Hi,
there is a way of doing this. As far as I know, you have to create
your own "version of numpy arrays". E. g. try this:
class myNumpy(numpy.ndarray):
pass
Then creating an instance as in
a = myNumpy(otherNumpyArray)
would make `a` behave just like any other array, except that you CAN
attach attributes to it.
Be carefull that some (many / most ?) operations on that array will
return you a normal numpy array again.
I don't understand the reasons behind all of this.
HTH,
Sebastian Haase
On 9/29/07, jelle
Hi,
I'm wondering whether i can re-write the following idiom with numpy arrays:
for i in some_list: i.some_attr = some_value
it would be wonderful if one was able to write this idiom as
arr[just_these].some_attr = some_value or setattr(arr[just_these], 'some_attr', some_value)
since often expensive loops through lists of object could be avoided.
any thoughts on this are much appreciated,
thanks,
-jelle
_______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion