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//! ```rust
//! use mdarray::{DTensor, tensor};
//! use mdarray_linalg::prelude::*; // Imports only traits
//! use mdarray_linalg::eig::EigDecomp;
//! use mdarray_linalg::svd::SVDDecomp;
//!
//! // Backends
//! use mdarray_linalg_lapack::Lapack;
//! use mdarray_linalg_lapack::SVDConfig;
//!
//! let a = tensor![[1., 2.], [3., 4.]];
//!
//! // ----- Eigenvalue decomposition -----
//! // Note: we must clone `a` here because decomposition routines destroy the input.
//! let bd = Lapack::new(); // Unlike Blas, Lapack is not a zero-sized backend so `new` must be called.
//! let EigDecomp {
//! eigenvalues,
//! right_eigenvectors,
//! ..
//! } = bd.eig(&mut a.clone()).expect("Eigenvalue decomposition failed");
//!
//! println!("Eigenvalues: {:?}", eigenvalues);
//! if let Some(vectors) = right_eigenvectors {
//! println!("Right eigenvectors: {:?}", vectors);
//! }
//!
//! // ----- Singular Value Decomposition (SVD) -----
//! let bd = Lapack::new().config_svd(SVDConfig::DivideConquer);
//! let SVDDecomp { s, u, vt } = bd.svd(&mut a.clone()).expect("SVD failed");
//! println!("Singular values: {:?}", s);
//! println!("Left singular vectors U: {:?}", u);
//! println!("Right singular vectors V^T: {:?}", vt);
//!
//! // ----- QR Decomposition -----
//! let (m, n) = *a.shape();
//! let mut q = DTensor::<f64, 2>::zeros([m, m]);
//! let mut r = DTensor::<f64, 2>::zeros([m, n]);
//!
//! let bd = Lapack::new();
//! bd.qr_overwrite(&mut a.clone(), &mut q, &mut r); //
//! println!("Q: {:?}", q);
//! println!("R: {:?}", r);
//! ```