我正在尝试制作一个包含两个子图的图表,每个子图都有一个寄生轴,如文档here所示。但是,虽然我可以使用单个图复制该示例,但它似乎不适用于2个子图。 Matplotlib是否能够做到这一点?
这是我的代码:
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import host_subplot
import mpl_toolkits.axisartist as AA
host = host_subplot(111, axes_class=AA.Axes)
plt.subplots_adjust(right=0.75)
plt.subplot(2,1,1)
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))
par1.axis["right"].toggle(all=True)
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()
host.axis["left"].label.set_color(p1.get_color())
par1.axis["right"].label.set_color(p2.get_color())
par2.axis["right"].label.set_color(p3.get_color())
#####2#####
plt.subplot(2,1,2)
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))
par1.axis["right"].toggle(all=True)
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()
host.axis["left"].label.set_color(p1.get_color())
par1.axis["right"].label.set_color(p2.get_color())
par2.axis["right"].label.set_color(p3.get_color())
plt.draw()
plt.show()
当我跑步时,我最终得到一组空白的子图:
对不起,如果我正在做一些蠢事!
非常感谢, 亚历克斯
答案 0 :(得分:1)
那里有一些小错误。首先覆盖plt.subplot()
命令的host_subplot()
命令(请参阅note in the matplotlib.pyplot.subplot() documentation:"创建子图将删除与其重叠的任何预先存在的子图,除了共享边界& #34)。此外,您必须分别跟踪两个图的实例。我解决了这个问题,因为我为第一个host1
和par11
,par12
和{{Axes
创建了host2
,par21
和par22
1}}用于第二个Axes
。整个代码现在看起来像这样:
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import host_subplot
import mpl_toolkits.axisartist as AA
fig = plt.figure()
host1 = host_subplot(211, axes_class=AA.Axes)
plt.subplots_adjust(right=0.75)
par11 = host1.twinx()
par12 = host1.twinx()
offset = 60
new_fixed_axis = par12.get_grid_helper().new_fixed_axis
par12.axis["right"] = new_fixed_axis(loc="right",
axes=par12,
offset=(offset, 0))
par11.axis["right"].toggle(all=True)
par12.axis["right"].toggle(all=True)
host1.set_xlim(0, 2)
host1.set_ylim(0, 2)
host1.set_xlabel("Distance")
host1.set_ylabel("Density")
par11.set_ylabel("Temperature")
par12.set_ylabel("Velocity")
p1, = host1.plot([0, 1, 2], [0, 1, 2], label="Density")
p2, = par11.plot([0, 1, 2], [0, 3, 2], label="Temperature")
p3, = par12.plot([0, 1, 2], [50, 30, 15], label="Velocity")
par11.set_ylim(0, 4)
par12.set_ylim(1, 65)
host1.legend()
host1.axis["left"].label.set_color(p1.get_color())
par11.axis["right"].label.set_color(p2.get_color())
par12.axis["right"].label.set_color(p3.get_color())
#####2#####
host2 = host_subplot(212, axes_class=AA.Axes)
plt.subplots_adjust(right=0.75)
par21 = host2.twinx()
par22 = host2.twinx()
offset = 60
new_fixed_axis = par22.get_grid_helper().new_fixed_axis
par22.axis["right"] = new_fixed_axis(loc="right",
axes=par22,
offset=(offset, 0))
par21.axis["right"].toggle(all=True)
par22.axis["right"].toggle(all=True)
host2.set_xlim(0, 2)
host2.set_ylim(0, 2)
host2.set_xlabel("Distance")
host2.set_ylabel("Density")
par21.set_ylabel("Temperature")
par22.set_ylabel("Velocity")
p1, = host2.plot([0, 1, 2], [0, 1, 2], label="Density")
p2, = par21.plot([0, 1, 2], [0, 3, 2], label="Temperature")
p3, = par22.plot([0, 1, 2], [50, 30, 15], label="Velocity")
par21.set_ylim(0, 4)
par22.set_ylim(1, 65)
host2.legend()
host2.axis["left"].label.set_color(p1.get_color())
par21.axis["right"].label.set_color(p2.get_color())
par22.axis["right"].label.set_color(p3.get_color())
fig.tight_layout()
plt.draw()
plt.show()
结果如下:
希望这有帮助。