On Fri, Jun 18, 2010 at 08:45:14PM +0900, Darren Cook wrote:
> >> distance=C.(dx+dy+max(dx,dy))
> > I'm calling this "the gridcular metric", ...
> > ...
> > Most programs relying on gamma-pattern combinations are probably using
> > this; at least Pachi is for sure, CrazyStone and others apparently too.
>
> Why is it good in those algorithms?
>
> Simple manhatten distance:
>
> X 1 2 3 4
> 1 2 3 4
> 2 3 4
> 3 4
> 4
>
> Adding in the max(dx,dy):
>
> X 2 4 6 8
> 2 3 5 7
> 4 5 6
> 6 7
> 8
>
> I.e. it makes the diagonal directions more important, compared to moves
> in a straight line.
I try to make that apparent in the presentation, and maybe also in the
name I use - it creates circle-like structures on the square grid. In
other words, increments in gridcular metric approximate increments in
the classical Euclidean metric. At the same time, the increments provide
quite fine granularity in the area covered, which is also useful in the
usual application - matching of variable-sized patterns.
--
Petr "Pasky" Baudis
The true meaning of life is to plant a tree under whose shade
you will never sit.
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