...
This is the standard option in NCL and pyNGL for plotting unstructured data. NCL will internally compute a Delaunay triangulation of the data (via http://www.cs.cmu.edu/~quake/triangle.html ), where the data now lives on the vertex of each triangle. NCL then appears to form the Voronoi diagram (dual grid of the triangulation). On the this dual grid, the data is now located at the center of each of the dual grids polygonsVoronoi cells. With “RasterFill”, each of these dual grid polygons Voronoi cells will be colored based on the value of the original data set. The This results are an accurate representation of all the data points in the original field, but can be quite ugly and is a very unnatural representation of the original spectral element data.
...
This approach is not available in NCL, but is available in matplotlib. In this approach, the same a Delaunay triangulation is first computed. Then each triangle is shaded using a linear interpolating based on the its three vertex values. This produces nice looking results. It also has the advantage that it is monotone and min/max/oscillation preserving. All values in the original data set will be plotted. It’s perhaps the best visual representation of GLL vertex data.
...