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**NAME**

random - Pseudo-random number generation.

**DESCRIPTION**

This module provides a random number generator. The method is attributed to B.A. Wichmann and I.D. Hill in 'An efficient and portable pseudo-random number generator', Journal of Applied Statistics. AS183. 1982. Also Byte March 1987. The algorithm is a modification of the version attributed to Richard A. O'Keefe in the standard Prolog library. Every time a random number is requested, a state is used to calculate it, and a new state is produced. The state can either be implicit (kept in the process dictionary) or be an explicit argument and return value. In this implementation, the state (the typeran()) consists of a tuple of three integers.Note:This random number generator is not cryptographically strong. If a strong cryptographic random number generator is needed, use one of functions in thecryptomodule, for example,crypto:strong_rand_bytes/1.Note:The improvedrandmodule is to be used instead of this module.

**DATA** **TYPES**

ran()= {integer(), integer(), integer()} The state.

**EXPORTS**

seed()->ran()Seeds random number generation with default (fixed) values in the process dictionary and returns the old state.seed(SValue)->undefined|ran()Types: SValue = {A1, A2, A3} | integer() A1 = A2 = A3 = integer()seed({A1,A2,A3})is equivalent toseed(A1,A2,A3).seed(A1,A2,A3)->undefined|ran()Types: A1 = A2 = A3 = integer() Seeds random number generation with integer values in the process dictionary and returns the old state. The following is an easy way of obtaining a unique value to seed with: random:seed(erlang:phash2([node()]), erlang:monotonic_time(), erlang:unique_integer()) For details, seeerlang:phash2/1,erlang:node/0,erlang:monotonic_time/0, anderlang:unique_integer/0.seed0()->ran()Returns the default state.uniform()->float()Returns a random float uniformly distributed between0.0and1.0, updating the state in the process dictionary.uniform(N)->integer()>=1Types: N = integer() >= 1 Returns, for a specified integerN>=1, a random integer uniformly distributed between1andN, updating the state in the process dictionary.uniform_s(State0)->{float(),State1}Types: State0 = State1 =ran()Returns, for a specified state, a random float uniformly distributed between0.0and1.0, and a new state.uniform_s(N,State0)->{integer(),State1}Types: N = integer() >= 1 State0 = State1 =ran()Returns, for a specified integerN>=1and a state, a random integer uniformly distributed between1andN, and a new state.

**NOTE**

Some of the functions use the process dictionary variablerandom_seedto remember the current seed. If a process callsuniform/0oruniform/1without setting a seed first,seed/0is called automatically. The implementation changed in Erlang/OTP R15. Upgrading to R15 breaks applications that expect a specific output for a specified seed. The output is still deterministic number series, but different compared to releases older than R15. Seed{0,0,0}does, for example, no longer produce a flawed series of only zeros.