refactor: remove numpy dependency from SkillCorner (#375)

kloppy/infra/serializers/tracking/skillcorner.py

@@ -1,13 +1,11 @@
 import json
 import logging
 import warnings
-from collections import Counter
+from collections import Counter, defaultdict
 from datetime import datetime, timedelta, timezone
 from pathlib import Path
 from typing import IO, Dict, NamedTuple, Optional, Union
 
-import numpy as np
-
 from kloppy.domain import (
     AttackingDirection,
     DatasetFlag,
@@ -207,22 +205,21 @@ def _get_skillcorner_attacking_directions(cls, frames, periods):
         x-coords might not reflect the attacking direction.
         """
         attacking_directions = {}
-        frame_period_ids = np.array([_frame.period.id for _frame in frames])
-        frame_attacking_directions = np.array(
-            [
-                attacking_direction_from_frame(frame)
-                if len(frame.players_data) > 0
-                else AttackingDirection.NOT_SET
-                for frame in frames
-            ]
-        )
 
+        # Group attacking directions by period ID
+        period_direction_map = defaultdict(list)
+        for frame in frames:
+            if len(frame.players_data) > 0:
+                direction = attacking_direction_from_frame(frame)
+            else:
+                direction = AttackingDirection.NOT_SET
+            period_direction_map[frame.period.id].append(direction)
+
+        # Determine the most common attacking direction for each period
         for period_id in periods.keys():
-            if period_id in frame_period_ids:
-                count = Counter(
-                    frame_attacking_directions[frame_period_ids == period_id]
-                )
-                attacking_directions[period_id] = count.most_common()[0][0]
+            if period_id in period_direction_map:
+                count = Counter(period_direction_map[period_id])
+                attacking_directions[period_id] = count.most_common(1)[0][0]
             else:
                 attacking_directions[period_id] = AttackingDirection.NOT_SET
 
@@ -252,28 +249,33 @@ def __get_periods(cls, tracking):
         """gets the Periods contained in the tracking data"""
         periods = {}
 
-        _periods = np.array([f["period"] for f in tracking])
-        unique_periods = set(_periods)
-        unique_periods = [
-            period for period in unique_periods if period is not None
-        ]
+        # Extract unique periods while filtering out None values
+        unique_periods = {
+            frame["period"]
+            for frame in tracking
+            if frame["period"] is not None
+        }
 
         for period in unique_periods:
+            # Filter frames that belong to the current period and have valid "time"
             _frames = [
                 frame
                 for frame in tracking
                 if frame["period"] == period and frame["time"] is not None
             ]
 
-            periods[period] = Period(
-                id=period,
-                start_timestamp=timedelta(
-                    seconds=_frames[0]["frame"] / frame_rate
-                ),
-                end_timestamp=timedelta(
-                    seconds=_frames[-1]["frame"] / frame_rate
-                ),
-            )
+            # Ensure _frames is not empty before accessing the first and last elements
+            if _frames:
+                periods[period] = Period(
+                    id=period,
+                    start_timestamp=timedelta(
+                        seconds=_frames[0]["frame"] / frame_rate
+                    ),
+                    end_timestamp=timedelta(
+                        seconds=_frames[-1]["frame"] / frame_rate
+                    ),
+                )
+
         return periods
 
     @classmethod