Trait ndarray_stats::HistogramExt

source · 
pub trait HistogramExt<A, S>where
    S: Data<Elem = A>,{
    fn histogram(&self, grid: Grid<A>) -> Histogram<A>
    where
        A: Ord;
}
Expand description

Extension trait for ArrayBase providing methods to compute histograms.

Required Methods

Returns the histogram for a 2-dimensional array of points M.

Let (n, d) be the shape of M:

  • n is the number of points;
  • d is the number of dimensions of the space those points belong to. It follows that every column in M is a d-dimensional point.

For example: a (3, 4) matrix M is a collection of 3 points in a 4-dimensional space.

Important: points outside the grid are ignored!

Panics if d is different from grid.ndim().

Example:
extern crate ndarray_stats;
#[macro_use(array)]
extern crate ndarray;
extern crate noisy_float;
use ndarray_stats::{
    HistogramExt,
    histogram::{
        Histogram, Grid, GridBuilder,
        Edges, Bins,
        strategies::Sqrt},
};
use noisy_float::types::{N64, n64};

let observations = array![
    [n64(1.), n64(0.5)],
    [n64(-0.5), n64(1.)],
    [n64(-1.), n64(-0.5)],
    [n64(0.5), n64(-1.)]
];
let grid = GridBuilder::<Sqrt<N64>>::from_array(&observations).build();
let expected_grid = Grid::from(
    vec![
        Bins::new(Edges::from(vec![n64(-1.), n64(0.), n64(1.), n64(2.)])),
        Bins::new(Edges::from(vec![n64(-1.), n64(0.), n64(1.), n64(2.)])),
    ]
);
assert_eq!(grid, expected_grid);

let histogram = observations.histogram(grid);

let histogram_matrix = histogram.counts();
// Bins are left inclusive, right exclusive!
let expected = array![
    [1, 0, 1],
    [1, 0, 0],
    [0, 1, 0],
];
assert_eq!(histogram_matrix, expected.into_dyn());

Implementations on Foreign Types

Implementors