This is not the first time this issue is raised here.
You may try this piece of code, which may take less memory:
(A*x).sum(axis=1).T
Nadav
-הודעה מקורית-
מאת: numpy-discussion-boun...@scipy.org בשם Gideon Simpson
נשלח: א 18-ינואר-09 07:30
אל: Discussion of Numerical Python
נושא:
On Sat, Jan 17, 2009 at 11:44 PM, Robert Kern robert.k...@gmail.com wrote:
On Sat, Jan 17, 2009 at 22:35, Darren Dale dsdal...@gmail.com wrote:
On Sat, Jan 17, 2009 at 11:23 PM, Robert Kern robert.k...@gmail.com
wrote:
On Sat, Jan 17, 2009 at 22:06, Darren Dale dsdal...@gmail.com wrote:
I have implemented an iterative gaussian smoothing approach that is
working well for my purposes. My approach uses a median filter to
populate the initial values and then runs a few passes with gaussian
smoothing. This works very well for the missing values that I care
about within the
Francesc Alted wrote:
Numexpr is a fast numerical expression evaluator for NumPy. With
it, expressions that operate on arrays (like 3*a+4*b) are
accelerated and use less memory than doing the same calculation in
Python.
Please pardon my ignorance as I know this project has been
