how do you incorporate functions in features64/ with xgboost model?

After training the model and saving xgboost model, how do you incorporate handmade functions in features64/ to improve the classification?
I particularly do not understand how to organize input to each of the functions in features64/ as "numpy array of n rows and 3 columns".

Any help would be greatly appreciated.
Thank you.