如何修复：TypeError：'numpy.ndarray'对象不可调用

Question

我目前正在致力于实现牛顿-拉夫森算法来解决统计问题。但是，我遇到了矩阵乘法的问题，导致以下错误： TypeError: 'numpy.ndarray' object is not callable.

我使用的代码是：

def U_score(x, theta):
    a = theta[0]
    b = theta[1]
    n = len(x)
    d_a = -sp.digamma(a) + sp.digamma(a + b) + sum(np.log(x)) / n
    d_b = -sp.digamma(b) + sp.digamma(a + b) + sum(np.log(1 - x)) / n 
    return np.array([d_a, d_b])

def Hessiana(x, theta):
    a = theta[0]
    b = theta[1]
    h11 = sp.polygamma(1, a + b) - sp.polygamma(1, a)
    h12 = sp.polygamma(1, a + b)
    h21 = sp.polygamma(1, a + b) - sp.polygamma(1, b)
    h22 = sp.polygamma(1, a + b)
    return np.array([[h11, h12], [h21, h22]])

def H_inv(x, theta):
    H = Hessiana(x, theta)
    ridge = 1e-6  # Small constant
    H_ridge = H + ridge * np.eye(H.shape[0])
    return np.linalg.inv(H_ridge)

def max_likelihood(x, theta, tol):
    theta_new = np.array([0, 0])
    while np.linalg.norm(theta_new - theta) > tol:
        theta_new =  theta - H_inv(x, theta) @ U_score(x, theta)
    return theta_new

x = np.random.beta(2, 5, 100)
theta = np.array([1,1])
U = U_score(x, theta)
H = Hessiana(x, theta)
H_inv = H_inv(x, theta)

emv = max_likelihood(x, theta, 1e-5)
print(emv)

错误是：

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[80], line 1
----> 1 emv = max_likelihood(x, theta, 1e-5)
      2 print(emv)

Cell In[78], line 4
      2 theta_new = np.array([0, 0])
      3 while np.linalg.norm(theta_new - theta) > tol:
----> 4     theta_new =  theta - H_inv(x, theta) @ U_score(x, theta)
      5 return theta_new

TypeError: 'numpy.ndarray' object is not callable

Answer 1

您创建了一个名为

H_inv

的变量，它是

H_inv

函数的返回值（此结果是一个 numpy 数组），并且这样做会覆盖该函数。

H_inv = H_inv(x, theta)

当您在覆盖

max_likelihood

后调用

H_inv

时，Python 在全局范围内找到

H_inv

，但现在这是一个 numpy 数组而不是函数。

一个选项：将函数重命名为

get_H_inv

或类似名称，这样就不会将变量（函数的结果）与函数本身混淆。