Trait smartcore::linalg::traits::stats::MatrixPreprocessing

source · 
pub trait MatrixPreprocessing<T: RealNumber>: MutArrayView2<T> + Clone {
    // Provided methods
    fn binarize_mut(&mut self, threshold: T) { ... }
    fn binarize(self, threshold: T) -> Self
       where Self: Sized { ... }
}
Expand description

Defines baseline implementations for various matrix processing functions

Provided Methods§

source

fn binarize_mut(&mut self, threshold: T)

Each element of the matrix greater than the threshold becomes 1, while values less than or equal to the threshold become 0

use smartcore::linalg::basic::matrix::DenseMatrix;
use smartcore::linalg::traits::stats::MatrixPreprocessing;
let mut a = DenseMatrix::from_2d_array(&[&[0., 2., 3.], &[-5., -6., -7.]]);
let expected = DenseMatrix::from_2d_array(&[&[0., 1., 1.],&[0., 0., 0.]]);
a.binarize_mut(0.);

assert_eq!(a, expected);
source

fn binarize(self, threshold: T) -> Selfwhere Self: Sized,

Returns new matrix where elements are binarized according to a given threshold.

use smartcore::linalg::basic::matrix::DenseMatrix;
use smartcore::linalg::traits::stats::MatrixPreprocessing;
let a = DenseMatrix::from_2d_array(&[&[0., 2., 3.], &[-5., -6., -7.]]);
let expected = DenseMatrix::from_2d_array(&[&[0., 1., 1.],&[0., 0., 0.]]);

assert_eq!(a.binarize(0.), expected);

Implementors§