# -*- coding: utf-8 -*-
#Author: Pierre Ratinaud
-#Copyright (c) 2008-2011 Pierre Ratinaud
+#Copyright (c) 2008-2020 Pierre Ratinaud
+#modification pour python 3 : Laurent Mérat, 6x7 - mai 2020
#License: GNU/GPL
+#------------------------------------
+# import des modules python
+#------------------------------------
import tempfile
-from chemins import ffr, PathOut
import os
import locale
from datetime import datetime
import logging
+#------------------------------------
+# import des fichiers du projet
+#------------------------------------
+from chemins import ffr, PathOut
+
+
log = logging.getLogger('iramuteq.printRscript')
-class PrintRScript :
- def __init__ (self, analyse):
+
+class PrintRScript:
+
+ 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()
+ self.script = "#Script genere par IRaMuTeQ - %s\n" % datetime.now().ctime()
- def add(self, txt) :
+ def add(self, txt):
self.script = '\n'.join([self.script, txt])
- def defvar(self, name, value) :
+ def defvar(self, name, value):
self.add(' <- '.join([name, value]))
- def defvars(self, lvars) :
- for val in lvars :
+ def defvars(self, lvars):
+ for val in lvars:
self.defvar(val[0],val[1])
- def sources(self, lsources) :
- for source in lsources :
+ def sources(self, lsources):
+ for source in lsources:
self.add('source("%s", encoding = \'utf8\')' % ffr(source))
- def packages(self, lpks) :
- for pk in lpks :
+ def packages(self, lpks):
+ for pk in lpks:
self.add('library(%s)' % pk)
- def load(self, l) :
- for val in l :
+ def load(self, l):
+ for val in l:
self.add('load("%s")' % ffr(val))
- def write(self) :
- with open(self.scriptout, 'w') as f :
+ def write(self):
+ with open(self.scriptout, 'w') as f:
f.write(self.script)
-class chdtxt(PrintRScript) :
+# ???
+class chdtxt(PrintRScript):
pass
-def Rcolor(color) :
+
+def Rcolor(color):
return str(color).replace(')', ', max=255)')
-class Alceste2(PrintRScript) :
- def doscript(self) :
+
+class Alceste2(PrintRScript):
+
+ def doscript(self):
self.sources(['chdfunct'])
self.load(['Rdata'])
- lvars = [['clnb', `self.analyse.clnb`],
+ lvars = [['clnb', repr(self.analyse.clnb)],
['Contout', '"%s"' % self.pathout['Contout']],
['ContSupOut', '"%s"' % self.pathout['ContSupOut']],
['ContEtOut', '"%s"' % self.pathout['ContEtOut']],
self.defvars(lvars)
-
-
# txt = "clnb<-%i\n" % clnb
# txt += """
#source("%s")
#
-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")
source("%s")
source("%s")
""" % (ffr(RscriptPath['CHD']), ffr(RscriptPath['chdtxt']), ffr(RscriptPath['anacor']), ffr(RscriptPath['Rgraph']))
- if R_max_mem :
+ if R_max_mem:
txt += """
memory.limit(%i)
""" % R_max_mem
-
txt += """
nbt <- %i
""" % nbt
- if svdmethod == 'svdlibc' and libsvdc :
+ if svdmethod == 'svdlibc' and libsvdc:
txt += """
svd.method <- 'svdlibc'
libsvdc.path <- "%s"
""" % ffr(libsvdc_path)
- elif svdmethod == 'irlba' :
+ elif svdmethod == 'irlba':
txt += """
library(irlba)
svd.method <- 'irlba'
libsvdc.path <- NULL
"""
- else :
+ else:
txt += """
svd.method = 'svdR'
libsvdc.path <- NULL
"""
- if mode_patate :
+ if mode_patate:
txt += """
mode.patate = TRUE
"""
- else :
+ else:
txt += """
mode.patate = FALSE
"""
data1 <- as(data1, "dgCMatrix")
row.names(data1) <- 1:nrow(data1)
""" % ffr(DicoPath['TableUc1'])
-
if classif_mode == 0:
txt += """
data2 <- readMM("%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 += """
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)
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['arbre1'])
-
if classif_mode == 0:
txt += """
classeuce2 <- chd.result$cuce2
# plot(tree.tot2$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$tree.cl,classes, histo=TRUE)
plot(tree.cut1$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$dendro_tot_cl)
dev.off()
""" % (ffr(DicoPath['dendro2']), ffr(DicoPath['arbre2']))
-
txt += """
-
#save.image(file="%s")
""" % (ffr(DicoPath['RData']))
-
fileout = open(DicoPath['Rchdtxt'], 'w')
fileout.write(txt)
fileout.close()
fileout = open(DicoPath['Rchdtxt'], 'w')
fileout.write(txt)
fileout.close()
-
def RchdQuest(DicoPath, RscriptPath, nbcl = 10, mincl = 10):
txt = """
source("%s")
source("%s")
""" % (ffr(RscriptPath['CHD']), ffr(RscriptPath['chdquest']), ffr(RscriptPath['anacor']),ffr(RscriptPath['Rgraph']))
-
txt += """
nbt <- %i - 1
mincl <- %i
""" % (nbcl, mincl)
-
txt += """
chd.result<-Rchdquest("%s","%s","%s", nbt = nbt, mincl = mincl)
n1 <- chd.result$n1
classeuce1 <- chd.result$cuce1
""" % (ffr(DicoPath['mat01.csv']), ffr(DicoPath['listeuce1']), ffr(DicoPath['uce']))
-
txt += """
tree_tot1 <- make_tree_tot(chd.result$chd)
open_file_graph("%s", width = 600, height=400)
plot(tree_tot1$tree.cl)
dev.off()
""" % ffr(DicoPath['arbre1'])
-
txt += """
tree_cut1 <- make_dendro_cut_tuple(tree_tot1$dendro_tuple, chd.result$coord_ok, classeuce1, 1, nbt)
tree.cut1 <- tree_cut1
classes<-n1[,ncol(n1)]
plot.dendropr(tree_cut1$tree.cl,classes, histo = TRUE)
""" % (ffr(DicoPath['Rdendro']), ffr(DicoPath['dendro1']))
-
txt += """
save.image(file="%s")
""" % ffr(DicoPath['RData'])
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])
gbcluster<-n1
write.csv2(gbcluster,file="%s")
""" % (ffr(DictChdTxtOut['chisqtable']), ffr(DictChdTxtOut['ptable']), ffr(DictChdTxtOut['SbyClasseOut']))
- if clnb > 2 :
+ if clnb > 2:
txt += """
library(ca)
colnames(dataact)<-paste('classe',1:clnb,sep=' ')
txt += """
source("%s")
""" % ffr(RscriptsPath['Rgraph'])
-
txt += """
afc <- summary.ca.dm(afc)
afc_table <- create_afc_table(afc)
write.csv2(afc_table$colonne, file = "%s")
write.csv2(afc_table$ligne, file = "%s")
""" % (ffr(DictChdTxtOut['afc_facteur']), ffr(DictChdTxtOut['afc_col']), ffr(DictChdTxtOut['afc_row']))
-
txt += """
PARCEX<-%s
""" % taillecar
PlotAfc2dCoul(afc, as.data.frame(chistabletot), "%s", col=TRUE, what='coord', xlab = xlab, ylab = ylab, xmin = xyminmax$xminmax[1], xmax = xyminmax$xminmax[2], ymin = xyminmax$yminmax[1], ymax = xyminmax$yminmax[2], active=FALSE)
""" % (ffr(DictChdTxtOut['AFC2DCL_OUT']))
# txt += """
- # PlotAfc2dCoul(afc, as.data.frame(chistabletot), "%s", what='crl', deb=1, fin=(debsup-1), xlab = xlab, ylab = ylab)
- # PlotAfc2dCoul(afc, as.data.frame(chistabletot), "%s", what='crl', deb=debsup, fin=(debet-1), xlab = xlab, ylab = ylab)
- # PlotAfc2dCoul(afc, as.data.frame(chistabletot), "%s", what='crl', deb=debet, fin=fin, xlab = xlab, ylab = ylab)
- # PlotAfc2dCoul(afc, as.data.frame(chistabletot), "%s", col=TRUE, what='crl', xlab = xlab, ylab = ylab)
- # """ % (DictChdTxtOut['AFC2DCoul'], DictChdTxtOut['AFC2DCoulSup'], DictChdTxtOut['AFC2DCoulEt'], DictChdTxtOut['AFC2DCoulCl'])
-
+# PlotAfc2dCoul(afc, as.data.frame(chistabletot), "%s", what='crl', deb=1, fin=(debsup-1), xlab = xlab, ylab = ylab)
+# PlotAfc2dCoul(afc, as.data.frame(chistabletot), "%s", what='crl', deb=debsup, fin=(debet-1), xlab = xlab, ylab = ylab)
+# PlotAfc2dCoul(afc, as.data.frame(chistabletot), "%s", what='crl', deb=debet, fin=fin, xlab = xlab, ylab = ylab)
+# PlotAfc2dCoul(afc, as.data.frame(chistabletot), "%s", col=TRUE, what='crl', xlab = xlab, ylab = ylab)
+# """ % (DictChdTxtOut['AFC2DCoul'], DictChdTxtOut['AFC2DCoulSup'], DictChdTxtOut['AFC2DCoulEt'], DictChdTxtOut['AFC2DCoulCl'])
txt += """
#rm(dataact)
#rm(datasup)
file.write(txt)
file.close()
-
def write_afc_graph(self):
- if self.param['over'] : over = 'TRUE'
- else : over = 'FALSE'
-
- if self.param['do_select_nb'] : do_select_nb = 'TRUE'
- else : do_select_nb = 'FALSE'
-
- if self.param['do_select_chi'] : do_select_chi = 'TRUE'
- else : do_select_chi = 'FALSE'
-
- if self.param['do_select_chi_classe'] : do_select_chi_classe = 'TRUE'
- else : do_select_chi_classe = 'FALSE'
-
- if self.param['cex_txt'] : cex_txt = 'TRUE'
- else : cex_txt = 'FALSE'
-
- if self.param['tchi'] : tchi = 'TRUE'
- else : tchi = 'FALSE'
-
- if self.param['svg'] : svg = 'TRUE'
- else : svg = 'FALSE'
-
+ if self.param['over']:
+ over = 'TRUE'
+ else:
+ over = 'FALSE'
+ if self.param['do_select_nb']:
+ do_select_nb = 'TRUE'
+ else:
+ do_select_nb = 'FALSE'
+ if self.param['do_select_chi']:
+ do_select_chi = 'TRUE'
+ else:
+ do_select_chi = 'FALSE'
+ if self.param['do_select_chi_classe']:
+ do_select_chi_classe = 'TRUE'
+ else:
+ do_select_chi_classe = 'FALSE'
+ if self.param['cex_txt']:
+ cex_txt = 'TRUE'
+ else:
+ cex_txt = 'FALSE'
+ if self.param['tchi']:
+ tchi = 'TRUE'
+ else:
+ tchi = 'FALSE'
+ 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], \
ffr(os.path.dirname(self.fileout)),\
svg)
return scripts
-
+
def print_simi3d(self):
simi3d = self.parent.simi3dpanel
txt = '#Fichier genere par Iramuteq'
- if simi3d.movie.GetValue() :
+ if simi3d.movie.GetValue():
movie = "'" + ffr(os.path.dirname(self.DictPathOut['RData'])) + "'"
- else :
+ else:
movie = 'NULL'
-
- #if self.corpus.parametres['type'] == 'corpus' :
+ #if self.corpus.parametres['type'] == 'corpus':
# header = 'TRUE'
- #else :
+ #else:
# header = 'FALSE'
header = 'FALSE'
txt += """
dm<-read.csv2("%s",row.names=1,header = %s)
load("%s")
""" % (self.DictPathOut['Contout'], header, self.DictPathOut['RData'])
-
txt += """
source("%s")
""" % self.parent.RscriptsPath['Rgraph']
-
-
txt += """
make.simi.afc(dm,chistabletot, lim=%i, alpha = %.2f, movie = %s)
""" % (simi3d.spin_1.GetValue(), float(simi3d.slider_1.GetValue())/100, movie)
tmp.close()
return tmpfile
-def dendroandbarplot(table, rownames, colnames, rgraph, tmpgraph, intxt = False, dendro=False) :
- if not intxt :
+def dendroandbarplot(table, rownames, colnames, rgraph, tmpgraph, intxt = False, dendro=False):
+ if not intxt:
txttable = 'c(' + ','.join([','.join(line) for line in table]) + ')'
rownb = len(rownames)
rownames = 'c("' + '","'.join(rownames) + '")'
colnames = 'c("' + '","'.join(colnames) + '")'
- if not intxt :
+ if not intxt:
#FIXME
txt = """
di <- matrix(data=%s, nrow=%i, byrow = TRUE)
rownames(di)<- %s
colnames(di) <- %s
""" % (txttable, rownb, rownames, colnames)
- else :
+ else:
txt = intxt
txt += """
load("%s")
""" % (ffr(dendro),ffr(rgraph), ffr(tmpgraph))
return txt
-def barplot(table, parametres, intxt = False) :
- if not intxt :
+def barplot(table, parametres, intxt = False):
+ if not intxt:
txttable = 'c(' + ','.join([','.join(line) for line in table]) + ')'
#width = 100 + (15 * len(rownames)) + (100 * len(colnames))
#height = len(rownames) * 15
rownb = len(parametres['rownames'])
- #if height < 400 :
+ #if height < 400:
# height = 400
rownames = 'c("' + '","'.join(parametres['rownames']) + '")'
colnames = 'c("' + '","'.join(parametres['colnames']) + '")'
-
- if not intxt :
+ if not intxt:
#FIXME
txt = """
di <- matrix(data=%s, nrow=%i, byrow = TRUE)
rownames(di)<- %s
colnames(di) <- %s
""" % (txttable, rownb, rownames, colnames)
- else :
+ else:
txt = intxt
- if not 'tree' in parametres :
+ if not 'tree' in parametres:
txt += """
source("%s")
color = rainbow(nrow(di))
width <- %i
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)))
+ par(mar=c(0,0,0,0))
+ 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)
legend(x = 'center' , rownames(di), fill = color)
dev.off()
""" % (ffr(parametres['rgraph']), parametres['width'], parametres['height'], ffr(parametres['tmpgraph']), parametres['svg'])
- else :
+ else:
txt += """
load("%s")
library(ape)
# f.write(txt)
# f.close()
-class PrintSimiScript(PrintRScript) :
- def make_script(self) :
+
+class PrintSimiScript(PrintRScript):
+
+ def make_script(self):
self.txtgraph = ''
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' or self.parametres['type'] == 'simiclustermatrix') :
+ if not self.parametres['keep_coord'] and not (self.parametres['type'] == 'simimatrix' or self.parametres['type'] == 'simiclustermatrix'):
txt += """
dm.path <- "%s"
cn.path <- "%s"
selected.col <- "%s"
""" % (ffr(self.pathout['mat01.csv']), ffr(self.pathout['actives.csv']), ffr(self.pathout['selected.csv']))
- if 'word' in self.parametres :
+ if 'word' in self.parametres:
txt += """
word <- TRUE
index <- %i + 1
""" % self.parametres['word']
- else :
+ 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)
dm.path <- "%s"
selected.col <- "%s"
""" % (ffr(self.pathout['mat01.csv']), ffr(self.pathout['selected.csv']))
- if 'word' in self.parametres :
+ if 'word' in self.parametres:
txt += """
word <- TRUE
index <- %i + 1
""" % self.parametres['word']
- else :
+ else:
txt += """
word <- FALSE
"""
index <- which(colnames(dm) == forme)
}
"""
- else :
+ else:
txt += """
load("%s")
""" % ffr(self.pathout['RData.RData'])
-
- if self.parametres['coeff'] == 0 :
+ if self.parametres['coeff'] == 0:
method = 'cooc'
- if not self.parametres['keep_coord'] :
+ if not self.parametres['keep_coord']:
txt += """
method <- 'cooc'
mat <- make.a(dm)
"""
- else :
- if not self.parametres['keep_coord'] :
+ 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 += """
dm <- as.matrix(dm)
"""
- if self.parametres['coeff'] == 1 :
+ if self.parametres['coeff'] == 1:
method = 'prcooc'
txt += """
method <- 'Russel'
mat <- simil(dm, method = 'Russel', diag = TRUE, upper = TRUE, by_rows = FALSE)
"""
- elif self.analyse.indices[self.parametres['coeff']] == 'binomial' :
+ elif self.analyse.indices[self.parametres['coeff']] == 'binomial':
method = 'binomial'
- if not self.parametres['keep_coord'] :
+ 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'] :
+ if not self.parametres['keep_coord']:
txt += """
method <-"%s"
mat <- simil(dm, method = method, diag = TRUE, upper = TRUE, by_rows = FALSE)
""" % self.analyse.indices[self.parametres['coeff']]
- if not self.parametres['keep_coord'] :
+ if not self.parametres['keep_coord']:
txt += """
mat <- as.matrix(stats::as.dist(mat,diag=TRUE,upper=TRUE))
mat[is.na(mat)] <- 0
mat[infm] <- minmat
}
"""
- if 'word' in self.parametres and not self.parametres['keep_coord'] :
+ 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)]
+ 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'] == 1 : layout = 'circle'
- 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'] == 0:
+ layout = 'random'
+ if self.parametres['layout'] == 1:
+ layout = 'circle'
+ 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=''
- if self.parametres['type_graph'] == 0 : type = 'tkplot'
- if self.parametres['type_graph'] == 1 :
+ if self.parametres['type_graph'] == 0:
+ type = 'tkplot'
+ if self.parametres['type_graph'] == 1:
graphnb = 1
type = 'nplot'
dirout = os.path.dirname(self.pathout['mat01.csv'])
while os.path.exists(os.path.join(dirout,'graph_simi_'+str(graphnb)+'.png')):
graphnb +=1
self.filename = ffr(os.path.join(dirout,'graph_simi_'+str(graphnb)+'.png'))
- if self.parametres['type_graph'] == 2 : type = 'rgl'
- if self.parametres['type_graph'] == 3 :
+ if self.parametres['type_graph'] == 2:
+ type = 'rgl'
+ if self.parametres['type_graph'] == 3:
graphnb = 1
type = 'web'
dirout = os.path.dirname(self.pathout['mat01.csv'])
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 :
+ if self.parametres['type_graph'] == 4:
graphnb = 1
type = 'rglweb'
dirout = os.path.dirname(self.pathout['mat01.csv'])
graphnb +=1
self.filename = ffr(os.path.join(dirout,'webrgl_'+str(graphnb)))
os.mkdir(self.filename)
-
- if self.parametres['arbremax'] :
+ if self.parametres['arbremax']:
arbremax = 'TRUE'
self.txtgraph += ' - arbre maximum'
- else : arbremax = 'FALSE'
-
- if self.parametres['coeff_tv'] :
+ else:
+ arbremax = 'FALSE'
+
+ if self.parametres['coeff_tv']:
coeff_tv = self.parametres['coeff_tv_nb']
tvminmax = 'c(NULL,NULL)'
- elif not self.parametres['coeff_tv'] or self.parametres.get('sformchi', False) :
+ elif not self.parametres['coeff_tv'] or self.parametres.get('sformchi', False):
coeff_tv = 'NULL'
tvminmax = 'c(%i, %i)' %(self.parametres['tvmin'], self.parametres['tvmax'])
- if self.parametres['coeff_te'] : coeff_te = 'c(%i,%i)' % (self.parametres['coeff_temin'], self.parametres['coeff_temax'])
- else : coeff_te = 'NULL'
-
- if self.parametres['vcex'] or self.parametres.get('cexfromchi', False) :
+ if self.parametres['coeff_te']:
+ coeff_te = 'c(%i,%i)' % (self.parametres['coeff_temin'], self.parametres['coeff_temax'])
+ else:
+ coeff_te = 'NULL'
+ if self.parametres['vcex'] or self.parametres.get('cexfromchi', False):
vcexminmax = 'c(%i/10,%i/10)' % (self.parametres['vcexmin'],self.parametres['vcexmax'])
- else :
+ else:
vcexminmax = 'c(NULL,NULL)'
- if not self.parametres['label_v'] : label_v = 'FALSE'
- else : label_v = 'TRUE'
-
- if not self.parametres['label_e'] : label_e = 'FALSE'
- else : label_e = 'TRUE'
-
- if self.parametres['seuil_ok'] : seuil = str(self.parametres['seuil'])
- else : seuil = 'NULL'
-
- if not self.parametres.get('edgecurved', False) :
+ if not self.parametres['label_v']:
+ label_v = 'FALSE'
+ else:
+ label_v = 'TRUE'
+ if not self.parametres['label_e']:
+ label_e = 'FALSE'
+ else:
+ label_e = 'TRUE'
+ if self.parametres['seuil_ok']:
+ seuil = str(self.parametres['seuil'])
+ else:
+ seuil = 'NULL'
+ if not self.parametres.get('edgecurved', False):
ec = 'FALSE'
- else :
+ else:
ec = 'TRUE'
-
txt += """
edge.curved <- %s
""" % ec
-
cols = str(self.parametres['cols']).replace(')',', max=255)')
cola = str(self.parametres['cola']).replace(')',',max=255)')
-
txt += """
minmaxeff <- %s
""" % tvminmax
txt += """
cex = %i/10
""" % self.parametres['cex']
-
- if self.parametres['film'] :
+ if self.parametres['film']:
txt += """
film <- "%s"
""" % ffr(self.pathout['film'])
- else :
+ else:
txt += """
film <- NULL
"""
}
}
""" % seuil
-
txt += """
label.v <- %s
label.e <- %s
width <- %i
height <- %i
""" % (self.parametres['width'], self.parametres['height'])
- if self.parametres['keep_coord'] :
+ if self.parametres['keep_coord']:
txt += """
coords <- try(coords, TRUE)
if (!is.matrix(coords)) {
coords<-NULL
}
"""
- else :
+ else:
txt += """
coords <- NULL
"""
txt += """
alpha <- %i/100
""" % self.parametres['alpha']
-#############################################
- if self.parametres.get('bystar',False) :
+ ######### ??? ##########
+ if self.parametres.get('bystar',False):
txt += """
et <- list()
"""
- for i, line in enumerate(self.parametres['listet']) :
+ for i, line in enumerate(self.parametres['listet']):
txt+= """
et[[%i]] <- c(%s)
- """ % (i+1, ','.join([`val + 1` for val in line]))
+ """ % (i+1, ','.join([repr(val + 1) for val in line]))
txt+= """
unetoile <- c('%s')
""" % ("','".join([val for val in self.parametres['selectedstars']]))
chivertex.size <- norm.vec(toblack, vcexminmax[1], vcexminmax[2])
""" % (ffr(self.analyse.parent.RscriptsPath['chdfunct']))
- else :
+ else:
txt += """
vertex.label.color <- 'black'
chivertex.size <- 1
leg<-NULL
"""
-#############################################
-
+ ######### ??? ##########
# txt += """
# eff <- colSums(dm)
# g.ori <- graph.adjacency(mat, mode='lower', weighted = TRUE)
# g.toplot <- g.ori
# }
# """
- if self.parametres['com'] :
- com = `self.parametres['communities']`
- else :
+ if self.parametres['com']:
+ com = repr(self.parametres['communities'])
+ else:
com = 'NULL'
- if self.parametres['halo'] :
+ if self.parametres['halo']:
halo = 'TRUE'
- else :
+ else:
halo = 'FALSE'
txt += """
communities <- %s
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) :
- if self.parametres.get('cexfromchi', False) :
+ if self.parametres.get('bystar',False):
+ if self.parametres.get('cexfromchi', False):
txt+="""
label.cex<-chivertex.size
"""
- else :
+ else:
txt+="""
label.cex <- cex
"""
- if self.parametres.get('sfromchi', False) :
+ if self.parametres.get('sfromchi', False):
txt += """
vertex.size <- norm.vec(toblack, minmaxeff[1], minmaxeff[2])
"""
- else :
+ else:
txt += """
vertex.size <- NULL
"""
- else :
+ else:
#print 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 += """
txt += """
lchi <- lchi[sel.col]
"""
- if self.parametres['type'] in ['clustersimitxt', 'simimatrix', 'simiclustermatrix'] 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])
"""
- else :
+ else:
txt += """
if (is.null(vcexminmax[1])) {
label.cex <- cex
vertex.size <- norm.vec(lchi, minmaxeff[1], minmaxeff[2])
if (!length(vertex.size)) vertex.size <- 0
"""
- else :
+ else:
txt += """
if (is.null(minmaxeff[1])) {
vertex.size <- 0
}
"""
#txt += """ vertex.size <- NULL """
- if self.parametres['svg'] : svg = 'TRUE'
- else : svg = 'FALSE'
+ if self.parametres['svg']:
+ svg = 'TRUE'
+ else:
+ svg = 'FALSE'
txt += """
svg <- %s
""" % 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']))
-
self.add(txt)
self.write()
-class WordCloudRScript(PrintRScript) :
- def make_script(self) :
+
+class WordCloudRScript(PrintRScript):
+
+ def make_script(self):
self.sources([self.analyse.parent.RscriptsPath['Rgraph']])
self.packages(['wordcloud'])
bg_col = Rcolor(self.parametres['col_bg'])
txt_col = Rcolor(self.parametres['col_text'])
- if self.parametres['svg'] :
+ if self.parametres['svg']:
svg = 'TRUE'
- else :
+ else:
svg = 'FALSE'
txt = """
svg <- %s
self.add(txt)
self.write()
-class ProtoScript(PrintRScript) :
- def make_script(self) :
+
+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) :
+ if self.parametres.get('cloud', False):
cloud = 'TRUE'
- else :
+ else:
cloud = 'FALSE'
txt = """
errorn <- function(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')
+ 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) :
+class ExportAfc(PrintRScript):
+
+ def make_script(self):
self.source([self.analyse.parent.RscriptsPath['Rgraph']])
self.packages(['rgexf'])
txt = """
"""
-class MergeGraphes(PrintRScript) :
+
+class MergeGraphes(PrintRScript):
+
def __init__(self, analyse):
- self.script = u"#Script genere par IRaMuTeQ - %s\n" % datetime.now().ctime()
+ 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) :
+ def make_script(self):
#FIXME
-
txt = """
library(igraph)
library(Matrix)
V(g)$weight <- (graph.simi$mat.eff/nrow(dm))*100
graphs[['%s']] <- g
"""
- for i, graph in enumerate(self.parametres['graphs']) :
+ for i, graph in enumerate(self.parametres['graphs']):
path = os.path.dirname(graph)
- gname = ''.join(['g', `i`])
+ gname = ''.join(['g', repr(i)])
RData = os.path.join(path,'RData.RData')
txt += load % (ffr(RData), gname)
self.add(txt)
self.sources([self.analyse.parent.RscriptsPath['simi']])
txt = """
- ng <- merge.graph(graphs)
+ merge.type <- 'proto'
+ if (merge.type == 'normal') {
+ ng <- merge.graph(graphs)
+ } else {
+ ng <- merge.graph.proto(graphs)
+ }
ngraph <- list(graph=ng, layout=layout.fruchterman.reingold(ng, dim=3), labex.cex=V(ng)$weight)
write.graph(ng, "%s", format = 'graphml')
""" % ffr(self.parametres['grapheout'])
self.add(txt)
-
+
+
class TgenSpecScript(PrintRScript):
+
def make_script(self):
self.packages(['textometry'])
txt = """
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 = """
write.table(reslem$pchi2, file = "%s", sep='\\t', col.names = NA)
""" % (ffr(self.pathout['tgenlemchi2.csv']), ffr(self.pathout['tgenlempchi2.csv']))
self.add(txt)
-
+
+
class FreqMultiScript(PrintRScript):
+
def make_script(self):
self.sources([self.analyse.parent.RscriptsPath['Rgraph']])
txt = """
self.add(txt)
self.write()
-class LabbeScript(PrintRScript) :
- def make_script(self) :
+
+class LabbeScript(PrintRScript):
+
+ def make_script(self):
self.sources([self.analyse.parent.RscriptsPath['distance-labbe.R'],
self.analyse.parent.RscriptsPath['Rgraph']])
txt = """
txt +="""
open_file_graph("%s", width=1000, height=1000, svg=F)
par(mar=c(10,1,1,10))
- heatmap(as.matrix(dist.mat), symm = T, distfun=function(x) as.dist(x))
+ heatmap(as.matrix(dist.mat), symm = T, distfun=function(x) as.dist(x), margins=c(10,10))
dev.off()
""" % ffr(self.pathout['labbe-heatmap.png'])
txt += """
rn <- row.names(as.matrix(dist.mat))
open_file_graph("%s", width=1500, height=1000, svg=F)
par(mar=c(10,10,3,3))
- image(1:dim, 1:dim, dst, axes = FALSE, xlab="", ylab="")
+ image(1:dim, 1:dim, dst, axes = FALSE, xlab="", ylab="", col=heat.colors(99), breaks=seq(0.01,1,0.01))
axis(1, 1:dim, rn, cex.axis = 0.9, las=3)
axis(2, 1:dim, rn, cex.axis = 0.9, las=1)
text(expand.grid(1:dim, 1:dim), sprintf("%%0.2f", dst), cex=0.6)
dev.off()
""" % ffr(self.pathout['labbe-matrix.png'])
+ txt += """
+ library(igraph)
+ g <- graph.adjacency(as.matrix(1-dist.mat), mode="lower", weighted=T)
+ write.graph(g, file="%s", format='graphml')
+ open_file_graph("%s", width=1000, height=1000, svg=F)
+ plot(g)
+ dev.off()
+ E(g)$weight <- 1 - E(g)$weight
+ g <- minimum.spanning.tree(g)
+ E(g)$weight <- 1 - E(g)$weight
+ write.graph(g, file="%s", format='graphml')
+ open_file_graph("%s", width=1000, height=1000, svg=F)
+ plot(g)
+ dev.off()
+ """ % (ffr(self.pathout['graph_tot.graphml']), ffr(self.pathout['graph_tot.png']), ffr(self.pathout['graph_min.graphml']), ffr(self.pathout['graph_min.png']))
self.add(txt)
self.write()
-class ChronoChi2Script(PrintRScript) :
- def make_script(self) :
+
+class ChronoChi2Script(PrintRScript):
+
+ def make_script(self):
self.sources([self.analyse.parent.RscriptsPath['Rgraph']])
- print self.parametres
+ print(self.parametres)
txt = """
inRData <- "%s"
dendrof <- "%s"
ptc <- tcp/sum(tcp)
dpt <- t(dpt)
dd <- dpt
- """ % self.parametres['var'].replace(u'*', u"\\\\*")
+ """ % self.parametres['var'].replace('*', "\\\\*")
txt += """
classes <- n1[,ncol(n1)]
tcl <- table(classes)
tcl <- tcl[-to.vire]
}
tclp <- tcl/sum(tcl)
-
#chi2 colors
library(ape)
k <- 1e-02
tree.toplot <- tree.cut1$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))
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)
self.add(txt)
self.write()
-class ChronoPropScript(PrintRScript) :
- def make_script(self) :
+
+class ChronoPropScript(PrintRScript):
+
+ def make_script(self):
self.sources([self.analyse.parent.RscriptsPath['Rgraph']])
- print self.parametres
+ print(self.parametres)
txt = """
inRData <- "%s"
dendrof <- "%s"
ptc <- tcp/sum(tcp)
dpt <- t(dpt)
dd <- dpt
- """ % self.parametres['var'].replace(u'*', u"\\\\*")
+ """ % self.parametres['var'].replace('*', "\\\\*")
txt += """
classes <- n1[,ncol(n1)]
tcl <- table(classes)
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()
+ """
+ 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)