Francesc Alted wrote:
Just a C pointer to a malloc'ed area (it cannot be an ndarray, as the
data area might be compressed).
got it.
Ok. Thanks. The code is really simple, and that's great. However,
carray is quite more sophisticated, as it supports not only enlarging
arrays, but also
A Thursday 10 March 2011 22:25:27 Christopher Barker escrigué:
On 3/10/11 12:01 PM, Francesc Alted wrote:
3) when the extra space is used up, it re-allocates the entire
array, with some more extra room
again, carray works exactly the same: the extra room is just a new
chunk
does it
On 3/7/11 5:51 PM, Sturla Molden wrote:
Den 07.03.2011 18:28, skrev Christopher Barker:
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5, 6
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13, 14, 15
...
A ragged array, as implemented in C++, Java or C# is just an array of
arrays (or 'a pointer to an array of pointers').
Sure, but as a rule I don't
A Thursday 10 March 2011 18:05:11 Christopher Barker escrigué:
NOTE: this looks like it could use a growable numpy array, much
like one I've written before -- maybe it's time to revive that
project and use it here, fixing some performance issues while I'm at
it.
A growable array would be
On 3/10/11 9:51 AM, Francesc Alted wrote:
A Thursday 10 March 2011 18:05:11 Christopher Barker escrigué:
NOTE: this looks like it could use a growable numpy array, much
like one I've written before -- maybe it's time to revive that
project and use it here, fixing some performance issues while
On 3/10/11 11:29 AM, Christopher Barker wrote:
By the way, it would be great to have a growable array that could be
efficiently used in Cython code -- so you could accumulate a bunch of
native C datatype data easily.
I just noticed that carray is written in Cython, so that part should be
A Thursday 10 March 2011 20:29:00 Christopher Barker escrigué:
I don't think so -- my approach is a lot simpler that I think carray
is:
it acts much like a python list:
1) it pre-allocates extra space when an array is created.
same for carray
2) when you append, it uses that extra space
Hi folks,
I'm setting out to write some code to access and work with ragged arrays
stored in netcdf files. It dawned on me that ragged arrays are not all
that uncommon, so I'm wondering if any of you have any code you've
developed that I could learn-from borrow from, etc.
note that when I say
A Monday 07 March 2011 18:28:11 Christopher Barker escrigué:
Hi folks,
I'm setting out to write some code to access and work with ragged
arrays stored in netcdf files. It dawned on me that ragged arrays
are not all that uncommon, so I'm wondering if any of you have any
code you've developed
On 3/7/11 10:28 AM, Christopher Barker wrote:
Hi folks,
I'm setting out to write some code to access and work with ragged arrays
stored in netcdf files. It dawned on me that ragged arrays are not all
that uncommon, so I'm wondering if any of you have any code you've
developed that I could
@Jeff
I need to work with ragged arrays too. Are object arrays of 1d numpy arrays
slower than lists of 1d numpy arrays?
@ Christopher
I'd be interested in hearing if you come up with any better solutions.
On Mon, Mar 7, 2011 at 9:37 AM, Jeff Whitaker jsw...@fastmail.fm wrote:
On 3/7/11 10:28
On 3/7/11 9:33 AM, Francesc Alted wrote:
A Monday 07 March 2011 18:28:11 Christopher Barker escrigué:
I'm setting out to write some code to access and work with ragged
arrays stored in netcdf files. It dawned on me that ragged arrays
are not all that uncommon, so I'm wondering if any of you
On 3/7/11 11:42 AM, Christopher Barker wrote:
On 3/7/11 9:33 AM, Francesc Alted wrote:
A Monday 07 March 2011 18:28:11 Christopher Barker escrigué:
I'm setting out to write some code to access and work with ragged
arrays stored in netcdf files. It dawned on me that ragged arrays
are not all
A Monday 07 March 2011 19:42:00 Christopher Barker escrigué:
But now that you've entered the conversation, does HDF and/or
pytables have a standard way of dealing with this?
Well, I don't think there is such a 'standard' way for dealing with
ragged arrays, but yes, pytables has support for
On 3/7/11 11:18 AM, Francesc Alted wrote:
Well, I don't think there is such a 'standard' way for dealing with
ragged arrays, but yes, pytables has support for them. Creating them is
easy:
# Create a VLArray:
fileh = tables.openFile('vlarray1.h5', mode='w')
vlarray =
On 7 March 2011 15:29, Christopher Barker chris.bar...@noaa.gov wrote:
On 3/7/11 11:18 AM, Francesc Alted wrote:
but, instead of returning a numpy array of 'object' elements, plain
python lists are returned instead.
which gives you the append option -- I can see how that would be
usefull.
Den 07.03.2011 18:28, skrev Christopher Barker:
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5, 6
7, 8, 9, 10, 11, 12
13, 14, 15
...
In my case, these will only be 2-d, though I suppose one could have a
n-d version where the last dimension was ragged (or any dimension, I
suppose, though I'm having trouble wrapping my
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