Hi, The results are OK, they are very close. Your matrix is almost singular, is badly conditionned, ... But the results are very close is you check them in a relative way. 3.84433376e-03 or -6.835301757686207E-4 is the same compared to 2.76980401e+13
Matthieu 2008/2/20, [EMAIL PROTECTED] <[EMAIL PROTECTED]>: > > hi > i was calculating eigenvalues and eigenvectors for a covariancematrix > using numpy > > adjfaces=matrix(adjarr) > faces_trans=adjfaces.transpose() > covarmat=adjfaces*faces_trans > evalues,evect=eigh(covarmat) > > for a sample covarmat like > [[ 1.69365981e+13 , -5.44960784e+12, -9.00346400e+12 , -2.48352625e > +12] > [ -5.44960784e+12, 5.08860660e+12, -8.67539205e+11 , 1.22854045e > +12] > [ -9.00346400e+12, -8.67539205e+11, 1.78184943e+13 ,-7.94749110e > +12] > [ -2.48352625e+12 , 1.22854045e+12, -7.94749110e+12 , 9.20247690e > +12]] > > i get these > evalues > [ 3.84433376e-03, 4.17099934e+12 , 1.71771364e+13 , 2.76980401e+13] > > evect > [[ 0.5 -0.04330262 0.60041892 -0.62259297] > [ 0.5 -0.78034307 -0.35933516 0.10928372] > [ 0.5 0.25371931 0.3700265 0.74074753] > [ 0.5 0.56992638 -0.61111026 -0.22743827]] > > what bothers me is that for the same covarmat i get a different set of > eigenvectors and eigenvalues when i use java library Jama's methods > Matrix faceM = new Matrix(faces, nrfaces,length); > Matrix faceM_transpose = faceM.transpose(); > Matrix covarM = faceM.times(faceM_transpose); > EigenvalueDecomposition E = covarM.eig(); > double[] eigValue = diag(E.getD().getArray()); > double[][] eigVector = E.getV().getArray(); > > here the eigValue= > [-6.835301757686207E-4, 4.170999335736721E12, 1.7177136443134865E13, > 2.7698040117669414E13] > > and eigVector > [ > [0.5, -0.04330262221379265, 0.6004189175979487, 0.6225929700052174], > [0.5, -0.7803430730840767, -0.3593351608695496, -0.10928371540423852], > [0.49999999999999994, 0.2537193127299541, 0.370026504572483, > -0.7407475253159538], > [0.49999999999999994, 0.5699263825679145, -0.6111102613008821, > 0.22743827071497524] > ] > > I am quite confused bythis difference in results ..the first element > in eigValue is different and also the signs in last column of > eigVectors are diff..can someone tell me why this happens? > thanks > dn > > > > > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion > -- French PhD student Website : http://matthieu-brucher.developpez.com/ Blogs : http://matt.eifelle.com and http://blog.developpez.com/?blog=92 LinkedIn : http://www.linkedin.com/in/matthieubrucher
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