rm(data2)
"""
txt += """
- chd.result <- Rchdtxt("%s",mincl=%i,classif_mode=%i, nbt = nbt)
+ classif_mode <- %i
+ mincl <- %i
+ uceout <- "%s"
+ if (classif_mode == 0) {
+ chd.result <- Rchdtxt(uceout, chd1, chd2 = chd2, mincl = mincl,classif_mode = classif_mode, nbt = nbt)
+ } else {
+ chd.result <- Rchdtxt(uceout, chd1, chd2 = chd1, mincl = mincl,classif_mode = classif_mode, nbt = nbt)
+ }
n1 <- chd.result$n1
classeuce1 <- chd.result$cuce1
classeuce2 <- chd.result$cuce2
- """ % (DicoPath['uce'], mincl, classif_mode)
+ """ % (classif_mode, mincl, DicoPath['uce'])
txt += """
tree.tot1 <- make_tree_tot(chd1)
cn.path <- "%s"
selected.col <- "%s"
""" % (self.pathout['mat01.csv'], self.pathout['actives.csv'], self.pathout['selected.csv'])
+ if 'word' in self.parametres :
+ txt += """
+ word <- TRUE
+ index <- %i + 1
+ """ % self.parametres['word']
+ else :
+ txt += """
+ word <- FALSE
+ """
txt += """
dm <-readMM(dm.path)
cn <- read.table(cn.path, sep='\t', quote='"')
colnames(dm) <- cn[,1]
- sel.col <- read.csv2(selected.col)
- dm <- dm[, sel.col[,1] + 1]
+ sel.col <- read.csv2(selected.col, header = FALSE)
+ sel.col <- sel.col[,1] + 1
+ if (!word) {
+ dm <- dm[, sel.col]
+ } else {
+ forme <- colnames(dm)[index]
+ if (!index %in% sel.col) {
+ sel.col <- append(sel.col, index)
+ }
+ dm <- dm[, sel.col]
+ index <- which(colnames(dm) == forme)
+ }
"""
+
else :
txt += """
load("%s")
mat[is.na(mat)] <- 0
mat[is.infinite(mat)] <- 0
"""
+ if 'word' in self.parametres and not self.parametres['keep_coord'] :
+ txt += """
+ mat <- graph.word(mat, index)
+ cs <- colSums(mat)
+ if (length(cs)) 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 self.parametres['layout'] == 0 : layout = 'random'
if self.parametres['layout'] == 1 : layout = 'circle'
if self.parametres['layout'] == 2 : layout = 'frutch'
vertex.size <- NULL
"""
else :
- #FIXME
- tmpchi = False
- if tmpchi :
+ if self.parametres['type'] == 'clustersimitxt' :
txt += """
lchi <- read.table("%s")
lchi <- lchi[,1]
- """ % ffr(tmpchi)
- if 'selected_col' in dir(self.tableau) :
- txt += """
- lchi <- lchi[c%s+1]
- """ % datas
- if tmpchi and self.parametres.get('cexfromchi', False) :
+ """ % ffr(self.parametres['tmpchi'])
+ txt += """
+ lchi <- lchi[sel.col]
+ """
+ if self.parametres['type'] == 'clustersimitxt' and self.parametres.get('cexfromchi', False) :
txt += """
label.cex <- norm.vec(lchi, vcexminmax[1], vcexminmax[2])
"""
label.cex <- graph.simi$label.cex
}
"""
- if tmpchi and self.parametres.get('sfromchi', False) :
+ if self.parametres['type'] == 'clustersimitxt' and self.parametres.get('sfromchi', False) :
txt += """
vertex.size <- norm.vec(lchi, minmaxeff[1], minmaxeff[2])
"""