Producing Quick and Easy Plots of Topology within OpenPNM

The main way to visualize OpenPNM networks is Paraview, but this can be a bit a hassle when building a new network topology that needs quick feedback for troubleshooting. Starting in V1.6, OpenPNM offers two plotting functions for showing pore locations and the connections between them: OpenPNM.Network.tools.plot_coordinates and OpenPNM.Network.tools.plot_connections. This example demonstrates how to use these two methods.

Start by initializing OpenPNM and creating a network. For easier visualization we'll use a 2D network:



In [1]:

    
import openpnm as op
net = op.network.Cubic(shape=[5, 5, 1])









    



C:\Users\Tom\Anaconda3\lib\site-packages\h5py\__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters

Next we'll add boundary pores to two sides of the network, to better illustrate these plot commands:



In [2]:

    
net.add_boundary_pores(['left', 'right'])

Now let's use plot_coordinates to plot the pore centers in a 3D plot, starting with the internal pores:



In [3]:

    
fig = op.topotools.plot_coordinates(network=net, pores=net.pores('internal'), c='r')
ax = fig.gca()  # This line is only needed in Jupyter notebooks

Note that the above call to plot_coordinates returns a figure handle fig. This can be passed into subsequent plotting methods to overlay points.



In [4]:

    
Ps = net.pores('*boundary')
fig = op.topotools.plot_coordinates(network=net, pores=Ps, fig=fig, c='b')
ax.get_figure()  # This line is only needed in Jupyter notebooks









    Out[4]:

Next, let's add lines to the above plot indicating the throat connections. Again, by reusing the fig object we can overlay more information:



In [5]:

    
Ts = net.find_neighbor_throats(pores=Ps)
fig = op.topotools.plot_connections(network=net, throats=Ts, fig=fig, c='b')
Ts = net.find_neighbor_throats(pores=net.pores('internal'), mode='intersection')
fig = op.topotools.plot_connections(network=net, throats=Ts, fig=fig, c='r')
ax.get_figure()  # This line is only needed in Jupyter notebooks









    Out[5]:

These two methods are meant for quick and rough visualizations. If you require high quality 3D images, you should use Paraview: ![](https://i.imgur.com/uSBVFi9m.png)