How to resolve the algorithm Random numbers step by step in the Sather programming language

Published on 12 May 2024 09:40 PM
#Sather

How to resolve the algorithm Random numbers step by step in the Sather programming language

Table of Contents

Problem Statement

Generate a collection filled with   1000   normally distributed random (or pseudo-random) numbers with a mean of   1.0   and a   standard deviation   of   0.5 Many libraries only generate uniformly distributed random numbers. If so, you may use one of these algorithms.

Let's start with the solution:

Step by Step solution about How to resolve the algorithm Random numbers step by step in the Sather programming language

Source code in the sather programming language

class MAIN is
  main is
    a:ARRAY{FLTD} := #(1000);
    i:INT;

    RND::seed(2010);
    loop i := 1.upto!(1000) - 1;
      a[i] := 1.0d + 0.5d * RND::standard_normal;
    end;

    -- testing the distribution
    mean ::= a.reduce(bind(_.plus(_))) / a.size.fltd;
    #OUT + "mean " + mean + "\n";
    a.map(bind(_.minus(mean)));
    a.map(bind(_.pow(2.0d)));
    dev ::= (a.reduce(bind(_.plus(_))) / a.size.fltd).sqrt;
    #OUT + "dev  " + dev + "\n";
  end;
end;

You may also check:How to resolve the algorithm Deepcopy step by step in the Mathematica / Wolfram Language programming language
You may also check:How to resolve the algorithm CSV data manipulation step by step in the OCaml programming language
You may also check:How to resolve the algorithm GUI/Maximum window dimensions step by step in the PARI/GP programming language
You may also check:How to resolve the algorithm Palindrome detection step by step in the 360 Assembly programming language
You may also check:How to resolve the algorithm Top rank per group step by step in the TXR programming language