Struct ndarray_histogram::histogram::Edges
source · pub struct Edges<A: Ord + Send> { /* private fields */ }
Expand description
A sorted collection of type A
elements used to represent the boundaries of intervals, i.e.
Bins
on a 1-dimensional axis.
Note that all intervals are left-closed and right-open. See examples below.
Examples
use ndarray_histogram::histogram::{Bins, Edges};
use noisy_float::types::n64;
let unit_edges = Edges::from(vec![n64(0.), n64(1.)]);
let unit_interval = Bins::new(unit_edges);
// left-closed
assert_eq!(unit_interval.range_of(&n64(0.)).unwrap(), n64(0.)..n64(1.),);
// right-open
assert_eq!(unit_interval.range_of(&n64(1.)), None);
Implementations§
source§impl<A: Ord + Send> Edges<A>
impl<A: Ord + Send> Edges<A>
sourcepub fn len(&self) -> usize
pub fn len(&self) -> usize
Returns the number of edges in self
.
Examples
use ndarray_histogram::histogram::Edges;
use noisy_float::types::n64;
let edges = Edges::from(vec![n64(0.), n64(1.), n64(3.)]);
assert_eq!(edges.len(), 3);
sourcepub fn is_empty(&self) -> bool
pub fn is_empty(&self) -> bool
Returns true
if self
contains no edges.
Examples
use ndarray_histogram::histogram::Edges;
use noisy_float::types::{n64, N64};
let edges = Edges::<N64>::from(vec![]);
assert_eq!(edges.is_empty(), true);
let edges = Edges::from(vec![n64(0.), n64(2.), n64(5.)]);
assert_eq!(edges.is_empty(), false);
sourcepub fn as_array_view(&self) -> ArrayView1<'_, A>
pub fn as_array_view(&self) -> ArrayView1<'_, A>
Returns an immutable 1-dimensional array view of edges.
Examples
use ndarray::array;
use ndarray_histogram::histogram::Edges;
let edges = Edges::from(vec![0, 5, 3]);
assert_eq!(edges.as_array_view(), array![0, 3, 5].view());
sourcepub fn indices_of(&self, value: &A) -> Option<(usize, usize)>
pub fn indices_of(&self, value: &A) -> Option<(usize, usize)>
Returns indices of two consecutive edges
in self
, if the interval they represent
contains the given value
, or returns None
otherwise.
That is to say, it returns
Some((left, right))
, whereleft
andright
are the indices of two consecutive edges inself
andright == left + 1
, ifself[left] <= value < self[right]
;None
, otherwise.
Examples
use ndarray_histogram::histogram::Edges;
let edges = Edges::from(vec![0, 2, 3]);
// `1` is in the interval [0, 2), whose indices are (0, 1)
assert_eq!(edges.indices_of(&1), Some((0, 1)));
// `5` is not in any of intervals
assert_eq!(edges.indices_of(&5), None);
Trait Implementations§
source§impl<A: Ord + Send + Clone> From<ArrayBase<OwnedRepr<A>, Dim<[usize; 1]>>> for Edges<A>
impl<A: Ord + Send + Clone> From<ArrayBase<OwnedRepr<A>, Dim<[usize; 1]>>> for Edges<A>
source§fn from(edges: Array1<A>) -> Self
fn from(edges: Array1<A>) -> Self
Converts an Array1<A>
into an Edges<A>
, consuming the 1-dimensional array.
The array will be sorted in increasing order using an unstable sorting algorithm, with
duplicates removed.
Current implementation
The current sorting algorithm is the same as std::slice::sort_unstable()
,
which is based on pattern-defeating quicksort.
This sort is unstable (i.e., may reorder equal elements), in-place (i.e., does not allocate) , and O(n log n) worst-case.
Examples
use ndarray_histogram::histogram::Edges;
let edges = Edges::from(vec![1, 15, 10, 20]);
// The vec gets sorted!
assert_eq!(edges[1], 10);
source§impl<A: Ord + Send> From<Vec<A, Global>> for Edges<A>
impl<A: Ord + Send> From<Vec<A, Global>> for Edges<A>
source§fn from(edges: Vec<A>) -> Self
fn from(edges: Vec<A>) -> Self
Converts a Vec<A>
into an Edges<A>
, consuming the edges.
The vector will be sorted in increasing order using an unstable sorting algorithm, with
duplicates removed.
Current implementation
The current sorting algorithm is the same as std::slice::sort_unstable()
,
which is based on pattern-defeating quicksort.
This sort is unstable (i.e., may reorder equal elements), in-place (i.e., does not allocate) , and O(n log n) worst-case.
Examples
use ndarray::array;
use ndarray_histogram::histogram::Edges;
let edges = Edges::from(array![1, 15, 10, 10, 20]);
// The array gets sorted!
assert_eq!(edges[2], 15);