| /*M/////////////////////////////////////////////////////////////////////////////////////// |
| // |
| // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
| // |
| // By downloading, copying, installing or using the software you agree to this license. |
| // If you do not agree to this license, do not download, install, |
| // copy or use the software. |
| // |
| // |
| // Intel License Agreement |
| // |
| // Copyright (C) 2000, Intel Corporation, all rights reserved. |
| // Third party copyrights are property of their respective owners. |
| // |
| // Redistribution and use in source and binary forms, with or without modification, |
| // are permitted provided that the following conditions are met: |
| // |
| // * Redistribution's of source code must retain the above copyright notice, |
| // this list of conditions and the following disclaimer. |
| // |
| // * Redistribution's in binary form must reproduce the above copyright notice, |
| // this list of conditions and the following disclaimer in the documentation |
| // and/or other materials provided with the distribution. |
| // |
| // * The name of Intel Corporation may not be used to endorse or promote products |
| // derived from this software without specific prior written permission. |
| // |
| // This software is provided by the copyright holders and contributors "as is" and |
| // any express or implied warranties, including, but not limited to, the implied |
| // warranties of merchantability and fitness for a particular purpose are disclaimed. |
| // In no event shall the Intel Corporation or contributors be liable for any direct, |
| // indirect, incidental, special, exemplary, or consequential damages |
| // (including, but not limited to, procurement of substitute goods or services; |
| // loss of use, data, or profits; or business interruption) however caused |
| // and on any theory of liability, whether in contract, strict liability, |
| // or tort (including negligence or otherwise) arising in any way out of |
| // the use of this software, even if advised of the possibility of such damage. |
| // |
| //M*/ |
| |
| #include "_ml.h" |
| |
| typedef struct CvDI |
| { |
| double d; |
| int i; |
| } CvDI; |
| |
| int CV_CDECL |
| icvCmpDI( const void* a, const void* b, void* ) |
| { |
| const CvDI* e1 = (const CvDI*) a; |
| const CvDI* e2 = (const CvDI*) b; |
| |
| return (e1->d < e2->d) ? -1 : (e1->d > e2->d); |
| } |
| |
| CV_IMPL void |
| cvCreateTestSet( int type, CvMat** samples, |
| int num_samples, |
| int num_features, |
| CvMat** responses, |
| int num_classes, ... ) |
| { |
| CvMat* mean = NULL; |
| CvMat* cov = NULL; |
| CvMemStorage* storage = NULL; |
| |
| CV_FUNCNAME( "cvCreateTestSet" ); |
| |
| __BEGIN__; |
| |
| if( samples ) |
| *samples = NULL; |
| if( responses ) |
| *responses = NULL; |
| |
| if( type != CV_TS_CONCENTRIC_SPHERES ) |
| CV_ERROR( CV_StsBadArg, "Invalid type parameter" ); |
| |
| if( !samples ) |
| CV_ERROR( CV_StsNullPtr, "samples parameter must be not NULL" ); |
| |
| if( !responses ) |
| CV_ERROR( CV_StsNullPtr, "responses parameter must be not NULL" ); |
| |
| if( num_samples < 1 ) |
| CV_ERROR( CV_StsBadArg, "num_samples parameter must be positive" ); |
| |
| if( num_features < 1 ) |
| CV_ERROR( CV_StsBadArg, "num_features parameter must be positive" ); |
| |
| if( num_classes < 1 ) |
| CV_ERROR( CV_StsBadArg, "num_classes parameter must be positive" ); |
| |
| if( type == CV_TS_CONCENTRIC_SPHERES ) |
| { |
| CvSeqWriter writer; |
| CvSeqReader reader; |
| CvMat sample; |
| CvDI elem; |
| CvSeq* seq = NULL; |
| int i, cur_class; |
| |
| CV_CALL( *samples = cvCreateMat( num_samples, num_features, CV_32FC1 ) ); |
| CV_CALL( *responses = cvCreateMat( 1, num_samples, CV_32SC1 ) ); |
| CV_CALL( mean = cvCreateMat( 1, num_features, CV_32FC1 ) ); |
| CV_CALL( cvSetZero( mean ) ); |
| CV_CALL( cov = cvCreateMat( num_features, num_features, CV_32FC1 ) ); |
| CV_CALL( cvSetIdentity( cov ) ); |
| |
| /* fill the feature values matrix with random numbers drawn from standard |
| normal distribution */ |
| CV_CALL( cvRandMVNormal( mean, cov, *samples ) ); |
| |
| /* calculate distances from the origin to the samples and put them |
| into the sequence along with indices */ |
| CV_CALL( storage = cvCreateMemStorage() ); |
| CV_CALL( cvStartWriteSeq( 0, sizeof( CvSeq ), sizeof( CvDI ), storage, &writer )); |
| for( i = 0; i < (*samples)->rows; ++i ) |
| { |
| CV_CALL( cvGetRow( *samples, &sample, i )); |
| elem.i = i; |
| CV_CALL( elem.d = cvNorm( &sample, NULL, CV_L2 )); |
| CV_WRITE_SEQ_ELEM( elem, writer ); |
| } |
| CV_CALL( seq = cvEndWriteSeq( &writer ) ); |
| |
| /* sort the sequence in a distance ascending order */ |
| CV_CALL( cvSeqSort( seq, icvCmpDI, NULL ) ); |
| |
| /* assign class labels */ |
| num_classes = MIN( num_samples, num_classes ); |
| CV_CALL( cvStartReadSeq( seq, &reader ) ); |
| CV_READ_SEQ_ELEM( elem, reader ); |
| for( i = 0, cur_class = 0; i < num_samples; ++cur_class ) |
| { |
| int last_idx; |
| double max_dst; |
| |
| last_idx = num_samples * (cur_class + 1) / num_classes - 1; |
| CV_CALL( max_dst = (*((CvDI*) cvGetSeqElem( seq, last_idx ))).d ); |
| max_dst = MAX( max_dst, elem.d ); |
| |
| for( ; elem.d <= max_dst && i < num_samples; ++i ) |
| { |
| CV_MAT_ELEM( **responses, int, 0, elem.i ) = cur_class; |
| if( i < num_samples - 1 ) |
| { |
| CV_READ_SEQ_ELEM( elem, reader ); |
| } |
| } |
| } |
| } |
| |
| __END__; |
| |
| if( cvGetErrStatus() < 0 ) |
| { |
| if( samples ) |
| cvReleaseMat( samples ); |
| if( responses ) |
| cvReleaseMat( responses ); |
| } |
| cvReleaseMat( &mean ); |
| cvReleaseMat( &cov ); |
| cvReleaseMemStorage( &storage ); |
| } |
| |
| /* End of file. */ |