human
Solve the following python programming problem given the following code:
def LoadMultiDomainDataset(path_data, remove_bigrams = True) : 
    random.seed (1) 
    pos = [] 
    neg = [] 
    def get_words(line, remove_bigrams = True) : 
        z = [tuple (x.split (':')) for x in re.findall ('\\w*?:\\d', line)] 
        if remove_bigrams : 
            z = ' '.join ([' '.join (([x [0]] * int (x [1]))) for x in z if ('_' not in x [0])]) 
else : 
            z = ' '.join ([' '.join (([x [0]] * int (x [1]))) for x in z]) 
return z 
for line in open (os.path.join (path_data, 'negative.review')) : 
        neg.append (get_words (line, remove_bigrams)) 
for line in open (os.path.join (path_data, 'positive.review')) : 
        pos.append (get_words (line, remove_bigrams)) 
random.shuffle (pos) 
    random.shuffle (neg) 
    split_pos = int ((len (pos) * 0.8)) 
    split_neg = int ((len (neg) * 0.8)) 
    train_data = (test_data [: split_pos] + neg [: split_neg]) 
    test_data = (pos [split_pos :] + neg [split_neg :]) 
    train_labels = (([1] * len (pos [: split_pos])) + ([0] * len (neg [: split_neg]))) 
    test_labels = (([1] * len (pos [split_pos :])) + ([0] * len (neg [split_neg :]))) 
    return (train_data, np.array (train_labels), test_data, np.array (test_labels), ['neg', 'pos']) 

    
    

    Fix the buggy line: train_data = (test_data [: split_pos] + neg [: split_neg])
assistant
#Here is Python code to fix the buggy line: train_data = (test_data [: split_pos] + neg [: split_neg])
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train_data = (pos [: split_pos] + neg [: split_neg])