simulationexam/play_around.ipynb

In [1]:

from network.gibbs import *
from network.network import pp_network, can_antenna_be_turned_on
from collections import defaultdict
from random import Random
from numpy import matrix

In [2]:

mc = defaultdict(dict)
random = Random(66)

In [3]:

prec_network = 0

for i, network in zip(range(10**5), get_random_networks(2, random)):
    if network not in mc[prec_network]:
        mc[prec_network][network] = 0
    mc[prec_network][network] += 1
    prec_network = network

In [6]:

mc

Out [6]:

defaultdict(dict,
            {0: {0: 964, 1: 3671, 2: 1844, 4: 1759, 6: 1835, 8: 938, 9: 3387},
             1: {0: 891, 1: 3646, 2: 1832, 4: 1839, 6: 1729, 8: 938, 9: 3663},
             2: {0: 1810, 2: 3548, 4: 3517, 6: 3611, 8: 1811},
             4: {0: 1779, 2: 3519, 4: 3490, 6: 3486, 8: 1796},
             6: {0: 1885, 2: 3554, 4: 3465, 6: 3475, 8: 1757},
             8: {0: 3633, 1: 3553, 8: 3654, 9: 3572},
             9: {0: 3436, 1: 3668, 8: 3518, 9: 3527}})

In [4]:

def get_prob(from_, to):
    return mc[from_][to]/ sum(mc[from_].values())

def get_matrix(mc):
    n = len(mc)
    mat = [[] for i in range(n)]
    for i, from_ in enumerate(mc):
        for j in enumerate(mc):
            pass
            

In [ ]:

for key in mc:
    print(key)
    print( pp_network(key, 2))

In [5]:

ant = 1
print(get_prob(0, 2))
print(ant, can_antenna_be_turned_on(ant, 4, 2))

□-□
■-□

1 True

In [ ]:

0.5**4

In [ ]:

m = matrix([[1, 2], [3, 4]])
v = matrix([[1, 3]])

In [8]:

from numpy import std

In [10]:

std([1432, 1376, 1461, 1436, 1436, 1363, 1496])

Out [10]:

42.73458667121028

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