lin_algebra 0.1.1

A linear algebra package to compute image, kernel and rank of linear applications.
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46

use std::ops::BitXor;
use num_traits::Zero;

pub trait Number:
Copy + Eq + Ord + BitXor<Self> + Zero
{}

impl Number for u8 {}

pub trait MatrixTrait<T: Number>: HasElements<T>{
    fn rank(&self)-> usize;
    fn kernel(&self) -> Vec<Vec<T>>;
    fn echelon_form(&self) -> (Self, Vec<(usize, usize)>) where Self: Sized;
    fn image(&self) -> Vec<Vec<T>>;
    fn is_reduced_echelon(&self) -> bool;
    fn nrows(&self) -> usize {
         self.elements().len()
    }
    fn ncols(&self) -> usize {
        self.elements().get(0).map_or(0, |row| row.len())
    }
    fn get_pivot(vec: &Vec<T>) -> Option<usize> {
         vec.iter().position(|&x| !x.is_zero())
    }
}

pub trait HasElements<T: Number> {
    fn elements(&self) -> &Vec<Vec<T>>;
}

#[derive(Clone, Debug)]
pub struct Matrix<T: Number>{
    pub elements: Vec<Vec<T>>
}

impl<T: Number> Matrix<T> {
    pub fn new(elements: Vec<Vec<T>>) -> Self{
        Self { elements}
    }
}

impl <T: Number> HasElements<T> for Matrix<T> {
    fn elements(&self) -> &Vec<Vec<T>> {
        &self.elements
    }
}