--- /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