diff --git a/include/eigenpy/decompositions/LDLT.hpp b/include/eigenpy/decompositions/LDLT.hpp
index 6c30ae645e34009b0f001566138a631ad844c53e..1e4dbab8bb7095d61588aff2c2780ad3299bd978 100644
--- a/include/eigenpy/decompositions/LDLT.hpp
+++ b/include/eigenpy/decompositions/LDLT.hpp
@@ -1,5 +1,5 @@
/*
- * Copyright 2020 INRIA
+ * Copyright 2020-2021 INRIA
*/
#ifndef __eigenpy_decomposition_ldlt_hpp__
@@ -23,7 +23,8 @@ namespace eigenpy
typedef _MatrixType MatrixType;
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
- typedef Eigen::Matrix<Scalar,Eigen::Dynamic,1,MatrixType::Options> VectorType;
+ typedef Eigen::Matrix<Scalar,Eigen::Dynamic,1,MatrixType::Options> VectorXs;
+ typedef Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic,MatrixType::Options> MatrixXs;
typedef Eigen::LDLT<MatrixType> Solver;
template<class PyClass>
@@ -55,7 +56,7 @@ namespace eigenpy
"Returns the LDLT decomposition matrix.",
bp::return_internal_reference<>())
- .def("rankUpdate",(Solver & (Solver::*)(const Eigen::MatrixBase<VectorType> &, const RealScalar &))&Solver::template rankUpdate<VectorType>,
+ .def("rankUpdate",(Solver & (Solver::*)(const Eigen::MatrixBase<VectorXs> &, const RealScalar &))&Solver::template rankUpdate<VectorXs>,
bp::args("self","vector","sigma"),
bp::return_self<>())
@@ -78,8 +79,10 @@ namespace eigenpy
#endif
.def("reconstructedMatrix",&Solver::reconstructedMatrix,bp::arg("self"),
"Returns the matrix represented by the decomposition, i.e., it returns the product: L L^*. This function is provided for debug purpose.")
- .def("solve",&solve<VectorType>,bp::args("self","b"),
+ .def("solve",&solve<VectorXs>,bp::args("self","b"),
"Returns the solution x of A x = b using the current decomposition of A.")
+ .def("solve",&solve<MatrixXs>,bp::args("self","B"),
+ "Returns the solution X of A X = B using the current decomposition of A where B is a right hand side matrix.")
.def("setZero",&Solver::setZero,bp::arg("self"),
"Clear any existing decomposition.")
@@ -107,7 +110,7 @@ namespace eigenpy
static MatrixType matrixL(const Solver & self) { return self.matrixL(); }
static MatrixType matrixU(const Solver & self) { return self.matrixU(); }
- static VectorType vectorD(const Solver & self) { return self.vectorD(); }
+ static VectorXs vectorD(const Solver & self) { return self.vectorD(); }
static MatrixType transpositionsP(const Solver & self)
{
@@ -115,8 +118,8 @@ namespace eigenpy
self.matrixL().rows());
}
- template<typename VectorType>
- static VectorType solve(const Solver & self, const VectorType & vec)
+ template<typename MatrixOrVector>
+ static MatrixOrVector solve(const Solver & self, const MatrixOrVector & vec)
{
return self.solve(vec);
}
diff --git a/include/eigenpy/decompositions/LLT.hpp b/include/eigenpy/decompositions/LLT.hpp
index ba8c2f2b721a8febfce0820c68e3968e1eaa9e39..a06e937242571bd3f7ca5f777a3277592f5cbf00 100644
--- a/include/eigenpy/decompositions/LLT.hpp
+++ b/include/eigenpy/decompositions/LLT.hpp
@@ -1,5 +1,5 @@
/*
- * Copyright 2020 INRIA
+ * Copyright 2020-2021 INRIA
*/
#ifndef __eigenpy_decomposition_llt_hpp__
@@ -23,7 +23,8 @@ namespace eigenpy
typedef _MatrixType MatrixType;
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
- typedef Eigen::Matrix<Scalar,Eigen::Dynamic,1,MatrixType::Options> VectorType;
+ typedef Eigen::Matrix<Scalar,Eigen::Dynamic,1,MatrixType::Options> VectorXs;
+ typedef Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic,MatrixType::Options> MatrixXs;
typedef Eigen::LLT<MatrixType> Solver;
template<class PyClass>
@@ -46,10 +47,10 @@ namespace eigenpy
bp::return_internal_reference<>())
#if EIGEN_VERSION_AT_LEAST(3,3,90)
- .def("rankUpdate",(Solver& (Solver::*)(const VectorType &, const RealScalar &))&Solver::template rankUpdate<VectorType>,
+ .def("rankUpdate",(Solver& (Solver::*)(const VectorXs &, const RealScalar &))&Solver::template rankUpdate<VectorXs>,
bp::args("self","vector","sigma"), bp::return_self<>())
#else
- .def("rankUpdate",(Solver (Solver::*)(const VectorType &, const RealScalar &))&Solver::template rankUpdate<VectorType>,
+ .def("rankUpdate",(Solver (Solver::*)(const VectorXs &, const RealScalar &))&Solver::template rankUpdate<VectorXs>,
bp::args("self","vector","sigma"))
#endif
@@ -72,8 +73,10 @@ namespace eigenpy
#endif
.def("reconstructedMatrix",&Solver::reconstructedMatrix,bp::arg("self"),
"Returns the matrix represented by the decomposition, i.e., it returns the product: L L^*. This function is provided for debug purpose.")
- .def("solve",&solve<VectorType>,bp::args("self","b"),
+ .def("solve",&solve<VectorXs>,bp::args("self","b"),
"Returns the solution x of A x = b using the current decomposition of A.")
+ .def("solve",&solve<MatrixXs>,bp::args("self","B"),
+ "Returns the solution X of A X = B using the current decomposition of A where B is a right hand side matrix.")
;
}
@@ -99,8 +102,8 @@ namespace eigenpy
static MatrixType matrixL(const Solver & self) { return self.matrixL(); }
static MatrixType matrixU(const Solver & self) { return self.matrixU(); }
- template<typename VectorType>
- static VectorType solve(const Solver & self, const VectorType & vec)
+ template<typename MatrixOrVector>
+ static MatrixOrVector solve(const Solver & self, const MatrixOrVector & vec)
{
return self.solve(vec);
}
diff --git a/unittest/python/test_LDLT.py b/unittest/python/test_LDLT.py
index 7937aaec6c3ee328a853f1000e79d4cddbb37375..1cdb930c78720b6a24e32e2a041e471d89c68a1f 100644
--- a/unittest/python/test_LDLT.py
+++ b/unittest/python/test_LDLT.py
@@ -1,5 +1,4 @@
import eigenpy
-eigenpy.switchToNumpyArray()
import numpy as np
import numpy.linalg as la
@@ -16,3 +15,9 @@ D = ldlt.vectorD()
P = ldlt.transpositionsP()
assert eigenpy.is_approx(np.transpose(P).dot(L.dot(np.diag(D).dot(np.transpose(L).dot(P)))),A)
+
+X = np.random.rand(dim,20)
+B = A.dot(X)
+X_est = ldlt.solve(B)
+assert eigenpy.is_approx(X,X_est)
+assert eigenpy.is_approx(A.dot(X_est),B)
diff --git a/unittest/python/test_LLT.py b/unittest/python/test_LLT.py
index 4ad38fc21240f8fe394668e1f50e680cdb874089..2aac689ae63540feb9386273ae36737591a8238f 100644
--- a/unittest/python/test_LLT.py
+++ b/unittest/python/test_LLT.py
@@ -1,5 +1,4 @@
import eigenpy
-eigenpy.switchToNumpyArray()
import numpy as np
import numpy.linalg as la
@@ -12,5 +11,10 @@ A = (A + A.T)*0.5 + np.diag(10. + np.random.rand(dim))
llt = eigenpy.LLT(A)
L = llt.matrixL()
-
assert eigenpy.is_approx(L.dot(np.transpose(L)),A)
+
+X = np.random.rand(dim,20)
+B = A.dot(X)
+X_est = llt.solve(B)
+assert eigenpy.is_approx(X,X_est)
+assert eigenpy.is_approx(A.dot(X_est),B)