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N-D nearest point search
k = dsearchn(X,T,XI)
k = dsearchn(X,T,XI,outval)
k = dsearchn(X,XI)
[k,d] = dsearchn(X,...)
k = dsearchn(X,T,XI) returns the indices k of the closest points in X for each point in XI. X is an m-by-n matrix representing m points in n-dimensional space. XI is a p-by-n matrix, representing p points in n-dimensional space. T is a numt-by-n+1 matrix, a triangulation of the data X generated by delaunayn. The output k is a column vector of length p.
k = dsearchn(X,T,XI,outval) returns the indices k of the closest points in X for each point in XI, unless a point is outside the convex hull. If XI(J,:) is outside the convex hull, then K(J) is assigned outval, a scalar double. Inf is often used for outval. If outval is [], then k is the same as in the case k = dsearchn(X,T,XI).
k = dsearchn(X,XI) performs the search without using a triangulation. With large X and small XI, this approach is faster and uses much less memory.
[k,d] = dsearchn(X,...) also returns the distances d to the closest points. d is a column vector of length p.
[1] Barber, C. B., D.P. Dobkin, and H.T. Huhdanpaa, "The Quickhull Algorithm for Convex Hulls," ACM Transactions on Mathematical Software, Vol. 22, No. 4, Dec. 1996, p. 469–483.