# markov_v7_mem5

 Author PiotrekG Submission date 2018-08-24 07:58:59.581729 Rating 5964 Matches played 274 Win rate 58.39

Use rpsrunner.py to play unranked matches on your computer.

## Source code:

``````from __future__ import division
import random
import bisect

beat = {'R': 'P', 'P': 'S', 'S': 'R'}

class Markov_model():
def __init__(self, matrix):
self.matrix = matrix

def update_matrix(self, olag2, ilag1, lim):

self.matrix[olag2][ilag1]['N'] = self.matrix[olag2][ilag1]['N'] + 1

sum_n = 0
for i in self.matrix[olag2]:
sum_n += self.matrix[olag2][i]['N']

for i in self.matrix[olag2]:
self.matrix[olag2][i]['Pr'] = self.matrix[olag2][i]['N'] / sum_n

for i in self.matrix[olag2]:
self.matrix[olag2][i]['N'] = self.matrix[olag2][i]['N'] * lim / sum_n

@staticmethod
def weighted_choice(choices):
values, weights = zip(*choices)
total = 0
cum_weights = []
for w in weights:
total += w
cum_weights.append(total)
x = random.random() * total
i = bisect.bisect(cum_weights, x)
return values[i]

def predict(self, olag1):

prs = []
for i in self.matrix[olag1]:
prs.append((i, self.matrix[olag1][i]['Pr']))

prediction = self.weighted_choice(prs)

return prediction

lim = 5

if input == '':
output = random.choice(list(beat.keys()))
olag1 = ''
olag2 = ''
ilag1 = ''
# fist level is my output lag(2) and second level is input lag(1)
matrix = {
'R': {'R': {'Pr': 1 / 3, 'N': lim / 3},
'P': {'Pr': 1 / 3, 'N': lim / 3},
'S': {'Pr': 1 / 3, 'N': lim / 3}},
'S': {'R': {'Pr': 1 / 3, 'N': lim / 3},
'P': {'Pr': 1 / 3, 'N': lim / 3},
'S': {'Pr': 1 / 3, 'N': lim / 3}},
'P': {'R': {'Pr': 1 / 3, 'N': lim / 3},
'P': {'Pr': 1 / 3, 'N': lim / 3},
'S': {'Pr': 1 / 3, 'N': lim / 3}}
}

model = Markov_model(matrix)

elif olag2 != '':

model.update_matrix(olag2, ilag1, lim)
predicted_input = model.predict(olag1)
output = beat[predicted_input]

else:
output = random.choice(list(beat.keys()))

olag2 = olag1
olag1 = output
ilag1 = input``````