Le 24/08/2011 00:59, Greg Sterijevski a écrit :
Should I open a ticket, or do you want to handle this?
Please open a ticket.
For the moment, I am busy in other parts (integration, geometry and ODE)
and don't fiddle with linear algebra.
Luc
On Tue, Aug 23, 2011 at 5:47 PM, Luc Maisonobewro
Should I open a ticket, or do you want to handle this?
On Tue, Aug 23, 2011 at 5:47 PM, Luc Maisonobe wrote:
> Le 24/08/2011 00:44, Greg Sterijevski a écrit :
>
> I understand you want to support the general case, but why should it
>> necessitate instantiating a ref.
>>
>
> You are right, we cou
Le 24/08/2011 00:44, Greg Sterijevski a écrit :
I understand you want to support the general case, but why should it
necessitate instantiating a ref.
You are right, we could go with an array allocated only upon request.
Luc
On Tue, Aug 23, 2011 at 5:29 PM, Luc Maisonobewrote:
Le 23/08/201
I understand you want to support the general case, but why should it
necessitate instantiating a ref.
On Tue, Aug 23, 2011 at 5:29 PM, Luc Maisonobe wrote:
> Le 23/08/2011 20:45, Greg Sterijevski a écrit :
>
> Hello All,
>>
>> Since math gives eigendecomposition for symmetrics, why even allocate
Le 23/08/2011 20:45, Greg Sterijevski a écrit :
Hello All,
Since math gives eigendecomposition for symmetrics, why even allocate the
array imagEigenvalues ?
What am I missing?
For now, we are limited to symmetric matrices because we did not
implement anything else. However, we did prepare the
Hello All,
Since math gives eigendecomposition for symmetrics, why even allocate the
array imagEigenvalues ?
What am I missing?
Thanks,
-Greg
Ted Dunning wrote:
> 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,]01 -1
> [2,]11
On Sun, Sep 20, 2009 at 7:51 AM, Ted Dunning wrote:
> Numerical issues should not impinge on a computation this small.
...
> Your usage appears to be in accord with the suggested usage, but have you
> tried it with a tolerance of, say, 1e-3?
This gives the same result: {(NaN); (NaN); (NaN)}
--
Ax
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,]01 -1
[2,]110
[3,] -101
> eig(m)
Err
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 } };
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