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Setting some functions to const #28

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Setting some functions to const #28

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4 changes: 2 additions & 2 deletions include/kalman/SquareRootExtendedKalmanFilter.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -208,7 +208,7 @@ namespace Kalman {
template<class Type>
bool computePredictedCovarianceSquareRoot( const Jacobian<Type, State>& A, const CovarianceSquareRoot<State>& S,
const Jacobian<Type, Type>& B, const CovarianceSquareRoot<Type>& R,
CovarianceSquareRoot<Type>& S_pred)
CovarianceSquareRoot<Type>& S_pred) const
{
// Compute QR decomposition of (transposed) augmented matrix
Matrix<T, State::RowsAtCompileTime + Type::RowsAtCompileTime, Type::RowsAtCompileTime> tmp;
Expand Down Expand Up @@ -251,7 +251,7 @@ namespace Kalman {
template<class Measurement>
bool computeKalmanGain( const Jacobian<Measurement, State>& H,
const CovarianceSquareRoot<Measurement>& S_y,
KalmanGain<Measurement>& K)
KalmanGain<Measurement>& K) const
{
// Solve using backsubstitution
// AX=B with B = HSS^T and X = K^T and A = S_yS_y^T
Expand Down
4 changes: 2 additions & 2 deletions include/kalman/SquareRootUnscentedKalmanFilter.hpp
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Expand Up @@ -221,7 +221,7 @@ namespace Kalman {
*/
template<class Type>
bool computeCovarianceSquareRootFromSigmaPoints(const Type& mean, const SigmaPoints<Type>& sigmaPoints,
const CovarianceSquareRoot<Type>& noiseCov, CovarianceSquareRoot<Type>& cov)
const CovarianceSquareRoot<Type>& noiseCov, CovarianceSquareRoot<Type>& cov) const
{
// Compute QR decomposition of (transposed) augmented matrix
Matrix<T, 2*State::RowsAtCompileTime + Type::RowsAtCompileTime, Type::RowsAtCompileTime> tmp;
Expand Down Expand Up @@ -272,7 +272,7 @@ namespace Kalman {
bool computeKalmanGain( const Measurement& y,
const SigmaPoints<Measurement>& sigmaMeasurementPoints,
const CovarianceSquareRoot<Measurement>& S_y,
KalmanGain<Measurement>& K)
KalmanGain<Measurement>& K) const
{
// Note: The intermediate eval() is needed here (for now) due to a bug in Eigen that occurs
// when Measurement::RowsAtCompileTime == 1 AND State::RowsAtCompileTime >= 8
Expand Down
4 changes: 2 additions & 2 deletions include/kalman/UnscentedKalmanFilter.hpp
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Expand Up @@ -218,7 +218,7 @@ namespace Kalman {
*/
template<class Type>
bool computeCovarianceFromSigmaPoints( const Type& mean, const SigmaPoints<Type>& sigmaPoints,
const Covariance<Type>& noiseCov, Covariance<Type>& cov)
const Covariance<Type>& noiseCov, Covariance<Type>& cov) const
{
decltype(sigmaPoints) W = this->sigmaWeights_c.transpose().template replicate<Type::RowsAtCompileTime,1>();
decltype(sigmaPoints) tmp = (sigmaPoints.colwise() - mean);
Expand All @@ -241,7 +241,7 @@ namespace Kalman {
bool computeKalmanGain( const Measurement& y,
const SigmaPoints<Measurement>& sigmaMeasurementPoints,
const Covariance<Measurement>& P_yy,
KalmanGain<Measurement>& K)
KalmanGain<Measurement>& K) const
{
// Note: The intermediate eval() is needed here (for now) due to a bug in Eigen that occurs
// when Measurement::RowsAtCompileTime == 1 AND State::RowsAtCompileTime >= 8
Expand Down
8 changes: 5 additions & 3 deletions include/kalman/UnscentedKalmanFilterBase.hpp
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Expand Up @@ -137,7 +137,8 @@ namespace Kalman {
* @return The predicted measurement
*/
template<class Measurement, template<class> class CovarianceBase>
Measurement computeMeasurementPrediction(const MeasurementModelType<Measurement, CovarianceBase>& m, SigmaPoints<Measurement>& sigmaMeasurementPoints)
Measurement computeMeasurementPrediction(const MeasurementModelType<Measurement, CovarianceBase>& m,
SigmaPoints<Measurement>& sigmaMeasurementPoints) const
{
// Predict measurements for each sigma point
computeSigmaPointMeasurements<Measurement>(m, sigmaMeasurementPoints);
Expand Down Expand Up @@ -204,7 +205,8 @@ namespace Kalman {
* @param [out] sigmaMeasurementPoints The struct of expected sigma measurements to be computed
*/
template<class Measurement, template<class> class CovarianceBase>
void computeSigmaPointMeasurements(const MeasurementModelType<Measurement, CovarianceBase>& m, SigmaPoints<Measurement>& sigmaMeasurementPoints)
void computeSigmaPointMeasurements(const MeasurementModelType<Measurement, CovarianceBase>& m,
SigmaPoints<Measurement>& sigmaMeasurementPoints) const
{
for( int i = 0; i < SigmaPointCount; ++i )
{
Expand All @@ -221,7 +223,7 @@ namespace Kalman {
* @return The prediction
*/
template<class Type>
Type computePredictionFromSigmaPoints(const SigmaPoints<Type>& sigmaPoints)
Type computePredictionFromSigmaPoints(const SigmaPoints<Type>& sigmaPoints) const
{
// Use efficient matrix x vector computation
return sigmaPoints * sigmaWeights_m;
Expand Down