On 03/16/2011 08:56 AM, John Salvatier wrote:
Loop through to build a list of arrays, then use vstack on the list.
On Wed, Mar 16, 2011 at 1:36 AM, John <washa...@gmail.com
<mailto:washa...@gmail.com>> wrote:
Hello,
I have a dictionary with structured arrays, keyed by integers 0...n.
There are no other keys in the dictionary.
What is the most efficient way to convert the dictionary of arrays to
a single array?
All the arrays have the same 'headings' and width, but different
lengths.
Is there something I can do that would be more efficient than looping
through and using np.concatenate (vstack)?
--john
_______________________________________________
Numpy does not permit a 'single' array of different shapes - ie a
'ragged array'.
Sure you could convert this into a structured array (you know n so you
can create an appropriate empty structured array and assign the array by
looping across the dict) but that is still not a 'single' array. You can
use a masked array where you masked the missing elements across your arrays.
Francesc Alted pointed out in the 'ragged array implimentation' thread
(http://mail.scipy.org/pipermail/numpy-discussion/2011-March/055219.html) that
pytables does support this.
Bruce
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