二级轴与twinx():如何添加到图例?

小开

最佳答案

您可以通过添加以下行轻松添加第二个图例:

ax2.legend(loc=0)

你会得到这个:

enter image description here

但是如果你想要所有的标签都在一个图例上，那么你应该这样做:

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()

它会给你这个:

enter image description here

小开

我不确定这个功能是否是新的，但你也可以使用get_legend_handles_labels()方法，而不是自己跟踪行和标签:

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()

小开

你可以很容易地得到你想要的，在ax中添加一行:

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

或

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

这将没有任何情节，但添加一个标签的传说斧头。

我认为这是一个更简单的方法。当你在第二个轴上只有几条线时，没有必要自动跟踪线，因为像上面那样手动固定是非常容易的。不管怎样，这取决于你需要什么

整个代码如下:

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()

图如下:

enter image description here

更新:添加一个更好的版本:

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

这将什么都不做，而plot(0, 0)可能会改变轴范围。

另一个关于散点的例子

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)

小开

我发现了以下官方matplotlib示例，该示例使用host_subplot在一个图例中显示多个y轴和所有不同的标签。没有必要变通。目前为止我找到的最好的解决办法。 http://matplotlib.org/examples/axes_grid/demo_parasite_axes2.html < / p >

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()

小开

一个快速的hack，可能适合你的需要..

取下盒子的框架，手动将两个图例放在彼此旁边。就像这样…

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

其中loc元组是从左到右和从下到上的百分比，表示图表中的位置。

小开

从matplotlib版本2.1开始，你可以使用图的传说。我们可以创建一个图形图例，而不是ax.legend()，它会用来自轴ax的句柄生成一个图例

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()

为了将图例放回坐标轴，需要提供bbox_to_anchor和bbox_transform。后者将是图例应驻留的轴的轴变换。前者可能是由loc定义的边的坐标轴坐标。

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

小开

正如matplotlib.org中的例子所提供的，从多个轴实现单个图例的干净方法是使用plot句柄:

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()

小开

准备

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()

内容

我很惊讶它没有显示到目前为止，但最简单的方法是手动收集它们到一个轴objs(躺在彼此的顶部)

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 )

或者通过fig.legend()将它们自动收集到周围的图形中，并摆弄bbox_to_anchor参数:

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) )

终结

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

小开

这里有另一种方法:

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

小开

如果您正在使用Seaborn，您可以这样做:

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()