BIOMOD.formated.data: 'BIOMOD_FormatingData()' output object class
In biomodhub/biomod2: Ensemble Platform for Species Distribution Modeling

BIOMOD.formated.data

R Documentation

`BIOMOD_FormatingData()` output object class

Description

Class returned by BIOMOD_FormatingData, and used by bm_Tuning, bm_CrossValidation and BIOMOD_Modeling

Usage

## S4 method for signature 'numeric,data.frame'
BIOMOD.formated.data(
  sp,
  env,
  xy = NULL,
  dir.name = ".",
  data.type = NULL,
  sp.name = NULL,
  eval.sp = NULL,
  eval.env = NULL,
  eval.xy = NULL,
  na.rm = TRUE,
  data.mask = NULL,
  shared.eval.env = FALSE,
  filter.raster = FALSE
)

## S4 method for signature 'data.frame,ANY'
BIOMOD.formated.data(
  sp,
  env,
  xy = NULL,
  dir.name = ".",
  data.type = NULL,
  sp.name = NULL,
  eval.sp = NULL,
  eval.env = NULL,
  eval.xy = NULL,
  na.rm = TRUE,
  filter.raster = FALSE
)

## S4 method for signature 'numeric,matrix'
BIOMOD.formated.data(
  sp,
  env,
  xy = NULL,
  dir.name = ".",
  data.type = NULL,
  sp.name = NULL,
  eval.sp = NULL,
  eval.env = NULL,
  eval.xy = NULL,
  na.rm = TRUE,
  filter.raster = FALSE
)

## S4 method for signature 'numeric,SpatRaster'
BIOMOD.formated.data(
  sp,
  env,
  xy = NULL,
  dir.name = ".",
  data.type = NULL,
  sp.name = NULL,
  eval.sp = NULL,
  eval.env = NULL,
  eval.xy = NULL,
  na.rm = TRUE,
  shared.eval.env = FALSE,
  filter.raster = FALSE
)

## S4 method for signature 'BIOMOD.formated.data'
show(object)

Arguments

`sp`	a `vector`, a `SpatVector` without associated data (if presence-only), or a `SpatVector` object containing binary data (`0` : absence, `1` : presence, `NA` : indeterminate) for a single species that will be used to build the species distribution model(s) Note that old format from sp are still supported such as `SpatialPoints` (if presence-only) or `SpatialPointsDataFrame` object containing binary data.
`env`	a `matrix`, `data.frame`, `SpatVector` or `SpatRaster` object containing the explanatory variables (in columns or layers) that will be used to build the species distribution model(s). Note that old format from raster and sp are still supported such as `RasterStack` and `SpatialPointsDataFrame` objects.
`xy`	(optional, default `NULL`) If `resp.var` is a `vector`, a 2-columns `matrix` or `data.frame` containing the corresponding `X` and `Y` coordinates that will be used to build the species distribution model(s)
`dir.name`	a `character` corresponding to the modeling folder
`data.type`	a `character` corresponding to the data type
`sp.name`	a `character` corresponding to the species name
`eval.sp`	(optional, default `NULL`) A `vector`, a `SpatVector` without associated data (if presence-only), or a `SpatVector` object containing binary data (`0` : absence, `1` : presence, `NA` : indeterminate) for a single species that will be used to evaluate the species distribution model(s) with independent data Note that old format from sp are still supported such as `SpatialPoints` (if presence-only) or `SpatialPointsDataFrame` object containing binary data.
`eval.env`	(optional, default `NULL`) A `matrix`, `data.frame`, `SpatVector` or `SpatRaster` object containing the explanatory variables (in columns or layers) that will be used to evaluate the species distribution model(s) with independent data Note that old format from raster and sp are still supported such as `RasterStack` and `SpatialPointsDataFrame` objects.
`eval.xy`	(optional, default `NULL`) If `resp.var` is a `vector`, a 2-columns `matrix` or `data.frame` containing the corresponding `X` and `Y` coordinates that will be used to evaluate the species distribution model(s) with independent data
`na.rm`	(optional, default `TRUE`) A `logical` value defining whether points having one or several missing values for explanatory variables should be removed from the analysis or not
`data.mask`	(optional, default `NULL`) A `SpatRaster` object containing the mask of the studied area
`shared.eval.env`	(optional, default `FALSE`) A `logical` value defining whether the explanatory variables used for the evaluation dataset are the same than the ones for calibration (if `eval.env` not provided for example) or not
`filter.raster`	(optional, default `FALSE`) If `env` is of raster type, a `logical` value defining whether `sp` is to be filtered when several points occur in the same raster cell
`object`	a `BIOMOD.formated.data` object

Slots

data.type: a character corresponding to the data type
dir.name: a character corresponding to the modeling folder
sp.name: a character corresponding to the species name
coord: a 2-columns data.frame containing the corresponding X and Y coordinates
data.species: a vector containing the species observations (0, 1 or NA)
data.env.var: a data.frame containing explanatory variables
data.mask: a SpatRaster object containing the mask of the studied area
has.data.eval: a logical value defining whether evaluation data is given
has.filter.raster: a logical value defining whether filtering have been done or not
eval.coord: (optional, default NULL)
A 2-columns data.frame containing the corresponding X and Y coordinates for evaluation data
eval.data.species: (optional, default NULL)
A vector containing the species observations (0, 1 or NA) for evaluation data
eval.data.env.var: (optional, default NULL)
A data.frame containing explanatory variables for evaluation data
biomod2.version: a character corresponding to the biomod2 version
call: a language object corresponding to the call used to obtain the object

Author(s)

Damien Georges

Examples


showClass("BIOMOD.formated.data")

## ----------------------------------------------------------------------- #
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)



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

biomodhub/biomod2 documentation built on July 4, 2025, 6:15 p.m.