RandomNumberGenerator

提供生成偽亂數的方法。

說明

RandomNumberGenerator is a class for generating pseudo-random numbers. It currently uses PCG32.

Note: The underlying algorithm is an implementation detail and should not be depended upon.

To generate a random float number (within a given range) based on a time-dependent seed:

var rng = RandomNumberGenerator.new()
func _ready():
    var my_random_number = rng.randf_range(-10.0, 10.0)

教學

亂數產生

屬性

int	seed	`0`
int	state	`0`

方法

int	rand_weighted(weights: PackedFloat32Array)
float	randf()
float	randf_range(from: float, to: float)
float	randfn(mean: float = 0.0, deviation: float = 1.0)
int	randi()
int	randi_range(from: int, to: int)
void	randomize()

屬性說明

int seed = 0 🔗

void set_seed(value: int)
int get_seed()

根據給定的種子值初始化亂數產生器狀態。給定的種子將給出一個可重現的偽亂數序列。

注意：RNG 沒有雪崩效應，給定相似的種子可以輸出相似的隨機流。如果種子來自外部，請考慮使用雜湊函式來提高種子品質。

注意：設定該屬性會產生改變內部 state 的副作用，因此請確保在修改 state 之前初始化種子：

注意：該屬性的預設值是偽隨機的，會在呼叫 randomize() 時改變。文檔中記錄的 0 是預留位置，不是實際的預設種子。

var rng = RandomNumberGenerator.new()
rng.seed = hash("Godot")
rng.state = 100 # 恢復到之前保存的一些狀態。

int state = 0 🔗

void set_state(value: int)
int get_state()

The current state of the random number generator. Save and restore this property to restore the generator to a previous state:

var rng = RandomNumberGenerator.new()
print(rng.randf())
var saved_state = rng.state # Store current state.
print(rng.randf()) # Advance internal state.
rng.state = saved_state # Restore the state.
print(rng.randf()) # Prints the same value as previously.

Note: Do not set state to arbitrary values, since the random number generator requires the state to have certain qualities to behave properly. It should only be set to values that came from the state property itself. To initialize the random number generator with arbitrary input, use seed instead.

Note: The default value of this property is pseudo-random, and changes when calling randomize(). The 0 value documented here is a placeholder, and not the actual default state.

方法說明

int rand_weighted(weights: PackedFloat32Array) 🔗

Returns a random index with non-uniform weights. Prints an error and returns -1 if the array is empty.

var rng = RandomNumberGenerator.new()

var my_array = ["one", "two", "three", "four"]
var weights = PackedFloat32Array([0.5, 1, 1, 2])

# Prints one of the four elements in `my_array`.
# It is more likely to print "four", and less likely to print "one".
print(my_array[rng.rand_weighted(weights)])

float randf() 🔗

返回在 0.0 和 1.0 之間（含端點）的偽隨機浮點數。

float randf_range(from: float, to: float) 🔗

返回在 from 和 to 之間（含端點）的偽隨機浮點數。

float randfn(mean: float = 0.0, deviation: float = 1.0) 🔗

Returns a normally-distributed, pseudo-random floating-point number from the specified mean and a standard deviation. This is also known as a Gaussian distribution.

Note: This method uses the Box-Muller transform algorithm.

int randi() 🔗

返回在 0 和 4294967295 之間（含端點）的偽隨機 32 位不帶正負號的整數。

int randi_range(from: int, to: int) 🔗

返回在 from 和 to 之間（含端點）的偽隨機 32 位不帶正負號的整數。

void randomize() 🔗

Sets up a time-based seed for this RandomNumberGenerator instance. Unlike the @GlobalScope random number generation functions, different RandomNumberGenerator instances can use different seeds.