Voronoi diagram: Difference between revisions

=={{header|Prolog}}==

Works with SWI-Prolog and XPCE. <br>

3 Voronoi diagrams are given for the same sites, one with the Manhattan distance, one with the Euclidean distance and the last with the Minkowski distance (order 3).

<lang Prolog>:- dynamic pt/6.

voronoi :-

V is random(20) + 20,

retractall(pt(_,_,_,_)),

forall(between(1, V, I),

( X is random(390) + 5,

Y is random(390) + 5,

R is random(65535),

G is random(65535),

B is random(65535),

assertz(pt(I,X,Y, R, G, B))

)),

voronoi(manhattan, V),

voronoi(euclide, V),

voronoi(minkowski_3, V).

voronoi(Distance, V) :-

sformat(A, 'Voronoi 400X400 ~w ~w', [V, Distance]),

new(D, window(A)),

send(D, size, size(400,400)),

new(Img, image(@nil, width := 400, height := 400 , kind := pixmap)),

forall(between(0,399, I),

forall(between(0,399, J),

( get_nearest_site(V, Distance, I, J, S),

pt(S, _, _, R, G, B),

send(Img, pixel(I, J, colour(@default, R, G, B)))))),

new(Bmp, bitmap(Img)),

send(D, display, Bmp, point(0,0)),

send(D, open).

get_nearest_site(V, Distance, I, J, S) :-

get_nearest_site(V, Distance, I, J, 0, 65535, S).

get_nearest_site(0, _Distance, _I, _J, S, _D, S).

get_nearest_site(V, Distance, I, J, S, D, SF) :-

pt(V, XV, YV, _, _, _),

call(Distance, I, J, XV, YV, DT),

( DT < D -> S1 = V, D1 = DT; S1 = S, D1 = D),

V1 is V - 1,

get_nearest_site(V1, Distance, I, J, S1, D1, SF).

manhattan(X1, Y1, X2, Y2, D) :-

D is abs(X2 - X1) + abs(Y2-Y1).

euclide(X1, Y1, X2, Y2, D) :-

D is sqrt((X2 - X1)**2 + (Y2-Y1)**2).

minkowski_3(X1, Y1, X2, Y2, D) :-

D is (abs(X2 - X1)**3 + abs(Y2-Y1)**3)**0.33.

</lang>

=={{header|PureBasic}}=