曲线之间的着色交点

Question

我想为累积概率函数（CDF）和阶跃函数之间的交点着色。这是我的代码

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from scipy.stats import norm


np.random.seed(1024)

mu = 200
sigma = 25
n_bins = 50
bins = np.array([121.95403681, 124.56265713, 127.17127746, 129.77989779,
                 132.38851812, 134.99713844, 137.60575877, 140.2143791 ,
                 142.82299943, 145.43161975, 148.04024008, 150.64886041,
                 153.25748074, 155.86610106, 158.47472139, 161.08334172,
                 163.69196205, 166.30058237, 168.9092027 , 171.51782303,
                 174.12644336, 176.73506368, 179.34368401, 181.95230434,
                 184.56092467, 187.16954499, 189.77816532, 192.38678565,
                 194.99540598, 197.6040263 , 200.21264663, 202.82126696,
                 205.42988729, 208.03850761, 210.64712794, 213.25574827,
                 215.8643686 , 218.47298892, 221.08160925, 223.69022958,
                 226.29884991, 228.90747023, 231.51609056, 234.12471089,
                 236.73333122, 239.34195154, 241.95057187, 244.5591922 ,
                 247.16781253, 249.77643285, 252.38505318])

my_norm = norm(loc=mu, scale=sigma)
x = np.random.normal(mu, sigma, size=100)

fig, ax = plt.subplots(figsize=(8, 4))

# Add a line showing the expected distribution.
y = ((1 / (np.sqrt(2 * np.pi) * sigma)) * np.exp(-0.5 * (1 / sigma * (bins - mu))**2))
y = y.cumsum()
y /= y[-1]

step_x = [10, 20, 30, 40, 50]
step_y = [0.02, 0.1, 0.3, 0.7, 1]

ax.plot(step_x, step_y, drawstyle='steps-pre')
cdf_x = range(n_bins+1)
ax.plot(cdf_x, y, color='black', linewidth=2)
# tidy up the figure
ax.grid(False)
# ax.legend(loc='right')
ax.set_title('CDF plot')
ax.set_xlabel('returns')
ax.set_ylabel('probability density')

但是，通过添加

ax.fill_between(cdf_x, step_y, where=None, facecolor='pink', interpolate=True)

之后

ax.plot(cdf_x, y, color='black', linewidth=2)

返回

ValueError: operands could not be broadcast together with shapes (51,) (5,) 

由于形状不同，如何解决？

Answer 1

使用fill_between时，您需要提供两个长度相同的y-data。在这里，我建议您逐步填写：

for i,iy in enumerate(step_y[1:]):
    ax.fill_between(cdf_x[10*i+10:10*i+21],y[10*i+10:10*i+21],iy,facecolor='pink')