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spatstat (version 1.20-2)

nncross: Nearest Neighbours Between Two Patterns

Description

Given two point patterns X and Y, finds the nearest neighbour in Y of each point of X. Alternatively Y may be a line segment pattern.

Usage

nncross(X, Y, iX=NULL, iY=NULL)

Arguments

X
Point pattern (object of class "ppp").
Y
Either a point pattern (object of class "ppp") or a line segment pattern (object of class "psp").
iX, iY
Optional identifiers, applicable only in the case where Y is a point pattern, used to determine whether a point in X is identical to a point in Y. See Details

Value

  • A data frame with two columns:
  • distNearest neighbour distance
  • whichNearest neighbour index in Y

Details

Given two point patterns X and Y this function finds, for each point of X, the nearest point of Y. The distance between these points is also computed.

Alternatively if X is a point pattern and Y is a line segment pattern, the function finds the nearest line segment to each point of X, and computes the distance.

The return value is a data frame, with rows corresponding to the points of X. The first column gives the nearest neighbour distances (i.e. the ith entry is the distance from the ith point of X to the nearest element of Y). The second column gives the indices of the nearest neighbours (i.e. the ith entry is the index of the nearest element in Y.)

Note that this function is not symmetric in X and Y. To find the nearest neighbour in X of each point in Y, where Y is a point pattern, use nncross(Y,X).

The arguments iX and iY are used when the two point patterns X and Y have some points in common. In this situation nncross(X, Y) would return some zero distances. To avoid this, attach a unique integer identifier to each point, such that two points are identical if their identifying numbers are equal. Let iX be the vector of identifier values for the points in X, and iY the vector of identifiers for points in Y. Then the code will only compare two points if they have different values of the identifier. See the Examples.

See Also

nndist for nearest neighbour distances in a single point pattern.

Examples

Run this code
# two different point patterns
  X <- runifpoint(15)
  Y <- runifpoint(20)
  N <- nncross(X,Y)$which
  # note that length(N) = 15
  plot(superimpose(X=X,Y=Y), main="nncross", cols=c("red","blue"))
  arrows(X$x, X$y, Y[N]$x, Y[N]$y, length=0.15)

  # two patterns with some points in common
  Z <- runifpoint(50)
  X <- Z[1:30]
  Y <- Z[20:50]
  iX <- 1:30
  iY <- 20:50
  N <- nncross(X,Y, iX, iY)$which
  plot(superimpose(X=X, Y=Y), main="nncross", cols=c("red","blue"))
  arrows(X$x, X$y, Y[N]$x, Y[N]$y, length=0.15)

  # point pattern and line segment pattern
  X <- runifpoint(15)
  Y <- rpoisline(10)
  N <- nncross(X,Y)

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