# -*- coding: utf-8 -*-
#Author: Pierre Ratinaud
-#Copyright (c) 2008-2011 Pierre Ratinaud
-#Lisense: GNU/GPL
+#Copyright (c) 2008-2013 Pierre Ratinaud
+#License: GNU/GPL
-from chemins import ConstructPathOut, construct_simipath
-from corpus import Corpus
+from chemins import ffr, simipath
import os
-from ConfigParser import RawConfigParser
-from guifunct import getPage, getCorpus
-from dialog import StatDialog
-from functions import indices_simi, progressbar, treat_var_mod
-from tableau import Tableau
-from tabsimi import DoSimi
+from analysetxt import AnalyseText
+from guifunct import PrepSimi
+from functions import indices_simi, progressbar, treat_var_mod, read_list_file, print_liste
+from PrintRScript import PrintSimiScript
import wx
from copy import copy
+import logging
-class SimiTxt :
- def __init__(self, parent, cmd = False, param = None):
- self.parent = parent
- self.cmd = cmd
- self.ConfigPath = parent.ConfigPath
- self.DictPath = parent.DictPath
- self.KeyConf = RawConfigParser()
- self.KeyConf.read(self.ConfigPath['key'])
+log = logging.getLogger('iramuteq.textsimi')
+
+class SimiTxt(AnalyseText):
+ def doanalyse(self) :
+ self.parametres['type'] = 'simitxt'
+ self.pathout.basefiles(simipath)
self.indices = indices_simi
+ if self.dlg :
+ self.makesimiparam()
+ #FIXME
+ self.actives = self.corpus.make_actives_limit(3)
+ dictcol = dict([[i, [act, self.corpus.getlemeff(act)]] for i, act in enumerate(self.actives)])
+ continu = False
+ if self.dlg :
+ self.listet = self.corpus.make_etoiles()
+ self.listet.sort()
+ self.stars = copy(self.listet)
+ self.parametres['stars'] = copy(self.listet)
+ self.parametres['sfromchi'] = False
+ self.dlg.Destroy()
+ prep = PrepSimi(self.ira, self, self.parametres, self.pathout['selected.csv'], self.actives, indices_simi, wordlist=dictcol)
+ if prep.val == wx.ID_OK :
+ continu = True
+ self.parametres = prep.parametres
+ self.dlg = progressbar(self.ira, 4)
+ else :
+ return False
+ else :
+ continu = True
+ if continu :
+ self.makefiles()
+ script = PrintSimiScript(self)
+ script.make_script()
+ if not self.doR(script.scriptout, dlg = self.dlg, message = 'R...') :
+ log.info('Problem')
+ return False
+ if self.parametres['type_graph'] == 1:
+ if self.parametres['svg'] :
+ filename, ext = os.path.splitext(script.filename)
+ fileout = filename + '.svg'
+ else :
+ fileout = script.filename
+ if os.path.exists(self.pathout['liste_graph']):
+ graph_simi = read_list_file(self.pathout['liste_graph'])
+ graph_simi.append([os.path.basename(fileout), script.txtgraph])
+ else :
+ graph_simi = [[os.path.basename(fileout), script.txtgraph]]
+ print_liste(self.pathout['liste_graph'], graph_simi)
+ else :
+ return False
+
+ def makesimiparam(self) :
self.paramsimi = {'coeff' : 0,
'layout' : 2,
- 'type' : 1,
+ 'type_graph' : 1,
'arbremax' : 1,
'coeff_tv' : 1,
'coeff_tv_nb' : 0,
'height' : 1000,
'bystar' : False,
'first' : True,
- 'keep_coord' : True,
+ 'keep_coord' : False,
'alpha' : 20,
'film': False,
+ 'svg' : 0,
+ 'com' : 0,
+ 'communities' : 0,
+ 'halo' : 0,
+ #'ira' : self.pathout['Analyse.ira']
}
- page = getPage(self.parent)
- if page is not None :
- self.corpus = getCorpus(page)
- if self.corpus is not None :
- self.pathout = ConstructPathOut(self.corpus.parametre['openpath'], 'simitxt')
- self.dictpathout = construct_simipath(self.pathout)
- self.val = wx.ID_OK
- self.make_table()
- self.make_simi()
- else :
- self.corpus = Corpus(parent)
- self.corpus.content = self.parent.content
- self.corpus.parametre['encodage'] = parent.corpus_encodage
- self.corpus.parametre['lang'] = parent.corpus_lang
- self.corpus.parametre['filename'] = parent.filename
- self.corpus.parametre['eff_min_uce'] = None
- self.pathout = ConstructPathOut(self.corpus.parametre['filename'], 'simitxt')
- self.dictpathout = construct_simipath(self.pathout)
- dial = StatDialog(self, self.parent)
- dial.check_uce.SetValue(True)
- dial.check_uce.Enable(False)
- dial.OnCheckUce(wx.EVT_MENU)
- self.val = dial.ShowModal()
- if self.val == wx.ID_OK :
- with open(self.parent.ConfigPath['key'], 'w') as f:
- self.KeyConf.write(f)
- if dial.radio_lem.GetSelection() == 0 : lem = True
- else : lem = False
- if dial.exp.GetSelection() == 0 : exp = True
- else : exp = False
- dial.Destroy()
- self.corpus.parametre['lem'] = lem
- self.corpus.parametre['expressions'] = exp
- self.corpus.parametre['nbforme_uce'] = dial.spin_ctrl_4.GetValue()
- self.corpus.parametre['eff_min_forme'] = dial.spin_ctrl_5.GetValue()
- self.corpus.parametre['max_actives'] = dial.spin_max_actives.GetValue()
- self.make_corpus()
- self.make_table()
- self.make_simi()
- else :
- dial.Destroy()
+ self.parametres.update(self.paramsimi)
- def make_corpus(self) :
- print 'make corpus'
- if not self.cmd :
- dlg = progressbar(self, maxi = 6)
- self.corpus.supplementaires = [option for option in self.KeyConf.options('KEYS') if self.KeyConf.get('KEYS', option) == "2"]
- self.corpus.typeactive = [option for option in self.KeyConf.options('KEYS') if self.KeyConf.get('KEYS', option) == "1"]
- ucis_txt, ucis_paras_txt = self.corpus.start_analyse(self.parent, dlg = dlg, cmd = self.cmd)
- del ucis_txt
-
- if not self.cmd :
- dlg.Update(5, '%i ucis - Construction des uces' % len(ucis_paras_txt))
- self.corpus.make_ucis_paras_uces(ucis_paras_txt, make_uce = True)
- del ucis_paras_txt
-
- if self.corpus.para_coords != [[] for val in self.corpus.para_coords] :
- self.corpus.parametre['para'] = True
- else :
- self.corpus.parametre['para'] = False
- self.corpus.make_etoiles(self.corpus.para_coords)
- print 'len(ucis_paras_uces)', len(self.corpus.ucis_paras_uces)
+ def makefiles(self, lim=3) :
+ #self.actives, lim = self.corpus.make_actives_nb(self.parametres.get('max_actives',1500), 1)
+ self.parametres['eff_min_forme'] = lim
+ self.parametres['nbactives'] = len(self.actives)
+ self.parametres['fromprof'] = False
+ self.corpus.make_and_write_sparse_matrix_from_uces(self.actives, self.pathout['mat01.csv'], self.pathout['listeuce1.csv'])
+ with open(self.pathout['actives.csv'], 'w') as f :
+ f.write('\n'.join(self.actives).encode(self.ira.syscoding))
- if not self.cmd :
- dlg.Update(6, u'Dictionnaires')
- uces, self.orderuces = self.corpus.make_forms_and_uces()
- self.corpus.ucenb = len(uces)
- self.corpus.make_lems(self.parent.lexique)
+class SimiFromCluster(SimiTxt) :
+ def __init__(self, ira, corpus, actives, lfreq, lchi, numcluster, parametres = None, dlg = False) :
+ self.actives = actives
+ self.numcluster = numcluster
+ self.lfreq = lfreq
+ self.lchi = lchi
+ parametres['name'] = 'simi_classe_%i' % (numcluster + 1)
+ dlg.Destroy()
+ SimiTxt.__init__(self, ira, corpus, parametres, dlg=True, lemdial = False)
+
+ def preferences(self) :
+ return self.parametres
- self.corpus.make_var_actives()
- self.corpus.make_var_supp()
- self.corpus.lems_eff = self.corpus.make_lem_eff()
+ def doanalyse(self) :
+ self.parametres['type'] = 'clustersimitxt'
+ self.pathout.basefiles(simipath)
+ self.indices = indices_simi
+ if self.dlg :
+ self.makesimiparam()
+ if 'bystar' in self.parametres :
+ del self.parametres['bystar']
+ dictcol = dict([[i, [act, self.corpus.getlemclustereff(act, self.numcluster)]] for i, act in enumerate(self.actives)])
+ continu = True
+ #print self.dlg
+ if self.dlg :
+ self.dlg.Destroy()
+ self.stars = []#copy(self.listet)
+ self.parametres['stars'] = 0#copy(self.listet)
+ self.parametres['sfromchi'] = 1
+ prep = PrepSimi(self.ira, self, self.parametres, self.pathout['selected.csv'], self.actives, indices_simi, wordlist=dictcol)
+ if prep.val == wx.ID_OK :
+ continu = True
+ self.parametres = prep.parametres
+ else :
+ continu = False
+ if continu :
+ self.dlg = progressbar(self.parent, 3)
+ self.makefiles()
+ self.parametres['type'] = 'clustersimitxt'
+ script = PrintSimiScript(self)
+ script.make_script()
+ if not self.doR(script.scriptout, dlg = self.dlg, message = 'R ...') :
+ return False
+ if self.parametres['type_graph'] == 1:
+ if self.parametres['svg'] :
+ filename, ext = os.path.splitext(script.filename)
+ fileout = filename + '.svg'
+ else :
+ fileout = script.filename
+ if os.path.exists(self.pathout['liste_graph']):
+ graph_simi = read_list_file(self.pathout['liste_graph'])
+ graph_simi.append([os.path.basename(fileout), script.txtgraph])
+ else :
+ graph_simi = [[os.path.basename(fileout), script.txtgraph]]
+ print_liste(self.pathout['liste_graph'], graph_simi)
+ else :
+ return False
- #variables = treat_var_mod(listet)
- #print(variables)
- #self.corpus.write_etoiles(self.dictpathout['etoiles'])
- if not self.cmd :
- dlg.Destroy()
-
- def make_table(self) :
- if 'orderuces' not in dir(self) :
- self.orderuces = [(i,j,k) for i, uci in enumerate(self.corpus.ucis_paras_uces) for j, para in enumerate(uci) for k, uce in enumerate(para)]
- self.orderuces = dict([[val, i] for i, val in enumerate(self.orderuces)])
- self.corpus.ucenb = len(self.orderuces)
- #tabuc1 = self.corpus.make_table_with_uce(self.orderuces)
- #tabuc1.insert(0,self.corpus.actives)
- #tabuc1 = self.corpus.make_sparse_matrix_with_uce(self.orderuces)
- #self.corpus.write_sparse_matrix(self.dictpathout['mat01'], tabuc1, self.corpus.ucenb, len(self.corpus.actives))
- if self.corpus.actives is None :
- self.corpus.typeactive = [option for option in self.KeyConf.options('KEYS') if self.KeyConf.get('KEYS', option) == "1"]
- self.corpus.min_eff_formes()
- self.corpus.make_var_actives()
- self.corpus.make_and_write_sparse_matrix_from_uce(self.orderuces, self.dictpathout['mat01'])
- #self.corpus.write_tab(tabuc1,self.dictpathout['mat01'])
+ def makefiles(self) :
+ self.parametres['eff_min_forme'] = 3
+ self.parametres['nbactives'] = len(self.actives)
+ self.parametres['fromprof'] = True
+ self.corpus.make_and_write_sparse_matrix_from_classe(self.actives, self.corpus.lc[self.numcluster], self.pathout['mat01.csv'])
+ with open(self.pathout['actives.csv'], 'w') as f :
+ f.write('\n'.join(self.actives).encode(self.ira.syscoding))
+ with open(self.pathout['actives_nb.csv'], 'w') as f :
+ f.write('\n'.join([`val` for val in self.lfreq]))
+ with open(self.pathout['actives_chi.csv'], 'w') as f :
+ f.write('\n'.join([`val` for val in self.lchi]))
- def make_simi(self) :
- self.tableau = Tableau(self.parent, '')
- self.tableau.listactives = self.corpus.actives
- self.tableau.parametre['fromtxt'] = True
- if 'lems_eff' not in dir(self.corpus) :
- self.corpus.lems_eff = self.corpus.make_lem_eff()
- #print('ATTENTION ETOILES')
- #self.paramsimi['bystar'] = True
- self.listet = self.corpus.get_unique_etoiles()
- self.listet.sort()
- self.tableau.listet = copy(self.listet)
- self.paramsimi['stars'] = copy(self.listet)
- #self.paramsimi['cexfromchi'] = True
- self.paramsimi['sfromchi'] = False
- #self.paramsimi['vlabcolor'] = True
- self.tableau.actives = dict([[lem, self.corpus.lems_eff[lem]] for lem in self.corpus.actives])
- self.corpus.save_corpus(self.dictpathout['corpus'])
- DoSimi(self, fromprof = self.dictpathout['mat01'], param = self.paramsimi, pathout = self.pathout)
projects / iramuteq / blobdiff