Thanks for spotting the origin, I'll pass this along to our user maybe
they'll be able to figure out how to build python w/o openssl
C.
Robert Kern wrote:
> On Wed, Sep 3, 2008 at 10:39, Charles Doutriaux <[EMAIL PROTECTED]> wrote:
>
>> Hi Robert,
>>
>> The first email got intercepted because
On Sat, Aug 30, 2008 at 22:10, Zachary Pincus <[EMAIL PROTECTED]> wrote:
> Hi Alan,
>
>> Traceback (most recent call last):
>> File "/usr/local/lib/python2.5/site-packages/enthought.traits-2.0.4-
>> py2.5-linux-i686.egg/enthought/traits/trait_notifiers.py", line 325,
>> in call_1
>>self.handle
On Wed, Sep 3, 2008 at 10:39, Charles Doutriaux <[EMAIL PROTECTED]> wrote:
> Hi Robert,
>
> The first email got intercepted because the attachment was too big (awaits
> moderator), so i compressed the log and I resend this email.
>
> I'm attaching my Python build log, can you spot anything? It "see
On Wed, Sep 3, 2008 at 10:06 AM, Alan G Isaac <[EMAIL PROTECTED]> wrote:
> So the two formatting tests fail, as David warned.
> But they are known to fail on Windows, and there
> is no msg to that effect. Might one be added?
Absolutely, we will make sure to add a message to that effect and
possib
So the two formatting tests fail, as David warned.
But they are known to fail on Windows, and there
is no msg to that effect. Might one be added?
Alan Isaac
Python 2.5.1 (r251:54863, Apr 18 2007, 08:51:08) [MSC v.1310 32 bit
(Intel)] on
win32
Type "help", "copyright", "credits" or "license" for
Hi Robert,
The first email got intercepted because the attachment was too big
(awaits moderator), so i compressed the log and I resend this email.
I'm attaching my Python build log, can you spot anything? It "seems"
like md5 is built, i get a very similar log on my machine and i have a
worki
David Cournapeau wrote:
> FWIW, distance is deemed to move to a separate package, because distance
> computation is useful in other contexts than clustering.
>
>
Excellent. I was thinking about something similar. I'll have a look
to the separate package. Please drop an email to this list when
d
Emanuele Olivetti wrote:
>
> Thanks for the pointer but the distance subpackage in cluster is about
> the distance matrix of vectors in one set of vectors. So the resulting
> matrix is symmetric. I need to compute distances between two
> different sets of vectors (i.e. a non-symmetric distance matr
David Cournapeau wrote:
> Emanuele Olivetti wrote:
>> Hi,
>>
>> I'm trying to compute the distance matrix (weighted p-norm [*])
>> between two sets of vectors (data1 and data2). Example:
>>
>
> You may want to look at scipy.cluster.distance, which has a bunch of
> distance matrix implementation.
We used to care about memory when we were running on 32-bit platforms, but
with the move to 64-bit, enabled by the current work, the issue is removed
and I will probably be changing everything for more accuracy.
Thanks
Hanni
2008/9/3 David Cournapeau <[EMAIL PROTECTED]>
> Hanni Ali wrote:
> >
Oh ok, I shall have to find where I did that then. Thanks
2008/9/3 Matthieu Brucher <[EMAIL PROTECTED]>
> By default, numpy uses float64, but you told it to use float32 ;)
>
> Matthieu
>
> 2008/9/3, Hanni Ali <[EMAIL PROTECTED]>:
> > Also can you think of a way either dtype is always float64? I h
Hanni Ali wrote:
> Understood, but I would generally be more concerned with accuracy than
> memory?
It is a tradeof: you can choose accuracy if you want, but by using
float32, you are already kind of hinting that you care about memory and
speed (otherwise, why not using double, which is the defaul
By default, numpy uses float64, but you told it to use float32 ;)
Matthieu
2008/9/3, Hanni Ali <[EMAIL PROTECTED]>:
> Also can you think of a way either dtype is always float64? I have a lot of
> functions and to add dtype='float64' would require *loads* of testing,
> whereas if I can set it cent
Hanni Ali wrote:
> I'm afraid the matrix is not available anywhere and I would not be
> able to make it available.
>
Forget it, Sebastian is right. I was confused by the range of the error,
but the error between two floating point numbers is indeed 1e-7 for
float on most runtimes (FLT_EPS in C, wh
Understood, but I would generally be more concerned with accuracy than
memory?
2008/9/3 Matthieu Brucher <[EMAIL PROTECTED]>
> It should never do some black magic without telling you.
> People are concerned by memory consumption, so if you use more memory
> than what you think, you can encounter
Also can you think of a way either dtype is always float64? I have a lot of
functions and to add dtype='float64' would require *loads* of testing,
whereas if I can set it centrally on the matrix or in the environment that
would be so much easier.
Hanni
2008/9/3 Hanni Ali <[EMAIL PROTECTED]>
> S
It should never do some black magic without telling you.
People are concerned by memory consumption, so if you use more memory
than what you think, you can encounter bugs. Least surprise is always
better ;)
Matthieu
2008/9/3, Hanni Ali <[EMAIL PROTECTED]>:
> Sebastian you legend, that seems to be
Sebastian you legend, that seems to be it.
Thank you very much.
>>> matrix.mean(dtype='float64')
0.41582015156745911
What seems odd is that numpy doesn't do this on it's own...
2008/9/3 Sebastian Stephan Berg <[EMAIL PROTECTED]>
> Hi,
>
> just guessing here. But numarray seems to calculate t
I'm afraid the matrix is not available anywhere and I would not be able to
make it available.
However I can demonstrate by simply generating a random number and filling a
10x10 matrix with it.
I generated a random number in numpy and used that to do the same exercise
in numarray.
In numpy:
>>>
Hi,
just guessing here. But numarray seems to calculate the result in a
bigger dataype, while numpy uses float32 which is the input arrays size
(at least I thought so, trying it confused me right now ...). In any
case, maybe the difference will be gone if you
use .mean(dtype='float64') (or whateve
Hanni Ali wrote:
> Hi Matthieu,
>
> I thought as much, regarding the computations, but was just presenting
> the information.
Is your matrix available somewhere so that we can reproduce the problem
? Off-hand, I can't see any explanation, but I am not familiar with
numarray, so maybe I am missing
Hi Matthieu,
I thought as much, regarding the computations, but was just presenting the
information.
Thanks for the set_printoptions but it doesn't seem to apply when accessing
a specific item:
>>> numpy.set_printoptions(precision=12)
>>> port_result.agg_matrix[0]
array([ 2.11549568e+08,
Hi,
I can't help you with the first issues, but the display has nothing to
do with the quality of the computation. Numpy only prints a part of a
float value, but fir the computations, it obviously uses the correct
value. All this can be parametrized by using set_printoptions().
Matthieu
2008/9/3
Hi,
I have encountered a worrying problem, during migration of software from
numarray to numpy, perhaps someone could help me determine how this could be
addressed.
I have a large array or values 1 long 12 items per line. The matrix
contains floats, dtype=float32 in numpy and type=Float32 in
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