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 as plt, matplotlib.cm as cm, pylab

nseries = 10
colors = cm.rainbow(np.linspace(0, 1, nseries))

all_x = []
all_y = []
for i in range(nseries):
    x = np.random.random(12)+i/10.0
    y = np.random.random(12)+i/5.0
    plt.scatter(x, y, color=colors[i])
    all_x.extend(x)
    all_y.extend(y)

# Could I somehow do the next part (add identity_line) if I haven't been keeping track of all the x and y values I've seen?
identity_line = np.linspace(max(min(all_x), min(all_y)),
                            min(max(all_x), max(all_y)))
plt.plot(identity_line, identity_line, color="black", linestyle="dashed", linewidth=3.0)

plt.show()

In order to achieve this I've had to keep track of all the x and y values that went into the scatter plot so that I know where identity_line should start and end. Is there a way I can get y=x to show up even if I don't have a list of all the points that I plotted? I would think that something in matplotlib can give me a list of all the points after the fact, but I haven't been able to figure out how to get that list.

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