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Wolfram Language & System Documentation Center
SeedRandom
  • See Also
    • BlockRandom
    • RandomSeeding
    • RandomVariate
    • RandomInteger
    • RandomReal
    • RandomComplex
    • RandomChoice
    • RandomSample
    • RandomPrime
    • RandomGeneratorState
    • AbsoluteTime
    • Hash
    • GenerateDerivedKey
  • Related Guides
    • Random Number Generation
    • GPU Computing
    • GPU Computing with NVIDIA
    • GPU Computing with Apple
  • Tech Notes
    • Pseudorandom Numbers
    • Random Number Generation
    • See Also
      • BlockRandom
      • RandomSeeding
      • RandomVariate
      • RandomInteger
      • RandomReal
      • RandomComplex
      • RandomChoice
      • RandomSample
      • RandomPrime
      • RandomGeneratorState
      • AbsoluteTime
      • Hash
      • GenerateDerivedKey
    • Related Guides
      • Random Number Generation
      • GPU Computing
      • GPU Computing with NVIDIA
      • GPU Computing with Apple
    • Tech Notes
      • Pseudorandom Numbers
      • Random Number Generation

SeedRandom[s]

resets the pseudorandom generator, using s as a seed.

SeedRandom[]

resets the generator, using as a seed the time of day and certain attributes of the current Wolfram System session.

Details and Options
Details and Options Details and Options
Examples  
Basic Examples  
Scope  
Options  
Method  
Applications  
Properties & Relations  
See Also
Tech Notes
Related Guides
Related Links
History
Cite this Page
BUILT-IN SYMBOL
  • See Also
    • BlockRandom
    • RandomSeeding
    • RandomVariate
    • RandomInteger
    • RandomReal
    • RandomComplex
    • RandomChoice
    • RandomSample
    • RandomPrime
    • RandomGeneratorState
    • AbsoluteTime
    • Hash
    • GenerateDerivedKey
  • Related Guides
    • Random Number Generation
    • GPU Computing
    • GPU Computing with NVIDIA
    • GPU Computing with Apple
  • Tech Notes
    • Pseudorandom Numbers
    • Random Number Generation
    • See Also
      • BlockRandom
      • RandomSeeding
      • RandomVariate
      • RandomInteger
      • RandomReal
      • RandomComplex
      • RandomChoice
      • RandomSample
      • RandomPrime
      • RandomGeneratorState
      • AbsoluteTime
      • Hash
      • GenerateDerivedKey
    • Related Guides
      • Random Number Generation
      • GPU Computing
      • GPU Computing with NVIDIA
      • GPU Computing with Apple
    • Tech Notes
      • Pseudorandom Numbers
      • Random Number Generation

SeedRandom

SeedRandom[s]

resets the pseudorandom generator, using s as a seed.

SeedRandom[]

resets the generator, using as a seed the time of day and certain attributes of the current Wolfram System session.

Details and Options

  • You can use SeedRandom[s] to make sure you get the same sequence of pseudorandom numbers on different occasions.
  • SeedRandom affects RandomInteger, RandomReal, RandomComplex, RandomPrime, RandomChoice, RandomSample, and RandomVariate.
  • Possible settings for the seed s include:
  • RandomGeneratorState[…]a RandomGeneratorState object
    nan integer
    "seed"a string
    Automaticautomatically choose whether to reseed based on options
  • SeedRandom returns a RandomGeneratorState that for deterministic generators can be used as a seed in order to reproduce random sequences.
  • SeedRandom[Method->"method"] specifies what method should be used for the pseudorandom generator. If "method" has been previously used, this form does not reseed it.
  • SeedRandom[n,Method->"method"] resets the generator, specifying both a seed and the method to use.
  • SeedRandom[n] affects only the current generator; SeedRandom[n,Method->All] affects all generators for which seeds have been given.
  • Typical possible methods include:
  • "Congruential"linear congruential generator (low-quality randomness)
    "ExtendedCA"extended cellular automaton generator (default)
    "OpenSSL"OpenSSL cryptographically secure generator
    "MersenneTwister"Mersenne twister shift register generator
    "MKL"Intel MKL generator (Intel-based systems)
    "Rule30CA"Wolfram Rule 30 generator
  • Different methods may give sequences with different levels of randomness.

Examples

open all close all

Basic Examples  (1)

Use SeedRandom to make random numbers repeatable:

Scope  (3)

The seed can be a string:

Reseed the current random number generator:

Create a sequence of 5 random reals:

Reseed using the RandomGeneratorState object returned by SeedRandom:

The sequence of random real numbers is reproduced:

SeedRandom affects all random generators:

Options  (2)

Method  (2)

Switch to the Mersenne twister generator:

Random numbers are now generated using it:

A specific seed will affect the current Mersenne twister generator:

Give a seed to all initialized generators:

Applications  (2)

Reproduce a part of a computation that uses randomness:

Write a function that uses randomness, but returns predictable results:

Using the function again with more points just adds the additional points:

Properties & Relations  (4)

SeedRandom returns a RandomGeneratorState object with the new state:

When a RandomGeneratorState object is used as a seed, explicit Method options are ignored:

The state prior to seeding can be obtained from $RandomGeneratorState:

Use the current state:

Generate a new seed and and use the new state:

Seeding with the saved state reproduces the original sequence:

BlockRandom effectively saves the random generator state and restores it at the end of the computation:

See Also

BlockRandom  RandomSeeding  RandomVariate  RandomInteger  RandomReal  RandomComplex  RandomChoice  RandomSample  RandomPrime  RandomGeneratorState  AbsoluteTime  Hash  GenerateDerivedKey

Tech Notes

    ▪
  • Pseudorandom Numbers
  • ▪
  • Random Number Generation

Related Guides

    ▪
  • Random Number Generation
  • ▪
  • GPU Computing
  • ▪
  • GPU Computing with NVIDIA
  • ▪
  • GPU Computing with Apple

Related Links

  • An Elementary Introduction to the Wolfram Language : Interactive Manipulation
  • NKS|Online  (A New Kind of Science)

History

Introduced in 1988 (1.0) | Updated in 2007 (6.0) ▪ 2010 (8.0) ▪ 2020 (12.2)

Wolfram Research (1988), SeedRandom, Wolfram Language function, https://reference.wolfram.com/language/ref/SeedRandom.html (updated 2020).

Text

Wolfram Research (1988), SeedRandom, Wolfram Language function, https://reference.wolfram.com/language/ref/SeedRandom.html (updated 2020).

CMS

Wolfram Language. 1988. "SeedRandom." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2020. https://reference.wolfram.com/language/ref/SeedRandom.html.

APA

Wolfram Language. (1988). SeedRandom. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/SeedRandom.html

BibTeX

@misc{reference.wolfram_2025_seedrandom, author="Wolfram Research", title="{SeedRandom}", year="2020", howpublished="\url{https://reference.wolfram.com/language/ref/SeedRandom.html}", note=[Accessed: 04-February-2026]}

BibLaTeX

@online{reference.wolfram_2025_seedrandom, organization={Wolfram Research}, title={SeedRandom}, year={2020}, url={https://reference.wolfram.com/language/ref/SeedRandom.html}, note=[Accessed: 04-February-2026]}

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