Meaning of n_sample in gmm_progress #78
Description
@clement-moulin-frier: Looking into gmm_progress, I am wondering what the n_sample parameter stand for and what is a reasonable value for it.
https://github.com/flowersteam/explauto/blob/master/explauto/interest_model/gmm_progress.py#L38L46
From what I understood it is the size of the window used, that is only the last n_sample are considered when fitting the GMM. Hence the self.data[self.t % self.n_samples, ... with the % used as a rolling index?
The condition to trigger the update rule is also a bit hard to follow:
if abs(self.t % (self.n_samples * self.scale_t / 4.)) < self.scale_t:
self.update_gmm()I think it updates every n_samples/4 steps, because scale_t is always 1.
Does this mean the first updates are done while self.data is not fully filled yet, hence full of zero? What is the potential effect of this on the algorithm, I guess it will just put a gaussian at [0,0,...,0] and maybe not find it 'interresting'.
(See https://github.com/flowersteam/explauto/blob/master/explauto/interest_model/gmm_progress.py#L24: self.data = numpy.zeros((n_samples, len(expl_dims) + 2)))
I migth propose a simplification for this and add the update frequency in the parameters.