def team_rating(resultfile='ncaa_results.csv',
teamfile='ncaa_teams.txt',
K=16.):
'''
Rate the teams in the game results imported from a CSV file.
(1) import the W matrix from `resultfile` file.
(2) compute Elo ratings of all the teams
(3) return a list of team names sorted by descending order of Elo ratings
Input:
resultfile: the csv filename for the game result matrix, a string.
teamfile: the text filename for the team names, a string.
K: a float scalar value, which is the k-factor of Elo rating system
Output:
top_teams: the list of team names in descending order of their Elo ratings, a python list of string values, such as ['team a', 'team b','team c'].
top_ratings: the list of elo ratings in descending order, a python list of float values, such as ['600.', '500.','300.'].
'''
#########################################
## INSERT YOUR CODE HERE
W = import_W(resultfile)
N = import_team_names(teamfile)
top_teams = list()
M = elo_rating(W, len(N))
top_ratings = sorted(M, reverse=True)
ratings_indice = sorted(range(len(M)), reverse=True, key=lambda x: M[x])
for i in ratings_indice:
top_teams.append(N[i])
#########################################
return top_teams, top_ratings
def team_rating(resultfile = 'ncaa_results.csv',
teamfile='ncaa_teams.txt',
K=16.):
'''
Rate the teams in the game results imported from a CSV file.
(1) import the W matrix from `resultfile` file.
(2) compute Elo ratings of all the teams
(3) return a list of team names sorted by descending order of Elo ratings
Input:
resultfile: the csv filename for the game result matrix, a string.
teamfile: the text filename for the team names, a string.
K: a float scalar value, which is the k-factor of Elo rating system
Output:
top_teams: the list of team names in descending order of their Elo ratings, a python list of string values, such as ['team a', 'team b','team c'].
top_ratings: the list of elo ratings in descending order, a python list of float values, such as ['600.', '500.','300.'].
'''
W = import_W(resultfile)
team_names = import_team_names(teamfile)
num_teams = len(team_names)
ratings = elo_rating(W,num_teams,K)
team_ratings_dict = dict(zip(team_names, ratings))
sorted_dict = dict(sorted(team_ratings_dict.items(), key=lambda x: x[1], reverse=True))
top_teams = list(sorted_dict)
top_ratings = list(sorted_dict.values())
return top_teams, top_ratings
def team_rating(resultfile='ncaa_results.csv',
teamfile='ncaa_teams.txt',
K=16.):
'''
Rate the teams in the game results imported from a CSV file.
(1) import the W matrix from `resultfile` file.
(2) compute Elo ratings of all the teams
(3) return a list of team names sorted by descending order of Elo ratings
Input:
resultfile: the csv filename for the game result matrix, a string.
teamfile: the text filename for the team names, a string.
K: a float scalar value, which is the k-factor of Elo rating system
Output:
top_teams: the list of team names in descending order of their Elo ratings, a python list of string values, such as ['team a', 'team b','team c'].
top_ratings: the list of elo ratings in descending order, a python list of float values, such as ['600.', '500.','300.'].
'''
#########################################
## INSERT YOUR CODE HERE
W = import_W(resultfile)
team_names = import_team_names(teamfile)
R = elo_rating(W, len(team_names))
top_teams = [x for _, x in sorted(zip(R, team_names), reverse=True)]
top_ratings = sorted(R, reverse=True)
#########################################
return top_teams, top_ratings
def team_rating(resultfile='ncaa_results.csv',
teamfile='ncaa_teams.txt',
K=16.):
'''
Rate the teams based upon the game results imported from a CSV file.
(1) import the W matrix from `resultfile` file.
(2) compute Elo ratings of all the teams
(3) return a list of team names sorted by descending order of Elo ratings
Input:
resultfile: the csv filename for the game result matrix, a string.
teamfile: the text filename for the team names, a string.
K: a float scalar value, which is the k-factor of Elo rating system
Output:
top_teams: the list of team names in descending order of their Elo ratings, a python list of string values, such as ['Randolph Col', 'Liberty', ... ].
top_ratings: the list of elo ratings in descending order, a python list of float values, such as ['600.', '500.','300.'].
'''
#########################################
## INSERT YOUR CODE HERE
# load team names from 'teamfile'
team_names = import_team_names(teamfile)
print(len(team_names))
# load game results from 'resultfile'
game_results = list(import_W(resultfile).astype(int))
print(type(game_results[0][0]))
print(game_results[0])
# compute Elo rating of all the teams
elo_ratings = elo_rating(game_results, len(team_names))
print(len(elo_ratings))
# sort team names according to their Elo ratings
ratings_dict = dict(zip(list(range(len(team_names))), elo_ratings))
print(len(list(range(len(team_names)))))
print(list(range(len(team_names)))[0:5])
print(len(ratings_dict))
top_rating_dict = sorted(ratings_dict.items(),
key=lambda item: item[1],
reverse=True)
print(top_rating_dict[:3])
# top_ratings = sorted(ratings_dict.keys(), reverse= True)
top_ratings = [x[1] for x in top_rating_dict]
print(top_ratings[:3])
# top_teams = [ratings_dict[x] for x in top_ratings]
top_teams = [team_names[x[0]] for x in top_rating_dict]
print(len(top_teams))
print(top_teams[:3])
#########################################
return top_teams, top_ratings
def team_rating(resultfile = 'ncaa_results.csv',
teamfile='ncaa_teams.txt',
K=16.):
'''
Rate the teams based upon the game results imported from a CSV file.
(1) import the W matrix from `resultfile` file.
(2) compute Elo ratings of all the teams
(3) return a list of team names sorted by descending order of Elo ratings
Input:
resultfile: the csv filename for the game result matrix, a string.
teamfile: the text filename for the team names, a string.
K: a float scalar value, which is the k-factor of Elo rating system
Output:
top_teams: the list of team names in descending order of their Elo ratings, a python list of string values, such as ['Randolph Col', 'Liberty', ... ].
top_ratings: the list of elo ratings in descending order, a python list of float values, such as ['600.', '500.','300.'].
'''
#########################################
## INSERT YOUR CODE HERE
top_teams= []
top_ratings= []
# load team names from 'teamfile'
allTeams = import_team_names(teamfile)
# load game results from 'resultfile'
allResults = import_W(resultfile)
totalTeams = len(allTeams)
# compute Elo rating of all the teams
allElos = elo_rating(allResults, totalTeams, K= 16.)
# sort team names according to their Elo ratings
allData = np.vstack((allElos, allTeams)).T.tolist()
#print(allData)
#sortAllData = sorted(allData, key=itemgetter(0), reverse=True)
sortAllData = sorted(allData, key=lambda x: x[0], reverse=True)
print(sortAllData)
for i, team in enumerate(allTeams):
top_teams.append(sortAllData[i][1])
for i, result in enumerate(allElos):
top_ratings.append(float(sortAllData[i][0]))
#print(top_teams)
#print(top_ratings)
#########################################
return top_teams, top_ratings
def team_rating(resultfile = 'ncaa_results.csv',
teamfile='ncaa_teams.txt',
K=16.):
'''
Rate the teams based upon the game results imported from a CSV file.
(1) import the W matrix from `resultfile` file.
(2) compute Elo ratings of all the teams
(3) return a list of team names sorted by descending order of Elo ratings
Input:
resultfile: the csv filename for the game result matrix, a string.
teamfile: the text filename for the team names, a string.
K: a float scalar value, which is the k-factor of Elo rating system
Output:
top_teams: the list of team names in descending order of their Elo ratings, a python list of string values, such as ['Randolph Col', 'Liberty', ... ].
top_ratings: the list of elo ratings in descending order, a python list of float values, such as ['600.', '500.','300.'].
'''
#########################################
## INSERT YOUR CODE HERE
# load team names from 'teamfile'
team_names = import_team_names(teamfile)
# load game results from 'resultfile'
fr = import_W(resultfile)
results = fr.astype(int)
# compute Elo rating of all the teams
elo = elo_rating(results, len(team_names), K)
# sort team names according to their Elo ratings
sorted_teams = np.flip(np.argsort(elo))
top_teams = []
for x in sorted_teams:
top_teams.append(team_names[x])
top_ratings = np.flip(np.sort(elo))
print(top_ratings)
#########################################
return top_teams, top_ratings
def team_rating(resultfile='ncaa_results.csv',
teamfile='ncaa_teams.txt',
K=16.):
'''
Rate the teams in the game results imported from a CSV file.
(1) import the W matrix from `resultfile` file.
(2) compute Elo ratings of all the teams
(3) return a list of team names sorted by descending order of Elo ratings
Input:
resultfile: the csv filename for the game result matrix, a string.
teamfile: the text filename for the team names, a string.
K: a float scalar value, which is the k-factor of Elo rating system
Output:
top_teams: the list of team names in descending order of their Elo ratings, a python list of string values, such as ['team a', 'team b','team c'].
top_ratings: the list of elo ratings in descending order, a python list of float values, such as ['600.', '500.','300.'].
'''
#########################################
## INSERT YOUR CODE HERE
# load game results
W = import_W(resultfile)
# load team names
team_names = import_team_names(teamfile)
# number of teams
n_player = len(set(team_names))
# compute Elo rating of the teams
team_ratings = elo_rating(W, n_player)
team_info = zip(team_names, team_ratings)
# sort team names
team_info = sorted(team_info, key=lambda x: x[1], reverse=True)
top_teams, top_ratings = map(list, zip(*team_info))
#########################################
return top_teams, top_ratings
def team_rating(resultfile='ncaa_results.csv',
teamfile='ncaa_teams.txt',
K=16.):
'''
Rate the teams based upon the game results imported from a CSV file.
(1) import the W matrix from `resultfile` file.
(2) compute Elo ratings of all the teams
(3) return a list of team names sorted by descending order of Elo ratings
Input:
resultfile: the csv filename for the game result matrix, a string.
teamfile: the text filename for the team names, a string.
K: a float scalar value, which is the k-factor of Elo rating system
Output:
top_teams: the list of team names in descending order of their Elo ratings, a python list of string values, such as ['Randolph Col', 'Liberty', ... ].
top_ratings: the list of elo ratings in descending order, a python list of float values, such as ['600.', '500.','300.'].
'''
#########################################
## INSERT YOUR CODE HERE
# load team names from 'teamfile'
team_names = import_team_names(teamfile)
# load game results from 'resultfile'
W = import_W(resultfile)
n_players = np.size(team_names, 0)
# compute Elo rating of all the teams
R = elo_rating(W, n_players, K)
# sort team names according to their Elo ratings
zip_list = list(zip(R, team_names))
zip_list.sort(reverse=True)
top_ratings, top_teams = zip(*zip_list)
#########################################
return top_teams, top_ratings
def team_rating(resultfile='ncaa_results.csv',
teamfile='ncaa_teams.txt',
K=16.):
'''
Rate the teams based upon the game results imported from a CSV file.
(1) import the W matrix from `resultfile` file.
(2) compute Elo ratings of all the teams
(3) return a list of team names sorted by descending order of Elo ratings
Input:
resultfile: the csv filename for the game result matrix, a string.
teamfile: the text filename for the team names, a string.
K: a float scalar value, which is the k-factor of Elo rating system
Output:
top_teams: the list of team names in descending order of their Elo ratings, a python list of string values, such as ['Randolph Col', 'Liberty', ... ].
top_ratings: the list of elo ratings in descending order, a python list of float values, such as ['600.', '500.','300.'].
'''
#########################################
## INSERT YOUR CODE HERE
# load team names from 'teamfile'
team_name = import_team_names(teamfile)
# load game results from 'resultfile'
results = import_W(resultfile)
# compute Elo rating of all the teams
e = elo_rating(results, len(team_name), K=16.)
# sort team names according to their Elo ratings
top_set = zip(team_name, e)
top_set1 = sorted(top_set, key=lambda x: x[1], reverse=True)
top_teams, top_ratings = map(list, zip(*top_set1))
#########################################
return top_teams, top_ratings
team_names = []
with open(filename) as f:
line = f.readline()
while line:
line = line.strip('\n')
team_names.append(line)
line = f.readline()
f.close()
return team_names
# load game results
W = import_W(filename='ncaa_results.csv')
# load team names
team_names = import_team_names(filename='ncaa_teams.txt')
# number of teams
n_player = len(team_names)
# compute Elo rating of the teams
R = elo_rating(W, n_player, K=16.)
top_ratings = sorted(R,reverse=True)
print n_player
print R
print top_ratings
top = sorted(range(len(R)), key=lambda k: R[k],reverse=True)
top_teams = []
for i in top:
top_teams.append(team_names[i])
print top_teams
