Python code please.

Clusterization of 2D Point Scatters Data collected by imaging is often processed to detect individual point-like entities, like particles suspended in a fluid, or organisms in swarms, or stars in galaxies. A common processing method for point-like data is clustering, that is, automatic detection of distinct aggregations of points. In this assignment, you will write a Python program that will read in a set of 2D (x, y) points and, using a distance-based criterion, assign each point to a cluster. The criterion for deciding whether any two points belong to the same cluster is whether the distance between them is below some predefined threshhold value. An algorithm for identifying clusters in a for a set of points is below. Algorithm 1: Clusterization of 2D Point Scatters Input: A list of points; each point has an (x,y) position and a cluster index Result: Each point's cluster index indicating which cluster it belongs to for i i and j i and j