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3793c7ed9a
In the latest MSVC in C++17 mode including Eigen causes warnings:
warning C4996: 'std::unary_negate<_Fn>': warning STL4008: std::not1(),
std::not2(), std::unary_negate, and std::binary_negate are deprecated in
C++17. They are superseded by std::not_fn(). You can define
_SILENCE_CXX17_NEGATORS_DEPRECATION_WARNING or
_SILENCE_ALL_CXX17_DEPRECATION_WARNINGS to acknowledge that you have
received this warning.
This disables 4996 for the Eigen includes.
Catch generates a similar warning for std::uncaught_exception, so
disable the warning there, too.
In both cases this is temporary; we can (and should) remove the warnings
disabling once new upstream versions of Eigen and Catch are available
that address the warning. (The Catch one, in particular, looks to be
fixed in upstream master, so will probably be fixed in the next (2.0.2)
release).
330 lines
16 KiB
C++
330 lines
16 KiB
C++
/*
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tests/eigen.cpp -- automatic conversion of Eigen types
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Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
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All rights reserved. Use of this source code is governed by a
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BSD-style license that can be found in the LICENSE file.
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*/
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#include "pybind11_tests.h"
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#include "constructor_stats.h"
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#include <pybind11/eigen.h>
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#include <pybind11/stl.h>
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#if defined(_MSC_VER)
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# pragma warning(disable: 4996) // C4996: std::unary_negation is deprecated
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#endif
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#include <Eigen/Cholesky>
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using MatrixXdR = Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>;
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// Sets/resets a testing reference matrix to have values of 10*r + c, where r and c are the
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// (1-based) row/column number.
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template <typename M> void reset_ref(M &x) {
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for (int i = 0; i < x.rows(); i++) for (int j = 0; j < x.cols(); j++)
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x(i, j) = 11 + 10*i + j;
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}
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// Returns a static, column-major matrix
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Eigen::MatrixXd &get_cm() {
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static Eigen::MatrixXd *x;
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if (!x) {
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x = new Eigen::MatrixXd(3, 3);
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reset_ref(*x);
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}
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return *x;
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}
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// Likewise, but row-major
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MatrixXdR &get_rm() {
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static MatrixXdR *x;
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if (!x) {
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x = new MatrixXdR(3, 3);
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reset_ref(*x);
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}
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return *x;
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}
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// Resets the values of the static matrices returned by get_cm()/get_rm()
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void reset_refs() {
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reset_ref(get_cm());
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reset_ref(get_rm());
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}
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// Returns element 2,1 from a matrix (used to test copy/nocopy)
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double get_elem(Eigen::Ref<const Eigen::MatrixXd> m) { return m(2, 1); };
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// Returns a matrix with 10*r + 100*c added to each matrix element (to help test that the matrix
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// reference is referencing rows/columns correctly).
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template <typename MatrixArgType> Eigen::MatrixXd adjust_matrix(MatrixArgType m) {
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Eigen::MatrixXd ret(m);
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for (int c = 0; c < m.cols(); c++) for (int r = 0; r < m.rows(); r++)
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ret(r, c) += 10*r + 100*c;
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return ret;
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}
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struct CustomOperatorNew {
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CustomOperatorNew() = default;
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Eigen::Matrix4d a = Eigen::Matrix4d::Zero();
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Eigen::Matrix4d b = Eigen::Matrix4d::Identity();
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EIGEN_MAKE_ALIGNED_OPERATOR_NEW;
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};
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TEST_SUBMODULE(eigen, m) {
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using FixedMatrixR = Eigen::Matrix<float, 5, 6, Eigen::RowMajor>;
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using FixedMatrixC = Eigen::Matrix<float, 5, 6>;
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using DenseMatrixR = Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>;
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using DenseMatrixC = Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic>;
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using FourRowMatrixC = Eigen::Matrix<float, 4, Eigen::Dynamic>;
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using FourColMatrixC = Eigen::Matrix<float, Eigen::Dynamic, 4>;
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using FourRowMatrixR = Eigen::Matrix<float, 4, Eigen::Dynamic>;
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using FourColMatrixR = Eigen::Matrix<float, Eigen::Dynamic, 4>;
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using SparseMatrixR = Eigen::SparseMatrix<float, Eigen::RowMajor>;
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using SparseMatrixC = Eigen::SparseMatrix<float>;
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m.attr("have_eigen") = true;
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// various tests
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m.def("double_col", [](const Eigen::VectorXf &x) -> Eigen::VectorXf { return 2.0f * x; });
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m.def("double_row", [](const Eigen::RowVectorXf &x) -> Eigen::RowVectorXf { return 2.0f * x; });
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m.def("double_complex", [](const Eigen::VectorXcf &x) -> Eigen::VectorXcf { return 2.0f * x; });
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m.def("double_threec", [](py::EigenDRef<Eigen::Vector3f> x) { x *= 2; });
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m.def("double_threer", [](py::EigenDRef<Eigen::RowVector3f> x) { x *= 2; });
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m.def("double_mat_cm", [](Eigen::MatrixXf x) -> Eigen::MatrixXf { return 2.0f * x; });
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m.def("double_mat_rm", [](DenseMatrixR x) -> DenseMatrixR { return 2.0f * x; });
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// test_eigen_ref_to_python
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// Different ways of passing via Eigen::Ref; the first and second are the Eigen-recommended
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m.def("cholesky1", [](Eigen::Ref<MatrixXdR> x) -> Eigen::MatrixXd { return x.llt().matrixL(); });
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m.def("cholesky2", [](const Eigen::Ref<const MatrixXdR> &x) -> Eigen::MatrixXd { return x.llt().matrixL(); });
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m.def("cholesky3", [](const Eigen::Ref<MatrixXdR> &x) -> Eigen::MatrixXd { return x.llt().matrixL(); });
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m.def("cholesky4", [](Eigen::Ref<const MatrixXdR> x) -> Eigen::MatrixXd { return x.llt().matrixL(); });
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// test_eigen_ref_mutators
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// Mutators: these add some value to the given element using Eigen, but Eigen should be mapping into
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// the numpy array data and so the result should show up there. There are three versions: one that
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// works on a contiguous-row matrix (numpy's default), one for a contiguous-column matrix, and one
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// for any matrix.
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auto add_rm = [](Eigen::Ref<MatrixXdR> x, int r, int c, double v) { x(r,c) += v; };
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auto add_cm = [](Eigen::Ref<Eigen::MatrixXd> x, int r, int c, double v) { x(r,c) += v; };
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// Mutators (Eigen maps into numpy variables):
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m.def("add_rm", add_rm); // Only takes row-contiguous
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m.def("add_cm", add_cm); // Only takes column-contiguous
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// Overloaded versions that will accept either row or column contiguous:
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m.def("add1", add_rm);
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m.def("add1", add_cm);
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m.def("add2", add_cm);
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m.def("add2", add_rm);
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// This one accepts a matrix of any stride:
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m.def("add_any", [](py::EigenDRef<Eigen::MatrixXd> x, int r, int c, double v) { x(r,c) += v; });
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// Return mutable references (numpy maps into eigen varibles)
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m.def("get_cm_ref", []() { return Eigen::Ref<Eigen::MatrixXd>(get_cm()); });
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m.def("get_rm_ref", []() { return Eigen::Ref<MatrixXdR>(get_rm()); });
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// The same references, but non-mutable (numpy maps into eigen variables, but is !writeable)
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m.def("get_cm_const_ref", []() { return Eigen::Ref<const Eigen::MatrixXd>(get_cm()); });
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m.def("get_rm_const_ref", []() { return Eigen::Ref<const MatrixXdR>(get_rm()); });
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m.def("reset_refs", reset_refs); // Restores get_{cm,rm}_ref to original values
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// Increments and returns ref to (same) matrix
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m.def("incr_matrix", [](Eigen::Ref<Eigen::MatrixXd> m, double v) {
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m += Eigen::MatrixXd::Constant(m.rows(), m.cols(), v);
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return m;
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}, py::return_value_policy::reference);
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// Same, but accepts a matrix of any strides
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m.def("incr_matrix_any", [](py::EigenDRef<Eigen::MatrixXd> m, double v) {
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m += Eigen::MatrixXd::Constant(m.rows(), m.cols(), v);
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return m;
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}, py::return_value_policy::reference);
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// Returns an eigen slice of even rows
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m.def("even_rows", [](py::EigenDRef<Eigen::MatrixXd> m) {
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return py::EigenDMap<Eigen::MatrixXd>(
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m.data(), (m.rows() + 1) / 2, m.cols(),
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py::EigenDStride(m.outerStride(), 2 * m.innerStride()));
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}, py::return_value_policy::reference);
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// Returns an eigen slice of even columns
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m.def("even_cols", [](py::EigenDRef<Eigen::MatrixXd> m) {
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return py::EigenDMap<Eigen::MatrixXd>(
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m.data(), m.rows(), (m.cols() + 1) / 2,
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py::EigenDStride(2 * m.outerStride(), m.innerStride()));
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}, py::return_value_policy::reference);
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// Returns diagonals: a vector-like object with an inner stride != 1
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m.def("diagonal", [](const Eigen::Ref<const Eigen::MatrixXd> &x) { return x.diagonal(); });
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m.def("diagonal_1", [](const Eigen::Ref<const Eigen::MatrixXd> &x) { return x.diagonal<1>(); });
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m.def("diagonal_n", [](const Eigen::Ref<const Eigen::MatrixXd> &x, int index) { return x.diagonal(index); });
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// Return a block of a matrix (gives non-standard strides)
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m.def("block", [](const Eigen::Ref<const Eigen::MatrixXd> &x, int start_row, int start_col, int block_rows, int block_cols) {
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return x.block(start_row, start_col, block_rows, block_cols);
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});
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// test_eigen_return_references, test_eigen_keepalive
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// return value referencing/copying tests:
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class ReturnTester {
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Eigen::MatrixXd mat = create();
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public:
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ReturnTester() { print_created(this); }
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~ReturnTester() { print_destroyed(this); }
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static Eigen::MatrixXd create() { return Eigen::MatrixXd::Ones(10, 10); }
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static const Eigen::MatrixXd createConst() { return Eigen::MatrixXd::Ones(10, 10); }
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Eigen::MatrixXd &get() { return mat; }
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Eigen::MatrixXd *getPtr() { return &mat; }
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const Eigen::MatrixXd &view() { return mat; }
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const Eigen::MatrixXd *viewPtr() { return &mat; }
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Eigen::Ref<Eigen::MatrixXd> ref() { return mat; }
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Eigen::Ref<const Eigen::MatrixXd> refConst() { return mat; }
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Eigen::Block<Eigen::MatrixXd> block(int r, int c, int nrow, int ncol) { return mat.block(r, c, nrow, ncol); }
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Eigen::Block<const Eigen::MatrixXd> blockConst(int r, int c, int nrow, int ncol) const { return mat.block(r, c, nrow, ncol); }
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py::EigenDMap<Eigen::Matrix2d> corners() { return py::EigenDMap<Eigen::Matrix2d>(mat.data(),
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py::EigenDStride(mat.outerStride() * (mat.outerSize()-1), mat.innerStride() * (mat.innerSize()-1))); }
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py::EigenDMap<const Eigen::Matrix2d> cornersConst() const { return py::EigenDMap<const Eigen::Matrix2d>(mat.data(),
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py::EigenDStride(mat.outerStride() * (mat.outerSize()-1), mat.innerStride() * (mat.innerSize()-1))); }
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};
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using rvp = py::return_value_policy;
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py::class_<ReturnTester>(m, "ReturnTester")
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.def(py::init<>())
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.def_static("create", &ReturnTester::create)
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.def_static("create_const", &ReturnTester::createConst)
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.def("get", &ReturnTester::get, rvp::reference_internal)
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.def("get_ptr", &ReturnTester::getPtr, rvp::reference_internal)
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.def("view", &ReturnTester::view, rvp::reference_internal)
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.def("view_ptr", &ReturnTester::view, rvp::reference_internal)
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.def("copy_get", &ReturnTester::get) // Default rvp: copy
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.def("copy_view", &ReturnTester::view) // "
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.def("ref", &ReturnTester::ref) // Default for Ref is to reference
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.def("ref_const", &ReturnTester::refConst) // Likewise, but const
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.def("ref_safe", &ReturnTester::ref, rvp::reference_internal)
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.def("ref_const_safe", &ReturnTester::refConst, rvp::reference_internal)
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.def("copy_ref", &ReturnTester::ref, rvp::copy)
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.def("copy_ref_const", &ReturnTester::refConst, rvp::copy)
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.def("block", &ReturnTester::block)
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.def("block_safe", &ReturnTester::block, rvp::reference_internal)
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.def("block_const", &ReturnTester::blockConst, rvp::reference_internal)
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.def("copy_block", &ReturnTester::block, rvp::copy)
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.def("corners", &ReturnTester::corners, rvp::reference_internal)
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.def("corners_const", &ReturnTester::cornersConst, rvp::reference_internal)
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;
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// test_special_matrix_objects
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// Returns a DiagonalMatrix with diagonal (1,2,3,...)
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m.def("incr_diag", [](int k) {
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Eigen::DiagonalMatrix<int, Eigen::Dynamic> m(k);
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for (int i = 0; i < k; i++) m.diagonal()[i] = i+1;
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return m;
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});
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// Returns a SelfAdjointView referencing the lower triangle of m
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m.def("symmetric_lower", [](const Eigen::MatrixXi &m) {
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return m.selfadjointView<Eigen::Lower>();
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});
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// Returns a SelfAdjointView referencing the lower triangle of m
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m.def("symmetric_upper", [](const Eigen::MatrixXi &m) {
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return m.selfadjointView<Eigen::Upper>();
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});
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// Test matrix for various functions below.
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Eigen::MatrixXf mat(5, 6);
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mat << 0, 3, 0, 0, 0, 11,
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22, 0, 0, 0, 17, 11,
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7, 5, 0, 1, 0, 11,
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0, 0, 0, 0, 0, 11,
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0, 0, 14, 0, 8, 11;
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// test_fixed, and various other tests
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m.def("fixed_r", [mat]() -> FixedMatrixR { return FixedMatrixR(mat); });
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m.def("fixed_r_const", [mat]() -> const FixedMatrixR { return FixedMatrixR(mat); });
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m.def("fixed_c", [mat]() -> FixedMatrixC { return FixedMatrixC(mat); });
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m.def("fixed_copy_r", [](const FixedMatrixR &m) -> FixedMatrixR { return m; });
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m.def("fixed_copy_c", [](const FixedMatrixC &m) -> FixedMatrixC { return m; });
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// test_mutator_descriptors
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m.def("fixed_mutator_r", [](Eigen::Ref<FixedMatrixR>) {});
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m.def("fixed_mutator_c", [](Eigen::Ref<FixedMatrixC>) {});
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m.def("fixed_mutator_a", [](py::EigenDRef<FixedMatrixC>) {});
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// test_dense
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m.def("dense_r", [mat]() -> DenseMatrixR { return DenseMatrixR(mat); });
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m.def("dense_c", [mat]() -> DenseMatrixC { return DenseMatrixC(mat); });
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m.def("dense_copy_r", [](const DenseMatrixR &m) -> DenseMatrixR { return m; });
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m.def("dense_copy_c", [](const DenseMatrixC &m) -> DenseMatrixC { return m; });
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// test_sparse, test_sparse_signature
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m.def("sparse_r", [mat]() -> SparseMatrixR { return Eigen::SparseView<Eigen::MatrixXf>(mat); });
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m.def("sparse_c", [mat]() -> SparseMatrixC { return Eigen::SparseView<Eigen::MatrixXf>(mat); });
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m.def("sparse_copy_r", [](const SparseMatrixR &m) -> SparseMatrixR { return m; });
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m.def("sparse_copy_c", [](const SparseMatrixC &m) -> SparseMatrixC { return m; });
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// test_partially_fixed
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m.def("partial_copy_four_rm_r", [](const FourRowMatrixR &m) -> FourRowMatrixR { return m; });
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m.def("partial_copy_four_rm_c", [](const FourColMatrixR &m) -> FourColMatrixR { return m; });
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m.def("partial_copy_four_cm_r", [](const FourRowMatrixC &m) -> FourRowMatrixC { return m; });
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m.def("partial_copy_four_cm_c", [](const FourColMatrixC &m) -> FourColMatrixC { return m; });
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// test_cpp_casting
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// Test that we can cast a numpy object to a Eigen::MatrixXd explicitly
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m.def("cpp_copy", [](py::handle m) { return m.cast<Eigen::MatrixXd>()(1, 0); });
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m.def("cpp_ref_c", [](py::handle m) { return m.cast<Eigen::Ref<Eigen::MatrixXd>>()(1, 0); });
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m.def("cpp_ref_r", [](py::handle m) { return m.cast<Eigen::Ref<MatrixXdR>>()(1, 0); });
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m.def("cpp_ref_any", [](py::handle m) { return m.cast<py::EigenDRef<Eigen::MatrixXd>>()(1, 0); });
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// test_nocopy_wrapper
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// Test that we can prevent copying into an argument that would normally copy: First a version
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// that would allow copying (if types or strides don't match) for comparison:
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m.def("get_elem", &get_elem);
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// Now this alternative that calls the tells pybind to fail rather than copy:
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m.def("get_elem_nocopy", [](Eigen::Ref<const Eigen::MatrixXd> m) -> double { return get_elem(m); },
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py::arg().noconvert());
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// Also test a row-major-only no-copy const ref:
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m.def("get_elem_rm_nocopy", [](Eigen::Ref<const Eigen::Matrix<long, -1, -1, Eigen::RowMajor>> &m) -> long { return m(2, 1); },
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py::arg().noconvert());
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// test_issue738
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// Issue #738: 1xN or Nx1 2D matrices were neither accepted nor properly copied with an
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// incompatible stride value on the length-1 dimension--but that should be allowed (without
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// requiring a copy!) because the stride value can be safely ignored on a size-1 dimension.
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m.def("iss738_f1", &adjust_matrix<const Eigen::Ref<const Eigen::MatrixXd> &>, py::arg().noconvert());
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m.def("iss738_f2", &adjust_matrix<const Eigen::Ref<const Eigen::Matrix<double, -1, -1, Eigen::RowMajor>> &>, py::arg().noconvert());
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// test_issue1105
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// Issue #1105: when converting from a numpy two-dimensional (Nx1) or (1xN) value into a dense
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// eigen Vector or RowVector, the argument would fail to load because the numpy copy would fail:
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// numpy won't broadcast a Nx1 into a 1-dimensional vector.
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m.def("iss1105_col", [](Eigen::VectorXd) { return true; });
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m.def("iss1105_row", [](Eigen::RowVectorXd) { return true; });
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// test_named_arguments
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// Make sure named arguments are working properly:
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m.def("matrix_multiply", [](const py::EigenDRef<const Eigen::MatrixXd> A, const py::EigenDRef<const Eigen::MatrixXd> B)
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-> Eigen::MatrixXd {
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if (A.cols() != B.rows()) throw std::domain_error("Nonconformable matrices!");
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return A * B;
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}, py::arg("A"), py::arg("B"));
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// test_custom_operator_new
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py::class_<CustomOperatorNew>(m, "CustomOperatorNew")
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.def(py::init<>())
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.def_readonly("a", &CustomOperatorNew::a)
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.def_readonly("b", &CustomOperatorNew::b);
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// test_eigen_ref_life_support
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// In case of a failure (the caster's temp array does not live long enough), creating
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// a new array (np.ones(10)) increases the chances that the temp array will be garbage
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// collected and/or that its memory will be overridden with different values.
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m.def("get_elem_direct", [](Eigen::Ref<const Eigen::VectorXd> v) {
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py::module::import("numpy").attr("ones")(10);
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return v(5);
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});
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m.def("get_elem_indirect", [](std::vector<Eigen::Ref<const Eigen::VectorXd>> v) {
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py::module::import("numpy").attr("ones")(10);
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return v[0](5);
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});
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}
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