573 lines
20 KiB
C++
573 lines
20 KiB
C++
/*
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* Copyright (c) 2008 Timo Bingmann
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*
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* This program is free software; you can redistribute it and/or modify
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* it under the terms of the GNU General Public License version 2 as
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* published by the Free Software Foundation;
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program; if not, write to the Free Software
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* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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*
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* Author: Timo Bingmann <timo.bingmann@student.kit.edu>
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*/
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#include "ns3/command-line.h"
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#include "ns3/double.h"
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#include "ns3/gnuplot.h"
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#include "ns3/integer.h"
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#include "ns3/ptr.h"
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#include "ns3/random-variable-stream.h"
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#include "ns3/string.h"
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#include <cmath>
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#include <fstream>
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#include <iostream>
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#include <map>
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/**
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* \file
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* \ingroup core-examples
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* \ingroup randomvariable
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* Example program illustrating use of RandomVariableStream
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*/
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using namespace ns3;
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namespace
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{
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/**
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* Round a double number to the given precision.
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* For example, `dround(0.234, 0.1) = 0.2`
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* and `dround(0.257, 0.1) = 0.3`
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* \param [in] number The number to round.
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* \param [in] precision The least significant digit to keep in the rounding.
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* \returns \pname{number} rounded to \pname{precision}.
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*/
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double
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dround(double number, double precision)
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{
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number /= precision;
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if (number >= 0)
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{
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number = std::floor(number + 0.5);
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}
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else
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{
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number = std::ceil(number - 0.5);
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}
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number *= precision;
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return number;
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}
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/**
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* Generate a histogram from a RandomVariableStream.
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* \param [in] rndvar The RandomVariableStream to sample.
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* \param [in] probes The number of samples.
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* \param [in] precision The precision to round samples to.
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* \param [in] title The title for the histogram.
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* \param [in] impulses Set the plot style to IMPULSES.
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* \return The histogram as a GnuPlot data set.
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*/
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GnuplotDataset
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Histogram(Ptr<RandomVariableStream> rndvar,
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unsigned int probes,
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double precision,
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const std::string& title,
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bool impulses = false)
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{
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typedef std::map<double, unsigned int> histogram_maptype;
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histogram_maptype histogram;
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for (unsigned int i = 0; i < probes; ++i)
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{
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double val = dround(rndvar->GetValue(), precision);
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++histogram[val];
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}
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Gnuplot2dDataset data;
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data.SetTitle(title);
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if (impulses)
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{
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data.SetStyle(Gnuplot2dDataset::IMPULSES);
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}
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for (histogram_maptype::const_iterator hi = histogram.begin(); hi != histogram.end(); ++hi)
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{
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data.Add(hi->first, (double)hi->second / (double)probes / precision);
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}
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return data;
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}
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} // unnamed namespace
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int
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main(int argc, char* argv[])
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{
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CommandLine cmd(__FILE__);
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cmd.Parse(argc, argv);
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unsigned int probes = 1000000;
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double precision = 0.01;
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const std::string plotFile{"main-random-variables"};
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GnuplotCollection gnuplots(plotFile + ".pdf");
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gnuplots.SetTerminal("pdf enhanced");
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{
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std::cout << "UniformRandomVariable......." << std::flush;
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Gnuplot plot;
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plot.SetTitle("UniformRandomVariable");
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plot.AppendExtra("set yrange [0:]");
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auto x = CreateObject<UniformRandomVariable>();
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x->SetAttribute("Min", DoubleValue(0.0));
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x->SetAttribute("Max", DoubleValue(1.0));
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plot.AddDataset(Histogram(x, probes, precision, "UniformRandomVariable [0.0 .. 1.0)"));
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plot.AddDataset(Gnuplot2dFunction("1.0", "0 <= x && x <= 1 ? 1.0 : 0"));
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gnuplots.AddPlot(plot);
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std::cout << "done" << std::endl;
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}
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{
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std::cout << "ExponentialRandomVariable..." << std::flush;
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Gnuplot plot;
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plot.SetTitle("ExponentialRandomVariable");
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plot.AppendExtra("set xrange [0:4]");
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plot.AppendExtra("ExpDist(x,l) = 1/l * exp(-1/l * x)");
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auto x1 = CreateObject<ExponentialRandomVariable>();
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x1->SetAttribute("Mean", DoubleValue(0.5));
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plot.AddDataset(Histogram(x1, probes, precision, "ExponentialRandomVariable m=0.5"));
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plot.AddDataset(Gnuplot2dFunction("ExponentialDistribution mean 0.5", "ExpDist(x, 0.5)"));
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auto x2 = CreateObject<ExponentialRandomVariable>();
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x2->SetAttribute("Mean", DoubleValue(1.0));
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plot.AddDataset(Histogram(x2, probes, precision, "ExponentialRandomVariable m=1"));
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plot.AddDataset(Gnuplot2dFunction("ExponentialDistribution mean 1.0", "ExpDist(x, 1.0)"));
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auto x3 = CreateObject<ExponentialRandomVariable>();
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x3->SetAttribute("Mean", DoubleValue(1.5));
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plot.AddDataset(Histogram(x3, probes, precision, "ExponentialRandomVariable m=1.5"));
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plot.AddDataset(Gnuplot2dFunction("ExponentialDistribution mean 1.5", "ExpDist(x, 1.5)"));
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gnuplots.AddPlot(plot);
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std::cout << "done" << std::endl;
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}
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{
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std::cout << "ParetoRandomVariable........" << std::flush;
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Gnuplot plot;
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plot.SetTitle("ParetoRandomVariable");
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plot.AppendExtra("set xrange [0:4]");
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auto x1 = CreateObject<ParetoRandomVariable>();
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x1->SetAttribute("Scale", DoubleValue(1.0));
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x1->SetAttribute("Shape", DoubleValue(1.5));
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plot.AddDataset(
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Histogram(x1, probes, precision, "ParetoRandomVariable scale=1.0 shape=1.5"));
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auto x2 = CreateObject<ParetoRandomVariable>();
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x2->SetAttribute("Scale", DoubleValue(1.0));
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x2->SetAttribute("Shape", DoubleValue(2.0));
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plot.AddDataset(
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Histogram(x2, probes, precision, "ParetoRandomVariable scale=1.0 shape=2.0"));
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auto x3 = CreateObject<ParetoRandomVariable>();
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x3->SetAttribute("Scale", DoubleValue(1.0));
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x3->SetAttribute("Shape", DoubleValue(2.5));
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plot.AddDataset(
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Histogram(x3, probes, precision, "ParetoRandomVariable scale=1.0 shape=2.5"));
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gnuplots.AddPlot(plot);
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std::cout << "done" << std::endl;
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}
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{
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std::cout << "WeibullRandomVariable......." << std::flush;
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Gnuplot plot;
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plot.SetTitle("WeibullRandomVariable");
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plot.AppendExtra("set xrange [0:4]");
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auto x1 = CreateObject<WeibullRandomVariable>();
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x1->SetAttribute("Scale", DoubleValue(1.0));
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x1->SetAttribute("Shape", DoubleValue(1.0));
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plot.AddDataset(
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Histogram(x1, probes, precision, "WeibullRandomVariable scale=1.0 shape=1.0"));
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auto x2 = CreateObject<WeibullRandomVariable>();
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x2->SetAttribute("Scale", DoubleValue(1.0));
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x2->SetAttribute("Shape", DoubleValue(2.0));
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plot.AddDataset(
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Histogram(x2, probes, precision, "WeibullRandomVariable scale=1.0 shape=2.0"));
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auto x3 = CreateObject<WeibullRandomVariable>();
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x3->SetAttribute("Scale", DoubleValue(1.0));
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x3->SetAttribute("Shape", DoubleValue(3.0));
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plot.AddDataset(
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Histogram(x3, probes, precision, "WeibullRandomVariable scale=1.0 shape=3.0"));
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gnuplots.AddPlot(plot);
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std::cout << "done" << std::endl;
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}
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{
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std::cout << "NormalRandomVariable........" << std::flush;
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Gnuplot plot;
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plot.SetTitle("NormalRandomVariable");
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plot.AppendExtra("set xrange [-4:4]");
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plot.AppendExtra(
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"NormalDist(x,m,s) = 1 / (s * sqrt(2*pi)) * exp(-1.0 / 2.0 * ((x-m) / s)**2)");
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auto x1 = CreateObject<NormalRandomVariable>();
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x1->SetAttribute("Mean", DoubleValue(0.0));
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x1->SetAttribute("Variance", DoubleValue(1.0));
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plot.AddDataset(Histogram(x1, probes, precision, "NormalRandomVariable m=0.0 v=1.0"));
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plot.AddDataset(Gnuplot2dFunction("NormalDist {/Symbol m}=0.0 {/Symbol s}=1.0",
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"NormalDist(x,0.0,1.0)"));
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auto x2 = CreateObject<NormalRandomVariable>();
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x2->SetAttribute("Mean", DoubleValue(0.0));
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x2->SetAttribute("Variance", DoubleValue(2.0));
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plot.AddDataset(Histogram(x2, probes, precision, "NormalRandomVariable m=0.0 v=2.0"));
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plot.AddDataset(Gnuplot2dFunction("NormalDist {/Symbol m}=0.0 {/Symbol s}=sqrt(2.0)",
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"NormalDist(x,0.0,sqrt(2.0))"));
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auto x3 = CreateObject<NormalRandomVariable>();
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x3->SetAttribute("Mean", DoubleValue(0.0));
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x3->SetAttribute("Variance", DoubleValue(3.0));
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plot.AddDataset(Histogram(x3, probes, precision, "NormalRandomVariable m=0.0 v=3.0"));
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plot.AddDataset(Gnuplot2dFunction("NormalDist {/Symbol m}=0.0 {/Symbol s}=sqrt(3.0)",
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"NormalDist(x,0.0,sqrt(3.0))"));
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gnuplots.AddPlot(plot);
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std::cout << "done" << std::endl;
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}
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{
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std::cout << "EmpiricalVariable..........." << std::flush;
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Gnuplot plot;
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plot.SetTitle("EmpiricalRandomVariable");
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plot.AppendExtra("set xrange [*:*]");
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auto x = CreateObject<EmpiricalRandomVariable>();
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x->CDF(0.0, 0.0 / 15.0);
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x->CDF(0.2, 1.0 / 15.0);
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x->CDF(0.4, 3.0 / 15.0);
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x->CDF(0.6, 6.0 / 15.0);
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x->CDF(0.8, 10.0 / 15.0);
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x->CDF(1.0, 15.0 / 15.0);
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plot.AddDataset(
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Histogram(x, probes, precision, "EmpiricalRandomVariable (Sampling)", true));
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x->SetInterpolate(true);
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plot.AppendExtra("set y2range [0:*]");
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auto d2 = Histogram(x, probes, precision, "EmpiricalRandomVariable (Interpolate)");
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d2.SetExtra(" axis x1y2");
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plot.AddDataset(d2);
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gnuplots.AddPlot(plot);
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std::cout << "done" << std::endl;
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}
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{
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std::cout << "DeterministicVariable......." << std::flush;
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Gnuplot plot;
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plot.SetTitle("DeterministicRandomVariable");
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plot.AppendExtra("set xrange [*:*]");
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auto x1 = CreateObject<DeterministicRandomVariable>();
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double values[] = {0.0, 0.2, 0.2, 0.4, 0.2, 0.6, 0.8, 0.8, 1.0};
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x1->SetValueArray(values, sizeof(values) / sizeof(values[0]));
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plot.AddDataset(Histogram(x1, probes, precision, "DeterministicRandomVariable", true));
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gnuplots.AddPlot(plot);
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std::cout << "done" << std::endl;
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}
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{
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std::cout << "LogNormalRandomVariable....." << std::flush;
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Gnuplot plot;
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plot.SetTitle("LogNormalRandomVariable");
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plot.AppendExtra("set xrange [0:4]");
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plot.AppendExtra("LogNormalDist(x,m,s) = 1.0/x * NormalDist(log(x), m, s)");
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auto x1 = CreateObject<LogNormalRandomVariable>();
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x1->SetAttribute("Mu", DoubleValue(0.0));
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x1->SetAttribute("Sigma", DoubleValue(1.0));
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plot.AddDataset(Histogram(x1, probes, precision, "LogNormalRandomVariable m=0.0 s=1.0"));
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plot.AddDataset(
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Gnuplot2dFunction("LogNormalDist(x, 0.0, 1.0)", "LogNormalDist(x, 0.0, 1.0)"));
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auto x2 = CreateObject<LogNormalRandomVariable>();
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x2->SetAttribute("Mu", DoubleValue(0.0));
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x2->SetAttribute("Sigma", DoubleValue(0.5));
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plot.AddDataset(Histogram(x2, probes, precision, "LogNormalRandomVariable m=0.0 s=0.5"));
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auto x3 = CreateObject<LogNormalRandomVariable>();
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x3->SetAttribute("Mu", DoubleValue(0.0));
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x3->SetAttribute("Sigma", DoubleValue(0.25));
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plot.AddDataset(Histogram(x3, probes, precision, "LogNormalRandomVariable m=0.0 s=0.25"));
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plot.AddDataset(
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Gnuplot2dFunction("LogNormalDist(x, 0.0, 0.25)", "LogNormalDist(x, 0.0, 0.25)"));
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auto x4 = CreateObject<LogNormalRandomVariable>();
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x4->SetAttribute("Mu", DoubleValue(0.0));
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x4->SetAttribute("Sigma", DoubleValue(0.125));
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plot.AddDataset(Histogram(x4, probes, precision, "LogNormalRandomVariable m=0.0 s=0.125"));
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auto x5 = CreateObject<LogNormalRandomVariable>();
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x5->SetAttribute("Mu", DoubleValue(0.0));
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x5->SetAttribute("Sigma", DoubleValue(2.0));
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plot.AddDataset(Histogram(x5, probes, precision, "LogNormalRandomVariable m=0.0 s=2.0"));
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plot.AddDataset(
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Gnuplot2dFunction("LogNormalDist(x, 0.0, 2.0)", "LogNormalDist(x, 0.0, 2.0)"));
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auto x6 = CreateObject<LogNormalRandomVariable>();
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x6->SetAttribute("Mu", DoubleValue(0.0));
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x6->SetAttribute("Sigma", DoubleValue(2.5));
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plot.AddDataset(Histogram(x6, probes, precision, "LogNormalRandomVariable m=0.0 s=2.5"));
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gnuplots.AddPlot(plot);
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std::cout << "done" << std::endl;
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}
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{
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std::cout << "TriangularRandomVariable...." << std::flush;
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Gnuplot plot;
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plot.SetTitle("TriangularRandomVariable");
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plot.AppendExtra("set xrange [*:*]");
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auto x1 = CreateObject<TriangularRandomVariable>();
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x1->SetAttribute("Min", DoubleValue(0.0));
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x1->SetAttribute("Max", DoubleValue(1.0));
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x1->SetAttribute("Mean", DoubleValue(0.5));
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plot.AddDataset(
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Histogram(x1, probes, precision, "TriangularRandomVariable [0.0 .. 1.0) m=0.5"));
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auto x2 = CreateObject<TriangularRandomVariable>();
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x2->SetAttribute("Min", DoubleValue(0.0));
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x2->SetAttribute("Max", DoubleValue(1.0));
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x2->SetAttribute("Mean", DoubleValue(0.4));
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plot.AddDataset(
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Histogram(x2, probes, precision, "TriangularRandomVariable [0.0 .. 1.0) m=0.4"));
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auto x3 = CreateObject<TriangularRandomVariable>();
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x3->SetAttribute("Min", DoubleValue(0.0));
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x3->SetAttribute("Max", DoubleValue(1.0));
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x3->SetAttribute("Mean", DoubleValue(0.65));
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plot.AddDataset(
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Histogram(x3, probes, precision, "TriangularRandomVariable [0.0 .. 1.0) m=0.65"));
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gnuplots.AddPlot(plot);
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std::cout << "done" << std::endl;
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}
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{
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std::cout << "GammaRandomVariable........." << std::flush;
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Gnuplot plot;
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plot.SetTitle("GammaRandomVariable");
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plot.AppendExtra("set xrange [0:10]");
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plot.AppendExtra("set yrange [0:1]");
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plot.AppendExtra("GammaDist(x,a,b) = x**(a-1) * 1/b**a * exp(-x/b) / gamma(a)");
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plot.AppendExtra(
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"set label 1 '{/Symbol g}(x,{/Symbol a},{/Symbol b}) = x^{/Symbol a-1} e^{-x {/Symbol "
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"b}^{-1}} ( {/Symbol b}^{/Symbol a} {/Symbol G}({/Symbol a}) )^{-1}' at 0.7, 0.9");
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auto x1 = CreateObject<GammaRandomVariable>();
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x1->SetAttribute("Alpha", DoubleValue(1.0));
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x1->SetAttribute("Beta", DoubleValue(1.0));
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plot.AddDataset(Histogram(x1, probes, precision, "GammaRandomVariable a=1.0 b=1.0"));
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plot.AddDataset(Gnuplot2dFunction("{/Symbol g}(x, 1.0, 1.0)", "GammaDist(x, 1.0, 1.0)"));
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auto x2 = CreateObject<GammaRandomVariable>();
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x2->SetAttribute("Alpha", DoubleValue(1.5));
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x2->SetAttribute("Beta", DoubleValue(1.0));
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plot.AddDataset(Histogram(x2, probes, precision, "GammaRandomVariable a=1.5 b=1.0"));
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plot.AddDataset(Gnuplot2dFunction("{/Symbol g}(x, 1.5, 1.0)", "GammaDist(x, 1.5, 1.0)"));
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auto x3 = CreateObject<GammaRandomVariable>();
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x3->SetAttribute("Alpha", DoubleValue(2.0));
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x3->SetAttribute("Beta", DoubleValue(1.0));
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plot.AddDataset(Histogram(x3, probes, precision, "GammaRandomVariable a=2.0 b=1.0"));
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plot.AddDataset(Gnuplot2dFunction("{/Symbol g}(x, 2.0, 1.0)", "GammaDist(x, 2.0, 1.0)"));
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auto x4 = CreateObject<GammaRandomVariable>();
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x4->SetAttribute("Alpha", DoubleValue(4.0));
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x4->SetAttribute("Beta", DoubleValue(1.0));
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plot.AddDataset(Histogram(x4, probes, precision, "GammaRandomVariable a=4.0 b=1.0"));
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plot.AddDataset(Gnuplot2dFunction("{/Symbol g}(x, 4.0, 1.0)", "GammaDist(x, 4.0, 1.0)"));
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auto x5 = CreateObject<GammaRandomVariable>();
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x5->SetAttribute("Alpha", DoubleValue(2.0));
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x5->SetAttribute("Beta", DoubleValue(2.0));
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plot.AddDataset(Histogram(x5, probes, precision, "GammaRandomVariable a=2.0 b=2.0"));
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plot.AddDataset(Gnuplot2dFunction("{/Symbol g}(x, 2.0, 2.0)", "GammaDist(x, 2.0, 2.0)"));
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auto x6 = CreateObject<GammaRandomVariable>();
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x6->SetAttribute("Alpha", DoubleValue(2.5));
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x6->SetAttribute("Beta", DoubleValue(3.0));
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plot.AddDataset(Histogram(x6, probes, precision, "GammaRandomVariable a=2.5 b=3.0"));
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|
|
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plot.AddDataset(Gnuplot2dFunction("{/Symbol g}(x, 2.5, 3.0)", "GammaDist(x, 2.5, 3.0)"));
|
|
|
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auto x7 = CreateObject<GammaRandomVariable>();
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x7->SetAttribute("Alpha", DoubleValue(2.5));
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x7->SetAttribute("Beta", DoubleValue(4.5));
|
|
|
|
plot.AddDataset(Histogram(x7, probes, precision, "GammaRandomVariable a=2.5 b=4.5"));
|
|
|
|
plot.AddDataset(Gnuplot2dFunction("{/Symbol g}(x, 2.5, 4.5)", "GammaDist(x, 2.5, 4.5)"));
|
|
|
|
gnuplots.AddPlot(plot);
|
|
std::cout << "done" << std::endl;
|
|
}
|
|
|
|
{
|
|
std::cout << "ErlangRandomVariable........" << std::flush;
|
|
Gnuplot plot;
|
|
plot.SetTitle("ErlangRandomVariable");
|
|
plot.AppendExtra("set xrange [0:10]");
|
|
plot.AppendExtra("ErlangDist(x,k,l) = x**(k-1) * 1/l**k * exp(-x/l) / (k-1)!");
|
|
|
|
plot.AppendExtra("set label 1 'Erlang(x,k,{/Symbol l}) = x^{k-1} e^{-x {/Symbol l}^{-1}} ( "
|
|
"{/Symbol l}^k (k-1)! )^{-1}' at 0.7, 0.9");
|
|
|
|
auto x1 = CreateObject<ErlangRandomVariable>();
|
|
x1->SetAttribute("K", IntegerValue(1));
|
|
x1->SetAttribute("Lambda", DoubleValue(1.0));
|
|
|
|
plot.AddDataset(
|
|
Histogram(x1, probes, precision, "ErlangRandomVariable k=1 {/Symbol l}=1.0"));
|
|
|
|
plot.AddDataset(Gnuplot2dFunction("Erlang(x, 1, 1.0)", "ErlangDist(x, 1, 1.0)"));
|
|
|
|
auto x2 = CreateObject<ErlangRandomVariable>();
|
|
x2->SetAttribute("K", IntegerValue(2));
|
|
x2->SetAttribute("Lambda", DoubleValue(1.0));
|
|
|
|
plot.AddDataset(
|
|
Histogram(x2, probes, precision, "ErlangRandomVariable k=2 {/Symbol l}=1.0"));
|
|
|
|
plot.AddDataset(Gnuplot2dFunction("Erlang(x, 2, 1.0)", "ErlangDist(x, 2, 1.0)"));
|
|
|
|
auto x3 = CreateObject<ErlangRandomVariable>();
|
|
x3->SetAttribute("K", IntegerValue(3));
|
|
x3->SetAttribute("Lambda", DoubleValue(1.0));
|
|
|
|
plot.AddDataset(
|
|
Histogram(x3, probes, precision, "ErlangRandomVariable k=3 {/Symbol l}=1.0"));
|
|
|
|
plot.AddDataset(Gnuplot2dFunction("Erlang(x, 3, 1.0)", "ErlangDist(x, 3, 1.0)"));
|
|
|
|
auto x4 = CreateObject<ErlangRandomVariable>();
|
|
x4->SetAttribute("K", IntegerValue(5));
|
|
x4->SetAttribute("Lambda", DoubleValue(1.0));
|
|
|
|
plot.AddDataset(
|
|
Histogram(x4, probes, precision, "ErlangRandomVariable k=5 {/Symbol l}=1.0"));
|
|
|
|
plot.AddDataset(Gnuplot2dFunction("Erlang(x, 5, 1.0)", "ErlangDist(x, 5, 1.0)"));
|
|
|
|
auto x5 = CreateObject<ErlangRandomVariable>();
|
|
x5->SetAttribute("K", IntegerValue(2));
|
|
x5->SetAttribute("Lambda", DoubleValue(2.0));
|
|
|
|
plot.AddDataset(
|
|
Histogram(x5, probes, precision, "ErlangRandomVariable k=2 {/Symbol l}=2.0"));
|
|
|
|
plot.AddDataset(Gnuplot2dFunction("Erlang(x, 2, 2.0)", "ErlangDist(x, 2, 2.0)"));
|
|
|
|
auto x6 = CreateObject<ErlangRandomVariable>();
|
|
x6->SetAttribute("K", IntegerValue(2));
|
|
x6->SetAttribute("Lambda", DoubleValue(3.0));
|
|
|
|
plot.AddDataset(
|
|
Histogram(x6, probes, precision, "ErlangRandomVariable k=2 {/Symbol l}=3.0"));
|
|
|
|
plot.AddDataset(Gnuplot2dFunction("Erlang(x, 2, 3.0)", "ErlangDist(x, 2, 3.0)"));
|
|
|
|
auto x7 = CreateObject<ErlangRandomVariable>();
|
|
x7->SetAttribute("K", IntegerValue(2));
|
|
x7->SetAttribute("Lambda", DoubleValue(5.0));
|
|
|
|
plot.AddDataset(
|
|
Histogram(x7, probes, precision, "ErlangRandomVariable k=2 {/Symbol l}=5.0"));
|
|
|
|
plot.AddDataset(Gnuplot2dFunction("Erlang(x, 2, 5.0)", "ErlangDist(x, 2, 5.0)"));
|
|
|
|
gnuplots.AddPlot(plot);
|
|
std::cout << "done" << std::endl;
|
|
}
|
|
|
|
{
|
|
std::string gnuFile = plotFile + ".plt";
|
|
std::cout << "Writing Gnuplot file: " << gnuFile << "..." << std::flush;
|
|
std::ofstream gnuStream(gnuFile);
|
|
gnuplots.GenerateOutput(gnuStream);
|
|
gnuStream.close();
|
|
|
|
std::cout << "done\nGenerating " << plotFile << ".pdf..." << std::flush;
|
|
std::string shellcmd = "gnuplot " + gnuFile;
|
|
std::system(shellcmd.c_str());
|
|
std::cout << "done" << std::endl;
|
|
}
|
|
|
|
return 0;
|
|
}
|