Nim's standard random number generator.
Its implementation is based on the xoroshiro128+ (xor/rotate/shift/rotate) library.
- More information: http://xoroshiro.di.unimi.it/
- C implementation: http://xoroshiro.di.unimi.it/xoroshiro128plus.c
Do not use this module for cryptographic purposes!
基本の用法
To get started, here are some examples:
import random # Call randomize() once to initialize the default random number generator # If this is not called, the same results will occur every time these # examples are run randomize() # Pick a number between 0 and 100 let num = rand(100) echo num # Roll a six-sided die let roll = rand(1..6) echo roll # Pick a marble from a bag let marbles = ["red", "blue", "green", "yellow", "purple"] let pick = sample(marbles) echo pick # Shuffle some cards var cards = ["Ace", "King", "Queen", "Jack", "Ten"] shuffle(cards) echo cards
These examples all use the default random number generator. The Rand type represents the state of a random number generator. For convenience, this module contains a default Rand state that corresponds to the default random number generator. Most procs in this module which do not take in a Rand parameter, including those called in the above examples, use the default generator. Those procs are not thread-safe.
Note that the default generator always starts in the same state. The randomize proc can be called to initialize the default generator with a seed based on the current time, and it only needs to be called once before the first usage of procs from this module. If randomize is not called, then the default generator will always produce the same results.
Generators that are independent of the default one can be created with the initRand proc.
Again, it is important to remember that this module must not be used for cryptographic applications.
関連
- math module for basic math routines
- mersenne module for the Mersenne Twister random number generator
- stats module for statistical analysis
- list of cryptographic and hashing modules in the standard library
型
Rand = object a0, a1: Ui
-
State of a random number generator.
Create a new Rand state using the initRand proc.
The module contains a default Rand state for convenience. It corresponds to the default random number generator's state. The default Rand state always starts with the same values, but the randomize proc can be used to seed the default generator with a value based on the current time.
Many procs have two variations: one that takes in a Rand parameter and another that uses the default generator. The procs that use the default generator are not thread-safe!
ソース 編集
プロシージャ
proc next(r: var Rand): uint64 {...}{.raises: [], tags: [].}
-
Computes a random uint64 number using the given state.
関連:
- rand proc that returns an integer between zero and a given upper bound
- rand proc that returns a float
- rand proc that accepts a slice
- rand proc that accepts an integer or range type
- skipRandomNumbers proc
用例:
var r = initRand(2019) doAssert r.next() == 138744656611299'u64 doAssert r.next() == 979810537855049344'u64 doAssert r.next() == 3628232584225300704'u64
ソース 編集 proc skipRandomNumbers(s: var Rand) {...}{.raises: [], tags: [].}
-
The jump function for the generator.
This proc is equivalent to 2^64 calls to next, and it can be used to generate 2^64 non-overlapping subsequences for parallel computations.
When multiple threads are generating random numbers, each thread must own the Rand state it is using so that the thread can safely obtain random numbers. However, if each thread creates its own Rand state, the subsequences of random numbers that each thread generates may overlap, even if the provided seeds are unique. This is more likely to happen as the number of threads and amount of random numbers generated increases.
If many threads will generate random numbers concurrently, it is better to create a single Rand state and pass it to each thread. After passing the Rand state to a thread, call this proc before passing it to the next one. By using the Rand state this way, the subsequences of random numbers generated in each thread will never overlap as long as no thread generates more than 2^64 random numbers.
The following example below demonstrates this pattern:
# Compile this example with --threads:on import random import threadpool const spawns = 4 const numbers = 100000 proc randomSum(rand: Rand): int = var r = rand for i in 1..numbers: result += rand(1..10) var r = initRand(2019) var vals: array[spawns, FlowVar[int]] for val in vals.mitems: val = spawn(randomSum(r)) r.skipRandomNumbers() for val in vals: echo ^val
関連:
ソース 編集 proc random(max: int): int {...}{.gcsafe, locks: 0, deprecated: "Deprecated since v0.18.0; use \'rand\' instead", raises: [], tags: [].}
- ソース 編集
proc random(max: float): float {...}{.gcsafe, locks: 0, deprecated: "Deprecated since v0.18.0; use \'rand\' instead", raises: [], tags: [].}
- ソース 編集
proc random[T](x: HSlice[T, T]): T {...}{.deprecated: "Deprecated since v0.18.0; use \'rand\' instead".}
- ソース 編集
proc random[T](a: openArray[T]): T {...}{.deprecated: "Deprecated since v0.18.0; use \'sample\' instead".}
- ソース 編集
proc rand(r: var Rand; max: Natural): int {...}{.gcsafe, locks: 0, raises: [], tags: [].}
-
Returns a random integer in the range 0..max using the given state.
関連:
- rand proc that returns an integer using the default random number generator
- rand proc that returns a float
- rand proc that accepts a slice
- rand proc that accepts an integer or range type
用例:
var r = initRand(123) doAssert r.rand(100) == 0 doAssert r.rand(100) == 96 doAssert r.rand(100) == 66
ソース 編集 proc rand(max: int): int {...}{.gcsafe, locks: 0, raises: [], tags: [].}
-
Returns a random integer in the range 0..max.
If randomize has not been called, the sequence of random numbers returned from this proc will always be the same.
This proc uses the default random number generator. Thus, it is not thread-safe.
関連:
- rand proc that returns an integer using a provided state
- rand proc that returns a float
- rand proc that accepts a slice
- rand proc that accepts an integer or range type
用例:
randomize(123) doAssert rand(100) == 0 doAssert rand(100) == 96 doAssert rand(100) == 66
ソース 編集 proc rand(r: var Rand; max: range[0.0 .. high(float)]): float {...}{.gcsafe, locks: 0, raises: [], tags: [].}
-
Returns a random floating point number in the range 0.0..max using the given state.
関連:
- rand proc that returns a float using the default random number generator
- rand proc that returns an integer
- rand proc that accepts a slice
- rand proc that accepts an integer or range type
用例:
var r = initRand(234) let f = r.rand(1.0) ## f = 8.717181376738381e-07
ソース 編集 proc rand(max: float): float {...}{.gcsafe, locks: 0, raises: [], tags: [].}
-
Returns a random floating point number in the range 0.0..max.
If randomize has not been called, the sequence of random numbers returned from this proc will always be the same.
This proc uses the default random number generator. Thus, it is not thread-safe.
関連:
- rand proc that returns a float using a provided state
- rand proc that returns an integer
- rand proc that accepts a slice
- rand proc that accepts an integer or range type
用例:
randomize(234) let f = rand(1.0) ## f = 8.717181376738381e-07
ソース 編集 proc rand[T: Ordinal or SomeFloat](r: var Rand; x: HSlice[T, T]): T
-
For a slice a..b, returns a value in the range a..b using the given state.
Allowed types for T are integers, floats, and enums without holes.
関連:
- rand proc that accepts a slice and uses the default random number generator
- rand proc that returns an integer
- rand proc that returns a float
- rand proc that accepts an integer or range type
用例:
var r = initRand(345) doAssert r.rand(1 .. 6) == 4 doAssert r.rand(1 .. 6) == 4 doAssert r.rand(1 .. 6) == 6 let f = r.rand(-1.0 .. 1.0) ## f = 0.8741183448756229
ソース 編集 proc rand[T: Ordinal or SomeFloat](x: HSlice[T, T]): T
-
For a slice a..b, returns a value in the range a..b.
Allowed types for T are integers, floats, and enums without holes.
If randomize has not been called, the sequence of random numbers returned from this proc will always be the same.
This proc uses the default random number generator. Thus, it is not thread-safe.
関連:
- rand proc that accepts a slice and uses a provided state
- rand proc that returns an integer
- rand proc that returns a floating point number
- rand proc that accepts an integer or range type
用例:
randomize(345) doAssert rand(1 .. 6) == 4 doAssert rand(1 .. 6) == 4 doAssert rand(1 .. 6) == 6
ソース 編集 proc rand[T](r: var Rand; a: openArray[T]): T {...}{. deprecated: "Deprecated since v0.20.0; use \'sample\' instead".}
- ソース 編集
proc rand[T: SomeInteger](t: typedesc[T]): T
-
Returns a random integer in the range low(T)..high(T).
If randomize has not been called, the sequence of random numbers returned from this proc will always be the same.
This proc uses the default random number generator. Thus, it is not thread-safe.
関連:
- rand proc that returns an integer
- rand proc that returns a floating point number
- rand proc that accepts a slice
用例:
randomize(567) doAssert rand(int8) == 55 doAssert rand(int8) == -42 doAssert rand(int8) == 43 doAssert rand(uint32) == 578980729'u32 doAssert rand(uint32) == 4052940463'u32 doAssert rand(uint32) == 2163872389'u32 doAssert rand(range[1 .. 16]) == 11 doAssert rand(range[1 .. 16]) == 4 doAssert rand(range[1 .. 16]) == 16
ソース 編集 proc rand[T](a: openArray[T]): T {...}{.deprecated: "Deprecated since v0.20.0; use \'sample\' instead".}
- ソース 編集
proc sample[T](r: var Rand; s: set[T]): T
-
Returns a random element from the set s using the given state.
関連:
- sample proc that uses the default random number generator
- sample proc for openarrays
- sample proc that uses a cumulative distribution function
用例:
var r = initRand(987) let s = {1, 3, 5, 7, 9} doAssert r.sample(s) == 5 doAssert r.sample(s) == 7 doAssert r.sample(s) == 1
ソース 編集 proc sample[T](s: set[T]): T
-
Returns a random element from the set s.
If randomize has not been called, the order of outcomes from this proc will always be the same.
This proc uses the default random number generator. Thus, it is not thread-safe.
関連:
- sample proc that uses a provided state
- sample proc for openarrays
- sample proc that uses a cumulative distribution function
用例:
randomize(987) let s = {1, 3, 5, 7, 9} doAssert sample(s) == 5 doAssert sample(s) == 7 doAssert sample(s) == 1
ソース 編集 proc sample[T](r: var Rand; a: openArray[T]): T
-
Returns a random element from a using the given state.
関連:
- sample proc that uses the default random number generator
- sample proc that uses a cumulative distribution function
- sample proc for sets
用例:
let marbles = ["red", "blue", "green", "yellow", "purple"] var r = initRand(456) doAssert r.sample(marbles) == "blue" doAssert r.sample(marbles) == "yellow" doAssert r.sample(marbles) == "red"
ソース 編集 proc sample[T](a: openArray[T]): T
-
Returns a random element from a.
If randomize has not been called, the order of outcomes from this proc will always be the same.
This proc uses the default random number generator. Thus, it is not thread-safe.
関連:
- sample proc that uses a provided state
- sample proc that uses a cumulative distribution function
- sample proc for sets
用例:
let marbles = ["red", "blue", "green", "yellow", "purple"] randomize(456) doAssert sample(marbles) == "blue" doAssert sample(marbles) == "yellow" doAssert sample(marbles) == "red"
ソース 編集 proc sample[T, U](r: var Rand; a: openArray[T]; cdf: openArray[U]): T
-
Returns an element from a using a cumulative distribution function (CDF) and the given state.
The cdf argument does not have to be normalized, and it could contain any type of elements that can be converted to a float. It must be the same length as a. Each element in cdf should be greater than or equal to the previous element.
The outcome of the cumsum proc and the return value of the cumsummed proc, which are both in the math module, can be used as the cdf argument.
関連:
- sample proc that also utilizes a CDF but uses the default random number generator
- sample proc that does not use a CDF
- sample proc for sets
用例:
from math import cumsummed let marbles = ["red", "blue", "green", "yellow", "purple"] let count = [1, 6, 8, 3, 4] let cdf = count.cumsummed var r = initRand(789) doAssert r.sample(marbles, cdf) == "red" doAssert r.sample(marbles, cdf) == "green" doAssert r.sample(marbles, cdf) == "blue"
ソース 編集 proc sample[T, U](a: openArray[T]; cdf: openArray[U]): T
-
Returns an element from a using a cumulative distribution function (CDF).
This proc works similarly to sample[T, U](Rand, openArray[T], openArray[U]). See that proc's documentation for more details.
If randomize has not been called, the order of outcomes from this proc will always be the same.
This proc uses the default random number generator. Thus, it is not thread-safe.
関連:
- sample proc that also utilizes a CDF but uses a provided state
- sample proc that does not use a CDF
- sample proc for sets
用例:
from math import cumsummed let marbles = ["red", "blue", "green", "yellow", "purple"] let count = [1, 6, 8, 3, 4] let cdf = count.cumsummed randomize(789) doAssert sample(marbles, cdf) == "red" doAssert sample(marbles, cdf) == "green" doAssert sample(marbles, cdf) == "blue"
ソース 編集 proc initRand(seed: int64): Rand {...}{.raises: [], tags: [].}
-
Initializes a new Rand state using the given seed.
seed must not be zero. Providing a specific seed will produce the same results for that seed each time.
The resulting state is independent of the default random number generator's state.
関連:
- randomize proc that accepts a seed for the default random number generator
- randomize proc that initializes the default random number generator using the current time
用例:
from times import getTime, toUnix, nanosecond var r1 = initRand(123) let now = getTime() var r2 = initRand(now.toUnix * 1000000000 + now.nanosecond)
ソース 編集 proc randomize(seed: int64) {...}{.gcsafe, locks: 0, raises: [], tags: [].}
-
Initializes the default random number generator with the given seed.
seed must not be zero. Providing a specific seed will produce the same results for that seed each time.
関連:
- initRand proc
- randomize proc that uses the current time instead
用例:
from times import getTime, toUnix, nanosecond randomize(123) let now = getTime() randomize(now.toUnix * 1000000000 + now.nanosecond)
ソース 編集 proc shuffle[T](r: var Rand; x: var openArray[T])
-
Shuffles a sequence of elements in-place using the given state.
関連:
- shuffle proc that uses the default random number generator
用例:
var cards = ["Ace", "King", "Queen", "Jack", "Ten"] var r = initRand(678) r.shuffle(cards) doAssert cards == ["King", "Ace", "Queen", "Ten", "Jack"]
ソース 編集 proc shuffle[T](x: var openArray[T])
-
Shuffles a sequence of elements in-place.
If randomize has not been called, the order of outcomes from this proc will always be the same.
This proc uses the default random number generator. Thus, it is not thread-safe.
関連:
- shuffle proc that uses a provided state
用例:
var cards = ["Ace", "King", "Queen", "Jack", "Ten"] randomize(678) shuffle(cards) doAssert cards == ["King", "Ace", "Queen", "Ten", "Jack"]
ソース 編集 proc randomize() {...}{.gcsafe, locks: 0, raises: [], tags: [TimeEffect].}
-
Initializes the default random number generator with a value based on the current time.
This proc only needs to be called once, and it should be called before the first usage of procs from this module that use the default random number generator.
Note: Does not work for NimScript.
関連:
- randomize proc that accepts a seed
- initRand proc