Struct rand_distr::weighted_alias::WeightedAliasIndex

pub struct WeightedAliasIndex<W: AliasableWeight> { /* private fields */ }
This is supported on crate feature alloc only.
Expand description

A distribution using weighted sampling to pick a discretely selected item.

Sampling a WeightedAliasIndex<W> distribution returns the index of a randomly selected element from the vector used to create the WeightedAliasIndex<W>. The chance of a given element being picked is proportional to the value of the element. The weights can have any type W for which a implementation of AliasableWeight exists.

Performance

Given that n is the number of items in the vector used to create an WeightedAliasIndex<W>, it will require O(n) amount of memory. More specifically it takes up some constant amount of memory plus the vector used to create it and a Vec<u32> with capacity n.

Time complexity for the creation of a WeightedAliasIndex<W> is O(n). Sampling is O(1), it makes a call to Uniform<u32>::sample and a call to Uniform<W>::sample.

Example

use rand_distr::WeightedAliasIndex;
use rand::prelude::*;

let choices = vec!['a', 'b', 'c'];
let weights = vec![2, 1, 1];
let dist = WeightedAliasIndex::new(weights).unwrap();
for _ in 0..100 {
// 50% chance to print 'a', 25% chance to print 'b', 25% chance to print 'c'
println!("{}", choices[dist.sample(&mut rng)]);
}

let items = [('a', 0), ('b', 3), ('c', 7)];
let dist2 = WeightedAliasIndex::new(items.iter().map(|item| item.1).collect()).unwrap();
for _ in 0..100 {
// 0% chance to print 'a', 30% chance to print 'b', 70% chance to print 'c'
println!("{}", items[dist2.sample(&mut rng)].0);
}

Implementations

Creates a new WeightedAliasIndex.

Returns an error if:

• The vector is empty.
• The vector is longer than u32::MAX.
• For any weight w: w < 0 or w > max where max = W::MAX / weights.len().
• The sum of weights is zero.

Trait Implementations

Returns a copy of the value. Read more

Performs copy-assignment from source. Read more

Formats the value using the given formatter. Read more

Generate a random value of T, using rng as the source of randomness.

Create an iterator that generates random values of T, using rng as the source of randomness. Read more

Create a distribution of values of ‘S’ by mapping the output of Self through the closure F Read more

Blanket Implementations

Gets the TypeId of self. Read more

Immutably borrows from an owned value. Read more

Mutably borrows from an owned value. Read more

Performs the conversion.

Performs the conversion.

The resulting type after obtaining ownership.

Creates owned data from borrowed data, usually by cloning. Read more

🔬 This is a nightly-only experimental API. (toowned_clone_into)

Uses borrowed data to replace owned data, usually by cloning. Read more

The type returned in the event of a conversion error.

Performs the conversion.

The type returned in the event of a conversion error.

Performs the conversion.