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Add a random number generation tutorial
This closes #2436.
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@@ -10,3 +10,4 @@ Math | |
matrices_and_transforms | ||
interpolation | ||
beziers_and_curves | ||
random_number_generation |
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.. _doc_random_number_generation: | ||
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Random number generation | ||
======================== | ||
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Many games rely on randomness to implement core game mechanics. This tutorial | ||
guides you through common types of randomness and how to implement them in | ||
Godot. | ||
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.. note:: | ||
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Computers cannot generate "true" random numbers. Instead, they rely on | ||
`psuedorandom number generators <https://en.wikipedia.org/wiki/Pseudorandom_number_generator>`__ | ||
(PRNGs). | ||
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Global scope versus RandomNumberGenerator class | ||
----------------------------------------------- | ||
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Godot exposes two ways to generate random numbers: via *global scope* methods | ||
or using the :ref:`class_RandomNumberGenerator` class. | ||
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Global scope methods are easier to set up, but they don't offer as much control. | ||
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RandomNumberGenerator requires more code to use, but exposes many methods not | ||
found in global scope such as | ||
:ref:`randi_range() <class_RandomNumberGenerator_method_randi_range>` and | ||
:ref:`randfn() <class_RandomNumberGenerator_method_randfn>`. On top of that, | ||
it allows creating multiple instances each with their own seed. | ||
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This tutorial uses global scope methods, except when the method is only found in | ||
the RandomNumberGenerator class. | ||
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The randomize() method | ||
---------------------- | ||
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In global scope, you can find a :ref:`randomize() <class_@GDScript_method_randomize>` | ||
method. | ||
**This method should be called only once when your project starts to initialize | ||
the random seed.** Calling it multiple times is unnecessary and may impact | ||
performance negatively. | ||
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Putting it in your main scene script's ``_ready()`` method is a good choice:: | ||
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func _ready(): | ||
randomize() | ||
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You can also set a fixed random seed instead using | ||
:ref:`seed() <class_@GDScript_method_seed>`. This will give you *deterministic* | ||
results across runs:: | ||
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func _ready(): | ||
seed(12345) | ||
# To use a string as a seed, you can hash it to a number. | ||
seed("Hello world".hash()) | ||
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When using the RandomNumberGenerator class, you should call ``randomize()`` | ||
on the instance since it has its own seed:: | ||
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var rng = RandomNumberGenerator.new() | ||
rng.randomize() | ||
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Get a random number | ||
------------------- | ||
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Godot provides several methods to get random numbers. | ||
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:ref:`randi() <class_@GDScript_method_randi>` returns a random number between 0 | ||
and 2^32-1. Since the maximum value is really high, you most likely want to use | ||
the modulo operator (``%``) to bound the result between 0 and the denominator:: | ||
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# Prints a random integer between 0 and 49. | ||
print(randi() % 50) | ||
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# Prints a random integer between 10 and 60. | ||
print(randi() % 51 + 10) | ||
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:ref:`randf() <class_@GDScript_method_randf>` returns a random floating-point number | ||
between 0 and 1. This is useful to implement a | ||
:ref:`doc_random_number_generation_weighted_random_probability` system, among | ||
other things. | ||
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:ref:`randfn() <class_RandomNumberGenerator_method_randfn>` returns a random floating-point | ||
number between 0 and 1. Unlike :ref:`randf() <class_@GDScript_method_randf>` which follows | ||
an uniform distribution, the returned number follows a | ||
`normal distribution <https://en.wikipedia.org/wiki/Normal_distribution>`__. | ||
This means the returned value is more likely to be around 0.5 compared to the | ||
extreme bounds (0 and 1):: | ||
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# Prints a normally distributed floating-point number between 0.0 and 1.0. | ||
var rng = RandomNumberGenerator.new() | ||
rng.randomize() | ||
print(rng.randfn()) | ||
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:ref:`rand_range() <class_@GDScript_method_rand_range>` takes two arguments ``from`` and | ||
``to``, and returns a random floating-point number between ``from`` and ``to``:: | ||
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# Prints a random floating-point number between -4 and 6.5. | ||
print(rand_range(-4, 6.5)) | ||
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:ref:`RandomNumberGenerator.randi_range() <class_RandomNumberGenerator_method_randi_range>` | ||
takes two arguments ``from`` and ``to``, and returns a random integer between | ||
``from`` and ``to``:: | ||
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# Prints a random floating-point number between -10 and 10. | ||
var rng = RandomNumberGenerator.new() | ||
rng.randomize() | ||
print(rng.randi_range(-10, 10) | ||
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Get a random array element | ||
-------------------------- | ||
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We can use random integer generation to get a random element from an array:: | ||
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var fruits = ["apple", "orange", "pear", "banana"] | ||
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func _ready(): | ||
randomize() | ||
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for i in 100: | ||
# Pick 100 fruits randomly. | ||
# (``for i in 100`` is a faster shorthand for ``for i in range(100)``.) | ||
print(get_fruit()) | ||
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func get_fruit(): | ||
var random_fruit = fruits[randi() % fruits.size()] | ||
# Returns "apple", "orange", "pear", or "banana" every time the code is run. | ||
# The same fruit may be selected multiple times in succession. | ||
return random_fruit | ||
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To prevent the same fruit from being picked more than once in a row, we can add more | ||
logic to this method:: | ||
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var fruits = ["apple", "orange", "pear", "banana"] | ||
var last_fruit = "" | ||
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func _ready(): | ||
randomize() | ||
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for i in 100: | ||
# Pick 100 fruits randomly. | ||
# (``for i in 100`` is a faster shorthand for ``for i in range(100)``.) | ||
print(get_fruit()) | ||
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func get_fruit(): | ||
var random_fruit = fruits[randi() % fruits.size()] | ||
while random_fruit == last_fruit: | ||
# The last fruit was picked, try again until we get a different fruit. | ||
random_fruit = fruits[randi() % fruits.size()] | ||
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# Note: If the random element to pick is passed by reference | ||
# (such as an array or dictionary), | ||
# use `last_fruit = random_fruit.duplicate()` instead. | ||
last_fruit = random_fruit | ||
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# Returns "apple", "orange", "pear", or "banana" every time the code is run. | ||
# The same fruit will never be returned more than once in a row. | ||
return random_fruit | ||
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This approach can be useful to make random number generation feel less | ||
repetitive, but it doesn't prevent results from "ping-ponging" between a limited | ||
set of values. To prevent this, use the | ||
:ref:`shuffle bag <doc_random_number_generation_shuffle_bags>` pattern instead. | ||
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Get a random dictionary value | ||
----------------------------- | ||
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We can apply similar logic from arrays to dictionaries as well:: | ||
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var metals = { | ||
"copper": {"quantity": 50, "price": 50}, | ||
"silver": {"quantity": 20, "price": 150}, | ||
"gold": {"quantity": 3, "price": 500}, | ||
} | ||
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func _ready(): | ||
randomize() | ||
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for i in 20: | ||
print(get_metal()) | ||
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func get_metal(): | ||
var random_metal = metals.values()[randi() % metals.size()] | ||
# Returns a random metal value dictionary every time the code is run. | ||
# The same metal may be selected multiple times in succession. | ||
return random_metal | ||
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.. _doc_random_number_generation_weighted_random_probability: | ||
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Weighted random probability | ||
--------------------------- | ||
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The :ref:`randf() <class_@GDScript_method_randf>` method returns a floating-point number | ||
between 0.0 and 1.0. We can use this to create a "weighted" probability where | ||
different outcomes have different likelihoods:: | ||
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func _ready(): | ||
randomize() | ||
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for i in 100: | ||
print(get_item_rarity()) | ||
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func get_item_rarity(): | ||
var random_float = randf() | ||
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if random_float < 0.8: | ||
# 80% chance of being returned. | ||
return "Common" | ||
elif random_float < 0.95: | ||
# 15% chance of being returned. | ||
return "Uncommon" | ||
else: | ||
# 5% chance of being returned. | ||
return "Rare" | ||
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.. _doc_random_number_generation_shuffle_bags: | ||
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"Better" randomness using shuffle bags | ||
-------------------------------------- | ||
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Taking the same exemple as above, we would like to pick fruits at random. | ||
However, relying on random number generation every time a fruit is selected can | ||
lead to a less *uniform* distribution. If the player is lucky (or unlucky), they | ||
could get the same fruit 3 or more times in a row. | ||
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This can be accomplished by using the *shuffle bag* pattern. It works by | ||
removing the element from the array once it has been chosen. If this is done | ||
multiple times, the array might end up being empty. In this case, its value is | ||
reinitialized to its default state where it's full:: | ||
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var fruits = ["apple", "orange", "pear", "banana"] | ||
# A copy of the fruits array so we can restore the original value into `fruits`. | ||
var fruits_full = [] | ||
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func _ready(): | ||
randomize() | ||
fruits_full = fruits.duplicate() | ||
fruits.shuffle() | ||
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for i in 100: | ||
print(get_fruit()) | ||
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func get_fruit(): | ||
if fruits.empty(): | ||
# Fill the fruits array again and shuffle it. | ||
fruits = fruits_full.duplicate() | ||
fruits.shuffle() | ||
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# Get a random fruit (since the array has been suffled) | ||
# and remove it from the `fruits` array. | ||
var random_fruit = fruits.pop_front() | ||
# Prints "apple", "orange", "pear", or "banana" every time the code is run. | ||
return random_fruit | ||
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When running the above code, the same fruit will *never* be picked more than | ||
twice in a row. This is because once a fruit has been picked, it will no longer | ||
be a possible return value unless the array is now empty. When the array is | ||
empty, we reset it back to its full state, which makes it possible to have the | ||
same fruit again (but only once). | ||
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Random noise | ||
------------ | ||
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The random number generation shown above can show its limits when you need a | ||
value that *slowly* changes depending on the input. (The input can be a | ||
position, time, or anything else.) | ||
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To achieve this, you can use random *noise* functions. Noise functions are | ||
especially poopular in producedural generation to generate realistic-looking | ||
terrain. Godot provides :ref:`class_opensimplexnoise` for this, which supports | ||
1D, 2D, 3D, and 4D noise. Here's an example with 1D noise:: | ||
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var noise = OpenSimplexNoise.new() | ||
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func _ready(): | ||
randomize() | ||
# Configure the OpenSimplexNoise instance. | ||
noise.seed = randi() | ||
noise.octaves = 4 | ||
noise.period = 20.0 | ||
noise.persistence = 0.8 | ||
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for i in 100: | ||
# Prints a slowly-changing series of floating-point numbers | ||
# between -1.0 and 1.0. | ||
print(noise.get_noise_1d(i)) |