diff options
Diffstat (limited to 'lib/stdlib/doc')
| -rw-r--r-- | lib/stdlib/doc/src/rand.xml | 77 |
1 files changed, 67 insertions, 10 deletions
diff --git a/lib/stdlib/doc/src/rand.xml b/lib/stdlib/doc/src/rand.xml index e06d7e467d..563ca0b268 100644 --- a/lib/stdlib/doc/src/rand.xml +++ b/lib/stdlib/doc/src/rand.xml @@ -35,12 +35,19 @@ <module>rand</module> <modulesummary>Pseudo random number generation.</modulesummary> <description> - <p>This module provides a random number generator. The module contains - a number of algorithms. The uniform distribution algorithms use the - <url href="http://xorshift.di.unimi.it">scrambled Xorshift algorithms by - Sebastiano Vigna</url>. The normal distribution algorithm uses the - <url href="http://www.jstatsoft.org/v05/i08">Ziggurat Method by Marsaglia - and Tsang</url>.</p> + <p> + This module provides a pseudo random number generator. + The module contains a number of algorithms. + The uniform distribution algorithms use the + <url href="http://xorshift.di.unimi.it"> + xoroshiro116+ and xorshift1024* algorithms by Sebastiano Vigna. + </url> + The normal distribution algorithm uses the + <url href="http://www.jstatsoft.org/v05/i08"> + Ziggurat Method by Marsaglia and Tsang + </url> + on top of the uniform distribution algorithm. + </p> <p>For some algorithms, jump functions are provided for generating non-overlapping sequences for parallel computations. The jump functions perform calculations @@ -393,9 +400,34 @@ tests. We suggest to use a sign test to extract a random Boolean value.</pre> <name name="uniform" arity="0"/> <fsummary>Return a random float.</fsummary> <desc><marker id="uniform-0"/> - <p>Returns a random float uniformly distributed in the value + <p> + Returns a random float uniformly distributed in the value range <c>0.0 =< <anno>X</anno> < 1.0</c> and - updates the state in the process dictionary.</p> + updates the state in the process dictionary. + </p> + <p> + The generated numbers are on the form N * 2.0^(-53), + that is; equally spaced in the interval. + </p> + <warning> + <p> + This function may return exactly <c>0.0</c> which can be + fatal for certain applications. If that is undesired + you can use <c>(1.0 - rand:uniform())</c> to get the + interval <c>0.0 < <anno>X</anno> =< 1.0</c>. + </p> + <p> + If neither endpoint is desired you can test and re-try + like this: + </p> + <pre> +my_uniform() -> + case rand:uniform() of + 0.0 -> my_uniform(); + X -> X + end +end.</pre> + </warning> </desc> </func> @@ -414,9 +446,34 @@ tests. We suggest to use a sign test to extract a random Boolean value.</pre> <name name="uniform_s" arity="1"/> <fsummary>Return a random float.</fsummary> <desc> - <p>Returns, for a specified state, random float + <p> + Returns, for a specified state, random float uniformly distributed in the value range <c>0.0 =< - <anno>X</anno> < 1.0</c> and a new state.</p> + <anno>X</anno> < 1.0</c> and a new state. + </p> + <p> + The generated numbers are on the form N * 2.0^(-53), + that is; equally spaced in the interval. + </p> + <warning> + <p> + This function may return exactly <c>0.0</c> which can be + fatal for certain applications. If that is undesired + you can use <c>(1.0 - rand:uniform(State))</c> to get the + interval <c>0.0 < <anno>X</anno> =< 1.0</c>. + </p> + <p> + If neither endpoint is desired you can test and re-try + like this: + </p> + <pre> +my_uniform(State) -> + case rand:uniform(State) of + {0.0, NewState} -> my_uniform(NewState); + Result -> Result + end +end.</pre> + </warning> </desc> </func> |