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spatstat.linnet (version 3.2-2)

Math.linim: S3 Group Generic Methods for Images on a Linear Network

Description

These are group generic methods for images of class "linim", which allows for usual mathematical functions and operators to be applied directly to pixel images on a linear network. See Details for a list of implemented functions.

Usage

## S3 methods for group generics have prototypes:
Math(x, ...)
Ops(e1, e2)
Complex(z)
Summary(..., na.rm = FALSE)



Value

The return value is another object of class "linim", except in the following cases:

all and any return a single logical value; sum, prod, min and max

return a single numerical value; range returns a vector of two numerical values.

Arguments

x, z, e1, e2

objects of class "linim".

...

further arguments passed to methods.

na.rm

logical: should missing values be removed?

Author

Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner rolfturner@posteo.net and Ege Rubak rubak@math.aau.dk.

Details

An object of class "linim" represents a pixel image on a linear network. See linim.

Below is a list of mathematical functions and operators which are defined for these images. Not all functions will make sense for all types of images. For example, none of the functions in the "Math" group make sense for character-valued images. Note that the "Ops" group methods are implemented using eval.linim.

  1. Group "Math":

    • abs, sign, sqrt,
      floor, ceiling, trunc,
      round, signif

    • exp, log, expm1, log1p,
      cos, sin, tan,
      cospi, sinpi, tanpi,
      acos, asin, atan

      cosh, sinh, tanh,
      acosh, asinh, atanh

    • lgamma, gamma, digamma, trigamma

    • cumsum, cumprod, cummax, cummin

  2. Group "Ops":

    • "+", "-", "*", "/", "^", "%%", "%/%"

    • "&", "|", "!"

    • "==", "!=", "<", "<=", ">=", ">"

  3. Group "Summary":

    • all, any

    • sum, prod

    • min, max

    • range

  4. Group "Complex":

    • Arg, Conj, Im, Mod, Re

See Also

eval.linim for evaluating expressions involving images.

Examples

Run this code
  fx <- function(x,y,seg,tp) { (x - y)^2 }
  fL <- linfun(fx, simplenet)
  Z <- as.linim(fL)
  A <- Z+2
  A <- -Z
  A <- sqrt(Z)
  A <- !(Z > 0.1)

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