Contourf演示

如何使用 axes.Axes.contourf() 方法创建填充的等高线图。

  1. import numpy as np
  2. import matplotlib.pyplot as plt
  4. origin = 'lower'
  6. delta = 0.025
  8. x = y = np.arange(-3.0, 3.01, delta)
  9. X, Y = np.meshgrid(x, y)
  10. Z1 = np.exp(-X**2 - Y**2)
  11. Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
  12. Z = (Z1 - Z2) * 2
  14. nr, nc = Z.shape
  16. # put NaNs in one corner:
  17. Z[-nr // 6:, -nc // 6:] = np.nan
  18. # contourf will convert these to masked
  21. Z = np.ma.array(Z)
  22. # mask another corner:
  23. Z[:nr // 6, :nc // 6] = np.ma.masked
  25. # mask a circle in the middle:
  26. interior = np.sqrt((X**2) + (Y**2)) < 0.5
  27. Z[interior] = np.ma.masked
  29. # We are using automatic selection of contour levels;
  30. # this is usually not such a good idea, because they don't
  31. # occur on nice boundaries, but we do it here for purposes
  32. # of illustration.
  34. fig1, ax2 = plt.subplots(constrained_layout=True)
  35. CS = ax2.contourf(X, Y, Z, 10, cmap=plt.cm.bone, origin=origin)
  37. # Note that in the following, we explicitly pass in a subset of
  38. # the contour levels used for the filled contours.  Alternatively,
  39. # We could pass in additional levels to provide extra resolution,
  40. # or leave out the levels kwarg to use all of the original levels.
  42. CS2 = ax2.contour(CS, levels=CS.levels[::2], colors='r', origin=origin)
  44. ax2.set_title('Nonsense (3 masked regions)')
  45. ax2.set_xlabel('word length anomaly')
  46. ax2.set_ylabel('sentence length anomaly')
  48. # Make a colorbar for the ContourSet returned by the contourf call.
  49. cbar = fig1.colorbar(CS)
  50. cbar.ax.set_ylabel('verbosity coefficient')
  51. # Add the contour line levels to the colorbar
  52. cbar.add_lines(CS2)
  54. fig2, ax2 = plt.subplots(constrained_layout=True)
  55. # Now make a contour plot with the levels specified,
  56. # and with the colormap generated automatically from a list
  57. # of colors.
  58. levels = [-1.5, -1, -0.5, 0, 0.5, 1]
  59. CS3 = ax2.contourf(X, Y, Z, levels,
  60.                    colors=('r', 'g', 'b'),
  61.                    origin=origin,
  62.                    extend='both')
  63. # Our data range extends outside the range of levels; make
  64. # data below the lowest contour level yellow, and above the
  65. # highest level cyan:
  66. CS3.cmap.set_under('yellow')
  67. CS3.cmap.set_over('cyan')
  69. CS4 = ax2.contour(X, Y, Z, levels,
  70.                   colors=('k',),
  71.                   linewidths=(3,),
  72.                   origin=origin)
  73. ax2.set_title('Listed colors (3 masked regions)')
  74. ax2.clabel(CS4, fmt='%2.1f', colors='w', fontsize=14)
  76. # Notice that the colorbar command gets all the information it
  77. # needs from the ContourSet object, CS3.
  78. fig2.colorbar(CS3)
  80. # Illustrate all 4 possible "extend" settings:
  81. extends = ["neither", "both", "min", "max"]
  82. cmap = plt.cm.get_cmap("winter")
  83. cmap.set_under("magenta")
  84. cmap.set_over("yellow")
  85. # Note: contouring simply excludes masked or nan regions, so
  86. # instead of using the "bad" colormap value for them, it draws
  87. # nothing at all in them.  Therefore the following would have
  88. # no effect:
  89. # cmap.set_bad("red")
  91. fig, axs = plt.subplots(2, 2, constrained_layout=True)
  93. for ax, extend in zip(axs.ravel(), extends):
  94.     cs = ax.contourf(X, Y, Z, levels, cmap=cmap, extend=extend, origin=origin)
  95.     fig.colorbar(cs, ax=ax, shrink=0.9)
  96.     ax.set_title("extend = %s" % extend)
  97.     ax.locator_params(nbins=4)
  99. plt.show()

Contourf演示

Contourf演示2

Contourf演示3

参考

此示例中显示了以下函数，方法和类的使用：

  1. import matplotlib
  2. matplotlib.axes.Axes.contour
  3. matplotlib.pyplot.contour
  4. matplotlib.axes.Axes.contourf
  5. matplotlib.pyplot.contourf
  6. matplotlib.axes.Axes.clabel
  7. matplotlib.pyplot.clabel
  8. matplotlib.figure.Figure.colorbar
  9. matplotlib.pyplot.colorbar
  10. matplotlib.colors.Colormap
  11. matplotlib.colors.Colormap.set_bad
  12. matplotlib.colors.Colormap.set_under
  13. matplotlib.colors.Colormap.set_over

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