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.

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