Queue simulation in Scilab

This post is an answer for Agnes, who commented the last post:

Engineering and Scientific Computing with Scilab - Book

This script is a simple simulation of a queue of packs (or anything else) which there are a source, the queue and a destiny.

I coded this script for simulating and problem where there is a source that sends packs with a specific probability, a queue that receives the source packs and stores them, with a maximum number of stored packs, and a destiny that receives the packs from the queue with another specific probability.

All interested ones can run the code and comment it.

N_packs = 15; //total number of packs

P_send = 0.5; //probability of a pack to be sent

P_process = 0.5; //probability of a pack to be processed

N_queue = 10; //maximum number of elements in the queue

N_sent = 0; //number of packs sent to queue

N_line = 0; //number of packs in the queue

N_processed = 0; //number of packs processed

src = rand(N_packs, 2); //source packs

dst = []; //destiny packs

line = []; //queue

processed = []; //processed packs

while N_processed < N_packs,
    try
        plot(src(:,1) + N_queue + 2, src(:,2), '.g'); 

//plots source packs as green dots
    end;
    
    try
        plot(processed(:,1) + N_queue + 2, processed(:,2), '*k'); 

//plots the queue as line of blue dots
    end;
    
    plot(1:N_queue, zeros(1, N_queue), '.w'); //clears queue dots
    
    try
        plot(line(:,1), line(:,2), '.b'); 

//plots the queue as line of blue dots
    end;
    
    try
        plot(dst(:,1), dst(:,2), '.r'); 

//plots destiny packs as red dots
    end;
    
    if rand() < P_send then 

//sends a pack with P_send probability
        if and([N_line < N_queue N_sent < N_packs]) then 

//verifies the queue is full or all packs have been sent
            N_sent = N_sent + 1;
            
            N_line = N_line + 1;
            
            line(N_line,:) = [N_line 0];
            
            processed(N_sent,:) = src(1,:);
            
            src = src(2:$,:);
        end
    end
    
    if rand() < P_process then 

//processes a pack with P_process probability
        if N_line > 0 then 

//verifies the line has at least one pack
            N_processed = N_processed + 1;
            
            N_line = N_line - 1;
            
            line = line(1:N_line,:);
            
            dst(N_processed,:) = -rand(1, 2);
        end
    end
end

Engineering and Scientific Computing with Scilab - Book

I found this book today: Engineering and Scientific Computing with Scilab and there is a very good reference for Scilab users and engineers in general.

The beginning of the book has an introduction about Scilab software and how to use it. In Part II, the book contains information about a specific Systems and Control Toolbox for Scilab.

Part III presents Applications, and here we can apply all knowledge to create and model real systems for simulation and/or real-time control.

This kind of basis makes the difference in undergraduate studies, because the students can easily see and practice their theoretical concepts and improve their problems solving skills.

Using a simulation environment, students can safely test any system and see what happen in many cases and different situations.

So, everyone knows I'm a strong defender of simulations in engineering and all nature sciences, and a book like that is a great signal other people are investing time and work in the same ideal.

However, we must hold in mind, simulation is only the beginning, but it can cut off many problems, specially in design process.