R: Perspective View of Pixel Image on a Linear Network

persp.linim {spatstat.linnet} | R Documentation

## Perspective View of Pixel Image on a Linear Network

### Description

Given a pixel image on a linear network, generate a perspective view.

### Usage

     ## S3 method for class 'linim'
    persp(x, ..., main,
                           grid = TRUE, ngrid = 10,
                           col.grid = "grey", col.base = "white",
                           neg.args=list(), warncross=FALSE)

### Arguments

`x` | Pixel image on a linear network (object of class `"linim"`).
`...` | Arguments passed to `persp.default` to control the perspective view, or passed to `segments` or `polygon` to control the appearance of the vertical panes.
`main` | Main title for the plot.
`grid` | Logical value indicating whether to draw a rectangular grid at height zero, to assist the perception of perspective.
`ngrid` | Number of grid lines to draw, if `grid=TRUE`.
`col.grid` | Colour of grid lines, if `grid=TRUE`.
`col.base` | Colour of base plane, if `grid=TRUE`.
`neg.args` | Optional list of arguments passed to `polygon` when displaying negative values of the function.
`warncross` | Logical value indicating whether to issue a warning if two segments of the network cross each other (which causes difficulty for the algorithm).

### Details

The pixel values are interpreted as the spatially-varying height of a vertical surface erected on each segment of the linear network. These surfaces are drawn in perspective view.

This style of plot is often attributed to Okabe and Sugihara (2012).

### Value

(Invisibly) the perspective transformation matrix, as described in the help for `persp.default`.

### Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au and Greg McSwiggan.

### References

Okabe, A. and Sugihara, K. (2012) Spatial Analysis Along Networks. John Wiley and Sons, New York.

### See Also

`persp.linfun`

### Examples

      if(interactive()) {
        Z <- density(chicago, 100)
      } else {
        X <- runiflpp(10, simplenet)
        Z <- density(X, 0.1)
      }
      persp(Z, theta=30, phi=20)

[Package spatstat.linnet version 2.3-1 Index]