我先说： 我知道这是一个被问到很多的问题。我已经阅读了其他答案，并排除了：
我没有使用+ =作为作业;
我已经尝试在函数中明确地分配每个变量，以确保它们不为空，以防函数失败的其他工作;
他们不全局变量，我不希望它们 - 它们只是我用来计算我最终返回的内部变量。
## Gets the data from external website - refreshes whenever the programme is called.
## Urllib2 required module
## csv to make life easier handling the data
import urllib2
import csv
import sys
import math
# import sqlite3 #don't need this just now, will probably run Django with MySQL when it comes to it
# import MySQLdb Likewise, don't need this just now.
#python3
import atexit
from time import time
from datetime import timedelta
def secondsToStr(t):
return str(timedelta(seconds=t))
line = "="*40
def log(s, elapsed=None):
print(line)
print(secondsToStr(time()), '-', s)
if elapsed:
print("Elapsed time:", elapsed)
print(line)
print()
def endlog():
end = time()
elapsed = end-start
log("End Program", secondsToStr(elapsed))
def now():
return secondsToStr(time())
start = time()
atexit.register(endlog)
log("Start Program")
def open_external_source():
# Checks if the core file's been modified since the last time we used it - if it hasn't, then we skip all of the file reading stuff.
#need to change this to just pull the headers the first time.
master_data_file = urllib2.urlopen("http://www.football-data.co.uk/mmz4281/1213/E0.csv", "GET")
print master_data_file
headers = master_data_file.info()
last_mod = headers["last-modified"]
settings = open ("settings.csv","r+")
historic_last_mod = settings.readline() #this only works when the setting is a 1 line file
print "Local file version: " + historic_last_mod
print "Server file version: " +last_mod
if last_mod == historic_last_mod :
print "It's the same, file not loaded"
return true
else :
return false
settings.close()
#the if statement's commented out because it was messing up the variables into the function
#if open_external_source == False:
master_data_file = urllib2.urlopen("http://www.football-data.co.uk/mmz4281/1213/E0.csv", "GET")
data = list(tuple(rec) for rec in csv.reader(master_data_file, delimiter=','))
print len(data)
print "printing full file"
print data
league_list = ["Arsenal", "Chelsea", "Liverpool", "Man City", "Man United", "Newcastle", "Newcastle", "Norwich","Reading","Southampton", "Stoke", "Sunderland", "Swansea", "Tottenham", "West Brom", "West Ham", "Wigan"]
league_stats = league_list
#for teams in league_list: - come back to this, will do this as a split and append.
#call the next set of functions to skip the data reading stuff
#This is the data reading section, that puts the data into our system
#If we do proceed, then we redo all of the calculations, and read the data file in again, in case of any corrections, etc.
#Column references:
#Home Goals 4
#Away Goals 5
#Full Time Result 6
#Home Shots 10
#Away Shots 11
#Home Shots on Target 12
#Away Shots on Target 13
#Calculates the average for a given team at home, columns are 4 Home Goals, 5 Away Goa
def CalcAverageHome(team, column, data):
total = 0
count = 0
n=0
for row in data:
if data[count][2] == team:
total += int(data[count][column])
n+=1
count += 1
try:
average = float(total) / n
except ZeroDivisionError:
average = 'Not played'
return average
def CalcAverageAway(team, column, data):
total = 0
count = 0
n=0
for row in data:
if data[count][3] == team:
total += int(data[count][column])
n+=1
count += 1
try:
average = float(total) / n
except ZeroDivisionError:
average = 'Not played'
return average
home_team = "Chelsea"
away_team = "Newcastle"
print "Here's the Average number of goals scored Home"
home_goals = CalcAverageHome(home_team, 4, data)
away_goals = CalcAverageAway(home_team, 5, data)
home_conceded = CalcAverageHome(home_team, 5, data)
away_conceded = CalcAverageAway(away_team, 4, data)
adjusted_home = home_goals * away_conceded
adjusted_away = away_goals * home_conceded
print home_team, home_goals, home_conceded, adjusted_home
print away_team, away_goals, away_conceded, adjusted_away
print "starting to try and work the league averages out here."
def poisson_probability(actual, mean):
# naive: math.exp(-mean) * mean**actual / factorial(actual)
# iterative, to keep the components from getting too large or small:
p = math.exp(-mean)
for i in xrange(actual):
p *= mean
p /= i+1
return p
for i in range (10):
print str((100*poisson_probability(i,adjusted_home)))+"%"
league_list = ["Arsenal", "Chelsea", "Liverpool", "Man City", "Man United", "Newcastle", "Newcastle", "Norwich","Reading","Southampton", "Stoke", "Sunderland", "Swansea", "Tottenham", "West Brom", "West Ham", "Wigan"]
# just assign the league list to the stats for now -
# eventually each team entry will become the first column of a new sublist
def LeagueAverages(data,column):
total = 0
n = 0
for row in data :
string = row[column]
if string.isdigit() == True:
total = total + int(row[column])
n += 1
league_average = float(total) / n
return league_average
print "League home goals average is:", LeagueAverages(data, 4)
print "League away goals average is:", LeagueAverages(data, 5)
print "finished that loop..."
league_stats = []
test_team = "Arsenal"
# Function iterates through the league teams and calculates the averages
# and places them in one long list.
for team in league_list:
league_stats.append(team)
league_stats.append(CalcAverageHome(team, 4, data))
print CalcAverageHome(team, 4, data)
league_stats.append(CalcAverageHome(team, 5, data))
CalcAverageHome(team, 5, data)
league_stats.append(CalcAverageHome(team, 7, data))
CalcAverageHome(team, 7, data)
league_stats.append(CalcAverageHome(team, 8, data))
CalcAverageHome(team, 8, data)
league_stats.append(CalcAverageHome(team, 10, data))
CalcAverageHome(team, 10, data)
league_stats.append(CalcAverageHome(team, 11, data))
CalcAverageHome(team, 11, data)
league_stats.append(CalcAverageHome(team, 12, data))
CalcAverageHome(team, 12, data)
league_stats.append(CalcAverageHome(team, 13, data))
CalcAverageHome(team, 13, data)
# This function should chunk the 'file', as when we run the above code,
# we'll end up with one incredibly long list that contains every team on the same line
def chunker(seq, size):
return (seq[pos:pos + size] for pos in xrange(0, len(seq), size))
chunker (league_stats, 9)
final_stats = []
for group in chunker(league_stats, 9):
print repr(group)
final_stats.append(repr(group))
#retrieve a particular value from the final stats array
"""
for row in final_stats:
if data[count][2] == team:
total += int(data[count][column])
n+=1
count += 1
"""
def create_probability_table(hometeam, awayteam, final_stats):
#reads in the home and away sides, calculates their performance adjusted
#ratings and then calculates the likelihood of each team scoring a particular
#number of goals (from 0-10)
#those likelihoods are then combined to provide an 11x11 matrix of probabilities
poisson_array = []
poisson_list_home = []
poisson_list_away = []
goals_home = 0
conceded_home = 0
goals_away = 0
conceded_away = 0
for team in final_stats:
if team == hometeam:
goals_home = team[1]
conceded_home = team [3]
print "home Goals, Home Conceded"
print goals_home, conceded_home
elif team == awayteam:
goals_away = team[2]
conceded_away = team[4]
print "Away Goals, Away Conceded"
print goals_away, conceded_away,
else:
pass
adjusted_goals_home = goals_home * conceded_away
adjusted_goals_away = goals_away * conceded_home
#this section creates the two probability lists for home and away num goals scored
for i in range (10):
poisson_list_home.append = (100*poisson_probability(i,adjusted_goals_home))
poisson_list_away.append = (100*poisson_probability(i,adjusted_goals_away))
print poisson_list_home
print poisson_list_away
for number in poisson_list_home:
for number in poisson_list_away:
probability_table.append(poisson_list_home[number] * poisson_list_away[number])
return probability_table
create_probability_table("Arsenal", "Chelsea", final_stats)
#and this section cross multiplies them into a new list
# for i in range (10):
# print data_frame [0:100] prints to console to provide visual check
master_data_file.close()
当我运行它时，它会抛出一个
line 272, in create_probability_table
adjusted_goals_home = goals_home * conceded_away UnboundLocalError: local variable 'conceded_away' referenced before assignment
错误 - 我不明白为什么！它是在函数开始时定义和分配的。这不是全球性的。
我看过这些问题，他们似乎没有回答这个问题： Local (?) variable referenced before assignment Assigning to variable from parent function: "Local variable referenced before assignment" How is this "referenced before assignment"? UnboundLocalError: local variable 'Core_prices' referenced before assignment
答案 0 :(得分：4)
你拼错了“承认”：
condeded_away = 0
^
此外，您可能希望为final_stats使用不同的数据结构，如字典：
teams = {
'team1': [...],
'team2': [...],
...
}
然后，您可以更快地查找团队的统计数据：
stats = teams['team2']