Hi Thomas, you are definitely right. I was fooled by the "nice" result of the JAMA calculation, not noticing that it is there that I was extracting values in a strange order.
I now made some 3x3 tests on known results and also with the A * v = lambda * v constraint and everything is alright. I still have to figure out how to properly use the results to split higher elevation parts from lower z parts in a x,y,z dataset, but the eigenvectors and values are in the right place now. Thanks, Andrea On Mon, Nov 11, 2013 at 1:21 PM, Thomas Neidhart <thomas.neidh...@gmail.com> wrote: > On 11/11/2013 11:40 AM, andrea antonello wrote: >> Hi Thomas, >> thanks for your reply. >> >>> the result of CM and jama are identical, the difference is just in the >>> way how the data is stored. >>> >>> Afaik in jama calling getV() returns a vector in row format whereas in >>> CM the are stored in column format. >>> >>> If you transpose the matrix (or call getVT()) you will see that the >>> vectors are identical, except for the signs and order. The reason for >>> this is that for CM the eigenvalues/eigenvectors are sorted in >>> descending order in case of a symmetric matrix, which is the case for >>> your matrix. >> >> the problems is that the result is not just different in the >> transposed way. And in fact if I pick the getVT,results are still not >> the same. >> The result seems to be reflected on the secondary diagonal, not the >> primary diagonal. >> >> Furthermore, if I use the API, I do not expect to be problems of rows >> and columns, so if I use: >> >> double eigenValue = eigenDecomposition.getRealEigenvalue(i); >> RealVector eigenVector = eigenDecomposition.getEigenvector(i); >> >> I expect the eigenvector and eigenvalue to be the right ones for the >> given index, no matter how the results are given in the matrixes. >> >> But the results I get are, for the same eigenvalue: >> CM: eigenVal: 0.8056498828134406, eigenVect: [0.9015723557614027, >> 0.19005937823202243, 0.38864472217295326 >> JAMA: eigenVal: 0.8056498828134406, eigenVect: [-0.7731388420716028, >> 0.5012101463530931, -0.38864472217295326] >> >> I am still quite puzzled about what I am missing. > > I do not know how you get the eigenvector from jama, as there is no > getEigenVector method. > > The class javadoc of their EigenvalueDecomposition states: > > columns of V represent the eigenvectors in the sense that A*V = V*D, > i.e. A.times(V) equals V.times(D). The matrix V may be badly > conditioned, or even singular, so the validity of the equation > A = V*D*inverse(V) depends upon V.cond(). > > Looking at your example it looks like you took the rows of V to extract > your eigenvector. > > You can also easily verify if your eigenvector is correct: > > A * v = lambda * v > > Thomas > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@commons.apache.org > For additional commands, e-mail: user-h...@commons.apache.org > --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@commons.apache.org For additional commands, e-mail: user-h...@commons.apache.org
