realtime_stats.cpp File Reference

Compute statistics for data entered in rreal-time. More...

#include <cassert>
#include <cmath>
#include <iostream>

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Classes
class	statistics::stats_computer1< T >
class	statistics::stats_computer2< T >

Namespaces
namespace	statistics
	Statistical algorithms.

Functions
void	test_function (const float *test_data, const int number_of_samples)
int	main (int argc, char **argv)

Detailed Description

Compute statistics for data entered in rreal-time.

This algorithm is really beneficial to compute statistics on data read in realtime. For example, devices reading biometrics data. The algorithm is simple enough to be easily implemented in an embedded system.

Author

Krishna Vedala

Function Documentation

main()

int main	(	int	argc,
		char **	argv )

Main function

                                {
    const float test_data1[] = {3, 4, 5, -1.4, -3.6, 1.9, 1.};
    test_function(test_data1, sizeof(test_data1) / sizeof(test_data1[0]));
 
    std::cout
        << "Enter data. Any non-numeric data will terminate the data input."
        << std::endl;
 
    stats_computer1<float> stats1;
    stats_computer2<float> stats2;
 
    while (1) {
        double val;
        std::cout << "Enter number: ";
        std::cin >> val;
 
        // check for failure to read input. Happens for
        // non-numeric data
        if (std::cin.fail())
            break;
 
        stats1.new_val(val);
        stats2.new_val(val);
 
        std::cout << "\tMethod 1:"
                  << "\tMean: " << stats1.mean()
                  << "\t Variance: " << stats1.variance()
                  << "\t Std: " << stats1.std() << std::endl;
        std::cout << "\tMethod 2:"
                  << "\tMean: " << stats2.mean()
                  << "\t Variance: " << stats2.variance()
                  << "\t Std: " << stats2.std() << std::endl;
    }
 
    return 0;
}

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test_function()

void test_function	(	const float *	test_data,
		const int	number_of_samples )

Test the algorithm implementation

Parameters

[in]

test_data

array of data to test the algorithms

                                                                        {
    float mean = 0.f, variance = 0.f;
 
    stats_computer1<float> stats01;
    stats_computer2<float> stats02;
 
    for (int i = 0; i < number_of_samples; i++) {
        stats01.new_val(test_data[i]);
        stats02.new_val(test_data[i]);
        mean += test_data[i];
    }
 
    mean /= number_of_samples;
 
    for (int i = 0; i < number_of_samples; i++) {
        float temp = test_data[i] - mean;
        variance += temp * temp;
    }
    variance /= number_of_samples;
 
    std::cout << "<<<<<<<< Test Function >>>>>>>>" << std::endl
              << "Expected: Mean: " << mean << "\t Variance: " << variance
              << std::endl;
    std::cout << "\tMethod 1:"
              << "\tMean: " << stats01.mean()
              << "\t Variance: " << stats01.variance()
              << "\t Std: " << stats01.std() << std::endl;
    std::cout << "\tMethod 2:"
              << "\tMean: " << stats02.mean()
              << "\t Variance: " << stats02.variance()
              << "\t Std: " << stats02.std() << std::endl;
 
    assert(std::abs(stats01.mean() - mean) < 0.01);
    assert(std::abs(stats02.mean() - mean) < 0.01);
    assert(std::abs(stats02.variance() - variance) < 0.01);
 
    std::cout << "(Tests passed)" << std::endl;
}

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