s478993/fantastyczne_gole
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some work

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LukaszChrostowski 2024-01-08 22:32:55 +01:00
parent 4cbed48308
commit 0b3e58f05e
4 changed files with 12 additions and 6 deletions
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.DS_Store vendored
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app/src/flask-server/modele/__pycache__/modele.cpython-39.pyc
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app/src/flask-server/modele/modele.py
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@ -1,7 +1,9 @@
from joblib import load from joblib import load
import pandas as pd import pandas as pd
from math import sqrt from math import sqrt
import numpy as np
import math import math
from sklearn.preprocessing import LabelEncoder
# Funkcja zwraca prawdopodobieństwo zdobycia gola # Funkcja zwraca prawdopodobieństwo zdobycia gola
def LogisticRegression_predict_proba(position_x, position_y, distance_to_goalM, angle, match_minute, Number_Intervening_Opponents, Number_Intervening_Teammates, isFoot, isHead): def LogisticRegression_predict_proba(position_x, position_y, distance_to_goalM, angle, match_minute, Number_Intervening_Opponents, Number_Intervening_Teammates, isFoot, isHead):
@ -100,7 +102,7 @@ def xgboost_predict_proba_v2(shooter,goalkeeper,teamMatesList,opponentsList, min
'shot_open_goal','shot_follows_dribble', 'shot_redirect', 'shot_open_goal','shot_follows_dribble', 'shot_redirect',
'x1', 'y1','number_of_players_opponents', 'x1', 'y1','number_of_players_opponents',
'number_of_players_teammates','angle', 'distance', 'number_of_players_teammates','angle', 'distance',
'x_player_opponent_Goalkeeper', 'x_player_opponent_Goalkeeper', 'x_player_opponent_8',
'x_player_opponent_1', 'x_player_opponent_2','x_player_opponent_3', 'x_player_opponent_1', 'x_player_opponent_2','x_player_opponent_3',
'x_player_opponent_4','x_player_opponent_5', 'x_player_opponent_6', 'x_player_opponent_4','x_player_opponent_5', 'x_player_opponent_6',
'x_player_teammate_2','x_player_opponent_9', 'x_player_opponent_10', 'x_player_teammate_2','x_player_opponent_9', 'x_player_opponent_10',
@ -146,8 +148,8 @@ def xgboost_predict_proba_v2(shooter,goalkeeper,teamMatesList,opponentsList, min
shot_one_on_one = True if number_of_players_opponents == 1 else False shot_one_on_one = True if number_of_players_opponents == 1 else False
# TeamMate goalkeppe # TeamMate goalkeppe
x_player_teammate_Goalkeeper = None x_player_teammate_Goalkeeper = np.nan
y_player_teammate_Goalkeeper = None y_player_teammate_Goalkeeper = np.nan
#Reszta Zawodnikow #Reszta Zawodnikow
print("AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA") print("AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA")
@ -158,7 +160,7 @@ def xgboost_predict_proba_v2(shooter,goalkeeper,teamMatesList,opponentsList, min
shot_open_goal,shot_follows_dribble, shot_redirect, shot_open_goal,shot_follows_dribble, shot_redirect,
shooter[0], shooter[1],number_of_players_opponents, shooter[0], shooter[1],number_of_players_opponents,
number_of_players_teammates,angle, distance, number_of_players_teammates,angle, distance,
x_player_opponent_Goalkeeper, x_player_opponent_Goalkeeper, opponentsList[8][0],
opponentsList[0][0], opponentsList[1][0], opponentsList[2][0], opponentsList[0][0], opponentsList[1][0], opponentsList[2][0],
opponentsList[3][0], opponentsList[4][0], opponentsList[5][0], opponentsList[3][0], opponentsList[4][0], opponentsList[5][0],
opponentsList[6][0], opponentsList[7][0], teamMatesList[8][0], opponentsList[6][0], opponentsList[7][0], teamMatesList[8][0],
@ -178,6 +180,10 @@ def xgboost_predict_proba_v2(shooter,goalkeeper,teamMatesList,opponentsList, min
x_player_teammate_Goalkeeper, y_player_teammate_Goalkeeper, x_player_teammate_Goalkeeper, y_player_teammate_Goalkeeper,
shot_kick_off] shot_kick_off]
categorical_columns = ['position_name', 'shot_technique_name', 'shot_type_name', 'number_of_players_opponents', 'number_of_players_teammates', 'shot_body_part_name'] # list all your object columns here
# X_new = pd.get_dummies(X_new, columns=categorical_columns)
X_new[categorical_columns] = X_new[categorical_columns].astype('category')
return model.predict_proba(X_new)[0][1].round(2) return model.predict_proba(X_new)[0][1].round(2)
@ -213,5 +219,5 @@ def zmienWMaciez(lista):
maciez.append(player) maciez.append(player)
if(len(maciez) < 10): if(len(maciez) < 10):
for i in range(len(maciez),11,1): for i in range(len(maciez),11,1):
maciez.append([None,None]) maciez.append([np.nan,np.nan])
return maciez return maciez