Mercurial > repos > ecology > ecoregion_clara_cluster

annotate cluster_ceamarc.R @ 2:a7269e5eed27 draft default tip

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planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/Ecoregionalization_workflow commit ced658540f05bb07e1e687af30a3fa4ea8e4803c
author ecology
date Wed, 28 May 2025 10:11:06 +0000
parents a23e4fded433
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88964fcccfef planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/Ecoregionalization_workflow commit e03df85746a3b61a382a5ee7e3357a8bf42a5097
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1 ##13/04/2023
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2 ##Seguineau Pauline
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3 ### Clustering with Clara algorithm
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5 #load library
88964fcccfef planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/Ecoregionalization_workflow commit e03df85746a3b61a382a5ee7e3357a8bf42a5097
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6 library(cluster)
88964fcccfef planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/Ecoregionalization_workflow commit e03df85746a3b61a382a5ee7e3357a8bf42a5097
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7 library(dplyr)
88964fcccfef planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/Ecoregionalization_workflow commit e03df85746a3b61a382a5ee7e3357a8bf42a5097
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8 library(tidyverse)
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10 #load arguments
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11 args = commandArgs(trailingOnly=TRUE)
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12 if (length(args)==0)
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13 {
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14 stop("This tool needs at least one argument")
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15 }else{
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16 data <- args[1]
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17 enviro <- args[2]
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18 data.bio <- args[3]
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19 k <- as.numeric(args[4])
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20 metric <- args[5]
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21 sample <- as.numeric(args[6])
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22 }
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24 #load data
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25 env.data <- read.table(enviro, header=TRUE, sep="\t",dec = ".", na.strings = "-9999")
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26 data.bio <- read.table(data.bio, header=TRUE, sep="\t")
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27 test3 <- read.table(data, header = TRUE, sep="\t")
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29 ######################################################################################################
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30 #Make clustering
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32 k <- k #number of clusters
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33 test5 <- clara(test3, k, metric = metric, samples = sample, sampsize = min(nrow(test3), (nrow(data.bio)/nrow(test3))+2*k))
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35 #######################################################################################################
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36 #save results
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38 png("sih.png")
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39 plot(silhouette(test5))
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40 dev.off()
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42 clus <- cbind(data.bio[1:nrow(test3), 1:2],test5$clustering)
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43 names(clus) <- c("lat", "long", "cluster")
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44 clus <- cbind(clus,test3,env.data[,3:ncol(env.data)])
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46 write.table(clus[1:3], file = "points_clus.tsv", quote = FALSE, sep="\t", row.names = FALSE)
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47 write.table(clus, file = "clus.tsv", quote = FALSE, sep="\t", row.names = FALSE)
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