2010/12/1 greg whittier :
> On Wed, Nov 24, 2010 at 3:16 PM, Friedrich Romstedt
> wrote:
>> I assume you just need *some* interpolation, not that specific one?
>> In that case, I'd suggest the following:
>>
>> 1) Use a 2d interpolation, taking into account all nearest neighbours.
>> 2) For this,
On Wed, Nov 24, 2010 at 3:16 PM, Friedrich Romstedt <
friedrichromst...@gmail.com> wrote:
> 2010/11/16 greg whittier :
> > I'd like to be able to speed up the following code.
> >
> > def replace_dead(cube, dead):
> > # cube.shape == (320, 640, 1200)
> > # dead.shape == (320, 640)
> > # cube[
2010/11/16 greg whittier :
> I'd like to be able to speed up the following code.
>
> def replace_dead(cube, dead):
> # cube.shape == (320, 640, 1200)
> # dead.shape == (320, 640)
> # cube[i,j,:] are bad points to be replaced via interpolation if
> dead[i,j] == True
>
> bands = np.arange(0,
Hi all,
I'd like to be able to speed up the following code.
def replace_dead(cube, dead):
# cube.shape == (320, 640, 1200)
# dead.shape == (320, 640)
# cube[i,j,:] are bad points to be replaced via interpolation if
dead[i,j] == True
bands = np.arange(0, cube.shape[0])
for line i
