blob: d4f9517dd1c88664af0f2f027973f0369fd13322 (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
|
<?xml version="1.0" encoding="UTF-8" ?>
<class name="RandomNumberGenerator" inherits="Reference" version="4.0">
<brief_description>
A class for generating pseudo-random numbers.
</brief_description>
<description>
RandomNumberGenerator is a class for generating pseudo-random numbers. It currently uses [url=http://www.pcg-random.org/]PCG32[/url].
[b]Note:[/b] The underlying algorithm is an implementation detail. As a result, it should not be depended upon for reproducible random streams across Godot versions.
To generate a random float number (within a given range) based on a time-dependant seed:
[codeblock]
var rng = RandomNumberGenerator.new()
func _ready():
rng.randomize()
var my_random_number = rng.randf_range(-10.0, 10.0)
[/codeblock]
</description>
<tutorials>
<link title="Random number generation">https://docs.godotengine.org/en/latest/tutorials/math/random_number_generation.html</link>
</tutorials>
<methods>
<method name="randf">
<return type="float">
</return>
<description>
Generates a pseudo-random float between [code]0.0[/code] and [code]1.0[/code] (inclusive).
</description>
</method>
<method name="randf_range">
<return type="float">
</return>
<argument index="0" name="from" type="float">
</argument>
<argument index="1" name="to" type="float">
</argument>
<description>
Generates a pseudo-random float between [code]from[/code] and [code]to[/code] (inclusive).
</description>
</method>
<method name="randfn">
<return type="float">
</return>
<argument index="0" name="mean" type="float" default="0.0">
</argument>
<argument index="1" name="deviation" type="float" default="1.0">
</argument>
<description>
Generates a [url=https://en.wikipedia.org/wiki/Normal_distribution]normally-distributed[/url] pseudo-random number, using Box-Muller transform with the specified [code]mean[/code] and a standard [code]deviation[/code]. This is also called Gaussian distribution.
</description>
</method>
<method name="randi">
<return type="int">
</return>
<description>
Generates a pseudo-random 32-bit unsigned integer between [code]0[/code] and [code]4294967295[/code] (inclusive).
</description>
</method>
<method name="randi_range">
<return type="int">
</return>
<argument index="0" name="from" type="int">
</argument>
<argument index="1" name="to" type="int">
</argument>
<description>
Generates a pseudo-random 32-bit signed integer between [code]from[/code] and [code]to[/code] (inclusive).
</description>
</method>
<method name="randomize">
<return type="void">
</return>
<description>
Setups a time-based seed to generator.
</description>
</method>
</methods>
<members>
<member name="seed" type="int" setter="set_seed" getter="get_seed" default="-6398989897141750821">
The seed used by the random number generator. A given seed will give a reproducible sequence of pseudo-random numbers.
[b]Note:[/b] The RNG does not have an avalanche effect, and can output similar random streams given similar seeds. Consider using a hash function to improve your seed quality if they're sourced externally.
</member>
</members>
<constants>
</constants>
</class>
|