Mercurial > ift6266
view scripts/CalcPropNist.py @ 138:128507ac4edf
Initial commit for the stacked convolutional denoising autoencoders
author | Owner <salahmeister@gmail.com> |
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date | Sun, 21 Feb 2010 17:30:38 -0600 |
parents | 2d671ab3b730 |
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#!/usr/bin/python # coding: utf-8 ''' Script qui calcule la proportion de chiffres, lettres minuscules et lettres majuscules dans NIST train et NIST test. Sylvain Pannetier Lebeuf dans le cadre de IFT6266, hiver 2010 ''' from pylearn.io import filetensor as ft import matplotlib.pyplot as plt #f1 = open('/home/sylvain/Dropbox/Msc/IFT6266/donnees/all_train_labels.ft') f1 = open('/data/lisa/data/nist/by_class/all/all_train_labels.ft') train = ft.read(f1) #f2 = open('/home/sylvain/Dropbox/Msc/IFT6266/donnees/all_test_labels.ft') f2 = open('/data/lisa/data/nist/by_class/all/all_test_labels.ft') test = ft.read(f2) f1.close() f2.close() #Les 6 variables train_c=0 train_min=0 train_maj=0 test_c=0 test_min=0 test_maj=0 classe=0 #variable utilisee pour voir la classe presentement regardee #Calcul pour le train_set for i in xrange(len(train)): classe=train[i] if classe < 10: train_c += 1 elif classe < 36: train_maj += 1 elif classe < 62: train_min += 1 for j in xrange(len(test)): classe=test[j] if classe < 10: test_c += 1 elif classe < 36: test_maj += 1 elif classe < 62: test_min += 1 print "Train set:",len(train),"\nchiffres:",float(train_c)/len(train),"\tmajuscules:",\ float(train_maj)/len(train),"\tminuscules:",float(train_min)/len(train),\ "\nchiffres:", float(train_c)/len(train),"\tlettres:",float(train_maj+train_min)/len(train) print "\nTest set:",len(test),"\nchiffres:",float(test_c)/len(test),"\tmajuscules:",\ float(test_maj)/len(test),"\tminuscules:",float(test_min)/len(test),\ "\nchiffres:", float(test_c)/len(test),"\tlettres:",float(test_maj+test_min)/len(test) if test_maj+test_min+test_c != len(test): print "probleme avec le test, des donnees ne sont pas etiquetees" if train_maj+train_min+train_c != len(train): print "probleme avec le train, des donnees ne sont pas etiquetees" #train set plt.subplot(211) plt.hist(train,bins=62) plt.axis([0, 62,0,40000]) plt.axvline(x=10, ymin=0, ymax=40000,linewidth=2, color='r') plt.axvline(x=36, ymin=0, ymax=40000,linewidth=2, color='r') plt.text(3,36000,'chiffres') plt.text(18,36000,'majuscules') plt.text(40,36000,'minuscules') plt.title('Train set') #test set plt.subplot(212) plt.hist(test,bins=62) plt.axis([0, 62,0,7000]) plt.axvline(x=10, ymin=0, ymax=7000,linewidth=2, color='r') plt.axvline(x=36, ymin=0, ymax=7000,linewidth=2, color='r') plt.text(3,6400,'chiffres') plt.text(18,6400,'majuscules') plt.text(45,6400,'minuscules') plt.title('Test set') #afficher plt.show()