from layout import PrintRapport
from openanalyse import OpenAnalyse
from dialog import StatDialog
from layout import PrintRapport
from openanalyse import OpenAnalyse
from dialog import StatDialog
- def __init__(self, ira, corpus, parametres = None, dlg = False, lemdial = True) :
+ def __init__(self, ira, corpus, parametres=None, dlg=False, lemdial=True) :
- self.pathout = PathOut(corpus.parametres['originalpath'], analyse_type = parametres['type'], dirout = corpus.parametres['pathout'])
+ self.pathout = PathOut(corpus.parametres['originalpath'], analyse_type=parametres['type'], dirout=corpus.parametres['pathout'])
- self.pathout = PathOut(filename = corpus.parametres['originalpath'], dirout = self.parametres['pathout'], analyse_type = self.parametres['type'])
+ self.pathout = PathOut(filename=corpus.parametres['originalpath'], dirout=self.parametres['pathout'], analyse_type=self.parametres['type'])
self.parametres = self.lemparam()
if self.parametres is not None :
self.parametres = self.make_config(parametres)
self.parametres = self.lemparam()
if self.parametres is not None :
self.parametres = self.make_config(parametres)
gramact = [k for k in self.keys if self.keys[k] == 1]
gramsup = [k for k in self.keys if self.keys[k] == 2]
self.parametres['pathout'] = self.pathout.mkdirout()
gramact = [k for k in self.keys if self.keys[k] == 1]
gramsup = [k for k in self.keys if self.keys[k] == 2]
self.parametres['pathout'] = self.pathout.mkdirout()
self.pathout.createdir(self.parametres['pathout'])
self.parametres['corpus'] = self.corpus.parametres['uuid']
self.parametres['uuid'] = str(uuid4())
self.pathout.createdir(self.parametres['pathout'])
self.parametres['corpus'] = self.corpus.parametres['uuid']
self.parametres['uuid'] = str(uuid4())
- self.corpus.make_lems(lem = self.parametres['lem'])
- corpus.parse_active(gramact, gramsup)
+ self.corpus.make_lems(lem=self.parametres['lem'])
+ self.corpus.parse_active(gramact, gramsup)
- self.time = time() - self.t1
- minutes, seconds = divmod(self.time, 60)
- hours, minutes = divmod(minutes, 60)
- self.parametres['time'] = '%.0fh %.0fm %.0fs' % (hours, minutes, seconds)
- self.parametres['ira'] = self.pathout['Analyse.ira']
- DoConf().makeoptions([self.parametres['type']], [self.parametres], self.pathout['Analyse.ira'])
- self.ira.history.add(self.parametres)
- if dlg :
- dlg.Destroy()
- OpenAnalyse(self.parent, self.parametres['ira'])
- self.ira.tree.AddAnalyse(self.parametres)
- self.val = 5100
+ self.time = time() - self.t1
+ minutes, seconds = divmod(self.time, 60)
+ hours, minutes = divmod(minutes, 60)
+ self.parametres['time'] = '%.0fh %.0fm %.0fs' % (hours, minutes, seconds)
+ self.parametres['ira'] = self.pathout['Analyse.ira']
+ DoConf().makeoptions([self.parametres['type']], [self.parametres], self.pathout['Analyse.ira'])
+ self.ira.history.add(self.parametres)
+ if dlg :
+ dlg.Destroy()
+ OpenAnalyse(self.parent, self.parametres['ira'])
+ self.ira.tree.AddAnalyse(self.parametres)
+ self.val = 5100
- def doR(self, Rscript, wait = False, dlg = None, message = '') :
+ def doR(self, Rscript, wait=False, dlg=None, message='') :
self.actives, lim = self.corpus.make_actives_nb(self.parametres['max_actives'], 1)
self.parametres['eff_min_forme'] = lim
self.parametres['nbactives'] = len(self.actives)
self.actives, lim = self.corpus.make_actives_nb(self.parametres['max_actives'], 1)
self.parametres['eff_min_forme'] = lim
self.parametres['nbactives'] = len(self.actives)
if self.parametres['classif_mode'] == 0 :
lenuc1, lenuc2 = self.corpus.make_and_write_sparse_matrix_from_uc(self.actives, self.parametres['tailleuc1'], self.parametres['tailleuc2'], self.pathout['TableUc1'], self.pathout['TableUc2'], self.pathout['listeuce1'], self.pathout['listeuce2'])
self.parametres['lenuc1'] = lenuc1
if self.parametres['classif_mode'] == 0 :
lenuc1, lenuc2 = self.corpus.make_and_write_sparse_matrix_from_uc(self.actives, self.parametres['tailleuc1'], self.parametres['tailleuc2'], self.pathout['TableUc1'], self.pathout['TableUc2'], self.pathout['listeuce1'], self.pathout['listeuce2'])
self.parametres['lenuc1'] = lenuc1
self.corpus.make_and_write_sparse_matrix_from_uces(self.actives, self.pathout['TableUc1'], self.pathout['listeuce1'])
elif self.parametres['classif_mode'] == 2 :
self.corpus.make_and_write_sparse_matrix_from_uci(self.actives, self.pathout['TableUc1'], self.pathout['listeuce1'])
self.corpus.make_and_write_sparse_matrix_from_uces(self.actives, self.pathout['TableUc1'], self.pathout['listeuce1'])
elif self.parametres['classif_mode'] == 2 :
self.corpus.make_and_write_sparse_matrix_from_uci(self.actives, self.pathout['TableUc1'], self.pathout['listeuce1'])
- self.corpus.make_and_write_profile(self.actives, self.corpus.lc, self.pathout['Contout'])
+ self.corpus.make_and_write_profile(self.actives, self.corpus.lc, self.pathout['Contout'], uci = uci)
- self.corpus.make_and_write_profile(self.sup, self.corpus.lc, self.pathout['ContSupOut'])
- self.corpus.make_and_write_profile_et(self.corpus.lc, self.pathout['ContEtOut'])
+ self.corpus.make_and_write_profile(self.sup, self.corpus.lc, self.pathout['ContSupOut'], uci = uci)
+ self.corpus.make_and_write_profile_et(self.corpus.lc, self.pathout['ContEtOut'], uci = uci)
self.clnb = len(self.corpus.lc)
self.parametres['clnb'] = self.clnb
Rscript = self.printRscript2()
self.clnb = len(self.corpus.lc)
self.parametres['clnb'] = self.clnb
Rscript = self.printRscript2()
self.time = time() - self.t1
minutes, seconds = divmod(self.time, 60)
hours, minutes = divmod(minutes, 60)
self.time = time() - self.t1
minutes, seconds = divmod(self.time, 60)
hours, minutes = divmod(minutes, 60)
- RchdTxt(self.pathout, self.parent.RscriptsPath, self.parametres['mincl'], self.parametres['classif_mode'], nbt = self.parametres['nbcl_p1'] - 1, svdmethod = self.parametres['svdmethod'], libsvdc = self.parent.pref.getboolean('iramuteq','libsvdc'), libsvdc_path = self.parent.pref.get('iramuteq','libsvdc_path'), R_max_mem = False, mode_patate = self.parametres['mode.patate'])
+ RchdTxt(self.pathout, self.parent.RscriptsPath, self.parametres['mincl'], self.parametres['classif_mode'], nbt=self.parametres['nbcl_p1'] - 1, svdmethod=self.parametres['svdmethod'], libsvdc=self.parent.pref.getboolean('iramuteq', 'libsvdc'), libsvdc_path=self.parent.pref.get('iramuteq', 'libsvdc_path'), R_max_mem=False, mode_patate=self.parametres['mode.patate'])
chd_graph_list.append([os.path.basename(self.pathout['arbre1']), u'chd1'])
if self.parametres['classif_mode'] == 0 :
chd_graph_list.append([os.path.basename(self.pathout['arbre2']), u'chd2'])
chd_graph_list.append([os.path.basename(self.pathout['arbre1']), u'chd1'])
if self.parametres['classif_mode'] == 0 :
chd_graph_list.append([os.path.basename(self.pathout['arbre2']), u'chd2'])
- print_liste(self.pathout['liste_graph_afc'],afc_graph_list)
- print_liste(self.pathout['liste_graph_chd'],chd_graph_list)
+ print_liste(self.pathout['liste_graph_afc'], afc_graph_list)
+ print_liste(self.pathout['liste_graph_chd'], chd_graph_list)