On Thu, Feb 16, 2012 at 5:20 PM, Pauli Virtanen 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 t
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 alg
On Thu, Feb 16, 2012 at 10:20 AM, Pauli Virtanen 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 t
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 10:07 AM, wrote:
> On Thu, Feb 16, 2012 at 11:47 AM, wrote:
> > On Thu, Feb 16, 2012 at 11:30 AM, wrote:
> >> On Thu, Feb 16, 2012 at 11:20 AM, Warren Weckesser
> >> wrote:
> >>>
> >>>
> >>> On Thu, Feb 16, 2012 at 10:12 AM, Pierre Haessig <
> pierre.haes...@crans.org
On Thu, Feb 16, 2012 at 17:07, 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 enigma, a harmless
e
On Thu, Feb 16, 2012 at 11:47 AM, wrote:
> On Thu, Feb 16, 2012 at 11:30 AM, wrote:
>> On Thu, Feb 16, 2012 at 11:20 AM, Warren Weckesser
>> wrote:
>>>
>>>
>>> On Thu, Feb 16, 2012 at 10:12 AM, Pierre Haessig
>>> wrote:
Le 16/02/2012 16:20, josef.p...@gmail.com a écrit :
>
On Thu, Feb 16, 2012 at 2:08 PM, Pauli Virtanen 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 op
On Thu, Feb 16, 2012 at 11:30 AM, wrote:
> On Thu, Feb 16, 2012 at 11:20 AM, Warren Weckesser
> wrote:
>>
>>
>> On Thu, Feb 16, 2012 at 10:12 AM, Pierre Haessig
>> 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
On Thu, Feb 16, 2012 at 11:20 AM, Warren Weckesser
wrote:
>
>
> On Thu, Feb 16, 2012 at 10:12 AM, Pierre Haessig
> 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 pertur
On Thu, Feb 16, 2012 at 16:12, Pierre Haessig 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 values.
>
> Hi,
> I
On Thu, Feb 16, 2012 at 10:12 AM, Pierre Haessig
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 values.
>>
> Hi,
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 values.
Hi,
I just made a quick search in what R guys are doing. It happens there
On Thu, Feb 16, 2012 at 9:08 AM, Pauli Virtanen 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 op
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 n
On Thu, Feb 16, 2012 at 8:45 AM, Pauli Virtanen 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 exce
On Thu, Feb 16, 2012 at 8:14 AM, wrote:
> On Thu, Feb 16, 2012 at 4:44 AM, Pauli Virtanen 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
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 rando
On Thu, Feb 16, 2012 at 4:44 AM, Pauli Virtanen 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 o
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 c
On Wed, Feb 15, 2012 at 10:52 PM, 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
> though a see
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 between
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