我还没有找到一个解决方案来调整matplotlib的broken axis example的底部和顶部图的高度.

顺便说一句：两个地块之间的空间可以通过以下方式调整：

plt.subplots_adjust(hspace=0.03)

更新：

我几乎用gridspec解决了这个问题：

"""
Broken axis example, where the y-axis will have a portion cut out.
"""
import matplotlib.pylab as plt
# NEW:
import matplotlib.gridspec as gridspec
import numpy as np

pts = np.array([ 0.015,  0.166,  0.133,  0.159,  0.041,  0.024,  0.195,
    0.039, 0.161,  0.018,  0.143,  0.056,  0.125,  0.096,  0.094, 0.051,
    0.043,  0.021,  0.138,  0.075,  0.109,  0.195,  0.05 , 0.074, 0.079,
    0.155,  0.02 ,  0.01 ,  0.061,  0.008])
pts[[3,14]] += .8

# NEW:
gs = gridspec.GridSpec(2, 1, height_ratios=[1, 3])
ax = plt.subplot(gs[0])
ax2 = plt.subplot(gs[1])
plt.subplots_adjust(hspace=0.03)

ax.plot(pts)
ax2.plot(pts)
ax.set_ylim(.78,1.)
ax2.set_ylim(.0,.22)
ax.spines['bottom'].set_visible(False)
ax2.spines['top'].set_visible(False)
ax.xaxis.tick_top()
ax.tick_params(labeltop='off')
ax2.xaxis.tick_bottom()

d = .03
kwargs = dict(transform=ax.transAxes, color='k', clip_on=False)
ax.plot((0-d,0+d), (0-d,0+d), **kwargs)   # top-left diagonal
ax.plot((1-d,1+d), (0-d,0+d), **kwargs)   # top-right diagonal
kwargs.update(transform=ax2.transAxes)  # switch to the bottom axes
ax2.plot((0-d,0+d),(1-d,1+d), **kwargs) # bottom-left diagonal
ax2.plot((1-d,1+d),(1-d,1+d), **kwargs) # bottom-right diagonal

plt.show()

剩下的问题是：

>两个平行线段(断轴标记)
由于y轴的长度不同,因此不再平行.
>另一个问题是如何方便地定位ylabel.

最后我在gridspec中看不到sharex = True的选项.这有关系吗？

更新：

添加ylim和ylim2参数确定高度比率,使数据单位相等：

ylim  = [0.8, 1.0]
ylim2 = [0.0, 0.3]
ylimratio = (ylim[1]-ylim[0])/(ylim2[1]-ylim2[0]+ylim[1]-ylim[0])
ylim2ratio = (ylim2[1]-ylim2[0])/(ylim2[1]-ylim2[0]+ylim[1]-ylim[0])
gs = gridspec.GridSpec(2, 1, height_ratios=[ylimratio, ylim2ratio])
ax = plt.subplot(gs[0])
ax2 = plt.subplot(gs[1])
ax.set_ylim(ylim)
ax2.set_ylim(ylim2)

解决方法:

更新2018年

有一个github项目https://github.com/bendichter/brokenaxes可能更方便使用.

我自己的解决方案看起来像(使用gridspec,假设两个y轴的单位应相等)：

 """
 Broken axis example, where the y-axis will have a portion cut out.
 """
 import matplotlib.pylab as plt
 import matplotlib.gridspec as gridspec
 import numpy as np

 pts = np.array([ 0.015,  0.166,  0.133,  0.159,  0.041,  0.024,  0.195,
     0.039, 0.161,  0.018,  0.143,  0.056,  0.125,  0.096,  0.094, 0.051,
     0.043,  0.021,  0.138,  0.075,  0.109,  0.195,  0.05 , 0.074, 0.079,
     0.155,  0.02 ,  0.01 ,  0.061,  0.008])
 pts[[3,14]] += .8

 ylim  = [0.82, 1.0]
 ylim2 = [0.0, 0.32]
 ylimratio = (ylim[1]-ylim[0])/(ylim2[1]-ylim2[0]+ylim[1]-ylim[0])
 ylim2ratio = (ylim2[1]-ylim2[0])/(ylim2[1]-ylim2[0]+ylim[1]-ylim[0])
 gs = gridspec.GridSpec(2, 1, height_ratios=[ylimratio, ylim2ratio])
 fig = plt.figure()
 ax = fig.add_subplot(gs[0])
 ax2 = fig.add_subplot(gs[1])
 ax.plot(pts)
 ax2.plot(pts)
 ax.set_ylim(ylim)
 ax2.set_ylim(ylim2)
 plt.subplots_adjust(hspace=0.03)

 ax.spines['bottom'].set_visible(False)
 ax2.spines['top'].set_visible(False)
 ax.xaxis.tick_top()
 ax.tick_params(labeltop='off')
 ax2.xaxis.tick_bottom()

 ax2.set_xlabel('xlabel')
 ax2.set_ylabel('ylabel')
 ax2.yaxis.set_label_coords(0.05, 0.5, transform=fig.transFigure)

 kwargs = dict(color='k', clip_on=False)
 xlim = ax.get_xlim()
 dx = .02*(xlim[1]-xlim[0])
 dy = .01*(ylim[1]-ylim[0])/ylimratio
 ax.plot((xlim[0]-dx,xlim[0]+dx), (ylim[0]-dy,ylim[0]+dy), **kwargs)
 ax.plot((xlim[1]-dx,xlim[1]+dx), (ylim[0]-dy,ylim[0]+dy), **kwargs)
 dy = .01*(ylim2[1]-ylim2[0])/ylim2ratio
 ax2.plot((xlim[0]-dx,xlim[0]+dx), (ylim2[1]-dy,ylim2[1]+dy), **kwargs)
 ax2.plot((xlim[1]-dx,xlim[1]+dx), (ylim2[1]-dy,ylim2[1]+dy), **kwargs)
 ax.set_xlim(xlim)
 ax2.set_xlim(xlim)

 plt.savefig('broken_axis-mod.png')