On 05/04/2012 05:52 AM, Steven D'Aprano wrote:
On Thu, 03 May 2012 19:30:35 +0200, someone wrote:
So how do you explain that the natural frequencies from FEM (with
condition number ~1e6) generally correlates really good with real
measurements (within approx. 5%), at least for the first 3-4
On 05/04/2012 06:15 AM, Russ P. wrote:
On May 3, 4:59 pm, someonenewsbo...@gmail.com wrote:
On 05/04/2012 12:58 AM, Russ P. wrote:
Ok, but I just don't understand what's in the empirical category, sorry...
I didn't look it up, but as far as I know, empirical just means based
on experiment,
On 05/02/2012 11:45 PM, Russ P. wrote:
On May 2, 1:29 pm, someonenewsbo...@gmail.com wrote:
If your data starts off with only 1 or 2 digits of accuracy, as in your
example, then the result is meaningless -- the accuracy will be 2-2
digits, or 0 -- *no* digits in the answer can be trusted to
On May 3, 10:30 am, someone newsbo...@gmail.com wrote:
On 05/02/2012 11:45 PM, Russ P. wrote:
On May 2, 1:29 pm, someonenewsbo...@gmail.com wrote:
If your data starts off with only 1 or 2 digits of accuracy, as in your
example, then the result is meaningless -- the accuracy will be 2-2
On 05/03/2012 07:55 PM, Russ P. wrote:
On May 3, 10:30 am, someonenewsbo...@gmail.com wrote:
On 05/02/2012 11:45 PM, Russ P. wrote:
For any practical engineering or scientific work, I'd say that a
condition number of 1e6 is very likely to be completely unacceptable.
So how do you explain
Yeah, I realized that I should rephrase my previous statement to
something like this:
For any *empirical* engineering or scientific work, I'd say that a
condition number of 1e6 is likely to be unacceptable.
I'd put finite elements into the category of theoretical and numerical
rather than
On 05/04/2012 12:58 AM, Russ P. wrote:
Yeah, I realized that I should rephrase my previous statement to
something like this:
For any *empirical* engineering or scientific work, I'd say that a
condition number of 1e6 is likely to be unacceptable.
Still, I don't understand it. Do you have an
On Thu, 03 May 2012 19:30:35 +0200, someone wrote:
On 05/02/2012 11:45 PM, Russ P. wrote:
On May 2, 1:29 pm, someonenewsbo...@gmail.com wrote:
If your data starts off with only 1 or 2 digits of accuracy, as in
your example, then the result is meaningless -- the accuracy will be
2-2 digits,
On May 3, 4:59 pm, someone newsbo...@gmail.com wrote:
On 05/04/2012 12:58 AM, Russ P. wrote:
Yeah, I realized that I should rephrase my previous statement to
something like this:
For any *empirical* engineering or scientific work, I'd say that a
condition number of 1e6 is likely to be
On 05/02/2012 01:05 AM, Paul Rubin wrote:
someonenewsbo...@gmail.com writes:
Actually I know some... I just didn't think so much about, before
writing the question this as I should, I know theres also something
like singular value decomposition that I think can help solve
otherwise illposed
On 05/02/2012 01:38 AM, Russ P. wrote:
On May 1, 4:05 pm, Paul Rubinno.em...@nospam.invalid wrote:
someonenewsbo...@gmail.com writes:
Actually I know some... I just didn't think so much about, before
writing the question this as I should, I know theres also something
like singular value
On May 1, 11:03 pm, someone newsbo...@gmail.com wrote:
On 05/02/2012 01:38 AM, Russ P. wrote:
On May 1, 4:05 pm, Paul Rubinno.em...@nospam.invalid wrote:
someonenewsbo...@gmail.com writes:
Actually I know some... I just didn't think so much about, before
writing the question
someone writes:
except it would be nice to learn some things for future use (for
instance understanding SVD more - perhaps someone geometrically can
explain SVD, that'll be really nice, I hope)...
The Wikipedia article looks promising to me:
Russ P. russ.paie...@gmail.com writes:
The SVD can be thought of as factoring any linear transformation into
a rotation, then a scaling, followed by another rotation.
Ah yes, my description was backwards, sorry.
--
http://mail.python.org/mailman/listinfo/python-list
someone newsbo...@gmail.com writes:
You will probably get better advice if you are able to describe what
problem (ill-posed or otherwise) you are actually trying to solve. SVD
I don't understand what else I should write. I gave the singular
matrix and that's it. Nothing more is to say about
On 5/2/2012 8:00, someone wrote:
Still, I dont think I completely understand SVD. SVD (at least in
Matlab) returns 3 matrices, one is a diagonal matrix I think. I think I
would better understand it with geometric examples, if one would be so
kind to maybe write something about that... I can plot
On Wed, 02 May 2012 08:00:44 +0200, someone wrote:
On 05/02/2012 01:05 AM, Paul Rubin wrote:
someonenewsbo...@gmail.com writes:
Actually I know some... I just didn't think so much about, before
writing the question this as I should, I know theres also something
like singular value
Russ P. russ.paie...@gmail.com wrote in message
news:2275231f-405f-4ee3-966a-40c821b7c...@2g2000yqp.googlegroups.com...
On May 1, 11:52 am, someone newsbo...@gmail.com wrote:
On 04/30/2012 03:35 AM, Nasser M. Abbasi wrote:
On 04/29/2012 07:59 PM, someone wrote:
I do not use python much
On 05/02/2012 01:03 PM, Kiuhnm wrote:
On 5/2/2012 8:00, someone wrote:
Still, I dont think I completely understand SVD. SVD (at least in
Matlab) returns 3 matrices, one is a diagonal matrix I think. I think I
would better understand it with geometric examples, if one would be so
kind to maybe
On 05/02/2012 08:36 AM, Russ P. wrote:
On May 1, 11:03 pm, someonenewsbo...@gmail.com wrote:
On 05/02/2012 01:38 AM, Russ P. wrote:
..
On May 1, 4:05 pm, Paul Rubinno.em...@nospam.invalidwrote:
It would really appreciate if anyone could maybe post a simple SVD
example and tell what the
On 05/02/2012 01:52 PM, Steven D'Aprano wrote:
On Wed, 02 May 2012 08:00:44 +0200, someone wrote:
On 05/02/2012 01:05 AM, Paul Rubin wrote:
someonenewsbo...@gmail.com writes:
Actually I know some... I just didn't think so much about, before
writing the question this as I should, I know
On 05/02/2012 04:47 PM, Steven_Lord wrote:
Russ, you and the OP (and others) may be interested in one of the books
that Cleve Moler has written and made freely available on the MathWorks
website:
http://www.mathworks.com/moler/
The chapter Linear Equations in Numerical Computing with MATLAB
On May 2, 1:29 pm, someone newsbo...@gmail.com wrote:
If your data starts off with only 1 or 2 digits of accuracy, as in your
example, then the result is meaningless -- the accuracy will be 2-2
digits, or 0 -- *no* digits in the answer can be trusted to be accurate.
I just solved a FEM
On Apr 29, 5:17 pm, someone newsbo...@gmail.com wrote:
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
There is linalg.pinv, which computes a pseudoinverse based on SVD that
works on all matrices, regardless of the rank of the matrix. It merely
approximates A*A.I = I as well as A permits though, rather than being
a true inverse, which may not exist.
Anyway, there are no general answers for this
On 04/30/2012 02:57 AM, Paul Rubin wrote:
someonenewsbo...@gmail.com writes:
A is not just close to singular: it's singular!
Ok. When do you define it to be singular, btw?
Singular means the determinant is zero, i.e. the rows or columns
are not linearly independent. Let's give names to the
On 05/01/2012 08:56 AM, Russ P. wrote:
On Apr 29, 5:17 pm, someonenewsbo...@gmail.com wrote:
On 04/30/2012 12:39 AM, Kiuhnm wrote:
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?
On 04/30/2012 03:35 AM, Nasser M. Abbasi wrote:
On 04/29/2012 07:59 PM, someone wrote:
I do not use python much myself, but a quick google showed that pyhton
scipy has API for linalg, so use, which is from the documentation, the
following code example
X = scipy.linalg.solve(A, B)
But you still
I'm making my first steps now with numpy, so there's a lot I don't know
and haven't tried with numpy...
An excellent reason to subscribe to the numpy mailing list and
talk on there :)
Ramit
Ramit Prasad | JPMorgan Chase Investment Bank | Currencies Technology
712 Main Street | Houston, TX
On 01/05/2012 2:43 PM, someone wrote:
[snip]
a = [1 2 3]; b = [11 12 13]; c = [21 22 23].
Then notice that c = 2*b - a. So c is linearly dependent on a and b.
Geometrically this means the three vectors are in the same plane,
so the matrix doesn't have an inverse.
Does it not mean that there
On May 1, 11:52 am, someone newsbo...@gmail.com wrote:
On 04/30/2012 03:35 AM, Nasser M. Abbasi wrote:
On 04/29/2012 07:59 PM, someone wrote:
I do not use python much myself, but a quick google showed that pyhton
scipy has API for linalg, so use, which is from the documentation, the
On 05/01/2012 09:59 PM, Colin J. Williams wrote:
On 01/05/2012 2:43 PM, someone wrote:
[snip]
a = [1 2 3]; b = [11 12 13]; c = [21 22 23].
Then notice that c = 2*b - a. So c is linearly dependent on a and b.
Geometrically this means the three vectors are in the same plane,
so the matrix
On 05/01/2012 10:54 PM, Russ P. wrote:
On May 1, 11:52 am, someonenewsbo...@gmail.com wrote:
On 04/30/2012 03:35 AM, Nasser M. Abbasi wrote:
What's the limit in matlab (on the condition number of the matrices), by
the way, before it comes up with a warning ???
The threshold of
On 5/1/12 10:21 PM, someone wrote:
On 05/01/2012 10:54 PM, Russ P. wrote:
On May 1, 11:52 am, someonenewsbo...@gmail.com wrote:
On 04/30/2012 03:35 AM, Nasser M. Abbasi wrote:
What's the limit in matlab (on the condition number of the matrices), by
the way, before it comes up with a warning
On 5/1/2012 21:59, Colin J. Williams wrote:
On 01/05/2012 2:43 PM, someone wrote:
[snip]
a = [1 2 3]; b = [11 12 13]; c = [21 22 23].
Then notice that c = 2*b - a. So c is linearly dependent on a and b.
Geometrically this means the three vectors are in the same plane,
so the matrix doesn't
someone newsbo...@gmail.com writes:
Actually I know some... I just didn't think so much about, before
writing the question this as I should, I know theres also something
like singular value decomposition that I think can help solve
otherwise illposed problems,
You will probably get better
On May 1, 4:05 pm, Paul Rubin no.em...@nospam.invalid wrote:
someone newsbo...@gmail.com writes:
Actually I know some... I just didn't think so much about, before
writing the question this as I should, I know theres also something
like singular value decomposition that I think can help
On 4/30/2012 2:17, someone wrote:
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
On 4/30/2012 3:35, Nasser M. Abbasi wrote:
But you still need to check the cond(). If it is too large, not good.
How large and all that, depends on the problem itself. But the rule of
thumb, the lower the better. Less than 100 can be good in general, but I
really can't give you a fixed number to
On 4/30/2012 0:17, someone wrote:
Hi,
Notice cross-post, I hope you bear over with me for doing that (and I
imagine that some of you also like python in the matlab-group like
myself)...
--
Python vs. Matlab:
--
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
On 04/29/2012 05:17 PM, someone wrote:
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?
I hope you'll check the condition number all the time.
someone newsbo...@gmail.com writes:
A is not just close to singular: it's singular!
Ok. When do you define it to be singular, btw?
Singular means the determinant is zero, i.e. the rows or columns
are not linearly independent. Let's give names to the three rows:
a = [1 2 3]; b = [11 12 13];
On 04/30/2012 02:38 AM, Nasser M. Abbasi wrote:
On 04/29/2012 05:17 PM, someone wrote:
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?
I hope
On 04/29/2012 07:59 PM, someone wrote:
Also, as was said, do not use INV(A) directly to solve equations.
In Matlab I used x=A\b.
good.
I used inv(A) in python. Should I use some kind of pseudo-inverse or
what do you suggest?
I do not use python much myself, but a quick google showed
On 04/29/2012 07:17 PM, someone wrote:
Ok. When do you define it to be singular, btw?
There are things you can see right away about a matrix A being singular
without doing any computation. By just looking at it.
For example, If you see a column (or row) being a linear combination of
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