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lineartileindex

Determine Which Tile Contains Each Given Point on a Linear Network


Description

Given a tessellation on a linear network, and a list of points on the network, determine which tile of the tessellation contains each of the given points.

Usage

lineartileindex(seg, tp, Z, method = c("encode", "C", "interpreted"))

Arguments

seg,tp

Vectors of local coordinates of the query points. See Details.

Z

A tessellation on a linear network (object of class "lintess").

method

Internal use only.

Details

This low-level function is the analogue of tileindex for linear networks. For a tessellation Z on a linear network, and a list of query points on the same network, the function determines which tile of the tessellation contains each query point.

Argument Z should be a tessellation on a linear network (object of class "lintess").

The vectors seg and tp specify the locations of the query points, on the same network, using local coordinates: seg contains integer values specifying which segment of the network contains each query point; tp contains numeric values between 0 and 1 specifying the fractional position along that segment.

The result is a factor, of the same length as seg and tp, indicating which tile contains each point. The levels of the factor are the names of the tiles of Z.

Value

A factor, of the same length as seg and tp, whose levels are the names of the tiles of Z.

Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk

See Also

as.linfun.lintess to create a function whose value is the tile index.

cut.lpp for a neater way to classify the points of a point pattern on a linear network according to a tessellation on the network.

Examples

Z <- lineardirichlet(runiflpp(15, simplenet))
   X <- runiflpp(10, simplenet)
   coX <- coords(X)
   ii <- lineartileindex(coX$seg, coX$tp, Z)

spatstat.linnet

Linear Networks Functionality of the 'spatstat' Family

v2.1-1
GPL (>= 2)
Authors
Adrian Baddeley [aut, cre], Rolf Turner [aut], Ege Rubak [aut], Ottmar Cronie [ctb], Tilman Davies [ctb], Greg McSwiggan [ctb], Suman Rakshit [ctb]
Initial release
2021-03-28

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