On Nov 12, 2007 10:26 PM, David Cournapeau <[EMAIL PROTECTED]> wrote:
> Geoffrey Zhu wrote:
> > On Nov 12, 2007 12:37 PM, Keith Goodman <[EMAIL PROTECTED]> wrote:
> >> On Nov 12, 2007 10:10 AM, Peter Creasey <[EMAIL PROTECTED]> wrote:
> >>> The following code calling numpy v1.0.4 fails to terminate
Hey,
I just noticed that dumb_shelve.py and dumbdbm_patched.py were in both
scipy.io and scipy.weave. Since I assume that this was just an
oversight, I went ahead and cleaned it up. First, I made sure that
the newest code was in scipy.io:
http://projects.scipy.org/scipy/scipy/changeset/3521
Travis E. Oliphant wrote:
> David Cournapeau wrote:
>> Hi,
>>
>> I would appreciate to get some comment on whether there is any
>> chance to get my numpy.scons branch merge into the trunk at some near
>> future. I feel to have reached the point where the only big thing
>> missing is more tes
David Cournapeau wrote:
> Hi,
>
> I would appreciate to get some comment on whether there is any
> chance to get my numpy.scons branch merge into the trunk at some near
> future. I feel to have reached the point where the only big thing
> missing is more testing. I tried to test it on many p
I've just upgraded my OSX system to Leopard, and have successfully build
numpy from scratch. I am trying to build some code, which includes f2py
extensions, that build successfully on 10.4. I have the gfortran compiler
installed, and am building my code using:
python setup.py config_fc --fcompi
Geoffrey Zhu wrote:
> On Nov 12, 2007 12:37 PM, Keith Goodman <[EMAIL PROTECTED]> wrote:
>> On Nov 12, 2007 10:10 AM, Peter Creasey <[EMAIL PROTECTED]> wrote:
>>> The following code calling numpy v1.0.4 fails to terminate on my machine,
>>> which was not the case with v1.0.3.1
>>>
>>> from nump
Since PIL Images now have array interfaces, it has become a lot
simpler. The following should do the job:
from numpy import array
from PIL import Image
def imread(fname,flatten=False):
"""Return a copy of a PIL image as a numpy array.
*Parameters*:
im : PIL image
In
On Nov 12, 2007 12:37 PM, Keith Goodman <[EMAIL PROTECTED]> wrote:
>
> On Nov 12, 2007 10:10 AM, Peter Creasey <[EMAIL PROTECTED]> wrote:
> > The following code calling numpy v1.0.4 fails to terminate on my machine,
> > which was not the case with v1.0.3.1
> >
> > from numpy import arange, floa
It allows the check on egg dependencies IIRC
Matthieu
2007/11/12, Keith Goodman <[EMAIL PROTECTED]>:
>
> I noticed that
>
> python setup.py install --prefix=/usr/local
>
> installs a new file called numpy-1.0.5.dev4445.egg-info. It used to be
> that files were only installed in
> /usr/local/lib/p
I noticed that
python setup.py install --prefix=/usr/local
installs a new file called numpy-1.0.5.dev4445.egg-info. It used to be
that files were only installed in
/usr/local/lib/python2.4/site-packages/numpy.
What is the file used for?
$ cat /usr/local/lib/python2.4/site-packages/numpy-1.0.5.d
> > I think numpy.array(object) always makes a copy.
> >
> > You want numpy.asarray(object) which will make a view if object exposes
> > the array interface and matches the type and sizes requested.
FYI, numpy.asarray is a shortcut for numpy.array(copy=False), numpy.asanyarray
for numpy.array(cop
2007/11/12, Christopher Barker <[EMAIL PROTECTED]>:
>
> Matthieu Brucher wrote:
> > I have an object that exposes an array interface. I want to modify the
> > data it contains, but using numpy.array(myObject) seems to copy the data
> > and thus my object is not modified. Am I mistaken or did I make
Matthieu Brucher wrote:
> I have an object that exposes an array interface. I want to modify the
> data it contains, but using numpy.array(myObject) seems to copy the data
> and thus my object is not modified. Am I mistaken or did I make a
> mistake in my array interface ?
I think numpy.array(o
On Nov 13, 2007 3:37 AM, Keith Goodman <[EMAIL PROTECTED]> wrote:
>
> On Nov 12, 2007 10:10 AM, Peter Creasey <[EMAIL PROTECTED]> wrote:
> > The following code calling numpy v1.0.4 fails to terminate on my machine,
> > which was not the case with v1.0.3.1
> >
> > from numpy import arange, float
2007/11/12, Albert Strasheim <[EMAIL PROTECTED]>:
>
> Hello,
>
> Have you considered looking at the source for PyArray_CastToType in
> core/src/arrayobject.c?
>
> Cheers,
>
> Albert
Well no :( I didn't know where to look (and this should be fixed in the book
as well...)
Matthieu
--
French PhD s
Works fine on my computer (Mac OS X 10.4), Python
2.4. Runs in a second or so.
-- Lou Pecora
---Peter wrote:
Hi all,
The following code calling numpy v1.0.4 fails to
terminate on my machine, which was not the case with
v1.0.3.1
from numpy import arange, float64
from numpy.linalg impor
On Nov 12, 2007 10:10 AM, Peter Creasey <[EMAIL PROTECTED]> wrote:
> The following code calling numpy v1.0.4 fails to terminate on my machine,
> which was not the case with v1.0.3.1
>
> from numpy import arange, float64
> from numpy.linalg import eig
> a = arange(13*13, dtype = float64)
Hi all,
The following code calling numpy v1.0.4 fails to terminate on my machine,
which was not the case with v1.0.3.1
from numpy import arange, float64
from numpy.linalg import eig
a = arange(13*13, dtype = float64)
a.shape = (13,13)
a = a%17
eig(a)
Regards,
Peter
_
D.Hendriks (Dennis) wrote:
> Alan G Isaac wrote:
>> On Mon, 12 Nov 2007, "D.Hendriks (Dennis)" apparently wrote:
>>
>>> All of this makes me doubt the correctness of the formula
>>> you proposed.
>>>
>> It is always a good idea to hesitate before doubting Robert.
>> http://en.wikipedia.o
D.Hendriks (Dennis) wrote:
> Alan G Isaac wrote:
>> On Mon, 12 Nov 2007, "D.Hendriks (Dennis)" apparently wrote:
>>
>>> All of this makes me doubt the correctness of the formula
>>> you proposed.
>>>
>> It is always a good idea to hesitate before doubting Robert.
>> http://en.wikipedia.o
Hello,
Have you considered looking at the source for PyArray_CastToType in
core/src/arrayobject.c?
Cheers,
Albert
On Mon, 12 Nov 2007, Matthieu Brucher wrote:
> Nobody can answer this ?
>
> Matthieu
>
> 2007/11/4, Matthieu Brucher <[EMAIL PROTECTED]>:
> >
> > Hi,
> >
> > I'm trying to use P
Hi,
I have an object that exposes an array interface. I want to modify the data
it contains, but using numpy.array(myObject) seems to copy the data and thus
my object is not modified. Am I mistaken or did I make a mistake in my array
interface ?
Matthieu
--
French PhD student
Website : http://mi
Nobody can answer this ?
Matthieu
2007/11/4, Matthieu Brucher <[EMAIL PROTECTED]>:
>
> Hi,
>
> I'm trying to use PyArray_CastToType(), but according to the book, there
> are two arguments, a PyArrayObject* and a PyArrayDescr*, but according to
> the header file, there are three arguments, an addi
Alan G Isaac wrote:
On Mon, 12 Nov 2007, "D.Hendriks (Dennis)" apparently wrote:
All of this makes me doubt the correctness of the formula
you proposed.
It is always a good idea to hesitate before doubting Robert.
http://en.wikipedia.org/wiki/Weibull_distribution#Generating_Weibull-di
On Mon, 12 Nov 2007, "D.Hendriks (Dennis)" apparently wrote:
> All of this makes me doubt the correctness of the formula
> you proposed.
It is always a good idea to hesitate before doubting Robert.
http://en.wikipedia.org/wiki/Weibull_distribution#Generating_Weibull-distributed_random_variates
Hi,
I would appreciate to get some comment on whether there is any
chance to get my numpy.scons branch merge into the trunk at some near
future. I feel to have reached the point where the only big thing
missing is more testing. I tried to test it on many platforms, but there
is a limit to
Robert Kern wrote:
D.Hendriks (Dennis) wrote:
According to (for instance)
http://en.wikipedia.org/wiki/Weibull_distribution the Weibull
distribution has two parameters: lambda > 0 is the scale parameter
(real) and k > 0 is the shape parameter (real). However, the
numpy.random.weibull func
D.Hendriks (Dennis) wrote:
> According to (for instance)
> http://en.wikipedia.org/wiki/Weibull_distribution the Weibull
> distribution has two parameters: lambda > 0 is the scale parameter
> (real) and k > 0 is the shape parameter (real). However, the
> numpy.random.weibull function has only a
According to (for instance)
http://en.wikipedia.org/wiki/Weibull_distribution the Weibull
distribution has two parameters: lambda > 0 is the scale parameter
(real) and k > 0 is the shape parameter (real). However, the
numpy.random.weibull function has only a single 'a' parameter (except
for th
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