四条曲线

import numpy as np
import matplotlib.pyplot as plt

# 定义x的取值范围
x = np.linspace(-10, 10, 400)

# 定义y=kx+b，这里k=1, b=0作为示例
k, b = 1, 0
y_linear = k * x + b

# 定义y=e^x+c，这里c=0作为示例
c = 0
y_exp = np.exp(x/5) + c

# 定义y=sin(x)
y_sin = np.sin(x)

# 定义二维布朗运动曲线，这里使用随机数生成
x_brownian = np.linspace(0, 10, 1000)
y_brownian = np.random.normal(0, 1, len(x_brownian))
brownian_path = np.cumsum(y_brownian)

# 创建2x2的子图
fig, axs = plt.subplots(2, 2, figsize=(10, 10))

# 第一个图：y=kx+b
axs[0, 0].plot(x, y_linear, label='y=kx+b', color='crimson')
axs[0, 0].set_title('Linear Function')
axs[0, 0].legend()

# 第二个图：y=e^x+c
axs[0, 1].plot(x, y_exp, label='y=e^x+c', color='crimson')
axs[0, 1].set_title('Exponential Function')
axs[0, 1].legend()

# 第三个图：y=sin(x)
axs[1, 0].plot(x, y_sin, label='y=sin(x)', color='crimson')
axs[1, 0].set_title('Sine Function')
axs[1, 0].legend()

# 第四个图：二维布朗运动曲线
axs[1, 1].plot(x_brownian, brownian_path, label='2D Brownian Motion', color='crimson')
axs[1, 1].set_title('Brownian Motion')
axs[1, 1].legend()

# 调整子图间距
plt.tight_layout()

# 显示图形
plt.show()