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
import pandas as pd
from math import sqrt
import numpy as np
import math
from sklearn.preprocessing import LabelEncoder
# 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):
@ -100,7 +102,7 @@ def xgboost_predict_proba_v2(shooter,goalkeeper,teamMatesList,opponentsList, min
'shot_open_goal','shot_follows_dribble', 'shot_redirect',
'x1', 'y1','number_of_players_opponents',
'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_4','x_player_opponent_5', 'x_player_opponent_6',
'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
# TeamMate goalkeppe
x_player_teammate_Goalkeeper = None
y_player_teammate_Goalkeeper = None
x_player_teammate_Goalkeeper = np.nan
y_player_teammate_Goalkeeper = np.nan
#Reszta Zawodnikow
print("AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA")
@ -158,7 +160,7 @@ def xgboost_predict_proba_v2(shooter,goalkeeper,teamMatesList,opponentsList, min
shot_open_goal,shot_follows_dribble, shot_redirect,
shooter[0], shooter[1],number_of_players_opponents,
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[3][0], opponentsList[4][0], opponentsList[5][0],
opponentsList[6][0], opponentsList[7][0], teamMatesList[8][0],
@ -177,6 +179,10 @@ def xgboost_predict_proba_v2(shooter,goalkeeper,teamMatesList,opponentsList, min
teamMatesList[8][1], teamMatesList[9][1],
x_player_teammate_Goalkeeper, y_player_teammate_Goalkeeper,
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)
@ -213,5 +219,5 @@ def zmienWMaciez(lista):
maciez.append(player)
if(len(maciez) < 10):
for i in range(len(maciez),11,1):
maciez.append([None,None])
maciez.append([np.nan,np.nan])
return maciez

2
app/src/flask-server/server.py
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@ -50,7 +50,7 @@ def get_model():
print("bramkarz: " + str(goalkepper) )
response = xgboost_predict_proba_v2(shooter = shooter,
opponentsList = opponentsList, teamMatesList = teamMatesList ,minute = 20, position_name = position_name, shot_body_part_name = body_part, shot_technique_name = technique,
opponentsList = opponentsList, teamMatesList = teamMatesList, minute = 20, position_name = position_name, shot_body_part_name = body_part, shot_technique_name = technique,
shot_type_name = acionType, shot_first_time = False,
shot_aerial_won = False, shot_deflected = False, shot_open_goal = False,
shot_follows_dribble = False, shot_redirect = False, shot_kick_off = False, goalkeeper= goalkepper