import pandas as pd import sys import numpy as np import skfuzzy as fuzz import matplotlib.pyplot as plt def fuzzy(goalsV, xGPerMatchV, shotsPerMatchV, onTargetPerMatchV): goals = np.arange(0, 35, 1) xGPerMatch = np.arange(0, 1, 0.01) shotsPerMatch = np.arange(0, 5, 0.01) onTargetPerMatch = np.arange(0, 5, 0.01) ocena = np.arange(0, 101, 1) goals_low = fuzz.trapmf(goals, [0, 0, 10, 15]) goals_md = fuzz.trimf(goals, [10, 15, 20]) goals_hi = fuzz.trapmf(goals, [15, 20, 35, 100]) xGPerMatch_lo = fuzz.trapmf(xGPerMatch, [0, 0, 0.2, 0.5]) xGPerMatch_md = fuzz.trimf(xGPerMatch, [0.2, 0.5, 0.7]) xGPerMatch_hi = fuzz.trapmf(xGPerMatch, [0.5, 0.7, 2, 10]) shotsPerMatch_lo = fuzz.trapmf(shotsPerMatch, [0, 0, 1, 2]) shotsPerMatch_md = fuzz.trapmf(shotsPerMatch, [1, 2, 3, 4]) shotsPerMatch_hi = fuzz.trapmf(shotsPerMatch, [3, 4, 4.5, 10]) onTargetPerMatch_lo = fuzz.trapmf(onTargetPerMatch, [0, 0, 0.5, 1]) onTargetPerMatch_md = fuzz.trimf(onTargetPerMatch, [0.5, 1, 1.5]) onTargetPerMatch_hi = fuzz.trimf(onTargetPerMatch, [1, 1.5, 5]) ocena_lo = fuzz.trapmf(ocena, [0, 0, 40, 50]) ocena_md = fuzz.trapmf(ocena, [40, 50, 60, 80]) ocena_hi = fuzz.trapmf(ocena, [70, 80, 100, 100]) # # fig, (ax0, ax1, ax2, ax3, ax4) = plt.subplots(nrows=5, figsize=(8, 9)) # # ax0.plot(goals, goals_low, 'b', linewidth=1.5, label='Mało') # ax0.plot(goals, goals_md, 'g', linewidth=1.5, label='Średnio') # ax0.plot(goals, goals_hi, 'r', linewidth=1.5, label='Dużo') # ax0.set_title('Liczba bramek') # ax0.legend() # # ax1.plot(xGPerMatch, xGPerMatch_lo, 'b', linewidth=1.5, label='Mało') # ax1.plot(xGPerMatch, xGPerMatch_md, 'g', linewidth=1.5, label='Średno') # ax1.plot(xGPerMatch, xGPerMatch_hi, 'r', linewidth=1.5, label='Dużo') # ax1.set_title('Service quality') # ax1.legend() # # ax2.plot(shotsPerMatch, shotsPerMatch_lo, 'b', linewidth=1.5, label='Mało') # ax2.plot(shotsPerMatch, shotsPerMatch_md, 'g', linewidth=1.5, label='Średnio') # ax2.plot(shotsPerMatch, shotsPerMatch_hi, 'r', linewidth=1.5, label='Dużo') # ax2.set_title('Strzały na mecz') # ax2.legend() # # ax3.plot(onTargetPerMatch, onTargetPerMatch_lo, 'b', linewidth=1.5, label='Mało') # ax3.plot(onTargetPerMatch, onTargetPerMatch_md, 'g', linewidth=1.5, label='Średnio') # ax3.plot(onTargetPerMatch, onTargetPerMatch_hi, 'r', linewidth=1.5, label='Dużo') # ax3.set_title('Strzały w światlo bramki na mecz') # ax3.legend() # # ax4.plot(ocena, ocena_lo, 'b', linewidth=1.5, label='Niska') # ax4.plot(ocena, ocena_md, 'g', linewidth=1.5, label='Średnia') # ax4.plot(ocena, ocena_hi, 'r', linewidth=1.5, label='Wysoka') # ax4.set_title('Ocena') # ax4.legend() # # # Turn off top/right axes # for ax in (ax0, ax1, ax2, ax3, ax4): # ax.spines['top'].set_visible(False) # ax.spines['right'].set_visible(False) # ax.get_xaxis().tick_bottom() # ax.get_yaxis().tick_left() # # plt.tight_layout() goals_value = goalsV xGPerMatch_value = xGPerMatchV shotsPerMatch_value = shotsPerMatchV onTargetPerMatch_value = onTargetPerMatchV goals_level_lo = fuzz.interp_membership(goals, goals_low, goals_value) goals_level_md = fuzz.interp_membership(goals, goals_md, goals_value) goals_level_hi = fuzz.interp_membership(goals, goals_hi, goals_value) xGPerMatch_level_lo = fuzz.interp_membership(xGPerMatch, xGPerMatch_lo, xGPerMatch_value) xGPerMatch_level_md = fuzz.interp_membership(xGPerMatch, xGPerMatch_md, xGPerMatch_value) xGPerMatch_level_hi = fuzz.interp_membership(xGPerMatch, xGPerMatch_hi, xGPerMatch_value) shotsPerMatch_level_lo = fuzz.interp_membership(shotsPerMatch, shotsPerMatch_lo, shotsPerMatch_value) shotsPerMatch_level_md = fuzz.interp_membership(shotsPerMatch, shotsPerMatch_md, shotsPerMatch_value) shotsPerMatch_level_hi = fuzz.interp_membership(shotsPerMatch, shotsPerMatch_hi, shotsPerMatch_value) onTargetPerMatch_level_lo = fuzz.interp_membership(onTargetPerMatch, onTargetPerMatch_lo, onTargetPerMatch_value) onTargetPerMatch_level_md = fuzz.interp_membership(onTargetPerMatch, onTargetPerMatch_md, onTargetPerMatch_value) onTargetPerMatch_level_hi = fuzz.interp_membership(onTargetPerMatch, onTargetPerMatch_hi, onTargetPerMatch_value) active_rule1 = np.fmax(goals_level_hi, xGPerMatch_level_hi) active_rule2 = np.fmax(active_rule1, onTargetPerMatch_level_hi) ocena_activation_hi = np.fmin(active_rule2, ocena_hi) # removed entirely to 0 active_rule3 = np.fmax(np.fmin(goals_level_lo, xGPerMatch_level_hi), np.fmin(goals_level_lo, shotsPerMatch_level_hi)) active_rule4=np.fmax(np.fmin(goals_level_md, xGPerMatch_level_md), np.fmin(goals_level_md, shotsPerMatch_level_md)) active_rule5=np.fmax(active_rule3,active_rule4) ocena_activation_md = np.fmin(active_rule5, ocena_md) ocena_activation_lo = np.fmin(goals_level_lo, ocena_lo) ocena0 = np.zeros_like(ocena) # # fig, ax0 = plt.subplots(figsize=(8, 3)) # # ax0.fill_between(ocena, ocena0, ocena_activation_lo, facecolor='b', alpha=0.7) # ax0.plot(ocena, ocena_lo, 'b', linewidth=0.5, linestyle='--', ) # ax0.fill_between(ocena, ocena0, ocena_activation_md, facecolor='g', alpha=0.7) # ax0.plot(ocena, ocena_md, 'g', linewidth=0.5, linestyle='--') # ax0.fill_between(ocena, ocena0, ocena_activation_hi, facecolor='r', alpha=0.7) # ax0.plot(ocena, ocena_hi, 'r', linewidth=0.5, linestyle='--') # ax0.set_title('Output membership activity') # # # Turn off top/right axes # for ax in (ax0,): # ax.spines['top'].set_visible(False) # ax.spines['right'].set_visible(False) # ax.get_xaxis().tick_bottom() # ax.get_yaxis().tick_left() # # plt.tight_layout() aggregated = np.fmax(ocena_activation_lo, np.fmax(ocena_activation_md, ocena_activation_hi)) # Calculate defuzzified result ocena_output = fuzz.defuzz(ocena, aggregated, 'centroid') ocena_activation = fuzz.interp_membership(ocena, aggregated, ocena_output) # for plot # # Visualize this # fig, ax0 = plt.subplots(figsize=(8, 3)) # # ax0.plot(ocena, ocena_lo, 'b', linewidth=0.5, linestyle='--', ) # ax0.plot(ocena, ocena_md, 'g', linewidth=0.5, linestyle='--') # ax0.plot(ocena, ocena_hi, 'r', linewidth=0.5, linestyle='--') # ax0.fill_between(ocena, ocena0, aggregated, facecolor='Orange', alpha=0.7) # ax0.plot([ocena_output, ocena_output], [0, ocena_activation], 'k', linewidth=1.5, alpha=0.9) # ax0.set_title('Aggregated membership and result (line)') # # # Turn off top/right axes # for ax in (ax0,): # ax.spines['top'].set_visible(False) # ax.spines['right'].set_visible(False) # ax.get_xaxis().tick_bottom() # ax.get_yaxis().tick_left() # # plt.tight_layout() return ocena_output def main(): data = pd.read_csv("resources/Data.csv") # league = sys.argv[1] # year = sys.argv[2] # filtered_df = data.loc[data['Year'] == year] filtered_df = data.loc[data['League'] == "La Liga"] #print(filtered_df) results = [] for item in filtered_df.iterrows(): print(item) goals=item[1]["Goals"] xGPerMatch=item[1]["xG Per Avg Match"] shotsPerMatch=item[1]["Shots Per Avg Match"] onTargetPerMatch=item[1]["On Target Per Avg Match"] rate = fuzzy(goals,xGPerMatch,shotsPerMatch,onTargetPerMatch) results.append(rate) filtered_df['Rate'] = results filtered_df.to_csv('resources/out.csv') if __name__ == '__main__': main() #goals srednio #xG malo/srednio #shotspM srednio #onTarget malo/srednio