I'm generating rather large matrices with a fixed random seed using
rs = N.random.RandomState(123456789)
U = rs.uniform(low=-0.1 high=self.0.1 size=(480189, 1000)).astype('float32')
...
Several other arrays are instantiated as well.
Because they are so large, I do all calculations on single-precis
There is a (small) chance that sympy can help. Never the less you can use
scipy.optimize to obtain a numerical solution, once you specify the right merit
function.
Nadav
-הודעה מקורית-
מאת: numpy-discussion-boun...@scipy.org בשם olfa mraihi
נשלח: ד 24-דצמבר-08 12:55
אל: numpy-discuss
On Tue, Dec 23, 2008 at 02:10:50AM +0100, Olivier Grisel wrote:
>Interesting topic indeed. I think I have been hit with similar problems on
>toy experimental scripts. So far the solution was always adhoc FS caches
>of numpy arrays with manual filename management. Maybe the first step fo
olfa mraihi wrote:
Hello Numpy community,
I want to know if Numpy could deal with symbolic arrays and lists (by
symbolic I mean without specifying the concrete contents of list or
array)
For example I want to solve a system of equations containing lists and
arrays like this
solve(x+Sum[A[k],k=i..
Hello Numpy community,
I want to know if Numpy could deal with symbolic arrays and lists (by
symbolic I mean without specifying the concrete contents of list or
array)
For example I want to solve a system of equations containing lists and
arrays like this
solve(x+Sum[A[k],k=i..N]==y+Sum[B[k],k=m..N
