Protocols

A pseudo-random number generator (PRNG).

Reference types that conform to PRNG are infinite sequences of pseudo-random elements. Protocol extension methods iterate over such a sequence as necessary to generate pseudo-random values from the desired distribution.

Considerations for Conforming Types

For clarity to end users, custom PRNGs may be implemented in an extension to Random. For instance, the xoroshiro128+ algorithm is implemented in a final class named Random.Xoroshiro.

The static methods _entropy(_:) and _entropy(_:count:) return cryptographically secure random bytes that may be useful for seeding your custom PRNG. However, these methods may return nil if the requested number of random bytes is not available, and they are not recommended as a routine source of random data.

Adding Other Probability Distributions

Many built-in protocol extension methods make use of the primitive, overloaded method _random(_:bitCount:). You may wish to use the same method in new protocol extension methods that return pseudo-random values from other probability distributions.

The method _random(_:bitCount:) generates uniformly distributed binary floating-point values in the half-open range [0, 1) with a precision of either bitCount or the significand bit count of the floating-point type, whichever is less. Additionally, this method generates uniformly distributed unsigned integers in the half-open range [0, 2 ** x), where ** is the exponentiation operator and x is the lesser of bitCount and the bit width of the integer type.

For end users, however, the recommended spelling for a uniformly distributed numeric value is uniform(); that method is overloaded to permit custom minimum and maximum values for the uniform distribution.

A floating-point type that supports elementary functions and a selection of special functions.

The Real protocol provides a suitable basis for writing functions that work on any floating-point type that supports the required functions.

A signed numeric type that supports elementary functions.

The Math protocol provides a suitable basis for writing functions that work on any real or complex floating-point type that supports the required functions.