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
denis bzowy denis-bz-py at 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,
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 return the
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
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
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
any function which
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
___
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
George Dahl wrote:
Sturla Molden sturla at 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
2009/9/8 Charles سمير Doutriaux doutria...@llnl.gov:
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
Hi David,
On Tue, Sep 8, 2009 at 3:56 PM, David Warde-Farleyd...@cs.toronto.edu 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
Sturla Molden sturla at 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 paralellizable
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
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 great
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?
On Tue, Sep 8, 2009 at 5:57 PM, Christian Heimes li...@cheimes.de 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
Hi David,
On Tue, Sep 8, 2009 at 8:08 PM, David Cournapeaucourn...@gmail.com wrote:
On Wed, Sep 9, 2009 at 4:21 AM, Darren Daledsdal...@gmail.com 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
On Wed, Sep 9, 2009 at 9:30 AM, Daniel
Platzmail.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 for this
On Wed, Sep 9, 2009 at 9:37 AM, Darren Daledsdal...@gmail.com 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
On Tue, Sep 8, 2009 at 5:08 PM, David Cournapeau courn...@gmail.com 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
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 Wed, Sep 9, 2009 at 4:21 AM, Darren Daledsdal...@gmail.com 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
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 for
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
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
On Wed, Sep 9, 2009 at 2:10 PM, Sebastian Haaseseb.ha...@gmail.com 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
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