Hello all, I have an experiment in which I train a 5x5 map of nodes to describe meteorological fields with Self Organizing Maps. I am using the python library called minisom but I've tested a few others and have the same issue. I can initialize my som model by performing a principal component analysis and distributing my initial nodes along the main axes, but I think the library does not allow me to control the node values in finer detail. For example, if I train a som model with certain parameters, I obtain a set of nodes, and then I want to use those trained nodes to initialize a new training experiment, I can't do that, because the python "som" object only allows me to "see" the node values, not to change them or specify them in any other way than training.

So, I would like to know if I can achieve this with these simple python libraries or if I should be looking for more complex tools to train som models.