dlib C++ Library - running_stats_ex.cpp

// The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt
/*
 This is an example illustrating the use of the running_stats object from the dlib C++
 Library. It is a simple tool for computing basic statistics on a stream of numbers.
 In this example, we sample 100 points from the sinc function and then then compute the
 unbiased sample mean, variance, skewness, and excess kurtosis.
*/ 
#include <iostream>
#include <vector>
#include <dlib/statistics.h>
using namespace std;
using namespace dlib;
// Here we define the sinc function so that we may generate sample data. We compute the mean,
// variance, skewness, and excess kurtosis of this sample data.
double sinc(double x)
{
 if (x == 0)
 return 1;
 return sin(x)/x;
}
int main()
{
 running_stats<double> rs;
 double tp1 = 0;
 double tp2 = 0;
 // We first generate the data and add it sequentially to our running_stats object. We
 // then print every fifth data point.
 for (int x = 1; x <= 100; x++)
 {
 tp1 = x/100.0;
 tp2 = sinc(pi*x/100.0);
 rs.add(tp2);
 if(x % 5 == 0)
 {
 cout << " x = " << tp1 << " sinc(x) = " << tp2 << endl;
 }
 }
 // Finally, we compute and print the mean, variance, skewness, and excess kurtosis of
 // our data.
 cout << endl;
 cout << "Mean: " << rs.mean() << endl;
 cout << "Variance: " << rs.variance() << endl;
 cout << "Skewness: " << rs.skewness() << endl;
 cout << "Excess Kurtosis " << rs.ex_kurtosis() << endl;
 return 0;
}