--- On Mon, 6/8/09, Anne Archibald <[email protected]> wrote:
> > You can't, really. What you can do is just keep
> iterating with the
> > whole data set and ignore the parts that have already
> converged. Here
> > is an example:
>
> Well, yes and no. This is only worth doing if the number of
> problem
> points that require many iterations is small - not the case
> here
> without some sort of periodicity detection - but you can
> keep an array
> of not-yet-converged points, which you iterate. When some
> converge,
> you store them in a results array (with fancy indexing) and
> remove
> them from your still-converging array.
Thanks, Anne. This is the way I had anticipated implementing it myself
eventually, but the "fancy-indexing" requirement has caused me to keep
postponing it, waiting for some time when I'll have a hefty block of time to
figure it out and then, inevitably, debug it. :( Also, the transfer of points
from un-converged to converged - when that's a large number, might that not be
a large time-suck compared to Rob's method? (Too bad this wasn't posted a
couple weeks ago: I'd've had time then to implement your method and "race" it
against Rob's, but alas, now I have this doc editing job...but that's a good
thing, as my fractals are not yet making me any real money.) :-)
> It's also worth remembering that the overhead of for loops
> is large
> but not enormous, so you can often remove only the inner
> for loop, in
> this case perhaps iterating over the image a line at a
> time.
Yes, definitely well worth remembering - thanks for reminding us!
Thanks again,
DG
>
> Anne
>
_______________________________________________
Numpy-discussion mailing list
[email protected]
http://mail.scipy.org/mailman/listinfo/numpy-discussion
