# Struct rand_distr::weighted_tree::WeightedTreeIndex

``pub struct WeightedTreeIndex<W: Clone + PartialEq + PartialOrd + SampleUniform + SubAssign<W> + Weight> { /* private fields */ }``
Expand description

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

Sampling a `WeightedTreeIndex<W>` distribution returns the index of a randomly selected element from the vector used to create the `WeightedTreeIndex<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 an implementation of `Weight` exists.

## §Key differences

The main distinction between `WeightedTreeIndex<W>` and `rand::distr::WeightedIndex<W>` lies in the internal representation of weights. In `WeightedTreeIndex<W>`, weights are structured as a tree, which is optimized for frequent updates of the weights.

## §Caution: Floating point types

When utilizing `WeightedTreeIndex<W>` with floating point types (such as f32 or f64), exercise caution due to the inherent nature of floating point arithmetic. Floating point types are susceptible to numerical rounding errors. Since operations on floating point weights are repeated numerous times, rounding errors can accumulate, potentially leading to noticeable deviations from the expected behavior.

Ideally, use fixed point or integer types whenever possible.

## §Performance

A `WeightedTreeIndex<W>` with `n` elements requires `O(n)` memory.

Time complexity for the operations of a `WeightedTreeIndex<W>` are:

• Constructing: Building the initial tree from an iterator of weights takes `O(n)` time.
• Sampling: Choosing an index (traversing down the tree) requires `O(log n)` time.
• Weight Update: Modifying a weight (traversing up the tree), requires `O(log n)` time.
• Weight Addition (Pushing): Adding a new weight (traversing up the tree), requires `O(log n)` time.
• Weight Removal (Popping): Removing a weight (traversing up the tree), requires `O(log n)` time.

## §Example

``````use rand_distr::WeightedTreeIndex;
use rand::prelude::*;

let choices = vec!['a', 'b', 'c'];
let weights = vec![2, 0];
let mut dist = WeightedTreeIndex::new(&weights).unwrap();
dist.push(1).unwrap();
dist.update(1, 1).unwrap();
let mut samples = [0; 3];
for _ in 0..100 {
// 50% chance to print 'a', 25% chance to print 'b', 25% chance to print 'c'
let i = dist.sample(&mut rng);
samples[i] += 1;
}
println!("Results: {:?}", choices.iter().zip(samples.iter()).collect::<Vec<_>>());``````

## Implementations§

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### impl<W: Clone + PartialEq + PartialOrd + SampleUniform + SubAssign<W> + Weight> WeightedTreeIndex<W>

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#### pub fn new<I>(weights: I) -> Result<Self, WeightError>where I: IntoIterator, I::Item: SampleBorrow<W>,

Creates a new `WeightedTreeIndex` from a slice of weights.

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#### pub fn is_empty(&self) -> bool

Returns `true` if the tree contains no weights.

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#### pub fn len(&self) -> usize

Returns the number of weights.

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#### pub fn is_valid(&self) -> bool

Returns `true` if we can sample.

This is the case if the total weight of the tree is greater than zero.

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#### pub fn get(&self, index: usize) -> W

Gets the weight at an index.

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#### pub fn pop(&mut self) -> Option<W>

Removes the last weight and returns it, or `None` if it is empty.

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#### pub fn push(&mut self, weight: W) -> Result<(), WeightError>

Appends a new weight at the end.

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#### pub fn update(&mut self, index: usize, weight: W) -> Result<(), WeightError>

Updates the weight at an index.

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### impl<W: Clone + PartialEq + PartialOrd + SampleUniform + SubAssign<W> + Weight> WeightedTreeIndex<W>

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#### pub fn try_sample<R: Rng + ?Sized>( &self, rng: &mut R, ) -> Result<usize, WeightError>

Samples a randomly selected index from the weighted distribution.

Returns an error if there are no elements or all weights are zero. This is unlike `Distribution::sample`, which panics in those cases.

## Trait Implementations§

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### impl<W: Clone + Clone + PartialEq + PartialOrd + SampleUniform + SubAssign<W> + Weight> Clone for WeightedTreeIndex<W>

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#### fn clone(&self) -> WeightedTreeIndex<W>

Returns a copy of the value. Read more
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#### fn clone_from(&mut self, source: &Self)

Performs copy-assignment from `source`. Read more
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### impl<W: Debug + Clone + PartialEq + PartialOrd + SampleUniform + SubAssign<W> + Weight> Debug for WeightedTreeIndex<W>

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#### fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter. Read more
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### impl<W: Default + Clone + PartialEq + PartialOrd + SampleUniform + SubAssign<W> + Weight> Default for WeightedTreeIndex<W>

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#### fn default() -> WeightedTreeIndex<W>

Returns the “default value” for a type. Read more
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### impl<'de, W> Deserialize<'de> for WeightedTreeIndex<W>where W: Deserialize<'de> + Clone + PartialEq + PartialOrd + SampleUniform + SubAssign<W> + Weight, W::Sampler: Deserialize<'de>,

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#### fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer. Read more
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### impl<W: Clone + PartialEq + PartialOrd + SampleUniform + SubAssign<W> + Weight> Distribution<usize> for WeightedTreeIndex<W>

Samples a randomly selected index from the weighted distribution.

Caution: This method panics if there are no elements or all weights are zero. However, it is guaranteed that this method will not panic if a call to `WeightedTreeIndex::is_valid` returns `true`.

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#### fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> usize

Generate a random value of `T`, using `rng` as the source of randomness.
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#### fn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T> ⓘwhere R: Rng, Self: Sized,

Create an iterator that generates random values of `T`, using `rng` as the source of randomness. Read more
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#### fn map<F, S>(self, func: F) -> DistMap<Self, F, T, S>where F: Fn(T) -> S, Self: Sized,

Create a distribution of values of ‘S’ by mapping the output of `Self` through the closure `F` Read more
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### impl<W: PartialEq + Clone + PartialEq + PartialOrd + SampleUniform + SubAssign<W> + Weight> PartialEq for WeightedTreeIndex<W>

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#### fn eq(&self, other: &WeightedTreeIndex<W>) -> bool

Tests for `self` and `other` values to be equal, and is used by `==`.
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#### fn ne(&self, other: &Rhs) -> bool

Tests for `!=`. The default implementation is almost always sufficient, and should not be overridden without very good reason.
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### impl<W> Serialize for WeightedTreeIndex<W>where W: Serialize + Clone + PartialEq + PartialOrd + SampleUniform + SubAssign<W> + Weight, W::Sampler: Serialize,

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#### fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>where __S: Serializer,

Serialize this value into the given Serde serializer. Read more
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## Blanket Implementations§

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### impl<T> Any for Twhere T: 'static + ?Sized,

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#### fn type_id(&self) -> TypeId

Gets the `TypeId` of `self`. Read more
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### impl<T> Borrow<T> for Twhere T: ?Sized,

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#### fn borrow(&self) -> &T

Immutably borrows from an owned value. Read more
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### impl<T> BorrowMut<T> for Twhere T: ?Sized,

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#### fn borrow_mut(&mut self) -> &mut T

Mutably borrows from an owned value. Read more
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### impl<T> CloneToUninit for Twhere T: Clone,

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#### unsafe fn clone_to_uninit(&self, dst: *mut T)

🔬This is a nightly-only experimental API. (`clone_to_uninit`)
Performs copy-assignment from `self` to `dst`. Read more
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### impl<T> From<T> for T

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#### fn from(t: T) -> T

Returns the argument unchanged.

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### impl<T, U> Into<U> for Twhere U: From<T>,

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#### fn into(self) -> U

Calls `U::from(self)`.

That is, this conversion is whatever the implementation of `From<T> for U` chooses to do.

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### impl<T> ToOwned for Twhere T: Clone,

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#### type Owned = T

The resulting type after obtaining ownership.
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#### fn to_owned(&self) -> T

Creates owned data from borrowed data, usually by cloning. Read more
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#### fn clone_into(&self, target: &mut T)

Uses borrowed data to replace owned data, usually by cloning. Read more
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### impl<T, U> TryFrom<U> for Twhere U: Into<T>,

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#### type Error = Infallible

The type returned in the event of a conversion error.
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#### fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>

Performs the conversion.
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### impl<T, U> TryInto<U> for Twhere U: TryFrom<T>,

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

The type returned in the event of a conversion error.
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#### fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>

Performs the conversion.
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