利用python绘制正态分布曲线

#-*-coding:utf-8-*-
\"\"\"
python绘制标准正态分布曲线
\"\"\"
# ==============================================================
import numpy as np
import math
import matplotlib.pyplot as plt


def gd(x, mu=0, sigma=1):
  \"\"\"根据公式，由自变量x计算因变量的值

  Argument:
    x: array
      输入数据（自变量）
    mu: float
      均值
    sigma: float
      方差
  \"\"\"
  left = 1 / (np.sqrt(2 * math.pi) * np.sqrt(sigma))
  right = np.exp(-(x - mu)**2 / (2 * sigma))
  return left * right


if __name__ == \'__main__\':
  # 自变量
  x = np.arange(-4, 5, 0.1)
  # 因变量（不同均值或方差）
  y_1 = gd(x, 0, 0.2)
  y_2 = gd(x, 0, 1.0)
  y_3 = gd(x, 0, 5.0)
  y_4 = gd(x, -2, 0.5)

  # 绘图
  plt.plot(x, y_1, color=\'green\')
  plt.plot(x, y_2, color=\'blue\')
  plt.plot(x, y_3, color=\'yellow\')
  plt.plot(x, y_4, color=\'red\')
  # 设置坐标系
  plt.xlim(-5.0, 5.0)
  plt.ylim(-0.2, 1)

  ax = plt.gca()
  ax.spines[\'right\'].set_color(\'none\')
  ax.spines[\'top\'].set_color(\'none\')
  ax.xaxis.set_ticks_position(\'bottom\')
  ax.spines[\'bottom\'].set_position((\'data\', 0))
  ax.yaxis.set_ticks_position(\'left\')
  ax.spines[\'left\'].set_position((\'data\', 0))

  plt.legend(labels=[\'$\\mu = 0, \\sigma^2=0.2$\', \'$\\mu = 0, \\sigma^2=1.0$\', \'$\\mu = 0, \\sigma^2=5.0$\', \'$\\mu = -2, \\sigma^2=0.5$\'])
  plt.show()