sortOn: Sort 'agents'

In PredictiveEcology/NetLogoR: Build and Run Spatially Explicit Agent-Based Models

Sort agents

Description

Return the agents sorted according to their value.

Usage

sortOn(agents, world, var)

## S4 method for signature 'matrix,worldMatrix,missing'
sortOn(agents, world)

## S4 method for signature 'matrix,worldArray,character'
sortOn(agents, world, var)

## S4 method for signature 'agentMatrix,missing,character'
sortOn(agents, var)

Arguments

agents	Matrix (ncol = 2) with the first column pxcor and the second column pycor representing the patches coordinates, or `AgentMatrix` object representing the moving `agents`.
world	WorldMatrix or worldArray object.
var	Character. The name of the selected agents variable. If agents are patches and the world is a worldMatrix object, var must not be provided. If agents are patches and the world is a worldArray object, var is the name of the layer to use to define the patches values. If agents are turtles, var is one of the turtles' variable and can be equal to xcor, ycor, any of the variables created when turtles were created, as well as any variable created using turtlesOwn().

Details

world must not be provided if agents are turtles.

     The sorting of the `agents` is done in a increasing order.

Value

Matrix (ncol = 2) with the first column pxcor and the second column pycor representing the coordinates of the patches sorted according to their values, if agents are patches, or

    `AgentMatrix` representing the `turtles` sorted according
    to their `var` values, if `agents` are
    `turtles`.

Author(s)

Sarah Bauduin

References

Wilensky, U. 1999. NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University. Evanston, IL.

See Also

https://ccl.northwestern.edu/netlogo/docs/dictionary.html#sort-on

Examples

# Patches
w1 <- createWorld(
  minPxcor = 0, maxPxcor = 4, minPycor = 0, maxPycor = 4,
  data = sample(1:5, size = 25, replace = TRUE)
)
plot(w1)
p1 <- sortOn(agents = patches(w1), world = w1)

# Turtles
t1 <- createTurtles(n = 10, coords = randomXYcor(w1, n = 10))
sortHeadingT1 <- sortOn(agents = t1, var = "heading")

# or
library(quickPlot)

Plot(w1)
Plot(t1, addTo = "w1")

PredictiveEcology/NetLogoR documentation built on Jan. 31, 2024, 9:31 p.m.