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Another big refactoring change:
* add a new Eigen2Support module including Cwise, Flagged, and some other deprecated stuff * add a few cwiseXxx functions * adapt a few modules to use cwiseXxx instead of the .cwise() prefix
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@@ -225,7 +225,7 @@ void EigenSolver<MatrixType>::orthes(MatrixType& matH, RealVectorType& ort)
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for (int m = low+1; m <= high-1; ++m)
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{
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// Scale column.
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RealScalar scale = matH.block(m, m-1, high-m+1, 1).cwise().abs().sum();
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RealScalar scale = matH.block(m, m-1, high-m+1, 1).cwiseAbs().sum();
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if (scale != 0.0)
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{
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// Compute Householder transformation.
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@@ -312,7 +312,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH)
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// Store roots isolated by balanc and compute matrix norm
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// FIXME to be efficient the following would requires a triangular reduxion code
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// Scalar norm = matH.upper().cwise().abs().sum() + matH.corner(BottomLeft,n,n).diagonal().cwise().abs().sum();
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// Scalar norm = matH.upper().cwiseAbs().sum() + matH.corner(BottomLeft,n,n).diagonal().cwiseAbs().sum();
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Scalar norm = 0.0;
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for (int j = 0; j < nn; ++j)
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{
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@@ -321,7 +321,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH)
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{
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m_eivalues.coeffRef(j) = Complex(matH.coeff(j,j), 0.0);
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}
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norm += matH.row(j).segment(std::max(j-1,0), nn-std::max(j-1,0)).cwise().abs().sum();
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norm += matH.row(j).segment(std::max(j-1,0), nn-std::max(j-1,0)).cwiseAbs().sum();
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}
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// Outer loop over eigenvalue index
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