python -m pip install --user numpy scipy matplotlib ipython jupyter pandas sympy nose
pip install pulp

1. What dataset does the user want to use
    a. 's' (synthetic) for which we require the following arguments:
            'n' : int
                the size of the full rankings lists (also the total
                number of alternatives)
            'N' : int
                the total number of partial lists to be generated
            'theta' : float
                the parameter that is passed to the Mallows Model that
                dictates the probability distribution (consensus)
            'k' [optional] : int
                the distribution median (i.e. average candidates ranked)
                across all voters)
            's0' [optional] : int[]
                the ground list, which should order the n candidates 0,1,...,n-1
	'ep' (epsilon) If Score-Then-Adjust or Score-Then-Adjust Relaxed are part of the algorithms list, this parameter is required. Note: it gets passed with the algorithms list, not the parameters list

    b. 'r' (real), only requires a well formatted /path/to/file.CSV. By well
    formatted, we require that:

        i.  The first row has the number 'n' of alternatives

        ii. The following 'n' rows only have two columns: the first is the i'th
            candiate (int) and the second is a (str) describes the candiate

        iii.The n+2'nd row must have as its first column the total numbers
            of voters N (size of the input)

        iv. The top-lists being at line n+3, are newline separated from each other, and the
            alternatives within each list are comman separated and ordered from left to right

2. What algorithm(s) the user would like to use for top-list rank aggregation:
    a. 'FootRule+'
    b. 'RandomSort'
    c. 'Borda+'
    d. 'Score-Then-Borda+'
    e. 'Score-Then-Adjust'
    f. 'Local-Search'
    g. 'Relaxed-Linear-Program'
    h. 'Score-Then-Adjust-Relaxed'
    i. 'Copeland'
    j. 'Chanas"
    k. 'QS-Rand'
    l. 'QS-Det'
    m. 'IS'
    n. 'Opt'

3. Whether to run combinations of algorithms 'c' or not 'nc'. Combinations entails running Chanas and Local-Search as a postprocessing step for all algorithms (except opt).

4. An optinal seed argument. If provided, all random number generation will utilize the given seed. By default,
    random number generation will utilize the system's internal clock.

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	python3 sim.py [algo1,algo2,...,epsilon] s [n,N,theta,k] s0[OPTIONAL] c<OR>nc seed[OPTIONAL]
	python3 sim.py [algo,algo2,...] r FILEPATH c<OR>nc seed[OPTIONAL]

python3 sim.py [Opt] s [10,100,0.5,3] [8,4,6,1,2,9,3,7,5,10] nc 0

python3 sim.py [Chanas,RandomSort,Borda+,FootRule+] s [10,100,2,4] c

python3 sim.py [FootRule+] r ../data/soi/ED-00001-00000001.csv nc

python3 sim.py [Score-Then-Adjust,0.2,0.4,0.5,Score-Then-Borda+] s [5,50,0.5] nc 25