RandomGenerator

class RandomGenerator(*args, **kwargs)

Uniform random generator.

Refer to Uniform Random Generator.

The random generator of uniform(0,1) samples is based on the DSFTM (Double precision SIMD oriented Fast Mersenne Twister) algorithm.

Methods

Generate(*args)	Generate a pseudo-random vector.
GetState()	Get the state of the random generator.
IntegerGenerate(*args)	Generate a pseudo-random integer.
SetSeed(seed)	Set the seed of the random generator.
SetState(state)	Set the state of the random generator.

__init__(*args, **kwargs)

static Generate(*args)

Generate a pseudo-random vector.

Parameters

sizepositive int

Number of realizations required. When not given, by default it is equal to 1.

Returns

numbersfloat, Point

Pseudo-random numbers uniformly distributed over .

Examples

>>> import openturns as ot
>>> ot.RandomGenerator.SetSeed(0)
>>> print('%.6f' % ot.RandomGenerator.Generate())
0.629877
>>> print(ot.RandomGenerator.Generate(2))
[0.882805,0.135276]

static GetState()

Get the state of the random generator.

Returns

particularStateRandomGeneratorState

State of the random generator.

static IntegerGenerate(*args)

Generate a pseudo-random integer.

Available usages

IntegerGenerate(n)

IntegerGenerate(size, n)

Parameters

npositive int

Upper bound of the interval where the pseudo-random integers are.

sizepositive int

Number of integers to generate. When not given, by default it is equal to 1.

Returns

integerint, UnsignedIntegerCollection

Pseudo-random integers uniformly distributed over .

Examples

>>> import openturns as ot
>>> ot.RandomGenerator.SetSeed(0)
>>> print(ot.RandomGenerator.IntegerGenerate(30))
24
>>> print(ot.RandomGenerator.IntegerGenerate(5, 30))
[26,21,21,22,26]

static SetSeed(seed)

Set the seed of the random generator.

Parameters

nint

Notes

This method fixes a particular state of the random generator algorithm thanks to the seed . The seed of the random generator is automatically initialized to 0 when a session is launched.

static SetState(state)

Set the state of the random generator.

Parameters

particularStateRandomGeneratorState

State of the random generator.

Notes

This method fixes the entire state of the random generator algorithm thanks the specification of the entire state particularState usually previously obtained thanks to the GetState() method.