【解决报错&原因分析】画图plt.contourf(X,Y,Z)报错TypeError: unhashable type: ‘numpy.ndarray‘（含详细示例讲解）

今天简化画图代码的时候发现了很奇怪的报错现象，经过一系列尝试找到了根源，希望帮助后来人，主要问题出现在如下语句中（为了体现问题、方便比对，特意在这改变了x为xx，如果你不想看这冗长的示例，可以直接按照下文红字的方法修改）

import numpy as np
import matplotlib.pyplot as plt
#===========做等值线图===========
y = x = np.arange(10)
xx = [str(i) for i in x]#将x中的元素转化为字符串类型
X,Y = np.meshgrid(xx,y)
Z = np.sin(x)[:, np.newaxis] * np.cos(y)[np.newaxis, :]
plt.contourf(X,Y,Z)
#===========报错信息==============
'''
Traceback (most recent call last):

  Input In [63] in 
    plt.contourf(X,Y,Z)

  ...

TypeError: unhashable type: 'numpy.ndarray'
'''
#X、Y、Z的输出形式
'''
X
Out[90]: 
array([['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'],
       ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'],
       ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'],
       ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'],
       ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'],
       ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'],
       ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'],
       ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'],
       ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'],
       ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9']], dtype='

经过多次尝试，发现这是由于X和Y中含有'string'(字符)类型的元素导致的，只需更改为'int'或'float'(数字)，就能防止报错，并不需要改变X和Y的类型，他们可以依然是'numpy.ndarray'。

更改示例如下，

y = x = np.arange(10)
X,Y = np.meshgrid(x,y)
Z = np.sin(x)[:, np.newaxis] * np.cos(y)[np.newaxis, :]
plt.contourf(X,Y,Z)
plt.show()
'''
X
Out[85]: 
array([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
       [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]])

Y
Out[86]: 
array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
       [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
       [2, 2, 2, 2, 2, 2, 2, 2, 2, 2],
       [3, 3, 3, 3, 3, 3, 3, 3, 3, 3],
       [4, 4, 4, 4, 4, 4, 4, 4, 4, 4],
       [5, 5, 5, 5, 5, 5, 5, 5, 5, 5],
       [6, 6, 6, 6, 6, 6, 6, 6, 6, 6],
       [7, 7, 7, 7, 7, 7, 7, 7, 7, 7],
       [8, 8, 8, 8, 8, 8, 8, 8, 8, 8],
       [9, 9, 9, 9, 9, 9, 9, 9, 9, 9]])

Z
Out[87]: 
array([[ 0.        ,  0.        , -0.        , -0.        , -0.        ,
         0.        ,  0.        ,  0.        , -0.        , -0.        ],
       [ 0.84147098,  0.45464871, -0.35017549, -0.83304996, -0.55002214,
         0.2386935 ,  0.80795544,  0.63438687, -0.12243406, -0.76668968],
       [ 0.90929743,  0.4912955 , -0.37840125, -0.90019763, -0.59435646,
         0.2579333 ,  0.87308037,  0.68552138, -0.13230281, -0.8284884 ],
       [ 0.14112001,  0.07624747, -0.05872664, -0.13970775, -0.09224219,
         0.04003041,  0.13549924,  0.10639069, -0.02053297, -0.12857871],
       [-0.7568025 , -0.40890213,  0.31494096,  0.74922879,  0.49467912,
        -0.21467625, -0.72665927, -0.57055511,  0.11011479,  0.68954566],
       [-0.95892427, -0.518109  ,  0.3990533 ,  0.94932784,  0.62679474,
        -0.27201056, -0.9207306 , -0.72293517,  0.13952351,  0.87370493],
       [-0.2794155 , -0.15096884,  0.11627788,  0.27661925,  0.18263816,
        -0.07925961, -0.26828646, -0.21065197,  0.04065496,  0.25458392],
       [ 0.6569866 ,  0.35497137, -0.27340289, -0.6504118 , -0.4294351 ,
         0.18636225,  0.63081901,  0.49530368, -0.09559157, -0.59860037],
       [ 0.98935825,  0.53455254, -0.4117183 , -0.97945724, -0.64668771,
         0.28064352,  0.94995239,  0.74587941, -0.14395166, -0.90143424],
       [ 0.41211849,  0.22266857, -0.1715018 , -0.40799421, -0.26937862,
         0.11690243,  0.39570392,  0.31069706, -0.05996325, -0.37549362]])
'''

输出等值线图成功了：

 

显而易见地，两种写法并没有改变X和Y的numpy.adarray类型，只是做了列表元素类型上的修改。

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