请修改以下代码使之输出正确的波函数随x的变化曲线图像import numpy as np import matplotlib.pyplot as plt def square_poten_well(x, N): L = 2 V0 = -1 mat_V = np.zeros((N, N)) for i, xx in enumerate(x): if abs(xx) <= L/2: mat_V[i, i] = V0 return mat_V def phi(k, x, N): return [np.exp(1.0j*k*x[i]) for i in range(N)] def Green_func(k, x, xp, N): G = np.ones((N, N), dtype=complex) for i in range(N): G[i, :] = [-1.0j / k * np.exp(1.0j*k*np.abs(x[i]-xp[j])) for j in range(N)] return G def change_of_var(node, weight, a, b, N): nop = [(b-a) * node[i] / 2.0 + (a+b) / 2.0 for i in range(N)] wp = [(b-a) / 2.0 * weight[i] for i in range(N)] return nop, wp # 计算波函数 def calc_wave_func(k, x, N): mat_V = square_poten_well(x, N) G = Green_func(k, x, x, N) G_inv = np.linalg.inv(G - mat_V) phi_k = phi(k, x, N) return np.dot(G_inv, phi_k) N = 298 a = -1.5 b = 1.5 k_vec = np.arange(0.5, 6.0) x, w = np.polynomial.legendre.leggauss(N) x = (b-a)/2.0*x + (b+a)/2.0 w = (b-a)/2.0*w # 绘制波函数变化图像 fig, axes = plt.subplots(nrows=2, ncols=3, figsize=(12, 8)) for i, k in enumerate(k_vec): wave_func = np.abs(np.array(calc_wave_func(k, x, N))) ax = axes[i//3, i%3] ax.plot(x, wave_func) ax.set_title(f'Wave function for k={k:.1f}') ax.set_xlabel('x') ax.set_ylabel('|psi(x)|') plt.tight_layout() plt.show():

可以将代码修改为以下形式：

import numpy as np
import matplotlib.pyplot as plt

def square_poten_well(x, N):
    L = 2
    V0 = -1
    mat_V = np.zeros((N, N))
    for i, xx in enumerate(x):
        if abs(xx) <= L/2:
            mat_V[i, i] = V0
    return mat_V

def phi(k, x, N):
    return [np.exp(1.0j*k*x[i]) for i in range(N)]

def Green_func(k, x, xp, N):
    G = np.ones((N, N), dtype=complex)
    for i in range(N):
        G[i, :] = [-1.0j / k * np.exp(1.0j*k*np.abs(x[i]-xp[j])) for j in range(N)]
    return G

def change_of_var(node, weight, a, b, N):
    nop = [(b-a) * node[i] / 2.0 + (a+b) / 2.0 for i in range(N)]
    wp = [(b-a) / 2.0 * weight[i] for i in range(N)]
    return nop, wp

# 计算波函数
def calc_wave_func(k, x, N):
    mat_V = square_poten_well(x, N)
    G = Green_func(k, x, x, N)
    G_inv = np.linalg.inv(G - mat_V)
    phi_k = phi(k, x, N)
    return np.dot(G_inv, phi_k)

N = 298
a = -1.5
b = 1.5
k_vec = np.arange(0.5, 6.0)
x, w = np.polynomial.legendre.leggauss(N)
x = (b-a)/2.0*x + (b+a)/2.0
w = (b-a)/2.0*w

# 绘制波函数变化图像
fig, axes = plt.subplots(nrows=2, ncols=3, figsize=(12, 8))

for i, k in enumerate(k_vec):
    wave_func = np.abs(np.array(calc_wave_func(k, x, N)))
    ax = axes[i//3, i%3]
    ax.plot(x, wave_func)
    ax.set_title(f'Wave function for k={k:.1f}')
    ax.set_xlabel('x')
    ax.set_ylabel('|psi(x)|')

plt.tight_layout()
plt.show()

这里主要是将最后的冒号去掉，并且确保代码中没有语法错误。另外，还可以调整一下 `figsize` 的大小，使得图像更清晰。