In this lecture, we will cover the following:

• How to wrap our plotting logic into a reusable function
• How to add a wireframe, node markers, and conditional node and element labels
• How to take advantage of Plotly's built-in legend interactivity

Now that we have a procedurally generated mesh, we want to actually see it on screen. We will define a function called plot_mesh that takes in a Plotly figure, the nodes and elements arrays, and two Boolean flags that let us toggle node and element labels on and off. After extracting the $x$, $y$ and $z$ coordinates from the nodes array, we use the same triangulation approach we used in the previous section, splitting each quadrilateral into two triangles so that we can plot the entire surface in a single mesh3d call rather than iterating element by element.

On top of that surface, we add a wireframe by iterating through every element and plotting a closed scatter3d loop for its four edges. We also drop in node markers and, conditionally, text labels at each node and at the centroid of each element. We then set the axis labels, sizing and legend options through update_layout, and call the function to render the structure.

Next up

In the next lecture, we will move on to some more substantial finite element work and start calculating the transformation and rotation matrices for each element in our mesh.