WeightedRandom.Backend behaviour (weighted_random v1.0.0-alpha.1)

WeightedRandom.Backend offers a contract to all who implement it:

The main WeightedRandom package presents a novel interface for generating a list of probabilities (floats that can be summed to equal exactly 1.0).
The custom Backend module decides what to do with those probabilities once they are generated.

Summary

Types

backend_opts()

index()

indices()

opts()

percentage()

probability_type()

t()

table()

weight()

weights()

Callbacks

options()

Optionally provide the opts kwli

preprocess(input, opts)

weights is a list of floats which, if summed, would equal exactly 1.0. Each float represents the probability of being selected in the random sample.

take(table, count)

Given the struct returned by preprocess/2, return a list of random indices equal to count.

Functions

list_probability_types()

preprocess(backend, input, opts)

take(map, count)

Types

backend_opts()

@type backend_opts() :: [{:probability_type, probability_type()}]

index()

@type index() :: integer()

indices()

@type indices() :: [index()]

opts()

@type opts() :: keyword()

percentage()

@type percentage() :: float()

probability_type()

@type probability_type() :: :weights | :probabilities

t()

@type t() :: %WeightedRandom.Backend{
  backend: atom(),
  outcomes: list(),
  table: struct()
}

table()

@type table() :: struct()

weight()

@type weight() :: WeightedRandom.Input.Weight.t()

weights()

@type weights() :: [weight()]

Callbacks

options()

(optional)

@callback options() :: keyword()

Optionally provide the opts kwli

preprocess(input, opts)

@callback preprocess(input :: WeightedRandom.Input.t(), opts :: opts()) :: table()

weights is a list of floats which, if summed, would equal exactly 1.0. Each float represents the probability of being selected in the random sample.

So if given [0.25, 0.25, 0.5], then index 2 is twice as likely to be sampled as index 1.

This function must return some kind of struct that will later be passed into take/2.

take(table, count)

@callback take(table :: struct(), count :: integer()) :: indices :: [index :: integer()]

Given the struct returned by preprocess/2, return a list of random indices equal to count.

Functions

list_probability_types()

preprocess(backend, input, opts)

take(map, count)