Struct compress::entropy::ari::bin::Model

pub struct Model {
    pub rate: Border,
    // some fields omitted
}

A binary value frequency model

Fields

rate: Border

learning rate

Implementations

impl Model

pub fn new_flat(threshold: Border, rate: Border) -> Model

Create a new flat (50/50 probability) instance

pub fn new_custom(zero_percent: u8, threshold: Border, rate: Border) -> Model

Create a new instance with a given percentage for zeroes

pub fn reset_flat(&mut self)

Reset the model to 50/50 distribution

pub fn get_probability_zero(&self) -> Border

Return the probability of 0

pub fn get_probability_one(&self) -> Border

Return the probability of 1

pub fn update_zero(&mut self)

Update the frequency of zero

pub fn update_one(&mut self)

Update the frequency of one

pub fn update(&mut self, value: bool)

Update frequencies in favor of given 'value' Lower factors produce more aggressive updates

Trait Implementations

impl Model<bool> for Model

fn get_range(&self, value: bool) -> (Border, Border)

Get the probability range of a value

fn find_value(&self, offset: Border) -> (bool, Border, Border)

Find the value by a given probability offset, return with the range

fn get_denominator(&self) -> Border

Get the sum of all probabilities

fn encode(&self, value: V, re: &mut RangeEncoder, out: &mut [Symbol]) -> usize

Encode a value using a range encoder return the number of symbols written

fn decode(&self, code: Border, re: &mut RangeEncoder) -> (V, usize)

Decode a value using given 'code' on the range encoder return a (value, num_symbols_to_shift) pair