Mercurial > repos > ecology > pampa_glmcomm
annotate FunctExeCalcGLMGalaxy.r @ 1:61cc30e94df4 draft
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 30ad791ef2452487dc248d4266c0cf14eda79914"
author | ecology |
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date | Wed, 22 Jul 2020 11:53:35 -0400 |
parents | f0dc3958e65d |
children | 44b9069775ca |
rev | line source |
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f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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1 #Rscript |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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2 |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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3 ##################################################################################################################### |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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4 ##################################################################################################################### |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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5 ################################# Compute a Generalized Linear Model from your data ################################# |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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6 ##################################################################################################################### |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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7 ##################################################################################################################### |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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8 |
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"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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9 ###################### Packages |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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10 suppressMessages(library(multcomp)) |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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11 suppressMessages(library(glmmTMB)) ###Version: 0.2.3 |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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12 suppressMessages(library(gap)) |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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13 |
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"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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14 ###################### Load arguments and declaring variables |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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16 args = commandArgs(trailingOnly=TRUE) |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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17 #options(encoding = "UTF-8") |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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18 |
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"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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19 if (length(args) < 10) { |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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20 stop("At least 4 arguments must be supplied : \n- two input dataset files (.tabular) : metrics table and unitobs table \n- Interest variable field from metrics table \n- Response variable from unitobs table.", call.=FALSE) #si pas d'arguments -> affiche erreur et quitte / if no args -> error and exit1 |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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21 |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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22 } else { |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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23 Importdata <- args[1] ###### file name : metrics table |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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24 ImportUnitobs <- args[2] ###### file name : unitobs informations |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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25 colmetric <- as.numeric(args[3]) ###### Selected interest metric for GLM |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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26 listFact <- strsplit(args [4],",")[[1]] ###### Selected response factors for GLM |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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27 listRand <- strsplit(args [5],",")[[1]] ###### Selected randomized response factors for GLM |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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28 colFactAna <- args[6] ####### (optional) Selected splitting factors for GLMs |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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29 Distrib <- args[7] ###### (optional) Selected distribution for GLM |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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30 log <- args[8] ###### (Optional) Log on interest metric ? |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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31 aggreg <- args[9] ###### Aggregation level of the data table |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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32 source(args[10]) ###### Import functions |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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33 |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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34 } |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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35 #### Data must be a dataframe with at least 3 variables : unitobs representing location and year ("observation.unit"), species code ("species.code") and abundance ("number") |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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36 |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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37 |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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38 #Import des données / Import data |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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39 obs<- read.table(Importdata,sep="\t",dec=".",header=TRUE,encoding="UTF-8") # |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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40 obs[obs == -999] <- NA |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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41 metric <- colnames(obs)[colmetric] |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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42 tabUnitobs <- read.table(ImportUnitobs,sep="\t",dec=".",header=TRUE,encoding="UTF-8") |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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43 tabUnitobs[tabUnitobs == -999] <- NA |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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44 |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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45 if (colFactAna != "None") |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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46 { |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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47 FactAna <- colnames(tabUnitobs)[as.numeric(colFactAna)] |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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48 if (class(tabUnitobs[FactAna]) == "numeric" || FactAna == "observation.unit"){stop("Wrong chosen separation factor : Analysis can't be separated by observation unit or numeric factor")} |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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49 }else{ |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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50 FactAna <- colFactAna |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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51 } |
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"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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52 |
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"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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53 |
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"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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54 #factors <- fact.det.f(Obs=obs) |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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55 |
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"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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56 vars_data1<- NULL |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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57 err_msg_data1<-"The input metrics dataset doesn't have the right format. It needs to have at least the following 2 variables :\n- observation.unit (or year and site)\n- numeric or integer metric\n" |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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58 check_file(obs,err_msg_data1,vars_data1,2) |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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59 |
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"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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60 vars_data2 <- c(listFact,listRand) |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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61 err_msg_data2<-"The input unitobs dataset doesn't have the right format. It needs to have at least the following 2 variables :\n- observation.unit (or year and site)\n- factors used in GLM (habitat, year and/or site)\n" |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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62 check_file(tabUnitobs,err_msg_data2,vars_data2[vars_data2 != "None"],2) |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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63 |
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64 #################################################################################################### |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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65 ########## Computing Generalized Linear Model ## Function : modeleLineaireWP2.unitobs.f ############ |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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66 #################################################################################################### |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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67 |
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68 modeleLineaireWP2.unitobs.f <- function(metrique, listFact, listRand, FactAna, Distrib, log=FALSE, tabMetrics, tableMetrique, tabUnitobs, unitobs="observation.unit", nbName="number") |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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69 { |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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70 ## Purpose: Monitoring steps for GLM on unitobs |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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71 ## ---------------------------------------------------------------------- |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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72 ## Arguments: metrique : selected metric |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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73 ## listFact : Factors for GLM |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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74 ## listRand : Random factors for GLM |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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75 ## factAna : Separation factor for GLMs |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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76 ## Distrib : selected distribution for model |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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77 ## log : log transformation on data ? boolean |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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78 ## tabMetrics : data table metrics |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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79 ## tableMetrique : data table's name |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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80 ## tabUnitobs : data table unitobs |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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81 ## ---------------------------------------------------------------------- |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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82 ## Author: Yves Reecht, Date: 18 août 2010, 15:59 modified by Coline ROYAUX 04 june 2020 |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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83 |
f0dc3958e65d
"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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84 tmpData <- tabMetrics |
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85 |
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86 if (listRand[1] != "None") |
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87 { |
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88 if (all(is.element(listFact,listRand)) || listFact[1] == "None") |
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89 { |
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90 RespFact <- paste("(1|",paste(listRand,collapse=") + (1|"),")") |
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91 listF <- NULL |
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92 listFact <- listRand |
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93 }else{ |
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94 listF <- listFact[!is.element(listFact,listRand)] |
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95 RespFact <- paste(paste(listF, collapse=" + ")," + (1|",paste(listRand,collapse=") + (1|"),")") |
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96 listFact <- c(listF,listRand) |
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97 } |
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98 }else{ |
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99 listF <- listFact |
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100 RespFact <- paste(listFact, collapse=" + ") |
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101 } |
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102 |
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103 ##Creating model's expression : |
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104 |
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105 #if (log == FALSE) { |
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106 exprML <- eval(parse(text=paste(metrique, "~", RespFact))) |
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107 #}else{ |
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108 # exprML <- eval(parse(text=paste("log(",metrique,")", "~", RespFact))) |
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109 #} |
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110 |
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111 ##Creating analysis table : |
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112 |
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113 listFactTab <- c(listFact, FactAna) |
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114 listFactTab <- listFactTab[listFactTab != "None"] |
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115 |
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116 if (all(is.na(match(tmpData[,unitobs],tabUnitobs[,unitobs])))) {stop("Observation units doesn't match in the two input tables")} |
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117 |
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118 if(! is.element("species.code",colnames(tmpData))) |
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119 { |
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120 col <- c(unitobs,metrique) |
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121 tmpData <- cbind(tmpData[,col], tabUnitobs[match(tmpData[,unitobs],tabUnitobs[,unitobs]),listFactTab]) |
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122 colnames(tmpData) <- c(col,listFactTab) |
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123 |
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124 for (i in listFactTab) { |
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125 switch(i, |
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126 tmpData[,i] <- as.factor(tmpData[,i])) |
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127 } |
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128 }else{ |
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129 stop("Warning : wrong data frame, data frame should be aggregated by observation unit (year and site)") |
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130 } |
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131 |
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132 ## Suppress unsed 'levels' : |
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133 tmpData <- dropLevels.f(tmpData) |
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134 |
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135 ## Automatic choice of distribution if none is selected by user : |
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136 if (Distrib == "None") |
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137 { |
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138 switch(class(tmpData[,metrique]), |
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139 "integer"={loiChoisie <- "poisson"}, |
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140 "numeric"={loiChoisie <- "gaussian"}, |
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141 stop("Selected metric class doesn't fit, you should select an integer or a numeric variable")) |
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142 }else{ |
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143 loiChoisie <- Distrib |
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144 } |
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145 |
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146 |
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147 ## Compute Model(s) : |
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148 |
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149 if (FactAna != "None" && nlevels(tmpData[,FactAna]) > 1) |
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150 { |
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151 Anacut <- levels(tmpData[,FactAna]) |
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152 }else{ |
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153 Anacut <- NULL |
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154 } |
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155 |
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156 ##Create results table : |
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157 lev <- unlist(lapply(listF,FUN=function(x){levels(tmpData[,x])})) |
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158 |
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159 if (listRand[1] != "None") ## if random effects |
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160 { |
f0dc3958e65d
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161 TabSum <- data.frame(analysis=c("global", Anacut),AIC=NA,BIC=NA,logLik=NA, deviance=NA,df.resid=NA) |
f0dc3958e65d
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162 colrand <- unlist(lapply(listRand, |
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163 FUN=function(x){lapply(c("Std.Dev","NbObservation","NbLevels"), |
f0dc3958e65d
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164 FUN=function(y){paste(x,y,collapse = ":") |
f0dc3958e65d
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165 }) |
f0dc3958e65d
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166 })) |
f0dc3958e65d
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167 TabSum[,colrand] <- NA |
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168 |
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169 if (! is.null(lev)) ## if fixed effects + random effects |
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170 { |
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171 colcoef <- unlist(lapply(c("(Intercept)",lev), |
f0dc3958e65d
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172 FUN=function(x){lapply(c("Estimate","Std.Err","Zvalue","Pvalue","signif"), |
f0dc3958e65d
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173 FUN=function(y){paste(x,y,collapse = ":") |
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174 }) |
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175 })) |
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176 }else{ ## if no fixed effects |
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177 colcoef <- NULL |
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178 } |
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179 |
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180 }else{ ## if no random effects |
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181 TabSum <- data.frame(analysis=c("global", Anacut),AIC=NA,Resid.deviance=NA,df.resid=NA,Null.deviance=NA,df.null=NA) |
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182 |
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183 switch(loiChoisie, |
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184 "gaussian"={colcoef <- unlist(lapply(c("(Intercept)",lev), |
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185 FUN=function(x){lapply(c("Estimate","Std.Err","Tvalue","Pvalue","signif"), |
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186 FUN=function(y){paste(x,y,collapse = ":") |
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187 }) |
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188 }))}, |
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189 "quasipoisson"={colcoef <- unlist(lapply(c("(Intercept)",lev), |
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190 FUN=function(x){lapply(c("Estimate","Std.Err","Tvalue","Pvalue","signif"), |
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191 FUN=function(y){paste(x,y,collapse = ":") |
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192 }) |
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193 }))}, |
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194 colcoef <- unlist(lapply(c("(Intercept)",lev), |
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195 FUN=function(x){lapply(c("Estimate","Std.Err","Zvalue","Pvalue","signif"), |
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196 FUN=function(y){paste(x,y,collapse = ":") |
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197 }) |
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198 }))) |
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199 |
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200 } |
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201 |
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202 TabSum[,colcoef] <- NA |
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203 |
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204 ### creating rate table |
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205 TabRate <- data.frame(analysis=c("global", Anacut), complete_plan=NA, balanced_plan=NA, NA_proportion_OK=NA, no_residual_dispersion=NA, uniform_residuals=NA, outliers_proportion_OK=NA, no_zero_inflation=NA, observation_factor_ratio_OK=NA, enough_levels_random_effect=NA, rate=NA) |
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206 |
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207 for (cut in Anacut) |
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208 { |
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209 cutData <- tmpData[grep(cut,tmpData[,FactAna]),] |
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210 cutData <- dropLevels.f(cutData) |
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211 |
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212 res <-"" |
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213 |
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214 if (listRand[1] != "None") |
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215 { |
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216 res <- tryCatch(glmmTMB(exprML,family=loiChoisie, data=cutData), error=function(e){}) |
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217 }else{ |
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218 res <- tryCatch(glm(exprML,data=cutData,family=loiChoisie), error=function(e){}) |
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219 } |
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220 |
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221 ## Write results : |
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222 if (! is.null(res)) |
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223 { |
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224 TabSum <- sortiesLM.f(objLM=res, TabSum=TabSum, metrique=metrique, |
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225 factAna=factAna, cut=cut, colAna="analysis", lev=lev, #modSel=iFactGraphSel, listFactSel=listFactSel, |
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226 listFact=listFact, |
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227 Data=cutData, #Log=Log, |
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228 type=ifelse(tableMetrique == "unitSpSz" && factAna != "size.class", |
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229 "CL_unitobs", |
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230 "unitobs")) |
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231 |
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232 TabRate[TabRate[,"analysis"]==cut,c(2:11)] <- noteGLM.f(data=cutData, objLM=res, metric=metrique, listFact=listFact, details=TRUE) |
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233 |
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234 }else{ |
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235 cat("\nCannot compute GLM for level",cut,"Check if one or more factor(s) have only one level, or try with another distribution for the model in advanced settings \n\n") |
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236 } |
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237 |
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238 } |
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239 |
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240 ## Global analysis : |
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241 |
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242 if (listRand[1] != "None") |
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243 { |
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244 resG <- glmmTMB(exprML,family=loiChoisie, data=tmpData) |
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245 }else{ |
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246 resG <- glm(exprML,data=tmpData,family=loiChoisie) |
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247 } |
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248 |
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249 ## write results : |
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250 TabSum <- sortiesLM.f(objLM=resG, TabSum=TabSum, metrique=metrique, |
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251 factAna=factAna, cut="global", colAna="analysis", lev=lev, #modSel=iFactGraphSel, listFactSel=listFactSel, |
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252 listFact=listFact, |
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253 Data=tmpData, #Log=Log, |
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254 type=ifelse(tableMetrique == "unitSpSz" && factAna != "size.class", |
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255 "CL_unitobs", |
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256 "unitobs")) |
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257 |
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258 TabRate[TabRate[,"analysis"]=="global",c(2:11)] <- noteGLM.f(data=tmpData, objLM=resG, metric=metrique, listFact=listFact, details=TRUE) |
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"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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259 noteGLMs.f(tabRate=TabRate,exprML=exprML,objLM=resG, file_out=TRUE) |
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260 ## simple statistics and infos : |
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261 filename <- "GLMSummaryFull.txt" |
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262 |
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263 ## Save data on model : |
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264 |
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265 infoStats.f(filename=filename, Data=tmpData, agregLevel=aggreg, type="stat", |
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266 metrique=metrique, factGraph=factAna, #factGraphSel=modSel, |
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267 listFact=listFact)#, listFactSel=listFactSel) |
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268 |
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269 return(TabSum) |
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270 |
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271 } |
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272 |
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273 ################# Analysis |
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274 |
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275 Tab <- modeleLineaireWP2.unitobs.f(metrique=metric, listFact=listFact, listRand=listRand, FactAna=FactAna, Distrib=Distrib, log=log, tabMetrics=obs, tableMetrique=aggreg, tabUnitobs=tabUnitobs, nbName="number") |
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276 |
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277 write.table(Tab,"GLMSummary.tabular", row.names=FALSE, sep="\t", dec=".",fileEncoding="UTF-8") |