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numojo.routines.random

Random (numojo.routines.random)

Creates array of the given shape and populate it with random samples from a certain distribution.

This module is similar to numpy.random. However, in this module, the shape is always appearing as the first argument.

Functions

rand

Overload 1

rand[dtype: DType = DType.float64](shape: NDArrayShape) -> NDArray[dtype]

Creates an array of the given shape and populate it with random samples from a uniform distribution over [0, 1).

Example: 

from numojo import Shape
var arr = numojo.core.random.rand[numojo.i16](Shape(3,2,4))
print(arr)

Parameters:

  • dtype (DType): The data type of the NDArray elements.

Args:

  • shape (NDArrayShape): The shape of the NDArray.

Returns:

  • NDArray

Raises

Overload 2

rand[dtype: DType = DType.float64](*shape: Int) -> NDArray[dtype]

Overloads the function rand(shape: NDArrayShape). Creates an array of the given shape and populate it with random samples from a uniform distribution over [0, 1).

Parameters:

  • dtype (DType)

Args:

  • *shape (Int)

Returns:

  • NDArray

Raises

Overload 3

rand[dtype: DType = DType.float64](shape: List[Int]) -> NDArray[dtype]

Overloads the function rand(shape: NDArrayShape). Creates an array of the given shape and populate it with random samples from a uniform distribution over [0, 1).

Parameters:

  • dtype (DType)

Args:

  • shape (List)

Returns:

  • NDArray

Raises

Overload 4

rand[dtype: DType = DType.float64](shape: VariadicList[Int]) -> NDArray[dtype]

Overloads the function rand(shape: NDArrayShape) Creates an array of the given shape and populate it with random samples from a uniform distribution over [0, 1).

Parameters:

  • dtype (DType)

Args:

  • shape (VariadicList)

Returns:

  • NDArray

Raises

Overload 5

rand[dtype: DType = DType.float64](shape: NDArrayShape, min: Scalar[dtype], max: Scalar[dtype]) -> NDArray[dtype]

Creates an array of the given shape and populate it with random samples from a uniform distribution over [min, max). This is equivalent to min + rand() * (max - min).

Example: 

from numojo import Shape
var arr = numojo.core.random.rand[numojo.i16](Shape(3,2,4), min=0, max=100)
print(arr)

Parameters:

  • dtype (DType): The data type of the NDArray elements.

Args:

  • shape (NDArrayShape): The shape of the NDArray.
  • min (Scalar): The minimum value of the random values.
  • max (Scalar): The maximum value of the random values.

Returns:

  • NDArray

Raises

Error: If the dtype is not a floating-point type.

Overload 6

rand[dtype: DType = DType.float64](*shape: Int, *, min: Scalar[dtype], max: Scalar[dtype]) -> NDArray[dtype]

Overloads the function rand(shape: NDArrayShape, min, max). Creates an array of the given shape and populate it with random samples from a uniform distribution over [min, max). This is equivalent to min + rand() * (max - min).

Parameters:

  • dtype (DType)

Args:

  • *shape (Int)
  • min (Scalar)
  • max (Scalar)

Returns:

  • NDArray

Raises

Overload 7

rand[dtype: DType = DType.float64](shape: List[Int], min: Scalar[dtype], max: Scalar[dtype]) -> NDArray[dtype]

Overloads the function rand(shape: NDArrayShape, min, max). Creates an array of the given shape and populate it with random samples from a uniform distribution over [min, max). This is equivalent to min + rand() * (max - min).

Parameters:

  • dtype (DType)

Args:

  • shape (List)
  • min (Scalar)
  • max (Scalar)

Returns:

  • NDArray

Raises

randint

Overload 1

randint[dtype: DType = DType.int64](shape: NDArrayShape, low: Int, high: Int) -> NDArray[dtype] where dtype.is_integral()

Return an array of random integers from low (inclusive) to high (exclusive). Note that it is different from the built-in random.randint() function which returns integer in range low (inclusive) to high (inclusive).

Parameters:

  • dtype (DType): The data type of the NDArray elements.

Args:

  • shape (NDArrayShape): The shape of the NDArray.
  • low (Int): The minimum value of the random values.
  • high (Int): The maximum value of the random values.

Returns:

  • NDArray

Raises

Error: If the dtype is not a integer type.

Error: If high is not greater than low.

Overload 2

randint[dtype: DType = DType.int64](*shape: Int, *, low: Int, high: Int) -> NDArray[dtype] where dtype.is_integral()

Overloads the function randint(shape: NDArrayShape, low, high). Return an array of random integers from low (inclusive) to high (exclusive). Note that it is different from the built-in random.randint() function which returns integer in range low (inclusive) to high (inclusive).

Parameters:

  • dtype (DType)

Args:

  • *shape (Int)
  • low (Int)
  • high (Int)

Returns:

  • NDArray

Raises

Overload 3

randint[dtype: DType = DType.int64](shape: NDArrayShape, high: Int) -> NDArray[dtype] where dtype.is_integral()

Return an array of random integers from 0 (inclusive) to high (exclusive).

Parameters:

  • dtype (DType): The data type of the NDArray elements.

Args:

  • shape (NDArrayShape): The shape of the NDArray.
  • high (Int): The maximum value of the random values.

Returns:

  • NDArray

Raises

Error: If the dtype is not a integer type.

Error: If high <= 0.

Overload 4

randint[dtype: DType = DType.int64](*shape: Int, *, high: Int) -> NDArray[dtype] where dtype.is_integral()

Overloads the function randint(shape: NDArrayShape, high). Return an array of random integers from 0 (inclusive) to high (exclusive).

Parameters:

  • dtype (DType)

Args:

  • *shape (Int)
  • high (Int)

Returns:

  • NDArray

Raises

randn

Overload 1

randn[dtype: DType = DType.float64](shape: NDArrayShape) -> NDArray[dtype]

Creates an array of the given shape and populate it with random samples from a standard normal distribution.

Parameters:

  • dtype (DType): The data type of the NDArray elements.

Args:

  • shape (NDArrayShape): The shape of the NDArray.

Returns:

  • NDArray

Raises

Overload 2

randn[dtype: DType = DType.float64](*shape: Int) -> NDArray[dtype]

Overloads the function randn(shape: NDArrayShape). Creates an array of the given shape and populate it with random samples from a standard normal distribution.

Parameters:

  • dtype (DType)

Args:

  • *shape (Int)

Returns:

  • NDArray

Raises

Overload 3

randn[dtype: DType = DType.float64](shape: NDArrayShape, mean: Scalar[dtype], variance: Scalar[dtype]) -> NDArray[dtype]

Creates an array of the given shape and populate it with random samples from a normal distribution with given mean and variance.

Parameters:

  • dtype (DType): The data type of the NDArray elements.

Args:

  • shape (NDArrayShape): The shape of the NDArray.
  • mean (Scalar): The mean value of the random values.
  • variance (Scalar): The variance of the random values.

Returns:

  • NDArray

Raises

Overload 4

randn[dtype: DType = DType.float64](*shape: Int, *, mean: Scalar[dtype], variance: Scalar[dtype]) -> NDArray[dtype]

Overloads the function randn(shape: NDArrayShape, mean, variance). Creates an array of the given shape and populate it with random samples from a normal distribution with given mean and variance.

Parameters:

  • dtype (DType)

Args:

  • *shape (Int)
  • mean (Scalar)
  • variance (Scalar)

Returns:

  • NDArray

Raises

Overload 5

randn[dtype: DType = DType.float64](shape: List[Int], mean: Scalar[dtype], variance: Scalar[dtype]) -> NDArray[dtype]

Overloads the function randn(shape: NDArrayShape, mean, variance). Creates an array of the given shape and populate it with random samples from a normal distribution with given mean and variance.

Parameters:

  • dtype (DType)

Args:

  • shape (List)
  • mean (Scalar)
  • variance (Scalar)

Returns:

  • NDArray

Raises

exponential

Overload 1

exponential[dtype: DType = DType.float64](shape: NDArrayShape, scale: Scalar[dtype] = 1) -> NDArray[dtype] where dtype.is_floating_point()

Creates an array of the given shape and populate it with random samples from an exponential distribution with given scale parameter.

Example: 

var arr = numojo.random.exponential(Shape(3, 2, 4), 2.0)
print(arr)

Parameters:

  • dtype (DType): The data type of the NDArray elements.

Args:

  • shape (NDArrayShape): The shape of the NDArray.
  • scale (Scalar): The scale parameter of the exponential distribution (lambda).

Returns:

  • NDArray

Raises

Overload 2

exponential[dtype: DType = DType.float64](*shape: Int, *, scale: Scalar[dtype] = 1) -> NDArray[dtype] where dtype.is_floating_point()

Overloads the function exponential(shape: NDArrayShape, rate). Creates an array of the given shape and populate it with random samples from an exponential distribution with given scale parameter.

Parameters:

  • dtype (DType)

Args:

  • *shape (Int)
  • scale (Scalar)

Returns:

  • NDArray

Raises

Overload 3

exponential[dtype: DType = DType.float64](shape: List[Int], scale: Scalar[dtype] = 1) -> NDArray[dtype] where dtype.is_floating_point()

Overloads the function exponential(shape: NDArrayShape, rate). Creates an array of the given shape and populate it with random samples from an exponential distribution with given scale parameter.

Parameters:

  • dtype (DType)

Args:

  • shape (List)
  • scale (Scalar)

Returns:

  • NDArray

Raises