断轴

折断轴的示例，其中y轴将切割出一部分。

折断轴示例

  1. import matplotlib.pyplot as plt
  2. import numpy as np
  5. # 30 points between [0, 0.2) originally made using np.random.rand(30)*.2
  6. pts = np.array([
  7.     0.015, 0.166, 0.133, 0.159, 0.041, 0.024, 0.195, 0.039, 0.161, 0.018,
  8.     0.143, 0.056, 0.125, 0.096, 0.094, 0.051, 0.043, 0.021, 0.138, 0.075,
  9.     0.109, 0.195, 0.050, 0.074, 0.079, 0.155, 0.020, 0.010, 0.061, 0.008])
  11. # Now let's make two outlier points which are far away from everything.
  12. pts[[3, 14]] += .8
  14. # If we were to simply plot pts, we'd lose most of the interesting
  15. # details due to the outliers. So let's 'break' or 'cut-out' the y-axis
  16. # into two portions - use the top (ax) for the outliers, and the bottom
  17. # (ax2) for the details of the majority of our data
  18. f, (ax, ax2) = plt.subplots(2, 1, sharex=True)
  20. # plot the same data on both axes
  21. ax.plot(pts)
  22. ax2.plot(pts)
  24. # zoom-in / limit the view to different portions of the data
  25. ax.set_ylim(.78, 1.)  # outliers only
  26. ax2.set_ylim(0, .22)  # most of the data
  28. # hide the spines between ax and ax2
  29. ax.spines['bottom'].set_visible(False)
  30. ax2.spines['top'].set_visible(False)
  31. ax.xaxis.tick_top()
  32. ax.tick_params(labeltop=False)  # don't put tick labels at the top
  33. ax2.xaxis.tick_bottom()
  35. # This looks pretty good, and was fairly painless, but you can get that
  36. # cut-out diagonal lines look with just a bit more work. The important
  37. # thing to know here is that in axes coordinates, which are always
  38. # between 0-1, spine endpoints are at these locations (0,0), (0,1),
  39. # (1,0), and (1,1).  Thus, we just need to put the diagonals in the
  40. # appropriate corners of each of our axes, and so long as we use the
  41. # right transform and disable clipping.
  43. d = .015  # how big to make the diagonal lines in axes coordinates
  44. # arguments to pass to plot, just so we don't keep repeating them
  45. kwargs = dict(transform=ax.transAxes, color='k', clip_on=False)
  46. ax.plot((-d, +d), (-d, +d), **kwargs)        # top-left diagonal
  47. ax.plot((1 - d, 1 + d), (-d, +d), **kwargs)  # top-right diagonal
  49. kwargs.update(transform=ax2.transAxes)  # switch to the bottom axes
  50. ax2.plot((-d, +d), (1 - d, 1 + d), **kwargs)  # bottom-left diagonal
  51. ax2.plot((1 - d, 1 + d), (1 - d, 1 + d), **kwargs)  # bottom-right diagonal
  53. # What's cool about this is that now if we vary the distance between
  54. # ax and ax2 via f.subplots_adjust(hspace=...) or plt.subplot_tool(),
  55. # the diagonal lines will move accordingly, and stay right at the tips
  56. # of the spines they are 'breaking'
  58. plt.show()

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