comparison brt.R @ 1:b38b954b92b9 draft

planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/Ecoregionalization_workflow commit 459ba1277acd7d8d4a02f90dbd7ff444bf8eac92

0:3d750279158b

#16/02/2023
## Analyse BRT data Ceamarc

### Clean environment 
rm(list = ls(all.names = TRUE))
options(warn=-1)

    stop("This tool needs at least one argument")
}else{
    enviro <- args[1]
    species_files <- args[2]
    abio_para <- args[3]
}

### load data

env = read.table(enviro, header = TRUE, dec = ".", na.strings = "-9999")
pred.vars = strsplit(abio_para, ",")[[1]] 
data_files = strsplit(species_files,",")

#environemental parameters
#Carbo,Grav,Maxbearing,Maxmagnit,Meancurmag,Meansal,Meantheta,Mud,Prof,Rugosity,Sand,Seaice_prod,Sili,Slope,Standcurmag,Standsal,Standtheta

#Load functions

    coord_quickmap()
  output_directory <- ggsave(paste("BRT-",spe,"_pred_plot.png"))
  
  #Write prediction in a file
  preds <- cbind(preds,spe)
  write.table(preds, paste(nb_file,"_brts_pred_ceamarc.txt",sep=""), quote=FALSE, dec=".", row.names=F, col.names=T,append = T)
}

#### RUN BRT ####
nb_file = 0

for (file in data_files[[1]]) {
  species_data <- read.table(file, dec = ",", sep = ";", header = TRUE, na.strings = "na", colClasses = "numeric")
  nb_file = nb_file + 1
  `%!in%` <- Negate(`%in%`)
  sp = list()
  for (n in names(species_data)) {
    if (n %!in% names(env) && n != 'station'){
       sp = cbind(sp,n)
    }
  }
  
  for (spe in sp){
   try(make.prediction.brt(make.brt(spe,species_data,pred.vars,env,nb_file)))
   }
}

1:b38b954b92b9

#16/02/2023
## Analyse BRT data

### Clean environment 
rm(list = ls(all.names = TRUE))
options(warn=-1)

    stop("This tool needs at least one argument")
}else{
    enviro <- args[1]
    species_files <- args[2]
    abio_para <- args[3]
    dec_env <- args[8]
    dec_species <- args[9]
}

### load data

env = read.table(enviro, dec = dec_env, header = TRUE, sep="\t", na.strings = "-9999")
pred_vars = strsplit(abio_para, ",")[[1]] 
data_files = strsplit(species_files,",")

pred.vars <- character(length(pred_vars))

for (i in seq_along(pred_vars)) {
       pred_var_col <- as.numeric(pred_vars[i])
       pred.vars[i] <- names(env)[pred_var_col]}
       
#environemental parameters
#Carbo,Grav,Maxbearing,Maxmagnit,Meancurmag,Meansal,Meantheta,Mud,Prof,Rugosity,Sand,Seaice_prod,Sili,Slope,Standcurmag,Standsal,Standtheta

#Load functions

    coord_quickmap()
  output_directory <- ggsave(paste("BRT-",spe,"_pred_plot.png"))
  
  #Write prediction in a file
  preds <- cbind(preds,spe)
  write.table(preds, paste(nb_file,"_brts_pred_ceamarc.tsv",sep=""), quote=FALSE, dec=".", row.names=F, col.names=T,append = T,sep="\t")
}

#### RUN BRT ####
nb_file = 0

for (file in data_files[[1]]) {
  species_data <- read.table(file, dec = dec_species, sep = "\t", header = TRUE, na.strings = "NA", colClasses = "numeric")
  nb_file = nb_file + 1
  `%!in%` <- Negate(`%in%`)
  sp = list()
  for (n in names(species_data)) {
    if (n %!in% names(env) && n != 'station'){
       sp = cbind(sp,n)
    }
  }     
  for (spe in sp){
   try(make.prediction.brt(make.brt(spe,species_data,pred.vars,env,nb_file)))
   }
}

cat("Here is the list of your abiotic parameters:\n")
cat(paste(pred.vars, collapse = ", "), "\n")