Merge pull request #36 from UnravelSports/feat/unravel_graph

fix padding datatypes

Author: UnravelSports

tests/files/plot/test-1.mp4

@@ -350,6 +350,21 @@ def custom_edge_feature(**kwargs):
                 verbose=False,
             )
 
+    # def test_skillcorner_warning(
+    #     self, kloppy_dataset: TrackingDataset
+    # ) -> KloppyPolarsDataset:
+    #     with pytest.warns(UserWarning):
+    #         dataset = KloppyPolarsDataset(
+    #             kloppy_dataset=kloppy_dataset,
+    #             ball_carrier_threshold=25.0,
+    #             max_player_speed=12.0,
+    #             max_player_acceleration=12.0,
+    #             max_ball_speed=13.5,
+    #             max_ball_acceleration=100,
+    #         )
+    #         dataset.add_dummy_labels(by=["game_id", "frame_id"], random_seed=42)
+    #         dataset.add_graph_ids(by=["game_id", "frame_id"])
+
     def test_incorrect_custom_features_no_decorator(
         self, kloppy_polars_dataset: KloppyPolarsDataset
     ) -> SoccerGraphConverterPolars:

tests/files/plot/test-no-extension.png

@@ -25,6 +25,8 @@
 
 import polars as pl
 
+import warnings
+
 
 DEFAULT_PLAYER_SMOOTHING_PARAMS = {"window_length": 7, "polyorder": 1}
 DEFAULT_BALL_SMOOTHING_PARAMS = {"window_length": 3, "polyorder": 1}
@@ -688,13 +690,16 @@ def load(
         df = df.drop(["dx", "dy", "dz", "dt", "dvx", "dvy", "dvz"])
         df = df.filter(~(pl.col(Column.X).is_null() & pl.col(Column.Y).is_null()))
 
-        if (
-            df[Column.BALL_OWNING_TEAM_ID].is_null().all()
-            and self.ball_carrier_threshold is None
-        ):
-            raise ValueError(
-                f"This dataset requires us to infer the {Column.BALL_OWNING_TEAM_ID}, please specifiy a ball_carrier_threshold (float) to do so."
-            )
+        if df[Column.BALL_OWNING_TEAM_ID].is_null().all():
+            if self.ball_carrier_threshold is None:
+                raise ValueError(
+                    f"This dataset requires us to infer the {Column.BALL_OWNING_TEAM_ID}, please specifiy a ball_carrier_threshold (float) to do so."
+                )
+            else:
+                warnings.warn(
+                    "This dataset does not come with 'ball owning team' information. As a result we infer this using distance to ball using the 'ball_carrier_threshold'. Please note this might cause unexpected results.",
+                    UserWarning,
+                )
 
         df = self.__infer_ball_carrier(df)
 

tests/files/plot/test-png.png

@@ -260,6 +260,11 @@ def _apply_padding(self) -> pl.DataFrame:
                 for col in user_defined_columns
             ]
         )
+
+        padding_df = padding_df.with_columns(
+            [pl.col(col).cast(df.schema[col]).alias(col) for col in group_by_columns]
+        )
+
         padding_df = padding_df.join(
             (
                 df.unique(group_by_columns).select(