This file defines the basic pseudorandom number generation functionality used by the core library, as well as functions to sample from a number of built-in distributions such as categorical, discrete uniform, continuous uniform, Bernoulli, geometric, beta, gamma, and Dirichlet.
| Classes, functions, and variables in this file | |
|---|---|
| unsigned int | get_seed () |
| void | set_seed (unsigned int new_seed) |
| bool | read_random_state (Stream & in) |
| bool | write_random_state (Stream & out) |
| unsigned int | sample_categorical (V * probability, unsigned int length) |
| unsigned int | select_categorical (const U * probability, V random, unsigned int length) |
| unsigned int | sample_categorical (const V * probability, V sum, unsigned int length) |
| unsigned int | sample_categorical (const unsigned int * probability, unsigned int sum, unsigned int length) |
| unsigned int | sample_uniform (unsigned int n) |
| const T & | sample_uniform (const T * elements, unsigned int length) |
| const T & | sample_uniform (const T (&elements)[N]) |
| const T & | sample_uniform (const array< T > & elements) |
| V | sample_uniform () |
| bool | sample_bernoulli (const V & p) |
| unsigned int | sample_geometric (const V & p) |
| double | log_probability_negative_binomial (unsigned int x, const V & r, const V & p) |
| V | sample_beta (const V & alpha) |
| V | sample_beta (const V & alpha, const V & beta) |
| V | sample_gamma (const V & alpha, const V & beta) |
| V | log_probability_gamma (const V & x, const V & alpha, const V & beta) |
| void | sample_dirichlet (V * dst, const V * alpha, unsigned int length) |
Returns the initial random seed used by all core functions that require pseudorandom number generation.
| unsigned int | new_seed | ) |
Sets the seed of the underlying pseudorandom number generator.
Reads the state of the pseudorandom number generator from in. This is useful to persist the state of the pseudorandom number generator.
Writes the state of the pseudorandom number generator to out. This is useful to persist the state of the pseudorandom number generator.
Samples from a categorical distribution, where the unnormalized probability of returning the index i is given by probability[i]. This function normalizes and overwrites probability with its cumulative distribution function.
| const U * | probability, | |
| V | random, | |
| unsigned int | length | ) |
Returns the smallest index i such that random < sum from j=0 to i-1 of probability[j]. Thus, this function implements the inverse cumulative distribution function for the categorical distribution with unnormalized probabilities given by probability.
| const V * | probability, | |
| V | sum, | |
| unsigned int | length | ) |
Samples from a categorical distribution, where the unnormalized probability of returning the index i is given by probability[i] and its sum is given by the floating-point sum. This function doesn't modify probability.
| const unsigned int * | probability, | |
| unsigned int | sum, | |
| unsigned int | length | ) |
Samples from a categorical distribution, where the unnormalized probability of returning the index i is given by probability[i] and its sum is given by the unsigned integer sum. This function doesn't modify probability.
| unsigned int | n | ) |
Returns a sample from the discrete uniform distribution over {0, ..., n - 1}.
Returns a sample from the discrete uniform distribution over elements.
Returns a sample from the discrete uniform distribution over elements.
Returns a sample from the discrete uniform distribution over elements.
Returns a sample from the continuous uniform distribution over [0, 1].
Returns a sample from the Bernoulli distribution: with probability 0.5, true is returned, otherwise false is returned.
Returns a sample from the geometric distribution with success probability p.
| unsigned int | x, | |
| const V & | r, | |
| const V & | p | ) |
Returns a sample from the negative binomial distribution with number of failures r and success probability p.
Returns a sample from the beta distribution with shape parameter alpha and scale parameter 1. This function assumes alpha > 0.
Returns a sample from the beta distribution with shape parameter alpha and scale parameter beta. This function assumes alpha > 0 and beta > 0.
Returns a sample from the gamma distribution with shape parameter alpha and rate parameter beta. This function assumes alpha > 0 and beta > 0.
Returns the log probability of drawing the observation x from a gamma distribution with shape parameter alpha and rate parameter beta. This function assumes x > 0, alpha > 0, and beta > 0.
Samples from the Dirichlet distribution with parameter alpha and dimension length. The sample is written to dst. This function assumes dst has size at least length, alpha[i] > 0 for all i = 0, ..., length - 1.