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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
// This C++ file compiles to binary code that can be linked to by your C program,
// thanks to the extern "C" syntax used in the declarations in binary_library.h.
#include "binary_library.h"
#include <Eigen/Core>
using namespace Eigen;
/************************* pointer conversion methods **********************************************/
////// class MatrixXd //////
inline MatrixXd &c_to_eigen(C_MatrixXd *ptr) { return *reinterpret_cast<MatrixXd *>(ptr); }
inline const MatrixXd &c_to_eigen(const C_MatrixXd *ptr) { return *reinterpret_cast<const MatrixXd *>(ptr); }
inline C_MatrixXd *eigen_to_c(MatrixXd &ref) { return reinterpret_cast<C_MatrixXd *>(&ref); }
inline const C_MatrixXd *eigen_to_c(const MatrixXd &ref) { return reinterpret_cast<const C_MatrixXd *>(&ref); }
////// class Map<MatrixXd> //////
inline Map<MatrixXd> &c_to_eigen(C_Map_MatrixXd *ptr) { return *reinterpret_cast<Map<MatrixXd> *>(ptr); }
inline const Map<MatrixXd> &c_to_eigen(const C_Map_MatrixXd *ptr) {
return *reinterpret_cast<const Map<MatrixXd> *>(ptr);
}
inline C_Map_MatrixXd *eigen_to_c(Map<MatrixXd> &ref) { return reinterpret_cast<C_Map_MatrixXd *>(&ref); }
inline const C_Map_MatrixXd *eigen_to_c(const Map<MatrixXd> &ref) {
return reinterpret_cast<const C_Map_MatrixXd *>(&ref);
}
/************************* implementation of classes **********************************************/
////// class MatrixXd //////
C_MatrixXd *MatrixXd_new(int rows, int cols) { return eigen_to_c(*new MatrixXd(rows, cols)); }
void MatrixXd_delete(C_MatrixXd *m) { delete &c_to_eigen(m); }
double *MatrixXd_data(C_MatrixXd *m) { return c_to_eigen(m).data(); }
void MatrixXd_set_zero(C_MatrixXd *m) { c_to_eigen(m).setZero(); }
void MatrixXd_resize(C_MatrixXd *m, int rows, int cols) { c_to_eigen(m).resize(rows, cols); }
void MatrixXd_copy(C_MatrixXd *dst, const C_MatrixXd *src) { c_to_eigen(dst) = c_to_eigen(src); }
void MatrixXd_copy_map(C_MatrixXd *dst, const C_Map_MatrixXd *src) { c_to_eigen(dst) = c_to_eigen(src); }
void MatrixXd_set_coeff(C_MatrixXd *m, int i, int j, double coeff) { c_to_eigen(m)(i, j) = coeff; }
double MatrixXd_get_coeff(const C_MatrixXd *m, int i, int j) { return c_to_eigen(m)(i, j); }
void MatrixXd_print(const C_MatrixXd *m) { std::cout << c_to_eigen(m) << std::endl; }
void MatrixXd_multiply(const C_MatrixXd *m1, const C_MatrixXd *m2, C_MatrixXd *result) {
c_to_eigen(result) = c_to_eigen(m1) * c_to_eigen(m2);
}
void MatrixXd_add(const C_MatrixXd *m1, const C_MatrixXd *m2, C_MatrixXd *result) {
c_to_eigen(result) = c_to_eigen(m1) + c_to_eigen(m2);
}
////// class Map_MatrixXd //////
C_Map_MatrixXd *Map_MatrixXd_new(double *array, int rows, int cols) {
return eigen_to_c(*new Map<MatrixXd>(array, rows, cols));
}
void Map_MatrixXd_delete(C_Map_MatrixXd *m) { delete &c_to_eigen(m); }
void Map_MatrixXd_set_zero(C_Map_MatrixXd *m) { c_to_eigen(m).setZero(); }
void Map_MatrixXd_copy(C_Map_MatrixXd *dst, const C_Map_MatrixXd *src) { c_to_eigen(dst) = c_to_eigen(src); }
void Map_MatrixXd_copy_matrix(C_Map_MatrixXd *dst, const C_MatrixXd *src) { c_to_eigen(dst) = c_to_eigen(src); }
void Map_MatrixXd_set_coeff(C_Map_MatrixXd *m, int i, int j, double coeff) { c_to_eigen(m)(i, j) = coeff; }
double Map_MatrixXd_get_coeff(const C_Map_MatrixXd *m, int i, int j) { return c_to_eigen(m)(i, j); }
void Map_MatrixXd_print(const C_Map_MatrixXd *m) { std::cout << c_to_eigen(m) << std::endl; }
void Map_MatrixXd_multiply(const C_Map_MatrixXd *m1, const C_Map_MatrixXd *m2, C_Map_MatrixXd *result) {
c_to_eigen(result) = c_to_eigen(m1) * c_to_eigen(m2);
}
void Map_MatrixXd_add(const C_Map_MatrixXd *m1, const C_Map_MatrixXd *m2, C_Map_MatrixXd *result) {
c_to_eigen(result) = c_to_eigen(m1) + c_to_eigen(m2);
}