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core(test): refactor PCA test
- CV_L2 -> relative NORM_L2 - eigenEps: 1e-6 ==> 1e-4 - evalEps: 1e-6 ==> 1e-5 - evecEps: 1e-3 ==> 5e-3 - RNG seed: 12345 - drop non-informative legacy test code (ts->printf, etc)
This commit is contained in:
Alexander Alekhin
Alexander Alekhin
parent
611cf8d86f
commit
d48d2d7fe2
@ -286,258 +286,188 @@ void Core_ReduceTest::run( int )
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#define CHECK_C
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class Core_PCATest : public cvtest::BaseTest
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TEST(Core_PCA, accuracy)
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{
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public:
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Core_PCATest() {}
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protected:
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void run(int)
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const Size sz(200, 500);
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double diffPrjEps, diffBackPrjEps,
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prjEps, backPrjEps,
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evalEps, evecEps;
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int maxComponents = 100;
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double retainedVariance = 0.95;
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Mat rPoints(sz, CV_32FC1), rTestPoints(sz, CV_32FC1);
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RNG rng(12345);
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rng.fill( rPoints, RNG::UNIFORM, Scalar::all(0.0), Scalar::all(1.0) );
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rng.fill( rTestPoints, RNG::UNIFORM, Scalar::all(0.0), Scalar::all(1.0) );
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PCA rPCA( rPoints, Mat(), CV_PCA_DATA_AS_ROW, maxComponents ), cPCA;
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// 1. check C++ PCA & ROW
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Mat rPrjTestPoints = rPCA.project( rTestPoints );
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Mat rBackPrjTestPoints = rPCA.backProject( rPrjTestPoints );
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Mat avg(1, sz.width, CV_32FC1 );
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cv::reduce( rPoints, avg, 0, CV_REDUCE_AVG );
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Mat Q = rPoints - repeat( avg, rPoints.rows, 1 ), Qt = Q.t(), eval, evec;
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Q = Qt * Q;
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Q = Q /(float)rPoints.rows;
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eigen( Q, eval, evec );
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/*SVD svd(Q);
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evec = svd.vt;
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eval = svd.w;*/
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Mat subEval( maxComponents, 1, eval.type(), eval.ptr() ),
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subEvec( maxComponents, evec.cols, evec.type(), evec.ptr() );
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#ifdef CHECK_C
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Mat prjTestPoints, backPrjTestPoints, cPoints = rPoints.t(), cTestPoints = rTestPoints.t();
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CvMat _points, _testPoints, _avg, _eval, _evec, _prjTestPoints, _backPrjTestPoints;
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#endif
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// check eigen()
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double eigenEps = 1e-4;
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double err;
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for(int i = 0; i < Q.rows; i++ )
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{
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const Size sz(200, 500);
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Mat v = evec.row(i).t();
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Mat Qv = Q * v;
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double diffPrjEps, diffBackPrjEps,
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prjEps, backPrjEps,
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evalEps, evecEps;
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int maxComponents = 100;
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double retainedVariance = 0.95;
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Mat rPoints(sz, CV_32FC1), rTestPoints(sz, CV_32FC1);
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RNG& rng = ts->get_rng();
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rng.fill( rPoints, RNG::UNIFORM, Scalar::all(0.0), Scalar::all(1.0) );
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rng.fill( rTestPoints, RNG::UNIFORM, Scalar::all(0.0), Scalar::all(1.0) );
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PCA rPCA( rPoints, Mat(), CV_PCA_DATA_AS_ROW, maxComponents ), cPCA;
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// 1. check C++ PCA & ROW
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Mat rPrjTestPoints = rPCA.project( rTestPoints );
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Mat rBackPrjTestPoints = rPCA.backProject( rPrjTestPoints );
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Mat avg(1, sz.width, CV_32FC1 );
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cv::reduce( rPoints, avg, 0, CV_REDUCE_AVG );
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Mat Q = rPoints - repeat( avg, rPoints.rows, 1 ), Qt = Q.t(), eval, evec;
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Q = Qt * Q;
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Q = Q /(float)rPoints.rows;
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eigen( Q, eval, evec );
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/*SVD svd(Q);
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evec = svd.vt;
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eval = svd.w;*/
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Mat subEval( maxComponents, 1, eval.type(), eval.ptr() ),
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subEvec( maxComponents, evec.cols, evec.type(), evec.ptr() );
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#ifdef CHECK_C
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Mat prjTestPoints, backPrjTestPoints, cPoints = rPoints.t(), cTestPoints = rTestPoints.t();
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CvMat _points, _testPoints, _avg, _eval, _evec, _prjTestPoints, _backPrjTestPoints;
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#endif
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// check eigen()
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double eigenEps = 1e-6;
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double err;
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for(int i = 0; i < Q.rows; i++ )
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Mat lv = eval.at<float>(i,0) * v;
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err = cvtest::norm(Qv, lv, NORM_L2 | NORM_RELATIVE);
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EXPECT_LE(err, eigenEps) << "bad accuracy of eigen(); i = " << i;
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}
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// check pca eigenvalues
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evalEps = 1e-5, evecEps = 5e-3;
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err = cvtest::norm(rPCA.eigenvalues, subEval, NORM_L2 | NORM_RELATIVE);
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EXPECT_LE(err , evalEps) << "pca.eigenvalues is incorrect (CV_PCA_DATA_AS_ROW)";
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// check pca eigenvectors
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for(int i = 0; i < subEvec.rows; i++)
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{
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Mat r0 = rPCA.eigenvectors.row(i);
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Mat r1 = subEvec.row(i);
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// eigenvectors have normalized length, but both directions v and -v are valid
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double err1 = cvtest::norm(r0, r1, NORM_L2 | NORM_RELATIVE);
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double err2 = cvtest::norm(r0, -r1, NORM_L2 | NORM_RELATIVE);
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err = std::min(err1, err2);
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if (err > evecEps)
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{
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Mat v = evec.row(i).t();
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Mat Qv = Q * v;
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Mat tmp;
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absdiff(rPCA.eigenvectors, subEvec, tmp);
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double mval = 0; Point mloc;
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minMaxLoc(tmp, 0, &mval, 0, &mloc);
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Mat lv = eval.at<float>(i,0) * v;
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err = cvtest::norm( Qv, lv, NORM_L2 );
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if( err > eigenEps )
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{
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ts->printf( cvtest::TS::LOG, "bad accuracy of eigen(); err = %f\n", err );
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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return;
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}
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}
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// check pca eigenvalues
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evalEps = 1e-6, evecEps = 1e-3;
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err = cvtest::norm( rPCA.eigenvalues, subEval, NORM_L2 );
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if( err > evalEps )
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{
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ts->printf( cvtest::TS::LOG, "pca.eigenvalues is incorrect (CV_PCA_DATA_AS_ROW); err = %f\n", err );
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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return;
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}
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// check pca eigenvectors
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for(int i = 0; i < subEvec.rows; i++)
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{
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Mat r0 = rPCA.eigenvectors.row(i);
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Mat r1 = subEvec.row(i);
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err = cvtest::norm( r0, r1, CV_L2 );
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if( err > evecEps )
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{
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r1 *= -1;
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double err2 = cvtest::norm(r0, r1, CV_L2);
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if( err2 > evecEps )
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{
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Mat tmp;
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absdiff(rPCA.eigenvectors, subEvec, tmp);
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double mval = 0; Point mloc;
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minMaxLoc(tmp, 0, &mval, 0, &mloc);
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ts->printf( cvtest::TS::LOG, "pca.eigenvectors is incorrect (CV_PCA_DATA_AS_ROW); err = %f\n", err );
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ts->printf( cvtest::TS::LOG, "max diff is %g at (i=%d, j=%d) (%g vs %g)\n",
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mval, mloc.y, mloc.x, rPCA.eigenvectors.at<float>(mloc.y, mloc.x),
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subEvec.at<float>(mloc.y, mloc.x));
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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return;
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}
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}
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}
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prjEps = 1.265, backPrjEps = 1.265;
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for( int i = 0; i < rTestPoints.rows; i++ )
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{
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// check pca project
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Mat subEvec_t = subEvec.t();
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Mat prj = rTestPoints.row(i) - avg; prj *= subEvec_t;
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err = cvtest::norm(rPrjTestPoints.row(i), prj, CV_RELATIVE_L2);
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if( err > prjEps )
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{
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ts->printf( cvtest::TS::LOG, "bad accuracy of project() (CV_PCA_DATA_AS_ROW); err = %f\n", err );
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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return;
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}
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// check pca backProject
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Mat backPrj = rPrjTestPoints.row(i) * subEvec + avg;
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err = cvtest::norm( rBackPrjTestPoints.row(i), backPrj, CV_RELATIVE_L2 );
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if( err > backPrjEps )
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{
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ts->printf( cvtest::TS::LOG, "bad accuracy of backProject() (CV_PCA_DATA_AS_ROW); err = %f\n", err );
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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return;
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}
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}
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// 2. check C++ PCA & COL
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cPCA( rPoints.t(), Mat(), CV_PCA_DATA_AS_COL, maxComponents );
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diffPrjEps = 1, diffBackPrjEps = 1;
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Mat ocvPrjTestPoints = cPCA.project(rTestPoints.t());
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err = cvtest::norm(cv::abs(ocvPrjTestPoints), cv::abs(rPrjTestPoints.t()), CV_RELATIVE_L2 );
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if( err > diffPrjEps )
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{
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ts->printf( cvtest::TS::LOG, "bad accuracy of project() (CV_PCA_DATA_AS_COL); err = %f\n", err );
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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return;
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}
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err = cvtest::norm(cPCA.backProject(ocvPrjTestPoints), rBackPrjTestPoints.t(), CV_RELATIVE_L2 );
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if( err > diffBackPrjEps )
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{
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ts->printf( cvtest::TS::LOG, "bad accuracy of backProject() (CV_PCA_DATA_AS_COL); err = %f\n", err );
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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return;
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}
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// 3. check C++ PCA w/retainedVariance
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cPCA( rPoints.t(), Mat(), CV_PCA_DATA_AS_COL, retainedVariance );
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diffPrjEps = 1, diffBackPrjEps = 1;
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Mat rvPrjTestPoints = cPCA.project(rTestPoints.t());
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if( cPCA.eigenvectors.rows > maxComponents)
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err = cvtest::norm(cv::abs(rvPrjTestPoints.rowRange(0,maxComponents)), cv::abs(rPrjTestPoints.t()), CV_RELATIVE_L2 );
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else
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err = cvtest::norm(cv::abs(rvPrjTestPoints), cv::abs(rPrjTestPoints.colRange(0,cPCA.eigenvectors.rows).t()), CV_RELATIVE_L2 );
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if( err > diffPrjEps )
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{
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ts->printf( cvtest::TS::LOG, "bad accuracy of project() (CV_PCA_DATA_AS_COL); retainedVariance=0.95; err = %f\n", err );
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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return;
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}
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err = cvtest::norm(cPCA.backProject(rvPrjTestPoints), rBackPrjTestPoints.t(), CV_RELATIVE_L2 );
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if( err > diffBackPrjEps )
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{
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ts->printf( cvtest::TS::LOG, "bad accuracy of backProject() (CV_PCA_DATA_AS_COL); retainedVariance=0.95; err = %f\n", err );
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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return;
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}
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#ifdef CHECK_C
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// 4. check C PCA & ROW
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_points = rPoints;
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_testPoints = rTestPoints;
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_avg = avg;
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_eval = eval;
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_evec = evec;
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prjTestPoints.create(rTestPoints.rows, maxComponents, rTestPoints.type() );
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backPrjTestPoints.create(rPoints.size(), rPoints.type() );
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_prjTestPoints = prjTestPoints;
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_backPrjTestPoints = backPrjTestPoints;
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cvCalcPCA( &_points, &_avg, &_eval, &_evec, CV_PCA_DATA_AS_ROW );
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cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints );
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cvBackProjectPCA( &_prjTestPoints, &_avg, &_evec, &_backPrjTestPoints );
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err = cvtest::norm(prjTestPoints, rPrjTestPoints, CV_RELATIVE_L2);
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if( err > diffPrjEps )
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{
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ts->printf( cvtest::TS::LOG, "bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_ROW); err = %f\n", err );
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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return;
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}
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err = cvtest::norm(backPrjTestPoints, rBackPrjTestPoints, CV_RELATIVE_L2);
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if( err > diffBackPrjEps )
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{
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ts->printf( cvtest::TS::LOG, "bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_ROW); err = %f\n", err );
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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return;
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}
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// 5. check C PCA & COL
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_points = cPoints;
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_testPoints = cTestPoints;
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avg = avg.t(); _avg = avg;
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eval = eval.t(); _eval = eval;
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evec = evec.t(); _evec = evec;
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prjTestPoints = prjTestPoints.t(); _prjTestPoints = prjTestPoints;
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backPrjTestPoints = backPrjTestPoints.t(); _backPrjTestPoints = backPrjTestPoints;
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cvCalcPCA( &_points, &_avg, &_eval, &_evec, CV_PCA_DATA_AS_COL );
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cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints );
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cvBackProjectPCA( &_prjTestPoints, &_avg, &_evec, &_backPrjTestPoints );
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err = cvtest::norm(cv::abs(prjTestPoints), cv::abs(rPrjTestPoints.t()), CV_RELATIVE_L2 );
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if( err > diffPrjEps )
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{
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ts->printf( cvtest::TS::LOG, "bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_COL); err = %f\n", err );
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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return;
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}
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err = cvtest::norm(backPrjTestPoints, rBackPrjTestPoints.t(), CV_RELATIVE_L2);
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if( err > diffBackPrjEps )
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{
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ts->printf( cvtest::TS::LOG, "bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_COL); err = %f\n", err );
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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return;
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}
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#endif
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// Test read and write
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FileStorage fs( "PCA_store.yml", FileStorage::WRITE );
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rPCA.write( fs );
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fs.release();
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PCA lPCA;
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fs.open( "PCA_store.yml", FileStorage::READ );
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lPCA.read( fs.root() );
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err = cvtest::norm( rPCA.eigenvectors, lPCA.eigenvectors, CV_RELATIVE_L2 );
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if( err > 0 )
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{
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ts->printf( cvtest::TS::LOG, "bad accuracy of write/load functions (YML); err = %f\n", err );
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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}
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err = cvtest::norm( rPCA.eigenvalues, lPCA.eigenvalues, CV_RELATIVE_L2 );
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if( err > 0 )
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{
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ts->printf( cvtest::TS::LOG, "bad accuracy of write/load functions (YML); err = %f\n", err );
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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}
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err = cvtest::norm( rPCA.mean, lPCA.mean, CV_RELATIVE_L2 );
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if( err > 0 )
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{
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ts->printf( cvtest::TS::LOG, "bad accuracy of write/load functions (YML); err = %f\n", err );
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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EXPECT_LE(err, evecEps) << "pca.eigenvectors is incorrect (CV_PCA_DATA_AS_ROW) at " << i << " "
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<< cv::format("max diff is %g at (i=%d, j=%d) (%g vs %g)\n",
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mval, mloc.y, mloc.x, rPCA.eigenvectors.at<float>(mloc.y, mloc.x),
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subEvec.at<float>(mloc.y, mloc.x))
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<< "r0=" << r0 << std::endl
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<< "r1=" << r1 << std::endl
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<< "err1=" << err1 << " err2=" << err2
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;
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}
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}
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};
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prjEps = 1.265, backPrjEps = 1.265;
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for( int i = 0; i < rTestPoints.rows; i++ )
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{
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// check pca project
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Mat subEvec_t = subEvec.t();
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Mat prj = rTestPoints.row(i) - avg; prj *= subEvec_t;
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err = cvtest::norm(rPrjTestPoints.row(i), prj, NORM_L2 | NORM_RELATIVE);
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if (err < prjEps)
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{
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EXPECT_LE(err, prjEps) << "bad accuracy of project() (CV_PCA_DATA_AS_ROW)";
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continue;
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}
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// check pca backProject
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Mat backPrj = rPrjTestPoints.row(i) * subEvec + avg;
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err = cvtest::norm(rBackPrjTestPoints.row(i), backPrj, NORM_L2 | NORM_RELATIVE);
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if (err > backPrjEps)
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{
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EXPECT_LE(err, backPrjEps) << "bad accuracy of backProject() (CV_PCA_DATA_AS_ROW)";
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continue;
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}
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}
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// 2. check C++ PCA & COL
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cPCA( rPoints.t(), Mat(), CV_PCA_DATA_AS_COL, maxComponents );
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diffPrjEps = 1, diffBackPrjEps = 1;
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Mat ocvPrjTestPoints = cPCA.project(rTestPoints.t());
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err = cvtest::norm(cv::abs(ocvPrjTestPoints), cv::abs(rPrjTestPoints.t()), NORM_L2 | NORM_RELATIVE);
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ASSERT_LE(err, diffPrjEps) << "bad accuracy of project() (CV_PCA_DATA_AS_COL)";
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err = cvtest::norm(cPCA.backProject(ocvPrjTestPoints), rBackPrjTestPoints.t(), NORM_L2 | NORM_RELATIVE);
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ASSERT_LE(err, diffBackPrjEps) << "bad accuracy of backProject() (CV_PCA_DATA_AS_COL)";
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|
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// 3. check C++ PCA w/retainedVariance
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cPCA( rPoints.t(), Mat(), CV_PCA_DATA_AS_COL, retainedVariance );
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diffPrjEps = 1, diffBackPrjEps = 1;
|
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Mat rvPrjTestPoints = cPCA.project(rTestPoints.t());
|
||||
|
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if( cPCA.eigenvectors.rows > maxComponents)
|
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err = cvtest::norm(cv::abs(rvPrjTestPoints.rowRange(0,maxComponents)), cv::abs(rPrjTestPoints.t()), NORM_L2 | NORM_RELATIVE);
|
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else
|
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err = cvtest::norm(cv::abs(rvPrjTestPoints), cv::abs(rPrjTestPoints.colRange(0,cPCA.eigenvectors.rows).t()), NORM_L2 | NORM_RELATIVE);
|
||||
|
||||
ASSERT_LE(err, diffPrjEps) << "bad accuracy of project() (CV_PCA_DATA_AS_COL); retainedVariance=" << retainedVariance;
|
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err = cvtest::norm(cPCA.backProject(rvPrjTestPoints), rBackPrjTestPoints.t(), NORM_L2 | NORM_RELATIVE);
|
||||
ASSERT_LE(err, diffBackPrjEps) << "bad accuracy of backProject() (CV_PCA_DATA_AS_COL); retainedVariance=" << retainedVariance;
|
||||
|
||||
#ifdef CHECK_C
|
||||
// 4. check C PCA & ROW
|
||||
_points = rPoints;
|
||||
_testPoints = rTestPoints;
|
||||
_avg = avg;
|
||||
_eval = eval;
|
||||
_evec = evec;
|
||||
prjTestPoints.create(rTestPoints.rows, maxComponents, rTestPoints.type() );
|
||||
backPrjTestPoints.create(rPoints.size(), rPoints.type() );
|
||||
_prjTestPoints = prjTestPoints;
|
||||
_backPrjTestPoints = backPrjTestPoints;
|
||||
|
||||
cvCalcPCA( &_points, &_avg, &_eval, &_evec, CV_PCA_DATA_AS_ROW );
|
||||
cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints );
|
||||
cvBackProjectPCA( &_prjTestPoints, &_avg, &_evec, &_backPrjTestPoints );
|
||||
|
||||
err = cvtest::norm(prjTestPoints, rPrjTestPoints, NORM_L2 | NORM_RELATIVE);
|
||||
ASSERT_LE(err, diffPrjEps) << "bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_ROW)";
|
||||
err = cvtest::norm(backPrjTestPoints, rBackPrjTestPoints, NORM_L2 | NORM_RELATIVE);
|
||||
ASSERT_LE(err, diffBackPrjEps) << "bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_ROW)";
|
||||
|
||||
// 5. check C PCA & COL
|
||||
_points = cPoints;
|
||||
_testPoints = cTestPoints;
|
||||
avg = avg.t(); _avg = avg;
|
||||
eval = eval.t(); _eval = eval;
|
||||
evec = evec.t(); _evec = evec;
|
||||
prjTestPoints = prjTestPoints.t(); _prjTestPoints = prjTestPoints;
|
||||
backPrjTestPoints = backPrjTestPoints.t(); _backPrjTestPoints = backPrjTestPoints;
|
||||
|
||||
cvCalcPCA( &_points, &_avg, &_eval, &_evec, CV_PCA_DATA_AS_COL );
|
||||
cvProjectPCA( &_testPoints, &_avg, &_evec, &_prjTestPoints );
|
||||
cvBackProjectPCA( &_prjTestPoints, &_avg, &_evec, &_backPrjTestPoints );
|
||||
|
||||
err = cvtest::norm(cv::abs(prjTestPoints), cv::abs(rPrjTestPoints.t()), NORM_L2 | NORM_RELATIVE);
|
||||
ASSERT_LE(err, diffPrjEps) << "bad accuracy of cvProjectPCA() (CV_PCA_DATA_AS_COL)";
|
||||
err = cvtest::norm(backPrjTestPoints, rBackPrjTestPoints.t(), NORM_L2 | NORM_RELATIVE);
|
||||
ASSERT_LE(err, diffBackPrjEps) << "bad accuracy of cvBackProjectPCA() (CV_PCA_DATA_AS_COL)";
|
||||
#endif
|
||||
// Test read and write
|
||||
FileStorage fs( "PCA_store.yml", FileStorage::WRITE );
|
||||
rPCA.write( fs );
|
||||
fs.release();
|
||||
|
||||
PCA lPCA;
|
||||
fs.open( "PCA_store.yml", FileStorage::READ );
|
||||
lPCA.read( fs.root() );
|
||||
err = cvtest::norm(rPCA.eigenvectors, lPCA.eigenvectors, NORM_L2 | NORM_RELATIVE);
|
||||
EXPECT_LE(err, 0) << "bad accuracy of write/load functions (YML)";
|
||||
err = cvtest::norm(rPCA.eigenvalues, lPCA.eigenvalues, NORM_L2 | NORM_RELATIVE);
|
||||
EXPECT_LE(err, 0) << "bad accuracy of write/load functions (YML)";
|
||||
err = cvtest::norm(rPCA.mean, lPCA.mean, NORM_L2 | NORM_RELATIVE);
|
||||
EXPECT_LE(err, 0) << "bad accuracy of write/load functions (YML)";
|
||||
}
|
||||
|
||||
class Core_ArrayOpTest : public cvtest::BaseTest
|
||||
{
|
||||
@ -1227,7 +1157,6 @@ protected:
|
||||
}
|
||||
};
|
||||
|
||||
TEST(Core_PCA, accuracy) { Core_PCATest test; test.safe_run(); }
|
||||
TEST(Core_Reduce, accuracy) { Core_ReduceTest test; test.safe_run(); }
|
||||
TEST(Core_Array, basic_operations) { Core_ArrayOpTest test; test.safe_run(); }
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user