[][src]Struct rand::distributions::WeightedIndex

pub struct WeightedIndex<X: SampleUniform + PartialOrd> { /* fields omitted */ }

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

Sampling a WeightedIndex distribution returns the index of a randomly selected element from the iterator used when the WeightedIndex was created. The chance of a given element being picked is proportional to the value of the element. The weights can use any type X for which an implementation of Uniform<X> exists.

Performance

A WeightedIndex<X> contains a Vec<X> and a Uniform<X> and so its size is the sum of the size of those objects, possibly plus some alignment.

Creating a WeightedIndex<X> will allocate enough space to hold N - 1 weights of type X, where N is the number of weights. However, since Vec doesn't guarantee a particular growth strategy, additional memory might be allocated but not used. Since the WeightedIndex object also contains, this might cause additional allocations, though for primitive types, ['Uniform`] doesn't allocate any memory.

Time complexity of sampling from WeightedIndex is O(log N) where N is the number of weights.

Sampling from WeightedIndex will result in a single call to Uniform<X>::sample (method of the [Distribution] trait), which typically will request a single value from the underlying RngCore, though the exact number depends on the implementaiton of Uniform<X>::sample.

Example

use rand::prelude::*;
use rand::distributions::WeightedIndex;

let choices = ['a', 'b', 'c'];
let weights = [2,   1,   1];
let dist = WeightedIndex::new(&weights).unwrap();
let mut rng = thread_rng();
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 = WeightedIndex::new(items.iter().map(|item| item.1)).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);
}

Methods

impl<X: SampleUniform + PartialOrd> WeightedIndex<X>[src]

pub fn new<I>(weights: I) -> Result<WeightedIndex<X>, WeightedError> where
    I: IntoIterator,
    I::Item: SampleBorrow<X>,
    X: for<'a> AddAssign<&'a X> + Clone + Default
[src]

Creates a new a WeightedIndex [Distribution] using the values in weights. The weights can use any type X for which an implementation of Uniform<X> exists.

Returns an error if the iterator is empty, if any weight is < 0, or if its total value is 0.

Trait Implementations

impl<X> Distribution<usize> for WeightedIndex<X> where
    X: SampleUniform + PartialOrd
[src]

impl<X: Clone + SampleUniform + PartialOrd> Clone for WeightedIndex<X> where
    X::Sampler: Clone
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impl<X: Debug + SampleUniform + PartialOrd> Debug for WeightedIndex<X> where
    X::Sampler: Debug
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Auto Trait Implementations

impl<X> Send for WeightedIndex<X> where
    X: Send,
    <X as SampleUniform>::Sampler: Send

impl<X> Unpin for WeightedIndex<X> where
    X: Unpin,
    <X as SampleUniform>::Sampler: Unpin

impl<X> Sync for WeightedIndex<X> where
    X: Sync,
    <X as SampleUniform>::Sampler: Sync

impl<X> UnwindSafe for WeightedIndex<X> where
    X: UnwindSafe,
    <X as SampleUniform>::Sampler: UnwindSafe

impl<X> RefUnwindSafe for WeightedIndex<X> where
    X: RefUnwindSafe,
    <X as SampleUniform>::Sampler: RefUnwindSafe

Blanket Implementations

impl<T> ToOwned for T where
    T: Clone
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type Owned = T

The resulting type after obtaining ownership.

impl<T, U> Into<U> for T where
    U: From<T>, 
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impl<T> From<T> for T[src]

impl<T, U> TryFrom<U> for T where
    U: Into<T>, 
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type Error = Infallible

The type returned in the event of a conversion error.

impl<T, U> TryInto<U> for T where
    U: TryFrom<T>, 
[src]

type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.

impl<T> BorrowMut<T> for T where
    T: ?Sized
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impl<T> Borrow<T> for T where
    T: ?Sized
[src]

impl<T> Any for T where
    T: 'static + ?Sized
[src]