remove template from ParameterMatrix
Varun Agrawal
parent
9ae4146ef8
commit
87402328bf
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@ -169,7 +169,7 @@ class Basis {
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};
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/**
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* VectorEvaluationFunctor at a given x, applied to ParameterMatrix<M>.
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* VectorEvaluationFunctor at a given x, applied to ParameterMatrix.
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* This functor is used to evaluate a parameterized function at a given scalar
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* value x. When given a specific M*N parameters, returns an M-vector the M
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* corresponding functions at x, possibly with Jacobians wrpt the parameters.
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@ -211,14 +211,14 @@ class Basis {
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}
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/// M-dimensional evaluation
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VectorM apply(const ParameterMatrix<M>& P,
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VectorM apply(const ParameterMatrix& P,
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OptionalJacobian</*MxN*/ -1, -1> H = {}) const {
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if (H) *H = H_;
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return P.matrix() * this->weights_.transpose();
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}
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/// c++ sugar
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VectorM operator()(const ParameterMatrix<M>& P,
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VectorM operator()(const ParameterMatrix& P,
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OptionalJacobian</*MxN*/ -1, -1> H = {}) const {
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return apply(P, H);
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}
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@ -270,21 +270,21 @@ class Basis {
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}
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/// Calculate component of component rowIndex_ of P
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double apply(const ParameterMatrix<M>& P,
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double apply(const ParameterMatrix& P,
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OptionalJacobian</*1xMN*/ -1, -1> H = {}) const {
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if (H) *H = H_;
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return P.row(rowIndex_) * EvaluationFunctor::weights_.transpose();
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}
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/// c++ sugar
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double operator()(const ParameterMatrix<M>& P,
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double operator()(const ParameterMatrix& P,
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OptionalJacobian</*1xMN*/ -1, -1> H = {}) const {
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return apply(P, H);
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}
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};
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/**
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* Manifold EvaluationFunctor at a given x, applied to ParameterMatrix<M>.
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* Manifold EvaluationFunctor at a given x, applied to ParameterMatrix.
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* This functor is used to evaluate a parameterized function at a given scalar
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* value x. When given a specific M*N parameters, returns an M-vector the M
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* corresponding functions at x, possibly with Jacobians wrpt the parameters.
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@ -314,7 +314,7 @@ class Basis {
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: Base(N, x, a, b) {}
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/// Manifold evaluation
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T apply(const ParameterMatrix<M>& P,
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T apply(const ParameterMatrix& P,
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OptionalJacobian</*MxMN*/ -1, -1> H = {}) const {
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// Interpolate the M-dimensional vector to yield a vector in tangent space
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Eigen::Matrix<double, M, 1> xi = Base::operator()(P, H);
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@ -333,7 +333,7 @@ class Basis {
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}
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/// c++ sugar
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T operator()(const ParameterMatrix<M>& P,
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T operator()(const ParameterMatrix& P,
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OptionalJacobian</*MxN*/ -1, -1> H = {}) const {
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return apply(P, H); // might call apply in derived
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}
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@ -389,7 +389,7 @@ class Basis {
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};
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/**
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* VectorDerivativeFunctor at a given x, applied to ParameterMatrix<M>.
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* VectorDerivativeFunctor at a given x, applied to ParameterMatrix.
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*
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* This functor is used to evaluate the derivatives of a parameterized
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* function at a given scalar value x. When given a specific M*N parameters,
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@ -432,15 +432,14 @@ class Basis {
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calculateJacobian();
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}
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VectorM apply(const ParameterMatrix<M>& P,
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VectorM apply(const ParameterMatrix& P,
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OptionalJacobian</*MxMN*/ -1, -1> H = {}) const {
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if (H) *H = H_;
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return P.matrix() * this->weights_.transpose();
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}
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/// c++ sugar
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VectorM operator()(
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const ParameterMatrix<M>& P,
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OptionalJacobian</*MxMN*/ -1, -1> H = {}) const {
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VectorM operator()(const ParameterMatrix& P,
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OptionalJacobian</*MxMN*/ -1, -1> H = {}) const {
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return apply(P, H);
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}
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};
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@ -490,18 +489,17 @@ class Basis {
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calculateJacobian(N);
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}
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/// Calculate derivative of component rowIndex_ of F
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double apply(const ParameterMatrix<M>& P,
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double apply(const ParameterMatrix& P,
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OptionalJacobian</*1xMN*/ -1, -1> H = {}) const {
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if (H) *H = H_;
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return P.row(rowIndex_) * this->weights_.transpose();
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}
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/// c++ sugar
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double operator()(const ParameterMatrix<M>& P,
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double operator()(const ParameterMatrix& P,
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OptionalJacobian</*1xMN*/ -1, -1> H = {}) const {
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return apply(P, H);
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}
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};
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};
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} // namespace gtsam
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@ -93,9 +93,9 @@ class EvaluationFactor : public FunctorizedFactor<double, Vector> {
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*/
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template <class BASIS, int M>
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class VectorEvaluationFactor
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: public FunctorizedFactor<Vector, ParameterMatrix<M>> {
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: public FunctorizedFactor<Vector, ParameterMatrix> {
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private:
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using Base = FunctorizedFactor<Vector, ParameterMatrix<M>>;
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using Base = FunctorizedFactor<Vector, ParameterMatrix>;
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public:
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VectorEvaluationFactor() {}
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@ -156,11 +156,12 @@ class VectorEvaluationFactor
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*
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* @ingroup basis
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*/
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// TODO(Varun) remove template P
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template <class BASIS, size_t P>
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class VectorComponentFactor
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: public FunctorizedFactor<double, ParameterMatrix<P>> {
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: public FunctorizedFactor<double, ParameterMatrix> {
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private:
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using Base = FunctorizedFactor<double, ParameterMatrix<P>>;
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using Base = FunctorizedFactor<double, ParameterMatrix>;
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public:
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VectorComponentFactor() {}
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@ -226,10 +227,9 @@ class VectorComponentFactor
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* where `x` is the value (e.g. timestep) at which the rotation was evaluated.
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*/
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template <class BASIS, typename T>
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class ManifoldEvaluationFactor
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: public FunctorizedFactor<T, ParameterMatrix<traits<T>::dimension>> {
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class ManifoldEvaluationFactor : public FunctorizedFactor<T, ParameterMatrix> {
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private:
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using Base = FunctorizedFactor<T, ParameterMatrix<traits<T>::dimension>>;
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using Base = FunctorizedFactor<T, ParameterMatrix>;
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public:
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ManifoldEvaluationFactor() {}
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@ -326,11 +326,12 @@ class DerivativeFactor
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* @param BASIS: The basis class to use e.g. Chebyshev2
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* @param M: Size of the evaluated state vector derivative.
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*/
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//TODO(Varun) remove template M
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template <class BASIS, int M>
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class VectorDerivativeFactor
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: public FunctorizedFactor<Vector, ParameterMatrix<M>> {
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: public FunctorizedFactor<Vector, ParameterMatrix> {
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private:
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using Base = FunctorizedFactor<Vector, ParameterMatrix<M>>;
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using Base = FunctorizedFactor<Vector, ParameterMatrix>;
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using Func = typename BASIS::template VectorDerivativeFunctor<M>;
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public:
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@ -379,11 +380,12 @@ class VectorDerivativeFactor
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* @param BASIS: The basis class to use e.g. Chebyshev2
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* @param P: Size of the control component derivative.
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*/
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// TODO(Varun) remove template P
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template <class BASIS, int P>
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class ComponentDerivativeFactor
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: public FunctorizedFactor<double, ParameterMatrix<P>> {
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: public FunctorizedFactor<double, ParameterMatrix> {
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private:
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using Base = FunctorizedFactor<double, ParameterMatrix<P>>;
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using Base = FunctorizedFactor<double, ParameterMatrix>;
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using Func = typename BASIS::template ComponentDerivativeFunctor<P>;
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public:
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@ -30,16 +30,12 @@ namespace gtsam {
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/**
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* A matrix abstraction of MxN values at the Basis points.
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* This class serves as a wrapper over an Eigen matrix.
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* @tparam M: The dimension of the type you wish to evaluate.
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* @param N: the number of Basis points (e.g. Chebyshev points of the second
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* kind).
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*/
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template <int M>
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class ParameterMatrix {
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using MatrixType = Eigen::Matrix<double, M, -1>;
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private:
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MatrixType matrix_;
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Matrix matrix_;
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public:
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EIGEN_MAKE_ALIGNED_OPERATOR_NEW
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@ -48,15 +44,18 @@ class ParameterMatrix {
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/**
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* Create ParameterMatrix using the number of basis points.
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* @param M: The dimension size of the type you wish to evaluate.
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* @param N: The number of basis points (the columns).
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*/
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ParameterMatrix(const size_t N) : matrix_(M, N) { matrix_.setZero(); }
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ParameterMatrix(const size_t M, const size_t N) : matrix_(M, N) {
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matrix_.setZero();
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}
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/**
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* Create ParameterMatrix from an MxN Eigen Matrix.
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* @param matrix: An Eigen matrix used to initialze the ParameterMatrix.
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*/
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ParameterMatrix(const MatrixType& matrix) : matrix_(matrix) {}
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ParameterMatrix(const Matrix& matrix) : matrix_(matrix) {}
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/// Get the number of rows.
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size_t rows() const { return matrix_.rows(); }
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@ -65,10 +64,10 @@ class ParameterMatrix {
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size_t cols() const { return matrix_.cols(); }
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/// Get the underlying matrix.
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MatrixType matrix() const { return matrix_; }
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Matrix matrix() const { return matrix_; }
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/// Return the tranpose of the underlying matrix.
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Eigen::Matrix<double, -1, M> transpose() const { return matrix_.transpose(); }
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Matrix transpose() const { return matrix_.transpose(); }
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/**
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* Get the matrix row specified by `index`.
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@ -82,7 +81,7 @@ class ParameterMatrix {
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* Set the matrix row specified by `index`.
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* @param index: The row index to set.
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*/
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auto row(size_t index) -> Eigen::Block<MatrixType, 1, -1, false> {
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auto row(size_t index) -> Eigen::Block<Matrix, 1, -1, false> {
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return matrix_.row(index);
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}
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@ -90,7 +89,7 @@ class ParameterMatrix {
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* Get the matrix column specified by `index`.
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* @param index: The column index to retrieve.
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*/
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Eigen::Matrix<double, M, 1> col(size_t index) const {
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Eigen::Matrix<double, -1, 1> col(size_t index) const {
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return matrix_.col(index);
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}
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@ -98,7 +97,7 @@ class ParameterMatrix {
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* Set the matrix column specified by `index`.
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* @param index: The column index to set.
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*/
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auto col(size_t index) -> Eigen::Block<MatrixType, M, 1, true> {
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auto col(size_t index) -> Eigen::Block<Matrix, -1, 1, true> {
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return matrix_.col(index);
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}
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@ -111,37 +110,35 @@ class ParameterMatrix {
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* Add a ParameterMatrix to another.
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* @param other: ParameterMatrix to add.
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*/
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ParameterMatrix<M> operator+(const ParameterMatrix<M>& other) const {
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return ParameterMatrix<M>(matrix_ + other.matrix());
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ParameterMatrix operator+(const ParameterMatrix& other) const {
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return ParameterMatrix(matrix_ + other.matrix());
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}
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/**
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* Add a MxN-sized vector to the ParameterMatrix.
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* @param other: Vector which is reshaped and added.
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*/
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ParameterMatrix<M> operator+(
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const Eigen::Matrix<double, -1, 1>& other) const {
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ParameterMatrix operator+(const Eigen::Matrix<double, -1, 1>& other) const {
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// This form avoids a deep copy and instead typecasts `other`.
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Eigen::Map<const MatrixType> other_(other.data(), M, cols());
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return ParameterMatrix<M>(matrix_ + other_);
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Eigen::Map<const Matrix> other_(other.data(), rows(), cols());
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return ParameterMatrix(matrix_ + other_);
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}
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/**
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* Subtract a ParameterMatrix from another.
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* @param other: ParameterMatrix to subtract.
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*/
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ParameterMatrix<M> operator-(const ParameterMatrix<M>& other) const {
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return ParameterMatrix<M>(matrix_ - other.matrix());
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ParameterMatrix operator-(const ParameterMatrix& other) const {
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return ParameterMatrix(matrix_ - other.matrix());
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}
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/**
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* Subtract a MxN-sized vector from the ParameterMatrix.
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* @param other: Vector which is reshaped and subracted.
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*/
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ParameterMatrix<M> operator-(
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const Eigen::Matrix<double, -1, 1>& other) const {
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Eigen::Map<const MatrixType> other_(other.data(), M, cols());
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return ParameterMatrix<M>(matrix_ - other_);
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ParameterMatrix operator-(const Eigen::Matrix<double, -1, 1>& other) const {
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Eigen::Map<const Matrix> other_(other.data(), rows(), cols());
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return ParameterMatrix(matrix_ - other_);
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}
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/**
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@ -149,9 +146,7 @@ class ParameterMatrix {
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* @param other: Eigen matrix which should be multiplication compatible with
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* the ParameterMatrix.
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*/
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MatrixType operator*(const Eigen::Matrix<double, -1, -1>& other) const {
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return matrix_ * other;
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}
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Matrix operator*(const Matrix& other) const { return matrix_ * other; }
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/// @name Vector Space requirements
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/// @{
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@ -169,7 +164,7 @@ class ParameterMatrix {
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* @param other: The ParameterMatrix to check equality with.
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* @param tol: The absolute tolerance threshold.
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*/
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bool equals(const ParameterMatrix<M>& other, double tol = 1e-8) const {
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bool equals(const ParameterMatrix& other, double tol = 1e-8) const {
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return gtsam::equal_with_abs_tol(matrix_, other.matrix(), tol);
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}
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@ -189,27 +184,24 @@ class ParameterMatrix {
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* NOTE: The size at compile time is unknown so this identity is zero
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* length and thus not valid.
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*/
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inline static ParameterMatrix Identity() {
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// throw std::runtime_error(
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// "ParameterMatrix::Identity(): Don't use this function");
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return ParameterMatrix(0);
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inline static ParameterMatrix Identity(size_t M = 0, size_t N = 0) {
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return ParameterMatrix(M, N);
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}
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/// @}
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};
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// traits for ParameterMatrix
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template <int M>
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struct traits<ParameterMatrix<M>>
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: public internal::VectorSpace<ParameterMatrix<M>> {};
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/// traits for ParameterMatrix
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template <>
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struct traits<ParameterMatrix> : public internal::VectorSpace<ParameterMatrix> {
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};
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/* ************************************************************************* */
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// Stream operator that takes a ParameterMatrix. Used for printing.
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template <int M>
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inline std::ostream& operator<<(std::ostream& os,
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const ParameterMatrix<M>& parameterMatrix) {
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const ParameterMatrix& parameterMatrix) {
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os << parameterMatrix.matrix();
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return os;
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}
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} // namespace gtsam
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} // namespace gtsam
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@ -48,9 +48,8 @@ class Chebyshev2 {
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#include <gtsam/basis/ParameterMatrix.h>
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template <M = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15}>
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class ParameterMatrix {
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ParameterMatrix(const size_t N);
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ParameterMatrix(const size_t M, const size_t N);
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ParameterMatrix(const Matrix& matrix);
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Matrix matrix() const;
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@ -17,30 +17,29 @@
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* @brief unit tests for factors in BasisFactors.h
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*/
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#include <CppUnitLite/TestHarness.h>
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#include <gtsam/base/Testable.h>
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#include <gtsam/base/TestableAssertions.h>
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#include <gtsam/base/Vector.h>
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#include <gtsam/basis/Basis.h>
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#include <gtsam/basis/BasisFactors.h>
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#include <gtsam/basis/Chebyshev2.h>
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#include <gtsam/geometry/Pose2.h>
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#include <gtsam/inference/Symbol.h>
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#include <gtsam/nonlinear/FunctorizedFactor.h>
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#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
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#include <gtsam/nonlinear/factorTesting.h>
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#include <gtsam/inference/Symbol.h>
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#include <gtsam/base/Testable.h>
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#include <gtsam/base/TestableAssertions.h>
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#include <gtsam/base/Vector.h>
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#include <CppUnitLite/TestHarness.h>
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using gtsam::noiseModel::Isotropic;
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using gtsam::Pose2;
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using gtsam::Vector;
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using gtsam::Values;
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using gtsam::Chebyshev2;
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using gtsam::ParameterMatrix;
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using gtsam::LevenbergMarquardtParams;
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using gtsam::LevenbergMarquardtOptimizer;
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using gtsam::LevenbergMarquardtParams;
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using gtsam::NonlinearFactorGraph;
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using gtsam::NonlinearOptimizerParams;
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using gtsam::ParameterMatrix;
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using gtsam::Pose2;
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using gtsam::Values;
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using gtsam::Vector;
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using gtsam::noiseModel::Isotropic;
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constexpr size_t N = 2;
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@ -86,10 +85,10 @@ TEST(BasisFactors, VectorEvaluationFactor) {
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NonlinearFactorGraph graph;
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graph.add(factor);
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ParameterMatrix<M> stateMatrix(N);
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ParameterMatrix stateMatrix(M, N);
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Values initial;
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initial.insert<ParameterMatrix<M>>(key, stateMatrix);
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initial.insert<ParameterMatrix>(key, stateMatrix);
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LevenbergMarquardtParams parameters;
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parameters.setMaxIterations(20);
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@ -128,16 +127,16 @@ TEST(BasisFactors, VectorComponentFactor) {
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const size_t i = 2;
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const double measured = 0.0, t = 3.0, a = 2.0, b = 4.0;
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auto model = Isotropic::Sigma(1, 1.0);
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VectorComponentFactor<Chebyshev2, P> factor(key, measured, model, N, i,
|
||||
t, a, b);
|
||||
VectorComponentFactor<Chebyshev2, P> factor(key, measured, model, N, i, t, a,
|
||||
b);
|
||||
|
||||
NonlinearFactorGraph graph;
|
||||
graph.add(factor);
|
||||
|
||||
ParameterMatrix<P> stateMatrix(N);
|
||||
ParameterMatrix stateMatrix(P, N);
|
||||
|
||||
Values initial;
|
||||
initial.insert<ParameterMatrix<P>>(key, stateMatrix);
|
||||
initial.insert<ParameterMatrix>(key, stateMatrix);
|
||||
|
||||
LevenbergMarquardtParams parameters;
|
||||
parameters.setMaxIterations(20);
|
||||
|
|
@ -153,16 +152,16 @@ TEST(BasisFactors, ManifoldEvaluationFactor) {
|
|||
const Pose2 measured;
|
||||
const double t = 3.0, a = 2.0, b = 4.0;
|
||||
auto model = Isotropic::Sigma(3, 1.0);
|
||||
ManifoldEvaluationFactor<Chebyshev2, Pose2> factor(key, measured, model, N,
|
||||
t, a, b);
|
||||
ManifoldEvaluationFactor<Chebyshev2, Pose2> factor(key, measured, model, N, t,
|
||||
a, b);
|
||||
|
||||
NonlinearFactorGraph graph;
|
||||
graph.add(factor);
|
||||
|
||||
ParameterMatrix<3> stateMatrix(N);
|
||||
ParameterMatrix stateMatrix(3, N);
|
||||
|
||||
Values initial;
|
||||
initial.insert<ParameterMatrix<3>>(key, stateMatrix);
|
||||
initial.insert<ParameterMatrix>(key, stateMatrix);
|
||||
|
||||
LevenbergMarquardtParams parameters;
|
||||
parameters.setMaxIterations(20);
|
||||
|
|
@ -186,10 +185,10 @@ TEST(BasisFactors, VecDerivativePrior) {
|
|||
NonlinearFactorGraph graph;
|
||||
graph.add(vecDPrior);
|
||||
|
||||
ParameterMatrix<M> stateMatrix(N);
|
||||
ParameterMatrix stateMatrix(M, N);
|
||||
|
||||
Values initial;
|
||||
initial.insert<ParameterMatrix<M>>(key, stateMatrix);
|
||||
initial.insert<ParameterMatrix>(key, stateMatrix);
|
||||
|
||||
LevenbergMarquardtParams parameters;
|
||||
parameters.setMaxIterations(20);
|
||||
|
|
@ -213,8 +212,8 @@ TEST(BasisFactors, ComponentDerivativeFactor) {
|
|||
graph.add(controlDPrior);
|
||||
|
||||
Values initial;
|
||||
ParameterMatrix<M> stateMatrix(N);
|
||||
initial.insert<ParameterMatrix<M>>(key, stateMatrix);
|
||||
ParameterMatrix stateMatrix(M, N);
|
||||
initial.insert<ParameterMatrix>(key, stateMatrix);
|
||||
|
||||
LevenbergMarquardtParams parameters;
|
||||
parameters.setMaxIterations(20);
|
||||
|
|
|
|||
|
|
@ -108,7 +108,7 @@ TEST(Chebyshev2, InterpolateVector) {
|
|||
double t = 30, a = 0, b = 100;
|
||||
const size_t N = 3;
|
||||
// Create 2x3 matrix with Vectors at Chebyshev points
|
||||
ParameterMatrix<2> X(N);
|
||||
ParameterMatrix X(2, N);
|
||||
X.row(0) = Chebyshev2::Points(N, a, b); // slope 1 ramp
|
||||
|
||||
// Check value
|
||||
|
|
@ -120,11 +120,11 @@ TEST(Chebyshev2, InterpolateVector) {
|
|||
EXPECT(assert_equal(expected, fx(X, actualH), 1e-9));
|
||||
|
||||
// Check derivative
|
||||
std::function<Vector2(ParameterMatrix<2>)> f =
|
||||
std::function<Vector2(ParameterMatrix)> f =
|
||||
std::bind(&Chebyshev2::VectorEvaluationFunctor<2>::operator(), fx,
|
||||
std::placeholders::_1, nullptr);
|
||||
Matrix numericalH =
|
||||
numericalDerivative11<Vector2, ParameterMatrix<2>, 2 * N>(f, X);
|
||||
numericalDerivative11<Vector2, ParameterMatrix, 2 * N>(f, X);
|
||||
EXPECT(assert_equal(numericalH, actualH, 1e-9));
|
||||
}
|
||||
|
||||
|
|
@ -133,7 +133,7 @@ TEST(Chebyshev2, InterpolateVector) {
|
|||
TEST(Chebyshev2, InterpolatePose2) {
|
||||
double t = 30, a = 0, b = 100;
|
||||
|
||||
ParameterMatrix<3> X(N);
|
||||
ParameterMatrix X(3, N);
|
||||
X.row(0) = Chebyshev2::Points(N, a, b); // slope 1 ramp
|
||||
X.row(1) = Vector::Zero(N);
|
||||
X.row(2) = 0.1 * Vector::Ones(N);
|
||||
|
|
@ -148,11 +148,11 @@ TEST(Chebyshev2, InterpolatePose2) {
|
|||
EXPECT(assert_equal(expected, fx(X, actualH)));
|
||||
|
||||
// Check derivative
|
||||
std::function<Pose2(ParameterMatrix<3>)> f =
|
||||
std::function<Pose2(ParameterMatrix)> f =
|
||||
std::bind(&Chebyshev2::ManifoldEvaluationFunctor<Pose2>::operator(), fx,
|
||||
std::placeholders::_1, nullptr);
|
||||
Matrix numericalH =
|
||||
numericalDerivative11<Pose2, ParameterMatrix<3>, 3 * N>(f, X);
|
||||
numericalDerivative11<Pose2, ParameterMatrix, 3 * N>(f, X);
|
||||
EXPECT(assert_equal(numericalH, actualH, 1e-9));
|
||||
}
|
||||
|
||||
|
|
@ -169,7 +169,7 @@ TEST(Chebyshev2, InterpolatePose3) {
|
|||
Vector6 xi = Pose3::ChartAtOrigin::Local(pose);
|
||||
Eigen::Matrix<double, /*6x6N*/ -1, -1> actualH(6, 6 * N);
|
||||
|
||||
ParameterMatrix<6> X(N);
|
||||
ParameterMatrix X(6, N);
|
||||
X.col(11) = xi;
|
||||
|
||||
Chebyshev2::ManifoldEvaluationFunctor<Pose3> fx(N, t, a, b);
|
||||
|
|
@ -178,11 +178,11 @@ TEST(Chebyshev2, InterpolatePose3) {
|
|||
EXPECT(assert_equal(expected, fx(X, actualH)));
|
||||
|
||||
// Check derivative
|
||||
std::function<Pose3(ParameterMatrix<6>)> f =
|
||||
std::function<Pose3(ParameterMatrix)> f =
|
||||
std::bind(&Chebyshev2::ManifoldEvaluationFunctor<Pose3>::operator(), fx,
|
||||
std::placeholders::_1, nullptr);
|
||||
Matrix numericalH =
|
||||
numericalDerivative11<Pose3, ParameterMatrix<6>, 6 * N>(f, X);
|
||||
numericalDerivative11<Pose3, ParameterMatrix, 6 * N>(f, X);
|
||||
EXPECT(assert_equal(numericalH, actualH, 1e-8));
|
||||
}
|
||||
#endif
|
||||
|
|
@ -415,12 +415,12 @@ TEST(Chebyshev2, VectorDerivativeFunctor) {
|
|||
const double x = 0.2;
|
||||
using VecD = Chebyshev2::VectorDerivativeFunctor<M>;
|
||||
VecD fx(N, x, 0, 3);
|
||||
ParameterMatrix<M> X(N);
|
||||
ParameterMatrix X(M, N);
|
||||
Matrix actualH(M, M * N);
|
||||
EXPECT(assert_equal(Vector::Zero(M), (Vector)fx(X, actualH), 1e-8));
|
||||
|
||||
// Test Jacobian
|
||||
Matrix expectedH = numericalDerivative11<Vector2, ParameterMatrix<M>, M * N>(
|
||||
Matrix expectedH = numericalDerivative11<Vector2, ParameterMatrix, M * N>(
|
||||
std::bind(&VecD::operator(), fx, std::placeholders::_1, nullptr), X);
|
||||
EXPECT(assert_equal(expectedH, actualH, 1e-7));
|
||||
}
|
||||
|
|
@ -433,12 +433,12 @@ TEST(Chebyshev2, VectorDerivativeFunctor2) {
|
|||
|
||||
const Vector points = Chebyshev2::Points(N, 0, T);
|
||||
|
||||
// Assign the parameter matrix
|
||||
Vector values(N);
|
||||
// Assign the parameter matrix 1xN
|
||||
Matrix values(1, N);
|
||||
for (size_t i = 0; i < N; ++i) {
|
||||
values(i) = f(points(i));
|
||||
}
|
||||
ParameterMatrix<M> X(values);
|
||||
ParameterMatrix X(values);
|
||||
|
||||
// Evaluate the derivative at the chebyshev points using
|
||||
// VectorDerivativeFunctor.
|
||||
|
|
@ -452,7 +452,7 @@ TEST(Chebyshev2, VectorDerivativeFunctor2) {
|
|||
Matrix actualH(M, M * N);
|
||||
VecD vecd(N, points(0), 0, T);
|
||||
vecd(X, actualH);
|
||||
Matrix expectedH = numericalDerivative11<Vector1, ParameterMatrix<M>, M * N>(
|
||||
Matrix expectedH = numericalDerivative11<Vector1, ParameterMatrix, M * N>(
|
||||
std::bind(&VecD::operator(), vecd, std::placeholders::_1, nullptr), X);
|
||||
EXPECT(assert_equal(expectedH, actualH, 1e-6));
|
||||
}
|
||||
|
|
@ -465,11 +465,11 @@ TEST(Chebyshev2, ComponentDerivativeFunctor) {
|
|||
using CompFunc = Chebyshev2::ComponentDerivativeFunctor<M>;
|
||||
size_t row = 1;
|
||||
CompFunc fx(N, row, x, 0, 3);
|
||||
ParameterMatrix<M> X(N);
|
||||
ParameterMatrix X(M, N);
|
||||
Matrix actualH(1, M * N);
|
||||
EXPECT_DOUBLES_EQUAL(0, fx(X, actualH), 1e-8);
|
||||
|
||||
Matrix expectedH = numericalDerivative11<double, ParameterMatrix<M>, M * N>(
|
||||
Matrix expectedH = numericalDerivative11<double, ParameterMatrix, M * N>(
|
||||
std::bind(&CompFunc::operator(), fx, std::placeholders::_1, nullptr), X);
|
||||
EXPECT(assert_equal(expectedH, actualH, 1e-7));
|
||||
}
|
||||
|
|
|
|||
|
|
@ -190,7 +190,7 @@ TEST(Basis, VecDerivativeFunctor) {
|
|||
Matrix23 theta_mat = (Matrix32() << 0, 0, 0.7071, 0.7071, 0.7071, -0.7071)
|
||||
.finished()
|
||||
.transpose();
|
||||
ParameterMatrix<2> theta(theta_mat);
|
||||
ParameterMatrix theta(theta_mat);
|
||||
EXPECT(assert_equal(Vector(dotShape), dotShapeFunction(theta), 1e-4));
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -32,19 +32,19 @@ const size_t M = 2, N = 5;
|
|||
|
||||
//******************************************************************************
|
||||
TEST(ParameterMatrix, Constructor) {
|
||||
ParameterMatrix<2> actual1(3);
|
||||
ParameterMatrix<2> expected1(Matrix::Zero(2, 3));
|
||||
ParameterMatrix actual1(2, 3);
|
||||
ParameterMatrix expected1(Matrix::Zero(2, 3));
|
||||
EXPECT(assert_equal(expected1, actual1));
|
||||
|
||||
ParameterMatrix<2> actual2(Matrix::Ones(2, 3));
|
||||
ParameterMatrix<2> expected2(Matrix::Ones(2, 3));
|
||||
ParameterMatrix actual2(Matrix::Ones(2, 3));
|
||||
ParameterMatrix expected2(Matrix::Ones(2, 3));
|
||||
EXPECT(assert_equal(expected2, actual2));
|
||||
EXPECT(assert_equal(expected2.matrix(), actual2.matrix()));
|
||||
}
|
||||
|
||||
//******************************************************************************
|
||||
TEST(ParameterMatrix, Dimensions) {
|
||||
ParameterMatrix<M> params(N);
|
||||
ParameterMatrix params(M, N);
|
||||
EXPECT_LONGS_EQUAL(params.rows(), M);
|
||||
EXPECT_LONGS_EQUAL(params.cols(), N);
|
||||
EXPECT_LONGS_EQUAL(params.dim(), M * N);
|
||||
|
|
@ -52,7 +52,7 @@ TEST(ParameterMatrix, Dimensions) {
|
|||
|
||||
//******************************************************************************
|
||||
TEST(ParameterMatrix, Getters) {
|
||||
ParameterMatrix<M> params(N);
|
||||
ParameterMatrix params(M, N);
|
||||
|
||||
Matrix expectedMatrix = Matrix::Zero(2, 5);
|
||||
EXPECT(assert_equal(expectedMatrix, params.matrix()));
|
||||
|
|
@ -60,13 +60,13 @@ TEST(ParameterMatrix, Getters) {
|
|||
Matrix expectedMatrixTranspose = Matrix::Zero(5, 2);
|
||||
EXPECT(assert_equal(expectedMatrixTranspose, params.transpose()));
|
||||
|
||||
ParameterMatrix<M> p2(Matrix::Ones(M, N));
|
||||
ParameterMatrix p2(Matrix::Ones(M, N));
|
||||
Vector expectedRowVector = Vector::Ones(N);
|
||||
for (size_t r = 0; r < M; ++r) {
|
||||
EXPECT(assert_equal(p2.row(r), expectedRowVector));
|
||||
}
|
||||
|
||||
ParameterMatrix<M> p3(2 * Matrix::Ones(M, N));
|
||||
ParameterMatrix p3(2 * Matrix::Ones(M, N));
|
||||
Vector expectedColVector = 2 * Vector::Ones(M);
|
||||
for (size_t c = 0; c < M; ++c) {
|
||||
EXPECT(assert_equal(p3.col(c), expectedColVector));
|
||||
|
|
@ -75,7 +75,7 @@ TEST(ParameterMatrix, Getters) {
|
|||
|
||||
//******************************************************************************
|
||||
TEST(ParameterMatrix, Setters) {
|
||||
ParameterMatrix<M> params(Matrix::Zero(M, N));
|
||||
ParameterMatrix params(Matrix::Zero(M, N));
|
||||
Matrix expected = Matrix::Zero(M, N);
|
||||
|
||||
// row
|
||||
|
|
@ -97,31 +97,31 @@ TEST(ParameterMatrix, Setters) {
|
|||
|
||||
//******************************************************************************
|
||||
TEST(ParameterMatrix, Addition) {
|
||||
ParameterMatrix<M> params(Matrix::Ones(M, N));
|
||||
ParameterMatrix<M> expected(2 * Matrix::Ones(M, N));
|
||||
ParameterMatrix params(Matrix::Ones(M, N));
|
||||
ParameterMatrix expected(2 * Matrix::Ones(M, N));
|
||||
|
||||
// Add vector
|
||||
EXPECT(assert_equal(expected, params + Vector::Ones(M * N)));
|
||||
// Add another ParameterMatrix
|
||||
ParameterMatrix<M> actual = params + ParameterMatrix<M>(Matrix::Ones(M, N));
|
||||
ParameterMatrix actual = params + ParameterMatrix(Matrix::Ones(M, N));
|
||||
EXPECT(assert_equal(expected, actual));
|
||||
}
|
||||
|
||||
//******************************************************************************
|
||||
TEST(ParameterMatrix, Subtraction) {
|
||||
ParameterMatrix<M> params(2 * Matrix::Ones(M, N));
|
||||
ParameterMatrix<M> expected(Matrix::Ones(M, N));
|
||||
ParameterMatrix params(2 * Matrix::Ones(M, N));
|
||||
ParameterMatrix expected(Matrix::Ones(M, N));
|
||||
|
||||
// Subtract vector
|
||||
EXPECT(assert_equal(expected, params - Vector::Ones(M * N)));
|
||||
// Subtract another ParameterMatrix
|
||||
ParameterMatrix<M> actual = params - ParameterMatrix<M>(Matrix::Ones(M, N));
|
||||
ParameterMatrix actual = params - ParameterMatrix(Matrix::Ones(M, N));
|
||||
EXPECT(assert_equal(expected, actual));
|
||||
}
|
||||
|
||||
//******************************************************************************
|
||||
TEST(ParameterMatrix, Multiplication) {
|
||||
ParameterMatrix<M> params(Matrix::Ones(M, N));
|
||||
ParameterMatrix params(Matrix::Ones(M, N));
|
||||
Matrix multiplier = 2 * Matrix::Ones(N, 2);
|
||||
Matrix expected = 2 * N * Matrix::Ones(M, 2);
|
||||
EXPECT(assert_equal(expected, params * multiplier));
|
||||
|
|
@ -129,12 +129,12 @@ TEST(ParameterMatrix, Multiplication) {
|
|||
|
||||
//******************************************************************************
|
||||
TEST(ParameterMatrix, VectorSpace) {
|
||||
ParameterMatrix<M> params(Matrix::Ones(M, N));
|
||||
ParameterMatrix params(Matrix::Ones(M, N));
|
||||
// vector
|
||||
EXPECT(assert_equal(Vector::Ones(M * N), params.vector()));
|
||||
// identity
|
||||
EXPECT(assert_equal(ParameterMatrix<M>::Identity(),
|
||||
ParameterMatrix<M>(Matrix::Zero(M, 0))));
|
||||
EXPECT(assert_equal(ParameterMatrix::Identity(M),
|
||||
ParameterMatrix(Matrix::Zero(M, 0))));
|
||||
}
|
||||
|
||||
//******************************************************************************
|
||||
|
|
|
|||
|
|
@ -96,21 +96,7 @@ class Values {
|
|||
void insert(size_t j, const gtsam::imuBias::ConstantBias& constant_bias);
|
||||
void insert(size_t j, const gtsam::NavState& nav_state);
|
||||
void insert(size_t j, double c);
|
||||
void insert(size_t j, const gtsam::ParameterMatrix<1>& X);
|
||||
void insert(size_t j, const gtsam::ParameterMatrix<2>& X);
|
||||
void insert(size_t j, const gtsam::ParameterMatrix<3>& X);
|
||||
void insert(size_t j, const gtsam::ParameterMatrix<4>& X);
|
||||
void insert(size_t j, const gtsam::ParameterMatrix<5>& X);
|
||||
void insert(size_t j, const gtsam::ParameterMatrix<6>& X);
|
||||
void insert(size_t j, const gtsam::ParameterMatrix<7>& X);
|
||||
void insert(size_t j, const gtsam::ParameterMatrix<8>& X);
|
||||
void insert(size_t j, const gtsam::ParameterMatrix<9>& X);
|
||||
void insert(size_t j, const gtsam::ParameterMatrix<10>& X);
|
||||
void insert(size_t j, const gtsam::ParameterMatrix<11>& X);
|
||||
void insert(size_t j, const gtsam::ParameterMatrix<12>& X);
|
||||
void insert(size_t j, const gtsam::ParameterMatrix<13>& X);
|
||||
void insert(size_t j, const gtsam::ParameterMatrix<14>& X);
|
||||
void insert(size_t j, const gtsam::ParameterMatrix<15>& X);
|
||||
void insert(size_t j, const gtsam::ParameterMatrix& X);
|
||||
|
||||
template <T = {gtsam::Point2, gtsam::Point3}>
|
||||
void insert(size_t j, const T& val);
|
||||
|
|
@ -144,21 +130,7 @@ class Values {
|
|||
void update(size_t j, Vector vector);
|
||||
void update(size_t j, Matrix matrix);
|
||||
void update(size_t j, double c);
|
||||
void update(size_t j, const gtsam::ParameterMatrix<1>& X);
|
||||
void update(size_t j, const gtsam::ParameterMatrix<2>& X);
|
||||
void update(size_t j, const gtsam::ParameterMatrix<3>& X);
|
||||
void update(size_t j, const gtsam::ParameterMatrix<4>& X);
|
||||
void update(size_t j, const gtsam::ParameterMatrix<5>& X);
|
||||
void update(size_t j, const gtsam::ParameterMatrix<6>& X);
|
||||
void update(size_t j, const gtsam::ParameterMatrix<7>& X);
|
||||
void update(size_t j, const gtsam::ParameterMatrix<8>& X);
|
||||
void update(size_t j, const gtsam::ParameterMatrix<9>& X);
|
||||
void update(size_t j, const gtsam::ParameterMatrix<10>& X);
|
||||
void update(size_t j, const gtsam::ParameterMatrix<11>& X);
|
||||
void update(size_t j, const gtsam::ParameterMatrix<12>& X);
|
||||
void update(size_t j, const gtsam::ParameterMatrix<13>& X);
|
||||
void update(size_t j, const gtsam::ParameterMatrix<14>& X);
|
||||
void update(size_t j, const gtsam::ParameterMatrix<15>& X);
|
||||
void update(size_t j, const gtsam::ParameterMatrix& X);
|
||||
|
||||
void insert_or_assign(size_t j, const gtsam::Point2& point2);
|
||||
void insert_or_assign(size_t j, const gtsam::Point3& point3);
|
||||
|
|
@ -199,21 +171,7 @@ class Values {
|
|||
void insert_or_assign(size_t j, Vector vector);
|
||||
void insert_or_assign(size_t j, Matrix matrix);
|
||||
void insert_or_assign(size_t j, double c);
|
||||
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<1>& X);
|
||||
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<2>& X);
|
||||
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<3>& X);
|
||||
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<4>& X);
|
||||
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<5>& X);
|
||||
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<6>& X);
|
||||
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<7>& X);
|
||||
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<8>& X);
|
||||
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<9>& X);
|
||||
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<10>& X);
|
||||
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<11>& X);
|
||||
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<12>& X);
|
||||
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<13>& X);
|
||||
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<14>& X);
|
||||
void insert_or_assign(size_t j, const gtsam::ParameterMatrix<15>& X);
|
||||
void insert_or_assign(size_t j, const gtsam::ParameterMatrix& X);
|
||||
|
||||
template <T = {gtsam::Point2,
|
||||
gtsam::Point3,
|
||||
|
|
@ -244,21 +202,7 @@ class Values {
|
|||
Vector,
|
||||
Matrix,
|
||||
double,
|
||||
gtsam::ParameterMatrix<1>,
|
||||
gtsam::ParameterMatrix<2>,
|
||||
gtsam::ParameterMatrix<3>,
|
||||
gtsam::ParameterMatrix<4>,
|
||||
gtsam::ParameterMatrix<5>,
|
||||
gtsam::ParameterMatrix<6>,
|
||||
gtsam::ParameterMatrix<7>,
|
||||
gtsam::ParameterMatrix<8>,
|
||||
gtsam::ParameterMatrix<9>,
|
||||
gtsam::ParameterMatrix<10>,
|
||||
gtsam::ParameterMatrix<11>,
|
||||
gtsam::ParameterMatrix<12>,
|
||||
gtsam::ParameterMatrix<13>,
|
||||
gtsam::ParameterMatrix<14>,
|
||||
gtsam::ParameterMatrix<15>}>
|
||||
gtsam::ParameterMatrix}>
|
||||
T at(size_t j);
|
||||
};
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue