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//! Using the Cholesky decomposition of `A` for various operations, where `A`
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//! is a Hermitian (or real symmetric) positive definite matrix:
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//!
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- //! ```no_run
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+ //! ```
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//! #[macro_use]
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//! extern crate ndarray;
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//! extern crate ndarray_linalg;
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//!
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//! Solve `A * x = b`:
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//!
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- //! ```no_run
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+ //! ```
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//! #[macro_use]
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//! extern crate ndarray;
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//! extern crate ndarray_linalg;
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//! coefficient matrix `A`, it's faster to compute the LU factorization once at
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//! the beginning than solving directly using `A`:
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//!
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- //! ```no_run
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+ //! ```
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//! # extern crate ndarray;
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//! # extern crate ndarray_linalg;
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//!
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//!
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//! Solve `A * x = b`, where `A` is a Hermitian (or real symmetric) matrix:
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//!
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- //! ```no_run
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+ //! ```
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//! #[macro_use]
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//! extern crate ndarray;
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//! extern crate ndarray_linalg;
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//! Hermitian or real symmetric coefficient matrix `A`, it's faster to compute
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//! the factorization once at the beginning than solving directly using `A`:
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//!
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- //! ```no_run
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+ //! ```
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//! # extern crate ndarray;
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//! # extern crate ndarray_linalg;
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//! use ndarray::prelude::*;
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