[RL]均匀分布与高斯分布图绘制

简单分布图绘制

一、导入 import二、均匀分布与高斯分布函数三、可视化四、试验

一、导入 import

import numpy as np import matplotlib.pyplot as plt

二、均匀分布与高斯分布函数

均匀分布： def uniform(): return np.random.rand() #生成[0, 1)的数据 高斯分布： def gaussian(mean, sigma): return sigma*np.random.randn() + mean #randn生成均值为0，标准差为1的标准正态分布，sigma用于扩大数据，mean用来控制正态分布的对称轴

三、可视化

def plot(val_list): min_val = min(val_list) max_val = max(val_list) val = max(abs(min_val), abs(max_val)) max_val = val min_val = 0 if abs(min_val) < 1e-5 else -val if min_val < 0 else min_val plt.hist(val_list, density=True, bins=100, range=[min_val, max_val]) #绘制直方图 plt.ylim([0., 2.05]) plt.gca().set(title='PDF', xlabel='Values')

四、试验

vals = [uniform() for _ in range(100000)] plot(vals)

vals = [gaussian(0, 1) for _ in range(100000)] plot(vals)

vals = [gaussian(-1, 1) for _ in range(100000)] plot(vals)

vals = [gaussian(5, 3) for _ in range(100000)] plot(vals)

vals = [gaussian(5, 0.2) for _ in range(100000)] plot(vals)

sad = ':(' happy = ':)' sad if uniform() < 0.3 else happy

‘😦’ 哈哈