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I want to calculate the diameter of a convex polygon. That is, the largest distance between any pair of vertices. Here's my approach
pol = Polygon@{{-6.4, -8.3}, {-5.5, -9}, {-5, -8.4}, {-5, -7.9}, {-5.9, -7.6}};
vts = pol[[1]];
AbsoluteTiming@
Max@Table[Table[EuclideanDistance[vts[[i]], vts[[j]]],
{j, i + 1, Length@vts}], {i, Length@vts - 1}]
(* {0.000058, 1.45602} *)
What do you think? Is there a faster way of doing this?
$Version
(* "12.3.1 for Mac OS X x86 (64-bit) (June 19, 2021)" *)
Clear["Global`*"]
pol = Polygon@{{-6.4, -8.3}, {-5.5, -9}, {-5, -8.4}, {-5, -7.9}, \
{-5.9, -7.6}};
vts = pol[[1]];
AbsoluteTiming@Max[EuclideanDistance @@@ Subsets[vts, {2}]]
(* {0.000044, 1.45602} *)
Subsets. I'm running the same version on Windows 10 and I compared both approaches (essentially listed the timings over 10^5 runs and took the mean). Just in case you're curious: my absolute timing converged to $0.000020782$, while yours to $0.0000125165$.
$\endgroup$
Aug 4, 2021 at 13:44
See also DistanceMatrix which is a little slower than Subsets, and Outer which is about the same with this many points:
RepeatedTiming@Max@DistanceMatrix@pol[[1]]
RepeatedTiming[
Max@Outer[EuclideanDistance, #, #, 1] &@pol[[1]]
]
