I thank you for the answer!!!
Bu this with "temp" is also in core-Python bihind the scene!;-)
Den 22-06-2016 kl. 21:39 skrev Nathaniel Smith:
To repeat and (hopefully) clarify/summarize the other answers:
It's been left out on purpose so far.
Why was it left out? A few reasons:
- Usually in-place operations like "a += b" are preferred over the
out-of-place equivalents like "a[...] = a + b" because they avoid some
copies and potentially large temporary arrays. But for @= this is
impossible -- you have to make a temporary copy of the whole matrix,
because otherwise you find yourself writing output elements on top of
input elements that you're still using. So it's probably better style
to write this as "a[...] = a @ b": this makes it more clear to the
reader that a potentially large temporary array is being allocated.
- The one place where this doesn't apply, and where "a @= b" really
could be a performance win, is when working with higher dimensional
stacks of matrices. In this case we still have to make a temporary
copy of each matrix, but only of one matrix at a time, not the whole
stack together.
- But, not that many people are using matrix stacks yet, and in any
case "a @= b" is limited to cases where both matrices are square. And
making it efficient in the stacked case may require some non-trivial
surgery on the internals. So there hasn't been much urgency to fix this.
My guess is that eventually it will be supported because the stacked
matrix use case is somewhat compelling, but it will take a bit until
someone (maybe you!) decides they care enough and have the time/energy
to fix it.
-n
On Jun 21, 2016 17:39, "Hans Larsen" <jo...@mail.dk
<mailto:jo...@mail.dk>> wrote:
I have Python 3-5-1 and NumPy 1-11! windows 64bits!
When will by side 'M=M@P' be supported with 'M@=P'???:-(
--
Hans Larsen Galgebakken Sønder 4-11A 2620 Albertslund Danmark/Danio
_______________________________________________
NumPy-Discussion mailing list
NumPy-Discussion@scipy.org <mailto:NumPy-Discussion@scipy.org>
https://mail.scipy.org/mailman/listinfo/numpy-discussion
_______________________________________________
NumPy-Discussion mailing list
NumPy-Discussion@scipy.org
https://mail.scipy.org/mailman/listinfo/numpy-discussion
--
Hans Larsen Galgebakken Sønder 4-11A 2620 Albertslund Danmark/Danio
_______________________________________________
NumPy-Discussion mailing list
NumPy-Discussion@scipy.org
https://mail.scipy.org/mailman/listinfo/numpy-discussion
