is_approx: Remove the remaining np.allclose in tests and use nanoeigepy.is_approx instead

Author: Lucas-Haubert

include/nanoeigenpy/decompositions/generalized-self-adjoint-eigen-solver.hpp

@@ -13,6 +13,8 @@ template <typename _MatrixType>
 void exposeGeneralizedSelfAdjointEigenSolver(nb::module_ m, const char *name) {
   using MatrixType = _MatrixType;
   using Solver = Eigen::GeneralizedSelfAdjointEigenSolver<MatrixType>;
+  using Scalar = typename MatrixType::Scalar;
+  using VectorType = Eigen::Matrix<Scalar, Eigen::Dynamic, 1>;
 
   if (check_registration_alias<Solver>(m)) {
     return;
@@ -43,12 +45,16 @@ void exposeGeneralizedSelfAdjointEigenSolver(nb::module_ m, const char *name) {
           "Computes the generalized eigendecomposition of given matrix.",
           nb::rv_policy::reference)
 
-      .def("eigenvalues", &Solver::eigenvalues,
-           "Returns the eigenvalues of given matrix.",
-           nb::rv_policy::reference_internal)
-      .def("eigenvectors", &Solver::eigenvectors,
-           "Returns the eigenvectors of given matrix.",
-           nb::rv_policy::reference_internal)
+      .def(
+          "eigenvalues",
+          [](Solver &c) -> const VectorType & { return c.eigenvalues(); },
+          "Returns the eigenvalues of given matrix.",
+          nb::rv_policy::reference_internal)
+      .def(
+          "eigenvectors",
+          [](Solver &c) -> const MatrixType & { return c.eigenvectors(); },
+          "Returns the eigenvectors of given matrix.",
+          nb::rv_policy::reference_internal)
 
       .def(
           "computeDirect",

include/nanoeigenpy/decompositions/self-adjoint-eigen-solver.hpp

@@ -13,6 +13,8 @@ template <typename _MatrixType>
 void exposeSelfAdjointEigenSolver(nb::module_ m, const char *name) {
   using MatrixType = _MatrixType;
   using Solver = Eigen::SelfAdjointEigenSolver<MatrixType>;
+  using Scalar = typename MatrixType::Scalar;
+  using VectorType = Eigen::Matrix<Scalar, Eigen::Dynamic, 1>;
 
   if (check_registration_alias<Solver>(m)) {
     return;
@@ -26,12 +28,16 @@ void exposeSelfAdjointEigenSolver(nb::module_ m, const char *name) {
            "matrix"_a, "options"_a = Eigen::ComputeEigenvectors,
            "Computes eigendecomposition of given matrix")
 
-      .def("eigenvalues", &Solver::eigenvalues,
-           "Returns the eigenvalues of given matrix.",
-           nb::rv_policy::reference_internal)
-      .def("eigenvectors", &Solver::eigenvectors,
-           "Returns the eigenvectors of given matrix.",
-           nb::rv_policy::reference_internal)
+      .def(
+          "eigenvalues",
+          [](Solver &c) -> const VectorType & { return c.eigenvalues(); },
+          "Returns the eigenvalues of given matrix.",
+          nb::rv_policy::reference_internal)
+      .def(
+          "eigenvectors",
+          [](Solver &c) -> const MatrixType & { return c.eigenvectors(); },
+          "Returns the eigenvectors of given matrix.",
+          nb::rv_policy::reference_internal)
 
       .def(
           "compute",

tests/test_generalized_self_adjoint_eigen_solver.py

@@ -20,7 +20,7 @@
 
 @pytest.mark.parametrize("options", _options)
 def test_generalized_selfadjoint_eigensolver(options):
-    dim = 100
+    dim = 5
     rng = np.random.default_rng()
     A = rng.random((dim, dim))
     A = (A + A.T) * 0.5
@@ -61,7 +61,7 @@ def test_generalized_selfadjoint_eigensolver(options):
                 lam = D[i]
                 ABv = AB @ v
                 lam_v = lam * v
-                assert np.allclose(ABv, lam_v)
+                assert nanoeigenpy.is_approx(ABv, lam_v, 1e-10)
 
         elif options & nanoeigenpy.DecompositionOptions.BAx_lx.value:
             BA = B @ A
@@ -70,7 +70,7 @@ def test_generalized_selfadjoint_eigensolver(options):
                 lam = D[i]
                 BAv = BA @ v
                 lam_v = lam * v
-                assert np.allclose(BAv, lam_v)
+                assert nanoeigenpy.is_approx(BAv, lam_v, 1e-10)
 
     _gsaes_compute = gsaes.compute(A, B)
     _gsaes_compute_options = gsaes.compute(A, B, options)

tests/test_geometry.py

@@ -9,7 +9,7 @@
 
 def isapprox(a, b, epsilon=1e-6):
     if issubclass(a.__class__, np.ndarray) and issubclass(b.__class__, np.ndarray):
-        return np.allclose(a, b, epsilon)
+        return nanoeigenpy.is_approx(a, b, epsilon)
     else:
         return abs(a - b) < epsilon