BIOMOD.projection.out: `BIOMOD_Projection()` output object class

Description

Class returned by BIOMOD_Projection, and used by BIOMOD_EnsembleForecasting

Usage

# S4 method for BIOMOD.projection.out,missing
plot(
  x,
  coord = NULL,
  plot.output,
  do.plot = TRUE,
  std = TRUE,
  scales,
  size,
  maxcell = 5e+05,
  ...
)
# S4 method for BIOMOD.projection.out
show(object)

Arguments

x: a BIOMOD.projection.out object
coord: a 2-columns data.frame containing the corresponding X and Y
plot.output: (optional, default facet) a character determining the type of output: with plot.output = 'list' the function will return a list of plots (one plot per model) ; with 'facet' ; with plot.output = 'facet' the function will return a single plot with all asked projections as facet.
do.plot: (optional, default TRUE) a boolean determining whether the plot should be displayed or just returned.
std: (optional, default TRUE) a boolean controlling the limits of the color scales. With std = TRUE color scales are displayed between 0 and 1 (or 1000). With std = FALSE color scales are displayed between 0 and the maximum value observed.
scales: (optional, default fixed) a character determining whether x and y scales are shared among facet. Argument passed to facet_wrap. Possible values: 'fixed', 'free_x', 'free_y', 'free'.
size: (optional, default 0.75) a numeric determing the size of points on the plots and passed to geom_point.
maxcell: maximum number of cells to plot. Argument transmitted to plot.
...: additional parameters to be passed to get_predictions to select the models that will be plotted
object: a BIOMOD.projection.out object

Slots

modeling.id: a character corresponding to the name (ID) of the simulation set

proj.name

a character corresponding to the projection name

dir.name

a character corresponding to the modeling folder

sp.name

a character corresponding to the species name

expl.var.names

a vector containing names of explanatory variables

coord

a 2-columns matrix or data.frame containing the corresponding X and Y coordinates used to project the species distribution model(s)

scale.models

a logical value defining whether models have been rescaled or not

models.projected

a vector containing names of projected models

models.out

a BIOMOD.stored.data object

type

a character corresponding to the class of the val slot of the proj.out slot

proj.out

a BIOMOD.stored.data object

Author

Damien Georges

Examples

Run this code


showClass("BIOMOD.projection.out")

## ----------------------------------------------------------------------- #
library(terra)

# Load species occurrences (6 species available)
data(DataSpecies)
head(DataSpecies)

# Select the name of the studied species
myRespName <- 'GuloGulo'

# Get corresponding presence/absence data
myResp <- as.numeric(DataSpecies[, myRespName])

# Get corresponding XY coordinates
myRespXY <- DataSpecies[, c('X_WGS84', 'Y_WGS84')]

# Load environmental variables extracted from BIOCLIM (bio_3, bio_4, bio_7, bio_11 & bio_12)
data(bioclim_current)
myExpl <- terra::rast(bioclim_current)

# \dontshow{
myExtent <- terra::ext(0,30,45,70)
myExpl <- terra::crop(myExpl, myExtent)
# }

## ----------------------------------------------------------------------- #
file.out <- paste0(myRespName, "/", myRespName, ".AllModels.models.out")
if (file.exists(file.out)) {
  myBiomodModelOut <- get(load(file.out))
} else {

  # Format Data with true absences
  myBiomodData <- BIOMOD_FormatingData(resp.var = myResp,
                                       expl.var = myExpl,
                                       resp.xy = myRespXY,
                                       resp.name = myRespName)

  # Model single models
  myBiomodModelOut <- BIOMOD_Modeling(bm.format = myBiomodData,
                                      modeling.id = 'AllModels',
                                      models = c('RF', 'GLM'),
                                      CV.strategy = 'random',
                                      CV.nb.rep = 2,
                                      CV.perc = 0.8,
                                      OPT.strategy = 'bigboss',
                                      metric.eval = c('TSS','ROC'),
                                      var.import = 3,
                                      seed.val = 42)
}


## ----------------------------------------------------------------------- #
# Project single models
myBiomodProj <- BIOMOD_Projection(bm.mod = myBiomodModelOut,
                                  proj.name = 'Current',
                                  new.env = myExpl,
                                  models.chosen = 'all',
                                  metric.binary = 'all',
                                  metric.filter = 'all',
                                  build.clamping.mask = TRUE)
myBiomodProj
plot(myBiomodProj)