Thanks by that, I am reading and learning a lot because this need to be my next step (R or Python clustering), but not found yet clustering with max number of points per cluster and/or maximum distance, only minimum points and/or maximum distance. I got my result using NeighborFinder, but in manualy way, I cluster the firsts points and they get out of my analysis them I go ahead with the rest data and next NeighboorFinder, as I said, my data is small so this is possible, but I needed to create more than 50 neighborhoodfinder transforms and the result is ok, I can go through this way, its not the best fit, but it is acceptable.
My problem now is that I need to change the parameters and it´s not easy to change parameters of 50 neighboorfinder and with I change the distance and numbers of neighboor to find, I need to change the number of interactions, in that case I will reduce the number, so I gonna need more neighboorfinders interacions. So Looping into my NeighborFinders until my data is over is my goal, but it´s being quite impossible. I have made it perfect to my eyes and I got this answer "
f_12 (TransformFact): Custom transformer 'NEIBA' does not have a port named 'Input_2' which is suitable for parameter 'LOOPBACK_INPUT_TAG'
Custom transformer 'NEIBA' does not have a port named 'Input_2' which is suitable for parameter 'LOOPBACK_INPUT_TAG' "
But I have this port, but it´s not published (because I need the attributes from the last interaction). If I make thhis port visible (Published), my process go ahead, but it´s never end.
Because of necessity of transform qualification as Linked Always, I can´t see where the problem is. I am very frustated that I can´t make a simple loop with a block transform.