Merge pull request #46 from UnravelSports/feat/unravel_graph

Feat/unravel graph

Author: UnravelSports

README.md

@@ -152,13 +152,9 @@ These dependencies come pre-installed with the package. It is advised to create
 
 This package is tested on the latest versions of Ubuntu, MacOS and Windows. 
 
-🌀 Contributing
+🌀 Licenses
 ----
-All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. 
-
-An overview on how to contribute can be found in the [**contributing guide**](CONTRIBUTING.md).
-
-I try to keep an up-to-date list of [Open Issues](https://github.com/UnravelSports/unravelsports/issues). If you would like to work on any of these, or have ideas of your own that could be added, send me a message on [LinkedIn](https://www.linkedin.com/in/joris-bekkers-33138288/) or [BlueSky](https://bsky.app/profile/unravelsports.com)
+This project is licensed under the [Mozilla Public License Version 2.0 (MPL)](LICENSE), which requires that you include a copy of the license and provide attribution to the original authors. Any modifications you make to the MPL-licensed files must be documented, and the source code for those modifications must be made open-source under the same license.
 
 🌀 Citation
 ----
@@ -215,7 +211,5 @@ If you use this repository for any educational purposes, research, project etc.,
 [<img alt="alt_text" width="40px" src="https://upload.wikimedia.org/wikipedia/commons/c/ca/LinkedIn_logo_initials.png"/>](https://www.linkedin.com/in/joris-bekkers-33138288/)
 [<img alt="alt_text" width="40px" src="https://upload.wikimedia.org/wikipedia/commons/thumb/7/7a/Bluesky_Logo.svg/2319px-Bluesky_Logo.svg.png"/>](https://bsky.app/profile/unravelsports.com)
 
-🌀 Licenses
-----
-This project is licensed under the [Mozilla Public License Version 2.0 (MPL)](LICENSE), which requires that you include a copy of the license and provide attribution to the original authors. Any modifications you make to the MPL-licensed files must be documented, and the source code for those modifications must be made open-source under the same license.
+
 

unravel/soccer/graphs/graph_converter.py

@@ -982,8 +982,18 @@ def player_and_ball(frame_data, ax):
                     ]
                 )
                 ax.set_xlabel(f"Label: {frame_data['label'][0]}", fontsize=22)
+                ax.set_title(self._gameclock, fontsize=22)
 
         def frame_plot(self, frame_data):
+            def timestamp_to_gameclock(timestamp, period_id):
+                total_seconds = timestamp.total_seconds()
+
+                minutes = int(total_seconds // 60)
+                seconds = int(total_seconds % 60)
+                milliseconds = int((total_seconds % 1) * 1000)
+
+                return f"[{period_id}] - {minutes}:{seconds:02d}:{milliseconds:03d}"
+
             self._gs = GridSpec(
                 2,
                 3,
@@ -1023,6 +1033,10 @@ def frame_plot(self, frame_data):
                 frame_data[Column.IS_BALL_CARRIER] == True
             )[0][0]
             self._ball_owning_team_id = list(frame_data[Column.BALL_OWNING_TEAM_ID])[0]
+            self._gameclock = timestamp_to_gameclock(
+                timestamp=list(frame_data["timestamp"])[0],
+                period_id=list(frame_data["period_id"])[0],
+            )
 
             plot_vertical_pitch(frame_data)
             plot_graph()
@@ -1036,7 +1050,7 @@ def frame_plot(self, frame_data):
             df = self._sort(df)
 
         if generate_video:
-            writer = animation.FFMpegWriter(fps=fps, bitrate=1800)
+            writer = animation.FFMpegWriter(fps=fps, bitrate=1500)
 
             with writer.saving(self._fig, file_path, dpi=300):
                 for group_id, frame_data in df.group_by(

unravel/utils/objects/custom_spektral_dataset.py

@@ -90,7 +90,7 @@ def __convert(self, data) -> List[Graph]:
                     e=g["e"],
                     y=g["y"],
                     id=g["id"],
-                    frame_id=g["frame_id"],
+                    frame_id=g.get("frame_id", None),
                 )
                 for i, g in enumerate(data)
                 if i % self.sample == 0