On 04/30/2012 12:39 AM, Kiuhnm wrote:
So Matlab at least warns about "Matrix is close to singular or badly
scaled", which python (and I guess most other languages) does not...
A is not just close to singular: it's singular!
Ok. When do you define it to be singular, btw?
Which is the most accurate/best, even for such a bad matrix? Is it
possible to say something about that? Looks like python has a lot more
digits but maybe that's just a random result... I mean.... Element 1,1 =
2.81e14 in Python, but something like 3e14 in Matlab and so forth -
there's a small difference in the results...
Both results are *wrong*: no inverse exists.
What's the best solution of the two wrong ones? Best least-squares
solution or whatever?
With python, I would also kindly ask about how to avoid this problem in
the future, I mean, this maybe means that I have to check the condition
number at all times before doing anything at all ? How to do that?
If cond(A) is high, you're trying to solve your problem the wrong way.
So you're saying that in another language (python) I should check the
condition number, before solving anything?
You should try to avoid matrix inversion altogether if that's the case.
For instance you shouldn't invert a matrix just to solve a linear system.
What then?
Cramer's rule?
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