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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// Intel License Agreement
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//
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// Copyright (C) 2000, Intel Corporation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of Intel Corporation may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "precomp.hpp"
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namespace cv { namespace ml {
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struct PairDI
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{
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double d;
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int i;
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};
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struct CmpPairDI
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{
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bool operator ()(const PairDI& e1, const PairDI& e2) const
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{
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return (e1.d < e2.d) || (e1.d == e2.d && e1.i < e2.i);
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}
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};
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void createConcentricSpheresTestSet( int num_samples, int num_features, int num_classes,
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OutputArray _samples, OutputArray _responses)
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{
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if( num_samples < 1 )
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CV_Error( CV_StsBadArg, "num_samples parameter must be positive" );
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if( num_features < 1 )
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CV_Error( CV_StsBadArg, "num_features parameter must be positive" );
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if( num_classes < 1 )
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CV_Error( CV_StsBadArg, "num_classes parameter must be positive" );
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int i, cur_class;
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_samples.create( num_samples, num_features, CV_32F );
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_responses.create( 1, num_samples, CV_32S );
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Mat responses = _responses.getMat();
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Mat mean = Mat::zeros(1, num_features, CV_32F);
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Mat cov = Mat::eye(num_features, num_features, CV_32F);
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// fill the feature values matrix with random numbers drawn from standard normal distribution
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randMVNormal( mean, cov, num_samples, _samples );
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Mat samples = _samples.getMat();
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// calculate distances from the origin to the samples and put them
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// into the sequence along with indices
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std::vector<PairDI> dis(samples.rows);
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for( i = 0; i < samples.rows; i++ )
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{
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PairDI& elem = dis[i];
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elem.i = i;
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elem.d = norm(samples.row(i), NORM_L2);
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}
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std::sort(dis.begin(), dis.end(), CmpPairDI());
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// assign class labels
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num_classes = std::min( num_samples, num_classes );
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for( i = 0, cur_class = 0; i < num_samples; ++cur_class )
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{
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int last_idx = num_samples * (cur_class + 1) / num_classes - 1;
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double max_dst = dis[last_idx].d;
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max_dst = std::max( max_dst, dis[i].d );
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for( ; i < num_samples && dis[i].d <= max_dst; ++i )
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responses.at<int>(dis[i].i) = cur_class;
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}
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}
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}}
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/* End of file. */
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