DistEco: Tools for internal data structure exploration

In EcotoneFinder: Characterising and Locating Ecotones and Communities

Description

Tools for internal data structure exploration

Usage

DistEco(data, distance.method = "inner_product", transpose = TRUE,
  symm = FALSE, plot = c("heatmap", "network"),
  palette = "colorblind", spinglass = TRUE, run = 10,
  spinglass.groups = c("rounded", "raw"), manual.groups = NULL,
  return.network = TRUE, ...)

Arguments

data	A community or environmental matrix, containing species or variables as columns and sites as rows.
distance.method	The distance method to be used for the calculation of the distance matrix. Must be one of philentropy::distance
transpose	Logical. If TRUE, the distance matrix is calculated between species. If FALSE, it is calculated between sites.
symm	Logical indicating if x should be treated symmetrically; can only be true when x is a square matrix. See stats::heatmap.
plot	The kind of plot produced by the function. Can be “heatmap” or “network”.
palette	The colour palette for the network, if spinglass = TRUE. Must be one of the palettes supported by qgraph. Default to “colorblind”.
spinglass	Logical. Whether or not to run a spinglass algorithm to produce statistical groups for the network. The spinglass algorithm is performed with the CommunityNetwork function.
run	Number of runs for the spinglass algorithm. Higher numbers produce more trustable results but rapidly increase computation time. Default to 10.
spinglass.groups	If spinglass = TRUE, the type of grouping to use from the results of the spinglass algorithm. See Details.
manual.groups	If spinglass = FALSE, an object that indicates which nodes belong together. Can be a list in which each element is a vector of integers identifying the numbers of the nodes that belong together, or a factor.
return.network	Logical. If TRUE, the qgraph object is returned as output of the function.
...	Additionnal parameters for heatmap or qgraph.

Value

A plot corresponding to the plot argument.

Examples

 ### Artificial data:
 SyntheticTrial <- SyntheticData(SpeciesNum = 21, CommunityNum = 3,
                                 SpCo = NULL, Length = 500,
                                 Parameters = list(a=rep(60, 3),
                                                 b=c(0,250,500),
                                                 c=rep(0.01,3)),
                                 pal = c("#008585", "#FBF2C4", "#C7522B"))

 ## Network of species, with raw spinglass groups:
 DistEco(SyntheticTrial[,2:ncol(SyntheticTrial)], transpose = TRUE,
         plot = c("network"), spinglass = TRUE, run = 10,
         spinglass.groups = c("raw"))

 ## Heatmap of species:
 DistEco(SyntheticTrial[,2:ncol(SyntheticTrial)], transpose = TRUE,
         symm = FALSE, plot = c("heatmap"))

EcotoneFinder documentation built on Feb. 17, 2021, 1:07 a.m.