描述我要实现的目标的最佳方法是使用自己的图像
现在我在光谱图中有很多死角，尤其是在5200和6300之间。我的问题很简单，我如何添加一个类似//的漂亮的//断点（从网上举起的图像）
我将这种设置用于绘图：
nullfmt = pyplot.NullFormatter() fig = pyplot.figure(figsize=(16,6)) gridspec_layout1= gridspec.GridSpec(2,1) gridspec_layout1.update(left=0.05, right=0.97, hspace=0, wspace=0.018) pyplot_top = fig.add_subplot(gridspec_layout1[0]) pyplot_bottom = fig.add_subplot(gridspec_layout1[1]) pyplot_top.xaxis.set_major_formatter(nullfmt)
我敢肯定，使用gridpsec是可以实现的，但是非常感谢您详细介绍了如何实现此目标的高级教程。
如果以前已经在stackoverflow上解决了这个问题，我也深表歉意，但是我一直在广泛地寻找正确的过程，gridSpec但至今仍未找到任何答案。
gridSpec
但是，我的折断线没有我想要的陡峭…如何更改它们？（我利用了下面的示例答案）
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。
ax
ax2
xlim
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)
ax.plot((1-d,1+d), (-d,+d), **kwargs)
(1-d,-d)
(1+d,+d)
ax.plot((1-d/2,1+d/2), (-d,+d), **kwargs)
