2 #############################################################
3 #a, b, c, and d are the counts of all (TRUE, TRUE), (TRUE, FALSE), (FALSE, TRUE), and (FALSE, FALSE)
4 # n <- a + b + c + d = nrow(x)
6 make.a <- function(x) {
11 make.b <- function(x) {
16 make.c <- function(x) {
21 make.d <- function(x, a, b, c) {
23 d <- ncol(x) - a - b - c
27 ###########################################
29 ###########################################
30 my.jaccard <- function(x) {
34 d <- make.d(x, a, b, c)
35 jac <- a / (a + b + c)
40 prcooc <- function(x, a) {
45 make.bin <- function(cs, a, i, j, nb) {
48 res <- binom.test(ab, nb, (cs[i]/nb) * (cs[j]/nb), "less")
53 #res <- binom.test(ab, nb, (cs[i]/nb) * (cs[j]/nb), "less")
57 binom.sim <- function(x) {
61 mat <- matrix(0,ncol(x),ncol(x))
62 colnames(mat)<-colnames(a)
63 rownames(mat)<-rownames(a)
64 for (i in 1:(ncol(x)-1)) {
65 for (j in (i+1):ncol(x)) {
66 mat[j,i] <- make.bin(cs, a, i, j , n)
74 ############################################
76 ############################################
77 # jaccard a, b, c a / (a + b + c)
78 # Kulczynski1 a, b, c a / (b + c)
79 # Kulczynski2 a, b, c [a / (a + b) + a / (a + c)] / 2
80 # Mountford a, b, c 2a / (ab + ac + 2bc)
81 # Fager, McGowan a, b, c a / sqrt((a + b)(a + c)) - 1 / 2 sqrt(a + c)
83 # Dice, Czekanowski, Sorensen a, b, c 2a / (2a + b + c)
84 # Mozley, Margalef a, b, c an / (a + b)(a + c)
85 # Ochiai a, b, c a / sqrt[(a + b)(a + c)]
86 # Simpson a, b, c a / min{(a + b), (a + c)}
87 # Braun-Blanquet a, b, c a / max{(a + b), (a + c)}
89 #simple matching, Sokal/Michener a, b, c, d, ((a + d) /n)
90 # Hamman, a, b, c, d, ([a + d] - [b + c]) / n
91 # Faith , a, b, c, d, (a + d/2) / n
92 # Tanimoto, Rogers a, b, c, d, (a + d) / (a + 2b + 2c + d)
93 # Phi a, b, c, d (ad - bc) / sqrt[(a + b)(c + d)(a + c)(b + d)]
94 # Stiles a, b, c, d log(n(|ad-bc| - 0.5n)^2 / [(a + b)(c + d)(a + c)(b + d)])
95 # Michael a, b, c, d 4(ad - bc) / [(a + d)^2 + (b + c)^2]
96 # Yule a, b, c, d (ad - bc) / (ad + bc)
97 # Yule2 a, b, c, d (sqrt(ad) - sqrt(bc)) / (sqrt(ad) + sqrt(bc))
99 BuildProf01<-function(x,classes) {
101 #classes : classes de chaque lignes de x
102 dm<-cbind(x,cl=classes)
103 clnb=length(summary(as.data.frame(as.character(classes)),max=100))
105 print(summary(as.data.frame(as.character(classes)),max=100))
106 mat<-matrix(0,ncol(x),clnb)
107 rownames(mat)<-colnames(x)
109 dtmp<-dm[which(dm$cl==i),]
110 for (j in 1:(ncol(dtmp)-1)) {
111 mat[j,i]<-sum(dtmp[,j])
117 do.simi <- function(x, method = 'cooc',seuil = NULL, p.type = 'tkplot',layout.type = 'frutch', max.tree = TRUE, coeff.vertex=NULL, coeff.edge = NULL, minmaxeff=c(NULL,NULL), vcexminmax= c(NULL,NULL), cex = 1, coords = NULL, communities = NULL, halo = FALSE) {
120 v.label <- colnames(mat.simi)
121 g1<-graph.adjacency(mat.simi,mode="lower",weighted=TRUE)
123 weori<-get.edge.attribute(g1,'weight')
125 if (method == 'cooc') {
131 g.max<-minimum.spanning.tree(g1)
132 if (method == 'cooc') {
133 E(g.max)$weight<-1 / E(g.max)$weight
135 E(g.max)$weight<-1 - E(g.max)$weight
140 if (!is.null(seuil)) {
141 if (seuil >= max(mat.simi)) seuil <- 0
143 w<-E(g.toplot)$weight
144 tovire <- which(w<=seuil)
145 g.toplot <- delete.edges(g.toplot,(tovire))
146 for (i in 1:(length(V(g.toplot)))) {
147 if (length(neighbors(g.toplot,i))==0) {
151 g.toplot <- delete.vertices(g.toplot,vec)
152 v.label <- V(g.toplot)$name
153 if (!is.logical(vec)) mat.eff <- mat.eff[-(vec)]
158 if (!is.null(minmaxeff[1])) {
159 eff<-norm.vec(mat.eff,minmaxeff[1],minmaxeff[2])
163 if (!is.null(vcexminmax[1])) {
164 label.cex = norm.vec(mat.eff, vcexminmax[1], vcexminmax[2])
168 if (!is.null(coeff.edge)) {
169 we.width <- norm.vec(abs(E(g.toplot)$weight), coeff.edge[1], coeff.edge[2])
170 #we.width <- abs((E(g.toplot)$weight/max(abs(E(g.toplot)$weight)))*coeff.edge)
174 if (method != 'binom') {
175 we.label <- round(E(g.toplot)$weight,2)
177 we.label <- round(E(g.toplot)$weight,3)
179 if (p.type=='rgl' || p.type=='rglweb') {
184 if (is.null(coords)) {
185 if (layout.type == 'frutch')
186 lo <- layout.fruchterman.reingold(g.toplot,dim=nd)#, weightsA=E(g.toplot)$weight)
187 if (layout.type == 'kawa')
188 lo <- layout.kamada.kawai(g.toplot,dim=nd)
189 if (layout.type == 'random')
190 lo <- layout.random(g.toplot,dim=nd)
191 if (layout.type == 'circle' & p.type != 'rgl')
192 lo <- layout.circle(g.toplot)
193 if (layout.type == 'circle' & p.type == 'rgl')
194 lo <- layout.sphere(g.toplot)
195 if (layout.type == 'graphopt')
196 lo <- layout.graphopt(g.toplot)
200 if (!is.null(communities)) {
201 if (communities == 0 ){ #'edge.betweenness.community') {
202 com <- edge.betweenness.community(g.toplot)
203 } else if (communities == 1) {
204 com <- fastgreedy.community(g.toplot)
205 } else if (communities == 2) {
206 com <- label.propagation.community(g.toplot)
207 } else if (communities == 3) {
208 com <- leading.eigenvector.community(g.toplot)
209 } else if (communities == 4) {
210 com <- multilevel.community(g.toplot)
211 } else if (communities == 5) {
212 com <- optimal.community(g.toplot)
213 } else if (communities == 6) {
214 com <- spinglass.community(g.toplot)
215 } else if (communities == 7) {
216 com <- walktrap.community(g.toplot)
222 out <- list(graph = g.toplot, mat.eff = mat.eff, eff = eff, mat = mat.simi, v.label = v.label, we.width = we.width, we.label=we.label, label.cex = label.cex, layout = lo, communities = com, halo = halo, elim=vec)
225 plot.simi <- function(graph.simi, p.type = 'tkplot',filename=NULL, communities = NULL, vertex.col = 'red', edge.col = 'black', edge.label = TRUE, vertex.label=TRUE, vertex.label.color = 'black', vertex.label.cex= NULL, vertex.size=NULL, leg=NULL, width = 800, height = 800, alpha = 0.1, cexalpha = FALSE, movie = NULL, svg = FALSE) {
226 mat.simi <- graph.simi$mat
227 g.toplot <- graph.simi$graph
228 if (is.null(vertex.size)) {
229 vertex.size <- graph.simi$eff
231 vertex.size <- vertex.size
233 we.width <- graph.simi$we.width
235 #v.label <- vire.nonascii(graph.simi$v.label)
236 v.label <- graph.simi$v.label
241 we.label <- graph.simi$we.label
245 lo <- graph.simi$layout
246 if (!is.null(vertex.label.cex)) {
247 label.cex<-vertex.label.cex
249 label.cex = graph.simi$label.cex
252 alphas <- norm.vec(label.cex, 0.5,1)
254 if (length(vertex.label.color) == 1) {
255 for (i in 1:length(alphas)) {
256 nvlc <- append(nvlc, adjustcolor(vertex.label.color, alpha=alphas[i]))
259 for (i in 1:length(alphas)) {
260 nvlc <- append(nvlc, adjustcolor(vertex.label.color[i], alpha=alphas[i]))
263 vertex.label.color <- nvlc
265 if (p.type=='nplot') {
266 #print('ATTENTION - PAS OPEN FILE')
267 open_file_graph(filename, width = width, height = height, svg = svg)
270 layout(matrix(c(1,2),1,2, byrow=TRUE),widths=c(3,lcm(7)))
274 if (is.null(graph.simi$com)) {
275 plot(g.toplot,vertex.label='', edge.width=we.width, vertex.size=vertex.size, vertex.color=vertex.col, vertex.label.color='white', edge.label=we.label, edge.label.cex=cex, edge.color=edge.col, vertex.label.cex = 0, layout=lo, edge.curved=FALSE)#, rescale = FALSE)
277 if (graph.simi$halo) {
278 mark.groups <- communities(graph.simi$com)
282 plot(com, g.toplot,vertex.label='', edge.width=we.width, vertex.size=vertex.size, vertex.color=vertex.col, vertex.label.color='white', edge.label=we.label, edge.label.cex=cex, edge.color=edge.col, vertex.label.cex = 0, layout=lo, mark.groups = mark.groups, edge.curved=FALSE)
285 txt.layout <- layout.norm(lo, -1, 1, -1, 1, -1, 1)
286 #txt.layout <- txt.layout[order(label.cex),]
287 #vertex.label.color <- vertex.label.color[order(label.cex)]
288 #v.label <- v.label[order(label.cex)]
289 #label.cex <- label.cex[order(label.cex)]
290 text(txt.layout[,1], txt.layout[,2], v.label, cex=label.cex, col=vertex.label.color)
293 plot(0, axes = FALSE, pch = '')
294 legend(x = 'center' , leg$unetoile, fill = leg$gcol)
299 if (p.type=='tkplot') {
300 id <- tkplot(g.toplot,vertex.label=v.label, edge.width=we.width, vertex.size=vertex.size, vertex.color=vertex.col, vertex.label.color=vertex.label.color, edge.label=we.label, edge.color=edge.col, layout=lo)
301 coords = tkplot.getcoords(id)
302 ok <- try(coords <- tkplot.getcoords(id), TRUE)
303 while (is.matrix(ok)) {
304 ok <- try(coords <- tkplot.getcoords(id), TRUE)
311 if (p.type == 'rgl' || p.type == 'rglweb') {
315 lo <- layout.norm(lo, -10, 10, -10, 10, -10, 10)
317 rglplot(g.toplot,vertex.label='', edge.width=we.width/10, vertex.size=0.01, vertex.color=vertex.col, vertex.label.color="black", edge.color = edge.col, layout=lo, rescale = FALSE)
318 #los <- layout.norm(lo, -1, 1, -1, 1, -1, 1)
319 text3d(lo[,1], lo[,2], lo[,3], vire.nonascii(v.label), col = vertex.label.color, alpha = 1, cex = vertex.label.cex)
320 rgl.spheres(lo, col = vertex.col, radius = vertex.size/100, alpha = alpha)
321 #rgl.bg(color = c('white','black'))
323 if (!is.null(movie)) {
325 ReturnVal <- tkmessageBox(title="RGL 3 D",message="Cliquez pour commencer le film",icon="info",type="ok")
327 movie3d(spin3d(axis=c(0,1,0),rpm=6), movie = 'film_graph', frames = "tmpfilm", duration=10, clean=TRUE, top = TRUE, dir = movie)
328 ReturnVal <- tkmessageBox(title="RGL 3 D",message="Film fini !",icon="info",type="ok")
330 #play3d(spin3d(axis=c(0,1,0),rpm=6))
331 if (p.type == 'rglweb') {
332 writeWebGL(dir = filename, width = width, height= height)
335 ReturnVal <- tkmessageBox(title="RGL 3 D",message="Cliquez pour fermer",icon="info",type="ok")
338 # while (rgl.cur() != 0)
340 } else if (p.type == 'web') {
342 simi.to.gexf(filename, graph.simi, nodes.attr = NULL)
347 graph.word <- function(mat.simi, index) {
348 nm <- matrix(0, ncol = ncol(mat.simi), nrow=nrow(mat.simi), dimnames=list(row.names(mat.simi), colnames(mat.simi)))
349 nm[,index] <- mat.simi[,index]
350 nm[index,] <- mat.simi[index,]
355 #http://gopalakrishna.palem.in/iGraphExport.html#GexfExport
356 # Converts the given igraph object to GEXF format and saves it at the given filepath location
357 # g: input igraph object to be converted to gexf format
358 # filepath: file location where the output gexf file should be saved
360 saveAsGEXF = function(g, filepath="converted_graph.gexf")
365 # gexf nodes require two column data frame (id, label)
366 # check if the input vertices has label already present
367 # if not, just have the ids themselves as the label
368 if(is.null(V(g)$label))
369 V(g)$label <- as.character(V(g))
371 # similarily if edges does not have weight, add default 1 weight
372 if(is.null(E(g)$weight))
373 E(g)$weight <- rep.int(1, ecount(g))
375 nodes <- data.frame(cbind(1:vcount(g), V(g)$label))
376 nodes[,1] <- as.character(nodes[,1])
377 nodes[,2] <- as.character(nodes[,2])
378 edges <- t(Vectorize(get.edge, vectorize.args='id')(g, 1:ecount(g)))
380 # combine all node attributes into a matrix (and take care of & for xml)
381 vAttrNames <- setdiff(list.vertex.attributes(g), "label")
382 for (val in c("x","y","color")) {
383 vAttrNames <- setdiff(vAttrNames, val)
385 nodesAtt <- data.frame(sapply(vAttrNames, function(attr) sub("&", "&",get.vertex.attribute(g, attr))))
386 for (i in 1:ncol(nodesAtt)) {
387 nodesAtt[,i] <- as.character(nodesAtt[,i])
390 # combine all edge attributes into a matrix (and take care of & for xml)
391 eAttrNames <- setdiff(list.edge.attributes(g), "weight")
392 edgesAtt <- data.frame(sapply(eAttrNames, function(attr) sub("&", "&",get.edge.attribute(g, attr))))
394 # combine all graph attributes into a meta-data
395 graphAtt <- sapply(list.graph.attributes(g), function(attr) sub("&", "&",get.graph.attribute(g, attr)))
397 cc <- t(sapply(V(g)$color, col2rgb, alpha=TRUE))
399 # generate the gexf object
400 output <- write.gexf(nodes, edges,
401 edgesWeight=E(g)$weight,
403 #edgesVizAtt = list(size=as.matrix(E(g)$weight)),
405 nodesVizAtt=list(color=cc, position=cbind(V(g)$x,V(g)$y, rep(0,ll)), size=V(g)$weight),
406 meta=c(list(creator="iramuteq", description="igraph -> gexf converted file", keywords="igraph, gexf, R, rgexf"), graphAtt))
408 print(output, filepath, replace=T)