On 10/18/06, David Cournapeau <[EMAIL PROTECTED]> wrote:
Yes. Numpy generates a temporary where the _expression_ results are kept, the temporary is then assigned to foo. This can be inefficient, but knowing when you may overwrite data can be complicated. For instance:
foo = dot(foo,foo)
Can't be done in place because values needed later on in the dot evaluation would be overwritten.
Chuck
Sven Schreiber wrote:
>
> Yes it's intended; as far as I understand the python/numpy syntax, <+>
> is an operator, and that triggers assignment by copy (even if you do
> something trivial as bar = +foo, you get a copy, if I'm not mistaken),
>
So basically, whenever you have
foo = expr
with expr is a numpy _expression_ containing foo, you trigger a copy ?
Yes. Numpy generates a temporary where the _expression_ results are kept, the temporary is then assigned to foo. This can be inefficient, but knowing when you may overwrite data can be complicated. For instance:
foo = dot(foo,foo)
Can't be done in place because values needed later on in the dot evaluation would be overwritten.
Chuck
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