R: Convert Data to a Function on a Linear Network

as.linfun {spatstat.linnet} | R Documentation

## Convert Data to a Function on a Linear Network

### Description

Convert some kind of data to an object of class `"linfun"` representing a function on a linear network.

### Usage

      as.linfun(X, ...)

      ## S3 method for class 'linim'
    as.linfun(X, ...)

      ## S3 method for class 'lintess'
    as.linfun(X, ..., values=marks(X), navalue=NA)

### Arguments

`X` | Some kind of data to be converted.
`...` | Other arguments passed to methods.
`values` | Optional. Vector of function values, one entry associated with each tile of the tessellation.
`navalue` | Optional. Function value associated with locations that do not belong to a tile of the tessellation.

### Details

An object of class `"linfun"` represents a function defined on a linear network.

The function `as.linfun` is generic. The method `as.linfun.linim` converts objects of class `"linim"` (pixel images on a linear network) to functions on the network.

The method `as.linfun.lintess` converts a tessellation on a linear network into a function with a different value on each tile of the tessellation. The function values are specified by the argument `values`. It should be a vector with one entry for each tile of the tessellation; any point lying in tile number `i` will return the value `v[i]`. If `values` is missing, the marks of the tessellation are taken as the function values. If `values` is missing and the tessellation has no marks, or if `values` is given as `NULL`, then the function returns factor values identifying which tile contains each given point.

### Value

Object of class `"linfun"`.

### 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

`linfun`

### Examples

       X <- runiflpp(2, simplenet)
       Y <- runiflpp(5, simplenet)

       # image on network
       D <- density(Y, 0.1)

       f <- as.linfun(D)
       f
       f(X)

       # tessellation on network
       Z <- lineardirichlet(Y)
       g <- as.linfun(Z)
       g(X)
       h <- as.linfun(Z, values = runif(5))
       h(X)

[Package spatstat.linnet version 2.3-1 Index]