Basic Random Functions

All functions on this page are accessed via the np.random namespace and use the global MT19937 generator. Seed with np.random.seed() for reproducible results.

As of v1.2.0, random functions on this page (rand, randn, random, randint, uniform, normal, choice, shuffle, permutation, bytes) are now implemented as Zig-compiled WASM kernels. With np.random.seed(n), outputs match NumPy exactly for the same seed across every function listed here.

random

Generate random floats in the half-open interval [0.0, 1.0).

function random(size?: number | number[]): NDArray | number

Name	Type	Default	Description
`size`	`number \| number[]`	`undefined`	Output shape. If omitted, returns a single float.

Returns: NDArray | number — Random values in [0, 1).

import * as np from 'numpy-ts';

np.random.seed(42);

// Single value
const x = np.random.random();

// 1-D array
const a = np.random.random(5);
// array([...])  shape [5]

// 2-D array
const b = np.random.random([3, 4]);
// array([...])  shape [3, 4]

rand

Random values in a given shape. Variadic form of random — pass dimensions as separate arguments.

function rand(...shape: number[]): NDArray | number

Name	Type	Default	Description
`...shape`	`number[]`	—	Dimensions of the returned array. If no arguments, returns a single float.

Returns: NDArray | number — Random values in [0, 1).

import * as np from 'numpy-ts';

const a = np.random.rand(2, 3);
// array([...])  shape [2, 3]

randn

Return samples from the standard normal distribution (mean=0, std=1). Variadic shape, like rand.

function randn(...shape: number[]): NDArray | number

Name	Type	Default	Description
`...shape`	`number[]`	—	Dimensions of the returned array. If no arguments, returns a single float.

Returns: NDArray | number — Samples from the standard normal distribution.

import * as np from 'numpy-ts';

const a = np.random.randn(1000);
// 1000 standard-normal samples

randint

Return random integers from low (inclusive) to high (exclusive).

function randint(
  low: number,
  high?: number | null,
  size?: number | number[],
  dtype?: DType
): NDArray | number

Name	Type	Default	Description
`low`	`number`	—	Lowest integer (inclusive). If `high` is omitted, this is treated as the upper bound and `low` defaults to 0.
`high`	`number \| null`	`null`	One above the highest integer (exclusive).
`size`	`number \| number[]`	`undefined`	Output shape. If omitted, returns a single integer.
`dtype`	`DType`	`'int64'`	Desired output dtype.

Returns: NDArray | number — Random integers in [low, high).

import * as np from 'numpy-ts';

// 0 to 9
const a = np.random.randint(10);

// 5 to 14, shape [2, 3]
const b = np.random.randint(5, 15, [2, 3]);

random_sample

Alias for random(). Return random floats in [0.0, 1.0).

function random_sample(size?: number | number[]): NDArray | number

Name	Type	Default	Description
`size`	`number \| number[]`	`undefined`	Output shape.

Returns: NDArray | number — Random values in [0, 1).

ranf

Alias for random(). Return random floats in [0.0, 1.0).

function ranf(size?: number | number[]): NDArray | number

Name	Type	Default	Description
`size`	`number \| number[]`	`undefined`	Output shape.

Returns: NDArray | number — Random values in [0, 1).

sample

Alias for random(). Return random floats in [0.0, 1.0).

function sample(size?: number | number[]): NDArray | number

Name	Type	Default	Description
`size`	`number \| number[]`	`undefined`	Output shape.

Returns: NDArray | number — Random values in [0, 1).

random_integers

Deprecated. Use randint instead.

Return random integers between low and high, inclusive on both ends.

function random_integers(
  low: number,
  high?: number,
  size?: number | number[]
): NDArray | number

Name	Type	Default	Description
`low`	`number`	—	Lowest integer. If `high` is omitted, range is `[1, low]`.
`high`	`number`	`undefined`	Highest integer (inclusive).
`size`	`number \| number[]`	`undefined`	Output shape.

Returns: NDArray | number — Random integers in [low, high].

import * as np from 'numpy-ts';

// Random integers from 1 to 6 (inclusive), like a die roll
const die = np.random.random_integers(1, 6, [10]);

bytes

Return random bytes as a Uint8Array.

function bytes(length: number): Uint8Array

Name	Type	Default	Description
`length`	`number`	—	Number of random bytes to generate.

Returns: Uint8Array — Array of random bytes.

import * as np from 'numpy-ts';

const b = np.random.bytes(16);
// Uint8Array of 16 random bytes

choice

Generate a random sample from a given 1-D array or from range(a) when a is an integer.

function choice(
  a: number | ArrayLike,
  size?: number | number[],
  replace?: boolean,
  p?: ArrayLike
): NDArray | number

Name	Type	Default	Description
`a`	`number \| ArrayLike`	—	If `number`, sample from `0..a-1`; otherwise sample from the provided values.
`size`	`number \| number[]`	`undefined`	Output shape.
`replace`	`boolean`	`true`	Whether sampling is with replacement.
`p`	`ArrayLike`	`undefined`	Optional probabilities for each entry in `a`.

permutation

Randomly permute a sequence or return a permuted range.

function permutation(x: number | ArrayLike): NDArray

Name	Type	Default	Description
`x`	`number \| ArrayLike`	—	If `number`, permute `0..x-1`; otherwise permute the input values.

shuffle

Shuffle an array in place along the first axis.

function shuffle(x: ArrayLike): void

Name	Type	Default	Description
`x`	`ArrayLike`	—	Array to shuffle in place.

Overview

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Math

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Reductions & Statistics

Linear Algebra

Logic & Comparison

Sorting & Searching

Set Operations

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Gradient & Differences

Polynomials

Random (np.random)

FFT (np.fft)

I/O

Utilities

Basic Random Functions

random

rand

randn

randint

random_sample

ranf

sample

random_integers

bytes

choice

permutation

shuffle

​random

​rand

​randn

​randint

​random_sample

​ranf

​sample

​random_integers

​bytes

​choice

​permutation

​shuffle

random

rand

randn

randint

random_sample

ranf

sample

random_integers

bytes

choice

permutation

shuffle