In cesco-lab/Vigie-Chiro_scripts: Predict Distribution Of Chiropter

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  eval = FALSE #TODO Change to TRUE when reprex available
)

library(chirovigie)

Usage of the function `f_biodiv_modgis()`

# Load addings   ----------

library(spdep)
library(data.table)
library(randomForest)

# source(file.path("R", "f_biodiv_modgis.R"))


# Import biodiversity data   ----------

filename <- "DataSpSL_Urosp_90_Data"
DataCPL3 <- read.csv(
  file.path(
    "data",
    paste0(
      filename,
      ".csv"
    )
  )
)


# Import environmental data   ----------

CoordSIG <- read.csv(
  file.path(
    "data",
    "GI_coordWGS84_SpNuit2_50_DataLP_PF_exportTot.csv"
  )
)


# Merge two datasets   ----------

CoordPS <- merge(
  x = DataCPL3,
  y = CoordSIG,
  by.x = c("longitude", "latitude"),
  by.y = c("Group.1", "Group.2"),
  all  = FALSE
)


## Run Random Forest   ----------

mod <- f_biodiv_modgis(
  data          = CoordPS,
  metric        = "nb_contacts",
  x             = "longitude",
  y             = "latitude",
  date          = "date_debut",
  strata        = c("id_site", "localite"),
  num_coord     = 40,
  log_transform = TRUE,
  plot_var_imp  = TRUE
)


## Export model   ----------

dir.create(file.path("outputs"), recursive = TRUE, showWarnings = FALSE)
save(
  mod_rf,
  file = file.path(
    "outputs",
    paste0(
      metric,
      "_",
      filename,
      ".learner"
    )
  )
)