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Pass vectors and matrices by reference, rename classes to CamelCase style

This commit is contained in:
Carles Fernandez 2019-06-16 14:54:41 +02:00
parent d6887488f3
commit 16f7c4b889
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GPG Key ID: 4C583C52B0C3877D
4 changed files with 65 additions and 65 deletions
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46
src/algorithms/tracking/libs/nonlinear_tracking.cc
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@ -4,7 +4,7 @@
*
* Cubature_Filter implements the functionality of the Cubature Kalman
* Filter, which uses multidimensional cubature rules to estimate the
* time evolution of a nonlinear system. Unscented_filter implements
* time evolution of a nonlinear system. UnscentedFilter implements
* an Unscented Kalman Filter which uses Unscented Transform rules to
* perform a similar estimation.
*
@ -44,7 +44,7 @@
/***************** CUBATURE KALMAN FILTER *****************/
Cubature_filter::Cubature_filter()
CubatureFilter::CubatureFilter()
{
int nx = 1;
x_pred_out = arma::zeros(nx, 1);
@ -55,7 +55,7 @@ Cubature_filter::Cubature_filter()
}
Cubature_filter::Cubature_filter(int nx)
CubatureFilter::CubatureFilter(int nx)
{
x_pred_out = arma::zeros(nx, 1);
P_x_pred_out = arma::eye(nx, nx) * (nx + 1);
@ -65,7 +65,7 @@ Cubature_filter::Cubature_filter(int nx)
}
Cubature_filter::Cubature_filter(const arma::vec& x_pred_0, const arma::mat& P_x_pred_0)
CubatureFilter::CubatureFilter(const arma::vec& x_pred_0, const arma::mat& P_x_pred_0)
{
x_pred_out = x_pred_0;
P_x_pred_out = P_x_pred_0;
@ -75,10 +75,10 @@ Cubature_filter::Cubature_filter(const arma::vec& x_pred_0, const arma::mat& P_x
}
Cubature_filter::~Cubature_filter() = default;
CubatureFilter::~CubatureFilter() = default;
void Cubature_filter::initialize(const arma::mat& x_pred_0, const arma::mat& P_x_pred_0)
void CubatureFilter::initialize(const arma::mat& x_pred_0, const arma::mat& P_x_pred_0)
{
x_pred_out = x_pred_0;
P_x_pred_out = P_x_pred_0;
@ -91,7 +91,7 @@ void Cubature_filter::initialize(const arma::mat& x_pred_0, const arma::mat& P_x
/*
* Perform the prediction step of the cubature Kalman filter
*/
void Cubature_filter::predict_sequential(const arma::vec& x_post, const arma::mat& P_x_post, Model_Function* transition_fcn, const arma::mat& noise_covariance)
void CubatureFilter::predict_sequential(const arma::vec& x_post, const arma::mat& P_x_post, ModelFunction* transition_fcn, const arma::mat& noise_covariance)
{
// Compute number of cubature points
int nx = x_post.n_elem;
@ -133,7 +133,7 @@ void Cubature_filter::predict_sequential(const arma::vec& x_post, const arma::ma
/*
* Perform the update step of the cubature Kalman filter
*/
void Cubature_filter::update_sequential(const arma::vec& z_upd, const arma::vec& x_pred, const arma::mat& P_x_pred, Model_Function* measurement_fcn, const arma::mat& noise_covariance)
void CubatureFilter::update_sequential(const arma::vec& z_upd, const arma::vec& x_pred, const arma::mat& P_x_pred, ModelFunction* measurement_fcn, const arma::mat& noise_covariance)
{
// Compute number of cubature points
int nx = x_pred.n_elem;
@ -178,25 +178,25 @@ void Cubature_filter::update_sequential(const arma::vec& z_upd, const arma::vec&
}
arma::mat Cubature_filter::get_x_pred() const
arma::mat CubatureFilter::get_x_pred() const
{
return x_pred_out;
}
arma::mat Cubature_filter::get_P_x_pred() const
arma::mat CubatureFilter::get_P_x_pred() const
{
return P_x_pred_out;
}
arma::mat Cubature_filter::get_x_est() const
arma::mat CubatureFilter::get_x_est() const
{
return x_est;
}
arma::mat Cubature_filter::get_P_x_est() const
arma::mat CubatureFilter::get_P_x_est() const
{
return P_x_est;
}
@ -205,7 +205,7 @@ arma::mat Cubature_filter::get_P_x_est() const
/***************** UNSCENTED KALMAN FILTER *****************/
Unscented_filter::Unscented_filter()
UnscentedFilter::UnscentedFilter()
{
int nx = 1;
x_pred_out = arma::zeros(nx, 1);
@ -216,7 +216,7 @@ Unscented_filter::Unscented_filter()
}
Unscented_filter::Unscented_filter(int nx)
UnscentedFilter::UnscentedFilter(int nx)
{
x_pred_out = arma::zeros(nx, 1);
P_x_pred_out = arma::eye(nx, nx) * (nx + 1);
@ -226,7 +226,7 @@ Unscented_filter::Unscented_filter(int nx)
}
Unscented_filter::Unscented_filter(const arma::vec& x_pred_0, const arma::mat& P_x_pred_0)
UnscentedFilter::UnscentedFilter(const arma::vec& x_pred_0, const arma::mat& P_x_pred_0)
{
x_pred_out = x_pred_0;
P_x_pred_out = P_x_pred_0;
@ -236,10 +236,10 @@ Unscented_filter::Unscented_filter(const arma::vec& x_pred_0, const arma::mat& P
}
Unscented_filter::~Unscented_filter() = default;
UnscentedFilter::~UnscentedFilter() = default;
void Unscented_filter::initialize(const arma::mat& x_pred_0, const arma::mat& P_x_pred_0)
void UnscentedFilter::initialize(const arma::mat& x_pred_0, const arma::mat& P_x_pred_0)
{
x_pred_out = x_pred_0;
P_x_pred_out = P_x_pred_0;
@ -252,7 +252,7 @@ void Unscented_filter::initialize(const arma::mat& x_pred_0, const arma::mat& P_
/*
* Perform the prediction step of the Unscented Kalman filter
*/
void Unscented_filter::predict_sequential(const arma::vec& x_post, const arma::mat& P_x_post, Model_Function* transition_fcn, const arma::mat& noise_covariance)
void UnscentedFilter::predict_sequential(const arma::vec& x_post, const arma::mat& P_x_post, ModelFunction* transition_fcn, const arma::mat& noise_covariance)
{
// Compute number of sigma points
int nx = x_post.n_elem;
@ -307,7 +307,7 @@ void Unscented_filter::predict_sequential(const arma::vec& x_post, const arma::m
/*
* Perform the update step of the Unscented Kalman filter
*/
void Unscented_filter::update_sequential(const arma::vec& z_upd, const arma::vec& x_pred, const arma::mat& P_x_pred, Model_Function* measurement_fcn, const arma::mat& noise_covariance)
void UnscentedFilter::update_sequential(const arma::vec& z_upd, const arma::vec& x_pred, const arma::mat& P_x_pred, ModelFunction* measurement_fcn, const arma::mat& noise_covariance)
{
// Compute number of sigma points
int nx = x_pred.n_elem;
@ -364,25 +364,25 @@ void Unscented_filter::update_sequential(const arma::vec& z_upd, const arma::vec
}
arma::mat Unscented_filter::get_x_pred() const
arma::mat UnscentedFilter::get_x_pred() const
{
return x_pred_out;
}
arma::mat Unscented_filter::get_P_x_pred() const
arma::mat UnscentedFilter::get_P_x_pred() const
{
return P_x_pred_out;
}
arma::mat Unscented_filter::get_x_est() const
arma::mat UnscentedFilter::get_x_est() const
{
return x_est;
}
arma::mat Unscented_filter::get_P_x_est() const
arma::mat UnscentedFilter::get_P_x_est() const
{
return P_x_est;
}

40
src/algorithms/tracking/libs/nonlinear_tracking.h
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@ -2,9 +2,9 @@
* \file nonlinear_tracking.h
* \brief Interface of a library for nonlinear tracking algorithms
*
* Cubature_Filter implements the functionality of the Cubature Kalman
* CubatureFilter implements the functionality of the Cubature Kalman
* Filter, which uses multidimensional cubature rules to estimate the
* time evolution of a nonlinear system. Unscented_filter implements
* time evolution of a nonlinear system. UnscentedFilter implements
* an Unscented Kalman Filter which uses Unscented Transform rules to
* perform a similar estimation.
*
@ -47,29 +47,29 @@
#include <gnuradio/gr_complex.h>
// Abstract model function
class Model_Function
class ModelFunction
{
public:
Model_Function(){};
virtual arma::vec operator()(arma::vec input) = 0;
virtual ~Model_Function() = default;
ModelFunction(){};
virtual arma::vec operator()(const arma::vec& input) = 0;
virtual ~ModelFunction() = default;
};
class Cubature_filter
class CubatureFilter
{
public:
// Constructors and destructors
Cubature_filter();
Cubature_filter(int nx);
Cubature_filter(const arma::vec& x_pred_0, const arma::mat& P_x_pred_0);
~Cubature_filter();
CubatureFilter();
CubatureFilter(int nx);
CubatureFilter(const arma::vec& x_pred_0, const arma::mat& P_x_pred_0);
~CubatureFilter();
// Reinitialization function
void initialize(const arma::mat& x_pred_0, const arma::mat& P_x_pred_0);
// Prediction and estimation
void predict_sequential(const arma::vec& x_post, const arma::mat& P_x_post, Model_Function* transition_fcn, const arma::mat& noise_covariance);
void update_sequential(const arma::vec& z_upd, const arma::vec& x_pred, const arma::mat& P_x_pred, Model_Function* measurement_fcn, const arma::mat& noise_covariance);
void predict_sequential(const arma::vec& x_post, const arma::mat& P_x_post, ModelFunction* transition_fcn, const arma::mat& noise_covariance);
void update_sequential(const arma::vec& z_upd, const arma::vec& x_pred, const arma::mat& P_x_pred, ModelFunction* measurement_fcn, const arma::mat& noise_covariance);
// Getters
arma::mat get_x_pred() const;
@ -84,21 +84,21 @@ private:
arma::mat P_x_est;
};
class Unscented_filter
class UnscentedFilter
{
public:
// Constructors and destructors
Unscented_filter();
Unscented_filter(int nx);
Unscented_filter(const arma::vec& x_pred_0, const arma::mat& P_x_pred_0);
~Unscented_filter();
UnscentedFilter();
UnscentedFilter(int nx);
UnscentedFilter(const arma::vec& x_pred_0, const arma::mat& P_x_pred_0);
~UnscentedFilter();
// Reinitialization function
void initialize(const arma::mat& x_pred_0, const arma::mat& P_x_pred_0);
// Prediction and estimation
void predict_sequential(const arma::vec& x_post, const arma::mat& P_x_post, Model_Function* transition_fcn, const arma::mat& noise_covariance);
void update_sequential(const arma::vec& z_upd, const arma::vec& x_pred, const arma::mat& P_x_pred, Model_Function* measurement_fcn, const arma::mat& noise_covariance);
void predict_sequential(const arma::vec& x_post, const arma::mat& P_x_post, ModelFunction* transition_fcn, const arma::mat& noise_covariance);
void update_sequential(const arma::vec& z_upd, const arma::vec& x_pred, const arma::mat& P_x_pred, ModelFunction* measurement_fcn, const arma::mat& noise_covariance);
// Getters
arma::mat get_x_pred() const;

22
src/tests/unit-tests/signal-processing-blocks/tracking/cubature_filter_test.cc
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@ -36,21 +36,21 @@
#define CUBATURE_TEST_N_TRIALS 1000
#define CUBATURE_TEST_TOLERANCE 0.01
class Transition_Model : public Model_Function
class TransitionModel : public ModelFunction
{
public:
Transition_Model(arma::mat kf_F) { coeff_mat = kf_F; };
virtual arma::vec operator()(arma::vec input) { return coeff_mat * input; };
TransitionModel(const arma::mat& kf_F) { coeff_mat = kf_F; };
virtual arma::vec operator()(const arma::vec& input) { return coeff_mat * input; };
private:
arma::mat coeff_mat;
};
class Measurement_Model : public Model_Function
class MeasurementModel : public ModelFunction
{
public:
Measurement_Model(arma::mat kf_H) { coeff_mat = kf_H; };
virtual arma::vec operator()(arma::vec input) { return coeff_mat * input; };
MeasurementModel(const arma::mat& kf_H) { coeff_mat = kf_H; };
virtual arma::vec operator()(const arma::vec& input) { return coeff_mat * input; };
private:
arma::mat coeff_mat;
@ -58,7 +58,7 @@ private:
TEST(CubatureFilterComputationTest, CubatureFilterTest)
{
Cubature_filter kf_cubature;
CubatureFilter kf_cubature;
arma::vec kf_x;
arma::mat kf_P_x;
@ -88,8 +88,8 @@ TEST(CubatureFilterComputationTest, CubatureFilterTest)
arma::mat kf_P_y;
arma::mat kf_K;
Model_Function* transition_function;
Model_Function* measurement_function;
ModelFunction* transition_function;
ModelFunction* measurement_function;
//--- Perform initializations ------------------------------
@ -118,7 +118,7 @@ TEST(CubatureFilterComputationTest, CubatureFilterTest)
kf_F = arma::randu<arma::mat>(nx, nx);
kf_Q = arma::diagmat(arma::randu<arma::vec>(nx, 1));
transition_function = new Transition_Model(kf_F);
transition_function = new TransitionModel(kf_F);
arma::mat ttx = (*transition_function)(kf_x_post);
kf_cubature.predict_sequential(kf_x_post, kf_P_x_post, transition_function, kf_Q);
@ -141,7 +141,7 @@ TEST(CubatureFilterComputationTest, CubatureFilterTest)
kf_y = kf_H * (kf_F * kf_x + eta) + nu;
measurement_function = new Measurement_Model(kf_H);
measurement_function = new MeasurementModel(kf_H);
kf_cubature.update_sequential(kf_y, kf_x_pre, kf_P_x_pre, measurement_function, kf_R);
ckf_x_post = kf_cubature.get_x_est();

22
src/tests/unit-tests/signal-processing-blocks/tracking/unscented_filter_test.cc
View File

@ -36,21 +36,21 @@
#define UNSCENTED_TEST_N_TRIALS 10
#define UNSCENTED_TEST_TOLERANCE 10
class Transition_Model_UKF : public Model_Function
class TransitionModelUKF : public ModelFunction
{
public:
Transition_Model_UKF(arma::mat kf_F) { coeff_mat = kf_F; };
virtual arma::vec operator()(arma::vec input) { return coeff_mat * input; };
TransitionModelUKF(const arma::mat& kf_F) { coeff_mat = kf_F; };
virtual arma::vec operator()(const arma::vec& input) { return coeff_mat * input; };
private:
arma::mat coeff_mat;
};
class Measurement_Model_UKF : public Model_Function
class MeasurementModelUKF : public ModelFunction
{
public:
Measurement_Model_UKF(arma::mat kf_H) { coeff_mat = kf_H; };
virtual arma::vec operator()(arma::vec input) { return coeff_mat * input; };
MeasurementModelUKF(const arma::mat& kf_H) { coeff_mat = kf_H; };
virtual arma::vec operator()(const arma::vec& input) { return coeff_mat * input; };
private:
arma::mat coeff_mat;
@ -58,7 +58,7 @@ private:
TEST(UnscentedFilterComputationTest, UnscentedFilterTest)
{
Unscented_filter kf_unscented;
UnscentedFilter kf_unscented;
arma::vec kf_x;
arma::mat kf_P_x;
@ -88,8 +88,8 @@ TEST(UnscentedFilterComputationTest, UnscentedFilterTest)
arma::mat kf_P_y;
arma::mat kf_K;
Model_Function* transition_function;
Model_Function* measurement_function;
ModelFunction* transition_function;
ModelFunction* measurement_function;
//--- Perform initializations ------------------------------
@ -118,7 +118,7 @@ TEST(UnscentedFilterComputationTest, UnscentedFilterTest)
kf_F = arma::randu<arma::mat>(nx, nx);
kf_Q = arma::diagmat(arma::randu<arma::vec>(nx, 1));
transition_function = new Transition_Model_UKF(kf_F);
transition_function = new TransitionModelUKF(kf_F);
arma::mat ttx = (*transition_function)(kf_x_post);
kf_unscented.predict_sequential(kf_x_post, kf_P_x_post, transition_function, kf_Q);
@ -141,7 +141,7 @@ TEST(UnscentedFilterComputationTest, UnscentedFilterTest)
kf_y = kf_H * (kf_F * kf_x + eta) + nu;
measurement_function = new Measurement_Model_UKF(kf_H);
measurement_function = new MeasurementModelUKF(kf_H);
kf_unscented.update_sequential(kf_y, kf_x_pre, kf_P_x_pre, measurement_function, kf_R);
ukf_x_post = kf_unscented.get_x_est();