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authorRaimo Niskanen <[email protected]>2017-09-18 09:34:37 +0200
committerRaimo Niskanen <[email protected]>2017-09-18 09:34:37 +0200
commitea932523ae4df7c14ad85a6a993e9dda3bc6c025 (patch)
tree0b762cab5370480d3f36072e9a7c54841b9a54a4 /lib/stdlib
parent3db1b77f9d4f8b16cbc8aee764c81453603795d4 (diff)
parent7834f361c3bbec88ef562aed3060d1c07c8f7c11 (diff)
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Merge branch 'maint'
Diffstat (limited to 'lib/stdlib')
-rw-r--r--lib/stdlib/doc/src/rand.xml77
1 files changed, 67 insertions, 10 deletions
diff --git a/lib/stdlib/doc/src/rand.xml b/lib/stdlib/doc/src/rand.xml
index a68fb7d55f..89fb858823 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 =&lt; <anno>X</anno> &lt; 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 &lt; <anno>X</anno> =&lt; 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 =&lt;
- <anno>X</anno> &lt; 1.0</c> and a new state.</p>
+ <anno>X</anno> &lt; 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 &lt; <anno>X</anno> =&lt; 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>