ゲームのシミュレーション

game_simulation.py

#!/usr/bin/env python
# coding: utf-8

# In[1]:


import random
from pathlib import Path


# In[2]:


import pandas as pd


# In[3]:


class Player:
    def __init__(self, rating=1500, rate_num=0):
        self.rating = rating
        self.rate_num = rate_num
    def win_probability(self, rival):
        return 1. / (10. ** ((rival.rating - self.rating) / 400.) + 1.)
    def win(self, rival):
        return random.random() < self.win_probability(rival)
    @property
    def K(self):
        return 24 if self.rate_num >= 20 else 32


# In[4]:


random.seed(913) # ゲーム結果を固定する


# In[5]:


players = {
    'Emu': Player(2700.),
    'Parado': Player(2700.),
    'Niko': Player(2500.),
    'Taiga': Player(2000.),
    'Hiiro': Player(2000.),
    'Kiriya': Player(1700.),
    'Kuroto': Player(1700.),
    'Poppy': Player(1500.),
}


# In[6]:


column_names = []
for i in range(len(players) // 2):
    column_names.append(f'Match {i + 1} Winner')
    column_names.append(f'Match {i + 1} Loser')


# In[7]:


players_names = ['Emu', 'Parado', 'Niko', 'Taiga', 'Hiiro', 'Kiriya', 'Kuroto', 'Poppy']
rows = []
for _ in range(500):
    matching_order = []
    for players_name in players_names:
        matching_order.append((players_name,players[players_name],))
    matching_order = random.sample(matching_order, len(matching_order))
    result_per_game = matching_order.copy()
    for i in range(0, len(result_per_game), 2):
        if result_per_game[i + 1][1].win(result_per_game[i][1]):
            result_per_game[i],result_per_game[i + 1], = result_per_game[i + 1],result_per_game[i],
    result_per_game_name = list(map(lambda x: x[0], result_per_game))
    rows.append(pd.Series(result_per_game_name, index=column_names))


# In[8]:


result_df = pd.DataFrame(rows)
result_df.index = result_df.index + 1
result_df = result_df.reset_index()
result_df


# In[9]:


simulation_result_csv = Path('./simulation_result.csv')
result_df.to_csv(simulation_result_csv, index=False)