Four clusters were simulated in the Euclidean plane by sampling from the rotationally symmetric normal distribution with means corresponding to the different cluster centers and variance matrix I. The numbers of points in the clusters were 50, 100, 150, and 200 for the black, red, green, and blue clusters, respectively. A) A plot of the points is shown colored by cluster. B) Heatmap that color-codes the ordered adjacency matrix, calculated using the formula A(i,j) = 1 − [Euclidean.Distance(i,j)/ max(Euclidean.Distance(i,j))]2. In this plot red indicates a high adjacency, and green indicates a low adjacency. As expected, the adjacency within clusters is very high, and the adjacency between the blue and black clusters is the lowest since they are the furthest apart. C) The scatter plot between propensity (y-axis) and whole network connectivity (row sum of the adjacency matrix, Eq. 7) shows that the propensity is related to the distance between a point and its cluster’s center (given Eq. 10) in this example. D) Scatter plot between cluster similarity (y-axis) calculated using CPBA and the Euclidean distance between cluster centers (x-axis) shows a perfect negative correlation (-1).