iramuteq.org Git - iramuteq/blob - Rscripts/simiold.R

   1 #############################################################
   2 makesimi<-function(dm){
   3         a<-dm
   4         m<-matrix(0,ncol(dm),ncol(dm))
   5         rownames(m)<-colnames(a)
   6         colnames(m)<-colnames(a)
   7         eff<-colSums(a)
   8         for (col in 1:(ncol(a)-1)){
   9                 for (colc in (col+1):ncol(a)){
  10                         ta<-table(a[,col],a[,colc])
  11                         if (ncol(ta)==1 & colnames(ta)[1]=='0') {
  12                                 ta<-cbind(ta,'1'=c(0,0))
  13                         } else if (ncol(ta)==1 & colnames(ta)[1]=='1') {
  14                                 ta<-cbind('0'=c(0,0),t)
  15                         } else if (nrow(ta)==1 & rownames(ta)[1]=='0'){
  16                                 ta<-rbind(ta,'1'=c(0,0))
  17                         } else if (nrow(ta)==1 & rownames(ta)[1]=='1') {
  18                                 ta<-rbind('0'=c(0,0),ta)
  19                         }
  20                         #m[colc,col]<-length(which((a[,col]==1) & (a[,colc]==1)))
  21                         m[colc,col]<-ta[2,2]
  22                         m[col,colc]<-m[colc,col]
  23                 }
  24         }
  25         out<-list(mat=m,eff=eff)
  26 }
  27
  28 makejac<-function(dm){
  29         a<-dm
  30         m<-matrix(0,ncol(dm),ncol(dm))
  31         rownames(m)<-colnames(a)
  32         colnames(m)<-colnames(a)
  33         eff<-colSums(a)
  34         for (col in 1:(ncol(a)-1)){
  35                 for (colc in (col+1):ncol(a)){
  36                         ta<-table(a[,col],a[,colc])
  37                         if (ncol(ta)==1 & colnames(ta)[1]=='0') {
  38                                 ta<-cbind(ta,'1'=c(0,0))
  39                         } else if (ncol(ta)==1 & colnames(ta)[1]=='1') {
  40                                 ta<-cbind('0'=c(0,0),t)
  41                         } else if (nrow(ta)==1 & rownames(ta)[1]=='0'){
  42                                 ta<-rbind(ta,'1'=c(0,0))
  43                         } else if (nrow(ta)==1 & rownames(ta)[1]=='1') {
  44                                 ta<-rbind('0'=c(0,0),ta)
  45                         }
  46                         m[colc,col]<-(ta[2,2]/(ta[1,2]+ta[2,1]+ta[2,2]))*100
  47                         #m[colc,col]<-(length(which((a[,col]==1) & (a[,colc]==1)))/(eff[col]+eff[colc]-length(which((a[,col]==1) & (a[,colc]==1)))))*100
  48                         m[col,colc]<-m[colc,col]
  49                 }
  50         }
  51         out<-list(mat=m,eff=eff)
  52 }
  53
  54 makesimipond<-function(dm) {
  55         a<-dm
  56         m<-matrix(0,ncol(dm),ncol(dm))
  57         rownames(m)<-colnames(dm)
  58         colnames(m)<-colnames(dm)
  59         eff<-colSums(a)
  60         #a<-t(a)
  61         #print(a)
  62         #lt<-list()
  63         for (col in 1:(ncol(a)-1)){
  64                 for (colc in (col+1):ncol(a)){
  65                         m[colc,col]<-length(which((a[,col]>1) & (a[,colc]>1)))
  66                         m[col,colc]<-m[colc,col]
  67                 }
  68         }
  69         out<-list(mat=m,eff=eff)
  70 }
  71
  72 BuildProf01<-function(x,classes) {
  73         #x : donnees en 0/1
  74         #classes : classes de chaque lignes de x
  75         dm<-cbind(x,cl=classes)
  76         clnb=length(summary(as.data.frame(as.character(classes)),max=100))
  77         print(clnb)
  78         print(summary(as.data.frame(as.character(classes)),max=100))
  79         mat<-matrix(0,ncol(x),clnb)
  80         #print(mat)
  81         rownames(mat)<-colnames(x)
  82         for (i in 1:clnb) {
  83                 dtmp<-dm[which(dm$cl==i),]
  84                 for (j in 1:(ncol(dtmp)-1)) {
  85                         #print(rownames(dtmp[j,]))
  86                         mat[j,i]<-sum(dtmp[,j])
  87                 }
  88         }
  89         mat
  90 }
  91 ###################################################################
  92
  93 source('/home/pierre/workspace/iramuteq/Rscripts/chdfunct.R')
  94 #info<-read.csv2(file('/home/pierre/fac/etudiant/crepin/simi/info01.csv',encoding='latin1'),row.names=1)
  95 #cinf<-ncol(info)
  96 #biblio<-read.csv2(file('/home/pierre/fac/etudiant/crepin/simi/biblio01.csv',encoding='latin1'),row.names=1)
  97 #cbib<-ncol(biblio)
  98 #rechdoc<-read.csv2(file('/home/pierre/fac/etudiant/crepin/simi/recherdoc01.csv',encoding='latin1'),row.names=1)
  99 #crech<-ncol(rechdoc)
 100
 101 ######################@@
 102 #MV
 103 #########################
 104 #chaud<-read.csv2('/home/pierre/fac/etudiant/sab/Chaudronnier_pour_MV01.csv',row.names=1)
 105 ##cchaud<-ncol(chaud)
 106 #op<-read.csv2('/home/pierre/fac/etudiant/sab/ocn_pour_mv01.csv',row.names=1)
 107 ##cop<-ncol(op)
 108 #soud<-read.csv2('/home/pierre/fac/etudiant/sab/soudeur_pour_mv01.csv',row.names=1)
 109 ##csoud<-ncol(soud)
 110 #indus<-read.csv2('/home/pierre/fac/etudiant/sab/metier_indus01.csv',row.names=1)
 111 ##cmindus<-ncol(mindus)
 112 #infor<-read.csv2('/home/pierre/fac/etudiant/sab/Informaticien_pour_MV01.csv',row.names=1)
 113 ##cinfor<-ncol(infor)
 114 #trav<-read.csv2('/home/pierre/fac/etudiant/sab/travail_pour_mv01.csv',row.names=1)
 115 ##ctrav<-ncol(trav)
 116 #tot<-cbind(chaud,op)
 117 #tot<-cbind(tot,soud)
 118 #tot<-cbind(tot,indus)
 119 ##
 120 #list_data<-list('a'=chaud, 'b'=soud,'c'=infor,'d'=trav)
 121 #tot<-cbind(chaud,op)
 122 #tot<-chaud
 123 ##tot<-cbind(tot,infor)
 124 ##tot<-cbind(tot,trav)
 125 #mv<-read.csv2('/home/pierre/fac/etudiant/sab/chaud_soud_opn_metierindus01.csv')
 126 #mv<-mv[,-ncol(mv)]
 127 #grp<-read.csv2('/home/pierre/fac/etudiant/sab/grp2.csv')
 128 #tab<-tot
 129
 130 print('passe ici')
 131 #tot<-mv[,-ncol(mv)]
 132 #tot<-trav
 133 #################################################
 134 #AGIR
 135 #ag<-read.csv2('/home/pierre/workspace/iramuteq/corpus/tableau_agir2_recod_alc_entree_pourpassage_temp_AlcesteQuest_1/Act01.csv')
 136 #cag<-ncol(ag)
 137 #load('/home/pierre/workspace/iramuteq/corpus/tableau_agir2_recod_alc_entree_pourpassage_temp_AlcesteQuest_1/RData.RData')
 138
 139 ###############################################################
 140 #Vero
 141 #tot<-read.csv2('/home/pierre/fac/etudiant/crepin/simi/simitot01.csv')
 142 #grp<-vector(mode='integer',length=ncol(tot))
 143 #grp[1:54]<-1
 144 #grp[55:108]<-2
 145 #grp[109:162]<-3
 146 #prof<-BuildProf01(tot,grp[,1])
 147 ##prof<-prof[-nrow(prof),]
 148 #outp<-AsLexico(prof)
 149 #chistabletot<-outp[[2]]
 150
 151 ###################################################################
 152 #Steph
 153
 154 #tot<-read.csv2('/home/pierre/fac/etudiant/netto/simi-27-03-09/prof_inf_ecole_priv01.csv')
 155 #tot<-tot[,-ncol(tot)]
 156 #grp<-vector(mode='integer',length=nrow(tot))
 157 #grp[1:245]<-1
 158 #grp[246:490]<-2
 159 #prof<-BuildProf01(tot,grp)
 160 #print(nrow(prof))
 161 ##print(prof)
 162 #outp<-AsLexico(prof)
 163 #chistabletot<-outp[[2]]
 164
 165 #tot<-read.csv2('/home/pierre/fac/etudiant/netto/simi-27-03-09/etu_inf_pro_priv01.csv')
 166 #print(tot[,ncol(tot)])
 167 #tot<-tot[,-ncol(tot)]
 168 #grp<-vector(mode='integer',length=nrow(tot))
 169 #grp[1:175]<-1
 170 #grp[176:350]<-2
 171 #prof<-BuildProf01(tot,grp)
 172 #outp<-AsLexico(prof)
 173 #chistabletot<-outp[[2]]
 174
 175 #tot<-read.csv2('/home/pierre/fac/etudiant/netto/simi-27-03-09/prof_etu_inf_pro01.csv')
 176 #print(tot[,ncol(tot)])
 177 #tot<-tot[,-ncol(tot)]
 178 #grp<-vector(mode='integer',length=nrow(tot))
 179 #grp[1:245]<-1
 180 #grp[246:419]<-2
 181 #prof<-BuildProf01(tot,grp)
 182 #outp<-AsLexico(prof)
 183 #chistabletot<-outp[[2]]
 184
 185 #######################################################
 186 #grp ideal 2008
 187 #tot<-read.csv2('/home/pierre/workspace/iramuteq/corpus/grpiedal2008_01.csv')
 188 #print(tot[,ncol(tot)])
 189 #grp<-vector(mode='integer',length=ncol(tot))
 190 #grp[1:10]<-1
 191 #grp[11:20]<-2
 192 #prof<-BuildProf01(tot,grp)
 193 #outp<-AsLexico(prof)
 194 #chistabletot<-outp[[2]]
 195
 196 #ministre<-read.csv2('/home/pierre/workspace/iramuteq/corpus/Ministres_AFCUCI_3/TableCont.csv',header=TRUE)
 197 #eff<-colSums(ministre)
 198 #ministre<-ministre[,-which(eff<100)]
 199 #
 200 ##ministre<-(ministre/colSums(ministre))*1000
 201 #print(ncol(ministre))
 202 #pm<-t(ministre)
 203 #outp<-AsLexico(pm)
 204 #chistabletot<-outp[[2]]
 205 #ministre<-read.csv2('/home/pierre/workspace/iramuteq/corpus/Ministres_Alceste_1/TableUc1.csv',header=TRUE)
 206 #load('/home/pierre/workspace/iramuteq/corpus/Ministres_Alceste_1/RData.RData')
 207 #ministre<-ministre[,-which(eff<200)]
 208 #uce<-read.csv2('/home/pierre/workspace/iramuteq/corpus/Ministres_Alceste_1/listeUCE1.csv')
 209 #uc<-matrix(0,nrow(ministre),1)
 210 #uc<-list()
 211 #print(uce)
 212 #print(nrow(n1))
 213 #for (i in 1:nrow(uce)) {
 214 #    uc[[as.integer(uce[i,2])+1]]<-n1[i,ncol(n1)]
 215 #}
 216 #print(nrow(ministre))
 217 #grp<-unlist(uc)
 218 #prof<-BuildProf01(ag,n1[,ncol(n1)])
 219 #outp<-AsLexico(prof)
 220 #chistabletot<-outp[[2]]
 221
 222 #######################
 223 #Steph
 224 #########################
 225 #priv<-read.csv2('/home/pierre/workspace/iramuteq/corpus/simi/info_priv01.csv')
 226 #pro<-read.csv2('/home/pierre/workspace/iramuteq/corpus/simi/info_pro01.csv')
 227 #cpriv<-ncol(priv)
 228 #tot<-cbind(priv,pro)
 229 #tot<-read.csv2('/home/pierre/workspace/iramuteq/corpus/simi/priv_pro_ens01.csv')
 230 #print('tot')
 231 #print(ncol(tot))
 232
 233
 234 #grp<-vector(mode='integer',length=nrow(tot))
 235 #grp[1:245]<-1
 236 #grp[246:nrow(tot)]<-2
 237 #grp[491:635]<-3
 238 #prof<-BuildProf01(tot,grp)
 239 #prof<-prof[,-4]
 240 #print(prof)
 241 #print(nrow(prof))
 242 #outp<-AsLexico(prof)
 243 #chistabletot<-outp[[2]]
 244 #cs<-colSums(prof)
 245 #prof<-prof/cs
 246 #l<-vector(mode='integer',length=nrow(prof))
 247 #for (line in 1:nrow(prof)) {
 248 #    l[line]<-as.integer(which.max(prof[line,1:2]))
 249 #}
 250 print('lecture')
 251 #chistabletot<-chistabletot[1:ncol(ministre),]
 252 #print(nrow(chistabletot))
 253 #sc<-colSums(as.matrix(ministre))
 254 #print(length(sc))
 255 #outc<-which(sc>0)
 256 #print(length(outc))
 257 #ministre<-ministre[,outc]
 258 #print(ncol(ministre))
 259 #prof<-BuildProf01(ministre,grp)
 260 #outp<-AsLexico(prof)
 261 #chistabletot<-outp[[2]]
 262 #chistabletot<-chistabletot[outc,]
 263 #print(nrow(chistabletot))
 264 #ave<-read.csv2('/home/pierre/workspace/iramuteq/corpus/Avenir_Alceste_1/TableUc1.csv',header=TRUE)
 265 #load('/home/pierre/workspace/iramuteq/corpus/Avenir_Alceste_1/RData.RData')
 266 #chistabletot<-chistabletot[1:cag,]
 267
 268 #print(grp)
 269 #grp<-as.character(grp[,1])
 270 #titre<-c("chaudronnier","soudeur","informaticien","travail")
 271 #count<-0
 272 #split.screen(c(2,2))
 273 #for (tab in list_data) {
 274 #count<-count+1
 275 #screen(count)
 276 #par(cex=0.7)
 277 #grp<-rbind(grp,grp)
 278 #grp<-rbind(grp,grp)
 279 #print(ncol(tab))
 280
 281 #####################################################################
 282 #suede enfance en danger
 283 tot<-read.csv2('/home/pierre/fac/suede/resultats/cat_asso1_01.csv',row.names=1)
 284
 285 #prof<-BuildProf01(tab,grp[,1])
 286 #outp<-AsLexico(prof)
 287 #chistabletot<-outp[[2]]
 288
 289 #print('liste des classes')
 290 #listclasse<-vector(mode='integer',length=ncol(tab))
 291 #for (line in 1:nrow(chistabletot)) {
 292 #    if (max(chistabletot[line,])>0) {
 293 #        listclasse[line]<-as.vector(which.max(chistabletot[line,]))
 294 #    } else {
 295 #        listclasse[line]<-3
 296 #    }
 297 #}
 298 #classes<-listclasse
 299 #classes<-classes[1:cag]
 300 #print(classes)
 301 #tot<-cbind(info,biblio)
 302 #tot<-cbind(tot,rechdoc)
 303 listclasse<-vector(mode='integer',length=ncol(dt))
 304 for (line in 1:nrow(chistabletot)) {
 305         if ((max(chistabletot[line,])>3.84) || (min(prof[line,])==0)) {
 306                 if (max(chistabletot[line,])>3.84) {
 307                         listclasse[line]<-as.vector(which.max(chistabletot[line,]))
 308                 }
 309                 if (min(prof[line,])==0) {
 310                         print('zero')
 311                         listclasse[line]<-as.vector(which.max(prof[line,]))
 312                 }
 313         } else {
 314                 listclasse[line]<-3
 315         }
 316 }
 317
 318 print('matrice de similitude')
 319 mindus<-makesimi(tot)
 320 m<-mindus$m
 321 eff<-mindus$eff
 322
 323 #mateff<-makesimipond(ministre)
 324 #mateff<-makesimi(tot)
 325 #mateff<-makejac(tot)
 326 #m<-mateff$mat
 327 #eff<-mateff$eff
 328 #m<-as.matrix(dist(t(ministre),method='binary',upper=TRUE, diag=TRUE))
 329 #m<-as.matrix(simil(ministre), method='Jaccard', upper=TRUE, diag=TRUE, by_rows=FALSE)
 330 #print(nrow(m))
 331 #print(ncol(m))
 332 #print(length(colnames(ministre)))
 333 #colnames(m)<-colnames(ministre)
 334 #rownames(m)<-colnames(ministre)
 335 #eff<-colSums(ministre)
 336 #mateffp<-makesimi(ministre)
 337 #mateffp<-makesimipond(ministre)
 338 #m<-mateffp$mat
 339 #eff<-mateffp$eff
 340
 341 #matave<-makesimi(ministre)
 342 #m<-matave$m
 343 #eff<-matave$eff
 344
 345 print('couleur')
 346 #rain<-rainbow(3)
 347 #append(rain,'black')
 348 rain<-c("green","red","white")#"yellow","pink","black")#green","blue","red","black")
 349 vcol<-vector(mode='integer',length=length(eff))
 350 vcolb<-vector(mode='integer',length=length(eff))
 351 #classes<-classes[1:93]
 352 #classes<-grp
 353 #for (i in 1:length(eff)){
 354 #    vcol[i]<-rain[as.integer(classes[i])]
 355 #       vcolb[i]<-"black"
 356 #}
 357 #ll<-which(effp>=0.5)
 358 #for (i in which(effp>=0.5)) {
 359 #       if (i<=10) {
 360 #               vcol[i]<-"blue"
 361 #       } else {
 362 #               vcol[i]<-"pink"
 363 #       }
 364 #}
 365 #print('length(vcol)')
 366 #print(length(vcol))
 367 #vcol[1:cchaud]<-rain[1]
 368 #vcol[(cchaud+1):(cchaud+cop)]<-rain[2]
 369 #vcol[(cchaud+cop+1):length(eff)]<-rain[3]
 370 #print(classes)
 371 print('premier graph')
 372 library(igraph)
 373 #sink('graph.txt')
 374 g1<-graph.adjacency(m,mode="lower",weighted=TRUE)
 375
 376 #maxtree<-maxgraph(g1)
 377 #plot(maxtree, layout=layout.circle)
 378 #lo<-layout.circle(g1)
 379 eff<-(eff/max(eff))
 380 weori<-get.edge.attribute(g1,'weight')
 381 #tdel<-which(weori<3)
 382 we<-(weori/max(weori))*4
 383 print('arbre maximum')
 384 invw<-1/weori
 385 E(g1)$weight<-invw
 386 g3<-minimum.spanning.tree(g1)
 387 E(g3)$weight<-1/E(g3)$weight
 388 #print(E(g3)$weight)
 389 #sink()
 390 #g3<-g1
 391 wev<-eff*20
 392 wee<-(E(g3)$weight/max(E(g3)$weight))*10
 393 weori<-E(g3)$weight
 394 print('layout')
 395 #lo<-layout.kamada.kawai(g3,dim=3)
 396 lo<-layout.fruchterman.reingold(g3,dim=3)
 397 print('lo')
 398 #print(nrow(lo))
 399 #lo<-layout.sphere(g3)
 400 #lo<-cbind(lo,eff)
 401 vsize<-vector(mode='integer',length=nrow(lo))
 402 #print(we)
 403 #ecount(g1)
 404 #g2<-simplify(g1)
 405 #g2<-delete.edges(g2,tdel-1)
 406 #tmax<-clusters(g1)
 407 #print(tmax)
 408 #we<-we[-tdel]
 409 #weori<-weori[-tdel]
 410 #plot(g1,vertex.label=colnames(m),edge.width=get.edge.attribute(g1,'weight'),layout=layout.circle,vertex.shape='none')
 411 #igraph.par('print.edge.attributes',TRUE)
 412 #plot(g2,vertex.label=colnames(m),vertex.size=vsize,vertex.color=vcol,edge.width=we,layout=lo)#,vertex.shape='none')#,edge.label=weori)
 413 #rglplot(g3,vertex.label=colnames(m),edge.width=we,vertex.size=vsize,vertex.label.color=vcol,layout=lo,vertex.shape='none')#,edge.label=weori)
 414 print('plot')
 415 tkplot(g3,vertex.label=colnames(m),edge.width=wee,vertex.size=wev,vertex.label.color="black",layout=lo)#,vcolb vertex.label.dist=1)#,vertex.shape='none')#,edge.label=weori)
 416 #},vertex.color=vcol
 417 #rgl.bg(sphere=FALSE,color=c("black","white"))
 418 #vertex.color=vcol,vertex.label.color=vcol,edge.label=weori,
 419 #rgl.viewpoint(zoom=0.6)
 420 #movie3d(spin3d(axis=c(0,1,0),rpm=6),10,dir='/home/pierre/workspace/iramuteq/corpus/',movie="vero_cooc_explo",clean=TRUE,convert=TRUE,fps=20)
 421 #tkplot(g1,vertex.label=colnames(m),layout=layout.circle,vertex.shape='rectangle')
 422 #rglplot(g1,vertex.label=colnames(m),layout=layout.circle)
 423 #g1<-graph(m)
 424 #tkplot(g1)
 425
 426
 427
 428
 429
 430 #Ministre
 431 autre :
 432 dm<-read.csv2('classe_mod.csv',row.names=1,header = FALSE)
 433 load('RData.RData')
 434 #------------------------------------------------------
 435 #selectionner
 436 chimax<-as.matrix(apply(chistabletot,1,max))
 437 chimax<-as.matrix(chimax[,1][1:nrow(dm)])
 438 chimax<-cbind(chimax,1:nrow(dm))
 439 order_chi<-as.matrix(chimax[order(chimax[,1],decreasing = TRUE),])
 440 elim<-which(rownames(dm) == 'faire')
 441 dm<-dm[-elim,]
 442 dm<-dm[chimax[,2][1:300],]
 443 #-------------------------------------------------------
 444 limit<-nrow(dm)
 445 distm<-dist(dm,diag=TRUE)
 446 distm<-as.matrix(distm)
 447 g1<-graph.adjacency(distm,mode='lower',weighted=TRUE)
 448 g1<-minimum.spanning.tree(g1)
 449 lo<-layout.kamada.kawai(g1,dim=3)
 450 mc<-rainbow(ncol(chistabletot))
 451 chistabletot<-chistabletot[-elim,]
 452 cc<-vector()
 453 for (i in 1:limit) {
 454         cc<-append(cc,which.max(chistabletot[i,]))
 455 }
 456 cc<-mc[cc]
 457 mass<-rowSums(dm)/100
 458 rglplot(g1,vertex.label = rownames(dm),vertex.label.color=cc,vertex.color=cc,vertex.size = mass, layout=lo)
 459
 460
 461
 462 autre :
 463 dm<-read.csv2('enseignant_simi_opi.csv',row.names=1,na.string='')
 464 mat<-matrix(0,ncol=ncol(dm),nrow=ncol(dm))
 465 for (i in 1:(ncol(dm)-1)) {
 466         for (j in (i+1):ncol(dm)){
 467         tab<-table(dm[,i],dm[,j])
 468         chi<-chisq.test(tab)
 469         mat[i,j]<-chi$statistic
 470         mat[j,i]<-chi$statistic
 471         }
 472 }
 473 mat<-ifelse(mat>3.84,mat,0)
 474 mat<-ifelse(is.na(mat),0,mat)
 475 mat<-ifelse(is.infinite(mat),0,mat)
 476 cs<-colSums(mat)
 477 tovire<-which(cs==0)
 478 if (!is.integer(tovire)){
 479 mat<-mat[-tovire,]
 480 mat<-mat[,-tovire]
 481 }
 482 cn<-colnames(dm)
 483 if (!is.integer(tovire)) cn<-cn[-tovire]
 484 g1<-graph.adjacency(mat,mode='lower',weighted=TRUE)
 485 lo<-layout.fruchterman.reingold(g1,dim=2)
 486 wei<-E(g1)$weight
 487 plot(g1,vertex.label=cn,vertex.size=0.1,edge.width=wei,edge.label=round(wei,2),layout=lo)
 488
 489
 490
 491 levels.n<-mj$levels.n
 492 levelnames<-mj$levelnames
 493 cn<-mj$colnames
 494 count<-0
 495 for (j in 1:ncol(dm)) {
 496         for (i in 1:levels.n[j]) {
 497                 count<-count+1
 498                 print(paste(cn[j],'\\.',sep=''))
 499                 levelnames[count]<-gsub(paste(cn[j],'\\.',sep=''),'',levelnames[count])
 500         }
 501 }
 502