Pareto front and skyline ranking - Python

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Python

algorithm

I have the following Python code that calculates the Pareto Front of a specific list of 2-d vectors:

def pareto_frontier(Xs, Ys, maxX = True, maxY = True):
myList = sorted([[Xs[i], Ys[i]] for i in range(len(Xs))], reverse=maxX)
p_front = [myList[0]]    
for pair in myList[1:]:
    if maxY: 
        if pair[1] >= p_front[-1][1]:
            p_front.append(pair)
    else:
        if pair[1] <= p_front[-1][1]:
            p_front.append(pair)
p_frontX = [pair[0] for pair in p_front]
p_frontY = [pair[1] for pair in p_front]
return p_frontX, p_frontY

My goal is to convert this function into a ranking problem. I have read about the skyline ranking, and I would like to apply this ranking algorithm to a list of 100 5-d vectors (by minimising all variables). Since this is a fairly small list of vectors, I am not really interested in efficiency. As reference, these papers seem to present my desired goal:

https://www.sciencedirect.com/science/article/pii/S0169023X10000480

http://cgi.di.uoa.gr/~gvalk/pubs/dp-idp.pdf

https://www.sciencedirect.com/science/article/pii/S0306437911000421

What I have tried:

<pre>def pareto_frontier(Xs, Ys, maxX = True, maxY = True):
myList = sorted([[Xs[i], Ys[i]] for i in range(len(Xs))], reverse=maxX)
p_front = [myList[0]]    
for pair in myList[1:]:
    if maxY: 
        if pair[1] >= p_front[-1][1]:
            p_front.append(pair)
    else:
        if pair[1] <= p_front[-1][1]:
            p_front.append(pair)
p_frontX = [pair[0] for pair in p_front]
p_frontY = [pair[1] for pair in p_front]
return p_frontX, p_frontY