It took a bit of thinking, but I finally implemented the rest of the hierarchical clustering algorithm in python. However, there were a few fallbacks:

For one, there's a LOT of blank spaces in the array. Right now, I'm trying to train a 45 * 45 emotion distance matrix entirely by hand. which involves sitting down at a computer several times a day and answering questions about my feelings to the python script that I wrote. I want rin to be able to adapt to each user, which means the user should train rin themselves as well, but this will take way more time than I ever imagined.

I thought about shrinking the length of the emotional association list, but there's too many good description words for emotions in there. Maybe add a way for the user to reject emotions or use a matrix that only includes emotion data that they have chosen? 

Either way, I'll keep training rin in hopes that I'll finally create a dense enough distance matrix. Right now, all the 0's are being jammed together, meaning that the first 10 emotions are all in one huge similarity tree. I don't want to extrapolate by assuming that the first 10 emotions are all similar, so I'm holding off on playing with the similarity data until I've trained rin more.