I have two lists of continuous data with different length.
a) How should I measure (dis)similarity of these two lists? or, as these lists can be formed into histogram, how can I quantify (dis)similarity of these two histograms? I want to take into account the shape (distribution) and the location of these histograms, but want the frequency normalised.
b) are there any python implementation for that purpose?
to put into context, these list contain likelihood values from HMM score function

I have two lists of continuous data with different length.
a) How should I measure (dis)similarity of these two lists? or, as these lists can be formed into histogram, how can I quantify (dis)similarity of these two histograms? I want to take into account the shape and the location of these histograms, but want the frequency normalised.
b) are there any python implementation for that purpose?
to put into context, these list contain likelihood values from HMM score function