feat(bindings): adds .numpy() conversion for vector types

python/math3d/bindings/mat2_py.hpp

@@ -43,6 +43,10 @@ auto bindings_matrix2(py::module& m, const char* class_name) -> void {
         // cppcheck-suppress constParameter
         MATRIX_GETSET_ITEM(2, T)
         // clang-format on
+        .def("numpy",
+             [](const Class& self) -> py::array_t<T> {
+                 return ::math::mat2_to_nparray<T>(self);
+             })
         .def("flatten",
              [](const Class& self) -> py::array_t<T> {
                  auto array_np = py::array_t<T>(Class::BUFFER_SIZE);

python/math3d/bindings/mat3_py.hpp

@@ -43,6 +43,10 @@ auto bindings_matrix3(py::module& m, const char* class_name) -> void {
         // cppcheck-suppress constParameter
         MATRIX_GETSET_ITEM(3, T)
         // clang-format on
+        .def("numpy",
+             [](const Class& self) -> py::array_t<T> {
+                 return ::math::mat3_to_nparray<T>(self);
+             })
         .def("flatten",
              [](const Class& self) -> py::array_t<T> {
                  auto array_np = py::array_t<T>(Class::BUFFER_SIZE);

python/math3d/bindings/mat4_py.hpp

@@ -46,6 +46,10 @@ auto bindings_matrix4(py::module& m, const char* class_name) -> void {
         // cppcheck-suppress constParameter
         MATRIX_GETSET_ITEM(4, T)
         // clang-format on
+        .def("numpy",
+             [](const Class& self) -> py::array_t<T> {
+                 return ::math::mat4_to_nparray<T>(self);
+             })
         .def("flatten",
              [](const Class& self) -> py::array_t<T> {
                  auto array_np = py::array_t<T>(Class::BUFFER_SIZE);

python/math3d/bindings/vec2_py.hpp

@@ -15,6 +15,7 @@
 #include <math/vec2_t.hpp>
 
 #include <common_py.hpp>
+#include <conversions_py.hpp>
 
 namespace py = pybind11;
 
@@ -50,6 +51,9 @@ auto bindings_vector2(py::module& m, const char* class_name) -> void {
             VECTOR_METHODS(T)
             VECTOR_GETSET_ITEM(2, T)
             // clant-format on
+            .def("numpy", [](const Class& self) -> py::array_t<T> {
+                return ::math::vec2_to_nparray<T>(self);
+            })
             // NOLINTNEXTLINE
             .def_property_readonly("ndim", [](const Class&) {
                 return Class::VECTOR_NDIM;

python/math3d/bindings/vec3_py.hpp

@@ -13,6 +13,7 @@
 #include <math/vec3_t.hpp>
 
 #include <common_py.hpp>
+#include <conversions_py.hpp>
 
 namespace py = pybind11;
 
@@ -53,6 +54,9 @@ auto bindings_vector3(py::module& m, const char* class_name) -> void {
             })
             VECTOR_GETSET_ITEM(3, T)
             // clant-format on
+            .def("numpy", [](const Class& self) -> py::array_t<T> {
+                return ::math::vec3_to_nparray<T>(self);
+            })
             // NOLINTNEXTLINE
             .def_property_readonly("ndim", [](const Class&) {
                 return Class::VECTOR_NDIM;

python/math3d/bindings/vec4_py.hpp

@@ -13,6 +13,7 @@
 #include <math/vec4_t.hpp>
 
 #include <common_py.hpp>
+#include <conversions_py.hpp>
 
 namespace py = pybind11;
 
@@ -52,6 +53,9 @@ auto bindings_vector4(py::module& m, const char* class_name) -> void {
             VECTOR_METHODS(T)
             VECTOR_GETSET_ITEM(4, T)
             // clant-format on
+            .def("numpy", [](const Class& self) -> py::array_t<T> {
+                return ::math::vec4_to_nparray<T>(self);
+            })
             // NOLINTNEXTLINE
             .def_property_readonly("ndim", [](const Class&) {
                 return Class::VECTOR_NDIM;

python/math3d/typings/math3d.pyi

@@ -31,6 +31,7 @@ class Vector2:
     def squareNorm(self) -> float: ...
     def normalize(self) -> Vector2: ...
     def normalize_(self) -> None: ...
+    def numpy(self) -> ndarray: ...
 
 # Structure should be the same, except for the internal usage of f32 and f64
 Vector2f = Vector2
@@ -71,6 +72,7 @@ class Vector3:
     def squareNorm(self) -> float: ...
     def normalize(self) -> Vector3: ...
     def normalize_(self) -> None: ...
+    def numpy(self) -> ndarray: ...
 
 # Structure should be the same, except for the internal usage of f32 and f64
 Vector3f = Vector3
@@ -114,6 +116,7 @@ class Vector4:
     def squareNorm(self) -> float: ...
     def normalize(self) -> Vector4: ...
     def normalize_(self) -> None: ...
+    def numpy(self) -> ndarray: ...
 
 # Structure should be the same, except for the internal usage of f32 and f64
 Vector4f = Vector4

tests/python/vec2_test.py

@@ -120,3 +120,13 @@ def test_dot_product(self, Class: Vector2Cls) -> None:
         vec_a = Class(3.0, 5.0)
         vec_b = Class(7.0, 11.0)
         assert vec_a.dot(vec_b) == 76.0
+
+
+@pytest.mark.parametrize(
+    "Vec2,FloatType", [(m3d.Vector2f, np.float32), (m3d.Vector2d, np.float64)]
+)
+def test_convert_to_numpy(Vec2: Vector2Cls, FloatType: type) -> None:
+    vec2 = Vec2(1.0, 2.0)
+    np_vec2 = vec2.numpy()
+    assert type(np_vec2) == np.ndarray
+    assert np.allclose(np_vec2, np.array([1.0, 2.0], dtype=FloatType))

tests/python/vec3_test.py

@@ -154,3 +154,13 @@ def test_cross_product(self, Class: Vector3Cls) -> None:
         vec_c = vec_k.cross(vec_i)
         expected_c = Class(0.0, 1.0, 0.0)
         assert vec_c == expected_c
+
+
+@pytest.mark.parametrize(
+    "Vec3,FloatType", [(m3d.Vector3f, np.float32), (m3d.Vector3d, np.float64)]
+)
+def test_convert_to_numpy(Vec3: Vector3Cls, FloatType: type) -> None:
+    vec3 = Vec3(1.0, 2.0, 3.0)
+    np_vec3 = vec3.numpy()
+    assert type(np_vec3) == np.ndarray
+    assert np.allclose(np_vec3, np.array([1.0, 2.0, 3.0], dtype=FloatType))

tests/python/vec4_test.py

@@ -180,3 +180,13 @@ def test_dot_product(self, Class: Vector4Cls) -> None:
         vec_a = Class(3.0, 5.0, 7.0, 11.0)
         vec_b = Class(13.0, 17.0, 19.0, 23.0)
         assert np.abs(vec_a.dot(vec_b) - 510.0) < 1e-5
+
+
+@pytest.mark.parametrize(
+    "Vec4,FloatType", [(m3d.Vector4f, np.float32), (m3d.Vector4d, np.float64)]
+)
+def test_convert_to_numpy(Vec4: Vector4Cls, FloatType: type) -> None:
+    vec4 = Vec4(1.0, 2.0, 3.0, 4.0)
+    np_vec4 = vec4.numpy()
+    assert type(np_vec4) == np.ndarray
+    assert np.allclose(np_vec4, np.array([1.0, 2.0, 3.0, 4.0], dtype=FloatType))