Move MINRES to nanoeigenpy/solvers

Author: ManifoldFR

include/nanoeigenpy/decompositions.hpp

@@ -4,7 +4,6 @@
 
 #include "nanoeigenpy/decompositions/llt.hpp"
 #include "nanoeigenpy/decompositions/ldlt.hpp"
-#include "nanoeigenpy/decompositions/minres.hpp"
 #include "nanoeigenpy/decompositions/householder-qr.hpp"
 #include "nanoeigenpy/decompositions/full-piv-householder-qr.hpp"
 #include "nanoeigenpy/decompositions/col-piv-householder-qr.hpp"

include/nanoeigenpy/solvers.hpp

@@ -5,6 +5,7 @@
 #include "nanoeigenpy/solvers/basic-preconditioners.hpp"
 #include "nanoeigenpy/solvers/bfgs-preconditioners.hpp"
 #include "nanoeigenpy/solvers/iterative-solver-base.hpp"
+#include "nanoeigenpy/solvers/minres.hpp"
 #if EIGEN_VERSION_AT_LEAST(3, 3, 5)
 #include "nanoeigenpy/solvers/least-squares-conjugate-gradient.hpp"
 #endif

include/nanoeigenpy/decompositions/minres.hpp renamed to include/nanoeigenpy/solvers/minres.hpp

@@ -3,7 +3,7 @@
 #pragma once
 
 #include "nanoeigenpy/fwd.hpp"
-#include "../solvers/iterative-solver-base.hpp"
+#include "nanoeigenpy/solvers/iterative-solver-base.hpp"
 #include <nanobind/eigen/dense.h>
 #include <unsupported/Eigen/IterativeSolvers>
 

src/module.cpp

@@ -16,7 +16,6 @@ using SparseMatrix = Eigen::SparseMatrix<Scalar, Options>;
 
 NB_MAKE_OPAQUE(Eigen::LLT<Eigen::MatrixXd>)
 NB_MAKE_OPAQUE(Eigen::LDLT<Eigen::MatrixXd>)
-NB_MAKE_OPAQUE(Eigen::MINRES<Eigen::MatrixXd>)
 NB_MAKE_OPAQUE(Eigen::HouseholderQR<Eigen::MatrixXd>)
 NB_MAKE_OPAQUE(Eigen::FullPivHouseholderQR<Eigen::MatrixXd>)
 NB_MAKE_OPAQUE(Eigen::ColPivHouseholderQR<Eigen::MatrixXd>)
@@ -38,7 +37,6 @@ NB_MODULE(nanoeigenpy, m) {
   // Decompositions
   exposeLLTSolver<Matrix>(m, "LLT");
   exposeLDLTSolver<Matrix>(m, "LDLT");
-  exposeMINRESSolver<Matrix>(m, "MINRES");
   exposeHouseholderQRSolver<Matrix>(m, "HouseholderQR");
   exposeFullPivHouseholderQRSolver<Matrix>(m, "FullPivHouseholderQR");
   exposeColPivHouseholderQRSolver<Matrix>(m, "ColPivHouseholderQR");

src/solvers.cpp

@@ -11,6 +11,7 @@ void exposeSolvers(nb::module_& m) {
   exposeLeastSquareDiagonalPreconditioner<Scalar>(
       m, "LeastSquareDiagonalPreconditioner");
 #endif
+  exposeMINRESSolver<Matrix>(m, "MINRES");
 
   // Solvers
   using Eigen::ConjugateGradient;

tests/test_iterative_solvers.py

@@ -11,7 +11,7 @@
     nanoeigenpy.solvers.ConjugateGradient,
     nanoeigenpy.solvers.IdentityConjugateGradient,
     nanoeigenpy.solvers.LeastSquaresConjugateGradient,
-    nanoeigenpy.MINRES,
+    nanoeigenpy.solvers.MINRES,
 ]