#License: GNU/GPL
import tempfile
-from chemins import ffr
+from chemins import ffr, PathOut
import os
import locale
from datetime import datetime
self.pathout = analyse.pathout
self.analyse = analyse
self.parametres = analyse.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 add(self, txt) :
self.script = '\n'.join([self.script, txt])
-
+
def defvar(self, name, value) :
self.add(' <- '.join([name, value]))
data1 <- as(data1, "dgCMatrix")
row.names(data1) <- 1:nrow(data1)
""" % ffr(DicoPath['TableUc1'])
-
+
if classif_mode == 0:
txt += """
data2 <- readMM("%s")
row.names(data2) <- 1:nrow(data2)
""" % ffr(DicoPath['TableUc2'])
txt += """
- chd1<-CHD(data1, x = nbt, mode.patate = mode.patate, svd.method = svd.method, libsvdc.path = libsvdc.path)
- """
-
+ 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'])
+
if classif_mode == 0:
txt += """
- chd2<-CHD(data2, x = nbt, mode.patate = mode.patate, svd.method = svd.method, libsvdc.path = libsvdc.path)
- """
-
+ log2 <- "%s"
+ chd2<-CHD(data2, x = nbt, mode.patate = mode.patate, svd.method =
+ svd.method, libsvdc.path = libsvdc.path) log.file = log2)
+ """ % ffr(DicoPath['log-chd2.txt'])
+
txt += """
#lecture des uce
listuce1<-read.csv2("%s")
""" % ffr(DicoPath['listeuce1'])
-
+
if classif_mode == 0:
txt += """
listuce2<-read.csv2("%s")
""" % ffr(DicoPath['listeuce2'])
-
+
txt += """
rm(data1)
"""
-
+
if classif_mode == 0:
txt += """
rm(data2)
write.csv2(n1, file="%s")
rm(n1)
""" % (classif_mode, mincl, ffr(DicoPath['uce']), ffr(DicoPath['n1.csv']))
-
+
txt += """
tree.tot1 <- make_tree_tot(chd1)
# open_file_graph("%s", widt = 600, height=400)
# plot(tree.tot1$tree.cl)
# dev.off()
""" % ffr(DicoPath['arbre1'])
-
+
if classif_mode == 0:
txt += """
classeuce2 <- chd.result$cuce2
# open_file_graph("%s", width = 600, height=400)
# plot(tree.tot2$tree.cl)
# dev.off()
- """ % ffr(DicoPath['arbre2'] )
-
+ """ % ffr(DicoPath['arbre2'] )
+
txt += """
tree.cut1 <- make_dendro_cut_tuple(tree.tot1$dendro_tuple, chd.result$coord_ok, classeuce1, 1, nbt)
save(tree.cut1, file="%s")
-
+
open_file_graph("%s", width = 600, height=400)
plot.dendropr(tree.cut1$tree.cl,classes, histo=TRUE)
open_file_graph("%s", width = 600, height=400)
plot(tree.cut1$dendro_tot_cl)
dev.off()
""" % (ffr(DicoPath['Rdendro']), ffr(DicoPath['dendro1']), ffr(DicoPath['arbre1']))
-
+
if classif_mode == 0:
txt += """
tree.cut2 <- make_dendro_cut_tuple(tree.tot2$dendro_tuple, chd.result$coord_ok, classeuce2, 2, nbt)
plot(tree.cut2$dendro_tot_cl)
dev.off()
""" % (ffr(DicoPath['dendro2']), ffr(DicoPath['arbre2']))
-
+
txt += """
-
+
#save.image(file="%s")
""" % (ffr(DicoPath['RData']))
-
+
fileout = open(DicoPath['Rchdtxt'], 'w')
fileout.write(txt)
fileout.close()
fileout.write(txt)
fileout.close()
-def AlcesteTxtProf(DictChdTxtOut, RscriptsPath, clnb, taillecar):
+def ReinertTxtProf(DictChdTxtOut, RscriptsPath, clnb, taillecar):
txt = "clnb<-%i\n" % clnb
txt += """
source("%s")
self.packages(['igraph', 'proxy', 'Matrix'])
self.sources([self.analyse.parent.RscriptsPath['simi'], self.analyse.parent.RscriptsPath['Rgraph']])
txt = ''
- if not self.parametres['keep_coord'] and not self.parametres['type'] == 'simimatrix':
+ if not self.parametres['keep_coord'] and not (self.parametres['type'] == 'simimatrix' or self.parametres['type'] == 'simiclustermatrix') :
txt += """
dm.path <- "%s"
cn.path <- "%s"
index <- which(colnames(dm) == forme)
}
"""
- elif not self.parametres['keep_coord'] and self.parametres['type'] == 'simimatrix' :
+ elif not self.parametres['keep_coord'] and (self.parametres['type'] == 'simimatrix' or self.parametres['type'] == 'simiclustermatrix'):
txt += """
dm.path <- "%s"
selected.col <- "%s"
if self.parametres['seuil_ok'] : seuil = str(self.parametres['seuil'])
else : seuil = 'NULL'
-
+
+ if not self.parametres.get('edgecurved', False) :
+ ec = 'FALSE'
+ else :
+ ec = 'TRUE'
+
+ txt += """
+ edge.curved <- %s
+ """ % ec
+
cols = str(self.parametres['cols']).replace(')',', max=255)')
cola = str(self.parametres['cola']).replace(')',',max=255)')
seuil <- %s
if (!is.null(seuil)) {
if (method!='cooc') {
- seuil <- seuil/100
+ seuil <- seuil/1000
}
}
""" % seuil
"""
else :
#print self.parametres
- if (self.parametres['type'] == 'clustersimitxt' and self.parametres.get('tmpchi', False)) or (self.parametres['type'] == 'simimatrix' and 'tmpchi' in self.parametres):
+ if (self.parametres['type'] == 'clustersimitxt' and self.parametres.get('tmpchi', False)) or (self.parametres['type'] in ['simimatrix','simiclustermatrix'] and 'tmpchi' in self.parametres):
txt += """
lchi <- read.table("%s")
lchi <- lchi[,1]
txt += """
lchi <- lchi[sel.col]
"""
- if self.parametres['type'] == 'clustersimitxt' and self.parametres.get('cexfromchi', False) :
+ if self.parametres['type'] in ['clustersimitxt', 'simimatrix', 'simiclustermatrix'] and self.parametres.get('cexfromchi', False) :
txt += """
label.cex <- norm.vec(lchi, vcexminmax[1], vcexminmax[2])
"""
label.cex <- graph.simi$label.cex
}
"""
- if (self.parametres['type'] == 'clustersimitxt' or self.parametres['type'] == 'simimatrix') and self.parametres.get('sfromchi', False):
+ if (self.parametres['type'] in ['clustersimitxt', 'simimatrix', 'simiclustermatrix']) and self.parametres.get('sfromchi', False):
txt += """
vertex.size <- norm.vec(lchi, minmaxeff[1], minmaxeff[2])
if (!length(vertex.size)) vertex.size <- 0
vertex.label.color <- colm[membership(com)]
}
}
- 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, svg = svg)
+ 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']))
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')
dev.off()
- """ % (self.analyse.pathout['table.csv'], self.analyse.pathout['proto.png'], self.parametres['limfreq'], self.parametres['limrang'], self.parametres['typegraph'])
+ """ % (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()
txt = """
"""
+class MergeGraphes(PrintRScript) :
+ def __init__(self, parametres):
+ self.script = u"#Script genere par IRaMuTeQ - %s\n" % datetime.now().ctime()
+ self.pathout = PathOut()
+ self.parametres = parametres
+ self.scriptout = self.pathout['temp']
+
+ 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['lgraphes']) :
+ path = os.path.dirname(graph)
+ gname = ''.join(['g', `i`])
+ RData = os.path.join(path,'RData.RData')
+ txt += load % (ffr(RData), gname)
+ self.add(txt)
+ self.sources([self.analyse.parent.RscriptsPath['simi']])
+ txt = """
+ ng <- merge.graph(graphs)
+ ngraph <- list(graph=ng, layout=layout.fruchterman.reingold(ng, dim=3), labex.cex=V(ng)$weight)
+ write.graph(ng, "%s", format = 'graphml')
+ """ % ffr(self.parametres['grapheout'])
+ self.add(txt)
+
class TgenSpecScript(PrintRScript):
def make_script(self):
self.packages(['textometry'])
colnames(result) <- colnames(tgen)
row.names(result) <- rownames(tgen)
write.table(result, file = "%s", sep='\\t', col.names = NA)
- """ % self.pathout['tgenspec.csv']
+ """ % ffr(self.pathout['tgenspec.csv'])
+ self.add(txt)
+
+class TgenProfScript(PrintRScript):
+ def make_script(self):
+ self.sources([self.analyse.ira.RscriptsPath['chdfunct']])
+ txt = """
+ tgen <- read.csv2("%s", row.names = 1, sep = '\\t')
+ """ % ffr(self.parametres['tgeneff'])
+ txt += """
+ tgenlem <- read.csv2("%s", row.names = 1, sep = '\\t')
+ """ % ffr(self.parametres['tgenlemeff'])
+ txt += """
+ res <- build.prof.tgen(tgen)
+ write.table(res$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)
+ """ % (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()
+ """ % (self.pathout['distmat.csv'], self.pathout['dist-labbe.png'])
+ self.add(txt)
+ self.write()
+
+