Class returned by BIOMOD_Projection, and used by
BIOMOD_EnsembleForecasting
# S4 method for class 'BIOMOD.projection.out,missing'
plot(
  x,
  coord = NULL,
  plot.output,
  do.plot = TRUE,
  std = TRUE,
  scales,
  size,
  maxcell = 5e+05,
  ...
)
# S4 method for class 'BIOMOD.projection.out'
show(object)a BIOMOD.projection.out object
a 2-columns data.frame containing the corresponding X and Y
(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.
(optional, default TRUE) a boolean determining
whether the plot should be displayed or just returned.
(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.
(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'.
(optional, default 0.75) a numeric determining the
size of points on the plots and passed to
geom_point.
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
a BIOMOD.projection.out object
modeling.ida character corresponding to the name (ID) of the simulation set
proj.namea character corresponding to the projection name
dir.namea character corresponding to the modeling folder
sp.namea character corresponding to the species name
expl.var.namesa vector containing names of explanatory variables
coorda 2-columns matrix or data.frame containing the corresponding
X and Y coordinates used to project the species distribution model(s)
scale.modelsa logical value defining whether models have been rescaled or
not
models.projecteda vector containing names of projected models
models.outa BIOMOD.stored.data object
typea character corresponding to the class of the val slot of the
proj.out slot
data.typea character corresponding to the data type
proj.outa BIOMOD.stored.data object
calla language object corresponding to the call used to obtain the object
BIOMOD_Projection, BIOMOD_EnsembleForecasting
Other Toolbox objects:
BIOMOD.ensemble.models.out,
BIOMOD.formated.data,
BIOMOD.formated.data.PA,
BIOMOD.models.options,
BIOMOD.models.out,
BIOMOD.options.dataset,
BIOMOD.options.default,
BIOMOD.rangesize.out,
BIOMOD.stored.data,
biomod2_ensemble_model,
biomod2_model
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.name = myRespName,
                                       resp.var = myResp,
                                       resp.xy = myRespXY,
                                       expl.var = myExpl)
  # 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', 'AUCroc'),
                                      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)