6jgSN0Am

1# Import Modules
2import pandas as pd
3import numpy as np
4import os
5from pickle import dump,load
6from datetime import datetime
7
8class eloTable:
9
10    def __init__(self,df):
11        """
12        Constructor for creating an eloTable object
13        """
14
15        # Verify Pandas DataFrame
16        if not isinstance(df,pd.DataFrame):
17            raise NotImplementedError('eloTable object must be a Pandas DataFrame')
18
19        # Copy Constructor Arguments
20        self.df = df
21
22    def display(self):
23        """
24        Quick display of dataframe
25        """
26
27        # Print Out
28        print(self.df)
29
30    def save(self,dir,filename):
31        """
32        Description: Class method to pickle (save) an eloTable object
33
34        Input Arguments:
35	    dir -- Directory to write output pickle (.p) file to
36	    filename -- Name of output pickle (.p) file
37        """
38
39        # Verify Directory Exists
40        if not os.path.exists(dir):
41            raise OSError('Provided output directory %s does not exist' %(dir))
42
43        # Format filename
44        if not filename.endswith('.p'):
45            filename = filename + '.p'
46
47        # Generate Full File Path
48        file = os.path.join(dir,filename)
49
50        # Check if File Already Exists
51        if os.path.exists(file):
52            print('[%s] %s already exists on the system. Overwriting this file' %(datetime.now(),file))
53            os.remove(file)
54
55        # Create Pickle File
56        dump(self.df,open(file,'wb'))
57
58    def add_player(self,player,elo = 1000):
59        """
60        Description: Method to add new row (Player,Elo) to eloTable object
61
62        Input Arguments:
63        player -- Player's name
64        elo -- Elo rating for new player
65            Default: 1000
66        """
67
68        # Create DataFrame
69        data = {'Player': player,'Elo': elo,'GP': 0,'W': 0,'L':0}
70
71        # Append
72        self.df = self.df.append(data,ignore_index = True)
73
74    def update_elo(self,winners,losers,K = 20):
75        """
76        Description: Update Elo table for a new game
77
78        Input Argument(s):
79        winners -- List of game winners
80        losers -- List of game losers
81        """
82
83        def probability(a,b):
84            return 1.0 * 1.0 / (1 + 1.0 * 10**(1.0 * (a - b) / 400.0))
85
86        # Account for New Players
87        for player in (winners + losers):
88            if player not in self.df.values:
89                self.add_player(player)
90
91        # Get Elo Values for Both Teams
92        ra = np.mean(self.df.loc[self.df.Player.isin(winners),'Elo'])
93        rb = np.mean(self.df.loc[self.df.Player.isin(losers),'Elo'])
94
95        # Compute Probabilities
96        ea = probability(rb,ra)
97        eb = probability(ra,rb)
98
99        # Update Elo for Inidividuals
100        self.df.loc[self.df.Player.isin(winners),'Elo'] = round(self.df.loc[self.df.Player.isin(winners),'Elo'] + K * (1.0 - ea))
101        self.df.loc[self.df.Player.isin(losers),'Elo'] = round(self.df.loc[self.df.Player.isin(losers),'Elo'] + K * (0.0 - eb))
102
103        self.df.loc[self.df.Player.isin(winners + losers),'GP'] = self.df.loc[self.df.Player.isin(winners + losers),'GP'] + 1
104        self.df.loc[self.df.Player.isin(winners),'W'] = self.df.loc[self.df.Player.isin(winners),'W'] + 1
105        self.df.loc[self.df.Player.isin(losers),'L'] = self.df.loc[self.df.Player.isin(losers),'L'] + 1
106
107def load_pickle(file):
108    """
109    Description: Function to load pickle (.p) file
110
111    Input Argument(s):
112    file -- Absolute file path to pickle (.p) file
113
114    Output:
115    e -- Object
116    """
117
118    # Verify Existence of File
119    if not os.path.exists(file):
120        raise OSError('Provided output directory %s does not exist' %(file))
121
122    # Verify if Pickle File
123    if not file.endswith('.p'):
124        raise OSError('Provided file does not appear to be a pickle (.p) file')
125
126    # Load Pickle
127    df = load(open(file,'rb'))
128
129    # Generate Object
130    e = eloTable(df)
131
132    # Return
133    return e