Multiplying with the inverse of a matrix function

release/4.3a0
Frank Dellaert 2016-01-31 20:11:17 -08:00
parent e6521703e6
commit cb93c2bfc1
2 changed files with 103 additions and 7 deletions

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@ -13,13 +13,13 @@
namespace gtsam {
// Generic between, assumes existence of traits<T>::Between
template<typename T>
template <typename T>
Expression<T> between(const Expression<T>& t1, const Expression<T>& t2) {
return Expression<T>(traits<T>::Between, t1, t2);
}
// Generic compose, assumes existence of traits<T>::Compose
template<typename T>
template <typename T>
Expression<T> compose(const Expression<T>& t1, const Expression<T>& t2) {
return Expression<T>(traits<T>::Compose, t1, t2);
}
@ -60,8 +60,64 @@ struct MultiplyWithInverse {
}
};
/**
* Functor that implements multiplication with the inverse of a matrix, itself
* the result of a function f. It turn out we only need the derivatives of the
* operator phi(a): b -> f(a) * b
*/
template <typename T, int N>
struct MultiplyWithInverseFunction {
enum { M = traits<T>::dimension };
typedef Eigen::Matrix<double, N, 1> VectorN;
typedef Eigen::Matrix<double, N, N> MatrixN;
// The function phi should calculate f(a)*b, with derivatives in a and b.
// Naturally, the derivative in b is f(a).
typedef boost::function<VectorN(
const T&, const VectorN&, OptionalJacobian<N, M>, OptionalJacobian<N, N>)>
Operator;
/// Construct with function as explained above
MultiplyWithInverseFunction(const Operator& phi) : phi_(phi) {}
/// f(a).inverse() * b, with optional derivatives
VectorN operator()(const T& a, const VectorN& b,
OptionalJacobian<N, M> H1 = boost::none,
OptionalJacobian<N, N> H2 = boost::none) const {
MatrixN A;
phi_(a, b, boost::none, A); // get A = f(a) by calling f once
const MatrixN invA = A.inverse();
const VectorN c = invA * b;
if (H1) {
Eigen::Matrix<double, N, M> H;
phi_(a, c, H, boost::none); // get derivative H of forward mapping
*H1 = -invA* H;
}
if (H2) *H2 = invA;
return c;
}
/// Create expression
Expression<VectorN> operator()(const Expression<T>& a_,
const Expression<VectorN>& b_) const {
return Expression<VectorN>(*this, a_, b_);
}
private:
const Operator phi_;
};
// Some typedefs
typedef Expression<double> double_;
typedef Expression<Vector1> Vector1_;
typedef Expression<Vector2> Vector2_;
typedef Expression<Vector3> Vector3_;
typedef Expression<Vector4> Vector4_;
typedef Expression<Vector5> Vector5_;
typedef Expression<Vector6> Vector6_;
typedef Expression<Vector7> Vector7_;
typedef Expression<Vector8> Vector8_;
typedef Expression<Vector9> Vector9_;
} // \namespace gtsam
} // \namespace gtsam

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@ -600,10 +600,11 @@ TEST(Expression, testMultipleCompositions2) {
}
/* ************************************************************************* */
// Test multiplication with a matrix
// Test multiplication with the inverse of a matrix
TEST(ExpressionFactor, MultiplyWithInverse) {
// Create expression
auto model = noiseModel::Isotropic::Sigma(3, 1);
// Create expression
auto f_expr = MultiplyWithInverse<3>()(Key(0), Key(1));
// Check derivatives
@ -615,7 +616,46 @@ TEST(ExpressionFactor, MultiplyWithInverse) {
values.insert<Matrix3>(0, A);
values.insert<Vector3>(1, b);
ExpressionFactor<Vector3> factor(model, Vector3::Zero(), f_expr);
EXPECT_CORRECT_FACTOR_JACOBIANS(factor, values, 1e-5, 1e-5); // another way
EXPECT_CORRECT_FACTOR_JACOBIANS(factor, values, 1e-5, 1e-5);
}
/* ************************************************************************* */
// Test multiplication with the inverse of a matrix function
namespace test_operator {
Vector3 f(const Point2& a, const Vector3& b, OptionalJacobian<3, 2> H1,
OptionalJacobian<3, 3> H2) {
Matrix3 A = Vector3(1, 2, 3).asDiagonal();
A(0, 1) = a.x();
A(0, 2) = a.y();
A(1, 0) = a.x();
if (H1) *H1 << b.y(), b.z(), b.x(), 0, 0, 0;
if (H2) *H2 = A;
return A * b;
};
}
TEST(ExpressionFactor, MultiplyWithInverseFunction) {
auto model = noiseModel::Isotropic::Sigma(3, 1);
using test_operator::f;
auto f_expr = MultiplyWithInverseFunction<Point2, 3>(f)(Key(0), Key(1));
// Check derivatives
Point2 a(1, 2);
const Vector3 b(0.1, 0.2, 0.3);
Matrix32 H1;
Matrix3 A;
const Vector Ab = f(a, b, H1, A);
CHECK(assert_equal(A * b, Ab));
CHECK(assert_equal(numericalDerivative11<Vector3, Point2>(
boost::bind(f, _1, b, boost::none, boost::none), a),
H1));
Values values;
values.insert<Point2>(0, a);
values.insert<Vector3>(1, b);
ExpressionFactor<Vector3> factor(model, Vector3::Zero(), f_expr);
EXPECT_CORRECT_FACTOR_JACOBIANS(factor, values, 1e-5, 1e-5);
}
/* ************************************************************************* */