BlockWerk Documentation
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Generates pseudo-random numbers using a deterministic PRNG (xorshift64). Supports uniform and gaussian distributions. Same seed produces identical sequences.

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Mathematical Model

Uniform:y∼U(min,max)Gaussian:y∼N(μ,σ)\begin{aligned} &\text{Uniform:} && y \sim \mathcal{U}(\text{min}, \text{max}) \\ &\text{Gaussian:} && y \sim \mathcal{N}(\mu, \sigma) \end{aligned}

Implemented via xorshift64 pseudorandom number generator with configurable seed. Identical seeds always produce identical sequences.

Inputs & Outputs

Direction ID Label Type Status
← Out out Out number Output

Parameters

Parameters Label Type Default Description
distribution Distribution select uniform
minimum Minimum number 0
maximum Maximum number 1
mean Mean number 0
stdDev Std Dev number 1
seed Seed number 12345

Usage Examples

  • Zie de ingebouwde voorbeelden in de handleiding voor een demonstratie van dit blok.

Remarks & Best Practices

  • Deterministic: The same seed always produces the identical sequence — useful for reproducible simulations
  • Seed 0: Uses system entropy for initialization (truly non-deterministic start)
  • Gaussian distribution: Use for sensor noise, measurement uncertainty, and Monte Carlo analysis
  • Uniform distribution: Use for dithering, initial conditions, and stochastic rounding
  • Performance: xorshift64 is extremely fast; thousands of independent RNG blocks can run in parallel

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