From e88d6eb6910016f42a746aab22a4d6c6dd216d45 Mon Sep 17 00:00:00 2001
From: shunsuke-iwashita <iwashita.shunsuke@g.sp.m.is.nagoya-u.ac.jp>
Date: Wed, 1 Apr 2026 23:55:50 +0900
Subject: [PATCH 1/2] Adds play initiation detection to tracking data

Introduces a method for detecting and extracting play initiations in tracking datasets using configurable motion thresholds. Enhances processing by automating play segmentation, and supports saving detected plays for further analysis. Aims to streamline analysis of ultimate sports tracking data.
---
 .../ultimate/ultimate_space_class.py          | 81 +++++++++++++++++++
 1 file changed, 81 insertions(+)

diff --git a/preprocessing/sports/space_data/ultimate/ultimate_space_class.py b/preprocessing/sports/space_data/ultimate/ultimate_space_class.py
index fcd7a8c..5f8b031 100644
--- a/preprocessing/sports/space_data/ultimate/ultimate_space_class.py
+++ b/preprocessing/sports/space_data/ultimate/ultimate_space_class.py
@@ -95,3 +95,84 @@ def preprocessing(self):
                 )
 
         return event_data_dict, home_tracking_dict, away_tracking_dict
+
+    def detect_initiations(
+        self,
+        velocity_threshold=3.0,
+        acceleration_threshold=4.0,
+        distance_threshold=5.0,
+        player_threshold=2,
+    ):
+        """
+        Detect play initiations in tracking data.
+
+        This method processes raw tracking data (2_1.csv or 1_1_1.csv format),
+        calculates required motion features, detects play initiations, and optionally
+        extracts individual play segments.
+
+        Args:
+            velocity_threshold (float): Threshold for velocity (default: 3.0).
+            acceleration_threshold (float): Threshold for acceleration (default: 4.0).
+            distance_threshold (float): Threshold for distance (default: 5.0).
+            player_threshold (int): Threshold for player proximity (default: 2).
+            output_detected_dir (str): Optional directory to save detected play data.
+            output_extracted_dir (str): Optional directory to save extracted play segments.
+
+        Returns:
+            tuple: (detected_plays_dict, extracted_plays_dict)
+                - detected_plays_dict: Dictionary mapping match_id to detected play DataFrame
+                - extracted_plays_dict: Dictionary mapping (match_id, offense_id, play_num) to extracted play DataFrame
+        """
+        tracking_files = self.get_files()
+        if self.testing_mode:
+            tracking_files = tracking_files[:2]
+            print("Running in testing mode. Limited files will be processed.")
+
+        from .ultimate_space_detect_initiation import detect_play, extract_play
+        from .ultimate_space_preprocessing import create_intermediate_file
+
+        detected_plays_dict = {}
+        for tracking_path_i in tqdm(
+            tracking_files, total=len(tracking_files), desc="Processing tracking files"
+        ):
+            match_i = os.path.splitext(
+                os.path.splitext(os.path.basename(tracking_path_i))[0]
+            )[0]
+
+            # Read raw tracking data
+            match_tracking_df = pd.read_csv(tracking_path_i)
+
+            # Prepare data with required columns
+            intermediate_df = create_intermediate_file(match_tracking_df)
+
+            # Detect play initiations
+            detected_df = detect_play(
+                intermediate_df,
+                velocity_threshold=velocity_threshold,
+                acceleration_threshold=acceleration_threshold,
+                distance_threshold=distance_threshold,
+                player_threshold=player_threshold,
+            )
+
+            # Extract individual play segments
+
+            plays = extract_play(detected_df)
+
+            for play_key, play_df in plays.items():
+                detected_plays_dict[len(detected_plays_dict)] = (
+                    f"{match_i}-id{play_key[1]}-play{play_key[2]}"
+                )
+
+            if self.out_path:
+                os.makedirs(self.out_path + "/initiation/plays", exist_ok=True)
+
+                for play_key, df in plays.items():
+                    df.to_csv(
+                        os.path.join(
+                            self.out_path,
+                            "initiation/plays",
+                            f"{match_i}-id{play_key[1]}-play{play_key[2]}.csv",
+                        ),
+                        index=False,
+                    )
+        return detected_plays_dict

From c93ebca491da0fdcae601da932da016009306940 Mon Sep 17 00:00:00 2001
From: shunsuke-iwashita <iwashita.shunsuke@g.sp.m.is.nagoya-u.ac.jp>
Date: Wed, 1 Apr 2026 23:56:24 +0900
Subject: [PATCH 2/2] Bumps package version to 0.1.55

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index e99530b..09a8699 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -6,7 +6,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "openstarlab_preprocessing"
-version = "0.1.54"
+version = "0.1.55"
 description = "openstarlab preprocessing package"
 readme = "README.md"
 requires-python = ">=3.8"