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"))
