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Piotr Kopycki 2021-12-08 19:43:46 +01:00
parent cd6c8c2ea5
commit d48864172b
3 changed files with 226 additions and 4 deletions
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3
.gitignore vendored
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@ -112,6 +112,7 @@ venv/
ENV/
env.bak/
venv.bak/
fcl-venv/
# Spyder project settings
.spyderproject
@ -137,8 +138,6 @@ dmypy.json
# Cython debug symbols
cython_debug/
#Virtual env
fcl-venv/
#Other
.idea/

4
leagues.csv
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@ -1,4 +1,4 @@
league;country;clubs;goalsPerMatch;totalMarketValueInMln;avgMarketValueInMln;teamsInChampionsLeague;teamsInEuropaLeague;teamsInConferenceLeague;famousPlayers
league;country;clubs;goalsPerMatch;avgMarketValueInMln;totalMarketValueInMln;teamsInChampionsLeague;teamsInEuropaLeague;teamsInConferenceLeague;famousPlayers
Premier League;England;20;2.78;453.95;9080.0;4;2;1;35
LaLiga;Spain;20;2.45;246.89;4940.0;4;2;1;21
Serie A;Italy;20;3.05;245.69;4910.0;4;2;1;17
@ -52,4 +52,4 @@ Gibraltar National League;Gibraltar;11;3.68;1.01;11.11;1;0;3;0
Pepsi Max deild;Iceland;12;2.83;1.75;20.98;1;0;3;0
1. CFL;Montenegro;10;2.46;2.69;26.90;1;0;3;0
Primera Divisió;Andorra;8;2.80;1.38;11.05;1;0;2;0
Camp. Sammarinese;San Marino;15;2.67;0.333;4.99;1;0;2;0
Camp. Sammarinese;San Marino;15;2.67;0.33;4.99;1;0;2;0
1 league country clubs goalsPerMatch avgMarketValueInMln totalMarketValueInMln teamsInChampionsLeague teamsInEuropaLeague teamsInConferenceLeague famousPlayers
2 Premier League England 20 2.78 9080.0 453.95 453.95 9080.0 4 2 1 35
3 LaLiga Spain 20 2.45 4940.0 246.89 246.89 4940.0 4 2 1 21
4 Serie A Italy 20 3.05 4910.0 245.69 245.69 4910.0 4 2 1 17
52 Pepsi Max deild Iceland 12 2.83 20.98 1.75 1.75 20.98 1 0 3 0
53 1. CFL Montenegro 10 2.46 26.90 2.69 2.69 26.90 1 0 3 0
54 Primera Divisió Andorra 8 2.80 11.05 1.38 1.38 11.05 1 0 2 0
55 Camp. Sammarinese San Marino 15 2.67 4.99 0.33 0.333 4.99 1 0 2 0

223
main.py Normal file
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@ -0,0 +1,223 @@
import numpy as np
import skfuzzy as fuzz
import matplotlib.pyplot as plt
# https://pythonhosted.org/scikit-fuzzy/auto_examples/plot_tipping_problem.html
# Variables for universes
unv_clubs = unv_goals = unv_avgValue = unv_totValue = unv_players = unv_teamsChL = unv_teamsEuL = unv_teamsCfL = unv_score = None
# Variables for fuzzy membership functions
clubs_low = clubs_mid = clubs_hig = None
goals_low = goals_mid = goals_hig = None
avgValue_low = avgValue_mid = avgValue_hig = None
totValue_low = totValue_mid = totValue_hig = None
players_low = players_mid = players_hig = None
teamsChL_low = teamsChL_mid = teamsChL_hig = None
teamsEuL_low = teamsEuL_mid = teamsEuL_hig = None
teamsCfL_low = teamsCfL_mid = teamsCfL_hig = None
score_low = score_mid = score_hig = None
# Activations of fuzzy membership functions
clubs_low_level = clubs_mid_level = clubs_hig_level = None
goals_low_level = goals_mid_level = goals_hig_level = None
avgValue_low_level = avgValue_mid_level = avgValue_hig_level = None
totValue_low_level = totValue_mid_level = totValue_hig_level = None
players_low_level = players_mid_level = players_hig_level = None
teamsChL_low_level = teamsChL_mid_level = teamsChL_hig_level = None
teamsEuL_low_level = teamsEuL_mid_level = teamsEuL_hig_level = None
teamsCfL_low_level = teamsCfL_mid_level = teamsCfL_hig_level = None
def initFuzzyMembershipFunctions():
global unv_clubs, unv_goals, unv_avgValue, unv_totValue, unv_players, unv_teamsChL, unv_teamsEuL, unv_teamsCfL, unv_score
global clubs_low, clubs_mid, clubs_hig
global goals_low, goals_mid, goals_hig
global avgValue_low, avgValue_mid, avgValue_hig
global totValue_low, totValue_mid, totValue_hig
global players_low, players_mid, players_hig
global teamsChL_low, teamsChL_mid, teamsChL_hig
global teamsEuL_low, teamsEuL_mid, teamsEuL_hig
global teamsCfL_low, teamsCfL_mid, teamsCfL_hig
global score_low, score_mid, score_hig
# Universes for variables
unv_clubs = np.arange(2, 31, 1)
unv_goals = np.arange(2, 4, 0.01)
unv_avgValue = np.arange(0.01, 500.0, 0.01)
unv_totValue = np.arange(0.01, 10000.0, 0.01)
unv_players = np.arange(0, 100, 1)
unv_teamsChL = np.arange(0, 10, 1)
unv_teamsEuL = np.arange(0, 10, 1)
unv_teamsCfL = np.arange(0, 10, 1)
# Result score universum
unv_score = np.arange(0, 100, 1)
# Generate fuzzy membership functions
# trimf - triangular function
# trapmf - trapezoidal function
clubs_low = fuzz.trapmf(unv_clubs, [2, 2, 10, 14])
clubs_mid = fuzz.trapmf(unv_clubs, [10, 12, 16, 18])
clubs_hig = fuzz.trapmf(unv_clubs, [14, 16, 30, 30])
goals_low = fuzz.trapmf(unv_goals, [2.0, 2.0, 2.5, 3.0])
goals_mid = fuzz.trapmf(unv_goals, [2.0, 2.5, 3.0, 3.5])
goals_hig = fuzz.trapmf(unv_goals, [3.0, 3.5, 4.0, 4.0])
avgValue_low = fuzz.trapmf(unv_avgValue, [0.01, 0.01, 100.0, 150.0])
avgValue_mid = fuzz.trapmf(unv_avgValue, [100.0, 150.0, 350.0, 400.0])
avgValue_hig = fuzz.trapmf(unv_avgValue, [350.0, 400.0, 500.0, 500.0])
totValue_low = fuzz.trapmf(unv_totValue, [0.01, 0.01, 1000.0, 2000.0])
totValue_mid = fuzz.trapmf(unv_totValue, [1000.0, 2000.0, 7000.0, 8000.0])
totValue_hig = fuzz.trapmf(unv_totValue, [7000.0, 8000.0, 10000.0, 10000.0])
players_low = fuzz.trapmf(unv_players, [0, 0, 5, 10])
players_mid = fuzz.trapmf(unv_players, [5, 10, 15, 20])
players_hig = fuzz.trapmf(unv_players, [15, 20, 100, 100])
teamsChL_low = fuzz.trapmf(unv_teamsChL, [0, 0, 1, 2])
teamsChL_mid = fuzz.trimf(unv_teamsChL, [1, 2, 3])
teamsChL_hig = fuzz.trapmf(unv_teamsChL, [2, 3, 10, 10])
teamsEuL_low = fuzz.trapmf(unv_teamsEuL, [0, 0, 1, 2])
teamsEuL_mid = fuzz.trimf(unv_teamsEuL, [1, 2, 3])
teamsEuL_hig = fuzz.trapmf(unv_teamsEuL, [2, 3, 10, 10])
teamsCfL_low = fuzz.trapmf(unv_teamsCfL, [0, 0, 1, 2])
teamsCfL_mid = fuzz.trimf(unv_teamsCfL, [1, 2, 3])
teamsCfL_hig = fuzz.trapmf(unv_teamsCfL, [2, 3, 10, 10])
score_low = fuzz.trapmf(unv_score, [0, 0, 20, 40])
score_mid = fuzz.trapmf(unv_score, [20, 40, 60, 80])
score_hig = fuzz.trapmf(unv_score, [60, 80, 100, 100])
def activateFuzzyMembershipFunctions(values):
global unv_clubs, unv_goals, unv_avgValue, unv_totValue, unv_players, unv_teamsChL, unv_teamsEuL, unv_teamsCfL
global clubs_low, clubs_mid, clubs_hig
global goals_low, goals_mid, goals_hig
global avgValue_low, avgValue_mid, avgValue_hig
global totValue_low, totValue_mid, totValue_hig
global players_low, players_mid, players_hig
global teamsChL_low, teamsChL_mid, teamsChL_hig
global teamsEuL_low, teamsEuL_mid, teamsEuL_hig
global teamsCfL_low, teamsCfL_mid, teamsCfL_hig
global clubs_low_level, clubs_mid_level, clubs_hig_level
global goals_low_level, goals_mid_level, goals_hig_level
global avgValue_low_level, avgValue_mid_level, avgValue_hig_level
global totValue_low_level, totValue_mid_level, totValue_hig_level
global players_low_level, players_mid_level, players_hig_level
global teamsChL_low_level, teamsChL_mid_level, teamsChL_hig_level
global teamsEuL_low_level, teamsEuL_mid_level, teamsEuL_hig_level
global teamsCfL_low_level, teamsCfL_mid_level, teamsCfL_hig_level
# Activation of fuzzy membership functions at given values.
clubs_low_level = fuzz.interp_membership(unv_clubs, clubs_low, values['clubs'])
clubs_mid_level = fuzz.interp_membership(unv_clubs, clubs_mid, values['clubs'])
clubs_hig_level = fuzz.interp_membership(unv_clubs, clubs_hig, values['clubs'])
goals_low_level = fuzz.interp_membership(unv_goals, goals_low, values['goals'])
goals_mid_level = fuzz.interp_membership(unv_goals, goals_mid, values['goals'])
goals_hig_level = fuzz.interp_membership(unv_goals, goals_hig, values['goals'])
avgValue_low_level = fuzz.interp_membership(unv_avgValue, avgValue_low, values['avgValue'])
avgValue_mid_level = fuzz.interp_membership(unv_avgValue, avgValue_mid, values['avgValue'])
avgValue_hig_level = fuzz.interp_membership(unv_avgValue, avgValue_hig, values['avgValue'])
totValue_low_level = fuzz.interp_membership(unv_totValue, totValue_low, values['totValue'])
totValue_mid_level = fuzz.interp_membership(unv_totValue, totValue_mid, values['totValue'])
totValue_hig_level = fuzz.interp_membership(unv_totValue, totValue_hig, values['totValue'])
players_low_level = fuzz.interp_membership(unv_players, players_low, values['players'])
players_mid_level = fuzz.interp_membership(unv_players, players_mid, values['players'])
players_hig_level = fuzz.interp_membership(unv_players, players_hig, values['players'])
teamsChL_low_level = fuzz.interp_membership(unv_teamsChL, teamsChL_low, values['teamsChL'])
teamsChL_mid_level = fuzz.interp_membership(unv_teamsChL, teamsChL_mid, values['teamsChL'])
teamsChL_hig_level = fuzz.interp_membership(unv_teamsChL, teamsChL_hig, values['teamsChL'])
teamsEuL_low_level = fuzz.interp_membership(unv_teamsEuL, teamsEuL_low, values['teamsEuL'])
teamsEuL_mid_level = fuzz.interp_membership(unv_teamsEuL, teamsEuL_mid, values['teamsEuL'])
teamsEuL_hig_level = fuzz.interp_membership(unv_teamsEuL, teamsEuL_hig, values['teamsEuL'])
teamsCfL_low_level = fuzz.interp_membership(unv_teamsCfL, teamsCfL_low, values['teamsCfL'])
teamsCfL_mid_level = fuzz.interp_membership(unv_teamsCfL, teamsCfL_mid, values['teamsCfL'])
teamsCfL_hig_level = fuzz.interp_membership(unv_teamsCfL, teamsCfL_hig, values['teamsCfL'])
def defineRules():
global clubs_low_level, clubs_mid_level, clubs_hig_level
global goals_low_level, goals_mid_level, goals_hig_level
global avgValue_low_level, avgValue_mid_level, avgValue_hig_level
global totValue_low_level, totValue_mid_level, totValue_hig_level
global players_low_level, players_mid_level, players_hig_level
global teamsChL_low_level, teamsChL_mid_level, teamsChL_hig_level
global teamsEuL_low_level, teamsEuL_mid_level, teamsEuL_hig_level
global teamsCfL_low_level, teamsCfL_mid_level, teamsCfL_hig_level
global score_low, score_mid, score_hig, unv_score
# OR
active_rule1 = np.fmax(clubs_low_level,
np.fmax(goals_low_level,
np.fmax(avgValue_low_level,
np.fmax(totValue_low_level,
np.fmax(players_low_level,
np.fmax(teamsChL_low_level,
np.fmax(teamsEuL_low_level, teamsCfL_low_level)))))))
active_rule2 = np.fmax(clubs_mid_level,
np.fmax(goals_mid_level,
np.fmax(avgValue_mid_level,
np.fmax(totValue_mid_level,
np.fmax(players_mid_level,
np.fmax(teamsChL_mid_level,
np.fmax(teamsEuL_mid_level, teamsCfL_mid_level)))))))
active_rule3 = np.fmax(clubs_hig_level,
np.fmax(goals_hig_level,
np.fmax(avgValue_hig_level,
np.fmax(totValue_hig_level,
np.fmax(players_hig_level,
np.fmax(teamsChL_hig_level,
np.fmax(teamsEuL_hig_level, teamsCfL_hig_level)))))))
score_activation_low = np.fmin(active_rule1, score_low)
score_activation_mid = np.fmin(active_rule2, score_mid)
score_activation_hig = np.fmin(active_rule3, score_hig)
aggregated_rules = np.fmax(score_activation_low, np.fmax(score_activation_mid, score_activation_hig))
# active_rule1 = np.fmax(qual_level_lo, serv_level_lo)
# tip_activation_lo = np.fmin(active_rule1, tip_lo) # removed entirely to 0
#
#
# tip_activation_md = np.fmin(serv_level_md, tip_md)
#
# active_rule3 = np.fmax(qual_level_hi, serv_level_hi)
# tip_activation_hi = np.fmin(active_rule3, tip_hi)
#
# aggregated_rules = np.fmax(tip_activation_lo, np.fmax(tip_activation_md, tip_activation_hi))
score = fuzz.defuzz(unv_score, aggregated_rules, 'centroid')
score_activation = fuzz.interp_membership(unv_score, aggregated_rules, score) # for plot
return score_activation
if __name__ == "__main__":
values = {}
values['clubs'] = 18
values['goals'] = 2.76
values['avgValue'] = 14.16
values['totValue'] = 254.90
values['players'] = 0
values['teamsChL'] = 1
values['teamsEuL'] = 0
values['teamsCfL'] = 3
initFuzzyMembershipFunctions()
activateFuzzyMembershipFunctions(values)
result = defineRules()
print(f"Ekstraklasa score is: {result}")
#plt.show()