[Numpy-discussion] when and where to use numpy arrays vs nested lists
Mark P. Miller
mpmusu@cc.usu....
Thu Mar 1 12:27:44 CST 2007
Travis: Can you clarify this for me. The book doesn't have much detail
here and seems to differ from your notation (which gives me errors).
>> Getting single indices like this is a bit slower for NumPy then for
>> lists because of all the possibilities that must be distinguished for
>> array indexing. List indexing is a very simple thing. Thus, lists can
>> be seen as collections that are optimized for simple indexing. If all
>> you are doing is simple indexing, then lists are going to be faster.
>>
>> You can try using array1.item(randint(10), randint(10)), like this:
>>
>> getitem = array1.item
>> def random1():
>> getitem(randint(50), randint(50))
>>
>
>
>>> array1=numpy.zeros((10,10),int)
>>> array1.item(0,0)
Traceback (most recent call last):
File "<pyshell#43>", line 1, in ?
array1.item(0,0)
TypeError: function takes exactly 0 arguments (2 given)
>>> getitem = array1.item
>>> getitem(0,0)
Traceback (most recent call last):
File "<pyshell#55>", line 1, in ?
getitem(0,0)
TypeError: function takes exactly 0 arguments (2 given)
I also assume that .itemset should do the converse? However, the syntax
escapes me.
python 2.4.3
numpy 0.9.9.2706
WinXP
Thanks,
-Mark
>
>
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