matplotlib: 2 different legends on same graph
I have a plot where different colors are used for different parameters, and where different line styles are used for different algorithms. The goal is to compare the results of the different algorithms performed with similar parameters. It means in total I use 4 different colors, and 3 different line styles, for a total of 12 plots on the same graph.
I actually build the legend based on colors, associating each color with the corresponding parameter. Now I'd like to display a second legend on the same graph, with the meaning of each line style. It is possible to achieve that? How?
Here is what my code looks like actually:
colors = ['b', 'r', 'g', 'c']
cc = cycle(c)
for p in parameters:
d1 = algo1(p)
d2 = algo2(p)
d3 = algo3(p)
pyplot.hold(True)
c = next(cc)
pyplot.plot(d1, '-', color=c, label="d1")
pyplot.plot(d1, '--', color=c)
pyplot.plot(d2, '.-', color=c)
pyplot.legend()
There's a section in the matplotlib documentation on that exact subject.
Here's code for your specific example:
import itertools
from matplotlib import pyplot
colors = ['b', 'r', 'g', 'c']
cc = itertools.cycle(colors)
plot_lines = []
for p in parameters:
d1 = algo1(p)
d2 = algo2(p)
d3 = algo3(p)
pyplot.hold(True)
c = next(cc)
l1, = pyplot.plot(d1, '-', color=c)
l2, = pyplot.plot(d2, '--', color=c)
l3, = pyplot.plot(d3, '.-', color=c)
plot_lines.append([l1, l2, l3])
legend1 = pyplot.legend(plot_lines[0], ["algo1", "algo2", "algo3"], loc=1)
pyplot.legend([l[0] for l in plot_lines], parameters, loc=4)
pyplot.gca().add_artist(legend1)
Here's an example of its output:
Here is also a more "hands-on" way to do it (i.e. interacting explicitely with any figure axes):
import itertools
from matplotlib import pyplot
fig, axes = plt.subplot(1,1)
colors = ['b', 'r', 'g', 'c']
cc = itertools.cycle(colors)
plot_lines = []
for p in parameters:
d1 = algo1(p)
d2 = algo2(p)
d3 = algo3(p)
c = next(cc)
axes.plot(d1, '-', color=c)
axes.plot(d2, '--', color=c)
axes.plot(d3, '.-', color=c)
# In total 3x3 lines have been plotted
lines = axes.get_lines()
legend1 = pyplot.legend([lines[i] for i in [0,1,2]], ["algo1", "algo2", "algo3"], loc=1)
legend2 = pyplot.legend([lines[i] for i in [0,3,6]], parameters, loc=4)
axes.add_artist(legend1)
axes.add_artist(legend2)
I like this way of writing it since it allows potentially to play with different axes in a less obscure way. You can first create your set of legends, and then add them to the axes you want with the method "add_artist". Also, I am starting with matplotlib, and for me at least it is easier to understand scripts when objets are explicited.
NB: Be careful, your legends may be cutoff while displaying/saving. To solve this issue, use the method axes.set_position([left, bottom, width, length]) to shrink the subplot relatively to the figure size and make the legends appear.
What about using a twin ghost axis?
import matplotlib.pyplot as plt
import numpy as np
fig, ax = plt.subplots()
colors = ['b', 'r', 'g', ]
styles = ['-', '--', '-.']
for cc, col in enumerate(colors):
for ss, sty in enumerate(styles):
print(cc, ss)
ax.plot([0, 1], [cc, ss], c=colors[cc], ls=styles[ss])
for cc, col in enumerate(colors):
ax.plot(np.NaN, np.NaN, c=colors[cc], label=col)
ax2 = ax.twinx()
for ss, sty in enumerate(styles):
ax2.plot(np.NaN, np.NaN, ls=styles[ss],
label='style ' + str(ss), c='black')
ax2.get_yaxis().set_visible(False)
ax.legend(loc=1)
ax2.legend(loc=3)
plt.show()
You can also use line.get_label()
import matplotlib.pyplot as plt
plt.figure()
colors = ['b', 'r', 'g', 'c']
parameters = [1,2,3,4]
for p in parameters:
color = colors[parameters.index(p)]
plt.plot([1,10],[1,p], '-', c=color, label='auto label '+str(p))
lines = plt.gca().get_lines()
include = [0,1]
legend1 = plt.legend([lines[i] for i in include],[lines[i].get_label() for i in include], loc=1)
legend2 = plt.legend([lines[i] for i in [2,3]],['manual label 3','manual label 4'], loc=4)
plt.gca().add_artist(legend1)
plt.show()