Elementary cellular automaton/Random number generator
You are encouraged to solve this task according to the task description, using any language you may know.
Rule 30 is considered to be chaotic enough to generate good pseudo-random numbers. As a matter of fact, for a long time rule 30 was used by the Mathematica software for its default random number generator.
Steven Wolfram's recommendation for random number generation from rule 30 consists in extracting successive bits in a fixed position in the array of cells, as the automaton changes state.
The purpose of this task is to demonstrate this. With the code written in the parent task, which you don't need to re-write here, show the ten first bytes that emerge from this recommendation. To be precise, you will start with a state of all cells but one equal to zero, and you'll follow the evolution of the particular cell whose state was initially one. Then you'll regroup those bits by packets of eight, reconstituting bytes with the first bit being the most significant.
You can pick which ever length you want for the initial array but it should be visible in the code so that your output can be reproduced with an other language.
For extra-credits, you will make this algorithm run as fast as possible in your language, for instance with an extensive use of bitwise logic.
- Reference
11l
V n = 64
F pow2(x)
R UInt64(1) << x
F evolve(UInt64 =state; rule)
L 10
V b = UInt64(0)
L(q) (7 .. 0).step(-1)
V st = state
b [|]= (st [&] 1) << q
state = 0
L(i) 0 .< :n
V t = ((st >> (i - 1)) [|] (st << (:n + 1 - i))) [&] 7
I (rule [&] pow2(t)) != 0
state [|]= pow2(i)
print(‘ ’b, end' ‘’)
print()
evolve(1, 30)
- Output:
220 197 147 174 117 97 149 171 100 151
C
64-bits array size, cyclic borders.
#include <stdio.h>
#include <limits.h>
typedef unsigned long long ull;
#define N (sizeof(ull) * CHAR_BIT)
#define B(x) (1ULL << (x))
void evolve(ull state, int rule)
{
int i, p, q, b;
for (p = 0; p < 10; p++) {
for (b = 0, q = 8; q--; ) {
ull st = state;
b |= (st&1) << q;
for (state = i = 0; i < N; i++)
if (rule & B(7 & (st>>(i-1) | st<<(N+1-i))))
state |= B(i);
}
printf(" %d", b);
}
putchar('\n');
return;
}
int main(void)
{
evolve(1, 30);
return 0;
}
- Output:
220 197 147 174 117 97 149 171 100 151
C++
We'll re-write the code of the parent task here.
#include <bitset>
#include <stdio.h>
#define SIZE 80
#define RULE 30
#define RULE_TEST(x) (RULE & 1 << (7 & (x)))
void evolve(std::bitset<SIZE> &s) {
int i;
std::bitset<SIZE> t(0);
t[SIZE-1] = RULE_TEST( s[0] << 2 | s[SIZE-1] << 1 | s[SIZE-2] );
t[ 0] = RULE_TEST( s[1] << 2 | s[ 0] << 1 | s[SIZE-1] );
for (i = 1; i < SIZE-1; i++)
t[i] = RULE_TEST( s[i+1] << 2 | s[i] << 1 | s[i-1] );
for (i = 0; i < SIZE; i++) s[i] = t[i];
}
void show(std::bitset<SIZE> s) {
int i;
for (i = SIZE; i--; ) printf("%c", s[i] ? '#' : ' ');
printf("|\n");
}
unsigned char byte(std::bitset<SIZE> &s) {
unsigned char b = 0;
int i;
for (i=8; i--; ) {
b |= s[0] << i;
evolve(s);
}
return b;
}
int main() {
int i;
std::bitset<SIZE> state(1);
for (i=10; i--; )
printf("%u%c", byte(state), i ? ' ' : '\n');
return 0;
}
- Output:
220 197 147 174 117 97 149 171 240 241
D
Adapted from the C version, with improvements and bug fixes. Optimized for performance as requested in the task description. This is a lazy range.
import std.stdio, std.range, std.typecons;
struct CellularRNG {
private uint current;
private immutable uint rule;
private ulong state;
this(in ulong state_, in uint rule_) pure nothrow @safe @nogc {
this.state = state_;
this.rule = rule_;
popFront;
}
public enum bool empty = false;
@property uint front() pure nothrow @safe @nogc { return current; }
void popFront() pure nothrow @safe @nogc {
enum uint nBit = 8;
enum uint NU = ulong.sizeof * nBit;
current = 0;
foreach_reverse (immutable i; 0 .. nBit) {
immutable state2 = state;
current |= (state2 & 1) << i;
state = 0;
/*static*/ foreach (immutable j; staticIota!(0, NU)) {
// To avoid undefined behavior with out-of-range shifts.
static if (j > 0)
immutable aux1 = state2 >> (j - 1);
else
immutable aux1 = state2 >> 63;
static if (j == 0)
immutable aux2 = state2 << 1;
else static if (j == 1)
immutable aux2 = state2 << 63;
else
immutable aux2 = state2 << (NU + 1 - j);
immutable aux = 7 & (aux1 | aux2);
if (rule & (1UL << aux))
state |= 1UL << j;
}
}
}
}
void main() {
CellularRNG(1, 30).take(10).writeln;
CellularRNG(1, 30).drop(2_000_000).front.writeln;
}
- Output:
[220, 197, 147, 174, 117, 97, 149, 171, 100, 151] 44
Run-time: less than two seconds with the ldc2 compiler.
F#
This task uses Elementary cellular automaton#The_Function
// Generate random numbers using Rule 30. Nigel Galloway: August 1st., 2019
eca 30 [|yield 1; yield! Array.zeroCreate 99|]|>Seq.chunkBySize 8|>Seq.map(fun n->n|>Array.mapi(fun n g->g.[0]<<<(7-n))|>Array.sum)|>Seq.take 10|>Seq.iter(printf "%d "); printfn ""
- Output:
220 197 147 174 117 97 149 171 240 241
Go
package main
import "fmt"
const n = 64
func pow2(x uint) uint64 {
return uint64(1) << x
}
func evolve(state uint64, rule int) {
for p := 0; p < 10; p++ {
b := uint64(0)
for q := 7; q >= 0; q-- {
st := state
b |= (st & 1) << uint(q)
state = 0
for i := uint(0); i < n; i++ {
var t1, t2, t3 uint64
if i > 0 {
t1 = st >> (i - 1)
} else {
t1 = st >> 63
}
if i == 0 {
t2 = st << 1
} else if i == 1 {
t2 = st << 63
} else {
t2 = st << (n + 1 - i)
}
t3 = 7 & (t1 | t2)
if (uint64(rule) & pow2(uint(t3))) != 0 {
state |= pow2(i)
}
}
}
fmt.Printf("%d ", b)
}
fmt.Println()
}
func main() {
evolve(1, 30)
}
- Output:
220 197 147 174 117 97 149 171 100 151
Haskell
Assume the comonadic solution given at Elementary cellular automaton#Haskell is packed in a module CellularAutomata
import CellularAutomata (fromList, rule, runCA)
import Control.Comonad
import Data.List (unfoldr)
rnd = fromBits <$> unfoldr (pure . splitAt 8) bits
where
size = 80
bits =
extract
<$> runCA
(rule 30)
(fromList (1 : replicate size 0))
fromBits = foldl ((+) . (2 *)) 0
- Output:
λ> take 10 rnd [220,197,147,174,117,97,149,171,240,241]
Using the rule 30 CA it is possible to determine the RandomGen
instance which could be utilized by the Random
class:
import System.Random
instance RandomGen (Cycle Int) where
next c =
let x = c =>> step (rule 30)
in (fromBits (view x), x)
split = (,) <*> (fromList . reverse . view)
λ> let r30 = fromList [1,0,1,0,1,0,1,0,1,0,1,0,1] :: Cycle Int λ> take 15 $ randoms r30 [7509,4949,2517,2229,2365,2067,6753,5662,5609,7576,2885,3017,2912,5081,2356] λ> take 30 $ randomRs ('A','J') r30 "DHJHHFJHBDDFCBHACHDEHDHFBAEJFE"
We can compare it with standard generator on a small integer range, using simple bin counter:
λ> let bins lst = [ (n, length (filter (==n) lst)) | n <- nub lst] λ> bins . take 10000 . randomRs ('A','J') $ r30 [('D',1098),('H',1097),('J',1093),('F',850),('B',848),('C',1014),('A',1012),('E',1011),('G',1253),('I',724)] λ> bins . take 10000 . randomRs ('A','J') <$> getStdGen [('G',975),('B',1035),('F',970),('J',1034),('I',956),('H',984),('C',1009),('E',1023),('A',1009),('D',1005)]
J
ca is a cellular automata class. The rng class inherits ca and extends it with bit and byte verbs to sample the ca.
coclass'ca'
DOC =: 'locale creation: (RULE ; INITIAL_STATE) conew ''ca'''
create =: 3 :'''RULE STATE'' =: y'
next =: 3 :'STATE =: RULE (((8$2) #: [) {~ [: #. [: -. [: |: |.~"1 0&_1 0 1@]) STATE'
coclass'base'
coclass'rng'
coinsert'ca'
bit =: 3 :'([ next) ({. STATE)'
byte =: [: #. [: , [: bit"0 (i.8)"_
coclass'base'
Having installed these into a j session we create and use the mathematica prng.
m =: (30 ; 64 {. 1) conew 'rng' byte__m"0 i.10 220 197 147 174 117 97 149 171 100 151
Java
public class ElementaryCellularAutomatonRandomNumberGenerator {
public static void main(String[] aArgs) {
final int seed = 989898989;
evolve(seed, 30);
}
private static void evolve(int aState, int aRule) {
long state = aState;
for ( int i = 0; i <= 9; i++ ) {
int b = 0;
for ( int q = 7; q >= 0; q-- ) {
long stateCopy = state;
b |= ( stateCopy & 1 ) << q;
state = 0;
for ( int j = 0; j < BIT_COUNT; j++ ) {
long t = ( stateCopy >>> ( j - 1 ) ) | ( stateCopy << ( BIT_COUNT + 1 - j ) ) & 7;
if ( ( aRule & ( 1L << t ) ) != 0 ) {
state |= 1 << j;
}
}
}
System.out.print(" " + b);
}
System.out.println();
}
private static final int BIT_COUNT = 64;
}
- Output:
231 223 191 126 253 251 247 239 223 191
jq
Works with jq and gojq, the C and Go implementations of jq
The following also works with jaq, the Rust implementation of jq, provided the "include" directive is replaced with the set of definitions from the parent task, and that a suitable alternative to 100*"0" is presented.
include "elementary-cellular-automaton" {search : "."};
# If using jq, the def of _nwise can be omitted.
def _nwise($n):
def n: if length <= $n then . else .[0:$n] , (.[$n:] | n) end;
n;
# Input: an array of bits represented by 0s, 1s, "0"s, or "1"s
# Output: the corresponding decimal on the assumption that the leading bits are least significant,
# e.g. [0,1] => 2
def binary2number:
reduce (.[]|tonumber) as $x ({p:1}; .n += .p * $x | .p *= 2) | .n;
("1" + 100 * "0" ) | [automaton(30; 80) | .[0:1]] | [_nwise(8) | reverse | binary2number]
- Output:
[220,197,147,174,117,97,149,171,240,241]
Julia
function evolve(state, rule, N=64)
B(x) = UInt64(1) << x
for p in 0:9
b = UInt64(0)
for q in 7:-1:0
st = UInt64(state)
b |= (st & 1) << q
state = UInt64(0)
for i in 0:N-1
t1 = (i > 0) ? st >> (i - 1) : st >> (N - 1)
t2 = (i == 0) ? st << 1 : (i == 1) ? st << (N - 1) : st << (N + 1 - i)
if UInt64(rule) & B(7 & (t1 | t2)) != 0
state |= B(i)
end
end
end
print("$b ")
end
println()
end
evolve(1, 30)
- Output:
220 197 147 174 117 97 149 171 100 151
Kotlin
// version 1.1.51
const val N = 64
fun pow2(x: Int) = 1L shl x
fun evolve(state: Long, rule: Int) {
var state2 = state
for (p in 0..9) {
var b = 0
for (q in 7 downTo 0) {
val st = state2
b = (b.toLong() or ((st and 1L) shl q)).toInt()
state2 = 0L
for (i in 0 until N) {
val t = ((st ushr (i - 1)) or (st shl (N + 1 - i)) and 7L).toInt()
if ((rule.toLong() and pow2(t)) != 0L) state2 = state2 or pow2(i)
}
}
print(" $b")
}
println()
}
fun main(args: Array<String>) {
evolve(1, 30)
}
- Output:
220 197 147 174 117 97 149 171 100 151
Mathematica / Wolfram Language
FromDigits[#, 2] & /@ Partition[Flatten[CellularAutomaton[30, {{1}, 0}, {200, 0}]], 8]
- Output:
{220, 197, 147, 174, 117, 97, 149, 171, 240, 241, 92, 18, 199, 27, 104, 8, 251, 167, 29, 112, 100, 103, 159, 129, 253}
Nim
const N = 64
template pow2(x: uint): uint = 1u shl x
proc evolve(state: uint; rule: Positive) =
var state = state
for _ in 1..10:
var b = 0u
for q in countdown(7, 0):
let st = state
b = b or (st and 1) shl q
state = 0
for i in 0u..<N:
let t = (st shr (i - 1) or st shl (N + 1 - i)) and 7
if (rule.uint and pow2(t)) != 0: state = state or pow2(i)
stdout.write ' ', b
echo ""
evolve(1, 30)
- Output:
220 197 147 174 117 97 149 171 100 151
Pascal
Using ROR and ROL is as fast as assembler and more portable.
Try it online! counting CPU-Cycles 32 vs 31 on Ryzen Zen1 per Byte -> 100Mb/s
Program Rule30;
//http://en.wikipedia.org/wiki/Next_State_Rule_30;
//http://mathworld.wolfram.com/Rule30.html
{$IFDEF FPC}
{$Mode Delphi}{$ASMMODE INTEL}
{$OPTIMIZATION ON,ALL}
// {$CODEALIGN proc=1}
{$ELSE}
{$APPTYPE CONSOLE}
{$ENDIF}
uses
SysUtils;
const
maxRounds = 2*1000*1000;
rounds = 10;
var
Rule30_State : Uint64;
function GetCPU_Time: int64;
type
TCpu = record
HiCpu,
LoCpu : Dword;
end;
var
Cput : TCpu;
begin
asm
RDTSC;
MOV Dword Ptr [CpuT.LoCpu],EAX
MOV Dword Ptr [CpuT.HiCpu],EDX
end;
with Cput do
result := int64(HiCPU) shl 32 + LoCpu;
end;
procedure InitRule30_State;inline;
begin
Rule30_State:= 1;
end;
procedure Next_State_Rule_30;inline;
var
run, prev,next: Uint64;
begin
run := Rule30_State;
Prev := RORQword(run,1);
next := ROLQword(run,1);
Rule30_State := (next OR run) XOR prev;
end;
function NextRule30Byte:NativeInt;
//64-BIT can use many registers
//32-Bit still fast
var
run, prev,next: Uint64;
myOne : UInt64;
Begin
run := Rule30_State;
result := 0;
myOne := 1;
//Unrolling and inlining Next_State_Rule_30 by hand
result := (result+result) OR (run AND myOne);
next := ROLQword(run,1);
Prev := RORQword(run,1);
run := (next OR run) XOR prev;
result := (result+result) OR (run AND myOne);
next := ROLQword(run,1);
Prev := RORQword(run,1);
run := (next OR run) XOR prev;
result := (result+result) OR (run AND myOne);
next := ROLQword(run,1);
Prev := RORQword(run,1);
run := (next OR run) XOR prev;
result := (result+result) OR (run AND myOne);
next := ROLQword(run,1);
Prev := RORQword(run,1);
run := (next OR run) XOR prev;
result := (result+result) OR (run AND myOne);
next := ROLQword(run,1);
Prev := RORQword(run,1);
run := (next OR run) XOR prev;
result := (result+result) OR (run AND myOne);
next := ROLQword(run,1);
Prev := RORQword(run,1);
run := (next OR run) XOR prev;
result := (result+result) OR (run AND myOne);
next := ROLQword(run,1);
Prev := RORQword(run,1);
run := (next OR run) XOR prev;
result := (result+result) OR (run AND myOne);
next := ROLQword(run,1);
Prev := RORQword(run,1);
Rule30_State := (next OR run) XOR prev;
end;
procedure Speedtest;
var
T1,T0 : INt64;
i: NativeInt;
Begin
writeln('Speedtest for statesize of ',64,' bits');
//Warm up start to wake up CPU takes some time
For i := 100*1000*1000-1 downto 0 do
Next_State_Rule_30;
T0 := GetCPU_Time;
InitRule30_State;
For i := maxRounds-1 downto 0 do
NextRule30Byte;
T1 := GetCPU_Time;
writeln(NextRule30Byte);
writeln('cycles per Byte : ',(T1-t0)/maxRounds:0:2);
writeln;
end;
procedure Task;
var
i: integer;
Begin
writeln('The task ');
InitRule30_State;
For i := 1 to rounds do
write(NextRule30Byte:4);
writeln;
end;
Begin
SpeedTest;
Task;
write(' <ENTER> ');readln;
end.
- Output:
//compiled 64-Bit Speedtest for statesize of 64 bits 44 cycles per Byte : 30.95 The task 220 197 147 174 117 97 149 171 100 151 <ENTER> //compiled 32-Bit Speedtest for statesize of 64 bits 44 cycles per Byte : 128.56 The task 220 197 147 174 117 97 149 171 100 151 <ENTER>
Perl
package Automaton {
sub new {
my $class = shift;
my $rule = [ reverse split //, sprintf "%08b", shift ];
return bless { rule => $rule, cells => [ @_ ] }, $class;
}
sub next {
my $this = shift;
my @previous = @{$this->{cells}};
$this->{cells} = [
@{$this->{rule}}[
map {
4*$previous[($_ - 1) % @previous]
+ 2*$previous[$_]
+ $previous[($_ + 1) % @previous]
} 0 .. @previous - 1
]
];
return $this;
}
use overload
q{""} => sub {
my $this = shift;
join '', map { $_ ? '#' : ' ' } @{$this->{cells}}
};
}
my $a = Automaton->new(30, 1, map 0, 1 .. 100);
for my $n (1 .. 10) {
my $sum = 0;
for my $b (1 .. 8) {
$sum = $sum * 2 + $a->{cells}[0];
$a->next;
}
print $sum, $n == 10 ? "\n" : " ";
}
- Output:
220 197 147 174 117 97 149 171 240 241
Phix
Making the minimum possible changes to Elementary_cellular_automaton#Phix, output matches C, D, Go, J, Kotlin, Racket, and zkl, and with the changes marked [2] C++, Haskell, Perl, Python, Ruby, Scheme, and Sidef, but completely different to Rust and Tcl. No attempt to optimise.
with javascript_semantics --string s = ".........#.........", --(original) string s = "...............................#"& "................................", --string s = "#"&repeat('.',100), -- [2] t=s, r = "........" integer rule = 30, k, l = length(s), w = 0 for i=1 to 8 do r[i] = iff(mod(rule,2)?'#':'.') rule = floor(rule/2) end for sequence res = {} for i=0 to 80 do w = w*2 + (s[32]='#') -- w = w*2 + (s[1]='#') -- [2] if mod(i+1,8)=0 then res&=w w=0 end if for j=1 to l do k = (s[iff(j=1?l:j-1)]='#')*4 + (s[ j ]='#')*2 + (s[iff(j=l?1:j+1)]='#')+1 t[j] = r[k] end for s = t end for pp(res)
- Output:
{220,197,147,174,117,97,149,171,100,151}
- Output:
with the changes marked [2]
{220,197,147,174,117,97,149,171,240,241}
Python
Python: With zero padded ends
from elementary_cellular_automaton import eca, eca_wrap
def rule30bytes(lencells=100):
cells = '1' + '0' * (lencells - 1)
gen = eca(cells, 30)
while True:
yield int(''.join(next(gen)[0] for i in range(8)), 2)
if __name__ == '__main__':
print([b for i,b in zip(range(10), rule30bytes())])
- Output:
[255, 255, 255, 255, 255, 255, 255, 255, 255, 255]
!
Python: With wrapping of end cells
def rule30bytes(lencells=100):
cells = '1' + '0' * (lencells - 1)
gen = eca_wrap(cells, 30)
while True:
yield int(''.join(next(gen)[0] for i in range(8)), 2))
- Output:
[220, 197, 147, 174, 117, 97, 149, 171, 240, 241]
Racket
Implementation of Elementary cellular automaton is saved in "Elementary_cellular_automata.rkt"
#lang racket
;; below is the code from the parent task
(require "Elementary_cellular_automata.rkt")
(require racket/fixnum)
;; This is the RNG automaton
(define (CA30-random-generator
#:rule [rule 30] ; rule 30 is random, maybe you're interested in using others
;; width of the CA... this is implemented as a number of words plus,
;; maybe, another word containing the spare bits
#:bits [bits 256])
(define-values [full-words more-bits]
(quotient/remainder bits usable-bits/fixnum))
(define wrap-rule
(and (positive? more-bits) (wrap-rule-truncate-left-word more-bits)))
(define next-gen (CA-next-generation 30 #:wrap-rule wrap-rule))
(define v (make-fxvector (+ full-words (if more-bits 1 0))))
(fxvector-set! v 0 1) ; this bit will always have significance
(define (next-word)
(define-values [v+ o] (next-gen v 0))
(begin0 (fxvector-ref v 0) (set! v v+)))
(lambda (bits)
(for/fold ([acc 0]) ([_ (in-range bits)])
;; the CA is fixnum, but this function returns integers of arbitrary width
(bitwise-ior (arithmetic-shift acc 1) (bitwise-and (next-word) 1)))))
(module+ main
;; To match the other examples on this page, the automaton is 30+30+4 bits long
;; (i.e. 64 bits)
(define C30-rand-64 (CA30-random-generator #:bits 64))
;; this should be the list from "C"
(for/list ([i 10]) (C30-rand-64 8))
; we also do big numbers...
(number->string (C30-rand-64 256) 16)
(number->string (C30-rand-64 256) 16)
(number->string (C30-rand-64 256) 16)
(number->string (C30-rand-64 256) 16))
- Output:
(220 197 147 174 117 97 149 171 100 151) "ecd9fbcdcc34604d833950deb58447124b98706e74ccc74d9337cb4e53f38c5e" "9c8b6471a4bc2cb3508f10b6635e4eb959ad8bbe484480695e8ddb5795f956a" "6d85153a987dad6f013bc6159a41bf95b9d9b14af87733e17c702a3dc9052172" "fc6fd302f5ea8f2fba6f476cfe9d090dc877dbd558e5afba49044d05b14d258"
Raku
(formerly Perl 6)
class Automaton {
has $.rule;
has @.cells;
has @.code = $!rule.fmt('%08b').flip.comb».Int;
method gist { "|{ @!cells.map({+$_ ?? '#' !! ' '}).join }|" }
method succ {
self.new: :$!rule, :@!code, :cells(
@!code[
4 «*« @!cells.rotate(-1)
»+« 2 «*« @!cells
»+« @!cells.rotate(1)
]
)
}
}
my Automaton $a .= new: :rule(30), :cells( flat 1, 0 xx 100 );
say :2[$a++.cells[0] xx 8] xx 10;
- Output:
220 197 147 174 117 97 149 171 240 241
Ruby
size = 100
eca = ElemCellAutomat.new("1"+"0"*(size-1), 30)
eca.take(80).map{|line| line[0]}.each_slice(8){|bin| p bin.join.to_i(2)}
- Output:
220 197 147 174 117 97 149 171 240 241
Rust
//Assuming the code from the Elementary cellular automaton task is in the namespace.
fn main() {
struct WolfGen(ElementaryCA);
impl WolfGen {
fn new() -> WolfGen {
let (_, ca) = ElementaryCA::new(30);
WolfGen(ca)
}
fn next(&mut self) -> u8 {
let mut out = 0;
for i in 0..8 {
out |= ((1 & self.0.next())<<i)as u8;
}
out
}
}
let mut gen = WolfGen::new();
for _ in 0..10 {
print!("{} ", gen.next());
}
}
- Output:
157 209 228 58 87 195 212 106 147 244
Scheme
; uses SRFI-1 library http://srfi.schemers.org/srfi-1/srfi-1.html
(define (random-r30 n)
(let ((r30 (vector 0 1 1 1 1 0 0 0)))
(fold
(lambda (x y ls)
(if (= x 1)
(cons (* x y) ls)
(cons (+ (car ls) (* x y)) (cdr ls))))
'()
(circular-list 1 2 4 8 16 32 64 128)
(unfold-right
(lambda (x) (zero? (car x)))
cadr
(lambda (x) (cons (- (car x) 1)
(evolve (cdr x) r30)))
(cons (* 8 n) (cons 1 (make-list 79 0))))))) ; list
(random-r30 10)
- Output:
(220 197 147 174 117 97 149 171 240 241)
Sidef
var auto = Automaton(30, [1] + 100.of(0));
10.times {
var sum = 0;
8.times {
sum = (2*sum + auto.cells[0]);
auto.next;
};
say sum;
};
- Output:
220 197 147 174 117 97 149 171 240 241
Tcl
oo::class create RandomGenerator {
superclass ElementaryAutomaton
variable s
constructor {stateLength} {
next 30
set s [split 1[string repeat 0 $stateLength] ""]
}
method rand {} {
set bits {}
while {[llength $bits] < 8} {
lappend bits [lindex $s 0]
set s [my evolve $s]
}
return [scan [join $bits ""] %b]
}
}
Demonstrating:
set rng [RandomGenerator new 31]
for {set r {}} {[llength $r]<10} {} {
lappend r [$rng rand]
}
puts [join $r ,]
- Output:
220,197,147,174,241,126,135,130,143,234
Note that as the number of state bits is increased (the parameter to the constructor), the sequence tends to a limit of and that deviations from this are due to interactions between the state modification “wavefront” as the automaton wraps round.
Wren
As Wren cannot deal accurately with 64-bit unsigned integers and bit-wise operations thereon, we need to use BigInt here.
import "/big" for BigInt
var n = 64
var pow2 = Fn.new { |x| BigInt.one << x }
var evolve = Fn.new { |state, rule|
for (p in 0..9) {
var b = BigInt.zero
for (q in 7..0) {
var st = state.copy()
b = b | ((st & 1) << q)
state = BigInt.zero
for (i in 0...n) {
var t1 = (i > 0) ? st >> (i-1) : st >> 63
var t2 = (i == 0) ? st << 1 : (i == 1) ? st << 63 : st << (n+1-i)
var t3 = (t1 | t2) & 7
if ((pow2.call(t3) & rule) != BigInt.zero) state = state | pow2.call(i)
}
}
System.write(" %(b)")
}
System.print()
}
evolve.call(BigInt.one, 30)
- Output:
220 197 147 174 117 97 149 171 100 151
zkl
No attempts at extra credit and not fast.
fcn rule(n){ n=n.toString(2); "00000000"[n.len() - 8,*] + n }
fcn applyRule(rule,cells){
cells=String(cells[-1],cells,cells[0]); // wrap edges
(cells.len() - 2).pump(String,'wrap(n){ rule[7 - cells[n,3].toInt(2)] })
}
fcn rand30{
var r30=rule(30), cells="0"*63 + 1; // 64 bits (8 bytes), arbitrary
n:=0;
do(8){
n=n*2 + cells[-1]; // append bit 0
cells=applyRule(r30,cells); // next state
}
n
}
Note that "var" in a function is "static" in C, ie function local variables, initialized once.
do(10){ rand30().print(","); }
- Output:
220,197,147,174,117,97,149,171,100,151,