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/*!
* \file
* \brief Histogram class test program
* \author Andy Panov and Adam Piatyszek
*
* -------------------------------------------------------------------------
*
* IT++ - C++ library of mathematical, signal processing, speech processing,
* and communications classes and functions
*
* Copyright (C) 1995-2008 (see AUTHORS file for a list of contributors)
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
*
* -------------------------------------------------------------------------
*/
#include <itpp/itstat.h>
#include <iomanip>
using namespace itpp;
using namespace std;
void display_pdf(Histogram<double>& hist)
{
cout.setf(ios::fixed);
const int max_asterisks_per_line = 40;
ivec bins = hist.get_bins();
// compute and display experimental PDF
vec exp_pdf = hist.get_pdf();
double pdf_max = max(exp_pdf);
cout << " bin | count | PDF |" << endl
<< "------+-------+---------+-------------------------------------------"
<< endl;
for (int i = 0; i < exp_pdf.length(); i++) {
int num_asterisks = static_cast<int>(exp_pdf(i) * max_asterisks_per_line
/ pdf_max);
cout << setw(5) << setprecision(1) << round_to_zero(hist.get_bin_center(i))
<< " | " << setw(5) << hist.get_bin(i) << " | "
<< setw(7) << setprecision(5) << round_to_zero(exp_pdf(i)) << " | ";
for (int j = 0; j < num_asterisks; j++) {
cout << "*";
}
cout << endl;
}
cout << "------+-------+---------+-------------------------------------------"
<< endl;
cout << "Histogram trials counter : " << sum(hist.get_bins()) << endl;
cout << "Sum of the histogram bins : " << sum(hist.get_bins()) << endl;
cout << "Sum of PDF values : " << sum(exp_pdf) << endl;
cout << "--------------------------------------------------------------------"
<< endl << endl;
}
int main()
{
cout << "=======================" << endl;
cout << " Histogram tests " << endl;
cout << "=======================" << endl << endl;
// create histogram
Histogram<double> hist(-3, 3, 21);
// matrix dimension for statistical test
int mat_dim = 100;
cout << "Experimental PDF of " << mat_dim << "x" << mat_dim
<< " normal distributed random matrix:" << endl << endl;
// compute histogram for a random matrix
hist.update(randn(mat_dim, mat_dim));
display_pdf(hist);
// reset histogram, so we can start next experiment
hist.reset();
// compute histogram for a random vector
int num_stat_trials = 50000;
cout << "Experimental PDF of "<< num_stat_trials
<< " normal distributed random variables:" << endl << endl;
// compute histogram for random vector
hist.update(randn(num_stat_trials));
display_pdf(hist);
// compute CDF. CDF is computed vs. right bin boundaries
cout << "Experimental CDF (CDF(x) = Pr(a < x), a - random variable) " << endl
<< "of the same vector:" << endl << endl;
vec exp_cdf = hist.get_cdf();
for (int i = 0; i < exp_cdf.length(); i++)
cout << "CDF(" << setw(5) << setprecision(2) << hist.get_bin_right(i)
<< ") = " << setw(6) << setprecision(4) << exp_cdf(i) << endl;
return 0;
}
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