-#!/bin/env python
# -*- coding: utf-8 -*-
#Author: Pierre Ratinaud
-#Copyright (c) 2008-2012 Pierre Ratinaud
+#Copyright (c) 2008-2020 Pierre Ratinaud
+#modification pour python 3 : Laurent Mérat, 6x7 - mai 2020
#License: GNU/GPL
-from chemins import ffr
-from chemins import PathOut
-from analysetxt import AnalyseText
-#from corpus import Corpus
-from guifunct import getPage, getCorpus
-from ConfigParser import RawConfigParser
-from functions import sortedby, progressbar, CreateIraFile, exec_rcode, check_Rresult, DoConf
-from dialog import StatDialog
-from openanalyse import OpenAnalyse
-#from ttparser import *
+#------------------------------------
+# import des modules python
+#------------------------------------
import tempfile
from time import sleep
-import wx
-import os
-
import logging
-logger = logging.getLogger('iramuteq.textstat')
+import langue
+langue.run()
+#------------------------------------
+# import des fichiers du projet
+#------------------------------------
+from chemins import ffr
+from analysetxt import AnalyseText
+from functions import sortedby, progressbar, exec_rcode, check_Rresult
+
+
+logger = logging.getLogger('iramuteq.textstat')
class Stat(AnalyseText) :
+
def doanalyse(self) :
self.make_stats()
return self.parametres
def make_stats(self):
- if self.dlg :
- if not 'dlg' in dir(self) :
- self.dlg = progressbar(self, 7)
-
+# if self.dlg :
+# if not 'dlg' in dir(self) :
+ self.dlg = progressbar(self, 7)
formes = self.corpus.lems
tot = [[forme, formes[forme].freq, formes[forme].gram] for forme in formes if formes[forme].freq > 1]
- tot = sortedby(tot, 2,1)
+ tot = sortedby(tot, 2, 1)
tot = [[i, val] for i, val in enumerate(tot)]
hapax = [[forme, formes[forme].freq, formes[forme].gram] for forme in formes if formes[forme].freq == 1]
hapax = sortedby(hapax, 1, 1)
act = [[forme, formes[forme].freq, formes[forme].gram] for forme in formes if formes[forme].act == 1]
act = sortedby(act, 2, 1)
act = [[i, val] for i, val in enumerate(act)]
- supp = [[forme, formes[forme].freq, formes[forme].gram] for forme in formes if formes[forme].act == 2]
+ supp = [[forme, formes[forme].freq, formes[forme].gram] for forme in formes if formes[forme].act == 2]
supp = sortedby(supp, 2, 1)
-
supp = [[i, val] for i, val in enumerate(supp)]
-
- self.result = {u'total' : dict(tot), u'formes_actives' : dict(act), u'formes_supplémentaires' : dict(supp), u'hapax' : dict(hapax), u'glob' : ''}
+ ucesize = self.corpus.getucesize()
+ with open(self.pathout['stsize.csv'], 'w') as f :
+ f.write('\n'.join([repr(val) for val in ucesize]))
+ self.result = {'total' : dict(tot), 'formes_actives' : dict(act), 'formes_supplémentaires' : dict(supp), 'hapax' : dict(hapax), 'glob' : ''}
occurrences = sum([val[1][1] for val in tot]) + len(hapax)
phapax = (float(len(hapax)) / float(occurrences)) * 100
phapax_forme = (float(len(hapax)) / (float(len(formes)))) * 100
moy_occu_mot = float(occurrences) / float(len(formes))
- txt = 'Globale\n'
- txt += 'nombre de textes : %i\n' % len(self.corpus.ucis)
- txt += 'nombre d\'occurrences : %i\n' % occurrences
- txt += 'nombre de formes : %i\n' % (len(formes))
- txt += 'moyenne d\'occurrences par forme : %.2f\n' % moy_occu_mot
- txt += 'nombre d\'hapax : %i (%.2f%% des occurrences - %.2f%% des formes)\n' % (len(hapax), phapax, phapax_forme)
- print float(occurrences), float(len(self.corpus.ucis))
- txt += 'moyenne d\'occurrences par texte : %.2f' % (float(occurrences)/float(len(self.corpus.ucis)))
+ txt = ''.join([_('Abstract'), '\n'])
+ txt += ''.join([_('Number of texts'),' : ', '%i\n' % len(self.corpus.ucis)])
+ txt += ''.join([_("Number of occurrences"),' : %i\n' % occurrences])
+ txt += ''.join([_('Number of forms'), ' : %i\n' % (len(formes))])
+ txt += ''.join([_("Number of hapax"),' : %i (%.2f%% ' % (len(hapax),phapax), _('of occurrences'), ' - %.2f%% ' % phapax_forme, _('of forms'), ')\n'])
+ txt += ''.join([_("Mean of occurrences by text"), ' : %.2f' % (float(occurrences)/float(len(self.corpus.ucis)))])
if self.dlg :
- self.dlg.Update(7, u'Ecriture...')
+ self.dlg.Update(7, 'Ecriture...')
self.result['glob'] = txt
self.print_result()
# for Zipf grap
plot(tot[,1], log = 'xy', xlab='log(rangs)', ylab = 'log(frequences)', col = 'red', pch=16)
dev.off()
""" % (ffr(self.pathout['zipf.png']))
+ txt += """
+ stsize <- read.csv2("%s", header=F)
+ open_file_graph("%s", width = 400, height = 400)
+ barplot(table(stsize[,1]))
+ dev.off()
+ """ % (ffr(self.pathout['stsize.csv']), ffr(self.pathout['segments_size.png']))
tmpscript = tempfile.mktemp(dir=self.parent.TEMPDIR)
- with open(tmpscript, 'w') as f :
+ with open(tmpscript, 'w', encoding='utf8') as f :
f.write(txt)
pid = exec_rcode(self.parent.RPath, tmpscript, wait = False)
while pid.poll() == None :
for key in self.result :
if key != 'glob' :
dico = self.result[key]
- toprint = [[dico[val][0],`dico[val][1]`, dico[val][2]] for val in dico]
- with open(self.pathout['%s.csv' % key], 'w') as f :
- f.write('\n'.join([';'.join([val for val in ligne]) for ligne in toprint]).encode(self.parent.syscoding))
+ toprint = [[dico[val][0],repr(dico[val][1]), dico[val][2]] for val in dico]
+ with open(self.pathout['%s.csv' % key], 'w', encoding='utf8') as f :
+ f.write('\n'.join([';'.join([val for val in ligne]) for ligne in toprint]))
else :
- with open(self.pathout['%s.txt' % 'glob'], 'w') as f :
- f.write(self.result['glob'].encode(self.parent.syscoding))
+ with open(self.pathout['%s.txt' % 'glob'], 'w', encoding='utf8') as f :
+ f.write(self.result['glob'])
projects / iramuteq / blobdiff