Struct DiscreteDistribution 

pub struct DiscreteDistribution<'a, T: Probability> { /* private fields */ }

Represents empirical discrete distribution.

Implementations

impl<'_a, T: Probability> DiscreteDistribution<'_a, T>

pub fn new(items: &'_a Vec<T>, method: SamplingMethod) -> Result<Self>

Returns DiscreteDistribution based on the selection method.

use proportionate_selector::*;

#[derive(PartialEq)]
pub struct MultiVariantMarketingWebsiteItem {
    pub id: i32,
    /// Likelihood of recieve marketing website version.
    /// Rarity represents inverse lilihood of recieveing
    /// this item.
    ///
    /// e.g. rairity of 1, means website item item will be more
    /// frequently generated as opposed to rarity of 100.
    pub rarity: f64,
}

impl Probability for MultiVariantMarketingWebsiteItem {
    fn prob(&self) -> f64 {
        // rarity is modeled as 1 out of X occurance, so
        // rarity of 20 has probability of 1/20.
        1.0 / self.rarity
    }
}

let summer2020Launch = vec![
    MultiVariantMarketingWebsiteItem {id: 0, rarity: 5.0}, // 20%
    MultiVariantMarketingWebsiteItem {id: 1, rarity: 5.0}, // 20%
    MultiVariantMarketingWebsiteItem {id: 2, rarity: 10.0}, // 10%
    MultiVariantMarketingWebsiteItem {id: 3, rarity: 2.5}, // 40%
    MultiVariantMarketingWebsiteItem {id: 4, rarity: 10.0}, // 40%
];

// create distribution for sampling
let epdf = DiscreteDistribution::new(&summer2020Launch, SamplingMethod::Linear);
assert!(epdf.is_ok());

pub fn sample(&'_a self) -> Option<&T>

Returns a sample based on discrete distribution.

As invocation of sample() reaches large number (e.g. +infinity), the difference between population (defined discrete distribution), and distribution from generated sample diminishes.

use proportionate_selector::*;

#[derive(PartialEq)]
pub struct LootboxItem {
    pub id: i32,
    /// Likelihood of recieve item from lootbox.
    /// Rarity represents inverse lilihood of recieveing
    /// this item.
    ///
    /// e.g. rairity of 1, means lootbox item will be more
    /// frequently generated as opposed to rarity of 100.
    pub rarity: f64,
}

impl Probability for LootboxItem {
    fn prob(&self) -> f64 {
        // rarity is modeled as 1 out of X occurance, so
        // rarity of 20 has probability of 1/20.
        1.0 / self.rarity
    }
}

let endOfLevel1Box = vec![
    LootboxItem {id: 0, rarity: 5.0}, // 20%
    LootboxItem {id: 1, rarity: 5.0}, // 20%
    LootboxItem {id: 2, rarity: 10.0}, // 10%
    LootboxItem {id: 3, rarity: 2.5}, // 40%
    LootboxItem {id: 4, rarity: 10.0}, // 40%
];

// create discrete distribution for sampling
let epdf = DiscreteDistribution::new(&endOfLevel1Box, SamplingMethod::Linear).unwrap();
let s = epdf.sample();

assert!(s.is_some());