69 lines
		
	
	
		
			1.8 KiB
		
	
	
	
		
			V
		
	
	
			
		
		
	
	
			69 lines
		
	
	
		
			1.8 KiB
		
	
	
	
		
			V
		
	
	
| module rand
 | |
| // Ported from http://www.pcg-random.org/download.html
 | |
| // and https://github.com/imneme/pcg-c-basic/blob/master/pcg_basic.c
 | |
| pub struct Pcg32 {
 | |
| mut:
 | |
| 	state u64
 | |
| 	inc   u64
 | |
| }
 | |
| 
 | |
| /**
 | |
|  * new_pcg32 - a Pcg32 PRNG generator
 | |
|  * @param initstate - the initial state of the PRNG.
 | |
|  * @param initseq - the stream/step of the PRNG.
 | |
|  * @return a new Pcg32 PRNG instance
 | |
| */
 | |
| 
 | |
| 
 | |
| pub fn new_pcg32(initstate u64, initseq u64) Pcg32 {
 | |
| 	mut rng := Pcg32{
 | |
| 	}
 | |
| 	rng.state = u64(0)
 | |
| 	rng.inc = (initseq<<u64(1)) | u64(1)
 | |
| 	rng.next()
 | |
| 	rng.state += initstate
 | |
| 	rng.next()
 | |
| 	return rng
 | |
| }
 | |
| 
 | |
| /**
 | |
|  * Pcg32.next - update the PRNG state and get back the next random number
 | |
|  * @return the generated pseudo random number
 | |
| */
 | |
| 
 | |
| 
 | |
| [inline]
 | |
| pub fn (mut rng Pcg32) next() u32 {
 | |
| 	oldstate := rng.state
 | |
| 	rng.state = oldstate * (6364136223846793005) + rng.inc
 | |
| 	xorshifted := u32(((oldstate>>u64(18)) ^ oldstate)>>u64(27))
 | |
| 	rot := u32(oldstate>>u64(59))
 | |
| 	return ((xorshifted>>rot) | (xorshifted<<((-rot) & u32(31))))
 | |
| }
 | |
| 
 | |
| /**
 | |
|  * Pcg32.bounded_next - update the PRNG state. Get the next number <  bound
 | |
|  * @param bound - the returned random number will be < bound
 | |
|  * @return the generated pseudo random number
 | |
| */
 | |
| 
 | |
| 
 | |
| [inline]
 | |
| pub fn (mut rng Pcg32) bounded_next(bound u32) u32 {
 | |
| 	// To avoid bias, we need to make the range of the RNG a multiple of
 | |
| 	// bound, which we do by dropping output less than a threshold.
 | |
| 	threshold := (-bound % bound)
 | |
| 	// Uniformity guarantees that loop below will terminate. In practice, it
 | |
| 	// should usually terminate quickly; on average (assuming all bounds are
 | |
| 	// equally likely), 82.25% of the time, we can expect it to require just
 | |
| 	// one iteration. In practice, bounds are typically small and only a
 | |
| 	// tiny amount of the range is eliminated.
 | |
| 	for {
 | |
| 		r := rng.next()
 | |
| 		if r >= threshold {
 | |
| 			return (r % bound)
 | |
| 		}
 | |
| 	}
 | |
| 	return u32(0)
 | |
| }
 |