PSO 2D: Fitness Heatmap & Convergence Chart

Particle Swarm Optimization borrows its update rule from flocking behavior: every candidate solution ("particle") nudges its velocity toward the best position it has personally found and toward the best position known within its neighborhood, then moves. This 2D companion runs the identical PSO search over the Rastrigin benchmark, but represents it two genuinely 2D-native ways: the fitness landscape as a colour-mapped field on a flat grid (no elevation, no camera angle) instead of a 3D terrain, and a live convergence chart tracking best fitness and swarm diversity against iteration — a parameter-space view the 3D version has no equivalent of. Switch neighborhood topology between a fully-connected global-best swarm and a sparse local-best ring to see how it trades convergence speed against resistance to getting stuck in a local optimum.