Documentation for SLiM function localPopulationDensity, which is a method
of the SLiM class InteractionType.
Note that the R function is a stub, it does not do anything in R (except bring
up this documentation). It will only do
anything useful when used inside a slim_block function further
nested in a slim_script
function call, where it will be translated into valid SLiM code as part of a
full SLiM script.
localPopulationDensity(receivers, exerterSubpop)An object of type Individual object. See details for description.
An object of type null or Subpopulation object. Must be
of length 1 (a singleton). The default value is NULL. See details for
description.
An object of type float.
Documentation for this function can be found in the official SLiM manual: page 694.
Returns a vector of the local population density present at the location of each individual in receivers, which does not need to be a singleton; indeed, it can be a vector of all of the individuals in a given subpopulation. However, all receivers must be in the same subpopulation. The local population density is computed from exerters in exerterSubpop, or if that is NULL (the default), then from the receiver's subpopulation. The evaluate() method must have been previously called for the receiver and exerter subpopulations, and positions saved at evaluation time will be used. Population density is estimated using interaction strengths, effectively doing a kernel density estimate using the interaction function as the kernel. What is returned is computed as the total interaction strength present at a given point, divided by the integral of the interaction function around that point after clipping by the spatial bounds of the exerter subpopulation (what one might think of as the amount of "interaction field" around the point). This provides an estimate of local population density, in units of individuals per unit area, as a weighted average over the area covered by the interaction function, where the weight of each exerter in the average is the value of the interaction function at that exerter's position. This can also be thought of as a measure of the amount of interaction happening per unit of interaction field in the space surrounding the point. To calculate the clipped integral of the interaction function, this method uses the same numerical estimator used by the clippedIntegral() method of InteractionType, and all of the caveats described for that method apply here also; notably, all individuals must be within spatial bounds, the maximum interaction distance must be less than half the spatial extent of the subpopulation, and interaction() callbacks are not used (and so, for this method, are not allowed to be active). See the documentation for clippedIntegral() for further discussion of the details of these calculations. To calculate the total interaction strength around the position of a receiver, this method uses the same machinery as the totalOfNeighborStrengths() method of InteractionType, except that - in contrast to other InteractionType methods - the interaction strength exerted by the receiver itself is included in the total (if the exerter subpopulation is the receiver's own subpopulation). This is because population density at the location of an individual includes the individual itself. If this is not desirable, the totalOfNeighborStrengths() method should probably be used. To see the point of this method, consider a receiver located near the edge of the spatial bounds of its subpopulation. Some portion of the interaction function that surrounds that receiver falls outside the spatial bounds of its subpopulation, and will therefore never contain an interacting exerter. If, for example, interaction strengths are used as a measure of competition, this receiver will therefore have an advantage, because it will never feel any competition from the portion of its range that falls outside spatial bounds. However, that portion of its range is presumably also not available to the receiver itself, for foraging or hunting, in which case this advantage is not biologically realistic, but is instead just an undesirable "edge effect" artifact. Dividing by the integral of the interaction function, clipped to the spatial bounds, provides a way to compensate for this edge effect. A nice side effect of using local population densities instead of total interaction strengths is that the maximum interaction strength passed to setInteractionFunction() no longer matters; it cancels out when the total interaction strength is divided by the receiver's clipped integral. However, the shape of the interaction function does still matter; it determines the relative weights used for exerters at different distances from the position of the receiver.
This is documentation for a function in the SLiM software, and has been reproduced from the official manual, which can be found here: http://benhaller.com/slim/SLiM_Manual.pdf. This documentation is Copyright © 2016-2020 Philipp Messer. All rights reserved. More information about SLiM can be found on the official website: https://messerlab.org/slim/
Other InteractionType:
IT,
clippedIntegral(),
distanceFromPoint(),
distance(),
drawByStrength(),
evaluate(),
interactingNeighborCount(),
interactionDistance(),
nearestInteractingNeighbors(),
nearestNeighborsOfPoint(),
nearestNeighbors(),
neighborCountOfPoint(),
neighborCount(),
setConstraints(),
setInteractionFunction(),
strength(),
testConstraints(),
totalOfNeighborStrengths(),
unevaluate()