Temp

preprocessing/sports/event_data/soccer/soccer_event_class.py

@@ -92,15 +92,17 @@ def load_data_single_file(self):
             if self.soccertrackv2 == True:
                 df=soccer_load_data.load_soccertrack(self.event_path, self.tracking_path, self.meta_data, self.verbose)
             elif self.soccertrackv2 == False:
-                df=soccer_load_data.load_bepro(self.event_path, self.tracking_path, self.meta_data, self.verbose)
+                df=soccer_load_data.load_bepro(self.event_path, self.tracking_path, self.meta_data, self.match_id, self.verbose)
         else:
             raise ValueError('Data provider not supported or not found')
         return df
 
     def load_data(self):
         print(f'Loading data from {self.data_provider}')
         #check if the event path is a single file or a directory
-        if ((self.event_path is not None and os.path.isfile(self.event_path)) and self.data_provider != 'statsbomb') or \
+        if self.data_provider == 'bepro' and self.soccertrackv2 == False:
+            df = self.load_data_single_file()
+        elif ((self.event_path is not None and os.path.isfile(self.event_path)) and self.data_provider != 'statsbomb') or \
            (self.data_provider == 'statsbomb' and self.statsbomb_match_id is None and os.path.isfile(self.event_path)) or \
             (self.data_provider == 'statsbomb_skillcorner' and self.statsbomb_match_id is not None):
             df = self.load_data_single_file()
@@ -585,12 +587,31 @@ def process_single_match(match_id):
     # df_datastadium.to_csv(os.getcwd()+"/test/sports/event_data/data/datastadium/preprocess_UIED_class_multi.csv",index=False)
 
     #test soccertrack
-    soccer_track_event_path="/data_pool_1/soccertrackv2/2024-03-18/Event/event.csv"
-    soccer_track_tracking_path="/data_pool_1/soccertrackv2/2024-03-18/Tracking/tracking.xml"
-    soccer_track_meta_path="/data_pool_1/soccertrackv2/2024-03-18/Tracking/meta.xml"
-    df_soccertrack=Soccer_event_data('bepro',soccer_track_event_path,
-                                     st_track_path = soccer_track_tracking_path,
-                                     st_meta_path = soccer_track_meta_path,
-                                     verbose = True).load_data()
-    df_soccertrack.to_csv(os.getcwd()+"/test/sports/event_data/data/soccertrack/test_load_soccer_event_class.csv",index=False)
+    # soccer_track_event_path="/data_pool_1/soccertrackv2/2024-03-18/Event/event.csv"
+    # soccer_track_tracking_path="/data_pool_1/soccertrackv2/2024-03-18/Tracking/tracking.xml"
+    # soccer_track_meta_path="/data_pool_1/soccertrackv2/2024-03-18/Tracking/meta.xml"
+    # df_soccertrack=Soccer_event_data('bepro',soccer_track_event_path,
+    #                                  st_track_path = soccer_track_tracking_path,
+    #                                  st_meta_path = soccer_track_meta_path,
+    #                                  verbose = True).load_data()
+    # df_soccertrack.to_csv(os.getcwd()+"/test/sports/event_data/data/soccertrack/test_load_soccer_event_class.csv",index=False)
+
+    #test bepro
+    data_dir=["/data_pool_1/soccertrackv2/117093/2023-11-25_筑波大学 vs 筑波大学 - B1_1st Half.json",
+                            "/data_pool_1/soccertrackv2/117093/2023-11-25_筑波大学 vs 筑波大学 - B1_2nd Half.json"]
+    tracking_path="/data_pool_1/soccertrackv2/117093/tracker_box_data_125091.xml"
+    meta_data="/data_pool_1/soccertrackv2/117093/tracker_box_metadata_125091.xml"
+
+    df_bepro=Soccer_event_data(data_provider='bepro',
+                                            event_path=data_dir,
+                                            tracking_path=tracking_path,
+                                            meta_data=meta_data,
+                                            preprocess_method="UIED",
+                                            max_workers=1,
+                                            match_id=117093,
+                                            verbose=True).preprocessing()
+
+    #save
+    df_bepro.to_csv(os.getcwd()+"/test/sports/event_data/data/bepro/test_load_soccer_event_class.csv",index=False)
+
     print("-----------done-----------")

preprocessing/sports/event_data/soccer/soccer_load_data.py

@@ -7,6 +7,7 @@
 from statsbombpy import sb
 from tqdm import tqdm
 from datetime import datetime
+from typing import Union
 import os
 import pdb
 
@@ -1537,7 +1538,7 @@ def get_tracking_features(event_df, tracking_data, meta_data, verbose=True):
 
     return event_df
 
-def load_bepro(event_path: str, tracking_path: str, meta_path: str, verbose: bool = False) -> pd.DataFrame:
+def load_bepro(event_path: str, tracking_path: str, meta_path: str, match_id:Union[int, str], verbose: bool = False) -> pd.DataFrame:
     """
     Loads and processes event and tracking data from soccer match recordings.
 
@@ -1697,7 +1698,10 @@ def read_tracking_data(file_path):
 
         #load the event data
 
-    def get_additional_features(event_df, meta_data):
+    def get_additional_features(event_df, meta_data, match_id=None):
+
+        event_df['match_id'] = match_id
+
         #player info: id name nameEN shirtNumber position
         # create features period, seconds, event_type, event_type_2, outcome, home_team, x_unscaled, y_unscaled,
         period_dict = {1:"FIRST_HALF",2:"SECOND_HALF",3:"EXTRA_FIRST_HALF",4:"EXTRA_SECOND_HALF"}
@@ -1902,7 +1906,7 @@ def get_tracking_features(event_df, tracking_data, meta_data, verbose=True):
     # Load the meta data
     meta_data = read_meta_data(meta_path)
     # Get additional features
-    event_df = get_additional_features(event_df, meta_data)
+    event_df = get_additional_features(event_df, meta_data, match_id=match_id)
     # Get tracking features
     event_df = get_tracking_features(event_df, tracking_data, meta_data, verbose=verbose)
 

preprocessing/sports/event_data/soccer/soccer_processing.py

@@ -2068,7 +2068,6 @@ def UIED_bepro(data):
             else:
                 poss_id += 1
                 poss_id_list.append(poss_id)
-        poss_id+=1
     df["poss_id"] = poss_id_list
 
     new_df = []
@@ -2166,7 +2165,7 @@ def UIED_bepro(data):
     tracking_col_home = [col for col in tracking_col_home if col != "home_team"]
     tracking_col_away = df.columns[df.columns.str.startswith("away_")].tolist()
 
-    df = df[['poss_id', 'team', 'home_team', 'action', 'success', 'goal', 'home_score', 
+    df = df[['match_id', 'poss_id', 'team', 'home_team', 'action', 'success', 'goal', 'home_score', 
              'away_score', 'goal_diff', 'Period', 'Minute', 'Second', 'seconds', "delta_T", 'start_x', 
              'start_y', 'deltaX', 'deltaY', 'distance', 'dist2goal', 'angle2goal']+tracking_col_home+tracking_col_away]
 

pyproject.toml

@@ -6,7 +6,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "openstarlab_preprocessing"
-version = "0.1.51"
+version = "0.1.53"
 description = "openstarlab preprocessing package"
 readme = "README.md"
 requires-python = ">=3.8"