log = logging.getLogger('iramuteq.printRscript')
class PrintRScript :
- def __init__ (self, analyse):
+ def __init__ (self, analyse, parametres = None):
log.info('Rscript')
self.pathout = analyse.pathout
self.analyse = analyse
- self.parametres = analyse.parametres
+ if parametres is None :
+ self.parametres = analyse.parametres
+ else :
+ self.parametres = parametres
#self.scriptout = ffr(self.pathout['lastRscript.R'])
self.scriptout = self.pathout['temp']
self.script = u"#Script genere par IRaMuTeQ - %s\n" % datetime.now().ctime()
#
-def RchdTxt(DicoPath, RscriptPath, mincl, classif_mode, nbt = 9, svdmethod = 'svdR', libsvdc = False, libsvdc_path = None, R_max_mem = False, mode_patate = False):
+def RchdTxt(DicoPath, RscriptPath, mincl, classif_mode, nbt = 9, svdmethod = 'svdR', libsvdc = False, libsvdc_path = None, R_max_mem = False, mode_patate = False, nbproc=1):
txt = """
source("%s")
source("%s")
""" % ffr(DicoPath['TableUc2'])
txt += """
log1 <- "%s"
- chd1<-CHD(data1, x = nbt, mode.patate = mode.patate, svd.method =
- svd.method, libsvdc.path = libsvdc.path)#, log.file = log1)
- """ % ffr(DicoPath['log-chd1.txt'])
+ #print('FIXME : source newCHD')
+ #source('/home/pierre/workspace/iramuteq/Rscripts/newCHD.R')
+ #nbproc <- %s
+ #chd1<-CHD(data1, x = nbt, mode.patate = mode.patate, svd.method = svd.method, libsvdc.path = libsvdc.path, find='matrix', select.next='size', sample=20, amp=500, proc.nb=nbproc)
+ chd1<-CHD(data1, x = nbt, mode.patate = mode.patate, svd.method = svd.method, libsvdc.path = libsvdc.path)#, log.file = log1)
+ """ % (ffr(DicoPath['log-chd1.txt']), nbproc)
if classif_mode == 0:
txt += """
txt += """
classif_mode <- %i
mincl <- %i
+ if (mincl == 0) {mincl <- round(nrow(chd1$n1)/(nbt+1))}
uceout <- "%s"
+ write.csv2(chd1$n1, file="%s")
if (classif_mode == 0) {
chd.result <- Rchdtxt(uceout, chd1, chd2 = chd2, mincl = mincl,classif_mode = classif_mode, nbt = nbt)
+ classeuce1 <- chd.result$cuce1
+ tree.tot1 <- make_tree_tot(chd1)
+ tree.cut1 <- make_dendro_cut_tuple(tree.tot1$dendro_tuple, chd.result$coord_ok, classeuce1, 1, nbt)
+
} else {
- chd.result <- Rchdtxt(uceout, chd1, chd2 = chd1, mincl = mincl,classif_mode = classif_mode, nbt = nbt)
+ #chd.result <- Rchdtxt(uceout, chd1, chd2 = chd1, mincl = mincl,classif_mode = classif_mode, nbt = nbt)
+ tree.tot1 <- make_tree_tot(chd1)
+ terminales <- find.terminales(chd1$n1, chd1$list_mere, chd1$list_fille, mincl)
+ tree.cut1 <- make.classes(terminales, chd1$n1, tree.tot1$tree.cl, chd1$list_fille)
+ write.csv2(tree.cut1$n1, uceout)
+ chd.result <- tree.cut1
}
- n1 <- chd.result$n1
- classeuce1 <- chd.result$cuce1
- classes<-n1[,ncol(n1)]
- write.csv2(n1, file="%s")
- rm(n1)
- """ % (classif_mode, mincl, ffr(DicoPath['uce']), ffr(DicoPath['n1.csv']))
+ classes<-chd.result$n1[,ncol(chd.result$n1)]
+ write.csv2(chd.result$n1, file="%s")
+ """ % (classif_mode, mincl, ffr(DicoPath['uce']), ffr(DicoPath['n1-1.csv']), ffr(DicoPath['n1.csv']))
txt += """
- tree.tot1 <- make_tree_tot(chd1)
+# tree.tot1 <- make_tree_tot(chd1)
# open_file_graph("%s", widt = 600, height=400)
# plot(tree.tot1$tree.cl)
# dev.off()
""" % ffr(DicoPath['arbre2'] )
txt += """
- tree.cut1 <- make_dendro_cut_tuple(tree.tot1$dendro_tuple, chd.result$coord_ok, classeuce1, 1, nbt)
- save(tree.cut1, file="%s")
+ save(tree.cut1, file="%s")
open_file_graph("%s", width = 600, height=400)
plot.dendropr(tree.cut1$tree.cl,classes, histo=TRUE)
dataet<-read.csv2("%s", header = FALSE, sep = ';',quote = '\"', row.names = 1, na.strings = 'NA')
""" % (ffr(DictChdTxtOut['Contout']), ffr(DictChdTxtOut['ContSupOut']), ffr(DictChdTxtOut['ContEtOut']))
txt += """
-tablesqrpact<-BuildProf(as.matrix(dataact),n1,clnb)
-tablesqrpsup<-BuildProf(as.matrix(datasup),n1,clnb)
-tablesqrpet<-BuildProf(as.matrix(dataet),n1,clnb)
+print('ATTENTION NEW BUILD PROF')
+#tablesqrpact<-BuildProf(as.matrix(dataact),n1,clnb)
+#tablesqrpsup<-BuildProf(as.matrix(datasup),n1,clnb)
+#tablesqrpet<-BuildProf(as.matrix(dataet),n1,clnb)
+tablesqrpact<-new.build.prof(as.matrix(dataact),n1,clnb)
+tablesqrpsup<-new.build.prof(as.matrix(datasup),n1,clnb)
+tablesqrpet<-new.build.prof(as.matrix(dataet),n1,clnb)
+
"""
txt += """
PrintProfile(n1,tablesqrpact[4],tablesqrpet[4],tablesqrpact[5],tablesqrpet[5],clnb,"%s","%s",tablesqrpsup[4],tablesqrpsup[5])
if self.param['svg'] : svg = 'TRUE'
else : svg = 'FALSE'
+ if self.param['typegraph'] == 4 :
+ nodesfile = os.path.join(os.path.dirname(self.fileout),'nodes.csv')
+ edgesfile = os.path.join(os.path.dirname(self.fileout),'edges.csv')
+ else :
+ nodesfile = 'NULL'
+ edgesfile = 'NULL'
+
with open(self.RscriptsPath['afc_graph'], 'r') as f:
txt = f.read()
# self.DictPathOut['RData'], \
scripts = txt % (ffr(self.RscriptsPath['Rgraph']),\
self.param['typegraph'], \
+ edgesfile, nodesfile, \
self.param['what'], \
self.param['facteur'][0],\
self.param['facteur'][1], \
height <- %i
open_file_graph("%s",width = width, height = height, svg = %s)
par(mar=c(0,0,0,0))
- layout(matrix(c(1,2),1,2, byrow=TRUE),widths=c(3,lcm(7)))
+ layout(matrix(c(1,2),1,2, byrow=TRUE),widths=c(3,lcm(12)))
par(mar=c(8,4,1,0))
yp = ifelse(length(toinf), 0.2, 0)
ym = ifelse(length(tominf), 0.2, 0)
else :
txt += """
word <- FALSE
+ index <- NULL
"""
txt += """
dm <-readMM(dm.path)
- cn <- read.table(cn.path, sep='\t', quote='"')
+ cn <- read.table(cn.path, sep="\t", quote='"')
colnames(dm) <- cn[,1]
if (file.exists(selected.col)) {
sel.col <- read.csv2(selected.col, header = FALSE)
txt += """
load("%s")
""" % ffr(self.pathout['RData.RData'])
-
+
if self.parametres['coeff'] == 0 :
method = 'cooc'
if not self.parametres['keep_coord'] :
method <- 'cooc'
mat <- make.a(dm)
"""
+ elif self.analyse.indices[self.parametres['coeff']] == 'Jaccard' :
+ method = 'Jaccard'
+ if not self.parametres['keep_coord'] :
+ txt += """
+ method <- 'Jaccard'
+ mat <- sparse.jaccard(dm)
+ """
else :
if not self.parametres['keep_coord'] :
txt += """
method <- 'binomial'
mat <- binom.sim(dm)
"""
- elif self.parametres['coeff'] != 0 :
+ elif self.parametres['coeff'] != 0 and self.analyse.indices[self.parametres['coeff']] != 'Jaccard':
method = self.analyse.indices[self.parametres['coeff']]
if not self.parametres['keep_coord'] :
txt += """
txt += """
mat <- graph.word(mat, index)
cs <- colSums(mat)
- if (length(cs)) mat <- mat[,-which(cs==0)]
+ if (length(which(cs==0))) mat <- mat[,-which(cs==0)]
rs <- rowSums(mat)
- if (length(rs)) mat <- mat[-which(rs==0),]
- if (length(cs)) dm <- dm[, -which(cs==0)]
+ if (length(which(rs==0))) mat <- mat[-which(rs==0),]
+ if (length(which(cs==0))) dm <- dm[,-which(cs==0)]
+ if (word) {
+ index <- which(colnames(mat)==forme)
+ }
"""
if self.parametres['layout'] == 0 : layout = 'random'
if self.parametres['layout'] == 2 : layout = 'frutch'
if self.parametres['layout'] == 3 : layout = 'kawa'
if self.parametres['layout'] == 4 : layout = 'graphopt'
+ if self.parametres['layout'] == 5 : layout = 'spirale'
+ if self.parametres['layout'] == 6 : layout = 'spirale3D'
self.filename=''
while os.path.exists(os.path.join(dirout,'web_'+str(graphnb))):
graphnb +=1
self.filename = ffr(os.path.join(dirout,'web_'+str(graphnb)))
- os.mkdir(self.filename)
+ os.mkdir(self.filename)
self.filename = os.path.join(self.filename, 'gexf.gexf')
if self.parametres['type_graph'] == 4 :
graphnb = 1
txt += """
eff <- colSums(dm)
x <- list(mat = mat, eff = eff)
- graph.simi <- do.simi(x, method='%s', seuil = seuil, p.type = '%s', layout.type = '%s', max.tree = %s, coeff.vertex=%s, coeff.edge = %s, minmaxeff = minmaxeff, vcexminmax = vcexminmax, cex = cex, coords = coords, communities = communities, halo = halo)
+ graph.simi <- do.simi(x, method='%s', seuil = seuil, p.type = '%s', layout.type = '%s', max.tree = %s, coeff.vertex=%s, coeff.edge = %s, minmaxeff = minmaxeff, vcexminmax = vcexminmax, cex = cex, coords = coords, communities = communities, halo = halo, index.word=index)
""" % (method, type, layout, arbremax, coeff_tv, coeff_te)
if self.parametres.get('bystar',False) :
""" % svg
txt += """
vertex.col <- cols
+ col.from.proto <- F
+ if (col.from.proto) {
+ proto.col <- read.table('/tmp/matcol.csv')
+ v.proto.names <- make.names(proto.col[,1])
+ v.proto.col <- as.character(proto.col[,2])
+ v.proto.col[which(v.proto.col=='black')] <- 'yellow'
+ v.names <- V(graph.simi$graph)$name
+ num.color <- sapply(v.names, function(x) {if (x %%in%% v.proto.names) {v.proto.col[which(v.proto.names==x)]} else {'pink'}})
+ vertex.col <- num.color
+ V(graph.simi$graph)$proto.color <- vertex.col
+ }
if (!is.null(graph.simi$com)) {
com <- graph.simi$com
colm <- rainbow(length(com))
vertex.label.color <- colm[membership(com)]
}
}
+ if (!length(graph.simi$elim)==0) {
+ vertex.label.color <- vertex.label.color[-graph.simi$elim]
+ if (length(label.cex > 1)) {
+ label.cex <- label.cex[-graph.simi$elim]
+ }
+ }
coords <- plot.simi(graph.simi, p.type='%s',filename="%s", vertex.label = label.v, edge.label = label.e, vertex.col = vertex.col, vertex.label.color = vertex.label.color, vertex.label.cex=label.cex, vertex.size = vertex.size, edge.col = cola, leg=leg, width = width, height = height, alpha = alpha, movie = film, edge.curved = edge.curved, svg = svg)
save.image(file="%s")
""" % (type, self.filename, ffr(self.pathout['RData']))
}
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')
+ 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.add(txt)
self.sources([self.analyse.parent.RscriptsPath['simi']])
txt = """
- ng <- merge.graph(graphs)
+ 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)$weight)
write.graph(ng, "%s", format = 'graphml')
""" % ffr(self.parametres['grapheout'])
txt +="""
open_file_graph("%s", width=1000, height=1000, svg=F)
par(mar=c(10,1,1,10))
- heatmap(as.matrix(dist.mat), symm = T, distfun=function(x) as.dist(x))
+ heatmap(as.matrix(dist.mat), symm = T, distfun=function(x) as.dist(x), margins=c(10,10))
dev.off()
""" % ffr(self.pathout['labbe-heatmap.png'])
txt += """
rn <- row.names(as.matrix(dist.mat))
open_file_graph("%s", width=1500, height=1000, svg=F)
par(mar=c(10,10,3,3))
- image(1:dim, 1:dim, dst, axes = FALSE, xlab="", ylab="")
+ image(1:dim, 1:dim, dst, axes = FALSE, xlab="", ylab="", col=heat.colors(99), breaks=seq(0.01,1,0.01))
axis(1, 1:dim, rn, cex.axis = 0.9, las=3)
axis(2, 1:dim, rn, cex.axis = 0.9, las=1)
text(expand.grid(1:dim, 1:dim), sprintf("%%0.2f", dst), cex=0.6)
dev.off()
""" % ffr(self.pathout['labbe-matrix.png'])
+ txt += """
+ library(igraph)
+ g <- graph.adjacency(as.matrix(1-dist.mat), mode="lower", weighted=T)
+ write.graph(g, file="%s", format='graphml')
+ open_file_graph("%s", width=1000, height=1000, svg=F)
+ plot(g)
+ dev.off()
+ E(g)$weight <- 1 - E(g)$weight
+ g <- minimum.spanning.tree(g)
+ E(g)$weight <- 1 - E(g)$weight
+ write.graph(g, file="%s", format='graphml')
+ open_file_graph("%s", width=1000, height=1000, svg=F)
+ plot(g)
+ dev.off()
+ """ % (ffr(self.pathout['graph_tot.graphml']), ffr(self.pathout['graph_tot.png']), ffr(self.pathout['graph_min.graphml']), ffr(self.pathout['graph_min.png']))
self.add(txt)
self.write()
tree.toplot <- tree.cut1$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, x.lim=20, tip.color = col.tree)
+ #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))
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(u'*', u"\\\\*")
+ 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()
+ """
+ self.add(txt)
+ self.write()
+
+class DendroScript(PrintRScript) :
+ def make_script(self) :
+ if self.parametres['svg'] :
+ typefile = '.svg'
+ else :
+ typefile = '.png'
+ fileout = self.parametres['fileout']
+ width = self.parametres['width']
+ height = self.parametres['height']
+ type_dendro = self.parametres['dendro_type']
+ if self.parametres['taille_classe'] :
+ tclasse = 'TRUE'
+ else :
+ tclasse = 'FALSE'
+ if self.parametres['color_nb'] == 0 :
+ bw = 'FALSE'
+ else :
+ bw = 'TRUE'
+ if self.parametres['type_tclasse'] == 0 :
+ histo='FALSE'
+ else :
+ histo = 'TRUE'
+ if self.parametres['svg'] :
+ svg = 'TRUE'
+ else :
+ svg = 'FALSE'
+ dendro_path = self.pathout['Rdendro']
+ classe_path = self.pathout['uce']
+ txt = """
+ library(ape)
+ load("%s")
+ source("%s")
+ classes <- read.csv2("%s", row.names=1)
+ classes <- classes[,1]
+ """ % (ffr(dendro_path), ffr(self.parametres['Rgraph']), ffr(classe_path))
+ if self.parametres['dendro'] == 'simple' :
+ txt += """
+ open_file_graph("%s", width=%i, height=%i, svg=%s)
+ plot.dendropr(tree.cut1$tree.cl, classes, type.dendro="%s", histo=%s, bw=%s, lab=NULL, tclasse=%s)
+ """ % (ffr(fileout), width, height, svg, type_dendro, histo, bw, tclasse)
+ elif self.parametres['dendro'] == 'texte' :
+ txt += """
+ load("%s")
+ source("%s")
+ if (is.null(debsup)) {
+ debsup <- debet
+ }
+ chistable <- chistabletot[1:(debsup-1),]
+ """ % (ffr(self.pathout['RData.RData']), ffr(self.parametres['Rgraph']))
+ if self.parametres.get('translation', False) :
+ txt += """
+ rn <- read.csv2("%s", header=FALSE, sep='\t')
+ rnchis <- row.names(chistable)
+ commun <- intersect(rnchis, unique(rn[,2]))
+ idrnchis <- sapply(commun, function(x) {which(rnchis==x)})
+ idrn <- sapply(commun, function(x) {which(as.vector(rn[,2])==x)[1]})
+ rownames(chistable)[idrnchis] <- as.vector(rn[idrn,1])
+ """ % ffr(self.parametres['translation'])
+ txt += """
+ open_file_graph("%s", width=%i, height=%i, svg = %s)
+ plot.dendro.prof(tree.cut1$tree.cl, classes, chistable, nbbycl = 60, type.dendro="%s", bw=%s, lab=NULL)
+ """ % (ffr(fileout), width, height, svg, type_dendro, bw)
+ elif self.parametres['dendro'] == 'cloud' :
+ txt += """
+ load("%s")
+ source("%s")
+ if (is.null(debsup)) {
+ debsup <- debet
+ }
+ chistable <- chistabletot[1:(debsup-1),]
+ open_file_graph("%s", width=%i, height=%i, svg=%s)
+ plot.dendro.cloud(tree.cut1$tree.cl, classes, chistable, nbbycl = 300, type.dendro="%s", bw=%s, lab=NULL)
+ """ % (ffr(self.pathout['RData.RData']), ffr(self.parametres['Rgraph']), ffr(fileout), width, height, svg, type_dendro, bw)
+ self.add(txt)
+ self.write()
+
+
+class ReDoProfScript(PrintRScript) :
+ def make_script(self) :
+ self.sources([self.analyse.parent.RscriptsPath['chdfunct.R']])
+ print self.parametres
projects / iramuteq / blobdiff