- dlg = progressbar(self, 2)
- corpus = self.Source.corpus
- uces = corpus.lc[self.cl-1]
- dlg.Update(1, u'Tableau...')
- #tab = corpus.make_table_with_classe(uces, self.la)
- pathout = ConstructPathOut(self.Source.pathout.dirout+'/', 'simi_classe_%i' %self.cl)
- self.filename = os.path.join(pathout,'mat01.csv')
- dlg.Update(2, u'Ecriture...')
- #corpus.write_tab(tab, self.filename)
- #del tab
- corpus.make_and_write_sparse_matrix_from_classe(self.la, uces, self.filename)
- dlg.Destroy()
- paramsimi = {'coeff' : 0,
- 'layout' : 2,
- 'type' : 1,
- 'arbremax' : 1,
- 'coeff_tv' : 1,
- 'coeff_tv_nb' : 0,
- 'tvprop' : 0,
- 'tvmin' : 5,
- 'tvmax' : 30,
- 'coeff_te' : 1,
- 'coeff_temin' : 1,
- 'coeff_temax' : 10,
- 'label_v': 1,
- 'label_e': 0,
- 'vcex' : 0,
- 'vcexmin' : 10,
- 'vcexmax' : 25,
- 'cex' : 10,
- 'cexfromchi' : True,
- 'sfromchi': False,
- 'seuil_ok' : 0,
- 'seuil' : 1,
- 'cols' : (255,0,0),
- 'cola' : (200,200,200),
- 'width' : 1000,
- 'height' : 1000,
- 'first' : True,
- 'keep_coord' : True,
- 'alpha' : 20,
- 'film': False,
- }
- self.tableau = Tableau(self.parent, '')
- self.tableau.listactives = self.la
- self.tableau.actives = {}
- self.tableau.lchi = self.lchi
- self.tableau.chi = {}
- self.tableau.parametre['fromprof'] = True
- for i, val in enumerate(self.la) :
- self.tableau.actives[val] = [self.lfreq[i]]
- self.tableau.chi[val] = [self.lchi[i]]
- DoSimi(self, param = paramsimi, fromprof = ffr(self.filename), pathout = pathout)
+ self.parent.SimiFromCluster(self.parent, self.Source.corpus, self.la, self.cl - 1, parametres = {'type' : 'clustersimitxt', 'pathout' : self.Source.parametres['pathout']}, dlg = progressbar(self, 4))
+ #dlg = progressbar(self, 2)
+ #corpus = self.Source.corpus
+ #uces = corpus.lc[self.cl-1]
+ #dlg.Update(1, u'Tableau...')
+ ##tab = corpus.make_table_with_classe(uces, self.la)
+ #pathout = ConstructPathOut(self.Source.pathout.dirout+'/', 'simi_classe_%i' %self.cl)
+ #self.filename = os.path.join(pathout,'mat01.csv')
+ #dlg.Update(2, u'Ecriture...')
+ ##corpus.write_tab(tab, self.filename)
+ ##del tab
+ #corpus.make_and_write_sparse_matrix_from_classe(self.la, uces, self.filename)
+ #dlg.Destroy()
+ #paramsimi = {'coeff' : 0,
+ # 'layout' : 2,
+ # 'type' : 1,
+ # 'arbremax' : 1,
+ # 'coeff_tv' : 1,
+ # 'coeff_tv_nb' : 0,
+ # 'tvprop' : 0,
+ # 'tvmin' : 5,
+ # 'tvmax' : 30,
+ # 'coeff_te' : 1,
+ # 'coeff_temin' : 1,
+ # 'coeff_temax' : 10,
+ # 'label_v': 1,
+ # 'label_e': 0,
+ # 'vcex' : 0,
+ # 'vcexmin' : 10,
+ # 'vcexmax' : 25,
+ # 'cex' : 10,
+ # 'cexfromchi' : True,
+ # 'sfromchi': False,
+ # 'seuil_ok' : 0,
+ # 'seuil' : 1,
+ # 'cols' : (255,0,0),
+ # 'cola' : (200,200,200),
+ # 'width' : 1000,
+ # 'height' : 1000,
+ # 'first' : True,
+ # 'keep_coord' : True,
+ # 'alpha' : 20,
+ # 'film': False,
+ # }
+ #self.tableau = Tableau(self.parent, '')
+ #self.tableau.listactives = self.la
+ #self.tableau.actives = {}
+ #self.tableau.lchi = self.lchi
+ #self.tableau.chi = {}
+ #self.tableau.parametre['fromprof'] = True
+ #for i, val in enumerate(self.la) :
+ # self.tableau.actives[val] = [self.lfreq[i]]
+ # self.tableau.chi[val] = [self.lchi[i]]
+ #DoSimi(self, param = paramsimi, fromprof = ffr(self.filename), pathout = pathout)