I have two lists of continuous data with different length.<br/>
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.<br/>
b) are there any python implementation for that purpose?<br/>
to put into context, these list contain likelihood values from HMM score function