diff options
Diffstat (limited to 'Eigen/src/QR/EigenSolver.h')
| -rw-r--r-- | Eigen/src/QR/EigenSolver.h | 36 |
1 files changed, 18 insertions, 18 deletions
diff --git a/Eigen/src/QR/EigenSolver.h b/Eigen/src/QR/EigenSolver.h index 33dcd6daa..cd818a975 100644 --- a/Eigen/src/QR/EigenSolver.h +++ b/Eigen/src/QR/EigenSolver.h @@ -122,7 +122,7 @@ MatrixType EigenSolver<MatrixType>::pseudoEigenvalueMatrix() const { int n = m_eivec.cols(); MatrixType matD = MatrixType::Zero(n,n); - for (int i=0; i<n; i++) + for (int i=0; i<n; ++i) { if (ei_isMuchSmallerThan(ei_imag(m_eivalues.coeff(i)), ei_real(m_eivalues.coeff(i)))) matD.coeffRef(i,i) = ei_real(m_eivalues.coeff(i)); @@ -130,7 +130,7 @@ MatrixType EigenSolver<MatrixType>::pseudoEigenvalueMatrix() const { matD.template block<2,2>(i,i) << ei_real(m_eivalues.coeff(i)), ei_imag(m_eivalues.coeff(i)), -ei_imag(m_eivalues.coeff(i)), ei_real(m_eivalues.coeff(i)); - i++; + ++i; } } return matD; @@ -145,7 +145,7 @@ typename EigenSolver<MatrixType>::EigenvectorType EigenSolver<MatrixType>::eigen { int n = m_eivec.cols(); EigenvectorType matV(n,n); - for (int j=0; j<n; j++) + for (int j=0; j<n; ++j) { if (ei_isMuchSmallerThan(ei_abs(ei_imag(m_eivalues.coeff(j))), ei_abs(ei_real(m_eivalues.coeff(j))))) { @@ -155,14 +155,14 @@ typename EigenSolver<MatrixType>::EigenvectorType EigenSolver<MatrixType>::eigen else { // we have a pair of complex eigen values - for (int i=0; i<n; i++) + for (int i=0; i<n; ++i) { matV.coeffRef(i,j) = Complex(m_eivec.coeff(i,j), m_eivec.coeff(i,j+1)); matV.coeffRef(i,j+1) = Complex(m_eivec.coeff(i,j), -m_eivec.coeff(i,j+1)); } matV.col(j).normalize(); matV.col(j+1).normalize(); - j++; + ++j; } } return matV; @@ -198,7 +198,7 @@ void EigenSolver<MatrixType>::orthes(MatrixType& matH, RealVectorType& ort) int low = 0; int high = n-1; - for (int m = low+1; m <= high-1; m++) + for (int m = low+1; m <= high-1; ++m) { // Scale column. RealScalar scale = matH.block(m, m-1, high-m+1, 1).cwise().abs().sum(); @@ -290,7 +290,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH) // FIXME to be efficient the following would requires a triangular reduxion code // Scalar norm = matH.upper().cwise().abs().sum() + matH.corner(BottomLeft,n,n).diagonal().cwise().abs().sum(); Scalar norm = 0.0; - for (int j = 0; j < nn; j++) + for (int j = 0; j < nn; ++j) { // FIXME what's the purpose of the following since the condition is always false if ((j < low) || (j > high)) @@ -361,7 +361,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH) q = q / r; // Row modification - for (int j = n-1; j < nn; j++) + for (int j = n-1; j < nn; ++j) { z = matH.coeff(n-1,j); matH.coeffRef(n-1,j) = q * z + p * matH.coeff(n,j); @@ -369,7 +369,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH) } // Column modification - for (int i = 0; i <= n; i++) + for (int i = 0; i <= n; ++i) { z = matH.coeff(i,n-1); matH.coeffRef(i,n-1) = q * z + p * matH.coeff(i,n); @@ -377,7 +377,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH) } // Accumulate transformations - for (int i = low; i <= high; i++) + for (int i = low; i <= high; ++i) { z = m_eivec.coeff(i,n-1); m_eivec.coeffRef(i,n-1) = q * z + p * m_eivec.coeff(i,n); @@ -410,7 +410,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH) if (iter == 10) { exshift += x; - for (int i = low; i <= n; i++) + for (int i = low; i <= n; ++i) matH.coeffRef(i,i) -= x; s = ei_abs(matH.coeff(n,n-1)) + ei_abs(matH.coeff(n-1,n-2)); x = y = 0.75 * s; @@ -428,7 +428,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH) if (y < x) s = -s; s = x - w / ((y - x) / 2.0 + s); - for (int i = low; i <= n; i++) + for (int i = low; i <= n; ++i) matH.coeffRef(i,i) -= s; exshift += s; x = y = w = 0.964; @@ -463,7 +463,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH) m--; } - for (int i = m+2; i <= n; i++) + for (int i = m+2; i <= n; ++i) { matH.coeffRef(i,i-2) = 0.0; if (i > m+2) @@ -471,7 +471,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH) } // Double QR step involving rows l:n and columns m:n - for (int k = m; k <= n-1; k++) + for (int k = m; k <= n-1; ++k) { int notlast = (k != n-1); if (k != m) { @@ -510,7 +510,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH) r = r / p; // Row modification - for (int j = k; j < nn; j++) + for (int j = k; j < nn; ++j) { p = matH.coeff(k,j) + q * matH.coeff(k+1,j); if (notlast) @@ -523,7 +523,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH) } // Column modification - for (int i = 0; i <= std::min(n,k+3); i++) + for (int i = 0; i <= std::min(n,k+3); ++i) { p = x * matH.coeff(i,k) + y * matH.coeff(i,k+1); if (notlast) @@ -536,7 +536,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH) } // Accumulate transformations - for (int i = low; i <= high; i++) + for (int i = low; i <= high; ++i) { p = x * m_eivec.coeff(i,k) + y * m_eivec.coeff(i,k+1); if (notlast) @@ -686,7 +686,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH) } // Vectors of isolated roots - for (int i = 0; i < nn; i++) + for (int i = 0; i < nn; ++i) { // FIXME again what's the purpose of this test ? // in this algo low==0 and high==nn-1 !! |