biomod2 (version 4.1-2)

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, col = NULL, str.grep = NULL)
# S4 method for BIOMOD.projection.out
show(object)

Arguments

x

a BIOMOD.projection.out object

col

a vector containing colors for plot (default : colorRampPalette(c("grey90", "yellow4", "green4"))(100))

str.grep

a character corresponding to the name (or part of the name(s)) of models projected

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

See Also

BIOMOD_Projection, BIOMOD_EnsembleForecasting

Other Toolbox objects: BIOMOD.ensemble.models.out, BIOMOD.formated.data.PA, BIOMOD.formated.data, BIOMOD.models.options, BIOMOD.models.out, BIOMOD.stored.data, biomod2_ensemble_model, biomod2_model

Examples

showClass("BIOMOD.projection.out")

## ----------------------------------------------------------------------- #

# Load species occurrences (6 species available)
myFile <- system.file('external/species/mammals_table.csv', package = 'biomod2')
DataSpecies <- read.csv(myFile, row.names = 1)
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)
myFiles <- paste0('external/bioclim/current/bio', c(3, 4, 7, 11, 12), '.grd')
myExpl <- raster::stack(system.file(myFiles, package = 'biomod2'))

# \dontshow{
myExtent <- raster::extent(0,30,45,70)
myExpl <- raster::stack(raster::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)

  # Create default modeling options
  myBiomodOptions <- BIOMOD_ModelingOptions()

  # Model single models
  myBiomodModelOut <- BIOMOD_Modeling(bm.format = myBiomodData,
                                      modeling.id = 'AllModels',
                                      models = c('RF', 'GLM'),
                                      bm.options = myBiomodOptions,
                                      nb.rep = 2,
                                      data.split.perc = 80,
                                      metric.eval = c('TSS','ROC'),
                                      var.import = 3,
                                      do.full.models = FALSE,
                                      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)