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3f1ff3f4d1
This adds automatic casting when assigning to python types like dict, list, and attributes. Instead of: dict["key"] = py::cast(val); m.attr("foo") = py::cast(true); list.append(py::cast(42)); you can now simply write: dict["key"] = val; m.attr("foo") = true; list.append(42); Casts needing extra parameters (e.g. for a non-default rvp) still require the py::cast() call. set::add() is also supported. All usage is channeled through a SFINAE implementation which either just returns or casts. Combined non-converting handle and autocasting template methods via a helper method that either just returns (handle) or casts (C++ type).
135 lines
4.9 KiB
C++
135 lines
4.9 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 <pybind11/eigen.h>
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#include <Eigen/Cholesky>
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Eigen::VectorXf double_col(const Eigen::VectorXf& x)
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{ return 2.0f * x; }
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Eigen::RowVectorXf double_row(const Eigen::RowVectorXf& x)
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{ return 2.0f * x; }
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Eigen::MatrixXf double_mat_cm(const Eigen::MatrixXf& x)
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{ return 2.0f * x; }
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// Different ways of passing via Eigen::Ref; the first and second are the Eigen-recommended
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Eigen::MatrixXd cholesky1(Eigen::Ref<Eigen::MatrixXd> &x) { return x.llt().matrixL(); }
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Eigen::MatrixXd cholesky2(const Eigen::Ref<const Eigen::MatrixXd> &x) { return x.llt().matrixL(); }
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Eigen::MatrixXd cholesky3(const Eigen::Ref<Eigen::MatrixXd> &x) { return x.llt().matrixL(); }
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Eigen::MatrixXd cholesky4(Eigen::Ref<const Eigen::MatrixXd> &x) { return x.llt().matrixL(); }
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Eigen::MatrixXd cholesky5(Eigen::Ref<Eigen::MatrixXd> x) { return x.llt().matrixL(); }
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Eigen::MatrixXd cholesky6(Eigen::Ref<const Eigen::MatrixXd> x) { return x.llt().matrixL(); }
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typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> MatrixXfRowMajor;
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MatrixXfRowMajor double_mat_rm(const MatrixXfRowMajor& x)
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{ return 2.0f * x; }
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test_initializer eigen([](py::module &m) {
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typedef Eigen::Matrix<float, 5, 6, Eigen::RowMajor> FixedMatrixR;
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typedef Eigen::Matrix<float, 5, 6> FixedMatrixC;
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typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> DenseMatrixR;
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typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic> DenseMatrixC;
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typedef Eigen::SparseMatrix<float, Eigen::RowMajor> SparseMatrixR;
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typedef Eigen::SparseMatrix<float> SparseMatrixC;
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m.attr("have_eigen") = true;
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// Non-symmetric matrix with zero elements
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Eigen::MatrixXf mat(5, 6);
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mat << 0, 3, 0, 0, 0, 11, 22, 0, 0, 0, 17, 11, 7, 5, 0, 1, 0, 11, 0,
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0, 0, 0, 0, 11, 0, 0, 14, 0, 8, 11;
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m.def("double_col", &double_col);
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m.def("double_row", &double_row);
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m.def("double_mat_cm", &double_mat_cm);
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m.def("double_mat_rm", &double_mat_rm);
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m.def("cholesky1", &cholesky1);
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m.def("cholesky2", &cholesky2);
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m.def("cholesky3", &cholesky3);
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m.def("cholesky4", &cholesky4);
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m.def("cholesky5", &cholesky5);
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m.def("cholesky6", &cholesky6);
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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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// 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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m.def("fixed_r", [mat]() -> FixedMatrixR {
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return FixedMatrixR(mat);
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});
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m.def("fixed_c", [mat]() -> FixedMatrixC {
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return FixedMatrixC(mat);
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});
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m.def("fixed_passthrough_r", [](const FixedMatrixR &m) -> FixedMatrixR {
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return m;
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});
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m.def("fixed_passthrough_c", [](const FixedMatrixC &m) -> FixedMatrixC {
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return m;
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});
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m.def("dense_r", [mat]() -> DenseMatrixR {
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return DenseMatrixR(mat);
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});
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m.def("dense_c", [mat]() -> DenseMatrixC {
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return DenseMatrixC(mat);
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});
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m.def("dense_passthrough_r", [](const DenseMatrixR &m) -> DenseMatrixR {
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return m;
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});
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m.def("dense_passthrough_c", [](const DenseMatrixC &m) -> DenseMatrixC {
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return m;
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});
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m.def("sparse_r", [mat]() -> SparseMatrixR {
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return Eigen::SparseView<Eigen::MatrixXf>(mat);
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});
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m.def("sparse_c", [mat]() -> SparseMatrixC {
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return Eigen::SparseView<Eigen::MatrixXf>(mat);
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});
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m.def("sparse_passthrough_r", [](const SparseMatrixR &m) -> SparseMatrixR {
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return m;
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});
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m.def("sparse_passthrough_c", [](const SparseMatrixC &m) -> SparseMatrixC {
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return m;
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});
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});
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