Efficient test for points inside a convex hull in n dimensions. Inspired by the Matlab code by John D'Errico http://www.mathworks.com/matlabcentral/fileexchange/10226-inhull and https://tolstoy.newcastle.edu.au/R/e8/help/09/12/8784.html
inHull(testPts, vertices, hull = geometry::convhulln(vertices),
tol = mean(mean(abs(vertices))) * sqrt(.Machine$double.eps))A nxp array to test, n data points, in p dimensions If you have many points to test, it is most efficient to call this function once with the entire set.
A mxp array of vertices of the convex hull, as used by convhulln.
Tessellation (or triangulation) generated by convhulln If hull is left empty or not supplied, then it will be generated.
Tolerance on the tests for inclusion in the convex hull. You can think of tol as the distance a point may possibly lie outside the hull, and still be perceived as on the surface of the hull. Because of numerical slop nothing can ever be done exactly here. I might guess a semi-intelligent value of tol to be
tol = 1.e-13*mean(abs(vertices(:)))
In higher dimensions, the numerical issues of floating point arithmetic will probably suggest a larger value of tol.
An integer vector of length n