R/defineNulls.R

In eliotmiller/metricTester: Test Metric and Null Model Statistical Performance

#' Output all null models as a list of named functions
#'
#' Creates a list of named functions, each of which accept a nulls.input object
#'
#' @details All of the null models we calculated for our manuscript are included in this
#' function. To add additional null model functions, they can either be defined on the fly
#' or to permanently include a new model in all downstream simulations, it can be
#' included here. The function needs to be included with a name, and it must accept a
#' nulls.input object. If the function needs additional elements not included in that
#' input, then the prepNulls function must also be revised.
#'
#' @return A list of named functions
#'
#' @export
#'
#' @importFrom picante randomizeMatrix
#' @importFrom spacodiR as.picante resamp.2x resamp.3x resamp.1s resamp.2s
#'
#' @references Miller, E. T., D. R. Farine, and C. H. Trisos. 2016. Phylogenetic community
#' structure metrics and null models: a review with new methods and software.
#' Ecography DOI: 10.1111/ecog.02070
#'
#' @examples
#' defineNulls()

defineNulls <- function()
{
	list("twoX"=my_2x,
	"threeX"=my_3x,
	"oneS"=my_1s,
	"twoS"=my_2s,
	"old_regional"=my_oldRegional,
	"new_regional"=my_newRegional,
	"richness"=my_richnessNull,
	"frequency"=my_frequency,
	"independent_swap"=my_IS,
	"trial_swap"=my_TS,
	"dispersal"=my_dispersal
	)
}

my_2x <- function(nulls.input)
{
	temp.matrix <- resamp.2x(nulls.input$spacodi.cdm)
	new.matrix <- suppressMessages(as.picante(temp.matrix))
}

my_3x <- function(nulls.input)
{
	temp.matrix <- resamp.3x(nulls.input$spacodi.cdm)
	new.matrix <- suppressMessages(as.picante(temp.matrix))
}

my_1s <- function(nulls.input)
{
	temp.matrix <- resamp.1s(nulls.input$spacodi.cdm)
	new.matrix <- suppressMessages(as.picante(temp.matrix))
}

my_2s <- function(nulls.input)
{
	temp.matrix <- resamp.2s(nulls.input$spacodi.cdm)
	new.matrix <- suppressMessages(as.picante(temp.matrix))
}

my_oldRegional <- function(nulls.input)
{
	new.matrix <- oldRegionalNull(picante.cdm=nulls.input$picante.cdm, tree=nulls.input$tree, 
		regional.abundance=nulls.input$regional.abundance)
}

my_newRegional <- function(nulls.input)
{
	new.matrix <- newRegionalNull(picante.cdm=nulls.input$picante.cdm,
		regional.abundance=nulls.input$regional.abundance)
}

my_richnessNull <- function(nulls.input)
{
	new.matrix <- randomizeMatrix(nulls.input$picante.cdm, "richness")
}

my_frequency <- function(nulls.input)
{
	new.matrix <- randomizeMatrix(nulls.input$picante.cdm, "frequency")
}

my_IS <- function(nulls.input)
{
	new.matrix <- randomizeMatrix(nulls.input$picante.cdm, "independentswap", 
		iterations=100000)
}

my_TS <- function(nulls.input)
{
	new.matrix <- randomizeMatrix(nulls.input$picante.cdm, "trialswap", 
		iterations=100000)
}

my_dispersal <- function(nulls.input)
{
	new.matrix <- dispersalNull(picante.cdm=nulls.input$picante.cdm,
		tree=nulls.input$tree, distances.among=nulls.input$distances.among)
}