Abstract
Given an undirected network, we describe a two-dimensional graphical measure based on the connected component distribution of its degree-limited subgraphs. This process yields an unambiguous visual portrait, which reveals important network properties. It can be used as a classification tool, as graphs from related application areas have striking similarities. It can also be used as an efficient algorithm to demonstrate graph non-isomorphism for large graphs with identical degree distributions. Finally, it can be used as an analysis tool to help distinguish real-world networks from their synthetic counterparts.