I have had some resembling challenges in my work, and here appending the
nympy arrays to HDF5 files using PyTables has been the solution for me -
that used in combination with lzo compression/decompression has lead to very
high read/write performance in my application with low memory consumption.
Y
On 10-Aug-09, at 11:29 PM, Juan Fiol wrote:
> Hi, I am creating numpy arrays in chunks and I want to save the
> chunks while my program creates them. I tried to use numpy.save but
> it failed (because it is not intended to append data). I'd like to
> know what is, in your opinion, the best
Hi, I am creating numpy arrays in chunks and I want to save the chunks while my
program creates them. I tried to use numpy.save but it failed (because it is
not intended to append data). I'd like to know what is, in your opinion, the
best way to go. I will put a few thousands every time but buil
josef.p...@gmail.com wrote:
> On Mon, Aug 10, 2009 at 8:52 PM, Brennan
> Williams wrote:
>
>> Hi
>>
>> No doubt asked many times before so apologies
>>
>> I'm pulling a subset array out of a data array where I have a list of
>> the indices I want (could be an array rather than a list actuall
Brennan Williams wrote:
> Hi
>
> No doubt asked many times before so apologies
>
> I'm pulling a subset array out of a data array where I have a list of
> the indices I want (could be an array rather than a list actually - I
> have it in both).
>
> Potentially the number of points and the num
On Mon, Aug 10, 2009 at 8:52 PM, Brennan
Williams wrote:
> Hi
>
> No doubt asked many times before so apologies
>
> I'm pulling a subset array out of a data array where I have a list of
> the indices I want (could be an array rather than a list actually - I
> have it in both).
>
> Potentially t
Hi
No doubt asked many times before so apologies
I'm pulling a subset array out of a data array where I have a list of
the indices I want (could be an array rather than a list actually - I
have it in both).
Potentially the number of points and the number of times I do this can
get very la
A correction for the typo below.
Thanks,
Masha
liu...@usc.edu
On Aug 10, 2009, at 12:19 PM, Maria Liukis wrote:
Hello everybody,
I'm using following versions of Scipy and Numpy packages:
>>> scipy.__version__
'0.7.1'
>>> np.__version__
'1.3.0'
My code uses boolean arra
Hello everybody,
I'm using following versions of Scipy and Numpy packages:
>>> scipy.__version__
'0.7.1'
>>> np.__version__
'1.3.0'
My code uses boolean array to filter 2-dimensional array which
sometimes happens to be an empty array. It seems like I have to take
special care when dimension
Hi all,
A user on the pymc user list has reported a problem with f2py wrapped
fortran functions compiled with gfortran 4.3, which is the standard Ubuntu
Jaunty fortran compiler. I noticed the same bug in some of my own routines.
The problem, as far as I can understand, is that vectorize tries to f
On Mon, Aug 10, 2009 at 9:10 AM, wrote:
> On Mon, Aug 10, 2009 at 11:55 AM, Keith Goodman wrote:
>> On Thu, Aug 6, 2009 at 9:07 AM, Robert Kern wrote:
>>> On Thu, Aug 6, 2009 at 11:03, Keith Goodman wrote:
On Thu, Aug 6, 2009 at 8:55 AM, wrote:
> What's the best way of getting back the c
On Mon, Aug 10, 2009 at 11:55 AM, Keith Goodman wrote:
> On Thu, Aug 6, 2009 at 9:07 AM, Robert Kern wrote:
>> On Thu, Aug 6, 2009 at 11:03, Keith Goodman wrote:
>>> On Thu, Aug 6, 2009 at 8:55 AM, wrote:
What's the best way of getting back the correct shape to be able to
broadcast, mean
On Thu, Aug 6, 2009 at 9:07 AM, Robert Kern wrote:
> On Thu, Aug 6, 2009 at 11:03, Keith Goodman wrote:
>> On Thu, Aug 6, 2009 at 8:55 AM, wrote:
>>> What's the best way of getting back the correct shape to be able to
>>> broadcast, mean, min,.. to the original array, that works for
>>> arbitrary
when you use slice notation, [0:4] returns everything up-to but not
including index 4. That is a[4] is actually the 5th element of the
array (which doesn't exist) because arrays are zero-based in python.
http://docs.scipy.org/doc/numpy-1.3.x/user/basics.indexing.html
On Mon, Aug 10, 2009 at 11:0
Dear all,
I am having a few issues with indexing in numpy and wondered if you could help
me out.
If I define an array
a = zeros(( 4))
a
array([ 0., 0., 0., 0.])
Then I try and reference a point beyond the bounds of the array
a[4]
Traceback (most recent call last):
File "", line 1, in
IndexE
Sure.
On Aug 9, 2009, at 12:50 PM, Egor Zindy wrote:
> Bill,
>
> thank you for your comment. Would this do instead? (replacing the
> return NULL with SWIG_fail):
>
> %exception
> {
>errno = 0;
>$action
>
>if (errno != 0)
>{
>switch(errno)
>{
>case EPERM
Sorry if I posted this twice.
I wonder if anyone can suggest me how to fix this error which I find
during numpy build:
.
creating build/temp.linux-i686-2.6/numpy/linalg
compile options: '-DNO_ATLAS_INFO=1 -Inumpy/core/include
-Ibuild/src.linux-i686-2.6/numpy/core/include/numpy -Inumpy/cor
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