On Fri, Feb 15, 2008 at 7:12 AM, Stefan van der Walt <[EMAIL PROTECTED]> wrote: > As far as I know, the reference count to the array is increased when > you create a view, but the views themselves are not tracked anywhere. > You can therefore say whether there are references around, but you > cannot identify the Python objects.
I would like to occasionally dynamically grow an array (i.e. add length to existing dimensions) as I do not know th ultimately required length beforehand, but I have a good guess so I won't be need to reallocate that often if at all. The only way I know how to do this is numpy is to create a new larger array with the new dimensions and copy the existing data from the smaller array into it. Perhaps there is a better way that doesn't invalidate views on the array? I want to make sure that there are no outstanding references to the old array (i.e. views on it, etc.) so that I can raise a helpful exception while developing. Robin and Davide- Thanks for the pointer to the numpy.who method, while that only searches in a specified dictionary, it was the method that I thought I had encountered before. _______________________________________________ Numpy-discussion mailing list [email protected] http://projects.scipy.org/mailman/listinfo/numpy-discussion
