| Next changeset 1:af4987066235 (2020-05-11) |
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Commit message:
"planemo upload for repository https://github.com/Alanamosse/Galaxy-E/tree/stoctool/tools/stoc commit f82f897ab22464de40c878e17616333855814e25" |
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ExemakeTableAnalyseGalaxy.r FunctTrendSTOCGalaxy.r makeTableAnalyse.xml stoceps_macros.xml test-data/Datatransformedforfiltering_trendanalysis.tabular test-data/data_FrenchBBS_squarre_dataSTOCallSp_France_trend_2001_2017_ALAARV-PARCAE_2001_2018.tabular |
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| diff -r 000000000000 -r 22a784d2b0e0 ExemakeTableAnalyseGalaxy.r --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/ExemakeTableAnalyseGalaxy.r Thu Apr 02 03:33:29 2020 -0400 |
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| @@ -0,0 +1,42 @@ +#!/usr/bin/env Rscript + +################################################################################################################## +################ Data transformation for population evolution trend analyses function:makeTableAnalyse ######### +################################################################################################################## +########### + +library(data.table) +#delcaration des arguments et variables/ declaring some variables and load arguments + +args = commandArgs(trailingOnly=TRUE) ##### par defaut prends les arguments comme du texte !!!! / default behaviour is to take the arguments as text !!! + +if (length(args)==0) { + stop("At least one argument must be supplied, an input dataset file (.tabular).", call.=FALSE) #si pas d'arguments -> affiche erreur et quitte / if no args -> error and exit1 + +} else { + ImportduSTOC<-args[1] ###### Nom du fichier importé depuis la base de données STOCeps avec son extension / file name imported from the STOCeps database with the file type ".filetype" + source(args[2])### chargement des fonctions / load the functions + +} + +##### Le tableau de données doit posséder 4 variables en colonne: abondance ("abond"), les carrés ou sont réalisés les observatiosn ("carre"), la ou les années des observations ("annee"), et le code de ou des espèces ("espece") +##### Data must be a dataframe with 4 variables in column: abundance ("abond"), plots where observation where made ("carre"), year(s) of the different sampling ("annee"), and the species code ("espece") + + +#Import des données / Import data +data<- fread(ImportduSTOC,sep="\t",dec=".",header=TRUE,encoding="UTF-8") # +vars_data<-c("carre","annee","espece","abond") +err_msg_data<-"The input dataset filtered doesn't have the right format. It need to have the following 4 variables :\n- carre\n- annee\n- espece\n- abond\n" +check_file(data,err_msg_data,vars_data,4) + + + + +######### +#Do your analysis +tableAnalyse<-makeTableAnalyse(data) #la fonction a un 'return' il faut donc stocker le resultat dans une nouvelle variable +#save the data in a output file in a tabular format +filename <- "Datatransformedforfiltering_trendanalysis.tabular" +write.table(tableAnalyse, filename,row.names=FALSE,sep="\t",dec=".",fileEncoding="UTF-8") + +cat(paste("\nWrite table with data transformed for filtering. \n--> \"",filename,"\"\n",sep="")) |
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| diff -r 000000000000 -r 22a784d2b0e0 FunctTrendSTOCGalaxy.r --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/FunctTrendSTOCGalaxy.r Thu Apr 02 03:33:29 2020 -0400 |
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| b'@@ -0,0 +1,776 @@\n+#!/usr/bin/env Rscript\n+\n+\n+##################################################################################################################################\n+############## FUNCTION TO CALCULATE AND PLOT EVOLUTION OF SPECIES POPULATION function:main.glm ##############################\n+##################################################################################################################################\n+\n+#### Based on Romain Lorrilli\xc3\xa8re R script\n+#### Modified by Alan Amosse and Benjamin Yguel for integrating within Galaxy-E\n+\n+##### workes with the R version 3.5.1 (2018-07-02)\n+##### Package used with the version:\n+#suppressMessages(library(lme4)) version 1.1.18.1\n+#suppressMessages(library(ggplot2)) version 3.0.0\n+#suppressMessages(library(speedglm)) version 0.3.2\n+#suppressMessages(library(arm)) version 1.10.1\n+#suppressMessages(library(reshape)) version 0.8.8\n+#suppressMessages(library(data.table)) version 1.12.0\n+#suppressMessages(library(reshape2)) version 1.4.3\n+\n+\n+\n+######################################### debut de la fonction makeTableAnalyse / stard of the function makeTableAnalyse\n+## mise en colonne des especes et rajout de zero mais sur la base des carr\xc3\xa9s selectionn\xc3\xa9 sans l\'import / Species are placed in separated columns and addition of zero on plots where at least one selected species is present \n+\n+makeTableAnalyse <- function(data) {\n+ tab <- reshape(data\n+ ,v.names="abond"\n+ ,idvar=c("carre","annee") \n+ ,timevar="espece"\n+ ,direction="wide")\n+ tab[is.na(tab)] <- 0 ###### remplace les na par des 0 / replace NAs by 0 \n+\n+ colnames(tab) <- sub("abond.","",colnames(tab))### remplace le premier pattern "abond." par le second "" / replace the column names "abond." by ""\n+ return(tab)\n+}\n+\n+######################################### fin de la fonction makeTableAnalyse / end of the function makeTableAnalyse\n+\n+\n+\n+\n+\n+############################################# les fonctions qui filtrent les donn\xc3\xa9es pas suffisantes pour analyses fiables / The filtering functions removing species with not enough data to perform accurate analyses\n+\n+filter_absent_species<-function(tab){\n+##################### Filtre les esp\xc3\xa8ces jamais pr\xc3\xa9sentes (abondance=0) / Filter of species with 0 abundance\n+################################################################################# PARTIE POTENTIELLEMENT ISOLABLE ET INSERABLE AVANT LA BOUCLE = permet de gagner du temps sur la boucle car supprime sps pas vu, donc pas repris par la boucle\n+ \n+ ## Fait la somme des abondances totales par esp\xc3\xa8ce / calculate the sum of all abundance per species\n+ if(ncol(tab)==3) {\n+\ttabSum <- sum(tab[,3])## cas d\'une seule especes (probl\xc3\xa8me de format et manip un peu differente) / when selecting only one species, use a different method\n+\tnames(tabSum) <- colnames(tab)[3]\n+ } else { ## cas de plusieurs esp\xc3\xa8ce/ when selecting more than one species\n+ tabSum <- colSums(tab[,-(1:2)])\n+ }\n+ ## colNull= espece(s) toujours absente /species with 0 total abundance\n+ colNull <- names(which(tabSum==0))\n+ ## colconserve= espece(s) au moins presente 1 fois/ species at least with 1 presence\n+ colConserve <- names(which(tabSum>0))\n+ ## Affichage des esp\xc3\xa8ces rejetees / show species eliminated for the analyses\n+ if(length(colNull)>0){\n+ cat("\\n",length(colNull)," Species removed from the analysis, abundance is always 0.\\n\\n",sep="") #Esp\xc3\xa8ces enlev\xc3\xa9es de l\'analyse car abondance toujours \xc3\xa9gale a 0\\n\\n",sep="")\n+ #tabNull <- data.frame(Code_espece = colNull, nom_espece = tabsp[colNull,"nom"])\n+ #cat("\\n\\n",sep="")\n+ tab <- tab[,c("carre","annee",colConserve)]\n+ }\n+################################################################################ FIN DE LA PARTIE ISOLABLE\n+ return(tab) \n+}\n+\n+\n+\n+\n+###################### Filtre les especes trop ra'..b' ggplot2 / plots with ggplot2\n+ titre <- paste("Variation de l\'indicateur groupe de specialisation",sep="")\n+\n+ vecCouleur <- setNames(groupeCouleur,groupeNom)\n+ #browser()\n+ p <- ggplot(data = da, mapping = aes(x = annee, y = abondance_relative, colour=groupe,fill=groupe))\n+ p <- p + geom_hline(aes(yintercept = 1), colour="white", alpha=1,size=1.2) \n+ if(ICfigureGroupeSp)\n+ p <- p + geom_ribbon(mapping=aes(ymin=IC_inferieur,ymax=IC_superieur),linetype=2,alpha=.1,size=0.1) \n+ p <- p + geom_line(size=1.5)\n+ p <- p + ylab("") + xlab("Annee")+ ggtitle(titre) \n+ if(!is.null(groupeNom)) p <- p + scale_colour_manual(values=vecCouleur, name = "" )+\n+ scale_x_continuous(breaks=unique(da$annee))\n+ if(!is.null(groupeNom)) p <- p + scale_fill_manual(values=vecCouleur, name="")\n+ p <- p + theme(panel.grid.minor=element_blank(), panel.grid.major.y=element_blank()) \n+ ggsave(nameFileSpepng, p,width=17,height=10,units="cm")\n+\n+ # cat(" <==",nameFileSpepng,"\\n")\n+ \n+ ## calul pour chaque groupe une pente de regression d\'evolution des abondances sur la periode \xc3\xa9tudi\xc3\xa9e / calculating for each group the regression slope for the abundance evolution on the studied period\n+ vecSpe <- unique(da$groupe)\n+ datasum <- data.frame(groupe=NULL,tendance=NULL,pourcentage_variation=NULL)\n+ for(spe in 1:4){\n+ # print(spe)\n+ subtab <- subset(da,groupe==vecSpe[spe])\n+ if(nrow(subtab)>1) {\n+ sumlm <- summary(lm(abondance_relative~annee,data=subtab)) ##### recup\xc3\xa8re les resultats du mod\xc3\xa8le lin\xc3\xa9aire / retrieve the results of the linear model\n+ subdatasum <- data.frame(groupe=vecSpe[spe],\n+ tendance=round(sumlm$coefficients[2,1],3),\n+ pourcentage_variation=round(sumlm$coefficients[2,1]*(nrow(subtab)-1)*100,3)) #### assemble les resultats pour en faire une sortie / bring together the results for an output file\n+ datasum <- rbind(datasum,subdatasum)\n+ \n+ }\n+ \n+ }\n+ datasum <- merge(datasum,tIncert,by="groupe") #### \n+ datasum <- data.frame(id,datasum)\n+ #datasum$cat_tendance_EBCC <- affectCatEBCC(trend,pVal,ICinf,ICsup\n+ namefilesum <- paste("Output/",id,"/tendancesGlobalesGroupes_",id,\n+ ".tabular",sep="" )\n+ write.table(datasum,file=namefilesum,row.names=FALSE,quote=FALSE,sep="\\t",dec=".",fileEncoding="UTF-8")\n+ cat("-->",namefilesum,"\\n")\n+}\n+\n+################################################################################################################## fin de la fonction analyseGroupe / end of the function analyseGroupe\n+\n+\n+\n+\n+\n+\n+\n+################################################################################################################### debut de la fonction check_file / start of the function check_file\n+# Fonction pour verifier les donn\xc3\xa9es d\'entr\xc3\xa9e / General function to check integrity of input file. Will check numbers and contents of variables(colnames). \n+#return an error message and exit if mismatch detected\n+#Faut rentrer le nom du jeu de donn\xc3\xa9es, le nbre et le nom des variables / Enter dataset name, expected number and names of variables. + an exit error message to guide user.\n+\n+check_file<-function(dataset,err_msg,vars,nb_vars){\n+ if(ncol(dataset)!=nb_vars){ #Verifiction de la pr\xc3\xa9sence du bon nb de colonnes, si c\'est pas le cas= message d\'erreur / checking for right number of columns in the file if not = error message\n+ cat("\\nerr nb var\\n") \n+ stop(err_msg, call.=FALSE)\n+ }\n+\n+ for(i in vars){\n+ if(!(i %in% names(dataset))){\n+ stop(err_msg,call.=FALSE)\n+ }\n+ }\n+}\n+\n+#####################################################################################################################\n+\n' |
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| diff -r 000000000000 -r 22a784d2b0e0 makeTableAnalyse.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/makeTableAnalyse.xml Thu Apr 02 03:33:29 2020 -0400 |
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| @@ -0,0 +1,73 @@ +<tool id="stoceps_maketablecarrer" name="Preprocess population data" version="@VERSION@"> + <description>for evolution trend analyzes</description> + <macros> + <import>stoceps_macros.xml</import> + </macros> + <expand macro="reshape_requirements"/> + <command detect_errors="exit_code"><![CDATA[ + Rscript + '$__tool_directory__/ExemakeTableAnalyseGalaxy.r' + '$input' + '$__tool_directory__/FunctTrendSTOCGalaxy.r' + '$output' + ]]> + </command> + <inputs> + <param name="input" type="data" format="tabular" label="Input file" help="Population count file, with location, date, species and abundance."/> + </inputs> + <outputs> + <data name="output" from_work_dir="Datatransformedforfiltering_trendanalysis.tabular" format="tabular"/> + </outputs> + <tests> + <test> + <param name="input" value="data_FrenchBBS_squarre_dataSTOCallSp_France_trend_2001_2017_ALAARV-PARCAE_2001_2018.tabular"/> + <output name="output" file="Datatransformedforfiltering_trendanalysis.tabular"/> + </test> + </tests> + <help><![CDATA[ +=============================== +STOC preprocess population data +=============================== + +**What it does** + +Reshape the data for the next steps of STOC analyzes by adding zero count to sites that are in the dataset, for species having no count data for those sites. + + +| + +**Input description** + +A tabular file with abundance per year, per site and per species with no or few zero abundance. + +The data file can be extracted from the STOC database on demand : romain.lorrilliere@mnhn.fr + +The table needs the following structure (at least these 4 fours columns) : + ++-----------+---------+----------+---------+ +| carre | annee | espece | abond | ++===========+=========+==========+=========+ +| carreId1 | 2019 | especeId | 12 | ++-----------+---------+----------+---------+ +| ... | ... | ... | ... | ++-----------+---------+----------+---------+ + +| + +**Output** + +A tabular file transformed, with one column indicating the year, one indicating the site, and one column for each species abundance. + +This file is ready for the next filtering steps. + +| + +**Source** + +UnPublished script available at http://www.vigienature.fr/sites/vigienature/files/atoms/files/analysestoceps_0.zip + +First version written by romain.lorrilliere@mnhn.fr + ]]></help> + + <expand macro="stoceps_bibref" /> +</tool> |
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| diff -r 000000000000 -r 22a784d2b0e0 stoceps_macros.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/stoceps_macros.xml Thu Apr 02 03:33:29 2020 -0400 |
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| @@ -0,0 +1,73 @@ +<macros> + <token name="@VERSION@">0.0.1</token> + <xml name="reshape_requirements"> + <requirements> + <requirement type="package" version="0.8.8">r-reshape</requirement> + <requirement type="package" version="1.12.0">r-data.table</requirement> + </requirements> + </xml> + <xml name="reshape2_requirements"> + <requirements> + <requirement type="package" version="1.4.3">r-reshape2</requirement> + </requirements> + </xml> + <xml name="mainglm_requirements"> + <requirements> + <requirement type="package" version="3.0.0">r-ggplot2</requirement> + <requirement type="package" version="0.3_2">r-speedglm</requirement> + <requirement type="package" version="1.10_1">r-arm</requirement> + <requirement type="package" version="1.12.0">r-data.table</requirement> + <requirement type="package" version="1.4.3">r-reshape2</requirement> + </requirements> + </xml> + <xml name="temp_indic_requirements"> + <requirements> + <requirement type="package" version="1.3_15">r-rodbc</requirement> + <requirement type="package" version="0.8.8">r-reshape</requirement> + <requirement type="package" version="1.12.0">r-data.table</requirement> + <requirement type="package" version="1.4_3">r-rgdal</requirement> + <requirement type="package" version="1.7.4">r-lubridate</requirement> + <requirement type="package" version="4.6_2">r-doby</requirement> + <requirement type="package" version="1.10_1">r-arm</requirement> + <requirement type="package" version="3.1.0">r-ggplot2</requirement> + <requirement type="package" version="1.0.0">r-scales</requirement> + <requirement type="package" version="1.8_24">r-mgcv</requirement> + <requirement type="package" version="1.8.4">r-plyr</requirement> + <requirement type="package" version="0.3_2">r-speedglm</requirement> + <requirement type="package" version="3.1_0">r-lmertest</requirement> + <requirement type="package" version="0.2.3">r-glmmtmb</requirement> + </requirements> + </xml> + <xml name="stoceps_input_filtered"> + <param name="input" type="data" format="tabular" label="Stoc filtered input" help="Input Stoc count file, shaped and filtered with the 'preprocess population data' and 'filter species' tools." /> + </xml> + <xml name="stoceps_advanced_params_select"> + <param name="advanced" type="select" label="Specify advanced parameters"> + <option value="simple" selected="true">No, use program defaults.</option> + <option value="advanced">Yes, see full parameter list.</option> + </param> + <when value="simple"> + </when> + </xml> + <xml name="stoceps_compute_ic"> + <param name="compute_ic" type="boolean" truevalue="TRUE" falsevalue="FALSE" checked="yes" label="Compute confidence intervals"/> + </xml> + <xml name="stoceps_filter_glmmtmb"> + <filter> settings['advanced'] == 'advanced'</filter> + <filter> settings['method'] == 'glmmtmb'</filter> + </xml> + <xml name="stoceps_filter_gam"> + <filter> settings['method'] == 'gam'</filter> + </xml> + <xml name="stoceps_bibref"> + <citations> + <citation type="bibtex"> + @unpublished{stocepsromain, + title={Vigie-Nature STOC unpublished scripts}, + author={Lorrilliere, R}, + url={http://www.vigienature.fr/sites/vigienature/files/atoms/files/analysestoceps_0.zip} + } + </citation> + </citations> + </xml> +</macros> |
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| diff -r 000000000000 -r 22a784d2b0e0 test-data/Datatransformedforfiltering_trendanalysis.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/Datatransformedforfiltering_trendanalysis.tabular Thu Apr 02 03:33:29 2020 -0400 |
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| b'@@ -0,0 +1,426 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de"\t2018\t3\t7\n+"Le Mas"\t2018\t0\t7\n' |
| b |
| diff -r 000000000000 -r 22a784d2b0e0 test-data/data_FrenchBBS_squarre_dataSTOCallSp_France_trend_2001_2017_ALAARV-PARCAE_2001_2018.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/data_FrenchBBS_squarre_dataSTOCallSp_France_trend_2001_2017_ALAARV-PARCAE_2001_2018.tabular Thu Apr 02 03:33:29 2020 -0400 |
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