+ """ % (ffr(self.analyse.pathout['actives_eff.csv']), ffr(self.analyse.pathout['selected.csv']), self.parametres['maxword'], ffr(self.parametres['graphout']), self.parametres['width'], self.parametres['height'], bg_col, self.parametres['maxcex'], self.parametres['mincex'], txt_col)
+ self.add(txt)
+ self.write()
+
+
+class ProtoScript(PrintRScript):
+
+ def make_script(self):
+ self.sources([self.analyse.parent.RscriptsPath['Rgraph'], self.analyse.parent.RscriptsPath['prototypical.R']])
+ self.packages(['wordcloud'])
+ if self.parametres.get('cloud', False):
+ cloud = 'TRUE'
+ else:
+ cloud = 'FALSE'
+ txt = """
+ errorn <- function(x) {
+ qnorm(0.975)*sd(x)/sqrt(lenght(n))
+ }
+ errort <- function(x) {
+ qt(0.975,df=lenght(x)-1)*sd(x)/sqrt(lenght(x))
+ }
+ mat <- read.csv2("%s", header = FALSE, row.names=1, sep='\t', quote='"', dec='.')
+ open_file_graph("%s",height=800, width=1000)
+ prototypical(mat, mfreq = %s, mrank = %s, cloud = FALSE, cexrange=c(1,2.4), cexalpha= c(0.4, 1), type = '%s', mat.col.path='/tmp/matcol.csv')
+ dev.off()
+ """ % (ffr(self.analyse.pathout['table.csv']), ffr(self.analyse.pathout['proto.png']), self.parametres['limfreq'], self.parametres['limrang'], self.parametres['typegraph'])
+ self.add(txt)
+ self.write()
+
+
+class ExportAfc(PrintRScript):
+
+ def make_script(self):
+ self.source([self.analyse.parent.RscriptsPath['Rgraph']])
+ self.packages(['rgexf'])
+ txt = """
+ """
+
+
+class MergeGraphes(PrintRScript):
+
+ def __init__(self, analyse):
+ self.script = "#Script genere par IRaMuTeQ - %s\n" % datetime.now().ctime()
+ self.pathout = PathOut()
+ self.parametres = analyse.parametres
+ self.scriptout = self.pathout['temp']
+ self.analyse = analyse
+
+ def make_script(self):
+ #FIXME
+ txt = """
+ library(igraph)
+ library(Matrix)
+ graphs <- list()
+ """
+ load = """
+ load("%s")
+ g <- graph.simi$graph
+ V(g)$weight <- (graph.simi$mat.eff/nrow(dm))*100
+ graphs[['%s']] <- g
+ """
+ for i, graph in enumerate(self.parametres['graphs']):
+ path = os.path.dirname(graph)
+ gname = ''.join(['g', repr(i)])
+ RData = os.path.join(path,'RData.RData')
+ txt += load % (ffr(RData), gname)
+ self.add(txt)
+ self.sources([self.analyse.parent.RscriptsPath['simi']])
+ txt = """
+ merge.type <- 'proto'
+ if (merge.type == 'normal') {
+ ng <- merge.graph(graphs)
+ } else {
+ ng <- merge.graph.proto(graphs)
+ }
+ ngraph <- list(graph=ng, layout=layout.fruchterman.reingold(ng, dim=3), labex.cex=V(ng)$weight)
+ write.graph(ng, "%s", format = 'graphml')
+ """ % ffr(self.parametres['grapheout'])
+ self.add(txt)
+
+
+class TgenSpecScript(PrintRScript):
+
+ def make_script(self):
+ self.packages(['textometry'])
+ txt = """
+ tgen <- read.csv2("%s", row.names = 1, sep = '\\t')
+ """ % ffr(self.parametres['tgeneff'])
+ txt += """
+ tot <- tgen[nrow(tgen), ]
+ result <- NULL
+ tgen <- tgen[-nrow(tgen),]
+ for (i in 1:nrow(tgen)) {
+ mat <- rbind(tgen[i,], tot - tgen[i,])
+ specmat <- specificities(mat)
+ result <- rbind(result, specmat[1,])
+ }
+ colnames(result) <- colnames(tgen)
+ row.names(result) <- rownames(tgen)
+ write.table(result, file = "%s", sep='\\t', col.names = NA)
+ """ % ffr(self.pathout['tgenspec.csv'])
+ self.add(txt)
+
+
+class TgenProfScript(PrintRScript):
+
+ def make_script(self):
+ self.sources([self.analyse.ira.RscriptsPath['chdfunct']])
+ txt = """
+ tgen <- read.csv2("%s", row.names = 1, sep = '\\t')
+ """ % ffr(self.parametres['tgeneff'])
+ txt += """
+ tgenlem <- read.csv2("%s", row.names = 1, sep = '\\t')
+ """ % ffr(self.parametres['tgenlemeff'])
+ txt += """
+ res <- build.prof.tgen(tgen)
+ write.table(res$chi2, file = "%s", sep='\\t', col.names = NA)
+ write.table(res$pchi2, file = "%s", sep='\\t', col.names = NA)
+ """ % (ffr(self.pathout['tgenchi2.csv']), ffr(self.pathout['tgenpchi2.csv']))
+ txt += """
+ reslem <- build.prof.tgen(tgenlem)
+ write.table(reslem$chi2, file = "%s", sep='\\t', col.names = NA)
+ write.table(reslem$pchi2, file = "%s", sep='\\t', col.names = NA)
+ """ % (ffr(self.pathout['tgenlemchi2.csv']), ffr(self.pathout['tgenlempchi2.csv']))
+ self.add(txt)
+
+
+class FreqMultiScript(PrintRScript):
+
+ def make_script(self):
+ self.sources([self.analyse.parent.RscriptsPath['Rgraph']])
+ txt = """
+ freq <- read.csv2("%s", row.names=1, sep='\\t', dec='.')
+ """ % ffr(self.pathout['frequences.csv'])
+ txt += """
+ toplot <- freq[order(freq[,2]) ,2]
+ toplot.names = rownames(freq)[order(freq[,2])]
+ h <- 80 + (20 * nrow(freq))
+ open_file_graph("%s",height=h, width=500)
+ par(mar=c(3,20,3,3))
+ barplot(toplot, names = toplot.names, horiz=TRUE, las =1, col = rainbow(nrow(freq)))
+ dev.off()
+ """ % ffr(self.pathout['barplotfreq.png'])
+ txt += """
+ toplot <- freq[order(freq[,4]) ,4]
+ toplot.names = rownames(freq)[order(freq[,4])]
+ open_file_graph("%s",height=h, width=500)
+ par(mar=c(3,20,3,3))
+ barplot(toplot, names = toplot.names, horiz=TRUE, las =1, col = rainbow(nrow(freq)))
+ dev.off()
+ """ % ffr(self.pathout['barplotrow.png'])
+ self.add(txt)
+ self.write()
+
+
+class LabbeScript(PrintRScript):
+
+ def make_script(self):
+ self.sources([self.analyse.parent.RscriptsPath['distance-labbe.R'],
+ self.analyse.parent.RscriptsPath['Rgraph']])
+ txt = """
+ tab <- read.csv2("%s", header=TRUE, sep=';', row.names=1)
+ """ % (ffr(self.pathout['tableafcm.csv']))
+ txt += """
+ dist.mat <- dist.labbe(tab)
+ dist.mat <- as.dist(dist.mat, upper=F, diag=F)
+ write.table(as.matrix(dist.mat), "%s", sep='\t')
+ library(cluster)
+ library(ape)
+ chd <- hclust(dist.mat, method="ward.D2")
+ open_file_graph("%s", width=1000, height=1000, svg=F)
+ par(cex=1.2)
+ plot.phylo(as.phylo(chd), type='unrooted', lab4ut="axial")
+ dev.off()
+ """ % (ffr(self.pathout['distmat.csv']), ffr(self.pathout['labbe-tree.png']))
+ txt +="""
+ open_file_graph("%s", width=1000, height=1000, svg=F)
+ par(mar=c(10,1,1,10))
+ heatmap(as.matrix(dist.mat), symm = T, distfun=function(x) as.dist(x), margins=c(10,10))
+ dev.off()
+ """ % ffr(self.pathout['labbe-heatmap.png'])
+ txt += """
+ #http://stackoverflow.com/questions/3081066/what-techniques-exists-in-r-to-visualize-a-distance-matrix
+ dst <- data.matrix(dist.mat)
+ dim <- ncol(dst)
+ rn <- row.names(as.matrix(dist.mat))
+ open_file_graph("%s", width=1500, height=1000, svg=F)
+ par(mar=c(10,10,3,3))
+ image(1:dim, 1:dim, dst, axes = FALSE, xlab="", ylab="", col=heat.colors(99), breaks=seq(0.01,1,0.01))
+ axis(1, 1:dim, rn, cex.axis = 0.9, las=3)
+ axis(2, 1:dim, rn, cex.axis = 0.9, las=1)
+ text(expand.grid(1:dim, 1:dim), sprintf("%%0.2f", dst), cex=0.6)
+ dev.off()
+ """ % ffr(self.pathout['labbe-matrix.png'])
+ txt += """
+ library(igraph)
+ g <- graph.adjacency(as.matrix(1-dist.mat), mode="lower", weighted=T)
+ write.graph(g, file="%s", format='graphml')
+ open_file_graph("%s", width=1000, height=1000, svg=F)
+ plot(g)
+ dev.off()
+ E(g)$weight <- 1 - E(g)$weight
+ g <- minimum.spanning.tree(g)
+ E(g)$weight <- 1 - E(g)$weight
+ write.graph(g, file="%s", format='graphml')
+ open_file_graph("%s", width=1000, height=1000, svg=F)
+ plot(g)
+ dev.off()
+ """ % (ffr(self.pathout['graph_tot.graphml']), ffr(self.pathout['graph_tot.png']), ffr(self.pathout['graph_min.graphml']), ffr(self.pathout['graph_min.png']))
+ self.add(txt)
+ self.write()
+
+
+class ChronoChi2Script(PrintRScript):
+
+ def make_script(self):
+ self.sources([self.analyse.parent.RscriptsPath['Rgraph']])
+ print(self.parametres)
+ txt = """
+ inRData <- "%s"
+ dendrof <- "%s"
+ load(inRData)
+ load(dendrof)
+ """ % (ffr(self.pathout['RData.RData']), ffr(self.pathout['dendrogramme.RData']))
+ txt += """
+ svg <- %s
+ """ % self.parametres['svg']
+ txt += """
+ tc <- which(grepl("%s",rownames(chistabletot)))
+ rn <- rownames(chistabletot)[tc]
+ tc <- tc[order(rn)]
+ dpt <- chistabletot[tc,]
+ tot <- afctable[tc,]
+ tcp <- rowSums(tot)
+ ptc <- tcp/sum(tcp)
+ dpt <- t(dpt)
+ dd <- dpt
+ """ % self.parametres['var'].replace('*', "\\\\*")
+ txt += """
+ classes <- n1[,ncol(n1)]
+ tcl <- table(classes)
+ if ('0' %in% names(tcl)) {
+ to.vire <- which(names(tcl) == '0')
+ tcl <- tcl[-to.vire]
+ }
+ tclp <- tcl/sum(tcl)
+ #chi2 colors
+ library(ape)
+ k <- 1e-02
+ lcol <- NULL
+ lk <- k
+ for (i in 1:5) {
+ lcol <- c(lcol, qchisq(1-k,1))
+ k <- k/10
+ lk <- c(lk,k)
+ }
+ lcol <- c(3.84, lcol)
+ lcol <- c(-Inf,lcol)
+ lcol <- c(lcol, Inf)
+ lk <- c(0.05,lk)
+ breaks <- lcol
+ alphas <- seq(0,1, length.out=length(breaks))
+ clod <- rev(as.numeric(tree.cut1$tree.cl$tip.label))
+ #end
+ """
+ txt += """
+ open_file_graph("%s", w=%i, h=%i, svg=svg)
+ """ % (ffr(self.parametres['tmpgraph']), self.parametres['width'], self.parametres['height'])
+ txt += """
+ par(mar=c(3,3,3,3))
+ mat.graphic <- matrix(c(rep(1,nrow(dd)),c(2:(nrow(dd)+1))), ncol=2)
+ mat.graphic <- rbind(mat.graphic, c(max(mat.graphic) + 1 , max(mat.graphic) + 2))
+ hauteur <- tclp[clod] * 0.9
+ heights.graphic <- append(hauteur, 0.1)
+ layout(mat.graphic, heights=heights.graphic, widths=c(0.15,0.85))
+ par(mar=c(0,0,0,0))
+ tree.toplot <- tree.cut1$tree.cl
+ num.label <- as.numeric(tree.cut1$tree.cl$tip.label)
+ col.tree <- rainbow(length(num.label))[num.label]
+ #tree.toplot$tip.label <- paste('classe ', tree.toplot$tip.label)
+ plot.phylo(tree.toplot,label.offset=0.1, cex=1.1, no.margin=T, tip.color = col.tree)
+ for (i in clod) {
+ print(i)
+ par(mar=c(0,0,0,0))
+ lcol <- cut(dd[i,], breaks, include.lowest=TRUE)
+ ulcol <- names(table(lcol))
+ lcol <- as.character(lcol)
+ for (j in 1:length(ulcol)) {
+ lcol[which(lcol==ulcol[j])] <- j
+ }
+ lcol <- as.numeric(lcol)
+ mcol <- rainbow(nrow(dd))[i]
+ last.col <- NULL
+ for (k in alphas) {
+ last.col <- c(last.col, rgb(r=col2rgb(mcol)[1]/255, g=col2rgb(mcol)[2]/255, b=col2rgb(mcol)[3]/255, a=k))
+ }
+ #print(last.col)
+ barplot(rep(1,ncol(dd)), width=ptc, names.arg=FALSE, axes=FALSE, col=last.col[lcol], border=rgb(r=0, g=0, b=0, a=0.3))
+ }
+ plot(0,type='n',axes=FALSE,ann=FALSE)
+ label.coords <- barplot(rep(1, ncol(dd)), width=ptc, names.arg = F, las=2, axes=F, ylim=c(0,1), plot=T, col='white')
+ text(x=label.coords, y=0.5, labels=rn[order(rn)], srt=90)
+ dev.off()
+ """
+ self.add(txt)
+ self.write()
+
+
+class ChronoPropScript(PrintRScript):
+
+ def make_script(self):
+ self.sources([self.analyse.parent.RscriptsPath['Rgraph']])
+ print(self.parametres)
+ txt = """
+ inRData <- "%s"
+ dendrof <- "%s"
+ load(inRData)
+ load(dendrof)
+ """ % (ffr(self.pathout['RData.RData']), ffr(self.pathout['dendrogramme.RData']))
+ txt += """
+ svg <- %s
+ """ % self.parametres['svg']
+ txt += """
+ tc <- which(grepl("%s",rownames(chistabletot)))
+ rn <- rownames(chistabletot)[tc]
+ tc <- tc[order(rn)]
+ dpt <- chistabletot[tc,]
+ tot <- afctable[tc,]
+ tcp <- rowSums(tot)
+ ptc <- tcp/sum(tcp)
+ dpt <- t(dpt)
+ dd <- dpt
+ """ % self.parametres['var'].replace('*', "\\\\*")
+ txt += """
+ classes <- n1[,ncol(n1)]
+ tcl <- table(classes)
+ if ('0' %in% names(tcl)) {
+ to.vire <- which(names(tcl) == '0')
+ tcl <- tcl[-to.vire]
+ }
+ tclp <- tcl/sum(tcl)
+ """
+ txt += """
+ open_file_graph("%s", w=%i, h=%i, svg=svg)
+ """ % (ffr(self.parametres['tmpgraph']), self.parametres['width'], self.parametres['height'])
+ txt+= """
+ ptt <- prop.table(as.matrix(tot), 1)
+ par(mar=c(10,2,2,2))
+ barplot(t(ptt)[as.numeric(tree.cut1$tree.cl$tip.label),], col=rainbow(ncol(ptt))[as.numeric(tree.cut1$tree.cl$tip.label)], width=ptc, las=3, space=0.05, cex.axis=0.7, border=NA)
+ dev.off()
+ """
+ self.add(txt)
+ self.write()
+
+
+class ChronoggScript(PrintRScript):
+
+ def make_script(self):
+ self.sources([self.analyse.parent.RscriptsPath['Rgraph']])
+ print(self.parametres)
+ txt = """
+ library(ggplot2)
+ inRData <- "%s"
+ dendrof <- "%s"
+ load(inRData)
+ load(dendrof)
+ """ % (ffr(self.pathout['RData.RData']), ffr(self.pathout['dendrogramme.RData']))
+ txt += """
+ svg <- %s
+ """ % self.parametres['svg']
+ txt += """
+ tc <- which(grepl("%s",rownames(chistabletot)))
+ rn <- rownames(chistabletot)[tc]
+ tc <- tc[order(rn)]
+ dpt <- chistabletot[tc,]
+ tot <- afctable[tc,]
+ tcp <- rowSums(tot)
+ ptc <- tcp/sum(tcp)
+ dpt <- t(dpt)
+ dd <- dpt
+ """ % self.parametres['var'].replace('*', "\\\\*")
+ txt += """
+ classes <- n1[,ncol(n1)]
+ tcl <- table(classes)
+ if ('0' %in% names(tcl)) {
+ to.vire <- which(names(tcl) == '0')
+ tcl <- tcl[-to.vire]
+ }
+ tclp <- tcl/sum(tcl)
+ ptt <- prop.table(as.matrix(tot), 1)
+ ptt <- ptt[,as.numeric(tree.cut1$tree.cl$tip.label)]
+ rownames(ptt) <- cumsum(ptc)
+ nptt<-as.data.frame(as.table(ptt))
+ nptt[,1]<-as.numeric(as.character(nptt[,1]))
+ col <- rainbow(ncol(ptt))[as.numeric(tree.cut1$tree.cl$tip.label)]
+ """
+ txt += """
+ open_file_graph("%s", w=%i, h=%i, svg=svg)
+ """ % (ffr(self.parametres['tmpgraph']), self.parametres['width'], self.parametres['height'])
+ txt+= """
+ par(mar=c(10,2,2,2))
+ gg <- ggplot(data=nptt, aes(x=Var1,y=Freq,fill=Var2)) + geom_area(alpha=1 , size=0.5, colour="black")
+ gg + scale_fill_manual(values=col)
+ dev.off()
+ """