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53  * This class first reduces the input matrix to bi-diagonal form using class UpperBidiagonalization,
420 m_computed.diagonal().segment(firstCol + shift, n) = b.singularValues().head(n);
559 m_computed.block(firstCol + shift, firstCol + shift, n, n).diagonal() = singVals;
563 // the first column and on the diagonal and has undergone deflation, so diagonal is in increasing
576 m_workspace.head(n) = m_computed.block(firstCol, firstCol, n, n).diagonal();
720 // if col0(k) == 0, then entry is deflated, so singular value is on diagonal
869 // perturb singular value slightly if it equals diagonal entry to avoid division by zero later
1051 Diagonal<MatrixXr> fulldiag(m_computed);
1052 VectorBlock<Diagonal<MatrixXr>,Dynamic> diag(fulldiag, firstCol+shift, length);
1111 // Sort the diagonal entries, since diag(1:k-1) and diag(k:length) are already sorted, let's do a sorted merge.
1118 // Move deflated diagonal entries at the end.
1165 // swap diagonal and first column entries:
1197 eigen_internal_assert(abs(diag(i) - diag(i-1))<epsilon_coarse && " diagonal entries are not properly sorted");