Add rand-bool, rand-gaussian, rand-gaussian-int.
| author |
Steve Losh <steve@stevelosh.com> |
| date |
Thu, 08 Nov 2012 12:50:43 -0500 |
| parents |
3c3a3292e0db |
| children |
7f169e926d8b |
Usage
=====
Roul currently contains a few functions in one namespace. It'll expand in the
future, but for now that's all it is.
[TOC]
roul.random
-----------
The `roul.random` namespace contains wrappers around some of Clojure's built-in
random functions to make them more user friendly, as well as some uniqe
functions of its own.
The recommended way is to `require` this namespace into your own instead of
overwriting Clojure's builtins:
:::clojure
(ns foo.core
(:require [roul.random :as rr]))
; or
(require '[roul.random :as rr])
### rand
:::clojure
(rand) ; return a float in [0, 1)
(rand end) ; return a float in [0, end)
(rand start end) ; return a float in [start, end)
A wrapper around the built-in `rand`. Returns a random floating point number
between `start` (inclusive) and `end` (exclusive).
If not given, `start` defaults to `0` and `end` defaults to `1`.
### rand-int
:::clojure
(rand-int end) ; return an int in [0, end)
(rand-int start end) ; return an int in [start, end)
A wrapper around the built-in `rand-int`. Returns a random integer between
`start` (inclusive) and `end` (exclusive).
If not given, `start` defaults to `0`.
### rand-nth
:::clojure
(rand-nth coll) ; return a random element of coll
A wrapper around the built-in `rand-nth`. Returns a random element of the given
collection.
This is a transparent wrapper around the builtin, included only for
completeness. Unlike the other wrappers no new functionality has been added
(yet).
### rand-nth-weighted
:::clojure
(rand-nth-weighted coll) ; return a random element of coll
Returns a random element of a weighted collection.
A weighted collection can be any seq of `[choice, weight]` elements. The
weights can be arbitrary numbers -- they do not need to add up to anything
specific.
:::clojure
; Returns coffee roughly 80% of the time, tea 15%, and soda 5%.
(rr/rand-nth-weighted {:coffee 0.80, :tea 0.15, :soda 0.05})
; Returns cats roughly twice as often as boots.
(rr/rand-nth-weighted [[:boots 14]
[:cats 28]])
### rand-bool
:::clojure
(rand-bool) ; return true or false
(rand-bool percent) ; return true the given percent of the time, false the rest
Returns `true` or `false` randomly.
`percent` can be an integer or a float like `20` or `39.2`. If given, `true`
will be returned that percent of the time (and `false` the rest).
If percent is not given it defaults to `50` (an equal chance for `true` and
`false`).
### rand-gaussian
:::clojure
(rand-gaussian)
(rand-gaussian mean standard-deviation)
(rand-gaussian mean standard-deviation upper-bound lower-bound)
Return a random float taken from a Gaussian distribution with the given mean and
standard deviation.
`mean` defaults to 0.
`standard-deviation` defaults to 1.
A lower and upper bound can be specified if desired, which will clamp the output
of this function to those bounds. Note that this clamping does NOT adjust the
distribution, so if you clamp too tightly you'll get a disproportionate number
of the boundary values. It's just here to give you a way to prevent garbage
values.
:::clojure
; Generate an [x, y] pair with Gaussian-distributed values.
; The x value here is clamped between 0 and graph-width.
(let [x (rand-gaussian 100 20 0 graph-width)
y (rand-gaussian 200 40)]
...)
### rand-gaussian-int
:::clojure
(rand-gaussian)
(rand-gaussian mean standard-deviation)
(rand-gaussian mean standard-deviation upper-bound lower-bound)
Return a random int taken from a Gaussian distribution with the given mean and
standard deviation.
`mean` defaults to 0.
`standard-deviation` defaults to 1.
A lower and upper bound can be specified if desired, which will clamp the output
of this function to those bounds. Note that this clamping does NOT adjust the
distribution, so if you clamp too tightly you'll get a disproportionate number
of the boundary values. It's just here to give you a way to prevent garbage
values.
:::clojure
; Generate an [x, y] pair with Gaussian-distributed values.
; The x value here is clamped between 0 and graph-width.
(let [x (rand-gaussian 100 20 0 graph-width)
y (rand-gaussian 200 40)]
...)