On 22 Jun 2014, at 22:52, Eelco Hoogendoorn wrote:
> That's pretty cool; and it makes sense that way. Still, couldn't you fold
> this kind of computation into a shader?
>
> Have you looked at vispy btw? I think its a really nice initiative; having a
> high quality vector graphics module in th
That's pretty cool; and it makes sense that way. Still, couldn't you fold
this kind of computation into a shader?
Have you looked at vispy btw? I think its a really nice initiative; having
a high quality vector graphics module in there would make it even better.
Would be nice if those projects cou
Actually, it's already working pretty well but it slows down when you're doing
a lot of zoom in/out.
The trick is that rendering is done using shader (OpenGL) and this computation
is used to give information to the shader to where to draw antialiased lines.
In the end, this shader is able to d
Protip: if you are writing your own rasterization code in python, be
prepared to forget about performance altogether.
Something like numba or other c-like extension will be necessary unless you
are willing to leave big gobs of performance on the table; and even with
pure C you will get nowhere clo
Thanks, I'll try your solution.
Data (L) is not so big actually, it represents pixels on screen and (I)
represents line position (for grids). I need to compute this quantity everytime
the user zoom in or out.
Nicolas
On 22 Jun 2014, at 19:05, Eelco Hoogendoorn wrote:
> Well, if the spacin
Also, if you use scipy.spatial.KDTree, make sure to use cKDTree; the native
python kdtree is sure to be slow as hell.
On Sun, Jun 22, 2014 at 7:05 PM, Eelco Hoogendoorn <
hoogendoorn.ee...@gmail.com> wrote:
> Well, if the spacing is truly uniform, then of course you don't really
> need the searc
Well, if the spacing is truly uniform, then of course you don't really need
the search, and you can do away with the extra log-n, and there is a purely
linear solution:
def find_closest_direct(start, end, count, A):
Q = (A-start)/(end-start)*count
mid = ((Q[1:]+Q[:-1]+1)/2).astype(np.int)
I would echo KDTree, but one way I think you can simplify the existing code
you have is to shift the values of L by half the spacing, then you
shouldn't need the check for left and right values.
Cheers!
Ben Root
On Sun, Jun 22, 2014 at 4:22 AM, Nicolas P. Rougier <
nicolas.roug...@inria.fr> wrot
On So, 2014-06-22 at 17:16 +0200, Nicolas P. Rougier wrote:
> Thanks for the answer.
> I was secretly hoping for some kind of hardly-known numpy function that would
> make things faster auto-magically...
>
I doubt it is faster, but if you got scipy anyway, using KDTree may be
pretty idiomatic.
Thanks for the answer.
I was secretly hoping for some kind of hardly-known numpy function that would
make things faster auto-magically...
Nicolas
On 22 Jun 2014, at 10:30, Eelco Hoogendoorn wrote:
> Perhaps you could simplify some statements, but at least the algorithmic
> complexity is f
Perhaps you could simplify some statements, but at least the algorithmic
complexity is fine, and everything is vectorized, so I doubt you will get
huge gains.
You could take a look at the functions in scipy.spatial, and see how they
perform for your problem parameters.
On Sun, Jun 22, 2014 at 10
Hi,
I have an array L with regular spaced values between 0 and width.
I have a (sorted) array I with irregular spaced values between 0 and width.
I would like to find the closest value in I for any value in L.
Currently, I'm using the following script but I wonder if I missed an obvious
(and
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