Mercurial > repos > ecology > pampa_presabs

annotate FunctExeCalcPresAbsGalaxy.r @ 3:8d8aec182fb1 draft

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"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 04381ca7162ec3ec68419e308194b91d11cacb04"
author ecology
date Mon, 16 Nov 2020 11:02:09 +0000
parents c9dfe4e20a45
children 07b081730994
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1 #Rscript
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3 #####################################################################################################################
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4 #####################################################################################################################
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5 ############################ Calculate presence absence table from observation data #################################
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6 #####################################################################################################################
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7 #####################################################################################################################
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9 ###################### Packages
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10 suppressMessages(library(tidyr))
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12 ###################### Load arguments and declaring variables
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14 args <- commandArgs(trailingOnly = TRUE)
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17 if (length(args) < 2) {
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18 stop("At least one argument must be supplied, an input dataset file (.tabular).", call. = FALSE) # if no args -> error and exit1
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20 } else {
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21 import_data <- args[1] ###### Nom du fichier importé avec son extension / file name imported with the file type ".filetype"
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22 source(args[2]) ###### Import functions
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24 }
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25 #### d_ata must be a dataframe with at least 3 variables : unitobs representing location and year ("observation.unit"), species code ("species.code") and abundance ("number")
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28 #Import des données / Import data
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29 obs <- read.table(import_data, sep = "\t", dec = ".", header = TRUE, encoding = "UTF-8") #
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30 obs[obs == -999] <- NA
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31 factors <- fact_det_f(obs = obs)
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32 obs_type <- def_typeobs_f(obs = obs)
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33 obs <- create_unitobs(data = obs)
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35 vars_data <- c("observation.unit", "species.code", "number")
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36 err_msg_data <- "The input dataset doesn't have the right format. It need to have at least the following 3 variables :\n- observation.unit (or location and year)\n- species.code\n- number\n"
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37 check_file(obs, err_msg_data, vars_data, 3)
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40 ####################################################################################################
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41 #################### Create presence/absence table ## Function : calc_pres_abs_f ####################
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42 ####################################################################################################
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44 calc_pres_abs_f <- function(d_ata,
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45 nb_name = "number") {
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46 ## Purpose: Compute presence absence
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47 ## ----------------------------------------------------------------------
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48 ## Arguments: d_ata : temporary metrics table
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49 ## nb_name : name of abundance column
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50 ##
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51 ## Output: presence absence vector
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52 ## ----------------------------------------------------------------------
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53 ## Author: Yves Reecht, Date: 20 déc. 2011, 12:04 modified by Coline ROYAUX 04 june 2020
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55 ## Presence - absence :
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56 pres_abs <- integer(nrow(d_ata))
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57 pres_abs[d_ata[, nb_name] > 0] <- as.integer(1)
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58 pres_abs[d_ata[, nb_name] == 0] <- as.integer(0)
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60 return(pres_abs)
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61 }
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64 ################# Analysis
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66 res <- calc_numbers_f(obs, obs_type = obs_type, factors = factors, nb_name = "number")
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67 res$presence_absence <- calc_pres_abs_f(res, nb_name = "number")
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68 res <- create_year_location(res)
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70 #Save dataframe in a tabular format
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71 filename_pres_abs <- "TabPresAbs.tabular"
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72 write.table(res, filename_pres_abs, row.names = FALSE, sep = "\t", dec = ".", fileEncoding = "UTF-8")
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73 cat(paste("\nWrite table with presence/absence. \n--> \"", filename_pres_abs, "\"\n", sep = ""))