Function easy_ml::linear_algebra::cholesky_decomposition

pub fn cholesky_decomposition<T: Numeric + Sqrt<Output = T>>(
    matrix: &Matrix<T>
) -> Option<Matrix<T>> where
    &'a T: NumericRef<T>, 

Computes the cholesky decomposition of a matrix. This yields a matrix L such that for the provided matrix A, L * L^T = A. L will always be lower triangular, ie all entries above the diagonal will be 0. Hence cholesky decomposition can be interpreted as a generalised square root function.

Cholesky decomposition is defined for Hermitian, positive definite matrices. For a real valued (ie not containing complex numbers) matrix, if it is Symmetric it is Hermitian.

This function does not check that the provided matrix is Hermitian or positive definite at present, but may in the future, in which case None will be returned.