How to resolve the algorithm Knuth's algorithm S step by step in the zkl programming language

Published on 12 May 2024 09:40 PM
#Zkl

How to resolve the algorithm Knuth's algorithm S step by step in the zkl programming language

Table of Contents

Problem Statement

This is a method of randomly sampling n items from a set of M items, with equal probability; where M >= n and M, the number of items is unknown until the end. This means that the equal probability sampling should be maintained for all successive items > n as they become available (although the content of successive samples can change).

Note: A class taking n and generating a callable instance/function might also be used.

Let's start with the solution:

Step by Step solution about How to resolve the algorithm Knuth's algorithm S step by step in the zkl programming language

Source code in the zkl programming language

fcn s_of_n_creator(n){
   fcn(item,ri,N,samples){
      i:=ri.inc(); // 1,2,3,4,...
      if(i<=N) samples.append(item);
      else if ((0).random(i) < N) samples[(0).random(N)] = item;
      samples
   }.fp1(Ref(1),n,L())
}

s3:=s_of_n_creator(3);
[0..9].pump(List,s3,"copy").println();

dist:=L(0,0,0,0,0,0,0,0,0,0);
do(0d100_000){
   (0).pump(10,Void,s_of_n_creator(3)).apply2('wrap(n){dist[n]=dist[n]+1}) 
}
N:=dist.sum();
dist.apply('wrap(n){"%.2f%%".fmt(n.toFloat()/N*100)}).println();

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