I am trying to process a large set of location data where a list of start and end coordinate is given. For example,
[ [(start_lat1, start_lon1), (end_lat1, end_lon1)], [(start_lat2, start_lon2), (end_lat2, end_lon2)], [(start_lat3, start_lon3), (end_lat3, end_lon3)], [(start_lat4, start_lon4), (end_lat4, end_lon4)], [(start_lat5, start_lon5), (end_lat5, end_lon5)], ... ]
My goal is to create clusters so that if different pair of start and end locations are close, they will form a cluster of pair with those start and end locations. For example, the average for the clustered pair will look something like this,
[ [(start_lat_C1, start_lon_C1), (end_lat_C1, end_lon_C1)], [(start_lat_C2, start_lon_C2), (end_lat_C2, end_lon_C2) ... ]
I was following https://geoffboeing.com/2014/08/clustering-to-reduce-spatial-data-set-size/ this, but the tutorial only works for a single coordinate point. Any help about how to approach for paired clustering would be much appreciated.