Function cols_to_l_matrix 

pub fn cols_to_l_matrix<T: Scalar>(
    c: &mut Matrix<T>,
    p: &Matrix<T>,
    _left_orthogonal: bool,
) -> Result<()>

Convert L matrix to solve L * X = B given pivot matrix P

Modifies c in place so that the columns satisfy the triangular system defined by p. The matrix c must have at least p.nrows() columns.

Errors

Returns MatrixCIError::InvalidArgument when p is not square or c has too few columns, and MatrixCIError::SingularMatrix for a zero diagonal pivot.

Examples

use tensor4all_core::matrixlu::cols_to_l_matrix;
use tensor4all_tensorbackend::from_vec2d;

// Upper-triangular P (2x2)
let p = from_vec2d(vec![
    vec![2.0_f64, 1.0],
    vec![0.0, 3.0],
]);
// c has 3 rows, 2 columns (ncols >= p.nrows())
let mut c = from_vec2d(vec![
    vec![4.0_f64, 5.0],
    vec![6.0, 9.0],
    vec![8.0, 7.0],
]);
cols_to_l_matrix(&mut c, &p, true).unwrap();
// After processing: c[:,0] was divided by p[0,0]=2
assert!((c[[0, 0]] - 2.0).abs() < 1e-10);
assert!((c[[1, 0]] - 3.0).abs() < 1e-10);
assert!((c[[2, 0]] - 4.0).abs() < 1e-10);