diff --git a/Tesselation_de_voronoi_modif.ipynb b/Tesselation_de_voronoi_modif.ipynb
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+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "d5fbe906-9395-4c84-ac8d-5a2d774bf39b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#author: \"Clément Frainay\"\n",
+ "#output: html_document\n",
+ "#knitr::opts_chunk$set(echo = TRUE)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "8c08fd21-ec30-4f74-83e8-768ba4540915",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "Warning message:\n",
+ "\"package 'igraph' was built under R version 3.6.3\"\n",
+ "Attaching package: 'igraph'\n",
+ "\n",
+ "The following objects are masked from 'package:stats':\n",
+ "\n",
+ " decompose, spectrum\n",
+ "\n",
+ "The following object is masked from 'package:base':\n",
+ "\n",
+ " union\n",
+ "\n",
+ "Warning message:\n",
+ "\"package 'openxlsx' was built under R version 3.6.3\""
+ ]
+ }
+ ],
+ "source": [
+ "library(igraph)\n",
+ "library(scales)\n",
+ "library(openxlsx)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "449d0f84-38f5-4b22-adff-fad36d012f10",
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "ERROR",
+ "evalue": "Error in match.arg(arg = arg, choices = choices, several.ok = several.ok): 'arg' should be one of \"edgelist\", \"pajek\", \"ncol\", \"lgl\", \"graphml\", \"dimacs\", \"graphdb\", \"gml\", \"dl\"\n",
+ "output_type": "error",
+ "traceback": [
+ "Error in match.arg(arg = arg, choices = choices, several.ok = several.ok): 'arg' should be one of \"edgelist\", \"pajek\", \"ncol\", \"lgl\", \"graphml\", \"dimacs\", \"graphdb\", \"gml\", \"dl\"\nTraceback:\n",
+ "1. read_graph(\"C:/Users/mumec/Desktop/Mini_codes/CompoundNet_KEGG2SBML\", \n . format = \"txt\")",
+ "2. igraph.match.arg(format)",
+ "3. match.arg(arg = arg, choices = choices, several.ok = several.ok)",
+ "4. stop(gettextf(\"'arg' should be one of %s\", paste(dQuote(choices), \n . collapse = \", \")), domain = NA)"
+ ]
+ }
+ ],
+ "source": [
+ "#import networks in gml ( graph format)\n",
+ "g <- read_graph(\"C:/Users/mumec/Desktop/Mini_codes/CompoundNet_KEGG2SBML\",format = \"gml\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 136,
+ "id": "a975c1b3-2cc6-47d8-a744-79d5165779ba",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "corresp <- read.csv(\"C:/Users/mumec/Desktop/Mini_codes/100_metabolites_KEGG_ID.csv\", sep=\";\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 137,
+ "id": "704eb832-7948-43d0-8a4e-5e9ca49de549",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "Name_cor <- as.character(corresp$ NAME)\n",
+ "ID_cor <- as.character(corresp$ KEGG)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 138,
+ "id": "ccaf5941-4624-428b-8a53-beb73af67f93",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#extract main connected component (otherwise, inf in the matrix)\n",
+ "g <- decompose(g, mode=\"weak\", max.comps = 1)[[1]]\n",
+ "m <- distances(g) # Distance matrix without ID\n",
+ "rownames(m) <- V(g)$label # recup of name\n",
+ "colnames(m) <- V(g)$label"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 139,
+ "id": "f48cf29d-e94f-4ba0-8b71-d54c21bf7e65",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "## Center-Nodes computation\n",
+ "grid_size = c(10,10)# put the dimension of the grid\n",
+ "nclusters = grid_size[1]*grid_size[2]\n",
+ "centers <- data.frame(ID_cor)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 140,
+ "id": "2e5d1af7-b4a9-4897-8ec1-26d8663cdc3b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "## Neighborhood assignments\n",
+ "submed <- m[rownames(m) %in% centers[,1],]\n",
+ "minDist <- apply(submed,2, min)\n",
+ "minDistMatrix <- matrix(rep(minDist, each = nrow(submed)), nrow = nrow(submed), ncol = ncol(submed))\n",
+ "assignMatrix <- (submed==minDistMatrix)\n",
+ "assign <- apply(assignMatrix, 1, function(row) colnames(submed)[row])\n",
+ "\n",
+ " \n",
+ "vornoiBridge<-colnames(assignMatrix)[colSums(assignMatrix) > 1]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 141,
+ "id": "cab448f4-8181-4fcd-a030-787b277e40f5",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<strong>png:</strong> 2"
+ ],
+ "text/latex": [
+ "\\textbf{png:} 2"
+ ],
+ "text/markdown": [
+ "**png:** 2"
+ ],
+ "text/plain": [
+ "png \n",
+ " 2 "
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "## Subgraph building\n",
+ "Name_of_out_file=\"tesselation_test_modif\"\n",
+ "df <- data.frame(matrix(ncol = 5, nrow = length(assign)))\n",
+ "colnames(df) <- c(\"center\", \"nodes\", \"edges\", \"outEdges\",\"nbCC\")\n",
+ "\n",
+ "pdf(file=paste0(Name_of_out_file,nclusters,\".pdf\"),width=50, height=50)\n",
+ "#par(mfrow=c(grid_size[1],grid_size[2]), cex.main = 4)\n",
+ "par(mfrow=c(7,7), cex.main = 4)\n",
+ "\n",
+ "for(i in 1:length(assign)){\n",
+ " medoidId = names(assign[i]) # on récupére l'id e question ici on peux modifier l'ID par son nom usuel\n",
+ " #get neighborhood vertices\n",
+ " clusterVertex = V(g)[V(g)$label%in%assign[[i]]]\n",
+ " indice <- which(ID_cor == medoidId)\n",
+ " Name_ID = Name_cor[indice][1]\n",
+ " #build induced subgraph\n",
+ " clusterGraph = induced_subgraph(g,clusterVertex,impl = \"auto\")\n",
+ " #get edges that goes outside the cluster\n",
+ " incidentEdges <- incident_edges(g, clusterVertex, mode = \"all\")\n",
+ " incidentEdges <- setdiff(incidentEdges,E(clusterGraph))\n",
+ " \n",
+ " #cluser data\n",
+ " df$center[i] = Name_ID # dzdzdzdazdazdazdazdazdazdazd\n",
+ " df$nodes[i] = length(V(clusterGraph)) # number of graph vertices\n",
+ " df$edges[i] = length(E(clusterGraph)) # Number of graph edges \n",
+ " df$outEdges[i] = length(incidentEdges) # Number of out edges \n",
+ " df$nbCC[i] = count_components(clusterGraph, mode = \"weak\") # Counting related components\n",
+ " df$diameter[i]= diameter(clusterGraph)\n",
+ "\n",
+ " #clusters visualization\n",
+ " V(clusterGraph)$size <- 6\n",
+ " V(clusterGraph)$shape <- \"circle\"\n",
+ " V(clusterGraph)$color <- \"aquamarine\"\n",
+ " V(clusterGraph)[V(clusterGraph)$label == medoidId]$size <- 15 \n",
+ " V(clusterGraph)[V(clusterGraph)$label == medoidId]$color <- \"khaki1\"\n",
+ " V(clusterGraph)[V(clusterGraph)$label %in% vornoiBridge]$shape <- \"square\"\n",
+ " V(clusterGraph)[V(clusterGraph)$label %in% vornoiBridge]$size <- 4\n",
+ " V(clusterGraph)[V(clusterGraph)$label %in% vornoiBridge]$color <- \"mediumorchid1\"\n",
+ " plot(clusterGraph,vertex.label=NA, main =paste(Name_ID,collapse = '\\n'))\n",
+ " box(col = \"black\",lwd = 7)\n",
+ "}\n",
+ "dev.off()\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 142,
+ "id": "b6c838d4-3bdf-4a2c-a987-f6e313e8d7a6",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " center nodes edges outEdges nbCC diameter\n",
+ "1 bilirubin 244 945 243 1 13\n",
+ "2 sphinganine 176 695 173 1 13\n",
+ "3 pipecolinic acid 31 121 31 1 6\n",
+ "4 pyruvic acid 364 1054 363 1 16\n",
+ "5 L-glutamic acid 475 1783 475 1 13\n",
+ "6 glycine 305 782 305 1 14\n",
+ "7 succinic acid 267 1085 265 1 11\n",
+ "8 L-aspartic acid 247 878 247 1 13\n",
+ "9 L-lysine 99 210 99 1 11\n",
+ "10 L-serine 251 823 248 1 14\n",
+ "11 L-arginine 101 214 101 1 9\n",
+ "12 L-tryptophan 114 247 114 1 14\n",
+ "13 L-ornithine 5 10 5 1 2\n",
+ "14 L-methionine 232 617 232 1 15\n",
+ "15 L-tyrosine 126 316 126 1 12\n",
+ "16 beta-alanine 18 45 18 1 6\n",
+ "17 L-cysteine 335 1198 332 1 13\n",
+ "18 serotonin 50 112 50 1 10\n",
+ "19 trans-urocanic acid 2 2 2 1 1\n",
+ "20 creatine 51 120 51 1 6\n",
+ "21 spermidine 8 24 8 1 4\n",
+ "22 L-citrulline 96 203 96 1 9\n",
+ "23 glycine betaine 51 124 51 1 6\n",
+ "24 oleic acid 3 2 3 1 1\n",
+ "25 1-methylnicotinamide 51 120 51 1 6\n",
+ "26 4-acetamidobutanoic acid 2 2 2 1 1\n",
+ "27 9H-xanthine 10 36 10 1 4\n",
+ "28 5-hydroxyindoleacetic acid 40 95 40 1 5\n",
+ "29 octadecanoic acid 4 3 4 1 3\n",
+ "30 cholic acid 96 199 96 1 9\n",
+ "31 sarcosine 116 393 116 1 9\n",
+ "32 4-methyl-2-oxovaleric acid 39 85 39 1 8\n",
+ "33 hexadecanoic acid 172 475 172 1 13\n",
+ "34 taurine 25 49 25 1 6\n",
+ "35 riboflavin 164 551 164 1 14\n",
+ "36 D-glyceric acid 20 56 20 1 10\n",
+ "37 all-cis-5_8_11_14_17-icosapentaenoic acid 22 33 22 1 6\n",
+ "38 octanoic acid 37 144 37 1 7\n",
+ "39 hypoxanthine 15 27 15 1 6\n",
+ "40 linoleic acid 172 661 169 1 12\n",
+ "41 N6_N6_N6-trimethyl-L-lysine 2 2 2 1 1\n",
+ "42 uridine 148 650 148 1 13\n",
+ "43 inosine 26 60 26 1 10\n",
+ "44 Nn-methyl-L-histidine 2 4 2 1 1\n",
+ "45 trans-4-hydroxy-L-proline 37 75 37 1 6\n",
+ "46 5-oxo-L-proline 97 223 97 1 8\n",
+ "47 uracil 12 26 12 1 5\n",
+ "48 phosphocholine 65 243 65 1 10\n",
+ "49 choline 255 853 252 1 16\n",
+ "50 L-leucine 94 192 94 1 9\n",
+ "51 fumaric acid 27 50 27 1 7\n",
+ "52 L-histidine 102 212 102 1 10\n",
+ "53 indole-3-acetic acid 2 4 2 1 1\n",
+ "54 L-thyroxine 3 4 3 1 2\n",
+ "55 N-acetylputrescine 274 1055 271 1 16\n",
+ "56 3-methyl-2-oxobutanoic acid 43 112 43 1 8\n",
+ "57 (S)-malic acid 27 61 27 1 7\n",
+ "58 L-proline 111 232 111 1 13\n",
+ "59 adenine 107 231 107 1 10\n",
+ "60 beta-D-fructofuranose 37 121 37 1 9\n",
+ "61 nicotinamide 49 125 49 1 7\n",
+ "62 L-asparagine 159 434 159 1 12\n",
+ "63 citric acid 108 238 107 1 13\n",
+ "64 (2-hydroxyphenyl)acetic acid 3 4 3 1 2\n",
+ "65 N_N-dimethylglycine 70 177 70 1 9\n",
+ "66 L-threonine 97 204 97 1 9\n",
+ "67 cholesterol 352 1261 348 1 15\n",
+ "68 L-valine 102 211 102 1 11\n",
+ "69 4-guanidinobutanoic acid 2 4 2 1 1\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Sub-graphs analysis\n",
+ "print(df)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 143,
+ "id": "d0a0f33e-9f25-45f6-a4e2-c0863d1ff8bf",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "outfile <- \"C:/Users/mumec/Desktop/Mini_codes/data_out_tesselation.xlsx\"\n",
+ "write.xlsx(df, outfile, sheetName = \"Tesselation Voronoï\", row.names = FALSE)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 146,
+ "id": "262f1c2c-cd8a-4e5b-9503-0c1fa36b4bbf",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "Plot with title \"Voronoï cells topology\""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "df$density <- (df$diameter/(df$nodes*(df$nodes-1)))\n",
+ "plot(df$nodes ~ df$diameter,\n",
+ " ylab=\"Number of cell nodes\",\n",
+ " xlab=\"Cell diameter\",\n",
+ " main=\"Voronoï cells topology\",\n",
+ " cex = rescale(df$density, to = c(1, 5)))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 145,
+ "id": "70da4ec7-437d-4ee4-9d5a-98f633cbcf9c",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "Plot with title \"Voronoï cells topology\""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "df$density <- (df$edges/(df$nodes*(df$nodes-1)))\n",
+ "plot(df$nodes ~ df$edges,\n",
+ " ylab=\"Number of cell nodes\",\n",
+ " xlab=\"Total edges number\",\n",
+ " main=\"Voronoï cells topology\",\n",
+ " cex = rescale(df$density, to = c(1, 5)))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 97,
+ "id": "2f3c9af6-56c6-4190-996a-29089c35e5cb",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ "Plot with title \"BoxPlot of number of nodes\""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "boxplot(df$nodes,\n",
+ " ylab=\"Number of nodes\",\n",
+ " main=\"BoxPlot of number of nodes\"\n",
+ " )"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "R",
+ "language": "R",
+ "name": "ir"
+ },
+ "language_info": {
+ "codemirror_mode": "r",
+ "file_extension": ".r",
+ "mimetype": "text/x-r-source",
+ "name": "R",
+ "pygments_lexer": "r",
+ "version": "3.6.1"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}