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| /* | |
| tests/eigen.cpp -- automatic conversion of Eigen types | |
| Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch> | |
| All rights reserved. Use of this source code is governed by a | |
| BSD-style license that can be found in the LICENSE file. | |
| */ | |
| using MatrixXdR = Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>; | |
| // Sets/resets a testing reference matrix to have values of 10*r + c, where r and c are the | |
| // (1-based) row/column number. | |
| template <typename M> | |
| void reset_ref(M &x) { | |
| for (int i = 0; i < x.rows(); i++) { | |
| for (int j = 0; j < x.cols(); j++) { | |
| x(i, j) = 11 + 10 * i + j; | |
| } | |
| } | |
| } | |
| // Returns a static, column-major matrix | |
| Eigen::MatrixXd &get_cm() { | |
| static Eigen::MatrixXd *x; | |
| if (!x) { | |
| x = new Eigen::MatrixXd(3, 3); | |
| reset_ref(*x); | |
| } | |
| return *x; | |
| } | |
| // Likewise, but row-major | |
| MatrixXdR &get_rm() { | |
| static MatrixXdR *x; | |
| if (!x) { | |
| x = new MatrixXdR(3, 3); | |
| reset_ref(*x); | |
| } | |
| return *x; | |
| } | |
| // Resets the values of the static matrices returned by get_cm()/get_rm() | |
| void reset_refs() { | |
| reset_ref(get_cm()); | |
| reset_ref(get_rm()); | |
| } | |
| // Returns element 2,1 from a matrix (used to test copy/nocopy) | |
| double get_elem(const Eigen::Ref<const Eigen::MatrixXd> &m) { return m(2, 1); }; | |
| // Returns a matrix with 10*r + 100*c added to each matrix element (to help test that the matrix | |
| // reference is referencing rows/columns correctly). | |
| template <typename MatrixArgType> | |
| Eigen::MatrixXd adjust_matrix(MatrixArgType m) { | |
| Eigen::MatrixXd ret(m); | |
| for (int c = 0; c < m.cols(); c++) { | |
| for (int r = 0; r < m.rows(); r++) { | |
| ret(r, c) += 10 * r + 100 * c; // NOLINT(clang-analyzer-core.uninitialized.Assign) | |
| } | |
| } | |
| return ret; | |
| } | |
| struct CustomOperatorNew { | |
| CustomOperatorNew() = default; | |
| Eigen::Matrix4d a = Eigen::Matrix4d::Zero(); | |
| Eigen::Matrix4d b = Eigen::Matrix4d::Identity(); | |
| EIGEN_MAKE_ALIGNED_OPERATOR_NEW; | |
| }; | |
| TEST_SUBMODULE(eigen, m) { | |
| using FixedMatrixR = Eigen::Matrix<float, 5, 6, Eigen::RowMajor>; | |
| using FixedMatrixC = Eigen::Matrix<float, 5, 6>; | |
| using DenseMatrixR = Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>; | |
| using DenseMatrixC = Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic>; | |
| using FourRowMatrixC = Eigen::Matrix<float, 4, Eigen::Dynamic>; | |
| using FourColMatrixC = Eigen::Matrix<float, Eigen::Dynamic, 4>; | |
| using FourRowMatrixR = Eigen::Matrix<float, 4, Eigen::Dynamic>; | |
| using FourColMatrixR = Eigen::Matrix<float, Eigen::Dynamic, 4>; | |
| using SparseMatrixR = Eigen::SparseMatrix<float, Eigen::RowMajor>; | |
| using SparseMatrixC = Eigen::SparseMatrix<float>; | |
| // various tests | |
| m.def("double_col", [](const Eigen::VectorXf &x) -> Eigen::VectorXf { return 2.0f * x; }); | |
| m.def("double_row", | |
| [](const Eigen::RowVectorXf &x) -> Eigen::RowVectorXf { return 2.0f * x; }); | |
| m.def("double_complex", | |
| [](const Eigen::VectorXcf &x) -> Eigen::VectorXcf { return 2.0f * x; }); | |
| m.def("double_threec", [](py::EigenDRef<Eigen::Vector3f> x) { x *= 2; }); | |
| m.def("double_threer", [](py::EigenDRef<Eigen::RowVector3f> x) { x *= 2; }); | |
| m.def("double_mat_cm", [](const Eigen::MatrixXf &x) -> Eigen::MatrixXf { return 2.0f * x; }); | |
| m.def("double_mat_rm", [](const DenseMatrixR &x) -> DenseMatrixR { return 2.0f * x; }); | |
| // test_eigen_ref_to_python | |
| // Different ways of passing via Eigen::Ref; the first and second are the Eigen-recommended | |
| m.def("cholesky1", | |
| [](const Eigen::Ref<MatrixXdR> &x) -> Eigen::MatrixXd { return x.llt().matrixL(); }); | |
| m.def("cholesky2", [](const Eigen::Ref<const MatrixXdR> &x) -> Eigen::MatrixXd { | |
| return x.llt().matrixL(); | |
| }); | |
| m.def("cholesky3", | |
| [](const Eigen::Ref<MatrixXdR> &x) -> Eigen::MatrixXd { return x.llt().matrixL(); }); | |
| m.def("cholesky4", [](const Eigen::Ref<const MatrixXdR> &x) -> Eigen::MatrixXd { | |
| return x.llt().matrixL(); | |
| }); | |
| // test_eigen_ref_mutators | |
| // Mutators: these add some value to the given element using Eigen, but Eigen should be mapping | |
| // into the numpy array data and so the result should show up there. There are three versions: | |
| // one that works on a contiguous-row matrix (numpy's default), one for a contiguous-column | |
| // matrix, and one for any matrix. | |
| auto add_rm = [](Eigen::Ref<MatrixXdR> x, int r, int c, double v) { x(r, c) += v; }; | |
| auto add_cm = [](Eigen::Ref<Eigen::MatrixXd> x, int r, int c, double v) { x(r, c) += v; }; | |
| // Mutators (Eigen maps into numpy variables): | |
| m.def("add_rm", add_rm); // Only takes row-contiguous | |
| m.def("add_cm", add_cm); // Only takes column-contiguous | |
| // Overloaded versions that will accept either row or column contiguous: | |
| m.def("add1", add_rm); | |
| m.def("add1", add_cm); | |
| m.def("add2", add_cm); | |
| m.def("add2", add_rm); | |
| // This one accepts a matrix of any stride: | |
| m.def("add_any", | |
| [](py::EigenDRef<Eigen::MatrixXd> x, int r, int c, double v) { x(r, c) += v; }); | |
| // Return mutable references (numpy maps into eigen variables) | |
| m.def("get_cm_ref", []() { return Eigen::Ref<Eigen::MatrixXd>(get_cm()); }); | |
| m.def("get_rm_ref", []() { return Eigen::Ref<MatrixXdR>(get_rm()); }); | |
| // The same references, but non-mutable (numpy maps into eigen variables, but is !writeable) | |
| m.def("get_cm_const_ref", []() { return Eigen::Ref<const Eigen::MatrixXd>(get_cm()); }); | |
| m.def("get_rm_const_ref", []() { return Eigen::Ref<const MatrixXdR>(get_rm()); }); | |
| m.def("reset_refs", reset_refs); // Restores get_{cm,rm}_ref to original values | |
| // Increments and returns ref to (same) matrix | |
| m.def( | |
| "incr_matrix", | |
| [](Eigen::Ref<Eigen::MatrixXd> m, double v) { | |
| m += Eigen::MatrixXd::Constant(m.rows(), m.cols(), v); | |
| return m; | |
| }, | |
| py::return_value_policy::reference); | |
| // Same, but accepts a matrix of any strides | |
| m.def( | |
| "incr_matrix_any", | |
| [](py::EigenDRef<Eigen::MatrixXd> m, double v) { | |
| m += Eigen::MatrixXd::Constant(m.rows(), m.cols(), v); | |
| return m; | |
| }, | |
| py::return_value_policy::reference); | |
| // Returns an eigen slice of even rows | |
| m.def( | |
| "even_rows", | |
| [](py::EigenDRef<Eigen::MatrixXd> m) { | |
| return py::EigenDMap<Eigen::MatrixXd>( | |
| m.data(), | |
| (m.rows() + 1) / 2, | |
| m.cols(), | |
| py::EigenDStride(m.outerStride(), 2 * m.innerStride())); | |
| }, | |
| py::return_value_policy::reference); | |
| // Returns an eigen slice of even columns | |
| m.def( | |
| "even_cols", | |
| [](py::EigenDRef<Eigen::MatrixXd> m) { | |
| return py::EigenDMap<Eigen::MatrixXd>( | |
| m.data(), | |
| m.rows(), | |
| (m.cols() + 1) / 2, | |
| py::EigenDStride(2 * m.outerStride(), m.innerStride())); | |
| }, | |
| py::return_value_policy::reference); | |
| // Returns diagonals: a vector-like object with an inner stride != 1 | |
| m.def("diagonal", [](const Eigen::Ref<const Eigen::MatrixXd> &x) { return x.diagonal(); }); | |
| m.def("diagonal_1", | |
| [](const Eigen::Ref<const Eigen::MatrixXd> &x) { return x.diagonal<1>(); }); | |
| m.def("diagonal_n", | |
| [](const Eigen::Ref<const Eigen::MatrixXd> &x, int index) { return x.diagonal(index); }); | |
| // Return a block of a matrix (gives non-standard strides) | |
| m.def("block", | |
| [m](const py::object &x_obj, | |
| int start_row, | |
| int start_col, | |
| int block_rows, | |
| int block_cols) { | |
| return m.attr("_block")(x_obj, x_obj, start_row, start_col, block_rows, block_cols); | |
| }); | |
| m.def( | |
| "_block", | |
| [](const py::object &x_obj, | |
| const Eigen::Ref<const Eigen::MatrixXd> &x, | |
| int start_row, | |
| int start_col, | |
| int block_rows, | |
| int block_cols) { | |
| // See PR #4217 for background. This test is a bit over the top, but might be useful | |
| // as a concrete example to point to when explaining the dangling reference trap. | |
| auto i0 = py::make_tuple(0, 0); | |
| auto x0_orig = x_obj[*i0].cast<double>(); | |
| if (x(0, 0) != x0_orig) { | |
| throw std::runtime_error( | |
| "Something in the type_caster for Eigen::Ref is terribly wrong."); | |
| } | |
| double x0_mod = x0_orig + 1; | |
| x_obj[*i0] = x0_mod; | |
| auto copy_detected = (x(0, 0) != x0_mod); | |
| x_obj[*i0] = x0_orig; | |
| if (copy_detected) { | |
| throw std::runtime_error("type_caster for Eigen::Ref made a copy."); | |
| } | |
| return x.block(start_row, start_col, block_rows, block_cols); | |
| }, | |
| py::keep_alive<0, 1>()); | |
| // test_eigen_return_references, test_eigen_keepalive | |
| // return value referencing/copying tests: | |
| class ReturnTester { | |
| Eigen::MatrixXd mat = create(); | |
| public: | |
| ReturnTester() { print_created(this); } | |
| ~ReturnTester() { print_destroyed(this); } | |
| static Eigen::MatrixXd create() { return Eigen::MatrixXd::Ones(10, 10); } | |
| // NOLINTNEXTLINE(readability-const-return-type) | |
| static const Eigen::MatrixXd createConst() { return Eigen::MatrixXd::Ones(10, 10); } | |
| Eigen::MatrixXd &get() { return mat; } | |
| Eigen::MatrixXd *getPtr() { return &mat; } | |
| const Eigen::MatrixXd &view() { return mat; } | |
| const Eigen::MatrixXd *viewPtr() { return &mat; } | |
| Eigen::Ref<Eigen::MatrixXd> ref() { return mat; } | |
| Eigen::Ref<const Eigen::MatrixXd> refConst() { return mat; } | |
| Eigen::Block<Eigen::MatrixXd> block(int r, int c, int nrow, int ncol) { | |
| return mat.block(r, c, nrow, ncol); | |
| } | |
| Eigen::Block<const Eigen::MatrixXd> blockConst(int r, int c, int nrow, int ncol) const { | |
| return mat.block(r, c, nrow, ncol); | |
| } | |
| py::EigenDMap<Eigen::Matrix2d> corners() { | |
| return py::EigenDMap<Eigen::Matrix2d>( | |
| mat.data(), | |
| py::EigenDStride(mat.outerStride() * (mat.outerSize() - 1), | |
| mat.innerStride() * (mat.innerSize() - 1))); | |
| } | |
| py::EigenDMap<const Eigen::Matrix2d> cornersConst() const { | |
| return py::EigenDMap<const Eigen::Matrix2d>( | |
| mat.data(), | |
| py::EigenDStride(mat.outerStride() * (mat.outerSize() - 1), | |
| mat.innerStride() * (mat.innerSize() - 1))); | |
| } | |
| }; | |
| using rvp = py::return_value_policy; | |
| py::class_<ReturnTester>(m, "ReturnTester") | |
| .def(py::init<>()) | |
| .def_static("create", &ReturnTester::create) | |
| .def_static("create_const", &ReturnTester::createConst) | |
| .def("get", &ReturnTester::get, rvp::reference_internal) | |
| .def("get_ptr", &ReturnTester::getPtr, rvp::reference_internal) | |
| .def("view", &ReturnTester::view, rvp::reference_internal) | |
| .def("view_ptr", &ReturnTester::view, rvp::reference_internal) | |
| .def("copy_get", &ReturnTester::get) // Default rvp: copy | |
| .def("copy_view", &ReturnTester::view) // " | |
| .def("ref", &ReturnTester::ref) // Default for Ref is to reference | |
| .def("ref_const", &ReturnTester::refConst) // Likewise, but const | |
| .def("ref_safe", &ReturnTester::ref, rvp::reference_internal) | |
| .def("ref_const_safe", &ReturnTester::refConst, rvp::reference_internal) | |
| .def("copy_ref", &ReturnTester::ref, rvp::copy) | |
| .def("copy_ref_const", &ReturnTester::refConst, rvp::copy) | |
| .def("block", &ReturnTester::block) | |
| .def("block_safe", &ReturnTester::block, rvp::reference_internal) | |
| .def("block_const", &ReturnTester::blockConst, rvp::reference_internal) | |
| .def("copy_block", &ReturnTester::block, rvp::copy) | |
| .def("corners", &ReturnTester::corners, rvp::reference_internal) | |
| .def("corners_const", &ReturnTester::cornersConst, rvp::reference_internal); | |
| // test_special_matrix_objects | |
| // Returns a DiagonalMatrix with diagonal (1,2,3,...) | |
| m.def("incr_diag", [](int k) { | |
| Eigen::DiagonalMatrix<int, Eigen::Dynamic> m(k); | |
| for (int i = 0; i < k; i++) { | |
| m.diagonal()[i] = i + 1; | |
| } | |
| return m; | |
| }); | |
| // Returns a SelfAdjointView referencing the lower triangle of m | |
| m.def("symmetric_lower", | |
| [](const Eigen::MatrixXi &m) { return m.selfadjointView<Eigen::Lower>(); }); | |
| // Returns a SelfAdjointView referencing the lower triangle of m | |
| m.def("symmetric_upper", | |
| [](const Eigen::MatrixXi &m) { return m.selfadjointView<Eigen::Upper>(); }); | |
| // Test matrix for various functions below. | |
| Eigen::MatrixXf mat(5, 6); | |
| mat << 0, 3, 0, 0, 0, 11, 22, 0, 0, 0, 17, 11, 7, 5, 0, 1, 0, 11, 0, 0, 0, 0, 0, 11, 0, 0, 14, | |
| 0, 8, 11; | |
| // test_fixed, and various other tests | |
| m.def("fixed_r", [mat]() -> FixedMatrixR { return FixedMatrixR(mat); }); | |
| // Our Eigen does a hack which respects constness through the numpy writeable flag. | |
| // Therefore, the const return actually affects this type despite being an rvalue. | |
| // NOLINTNEXTLINE(readability-const-return-type) | |
| m.def("fixed_r_const", [mat]() -> const FixedMatrixR { return FixedMatrixR(mat); }); | |
| m.def("fixed_c", [mat]() -> FixedMatrixC { return FixedMatrixC(mat); }); | |
| m.def("fixed_copy_r", [](const FixedMatrixR &m) -> FixedMatrixR { return m; }); | |
| m.def("fixed_copy_c", [](const FixedMatrixC &m) -> FixedMatrixC { return m; }); | |
| // test_mutator_descriptors | |
| m.def("fixed_mutator_r", [](const Eigen::Ref<FixedMatrixR> &) {}); | |
| m.def("fixed_mutator_c", [](const Eigen::Ref<FixedMatrixC> &) {}); | |
| m.def("fixed_mutator_a", [](const py::EigenDRef<FixedMatrixC> &) {}); | |
| // test_dense | |
| m.def("dense_r", [mat]() -> DenseMatrixR { return DenseMatrixR(mat); }); | |
| m.def("dense_c", [mat]() -> DenseMatrixC { return DenseMatrixC(mat); }); | |
| m.def("dense_copy_r", [](const DenseMatrixR &m) -> DenseMatrixR { return m; }); | |
| m.def("dense_copy_c", [](const DenseMatrixC &m) -> DenseMatrixC { return m; }); | |
| // test_sparse, test_sparse_signature | |
| m.def("sparse_r", [mat]() -> SparseMatrixR { | |
| // NOLINTNEXTLINE(clang-analyzer-core.uninitialized.UndefReturn) | |
| return Eigen::SparseView<Eigen::MatrixXf>(mat); | |
| }); | |
| m.def("sparse_c", | |
| [mat]() -> SparseMatrixC { return Eigen::SparseView<Eigen::MatrixXf>(mat); }); | |
| m.def("sparse_copy_r", [](const SparseMatrixR &m) -> SparseMatrixR { return m; }); | |
| m.def("sparse_copy_c", [](const SparseMatrixC &m) -> SparseMatrixC { return m; }); | |
| // test_partially_fixed | |
| m.def("partial_copy_four_rm_r", [](const FourRowMatrixR &m) -> FourRowMatrixR { return m; }); | |
| m.def("partial_copy_four_rm_c", [](const FourColMatrixR &m) -> FourColMatrixR { return m; }); | |
| m.def("partial_copy_four_cm_r", [](const FourRowMatrixC &m) -> FourRowMatrixC { return m; }); | |
| m.def("partial_copy_four_cm_c", [](const FourColMatrixC &m) -> FourColMatrixC { return m; }); | |
| // test_cpp_casting | |
| // Test that we can cast a numpy object to a Eigen::MatrixXd explicitly | |
| m.def("cpp_copy", [](py::handle m) { return m.cast<Eigen::MatrixXd>()(1, 0); }); | |
| m.def("cpp_ref_c", [](py::handle m) { return m.cast<Eigen::Ref<Eigen::MatrixXd>>()(1, 0); }); | |
| m.def("cpp_ref_r", [](py::handle m) { return m.cast<Eigen::Ref<MatrixXdR>>()(1, 0); }); | |
| m.def("cpp_ref_any", | |
| [](py::handle m) { return m.cast<py::EigenDRef<Eigen::MatrixXd>>()(1, 0); }); | |
| // [workaround(intel)] ICC 20/21 breaks with py::arg().stuff, using py::arg{}.stuff works. | |
| // test_nocopy_wrapper | |
| // Test that we can prevent copying into an argument that would normally copy: First a version | |
| // that would allow copying (if types or strides don't match) for comparison: | |
| m.def("get_elem", &get_elem); | |
| // Now this alternative that calls the tells pybind to fail rather than copy: | |
| m.def( | |
| "get_elem_nocopy", | |
| [](const Eigen::Ref<const Eigen::MatrixXd> &m) -> double { return get_elem(m); }, | |
| py::arg{}.noconvert()); | |
| // Also test a row-major-only no-copy const ref: | |
| m.def( | |
| "get_elem_rm_nocopy", | |
| [](Eigen::Ref<const Eigen::Matrix<long, -1, -1, Eigen::RowMajor>> &m) -> long { | |
| return m(2, 1); | |
| }, | |
| py::arg{}.noconvert()); | |
| // test_issue738, test_zero_length | |
| // Issue #738: 1×N or N×1 2D matrices were neither accepted nor properly copied with an | |
| // incompatible stride value on the length-1 dimension--but that should be allowed (without | |
| // requiring a copy!) because the stride value can be safely ignored on a size-1 dimension. | |
| // Similarly, 0×N or N×0 matrices were not accepted--again, these should be allowed since | |
| // they contain no data. This particularly affects numpy ≥ 1.23, which sets the strides to | |
| // 0 if any dimension size is 0. | |
| m.def("iss738_f1", | |
| &adjust_matrix<const Eigen::Ref<const Eigen::MatrixXd> &>, | |
| py::arg{}.noconvert()); | |
| m.def("iss738_f2", | |
| &adjust_matrix<const Eigen::Ref<const Eigen::Matrix<double, -1, -1, Eigen::RowMajor>> &>, | |
| py::arg{}.noconvert()); | |
| // test_issue1105 | |
| // Issue #1105: when converting from a numpy two-dimensional (Nx1) or (1xN) value into a dense | |
| // eigen Vector or RowVector, the argument would fail to load because the numpy copy would | |
| // fail: numpy won't broadcast a Nx1 into a 1-dimensional vector. | |
| m.def("iss1105_col", [](const Eigen::VectorXd &) { return true; }); | |
| m.def("iss1105_row", [](const Eigen::RowVectorXd &) { return true; }); | |
| // test_named_arguments | |
| // Make sure named arguments are working properly: | |
| m.def( | |
| "matrix_multiply", | |
| [](const py::EigenDRef<const Eigen::MatrixXd> &A, | |
| const py::EigenDRef<const Eigen::MatrixXd> &B) -> Eigen::MatrixXd { | |
| if (A.cols() != B.rows()) { | |
| throw std::domain_error("Nonconformable matrices!"); | |
| } | |
| return A * B; | |
| }, | |
| py::arg("A"), | |
| py::arg("B")); | |
| // test_custom_operator_new | |
| py::class_<CustomOperatorNew>(m, "CustomOperatorNew") | |
| .def(py::init<>()) | |
| .def_readonly("a", &CustomOperatorNew::a) | |
| .def_readonly("b", &CustomOperatorNew::b); | |
| // test_eigen_ref_life_support | |
| // In case of a failure (the caster's temp array does not live long enough), creating | |
| // a new array (np.ones(10)) increases the chances that the temp array will be garbage | |
| // collected and/or that its memory will be overridden with different values. | |
| m.def("get_elem_direct", [](const Eigen::Ref<const Eigen::VectorXd> &v) { | |
| py::module_::import("numpy").attr("ones")(10); | |
| return v(5); | |
| }); | |
| m.def("get_elem_indirect", [](std::vector<Eigen::Ref<const Eigen::VectorXd>> v) { | |
| py::module_::import("numpy").attr("ones")(10); | |
| return v[0](5); | |
| }); | |
| } | |