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import time

import pandas as pd

import examples
import linear_program as lp


    

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t = time.clock()
setup = examples.run_setup_n(17)
print time.clock() - t


    

    




137.813685728

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times = lp.run_times(*setup, n=10)[:11]


    

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times


    

    
Out[10]:





[0.2922471828749167,
 6.672869102824848,
 10.80322061411988,
 6.233558384036712,
 8.512432526127157,
 6.098967572058143,
 7.980977029091207,
 4.346099130644006,
 5.768228565303218,
 3.563150185280506,
 6.903734518855003]

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t = pd.DataFrame(times)


    

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%matplotlib inline
t.hist()


    

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t.sort_values(0)


    

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def cumulative(t):
    n = len(t)
    t = t.sort_values(0)[0].values
    cum = [0] * n
    for i in range(0,n):
        if i > 0:
            cum[i] = cum[i-1] + t[i]
        else:
            cum[i] = t[i]
    return cum


    

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cumm = pd.DataFrame(cumulative(t))


    

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cumm.plot()


    

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sum(t.values)


    

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cumm


    

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