def ext(): # Read the pairs print "Read Pairs" print "Read Train" train = d.read_train_pairs() print "Read Valid" valid = d.read_valid_pairs() print "Read Sup1" sup1 = d.read_sup1_train_pairs() print "Read Sup2" sup2 = d.read_sup2_train_pairs() print "Read Sup3" sup3 = d.read_sup3_train_pairs() # Get the feature extractor combined = feat.feature_extractor() # Extract the features print 'Extract the features' print "Extract Train" train_att = combined.fit_transform(train) print "Extract Valid" valid_att = combined.fit_transform(valid) print "Extract Sup1" sup1_att = combined.fit_transform(sup1) print "Extract Sup2" sup2_att = combined.fit_transform(sup2) print "Extract Sup3" sup3_att = combined.fit_transform(sup3) print "Join" total_new_att = np.vstack((train_att, valid_att, sup1_att, sup2_att, sup3_att)) # Save extracted data np.save('total_new_att.npy', total_new_att)
def extrair_tudo(): combined = new_features1() print "Train" train = d.read_train_pairs() train_att = combined.fit_transform(train) np.save(train_att, open("train_att.npy", "wb")) print "Train1" valid = d.read_valid_pairs() valid_att = combined.fit_transform(valid) np.save(valid_att, open("valid_att.npy", "wb")) print "Train2" sup1 = d.read_sup1_train_pairs() sup1_att = combined.fit_transform(sup1) np.save(sup1_att, open("sup1_att.npy", "wb")) print "Train3" sup2 = d.read_sup2_train_pairs() sup2_att = combined.fit_transform(sup2) np.save(sup1_att, open("sup2_att.npy", "wb")) print "Train4" sup3 = d.read_sup3_train_pairs() sup3_att = combined.fit_transform(sup3) np.save(sup1_att, open("sup3_att.npy", "wb"))