CODEWITHSUNDEEP
pythonmatplotlibtriangulationmplot3d
deltasata
deltasata

Reputation: 411

How to plot 3d triangles in matplotlib with triangles vertices's coordinates (9 numbers for each triangle)?

I have many triangles (say N=10^6) with (x,y,z) coordinates of each vertex of the triangles stored in a file. So each triangle has 9 numbers stored as a row in the file. Hence the file has N rows. Now I just want to plot (in 3d) all the triangles filled with some colour. The triangles may or may not be adjacent. I am very very confused surfing through matplotlib documentation. Kindly help. Don't scold me please.

Upvotes: 0

Views: 8017

Answers (1)

ImportanceOfBeingErnest
ImportanceOfBeingErnest

Reputation: 339160

Plotting 10 million triangles on a plot which has at most 1 million pixels may not make too much sense. In any case, if you do not have information about which vertex is adjacent to which other, you cannot directly use the plot_trisurf method.

I see two options:

  1. Plot a Poly3DCollection.
  2. Filter the unique points from the data and supply those to plot_trisurf. Using this method, you may not be able to colorize the triangles to your wishes, but only according to z-Value.

The following would be an example on how to plot a Poly3DCollection from your input data. For the purpose of demonstration we first need to provide some sample data (this needs to be the duty of the questioner, not the answerer).

import numpy as np
np.set_printoptions(threshold='nan')

phi = np.linspace(0,2*np.pi, 7)
x = np.cos(phi) + np.sin(phi)
y = -np.sin(phi) + np.cos(phi)
z = np.cos(phi)*0.12+0.7

a = np.zeros((len(phi)-1, 9))
a[:,0] = x[:-1]
a[:,1] = y[:-1]
a[:,2] = z[:-1]
a[:,3:6] = np.roll( a[:,0:3], -1, axis=0)
a[:,8] = np.ones_like(phi[:-1])
a = np.around(a, 2)
print a

which prints 

[[ 1.    1.    0.82  1.37 -0.37  0.76  0.    0.    1.  ]
 [ 1.37 -0.37  0.76  0.37 -1.37  0.64  0.    0.    1.  ]
 [ 0.37 -1.37  0.64 -1.   -1.    0.58  0.    0.    1.  ]
 [-1.   -1.    0.58 -1.37  0.37  0.64  0.    0.    1.  ]
 [-1.37  0.37  0.64 -0.37  1.37  0.76  0.    0.    1.  ]
 [-0.37  1.37  0.76  1.    1.    0.82  0.    0.    1.  ]]

(every set of 3 columns belongs to one point, first column is x, second y, third, z).

Now we can actually build the Poly3Dcollection.

from mpl_toolkits.mplot3d.art3d import Poly3DCollection
import matplotlib.pyplot as plt

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

fc = ["crimson" if i%2 else "gold" for i in range(a.shape[0])]

poly3d = [[ a[i, j*3:j*3+3] for j in range(3)  ] for i in range(a.shape[0])]

ax.add_collection3d(Poly3DCollection(poly3d, facecolors=fc, linewidths=1))

ax.set_xlim(-1.5,1.5)
ax.set_ylim(-1.5,1.5)

plt.show()

enter image description here

Upvotes: 4

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