打印utf-8的numpy数组？

Question

我有以下python2.7代码，其中预测值测试（阿拉伯字），但结果在数给出没有字符串如下：

['\xd8\xa7\xd9\x84\xd9\x85\xd8\xa7\xd9\x84' 
'\xd8\xa7\xd9\x84\xd9\x85\xd8\xa7\xd9\x84'] 

我的Python代码：

# -*- coding: utf-8 -*- 
import numpy as np 
from sklearn.pipeline import Pipeline 
from sklearn.ensemble import ExtraTreesClassifier 


class MeanEmbeddingVectorizer(object): 
    def __init__(self, word2vec): 
     self.word2vec = word2vec 
     # this line is different from python2 version - no more itervalues 
     self.dim = len(list(word2vec.values())[0]) 

    def fit(self, X, y): 
     return self 

    def transform(self, X): 
     return np.array([ 
      np.mean([self.word2vec[w] for w in words if w in self.word2vec] 
        or [np.zeros(self.dim)], axis=0) 
      for words in X 
     ]) 

w2v = { 
    'من': [1, 1], 
    'العراق': [1.01, 1.01], 
    'مصر': [1.02, 1.02], 
    'مال': [-1, -1], 
    'حرف جر': [-1.01, -1.01], 
    'السودان': [-1.02, -1.02], 
    'فلوس': [1, -1], 
    'دولة': [1.01, -1.01], 
    'مصاري': [1.02, -1.02] 
} 

model = Pipeline([ 
    ("word2vec vectorizer", MeanEmbeddingVectorizer(w2v)), 
    ("extra trees", ExtraTreesClassifier(n_estimators=200))]) 

X = [['في'], 
    ['عقود']] 
y = ['حرف جر', 'المال'] 
model.fit(X, y) 
# never before seen words!!! 
test_X = [['من'], ['فلوس']] 
print(model.predict(test_X)) 

所以我如何打印阿拉伯文字！

我试图检查结果阵起诉：

arr = model.predict(test_X) 

print(np.info(arr)) 

，并得到了以下结果：

class: ndarray 
shape: (2,) 
strides: (11,) 
itemsize: 11 
aligned: True 
contiguous: True 
fortran: True 
data pointer: 0x1189760 
byteorder: little 
byteswap: False 
type: |S11 
None 

Answer 1

你可以试试这个：

arr = model.predict(test_X) 
for e in arr: 
    print(e) 

输出：

المال 
المال