图像掩码

显示与掩码数组输入和范围以外的颜色。

第二个子图说明了如何使用边界规范来获得填充轮廓效果。

  1. from copy import copy
  3. import numpy as np
  4. import matplotlib.pyplot as plt
  5. import matplotlib.colors as colors
  7. # compute some interesting data
  8. x0, x1 = -5, 5
  9. y0, y1 = -3, 3
  10. x = np.linspace(x0, x1, 500)
  11. y = np.linspace(y0, y1, 500)
  12. X, Y = np.meshgrid(x, y)
  13. Z1 = np.exp(-X**2 - Y**2)
  14. Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
  15. Z = (Z1 - Z2) * 2
  17. # Set up a colormap:
  18. # use copy so that we do not mutate the global colormap instance
  19. palette = copy(plt.cm.gray)
  20. palette.set_over('r', 1.0)
  21. palette.set_under('g', 1.0)
  22. palette.set_bad('b', 1.0)
  23. # Alternatively, we could use
  24. # palette.set_bad(alpha = 0.0)
  25. # to make the bad region transparent.  This is the default.
  26. # If you comment out all the palette.set* lines, you will see
  27. # all the defaults; under and over will be colored with the
  28. # first and last colors in the palette, respectively.
  29. Zm = np.ma.masked_where(Z > 1.2, Z)
  31. # By setting vmin and vmax in the norm, we establish the
  32. # range to which the regular palette color scale is applied.
  33. # Anything above that range is colored based on palette.set_over, etc.
  35. # set up the Axes objets
  36. fig, (ax1, ax2) = plt.subplots(nrows=2, figsize=(6, 5.4))
  38. # plot using 'continuous' color map
  39. im = ax1.imshow(Zm, interpolation='bilinear',
  40.                 cmap=palette,
  41.                 norm=colors.Normalize(vmin=-1.0, vmax=1.0),
  42.                 aspect='auto',
  43.                 origin='lower',
  44.                 extent=[x0, x1, y0, y1])
  45. ax1.set_title('Green=low, Red=high, Blue=masked')
  46. cbar = fig.colorbar(im, extend='both', shrink=0.9, ax=ax1)
  47. cbar.set_label('uniform')
  48. for ticklabel in ax1.xaxis.get_ticklabels():
  49.     ticklabel.set_visible(False)
  51. # Plot using a small number of colors, with unevenly spaced boundaries.
  52. im = ax2.imshow(Zm, interpolation='nearest',
  53.                 cmap=palette,
  54.                 norm=colors.BoundaryNorm([-1, -0.5, -0.2, 0, 0.2, 0.5, 1],
  55.                                          ncolors=palette.N),
  56.                 aspect='auto',
  57.                 origin='lower',
  58.                 extent=[x0, x1, y0, y1])
  59. ax2.set_title('With BoundaryNorm')
  60. cbar = fig.colorbar(im, extend='both', spacing='proportional',
  61.                     shrink=0.9, ax=ax2)
  62. cbar.set_label('proportional')
  64. fig.suptitle('imshow, with out-of-range and masked data')
  65. plt.show()

图像掩码示例

参考

下面的示例演示了以下函数和方法的使用：

  1. import matplotlib
  2. matplotlib.axes.Axes.imshow
  3. matplotlib.pyplot.imshow
  4. matplotlib.figure.Figure.colorbar
  5. matplotlib.pyplot.colorbar
  6. matplotlib.colors.BoundaryNorm
  7. matplotlib.colorbar.ColorbarBase.set_label

下载这个示例