Documentation for SLiM function nearestNeighbors, 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.
nearestNeighbors(receiver, count, exerterSubpop, returnDict)An object of type Individual object. See details for description.
An object of type integer. Must be of length 1 (a singleton). The
default value is 1. 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 logical. Must be of length 1 (a singleton).
The default value is F. See details for description.
An object of type .
Documentation for this function can be found in the official SLiM manual: page 696.
Returns an object<Individual> vector containing up to count individuals that are spatially closest to receiver, according to the distance metric of the InteractionType, from among the exerters in exerterSubpop (or, if that is NULL, then from among all individuals in the receiver's subpopulation). In the default mode of operation, receiver must be singleton (but see below). To obtain all of the individuals within the maximum interaction distance of receiver, simply pass a value for count that is greater than or equal to the size of individual's subpopulation. Note that if fewer than count individuals are within the maximum interaction distance, the vector returned may be shorter than count, or even zero-length; it is important to check for this possibility even when requesting a single neighbor. The evaluate() method must have been previously called for the receiver and exerter subpopulations, and positions saved at evaluation time will be used. If the InteractionType is nonspatial, this method may not be called. Note that this method does not use interaction eligibility as a criterion; it will return neighbors that could not interact with the receiver due to the configured receiver or exerter constraints. (It will never return the receiver as a neighbor of itself, however.) To find only neighbors that are eligible to exert an interaction upon the receiver, use nearestInteractingNeighbors(). Beginning in SLiM 4.1, this method has a vectorized mode of operation in which the receiver parameter may be non-singleton. To switch the method to this mode, pass T for returnDict, rather than the default of F (the operation of which is described above). In this mode, the return value is a Dictionary object instead of a vector of Individual objects. This dictionary uses integer keys that range from 0 to N-1, where N is the number of individuals passed in receiver; these keys thus correspond directly to the indices of the individuals in receiver, and there is one entry in the dictionary for each receiver. The value in the dictionary, for a given integer key, is an object<Individual> vector with the neighbors found for the corresponding receiver, exactly as described above for the non-vectorized case. The results for each receiver can therefore be obtained from the returned dictionary with getValue(), passing the index of the receiver. The speed of this mode of operation will probably be similar to the speed of making N separate non-vectorized calls to nearestNeighbors(), but may have other advantages. In this mode of operation, all receivers must belong to the same subpopulation.
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(),
localPopulationDensity(),
nearestInteractingNeighbors(),
nearestNeighborsOfPoint(),
neighborCountOfPoint(),
neighborCount(),
setConstraints(),
setInteractionFunction(),
strength(),
testConstraints(),
totalOfNeighborStrengths(),
unevaluate()