pub fn svd(a: &ArrayView2<'_, C64>) -> (CMat, Vec<f64>, CMat)Expand description
The thin singular value decomposition $A = U \Sigma V^{H}$ by one-sided Jacobi.
For an $m \times n$ matrix with $k = \min(m, n)$, returns $U$ ($m \times k$), the singular values in decreasing order ($k$ of them) and $V$ ($n \times k$). The columns of $U$ that belong to zero singular values are zero.