好吧，stats.probplot 让我有点困惑.该文档明确指出:

Okay, so stats.probplot has left me a little confused. The documentation clearly states that:

probplot 生成概率图，不应与Q-Q 或 P-P 图.

probplot generates a probability plot, which should not be confused with a Q-Q or a P-P plot.

然而，我能找到的所有来源都表明概率图是指 Q-Q 图或 P-P 图.去图.

Yet all the sources I can find state that a probability plot refers to either a Q-Q plot or P-P plot. Go figure.

无论如何，就我而言，您生成的是一个 Q-Q 图.

Anyway, as far as I'm concerned, what you've generated is a Q-Q plot.

在我看来，stats.probplot 的选项 fit=False 被忽略，并且总是向数据添加回归线.

It also seems to me that the option fit=False of stats.probplot is ignored, and a regression line is always added to the data.

无论如何，为了得到你想要的，我们可以显式地创建一个 matplotlib 轴实例，并使用 get_lines 方法去除不需要的回归线并改变标记颜色.

Anyway, to get what you desire, we can explicitly create a matplotlib axes instance, and use the get_lines method to remove the unwanted regression lines and change the marker colours.

import scipy.stats as stats
import numpy as np
import matplotlib.pyplot as plt

plt.style.use('seaborn')

x = numpy.random.beta(2, 3, size=100)

fig, ax = plt.subplots(1, 1, figsize=(6, 4))
stats.probplot(x, dist=stats.beta, sparams=(2,3), plot=plt, fit=False)
stats.probplot(x, dist=stats.beta, sparams=(1,2), plot=plt, fit=False)
stats.probplot(x, dist=stats.beta, sparams=(1,4), plot=plt, fit=False)

# Remove the regression lines
ax.get_lines()[1].remove()
ax.get_lines()[2].remove()
ax.get_lines()[3].remove()

# Change colour of scatter
ax.get_lines()[0].set_markerfacecolor('C0')
ax.get_lines()[1].set_markerfacecolor('C1')
ax.get_lines()[2].set_markerfacecolor('C2')

# Add on y=x line
ax.plot([0, 1], [0, 1], c='C3')

这给了我以下内容，我认为这次确实是您想要的:

This gave me the following, which I think this time really is what you desired: