散点图

散点图示例

  1. import numpy as np
  2. import matplotlib.pyplot as plt
  3. from mpl_toolkits.axes_grid1 import make_axes_locatable
  5. # Fixing random state for reproducibility
  6. np.random.seed(19680801)
  9. # the random data
  10. x = np.random.randn(1000)
  11. y = np.random.randn(1000)
  14. fig, axScatter = plt.subplots(figsize=(5.5, 5.5))
  16. # the scatter plot:
  17. axScatter.scatter(x, y)
  18. axScatter.set_aspect(1.)
  20. # create new axes on the right and on the top of the current axes
  21. # The first argument of the new_vertical(new_horizontal) method is
  22. # the height (width) of the axes to be created in inches.
  23. divider = make_axes_locatable(axScatter)
  24. axHistx = divider.append_axes("top", 1.2, pad=0.1, sharex=axScatter)
  25. axHisty = divider.append_axes("right", 1.2, pad=0.1, sharey=axScatter)
  27. # make some labels invisible
  28. axHistx.xaxis.set_tick_params(labelbottom=False)
  29. axHisty.yaxis.set_tick_params(labelleft=False)
  31. # now determine nice limits by hand:
  32. binwidth = 0.25
  33. xymax = max(np.max(np.abs(x)), np.max(np.abs(y)))
  34. lim = (int(xymax/binwidth) + 1)*binwidth
  36. bins = np.arange(-lim, lim + binwidth, binwidth)
  37. axHistx.hist(x, bins=bins)
  38. axHisty.hist(y, bins=bins, orientation='horizontal')
  40. # the xaxis of axHistx and yaxis of axHisty are shared with axScatter,
  41. # thus there is no need to manually adjust the xlim and ylim of these
  42. # axis.
  44. axHistx.set_yticks([0, 50, 100])
  46. axHisty.set_xticks([0, 50, 100])
  48. plt.show()

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