NumPy的矩阵必须是2维误差

Question

我有以下代码：

import numpy as np 
def J(x, y): 
    return np.matrix([[8-(4 * y), -4 * y], [y, -5 + x]]) 

x_0 = np.matrix([[1], [1]]) 
test = J(x_0[0], x_0[1]) 

当我去运行它，我收到以下错误：

Traceback (most recent call last): 
    File "broyden.py", line 15, in <module> 
    test = J(x_0[0][0], x_0[1][0]) 
    File "broyden.py", line 12, in J 
    return np.matrix([[8-(4 * y), -4 * y], [y, -5 + x]]) 
    File "/home/collin/anaconda/lib/python2.7/site-packages/numpy/matrixlib/defmatrix.py", line 261, in __new__ 
    raise ValueError("matrix must be 2-dimensional") 
ValueError: matrix must be 2-dimensional 

我不明白为什么我会得到这个错误。一切似乎都是二维的。

Answer 1

x_0[0]的类型仍然是numpy.matrixlib.defmatrix.matrix，而不是标量值。 你需要得到一个比例值作为矩阵元素。试试这个代码

test = J(x_0.item(0), x_0.item(1))