Question

我有一个代码，使用numpy和hermval以及多个函数来计算最终给定参数的psi。但我一直收到错误numpy.ndarray object not callable，我真的不明白为什么会这样。以下是我的代码的相关部分：

import numpy as np
import math
from numpy.linalg import eigh
from numpy.polynomial.hermite import hermval

def matrices(N, lam):
    H_0 = np.zeros([N+1, N+1])
    x_four_matrix = np.zeros([N+1, N+1])
    for n in range(N+1):
        for m in range(N+1):
            if n == m:
                H_0[n][m] = n + 0.5
                x_four_matrix[n][m] = (6.0*n**2 + 6.0*n + 3.0)/4.0
            elif n == m-2:
                x_four_matrix[n][m] = np.sqrt((n+1)*(n+2))*(n+1.5)
            elif n == m+2:
                x_four_matrix[n][m] = (n-0.5)*np.sqrt(n*(n-1))
            elif n == m-4:
                x_four_matrix[n][m] = np.sqrt((n+1)*(n+2)*(n+3)*(n+4))/4.0
            elif n == m+4:
                x_four_matrix[n][m] = np.sqrt((n-3)*(n-2)*(n-1)*n)/4.0
    return H_0, x_four_matrix

def H_lam(N, lam):
    return matrices(N, lam)[0] + lam*matrices(N, lam)[1]

# Solve for eigenvalues (energies)
def lowest_eigenvals(N, n, lam):
    lowest_eigs = []
    eigenvals = eigh(H_lam(N, lam))[0]
    eigenvals.sort()
    for i in range(n):
        lowest_eigs.append(eigenvals[i])
    return lowest_eigs

# Solve for eigenvectors
def lowest_eigenvectors(N, n, lam):
    lowest_vecs = []
    for i in range(len(lowest_eigenvals(N, n, lam))):
        for j in range(len(eig(H_lam(N, lam))[0])):
            if lowest_eigenvals(N, n, lam)[i] == eigh(H_lam(N, lam))[0][j]:
                lowest_vecs.append(eigh(H_lam(N, lam))[1][j])
    return np.array(lowest_vecs)

def N_coeff(i):
    return 1.0/np.sqrt(2**i*math.factorial(i)*np.sqrt(np.pi))

# for E_0 (first eigenfunction):
def psi(x, lowest_eigenvectors, i):
    herm_coeffs = [element*N_coeff(i) for element in lowest_eigenvectors(N, n, lam)[i]]
    return np.exp((x**2)/2.0)*hermval(x, herm_coeffs)

print [element*N_coeff(0) for element in lowest_eigenvectors(100, 4, 0.1)[0]]
print psi(1.0, lowest_eigenvectors(100, 4, 1.0), 0) # for lambda = 1

然后在我的上一个print语句中，我得到TypeError: 'numpy.ndarray' object is not callable来自我上一个函数中的herm_coeffs行。但是我不确定为什么会发生这种情况，因为第二个到最后一个print语句打印正确！这是怎么回事？

这是追溯：

TypeError                                 Traceback (most recent call last)
<ipython-input-350-04692f269a26> in <module>()
     13 # print [element*N_coeff(0) for element in lowest_eigenvectors(100, 4, 0.1)[0]]
     14 
---> 15 print psi(1.0, lowest_eigenvectors(100, 4, 0.1), 0)

<ipython-input-350-04692f269a26> in psi(x, lowest_eigenvectors, i)
      7 # for E_0 (first eigenfunction):
      8 def psi(x, lowest_eigenvectors, i):
----> 9     herm_coeffs = [element*N_coeff(i) for element in lowest_eigenvectors(N, n, lam)[i]]
     10     return np.exp((x**2)/2.0)*hermval(x, herm_coeffs)
     11 

TypeError: 'numpy.ndarray' object is not callable

Answer 1

函数lowest_eigenvectors中的

psi参数名称与函数lowest_eigenvectors发生冲突。

编辑：由于psi函数位于同一个lowest_eigenvectors内，因此您似乎无需通过psi函数lowest_eigenvectors 3}}为import matplotlib.pyplot as plt import numpy as np #create x and y values xval = np.arange(1,10) yval = np.square(xval) #define error bars and markersize yerrmi = np.abs(np.cos(xval) * xval) yerrpl = np.abs(np.sin(xval) * xval) yerr = np.stack([yerrpl, yerrmi]) markerpl = 5 * yval #plot error bars plt.errorbar(xval, yval, yerr = yerr, ls = "None", color = "r") #plot scatter plot plt.scatter(xval, yval, s = 5 * yval, marker = "h", color = "r") plt.show()。

Answer 2

建立@Scott建议的内容，我认为psi应该更改为：

def psi(x, vectors, i):
    herm_coeffs = [element*N_coeff(i) for element in vectors[i]]
    return np.exp((x**2)/2.0)*hermval(x, herm_coeffs)

print psi(1.0, lowest_eigenvectors(100, 4, 1.0), 0)

换句话说，您计算vectors = lowest_eigenvectors(100, 4, 1.0)，并将其传递给psi。即使你有这个数组与函数命名正确，使用：

lowest_eigenvectors(N, n, lam)

psi中的

会出现问题，因为N, n, lam未在函数中定义或全局定义。

我想知道这个功能是否可以通过以下方式进一步简化：

herm_coeffs = N_coeff(i)*vectors[i]

不明白为什么我得到'numpy.ndarray对象不可调用'错误？

2 个答案: