Struct DenseDist 

pub struct DenseDist<T> { /* private fields */ }

A discrete distribution of outcomes, stored densely in a Vec.

Probabilities have type T, e.g. f32, f64, BigRational etc. All distributions have finite support, represented by a Vec<T>.

Implementations

impl<T> DenseDist<T>

pub fn map<U, F: Fn(&T) -> U>(&self, f: F) -> DenseDist<U>

Trait Implementations

impl<T> AsRand<T> for DenseDist<T>

where for<'b> T: Num + FromPrimitive + PartialOrd + Clone + Weight + SampleUniform + MulAssign<&'b T> + SubAssign<&'b T> + AddAssign<&'b T>,

fn to_rand_distribution(&self) -> impl Distribution<isize>

Convert to a Distribution. Useful for sampling.

impl<T: Clone> Clone for DenseDist<T>

fn clone(&self) -> DenseDist<T>

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<T: Debug> Debug for DenseDist<T>

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

Formats the value using the given formatter.

impl<'de, T> Deserialize<'de> for DenseDist<T>

where T: Deserialize<'de>,

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl<T> Dist<T> for DenseDist<T>

where for<'b> T: Num + FromPrimitive + PartialOrd + Clone + MulAssign<&'b T> + SubAssign<&'b T> + AddAssign<&'b T>,

fn chance(&self, n: isize) -> Option<&T>

The chance that n will be sampled from the distribution. Returns None if outside the distribution’s support.

use diceystats::{
    dices::DiceFormula,
    dist::{DenseDist, Dist},
};

let expr: DiceFormula = "d10".parse().unwrap();
let dist: DenseDist<f64> = expr.dist();
let p = dist.chance(3).unwrap_or(&0.0);
assert_eq!(1.0 / 10.0, *p);

fn distance(&self, other: &DenseDist<T>) -> T

Distance between two distributions, measured by total elementwise difference of probabilities.

use diceystats::{
    dices::DiceFormula,
    dist::{DenseDist, Dist},
};
use num::BigRational;

let expr1: DenseDist<_> = "d4xd3".parse::<DiceFormula>().unwrap().dist();
let expr2: DenseDist<_> = "d4+d6".parse::<DiceFormula>().unwrap().dist();
let d: BigRational = expr1.distance(&expr2);
assert_eq!(d.to_string(), "25/54")

fn distance_max(&self, other: &DenseDist<T>) -> T

Distance between two distributions, measured by maximum elementwise difference of probabilities

use diceystats::{
    dices::DiceFormula,
    dist::{DenseDist, Dist},
};
use num::BigRational;

let expr1: DenseDist<_> = "d4xd3".parse::<DiceFormula>().unwrap().dist();
let expr2: DenseDist<_> = "d4+d6".parse::<DiceFormula>().unwrap().dist();
let d: BigRational = expr1.distance_max(&expr2);
assert_eq!(d.to_string(), "1/12");

fn evaluator() -> impl Evaluator<Self>

fn new_constant(n: isize) -> Self

New constant distribution, n has a 100% chance of occuring.

fn iter_enumerate<'a>(&'a self) -> impl Iterator<Item = (isize, &'a T)>

where T: 'a,

Iteratete through the distribution’s support, in order.

fn min_value(&self) -> isize

fn max_value(&self) -> isize

fn new_uniform(min: isize, max: isize) -> Self

New uniform distribution from min to, and including, max.

fn mean(&self) -> T

The expected value of the distribution.

fn variance(&self) -> T

The variance of the distribution

fn median(&self) -> isize

The median of the distribution; an x such that P(X <= m) >= 0.5 and P(m <= X) >= 0.5.

fn modes(&self) -> Vec<isize>

The modes of the distribution, i.e. the values of the distribution with the highest chance of occuring.

impl<T: Hash> Hash for DenseDist<T>

fn hash<__H: Hasher>(&self, state: &mut __H)

Feeds this value into the given Hasher.

fn hash_slice<H>(data: &[Self], state: &mut H)

where H: Hasher, Self: Sized,

Feeds a slice of this type into the given Hasher.

impl<T: Ord> Ord for DenseDist<T>

fn cmp(&self, other: &DenseDist<T>) -> Ordering

This method returns an Ordering between self and other.

fn max(self, other: Self) -> Self

where Self: Sized,

Compares and returns the maximum of two values.

fn min(self, other: Self) -> Self

where Self: Sized,

Compares and returns the minimum of two values.

fn clamp(self, min: Self, max: Self) -> Self

where Self: Sized,

Restrict a value to a certain interval.

impl<T: PartialEq> PartialEq for DenseDist<T>

fn eq(&self, other: &DenseDist<T>) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl<T: PartialOrd> PartialOrd for DenseDist<T>

fn partial_cmp(&self, other: &DenseDist<T>) -> Option<Ordering>

This method returns an ordering between self and other values if one exists.

fn lt(&self, other: &Rhs) -> bool

Tests less than (for self and other) and is used by the < operator.

fn le(&self, other: &Rhs) -> bool

Tests less than or equal to (for self and other) and is used by the <= operator.

fn gt(&self, other: &Rhs) -> bool

Tests greater than (for self and other) and is used by the > operator.

fn ge(&self, other: &Rhs) -> bool

Tests greater than or equal to (for self and other) and is used by the >= operator.

impl<T> Serialize for DenseDist<T>

where T: Serialize,

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

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl<T: Eq> Eq for DenseDist<T>

impl<T> StructuralPartialEq for DenseDist<T>