/*

* This file is part of the GreasePad distribution (https://github.com/FraunhoferIOSB/GreasePad).

* Copyright (c) 2022-2026 Jochen Meidow, Fraunhofer IOSB

*

* This program is free software: you can redistribute it and/or modify

* it under the terms of the GNU General Public License as published by

* the Free Software Foundation, either version 3 of the License, or

* (at your option) any later version.

*

* This program is distributed in the hope that it will be useful,

* but WITHOUT ANY WARRANTY; without even the implied warranty of

* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the

* GNU General Public License for more details.

*

* You should have received a copy of the GNU General Public License

* along with this program. If not, see <https://www.gnu.org/licenses/>.

*/

#ifndef ISCOV_H

#define ISCOV_H

#include <Eigen/Core>

#include <Eigen/Eigenvalues>

namespace Stats {

using Eigen::MatrixXd;

//! Check if matrix MM is a proper covariance matrix

[[maybe_unused, nodiscard]] static bool isCovMat( const MatrixXd & MM )

{

// qDebug() << Q_FUNC_INFO;

const Eigen::SelfAdjointEigenSolver<MatrixXd> eig( MM, Eigen::ComputeEigenvectors);

Eigen::VectorXcd ev = eig.eigenvalues();

constexpr double threshold = 1e-6;

#ifdef QT_DEBUG

if ( (ev.real().array() < -threshold ).any() ) {

for ( Eigen::Index i=0; i< ev.size(); i++) {

qDebug().noquote() << QStringLiteral( "(%1,%2)")

.arg( ev(i).real() )

.arg( ev(i).imag() );

}

}

#endif

return ( ev.real().array() >= -threshold ).all();

}

} // namespace Stats

#endif // ISCOV_H