Adding y=x to a matplotlib scatter plot if I haven't kept track of all the data points that went in

Question

Here\'s some code that does scatter plot of a number of different series using matplotlib and then adds the line y=x:

import numpy as np, matplotlib.pyplot a         


        

Answer 1

You don't need to know anything about your data per se. You can get away with what your matplotlib Axes object will tell you about the data.

See below:

import numpy as np
import matplotlib.pyplot as plt

# random data 
N = 37
x = np.random.normal(loc=3.5, scale=1.25, size=N)
y = np.random.normal(loc=3.4, scale=1.5, size=N)
c = x**2 + y**2

# now sort it just to make it look like it's related
x.sort()
y.sort()

fig, ax = plt.subplots()
ax.scatter(x, y, s=25, c=c, cmap=plt.cm.coolwarm, zorder=10)

Here's the good part:

lims = [
    np.min([ax.get_xlim(), ax.get_ylim()]),  # min of both axes
    np.max([ax.get_xlim(), ax.get_ylim()]),  # max of both axes
]

# now plot both limits against eachother
ax.plot(lims, lims, 'k-', alpha=0.75, zorder=0)
ax.set_aspect('equal')
ax.set_xlim(lims)
ax.set_ylim(lims)
fig.savefig('/Users/paul/Desktop/so.png', dpi=300)

Et voilà

Answer 2

If you set scalex and scaley to False, it saves a bit of bookkeeping. This is what I have been using lately to overlay y=x:

xpoints = ypoints = plt.xlim()
plt.plot(xpoints, ypoints, linestyle='--', color='k', lw=3, scalex=False, scaley=False)

or if you've got an axis:

xpoints = ypoints = ax.get_xlim()
ax.plot(xpoints, ypoints, linestyle='--', color='k', lw=3, scalex=False, scaley=False)

Of course, this won't give you a square aspect ratio. If you care about that, go with Paul H's solution.

Answer 3

In one line:

ax.plot([0,1],[0,1], transform=ax.transAxes)

No need to modify the xlim or ylim.