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 - . 
 
- numbersfloat, 
 - 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. 
 
- particularState
 
 - 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 - . 
 
- integerint, 
 - 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 
 
- 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. 
 
- particularState
 - 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.
 
 OpenTURNS
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