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# Untitled

a guest Mar 19th, 2020 108 Never
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1. import numpy as np
2. from mpl_toolkits.mplot3d import Axes3D
3. import matplotlib.pyplot as plt
4. import numpy as np
5.
6.
7. ### NOTE: make one of these an exact density or KDE to exactly match your plot intention.
8. randns1 = np.random.normal(size=10000)
9. counts1, bins1 =  np.histogram(randns1, bins=30)
10.
11. randns2 = np.random.normal(size=10000)
12. counts2, bins2 =  np.histogram(randns2, bins=30)
13.
14.
15. data = np.array([counts1,counts2])
16.
17. ## other data
18. fig = plt.figure()
19. ax = fig.add_subplot(111, projection='3d')
20. colors = ["r","g","b"]*10
21.
22. ## Draw 3D hist
23. ncnt, nbins = data.shape[:2]
24. xs_new = np.arange(-3,3,6/30)
25. for i in range(ncnt):
26.     ys = data[i]
27.     cs = [colors[i]] * nbins
28.     ax.bar(xs_new, ys.ravel(), zs=i, zdir='x', color=cs, alpha=0.8)
29.     ax.set_axis_off()
30.
31.
32. x = np.linspace(0, 1, 1000)
33. y = randns1[::10]
34. ax.plot(x, y, zs=0, zdir='z', label='curve in (x,y)')
35.
36.
37. # ax.set_xlabel('idx')
38. # ax.set_ylabel('bins')
39. # ax.set_zlabel('nums')
40. plt.show()
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