您可以直接将matplotlib示例改编为x轴上的中断点：
"""
Broken axis example, where the x-axis will have a portion cut out.
"""
import matplotlib.pylab as plt
import numpy as np
x = np.linspace(0,10,100)
x[75:] = np.linspace(40,42.5,25)
y = np.sin(x)
f,(ax,ax2) = plt.subplots(1,2,sharey=True, facecolor='w')
# plot the same data on both axes
ax.plot(x, y)
ax2.plot(x, y)
ax.set_xlim(0,7.5)
ax2.set_xlim(40,42.5)
# hide the spines between ax and ax2
ax.spines['right'].set_visible(False)
ax2.spines['left'].set_visible(False)
ax.yaxis.tick_left()
ax.tick_params(labelright='off')
ax2.yaxis.tick_right()
# This looks pretty good, and was fairly painless, but you can get that
# cut-out diagonal lines look with just a bit more work. The important
# thing to kNow here is that in axes coordinates, which are always
# between 0-1, spine endpoints are at these locations (0,0), (0,1),
# (1,0), and (1,1). Thus, we just need to put the diagonals in the
# appropriate corners of each of our axes, and so long as we use the
# right transform and disable clipping.
d = .015 # how big to make the diagonal lines in axes coordinates
# arguments to pass plot, just so we don't keep repeating them
kwargs = dict(transform=ax.transAxes, color='k', clip_on=False)
ax.plot((1-d,1+d), (-d,+d), **kwargs)
ax.plot((1-d,1+d),(1-d,1+d), **kwargs)
kwargs.update(transform=ax2.transAxes) # switch to the bottom axes
ax2.plot((-d,+d), (1-d,1+d), **kwargs)
ax2.plot((-d,+d), (-d,+d), **kwargs)
# What's cool about this is that Now if we vary the distance between
# ax and ax2 via f.subplots_adjust(hspace=...) or plt.subplot_tool(),
# the diagonal lines will move accordingly, and stay right at the tips
# of the spines they are 'breaking'
plt.show()
出于您的目的，只需两次绘制数据（在每个轴上绘制一次，ax然后适当地ax2设置xlims即可。“中断线”应移动以匹配新的中断，因为它们是在相对轴坐标而非数据坐标中绘制的。
折线只是在一对点之间绘制的未剪裁的绘图线。例如，在第一个轴上的ax.plot((1-d,1+d), (-d,+d), **kwargs)点(1-d,-d)与点之间绘制折线(1+d,+d)：这是右下角的折线。如果您想更改原图，请适当更改这些值。例如，要使这个陡峭，请尝试ax.plot((1-d/2,1+d/2), (-d,+d), **kwargs)
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