working 3D version, still a little bit slow
reduced the test data to only 200 points.
Slight optimization
working version, with amethod patch -> ordered patch
changing the output to output result of classification per patch, so to be able to vizualize which one is well classified and so
corrected a nasty bug which was producing duplicates in output
new files with cleaned version of python ot compute rforest, all ina  lib
slightly modified
few changes to output level when needed, so as to be able to generate screen for the article
removing debug print
adding a new function to extract all classes above 1% weight, instead of the dominant one
New file to decompose points per level on a f_k(i) = (2^k)^i function base