A MATLAB code for analyzing the distribution of CH distribution in C3S paste Core Functionality Circle Detection via Monte Carlo Simulation Generates num_simulations random circles within the image boundaries using uniform sampling Calculates pixel intensity sums within each circle's radius Ranks circles by pixel coverage and retains top num_circles_to_keep candidates Spatial Distribution Analysis Distance Matrix: Computes pairwise Euclidean distances between circle centers Uniformity Metrics: Average Nearest Neighbor Distance: Quantifies spatial clustering Clark-Evans Index: Tests randomness hypothesis (value >1 indicates uniformity) Moran's I: Measures spatial autocorrelation (requires custom spatial weights) Visualization Overlays detected circles on original/image masks using viscircles Plots center distributions via scatter plots with axis equalization Input/Output Specifications Parameter Description image Binary matrix (0-1 values) radius Pixel radius of target circles num_circles_to_keep Top-ranked circles by intensity summation Output circle_centers Coordinates matrix [X,Y] of optimal circles