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