Numerical issues should not impinge on a computation this small.
For reference, I replicated your computation and found reasonable
eigenvalues and vectors:
> m = matrix(c(0,1,-1,1,1,0,-1,0,1), nrow=3)
> m
[,1] [,2] [,3]
[1,] 0 1 -1
[2,] 1 1 0
[3,] -1 0 1
> eig(m)
Error: could not find function "eig"
> eigen(m)
$values
[1] 2 1 -1
$vectors
[,1] [,2] [,3]
[1,] 0.5773503 0.0000000 0.8164966
[2,] 0.5773503 0.7071068 -0.4082483
[3,] -0.5773503 0.7071068 0.4082483
>
Your usage appears to be in accord with the suggested usage, but have you
tried it with a tolerance of, say, 1e-3?
On Sat, Sep 19, 2009 at 10:41 PM, Axel <axel...@gmail.com> wrote:
> Hello
>
> I'm trying to calculate the Eigenvectors of this Wikipedia example:
> http://en.wikipedia.org/wiki/Eigenvalue_algorithm#Identifying_eigenvectors
>
> with this JUnit method:
>
> public void testEigenDecomposition() {
> double[][] m = { { 0.0, 1.0, -1.0 }, { 1.0, 1.0, 0.0 }, { -1.0,
> 0.0, 1.0 } };
> RealMatrix rm = new Array2DRowRealMatrix(m);
> assertEquals(rm.toString(),
>
> "Array2DRowRealMatrix{{0.0,1.0,-1.0},{1.0,1.0,0.0},{-1.0,0.0,1.0}}");
> EigenDecompositionImpl ed = new EigenDecompositionImpl(rm,
> MathUtils.SAFE_MIN);
> RealVector rv0 = ed.getEigenvector(0);
> assertEquals(rv0.toString(), "{(NaN); (NaN); (NaN)}");
> }
>
> but I'm getting only {(NaN); (NaN); (NaN)} as a result vector.
>
> Is this intentionally (because of numerical inaccuracy?) or am I doing
> something wrong in using EigenDecompositionImpl?
>
> --
> Axel Kramer
> http://code.google.com/p/symja
>
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>
--
Ted Dunning, CTO
DeepDyve
