pos) {
@ -88,7 +92,7 @@ public:
}
/// equals
bool equals(const GaussianFactor& lf, double tol) const {
bool equals(const GaussianFactor& lf, double tol) const override {
const This* f = dynamic_cast<const This*>(&lf);
if (!f)
return false;
@ -104,37 +108,36 @@ public:
}
/// Degrees of freedom of camera
virtual DenseIndex getDim(const_iterator variable) const {
DenseIndex getDim(const_iterator variable) const override {
return D;
}
virtual void updateHessian(const KeyVector& keys,
SymmetricBlockMatrix* info) const {
void updateHessian(const KeyVector& keys,
SymmetricBlockMatrix* info) const override {
throw std::runtime_error(
"RegularImplicitSchurFactor::updateHessian non implemented");
}
virtual Matrix augmentedJacobian() const {
Matrix augmentedJacobian() const override {
throw std::runtime_error(
"RegularImplicitSchurFactor::augmentedJacobian non implemented");
return Matrix();
}
virtual std::pair<Matrix, Vector> jacobian() const {
std::pair<Matrix, Vector> jacobian() const override {
throw std::runtime_error(
"RegularImplicitSchurFactor::jacobian non implemented");
return std::make_pair(Matrix(), Vector());
}
/// *Compute* full augmented information matrix
virtual Matrix augmentedInformation() const {
Matrix augmentedInformation() const override {
// Do the Schur complement
SymmetricBlockMatrix augmentedHessian = //
SymmetricBlockMatrix augmentedHessian =
Set::SchurComplement(FBlocks_, E_, b_);
return augmentedHessian.selfadjointView();
}
/// *Compute* full information matrix
virtual Matrix information() const {
Matrix information() const override {
Matrix augmented = augmentedInformation();
int m = this->keys_.size();
size_t M = D * m;
@ -145,7 +148,7 @@ public:
using GaussianFactor::hessianDiagonal;
/// Add the diagonal of the Hessian for this factor to existing VectorValues
virtual void hessianDiagonalAdd(VectorValues &d) const override {
void hessianDiagonalAdd(VectorValues &d) const override {
// diag(Hessian) = diag(F' * (I - E * PointCov * E') * F);
for (size_t k = 0; k < size(); ++k) { // for each camera
Key j = keys_[k];
@ -176,7 +179,7 @@ public:
* @brief add the contribution of this factor to the diagonal of the hessian
* d(output) = d(input) + deltaHessianFactor
*/
virtual void hessianDiagonal(double* d) const {
void hessianDiagonal(double* d) const override {
// diag(Hessian) = diag(F' * (I - E * PointCov * E') * F);
// Use eigen magic to access raw memory
typedef Eigen::Matrix<double, D, 1> DVector;
@ -202,7 +205,7 @@ public:
}
/// Return the block diagonal of the Hessian for this factor
virtual std::map<Key, Matrix> hessianBlockDiagonal() const {
std::map<Key, Matrix> hessianBlockDiagonal() const override {
std::map<Key, Matrix> blocks;
// F'*(I - E*P*E')*F
for (size_t pos = 0; pos < size(); ++pos) {
@ -227,17 +230,18 @@ public:
return blocks;
}
virtual GaussianFactor::shared_ptr clone() const {
GaussianFactor::shared_ptr clone() const override {
return boost::make_shared<RegularImplicitSchurFactor<CAMERA> >(keys_,
FBlocks_, PointCovariance_, E_, b_);
throw std::runtime_error(
"RegularImplicitSchurFactor::clone non implemented");
}
virtual bool empty() const {
bool empty() const override {
return false;
}
virtual GaussianFactor::shared_ptr negate() const {
GaussianFactor::shared_ptr negate() const override {
return boost::make_shared<RegularImplicitSchurFactor<CAMERA> >(keys_,
FBlocks_, PointCovariance_, E_, b_);
throw std::runtime_error(
@ -288,7 +292,7 @@ public:
* f = nonlinear error
* (x'*H*x - 2*x'*eta + f) = x'*F'*Q*F*x - 2*x'*F'*Q *b + f = x'*F'*Q*(F*x - 2*b) + f
*/
virtual double error(const VectorValues& x) const {
double error(const VectorValues& x) const override {
// resize does not do malloc if correct size
e1.resize(size());
@ -383,13 +387,12 @@ public:
void multiplyHessianAdd(double alpha, const double* x, double* y,
std::vector<size_t> keys) const {
}
;
/**
* @brief Hessian-vector multiply, i.e. y += F'*alpha*(I - E*P*E')*F*x
*/
void multiplyHessianAdd(double alpha, const VectorValues& x,
VectorValues& y) const {
VectorValues& y) const override {
// resize does not do malloc if correct size
e1.resize(size());
@ -432,7 +435,7 @@ public:
/**
* Calculate gradient, which is -F'Q*b, see paper
*/
VectorValues gradientAtZero() const {
VectorValues gradientAtZero() const override {
// calculate Q*b
e1.resize(size());
e2.resize(size());
@ -454,7 +457,7 @@ public:
/**
* Calculate gradient, which is -F'Q*b, see paper - RAW MEMORY ACCESS
*/
virtual void gradientAtZero(double* d) const {
void gradientAtZero(double* d) const override {
// Use eigen magic to access raw memory
typedef Eigen::Matrix<double, D, 1> DVector;
@ -474,7 +477,7 @@ public:
}
/// Gradient wrt a key at any values
Vector gradient(Key key, const VectorValues& x) const {
Vector gradient(Key key, const VectorValues& x) const override {
throw std::runtime_error(
"gradient for RegularImplicitSchurFactor is not implemented yet");
}