On Wed, Sep 9, 2009 at 2:10 PM, Sebastian Haase wrote:
> Hi,
> you can probably use PyTables for this. Even though it's meant to
> save/load data to/from disk (in HDF5 format) as far as I understand,
> it can be used to make your task solvable - even on a 32bit system !!
> It's free (pytables.org)
Hi,
you can probably use PyTables for this. Even though it's meant to
save/load data to/from disk (in HDF5 format) as far as I understand,
it can be used to make your task solvable - even on a 32bit system !!
It's free (pytables.org) -- so maybe you can try it out and tell me if
I'm right
Or s
Daniel Platz skrev:
> data1 = numpy.zeros((256,200),dtype=int16)
> data2 = numpy.zeros((256,200),dtype=int16)
>
> This works for the first array data1. However, it returns with a
> memory error for array data2. I have read somewhere that there is a
> 2GB limit for numpy arrays on a 32 bit m
On Tue, Sep 8, 2009 at 7:30 PM, Daniel Platz <
mail.to.daniel.pl...@googlemail.com> wrote:
> Hi,
>
> I have a numpy newbie question. I want to store a huge amount of data
> in an array. This data come from a measurement setup and I want to
> write them to disk later since there is nearly no time
Ok I finally got it
I was going at it backward... Instead of checking for NPY_INT64 and
trying to figure out which letter it is different on each platform) I
needed to check for
NPY_LONGLONG /NPY_LONG/ NPY_INT, etc..
i.e I need to check for the numpy types that have an associated unique
On Tue, Sep 8, 2009 at 5:08 PM, David Cournapeau wrote:
> - it remains to be seen whether we can do the py3k support in the
> same source tree as the one use for python >= 2.4. Having two source
> trees would make the effort even much bigger, well over the current
> developers capacity IMHO.
I k
On Wed, Sep 9, 2009 at 9:37 AM, Darren Dale wrote:
> Hi David,
>> I already gave my own opinion on py3k, which can be summarized as:
>> - it is a huge effort, and no core numpy/scipy developer has
>> expressed the urge to transition to py3k, since py3k does not bring
>> much for scientific comput
On Wed, Sep 9, 2009 at 9:30 AM, Daniel
Platz wrote:
> Hi,
>
> I have a numpy newbie question. I want to store a huge amount of data
> in an array. This data come from a measurement setup and I want to
> write them to disk later since there is nearly no time for this during
> the measurement. To pu
Hi,
I have a numpy newbie question. I want to store a huge amount of data
in an array. This data come from a measurement setup and I want to
write them to disk later since there is nearly no time for this during
the measurement. To put some numbers up: I have 2*256*200 int16
numbers which I w
Hi David,
On Tue, Sep 8, 2009 at 8:08 PM, David Cournapeau wrote:
> On Wed, Sep 9, 2009 at 4:21 AM, Darren Dale wrote:
>> I'm not a core numpy developer and don't want to step on anybody's
>> toes here. But I was wondering if anyone had considered approaching
>> the Python Software Foundation abou
On Wed, Sep 9, 2009 at 4:21 AM, Darren Dale wrote:
> I'm not a core numpy developer and don't want to step on anybody's
> toes here. But I was wondering if anyone had considered approaching
> the Python Software Foundation about support to help get numpy working
> with python-3?
I already gave my
On Tue, Sep 8, 2009 at 5:57 PM, Christian Heimes wrote:
> Darren Dale wrote:
> > I'm not a core numpy developer and don't want to step on anybody's
> > toes here. But I was wondering if anyone had considered approaching
> > the Python Software Foundation about support to help get numpy working
>
Darren Dale wrote:
> I'm not a core numpy developer and don't want to step on anybody's
> toes here. But I was wondering if anyone had considered approaching
> the Python Software Foundation about support to help get numpy working
> with python-3?
What kind of support are you talking about? Develo
George Dahl wrote:
> Sturla Molden molden.no> writes:
>> Teraflops peak performance of modern GPUs is impressive. But NumPy
>> cannot easily benefit from that.
> I know that for my work, I can get around an order of a 50-fold speedup over
> numpy using a python wrapper for a simple GPU matrix c
Hi David,
On Tue, Sep 8, 2009 at 3:56 PM, David Warde-Farley wrote:
> Hey Darren,
>
> On 8-Sep-09, at 3:21 PM, Darren Dale wrote:
>
>> I'm not a core numpy developer and don't want to step on anybody's
>> toes here. But I was wondering if anyone had considered approaching
>> the Python Software Fo
Hi Robert,
Ok we have a section of code that used to be like that:
char t;
switch(type) {
case NPY_CHAR:
t = 'c';
break;
etc...
I now replaced with
char t;
switch(type) {
case NPY_CHAR:
t = NPY_CHARLTR;
break;
But I'm still stuck with numpy.uint64
NPY_UINT6
2009/9/8 Charles سمير Doutriaux :
> Hi,
>
> I'm testing our code on 64bit vs 32bit
>
> I just realized that the dtype.car is platform dependent.
>
> I guess it's normal
>
> her emy little test:
> for t in
> [numpy
> .byte
> ,numpy
> .short
> ,numpy
> .int
> ,numpy
> .int32
> ,numpy
> .float
> ,nump
Hi,
I'm testing our code on 64bit vs 32bit
I just realized that the dtype.car is platform dependent.
I guess it's normal
her emy little test:
for t in
[numpy
.byte
,numpy
.short
,numpy
.int
,numpy
.int32
,numpy
.float
,numpy
.float32
,numpy
.double,numpy.ubyte,numpy.ushort,numpy.
Hey Darren,
On 8-Sep-09, at 3:21 PM, Darren Dale wrote:
> I'm not a core numpy developer and don't want to step on anybody's
> toes here. But I was wondering if anyone had considered approaching
> the Python Software Foundation about support to help get numpy working
> with python-3?
It's a grea
Sturla Molden molden.no> writes:
>
> Erik Tollerud skrev:
> >> NumPy arrays on the GPU memory is an easy task. But then I would have to
> >> write the computation in OpenCL's dialect of C99?
> > This is true to some extent, but also probably difficult to do given
> > the fact that paralellizabl
I'm not a core numpy developer and don't want to step on anybody's
toes here. But I was wondering if anyone had considered approaching
the Python Software Foundation about support to help get numpy working
with python-3?
Thanks,
Darren
___
NumPy-Discussi
On 2009-09-08 10:38 , Christopher Barker wrote:
> Giuseppe Aprea wrote:
>> I have some files with data stored in columns:
>>
>> x1 y1 z1
>> x2 y2 z2
>> x3 y3 z3
>> x4 y4 z4
>> x5 y5 z5
>> I usually load data using 3 lists: x, y and z; I wonder if there is
>>
David Cournapeau wrote:
> I think it is best to avoid touching anything in /System.
Yes, it is.
> The better
> solution is to install things locally, at least if you don't need to
> share with several users one install.
And if you do, you can put it in:
/Library/Frameworks
(/Library is kind Ap
Skipper Seabold wrote:
> Hmm, okay, well I came across this in trying to create a recarray like
> data2 below, so I guess I should just combine the two questions.
key to understanding this is to understand what is going on under the
hood in numpy. Travis O. gave a nice intro in an Enthought webca
Giuseppe Aprea wrote:
> I have some files with data stored in columns:
>
> x1 y1 z1
> x2 y2 z2
> x3 y3 z3
> x4 y4 z4
> x5 y5 z5
> I usually load data using 3 lists: x, y and z; I wonder if there is
> any function which is able to take these 3 lists and retur
Hi list,
I have some files with data stored in columns:
x1 y1 z1
x2 y2 z2
x3 y3 z3
x4 y4 z4
x5 y5 z5
...
and I need to make a contour plot of this data using matplotlib. The
problem is that contour plot functions usually handle a different kind
of inpu
denis bzowy t-online.de> writes:
>
> Does anyone have a program to generate a file with one line per Numpy function
> / class / method, for local grepping ?
Sorry I wasn't clear: I want just all defs, one per long line, like this:
...
PyQt4.QtCore.QObject.findChildren(type type, QRegExp regExp)
27 matches
Mail list logo
