[Matplotlib-users] Matplotlib with invalid triangulations

[Pat Prodanovic]

Hello,

I am using JR Shewchuk's Triangle to create triangulations for use in 
floodplain modeling. I am using a city's digital terrain model with 
hundreds of thousands of breaklines that constrain where triangles can 
form in the triangulations (streets, rivers, etc). Triangle does this 
very efficiently.

Sometimes the input topology I am using has bad inputs which makes 
Triangle create zero area elements. When I import these triangulations 
to Matplotlib I get the error that such triangulations are invalid (when 
using the LinearTriInterpolator() method). I understand the trapezoid 
map algorithm implemented requires only valid triangulations. So far, so 
good.

The option of cleaning the input topology before using Matplotlib 
exists, but it is really cumbersome. Rather than topology cleaning, am I 
am able to somehow throw out the zero area elements from the call to 
LinearTriInterpolator() method, and still use the triangulation in 
Matplotlib? My other alternative is to use something other than 
trapezoidal map algorithm, but this is just not computationally efficient.

I've reproduced the following example that illustrates the problem in a 
small code snippet. Any suggestions?

Thanks,

Pat Prodanovic

# +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-
import matplotlib.tri as mtri
import numpy as np

# manually construct an invalid triangulation having a zero area element
x = np.array([0.0, 1.0, 1.0, 1.0, 2.0])
y = np.array([1.0, 0.0, 2.0, 1.0, 1.0])
z = np.zeros(5)

triangles = np.array( [[0, 1, 2], [1, 3, 2], [1, 4, 2], [0, 4, 1]])

# create a Matplotlib Triangulation
triang = mtri.Triangulation(x,y,triangles)

# to perform the linear interpolation
interpolator = mtri.LinearTriInterpolator(triang, z)
m_z = interpolator(1.0, 1.0)
# +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-