cc.manip | R Documentation |
As described in the vignette, we recommend using these wrappers to
manipulate species and site data, as it guarantees that everything
will be kept consistent across all parts of the
comparative.comm
object. With them, you can drop
species, sites, and work directly with each part of your data. You
can also manipulate your comparative.comm
object's
phy
, data
, env
, and comm
slots directly
if you wish, but altering the object directly yourself runs the
risk of things getting unsynchronised.
## S3 method for class 'comparative.comm' x[sites, spp, warn = FALSE] trait.names(object) env.names(object) species(x) species(x) <- value sites(x) sites(x) <- value traits(x) <- value traits(x) env(x) <- value env(x) comm(x) <- value comm(x) tree(x) phy(x) tree(x) <- value phy(x) <- value assemblage.phylogenies(data) ## S3 method for class 'comparative.comm' as.data.frame( x, row.names = NULL, optional = FALSE, abundance.weighted = FALSE, ... ) ## S3 method for class 'comparative.comm' within(data, expr, ...)
x |
|
sites |
numbers of sites to be kept or dropped from |
spp |
numbers of species to be kept or dropped from |
warn |
whether to warn if species/sites are dropped when creating object (default: TRUE) |
object |
A |
value |
when altering a |
data |
A |
row.names |
ignored |
optional |
ignored presence-absence dataset (default: FALSE) |
abundance.weighted |
whether to create to create a |
... |
ignored |
expr |
expression to be evaluated within the scope of
|
Names of the traits or environmental variables
As described in comparative.comm
, each
comparative.comm
object contains a phylogeny
($phy
) and a site-by-species community matrix (as used in
vegan
). Optionally, it may contain a
data.frame
of trait data (each row a species, each column a
trait ) *called data
* for compatibility with
comparative.data
.
comparative.comm plot.comaparative.comm
data(laja) data <- comparative.comm(invert.tree, river.sites, invert.traits, river.env) #Subset on species, then sites data <- data[1:5,] data <- data[,1:5] #Site and species can be manipulated species(data) sites(data)[1:3] <- c("lovely", "invert", "sites") #Other data can be viewed trait.names(data) env.names(data) #Get assemblage phylogenies of all sites assemblage.phylogenies(data) #Add some trait/env data in traits(data)$new.trait <- sample(letters, nrow(comm(data)), replace=TRUE) env(data)$new.env <- sample(letters, ncol(comm(data)), replace=TRUE) #Manipulate/check phylogeny and community matrix phy(data) #...tree(data) works too... comm(data)[1,3] <- 3 comm(data) <- comm(data)[-3,]
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