In [3]:

    

import pandas
folder = '/Users/garcia/Dropbox/simulationResults/repeatedgameswithmistakes/third_trial_harvard/'


    

In [5]:

    

df = pandas.read_csv(folder + 'tr_3_time_game_2_scheme_bias_mistake_0.0.csv', nrows=100)


    

In [27]:

    

one_pop = df['population'][18]


    

In [18]:

    

one_pop


    

    
Out[18]:





'[D/DD0DC0CD0CC0]:186; [D/DD0DC0CD1CC0, C/DD0DC1CD0CC1]:14'

In [16]:

    

(len(str(one_pop).split(':'))/2)


    

    
Out[16]:





1

In [39]:

    

splitted = str(one_pop).split(';')


    

In [40]:

    

pairs = zip(splitted[::2], splitted[1::2])


    

In [42]:

    

pairs[0][0]


    

    
Out[42]:





'[D/DD0DC0CD0CC0]:186'

In [43]:

    

splitted


    

    
Out[43]:





['[D/DD0DC0CD0CC0]:186', ' [D/DD0DC0CD1CC0, C/DD0DC1CD0CC1]:14']

In [46]:

    

def build_dict(population_string):
    ans = dict()
    splitted = str(population_string).split(';')
    for pair in splitted:
        strategy = pair.split(':')[0]
        count = int(pair.split(':')[1])
        ans[strategy] = count
    return ans


    

In [47]:

    

build_dict(one_pop)


    

    
Out[47]:





{' [D/DD0DC0CD1CC0, C/DD0DC1CD0CC1]': 14, '[D/DD0DC0CD0CC0]': 186}

In [48]:

    

resultado = _


    

In [88]:

    

def average_automaton_size(diccionario):
    number_of_individuals = np.sum(diccionario.values())
    ans = 0.0
    for key, value in diccionario.items():
        freq = float(value)
        states = float(key.count('/'))
        ans = ans + freq*states
    return ans/number_of_individuals


    

In [83]:

    

resultado.items()


    

    
Out[83]:





[(' [D/DD0DC0CD1CC0, C/DD0DC1CD0CC1]', 14), ('[D/DD0DC0CD0CC0]', 186)]

In [87]:

    

average_automaton_size(resultado)


    

    
Out[87]:





1.0700000000000001

In [84]:

    

(14*2+186)/200.0


    

    
Out[84]:





1.07

In [ ]: