/usr/include/Rivet/Math/MatrixN.hh is in librivet-dev 1.8.3-1.1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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#define RIVET_MATH_MATRIXN
#include "Rivet/Math/MathHeader.hh"
#include "Rivet/Math/MathUtils.hh"
#include "Rivet/Math/Vectors.hh"
#include "Rivet/Math/eigen/matrix.h"
namespace Rivet {
template <size_t N>
class Matrix;
typedef Matrix<4> Matrix4;
template <size_t N>
Matrix<N> multiply(const Matrix<N>& a, const Matrix<N>& b);
template <size_t N>
Matrix<N> divide(const Matrix<N>&, const double);
template <size_t N>
Matrix<N> operator*(const Matrix<N>& a, const Matrix<N>& b);
///////////////////////////////////
/// @brief General \f$ N \f$-dimensional mathematical matrix object.
template <size_t N>
class Matrix {
template <size_t M>
friend Matrix<M> add(const Matrix<M>&, const Matrix<M>&);
template <size_t M>
friend Matrix<M> multiply(const double, const Matrix<M>&);
template <size_t M>
friend Matrix<M> multiply(const Matrix<M>&, const Matrix<M>&);
template <size_t M>
friend Vector<M> multiply(const Matrix<M>&, const Vector<M>&);
template <size_t M>
friend Matrix<M> divide(const Matrix<M>&, const double);
public:
static Matrix<N> mkZero() {
Matrix<N> rtn;
return rtn;
}
static Matrix<N> mkDiag(Vector<N> diag) {
Matrix<N> rtn;
for (size_t i = 0; i < N; ++i) {
rtn.set(i, i, diag[i]);
}
return rtn;
}
static Matrix<N> mkIdentity() {
Matrix<N> rtn;
for (size_t i = 0; i < N; ++i) {
rtn.set(i, i, 1);
}
return rtn;
}
public:
Matrix() {
_matrix.loadZero();
}
Matrix(const Matrix<N>& other) {
_matrix = other._matrix;
}
Matrix& set(const size_t i, const size_t j, const double value) {
if (i < N && j < N) {
_matrix(i, j) = value;
} else {
throw std::runtime_error("Attempted set access outside matrix bounds.");
}
return *this;
}
double get(const size_t i, const size_t j) const {
if (i < N && j < N) {
return _matrix(i, j);
} else {
throw std::runtime_error("Attempted get access outside matrix bounds.");
}
}
Vector<N> getRow(const size_t row) const {
Vector<N> rtn;
for (size_t i = 0; i < N; ++i) {
rtn.set(i, _matrix(row,i));
}
return rtn;
}
Matrix<N>& setRow(const size_t row, const Vector<N>& r) {
for (size_t i = 0; i < N; ++i) {
_matrix(row,i) = r.get(i);
}
return *this;
}
Vector<N> getColumn(const size_t col) const {
Vector<N> rtn;
for (size_t i = 0; i < N; ++i) {
rtn.set(i, _matrix(i,col));
}
return rtn;
}
Matrix<N>& setColumn(const size_t col, const Vector<N>& c) {
for (size_t i = 0; i < N; ++i) {
_matrix(i,col) = c.get(i);
}
return *this;
}
Matrix<N> transpose() const {
Matrix<N> tmp = *this;
tmp._matrix.replaceWithAdjoint();
return tmp;
}
// Matrix<N>& transposeInPlace() {
// _matrix.replaceWithAdjoint();
// return *this;
// }
/// Calculate inverse
Matrix<N> inverse() const {
Matrix<N> tmp;
tmp._matrix = _matrix.inverse();
return tmp;
}
/// Calculate determinant
double det() const {
return _matrix.determinant();
}
/// Calculate trace
double trace() const {
double tr = 0.0;
for (size_t i = 0; i < N; ++i) {
tr += _matrix(i,i);
}
return tr;
// return _matrix.trace();
}
/// Negate
Matrix<N> operator-() const {
Matrix<N> rtn;
rtn._matrix = -_matrix;
return rtn;
}
/// Get dimensionality
size_t size() const {
return N;
}
/// Index-wise check for nullness, allowing for numerical precision
bool isZero(double tolerance=1E-5) const {
for (size_t i=0; i < N; ++i) {
for (size_t j=0; j < N; ++j) {
if (! Rivet::isZero(_matrix(i,j), tolerance) ) return false;
}
}
return true;
}
/// Check for index-wise equality, allowing for numerical precision
bool isEqual(Matrix<N> other) const {
for (size_t i=0; i < N; ++i) {
for (size_t j=i; j < N; ++j) {
if (! Rivet::isZero(_matrix(i,j) - other._matrix(i,j)) ) return false;
}
}
return true;
}
/// Check for symmetry under transposition
bool isSymm() const {
return isEqual(this->transpose());
}
/// Check that all off-diagonal elements are zero, allowing for numerical precision
bool isDiag() const {
for (size_t i=0; i < N; ++i) {
for (size_t j=0; j < N; ++j) {
if (i == j) continue;
if (! Rivet::isZero(_matrix(i,j)) ) return false;
}
}
return true;
}
bool operator==(const Matrix<N>& a) const {
return _matrix == a._matrix;
}
bool operator!=(const Matrix<N>& a) const {
return _matrix != a._matrix;
}
bool operator<(const Matrix<N>& a) const {
return _matrix < a._matrix;
}
bool operator<=(const Matrix<N>& a) const {
return _matrix <= a._matrix;
}
bool operator>(const Matrix<N>& a) const {
return _matrix > a._matrix;
}
bool operator>=(const Matrix<N>& a) const {
return _matrix >= a._matrix;
}
Matrix<N>& operator*=(const Matrix<N>& m) {
_matrix = _matrix * m._matrix;
return *this;
}
Matrix<N>& operator*=(const double a) {
_matrix *= a;
return *this;
}
Matrix<N>& operator/=(const double a) {
_matrix /= a;
return *this;
}
Matrix<N>& operator+=(const Matrix<N>& m) {
_matrix += m._matrix;
return *this;
}
Matrix<N>& operator-=(const Matrix<N>& m) {
_matrix -= m._matrix;
return *this;
}
protected:
typedef Eigen::Matrix<double,N> EMatrix;
EMatrix _matrix;
};
/////////////////////////////////
template <size_t N>
inline Matrix<N> add(const Matrix<N>& a, const Matrix<N>& b) {
Matrix<N> result;
result._matrix = a._matrix + b._matrix;
return result;
}
template <size_t N>
inline Matrix<N> subtract(const Matrix<N>& a, const Matrix<N>& b) {
return add(a, -b);
}
template <size_t N>
inline Matrix<N> operator+(const Matrix<N> a, const Matrix<N>& b) {
return add(a, b);
}
template <size_t N>
inline Matrix<N> operator-(const Matrix<N> a, const Matrix<N>& b) {
return subtract(a, b);
}
template <size_t N>
inline Matrix<N> multiply(const double a, const Matrix<N>& m) {
Matrix<N> rtn;
rtn._matrix = a * m._matrix;
return rtn;
}
template <size_t N>
inline Matrix<N> multiply(const Matrix<N>& m, const double a) {
return multiply(a, m);
}
template <size_t N>
inline Matrix<N> divide(const Matrix<N>& m, const double a) {
return multiply(1/a, m);
}
template <size_t N>
inline Matrix<N> operator*(const double a, const Matrix<N>& m) {
return multiply(a, m);
}
template <size_t N>
inline Matrix<N> operator*(const Matrix<N>& m, const double a) {
return multiply(a, m);
}
template <size_t N>
inline Matrix<N> multiply(const Matrix<N>& a, const Matrix<N>& b) {
Matrix<N> tmp;
tmp._matrix = a._matrix * b._matrix;
return tmp;
}
template <size_t N>
inline Matrix<N> operator*(const Matrix<N>& a, const Matrix<N>& b) {
return multiply(a, b);
}
template <size_t N>
inline Vector<N> multiply(const Matrix<N>& a, const Vector<N>& b) {
Vector<N> tmp;
tmp._vec = a._matrix * b._vec;
return tmp;
}
template <size_t N>
inline Vector<N> operator*(const Matrix<N>& a, const Vector<N>& b) {
return multiply(a, b);
}
template <size_t N>
inline Matrix<N> transpose(const Matrix<N>& m) {
// Matrix<N> tmp;
// for (size_t i = 0; i < N; ++i) {
// for (size_t j = 0; j < N; ++j) {
// tmp.set(i, j, m.get(j, i));
// }
// }
// return tmp;
return m.transpose();
}
template <size_t N>
inline Matrix<N> inverse(const Matrix<N>& m) {
return m.inverse();
}
template <size_t N>
inline double det(const Matrix<N>& m) {
return m.determinant();
}
template <size_t N>
inline double trace(const Matrix<N>& m) {
return m.trace();
}
/////////////////////////////////
/// Make string representation
template <size_t N>
inline string toString(const Matrix<N>& m) {
ostringstream ss;
ss << "[ ";
for (size_t i = 0; i < m.size(); ++i) {
ss << "( ";
for (size_t j = 0; j < m.size(); ++j) {
const double e = m.get(i, j);
ss << (Rivet::isZero(e) ? 0.0 : e) << " ";
}
ss << ") ";
}
ss << "]";
return ss.str();
}
/// Stream out string representation
template <size_t N>
inline ostream& operator<<(std::ostream& out, const Matrix<N>& m) {
out << toString(m);
return out;
}
/////////////////////////////////////////////////
/// Compare two matrices by index, allowing for numerical precision
template <size_t N>
inline bool fuzzyEquals(const Matrix<N>& ma, const Matrix<N>& mb, double tolerance=1E-5) {
for (size_t i = 0; i < N; ++i) {
for (size_t j = 0; j < N; ++j) {
const double a = ma.get(i, j);
const double b = mb.get(i, j);
if (!Rivet::fuzzyEquals(a, b, tolerance)) return false;
}
}
return true;
}
/// External form of numerically safe nullness check
template <size_t N>
inline bool isZero(const Matrix<N>& m, double tolerance=1E-5) {
return m.isZero(tolerance);
}
}
#endif
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