| Revisão | de06c9b275e739903408086766aa49ed03a22294 (tree) |
|---|---|
| Hora | 2016-04-14 22:01:29 |
| Autor | Lorenzo Isella <lorenzo.isella@gmai...> |
| Commiter | Lorenzo Isella |
Another code to deal with the plotting of a complex hull.
| @@ -0,0 +1,92 @@ | ||
| 1 | +#! /usr/bin/env python | |
| 2 | + | |
| 3 | + | |
| 4 | +import numpy as np | |
| 5 | +import pylab as pl | |
| 6 | +import scipy as sp | |
| 7 | +from scipy.spatial import ConvexHull | |
| 8 | +from scipy.spatial.distance import euclidean | |
| 9 | +import matplotlib.pyplot as plt | |
| 10 | +import mpl_toolkits.mplot3d as a3 | |
| 11 | + | |
| 12 | + | |
| 13 | +cluster_agglomerate=np.array([[ 0.14513811, -0.18930948, -1.44428171], | |
| 14 | + [ 0.88042945, 1.67057596, -1.45742688], | |
| 15 | + [-1.66682741, -0.99554261, -1.70267889], | |
| 16 | + [-0.95535694, 2.3159907 , -1.93637881], | |
| 17 | + [ 1.09396798, 1.7987614 , -3.44524095], | |
| 18 | + [-2.63620654, 0.16588691, -3.02436539], | |
| 19 | + [ 0.19027056, 2.70740725, 0.11479029], | |
| 20 | + [ 2.77638842, 1.70535678, -2.10208878], | |
| 21 | + [-0.09149779, -0.81908733, 2.07425244], | |
| 22 | + [-0.48408772, 0.96793567, 1.26652603], | |
| 23 | + [ 0.67499278, -2.5386008 , 1.39914827], | |
| 24 | + [ 1.02571108, -1.60932884, -0.34500693], | |
| 25 | + [ 2.78789155, -1.42050584, 0.59682802], | |
| 26 | + [-0.14688239, -2.36883246, 3.35177362], | |
| 27 | + [-1.71507089, 0.19184887, 2.68408562], | |
| 28 | + [-1.87886026, -1.58255618, 3.97006406], | |
| 29 | + [ 6.61540229, 1.98324725, 0.82767368], | |
| 30 | + [ 7.46818823, 3.00950487, -0.66214223], | |
| 31 | + [ 4.80777628, 1.97159273, 1.68344958], | |
| 32 | + [ 6.3548727 , 2.26459561, 2.92819854], | |
| 33 | + [ 4.70026626, 0.44618044, 0.3866837 ], | |
| 34 | + [ 3.44366671, 1.87939977, -0.2203051 ], | |
| 35 | + [ 2.92460648, 1.98510457, 2.37510769], | |
| 36 | + [ 5.07053866, -0.10349542, -1.51041234], | |
| 37 | + [ 7.21643437, -1.32050186, -0.70707322], | |
| 38 | + [ 6.93292243, 0.58458074, -1.2458508 ], | |
| 39 | + [ 7.84238244, -2.97562362, -1.63914669], | |
| 40 | + [ 7.43212373, 0.10620418, 0.68315389], | |
| 41 | + [ 9.59692827, -2.0843759 , -1.26623658], | |
| 42 | + [ 8.34540867, -1.14927294, 1.95073173], | |
| 43 | + [ 6.57425162, -2.13797392, -2.94804639], | |
| 44 | + [ 6.93340304, -4.4591665 , -0.63578546]]) | |
| 45 | + | |
| 46 | + | |
| 47 | + | |
| 48 | +# see http://bit.ly/1qJlWkP | |
| 49 | + | |
| 50 | + | |
| 51 | + | |
| 52 | +# Generate random points & convex hull | |
| 53 | +points = cluster_agglomerate # np.random.rand(20,3) | |
| 54 | +print "points are, ", points | |
| 55 | +hull = ConvexHull(points) | |
| 56 | +print "I calculated the convex hull" | |
| 57 | + | |
| 58 | +# either this, or the alternative after the comments | |
| 59 | + | |
| 60 | +# ax = a3.Axes3D(pl.figure()) | |
| 61 | +# facetCol = [0, 1, 0.0] | |
| 62 | + | |
| 63 | +# ax.plot_trisurf(points[:,0], points[:,1], points[:,2], | |
| 64 | +# triangles=hull.simplices) | |
| 65 | + | |
| 66 | + | |
| 67 | +# ax.scatter(points[:,0], points[:,1], points[:,2], s=6000) | |
| 68 | + | |
| 69 | +# plt.axis('off') | |
| 70 | +# plt.show() | |
| 71 | + | |
| 72 | + | |
| 73 | + | |
| 74 | + | |
| 75 | +ax = a3.Axes3D(pl.figure()) | |
| 76 | +facetCol = sp.rand(3) #[0.0, 1.0, 0.0] | |
| 77 | + | |
| 78 | + | |
| 79 | +for simplex in hull.simplices: | |
| 80 | + vtx = [points[simplex[0],:], points[simplex[1],:], points[simplex[2],:]] | |
| 81 | + tri = a3.art3d.Poly3DCollection([vtx], linewidths = 2, alpha = 0.5) | |
| 82 | + tri.set_color(facetCol) | |
| 83 | + tri.set_edgecolor('k') | |
| 84 | + ax.add_collection3d(tri) | |
| 85 | + | |
| 86 | +ax.scatter(points[:,0], points[:,1], points[:,2], s=6000) | |
| 87 | + | |
| 88 | + | |
| 89 | +plt.axis('off') | |
| 90 | +plt.show() | |
| 91 | + | |
| 92 | +print "So far so good" |
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Python-codes/convex-hull-test.py