+++ /dev/null
-/*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. */
projects / opencv / blobdiff