Secondary axis with twinx(): how to add to legend?

I have a plot with two y-axes, using twinx(). I also give labels to the lines, and want to show them with legend(), but I only succ开发者_JAVA百科eed to get the labels of one axis in the legend:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rc
rc('mathtext', default='regular')

fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(time, Swdown, '-', label = 'Swdown')
ax.plot(time, Rn, '-', label = 'Rn')
ax2 = ax.twinx()
ax2.plot(time, temp, '-r', label = 'temp')
ax.legend(loc=0)
ax.grid()
ax.set_xlabel("Time (h)")
ax.set_ylabel(r"Radiation ($MJ\,m^{-2}\,d^{-1}$)")
ax2.set_ylabel(r"Temperature ($^\circ$C)")
ax2.set_ylim(0, 35)
ax.set_ylim(-20,100)
plt.show()

So I only get the labels of the first axis in the legend, and not the label 'temp' of the second axis. How could I add this third label to the legend?

You can easily add a second legend by adding the line:

ax2.legend(loc=0)

You'll get this:

But if you want all labels on one legend then you should do something like this:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rc
rc('mathtext', default='regular')

time = np.arange(10)
temp = np.random.random(10)*30
Swdown = np.random.random(10)*100-10
Rn = np.random.random(10)*100-10

fig = plt.figure()
ax = fig.add_subplot(111)

lns1 = ax.plot(time, Swdown, '-', label = 'Swdown')
lns2 = ax.plot(time, Rn, '-', label = 'Rn')
ax2 = ax.twinx()
lns3 = ax2.plot(time, temp, '-r', label = 'temp')

# added these three lines
lns = lns1+lns2+lns3
labs = [l.get_label() for l in lns]
ax.legend(lns, labs, loc=0)

ax.grid()
ax.set_xlabel("Time (h)")
ax.set_ylabel(r"Radiation ($MJ\,m^{-2}\,d^{-1}$)")
ax2.set_ylabel(r"Temperature ($^\circ$C)")
ax2.set_ylim(0, 35)
ax.set_ylim(-20,100)
plt.show()

Which will give you this:

I'm not sure if this functionality is new, but you can also use the get_legend_handles_labels() method rather than keeping track of lines and labels yourself:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rc
rc('mathtext', default='regular')

pi = np.pi

# fake data
time = np.linspace (0, 25, 50)
temp = 50 / np.sqrt (2 * pi * 3**2) \
        * np.exp (-((time - 13)**2 / (3**2))**2) + 15
Swdown = 400 / np.sqrt (2 * pi * 3**2) * np.exp (-((time - 13)**2 / (3**2))**2)
Rn = Swdown - 10

fig = plt.figure()
ax = fig.add_subplot(111)

ax.plot(time, Swdown, '-', label = 'Swdown')
ax.plot(time, Rn, '-', label = 'Rn')
ax2 = ax.twinx()
ax2.plot(time, temp, '-r', label = 'temp')

# ask matplotlib for the plotted objects and their labels
lines, labels = ax.get_legend_handles_labels()
lines2, labels2 = ax2.get_legend_handles_labels()
ax2.legend(lines + lines2, labels + labels2, loc=0)

ax.grid()
ax.set_xlabel("Time (h)")
ax.set_ylabel(r"Radiation ($MJ\,m^{-2}\,d^{-1}$)")
ax2.set_ylabel(r"Temperature ($^\circ$C)")
ax2.set_ylim(0, 35)
ax.set_ylim(-20,100)
plt.show()

From matplotlib version 2.1 onwards, you may use a figure legend. Instead of ax.legend(), which produces a legend with the handles from the axes ax, one can create a figure legend

fig.legend(loc="upper right")

which will gather all handles from all subplots in the figure. Since it is a figure legend, it will be placed at the corner of the figure, and the loc argument is relative to the figure.

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0,10)
y = np.linspace(0,10)
z = np.sin(x/3)**2*98

fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(x,y, '-', label = 'Quantity 1')

ax2 = ax.twinx()
ax2.plot(x,z, '-r', label = 'Quantity 2')
fig.legend(loc="upper right")

ax.set_xlabel("x [units]")
ax.set_ylabel(r"Quantity 1")
ax2.set_ylabel(r"Quantity 2")

plt.show()

In order to place the legend back into the axes, one would supply a bbox_to_anchor and a bbox_transform. The latter would be the axes transform of the axes the legend should reside in. The former may be the coordinates of the edge defined by loc given in axes coordinates.

fig.legend(loc="upper right", bbox_to_anchor=(1,1), bbox_transform=ax.transAxes)

You can easily get what you want by adding the line in ax:

ax.plot([], [], '-r', label = 'temp')

or

ax.plot(np.nan, '-r', label = 'temp')

This would plot nothing but add a label to legend of ax.

I think this is a much easier way. It's not necessary to track lines automatically when you have only a few lines in the second axes, as fixing by hand like above would be quite easy. Anyway, it depends on what you need.

The whole code is as below:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rc
rc('mathtext', default='regular')

time = np.arange(22.)
temp = 20*np.random.rand(22)
Swdown = 10*np.random.randn(22)+40
Rn = 40*np.random.rand(22)

fig = plt.figure()
ax = fig.add_subplot(111)
ax2 = ax.twinx()

#---------- look at below -----------

ax.plot(time, Swdown, '-', label = 'Swdown')
ax.plot(time, Rn, '-', label = 'Rn')

ax2.plot(time, temp, '-r')  # The true line in ax2
ax.plot(np.nan, '-r', label = 'temp')  # Make an agent in ax

ax.legend(loc=0)

#---------------done-----------------

ax.grid()
ax.set_xlabel("Time (h)")
ax.set_ylabel(r"Radiation ($MJ\,m^{-2}\,d^{-1}$)")
ax2.set_ylabel(r"Temperature ($^\circ$C)")
ax2.set_ylim(0, 35)
ax.set_ylim(-20,100)
plt.show()

The plot is as below:

Update: add a better version:

ax.plot(np.nan, '-r', label = 'temp')

This will do nothing while plot(0, 0) may change the axis range.

One extra example for scatter

ax.scatter([], [], s=100, label = 'temp')  # Make an agent in ax
ax2.scatter(time, temp, s=10)  # The true scatter in ax2

ax.legend(loc=1, framealpha=1)

Preparation

import numpy as np
from matplotlib import pyplot as plt

fig, ax1 = plt.subplots( figsize=(15,6) )

Y1, Y2 = np.random.random((2,100))

ax2 = ax1.twinx()

Content

I'm surprised it did not show up so far but the simplest way is to either collect them manually into one of the axes objs (that lie on top of each other)

l1 = ax1.plot( range(len(Y1)), Y1, label='Label 1' )
l2 = ax2.plot( range(len(Y2)), Y2, label='Label 2', color='orange' )

ax1.legend( handles=l1+l2 )

or have them collected automatically into the surrounding figure by fig.legend() and fiddle around with the the bbox_to_anchor parameter:

ax1.plot( range(len(Y1)), Y1, label='Label 1' )
ax2.plot( range(len(Y2)), Y2, label='Label 2', color='orange' )

fig.legend( bbox_to_anchor=(.97, .97) )

Finalization

fig.tight_layout()
fig.savefig('stackoverflow.png', bbox_inches='tight')

A quick hack that may suit your needs..

Take off the frame of the box and manually position the two legends next to each other. Something like this..

ax1.legend(loc = (.75,.1), frameon = False)
ax2.legend( loc = (.75, .05), frameon = False)

Where the loc tuple is left-to-right and bottom-to-top percentages that represent the location in the chart.

I found an following official matplotlib example that uses host_subplot to display multiple y-axes and all the different labels in one legend. No workaround necessary. Best solution I found so far. http://matplotlib.org/examples/axes_grid/demo_parasite_axes2.html

from mpl_toolkits.axes_grid1 import host_subplot
import mpl_toolkits.axisartist as AA
import matplotlib.pyplot as plt

host = host_subplot(111, axes_class=AA.Axes)
plt.subplots_adjust(right=0.75)

par1 = host.twinx()
par2 = host.twinx()

offset = 60
new_fixed_axis = par2.get_grid_helper().new_fixed_axis
par2.axis["right"] = new_fixed_axis(loc="right",
                                    axes=par2,
                                    offset=(offset, 0))

par2.axis["right"].toggle(all=True)

host.set_xlim(0, 2)
host.set_ylim(0, 2)

host.set_xlabel("Distance")
host.set_ylabel("Density")
par1.set_ylabel("Temperature")
par2.set_ylabel("Velocity")

p1, = host.plot([0, 1, 2], [0, 1, 2], label="Density")
p2, = par1.plot([0, 1, 2], [0, 3, 2], label="Temperature")
p3, = par2.plot([0, 1, 2], [50, 30, 15], label="Velocity")

par1.set_ylim(0, 4)
par2.set_ylim(1, 65)

host.legend()

plt.draw()
plt.show()

If you are using Seaborn you can do this:

g = sns.barplot('arguments blah blah')
g2 = sns.lineplot('arguments blah blah')
h1,l1 = g.get_legend_handles_labels()
h2,l2 = g2.get_legend_handles_labels()
#Merging two legends
g.legend(h1+h2, l1+l2, title_fontsize='10')
#removes the second legend
g2.get_legend().remove()

As provided in the example from matplotlib.org, a clean way to implement a single legend from multiple axes is with plot handles:

import matplotlib.pyplot as plt


fig, ax = plt.subplots()
fig.subplots_adjust(right=0.75)

twin1 = ax.twinx()
twin2 = ax.twinx()

# Offset the right spine of twin2.  The ticks and label have already been
# placed on the right by twinx above.
twin2.spines.right.set_position(("axes", 1.2))

p1, = ax.plot([0, 1, 2], [0, 1, 2], "b-", label="Density")
p2, = twin1.plot([0, 1, 2], [0, 3, 2], "r-", label="Temperature")
p3, = twin2.plot([0, 1, 2], [50, 30, 15], "g-", label="Velocity")

ax.set_xlim(0, 2)
ax.set_ylim(0, 2)
twin1.set_ylim(0, 4)
twin2.set_ylim(1, 65)

ax.set_xlabel("Distance")
ax.set_ylabel("Density")
twin1.set_ylabel("Temperature")
twin2.set_ylabel("Velocity")

ax.yaxis.label.set_color(p1.get_color())
twin1.yaxis.label.set_color(p2.get_color())
twin2.yaxis.label.set_color(p3.get_color())

tkw = dict(size=4, width=1.5)
ax.tick_params(axis='y', colors=p1.get_color(), **tkw)
twin1.tick_params(axis='y', colors=p2.get_color(), **tkw)
twin2.tick_params(axis='y', colors=p3.get_color(), **tkw)
ax.tick_params(axis='x', **tkw)

ax.legend(handles=[p1, p2, p3])

plt.show()

Here is another way to do this:

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rc
rc('mathtext', default='regular')

fig = plt.figure()
ax = fig.add_subplot(111)
pl_1, = ax.plot(time, Swdown, '-')
label_1 = 'Swdown'
pl_2, = ax.plot(time, Rn, '-')
label_2 = 'Rn'

ax2 = ax.twinx()
pl_3, = ax2.plot(time, temp, '-r')
label_3 = 'temp'

ax.legend([pl[enter image description here][1]_1, pl_2, pl_3], [label_1, label_2, label_3], loc=0)

ax.grid()
ax.set_xlabel("Time (h)")
ax.set_ylabel(r"Radiation ($MJ\,m^{-2}\,d^{-1}$)")
ax2.set_ylabel(r"Temperature ($^\circ$C)")
ax2.set_ylim(0, 35)
ax.set_ylim(-20,100)
plt.show()

enter image description here

The solutions proposed so far have one or two inconvenients:

• Handles needs to be collected individually when plotting, e.g. lns1 = ax.plot(time, Swdown, '-', label = 'Swdown'). There is a risk of forgetting handles when updating the code.

• Legend is drawn for the whole figure, not by subplot, which is likely a no-go if you have multiple subplots.

This new solution takes advantage of Axes.get_legend_handles_labels() to collect existing handles and labels for the main axis and for the twin axis.

Collecting handles and labels automatically

This numpy operation will scan all axes which share the same subplot area than ax, including ax and return merged handles and labels:

hl = np.hstack([axis.get_legend_handles_labels()
                for axis in ax.figure.axes
                if axis.bbox.bounds == ax.bbox.bounds])

It can be used to feed legend() arguments this way:

import numpy as np
import matplotlib.pyplot as plt

t = np.arange(1, 200)
signals = [np.exp(-t/20) * np.cos(t*k) for k in (1, 2)]

fig, axes = plt.subplots(nrows=2, figsize=(10, 3), layout='constrained')
axes = axes.flatten()

for i, (ax, signal) in enumerate(zip(axes, signals)):
    # Plot as usual, no change to the code
    ax.plot(t, signal, label=f'plotted on axes[{i}]', c='C0', lw=9, alpha=0.3)
    ax2 = ax.twinx()
    ax2.plot(t, signal, label=f'plotted on axes[{i}].twinx()', c='C1')

    # The only specificity of the code is when plotting the legend
    h, l = np.hstack([axis.get_legend_handles_labels()
                      for axis in ax.figure.axes
                      if axis.bbox.bounds == ax.bbox.bounds]).tolist()
    ax2.legend(handles=h, labels=l, loc='upper right')