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