98 lines
2.8 KiB
Markdown
98 lines
2.8 KiB
Markdown
# Description
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The V `rand` module provides two main ways in which users can generate pseudorandom numbers:
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## Direct Access Through The `rand` Module
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```
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// Import the rand module
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import rand
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...
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// Optionally seed the default generator
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rand.seed([u32(3110), 50714])
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...
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// Use the top-level functions
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rand.u32n(100)?
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rand.int() // among others ...
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```
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## Through A Generator Of Choice
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```
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// Import the rand module
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import rand
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import rand.seed
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// Import the module of the generator you want to use
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import rand.pcg32
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...
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// Initialise the generator struct (note the `mut`)
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mut rng := &rand.PRNG(pcg32.PCG32RNG{})
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// Optionally seed the generator
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rng.seed(seed.time_seed_array(pcg32.seed_len))
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...
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// Use functions of your choice
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rng.u32n(100)?
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rng.int() // among others ...
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```
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## More Information
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You can change the default generator to a different one. The only requirement is that
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the generator must implement the `PRNG` interface. See `get_current_rng()` and `set_rng()`.
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**Note:** The global PRNG is not thread safe. It is recommended to use separate generators for
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separate threads in multi-threaded applications.
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There are only a few extra functions that are defined only in this top-level `rand` module.
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Otherwise, there is feature parity between the generator functions and the top-level functions.
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# General Background
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A PRNG is a Pseudo Random Number Generator.
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Computers cannot generate truly random numbers without an external source of noise or entropy.
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We can use algorithms to generate sequences of seemingly random numbers,
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but their outputs will always be deterministic.
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This is often useful for simulations that need the same starting seed.
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If you need truly random numbers that are going to be used for cryptography,
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use the `crypto.rand` module.
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# Seeding Functions
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All the generators are time-seeded.
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The helper functions publicly available in `rand.seed` module are:
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1. `time_seed_array()` - returns a `[]u32` that can be directly plugged into the `seed()` functions.
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2. `time_seed_32()` and `time_seed_64()` - 32-bit and 64-bit values respectively
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that are generated from the current time.
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# Caveats
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Note that the `sys.SysRNG` struct (in the C backend) uses `C.srand()` which sets the seed globally.
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Consequently, all instances of the RNG will be affected.
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This problem does not arise for the other RNGs.
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A workaround (if you _must_ use the libc RNG) is to:
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1. Seed the first instance.
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2. Generate all values required.
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3. Seed the second instance.
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4. Generate all values required.
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5. And so on...
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# Notes
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Please note that [math interval](<https://en.wikipedia.org/wiki/Interval_(mathematics)#Including_or_excluding_endpoints>) notation is used throughout
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the function documentation to denote what numbers ranges include.
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An example of `[0, max)` thus denotes a range with all posible values
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between `0` and `max` **including** 0 but **excluding** `max`.
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