Hi,
16.02.2012 06:09, josef.p...@gmail.com kirjoitti:
[clip]
numpy linalg.svd doesn't produce always the same results
running this gives two different answers,
using scipy.linalg.svd I always get the same answer, which is one of
the numpy answers
(numpy random.multivariate_normal is
On Thu, Feb 16, 2012 at 4:44 AM, Pauli Virtanen p...@iki.fi wrote:
Hi,
16.02.2012 06:09, josef.p...@gmail.com kirjoitti:
[clip]
numpy linalg.svd doesn't produce always the same results
running this gives two different answers,
using scipy.linalg.svd I always get the same answer, which is
16.02.2012 14:14, josef.p...@gmail.com kirjoitti:
[clip]
We had other cases of several patterns in quasi-deterministic linalg
before, but as far as I remember only in the final digits of
precision, where it didn't matter much except for reducing test
precision in my cases.
In the random
On Thu, Feb 16, 2012 at 8:45 AM, Pauli Virtanen p...@iki.fi wrote:
16.02.2012 14:14, josef.p...@gmail.com kirjoitti:
[clip]
We had other cases of several patterns in quasi-deterministic linalg
before, but as far as I remember only in the final digits of
precision, where it didn't matter much
16.02.2012 14:54, josef.p...@gmail.com kirjoitti:
[clip]
If I interpret you correctly, this should be a svd ticket, or an svd
ticket as duplicate ?
I think it should be a multivariate normal ticket.
Fixing SVD is in my opinion not sensible: its only guarantee is that A
= U S V^H down to
On Thu, Feb 16, 2012 at 9:08 AM, Pauli Virtanen p...@iki.fi wrote:
16.02.2012 14:54, josef.p...@gmail.com kirjoitti:
[clip]
If I interpret you correctly, this should be a svd ticket, or an svd
ticket as duplicate ?
I think it should be a multivariate normal ticket.
Fixing SVD is in my
On Thu, Feb 16, 2012 at 10:12 AM, Pierre Haessig
pierre.haes...@crans.orgwrote:
Le 16/02/2012 16:20, josef.p...@gmail.com a écrit :
I don't see any way to fix multivariate_normal for this case, except
for dropping svd or for random perturbing a covariance matrix with
multiplicity of
On Thu, Feb 16, 2012 at 16:12, Pierre Haessig pierre.haes...@crans.org wrote:
Le 16/02/2012 16:20, josef.p...@gmail.com a écrit :
I don't see any way to fix multivariate_normal for this case, except
for dropping svd or for random perturbing a covariance matrix with
multiplicity of singular
On Thu, Feb 16, 2012 at 11:20 AM, Warren Weckesser
warren.weckes...@enthought.com wrote:
On Thu, Feb 16, 2012 at 10:12 AM, Pierre Haessig pierre.haes...@crans.org
wrote:
Le 16/02/2012 16:20, josef.p...@gmail.com a écrit :
I don't see any way to fix multivariate_normal for this case, except
On Thu, Feb 16, 2012 at 11:30 AM, josef.p...@gmail.com wrote:
On Thu, Feb 16, 2012 at 11:20 AM, Warren Weckesser
warren.weckes...@enthought.com wrote:
On Thu, Feb 16, 2012 at 10:12 AM, Pierre Haessig pierre.haes...@crans.org
wrote:
Le 16/02/2012 16:20, josef.p...@gmail.com a écrit :
I
On Thu, Feb 16, 2012 at 2:08 PM, Pauli Virtanen p...@iki.fi wrote:
16.02.2012 14:54, josef.p...@gmail.com kirjoitti:
[clip]
If I interpret you correctly, this should be a svd ticket, or an svd
ticket as duplicate ?
I think it should be a multivariate normal ticket.
Fixing SVD is in my
On Thu, Feb 16, 2012 at 11:47 AM, josef.p...@gmail.com wrote:
On Thu, Feb 16, 2012 at 11:30 AM, josef.p...@gmail.com wrote:
On Thu, Feb 16, 2012 at 11:20 AM, Warren Weckesser
warren.weckes...@enthought.com wrote:
On Thu, Feb 16, 2012 at 10:12 AM, Pierre Haessig pierre.haes...@crans.org
On Thu, Feb 16, 2012 at 17:07, josef.p...@gmail.com wrote:
cholesky is also deterministic in my runs
We will need to check a variety of builds with different LAPACK
libraries and also different matrix sizes to be sure. Alas!
--
Robert Kern
I have come to believe that the whole world is an
On Thu, Feb 16, 2012 at 10:07 AM, josef.p...@gmail.com wrote:
On Thu, Feb 16, 2012 at 11:47 AM, josef.p...@gmail.com wrote:
On Thu, Feb 16, 2012 at 11:30 AM, josef.p...@gmail.com wrote:
On Thu, Feb 16, 2012 at 11:20 AM, Warren Weckesser
warren.weckes...@enthought.com wrote:
On Thu,
Hi,
16.02.2012 18:00, Nathaniel Smith kirjoitti:
[clip]
I agree, but the behavior is still surprising -- people reasonably
expect something like svd to be deterministic. So there's probably a
doc bug for alerting people that their reasonable expectation is, in
fact, wrong :-).
The problem
On Thu, Feb 16, 2012 at 10:20 AM, Pauli Virtanen p...@iki.fi wrote:
Hi,
16.02.2012 18:00, Nathaniel Smith kirjoitti:
[clip]
I agree, but the behavior is still surprising -- people reasonably
expect something like svd to be deterministic. So there's probably a
doc bug for alerting people
On Thu, Feb 16, 2012 at 05:00:29PM +, Nathaniel Smith wrote:
I agree, but the behavior is still surprising -- people reasonably
expect something like svd to be deterministic.
People are wrong then. Trust me, I work enough with ill-conditionned
problems, including SVDs, to know that the
On Thu, Feb 16, 2012 at 5:20 PM, Pauli Virtanen p...@iki.fi wrote:
Hi,
16.02.2012 18:00, Nathaniel Smith kirjoitti:
[clip]
I agree, but the behavior is still surprising -- people reasonably
expect something like svd to be deterministic. So there's probably a
doc bug for alerting people that
Doing a bit of browsing in the numpy tracker, I found this. From my
search this was not discussed on the mailing list.
http://projects.scipy.org/numpy/ticket/1842
The multivariate normal random sample is not always the same, even
though a seed is specified.
It seems to alternate randomly
On Wed, Feb 15, 2012 at 10:52 PM, josef.p...@gmail.com wrote:
Doing a bit of browsing in the numpy tracker, I found this. From my
search this was not discussed on the mailing list.
http://projects.scipy.org/numpy/ticket/1842
The multivariate normal random sample is not always the same, even
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