Struct LuResult 

pub struct LuResult<T: Scalar> {
    pub p: Vec<usize>,
    pub l: Tensor<T>,
    pub u: Tensor<T>,
}

LU decomposition result: A = P * L * U (partial pivoting).

For an input of shape (m, n, *) with k = min(m, n):

• p: permutation indices, shape (m, *)
• l: shape (m, k, *) (unit lower triangular)
• u: shape (k, n, *) (upper triangular)

Examples

use tenferro_linalg::lu;
use tenferro_tensor::{Tensor, MemoryOrder};
use tenferro_device::LogicalMemorySpace;

let a = Tensor::<f64>::zeros(&[3, 3],
    LogicalMemorySpace::MainMemory, MemoryOrder::ColumnMajor);
let result = lu(&a).unwrap();

Fields

p: Vec<usize>

Row permutation indices (partial pivoting). Shape: (m, *).

l: Tensor<T>

Unit lower triangular factor. Shape: (m, k, *).

u: Tensor<T>

Upper triangular factor. Shape: (k, n, *).