Added platformdirs & python3.14

.github/workflows/linters_and_tests.yml

@@ -21,7 +21,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: ["3.10", "3.11", "3.12", "3.13"]
+        python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"]
     defaults:
       run:
         shell: bash

databallpy/data_parsers/tracking_data_parsers/tracab_parser.py

@@ -1,14 +1,14 @@
 import datetime as dt
 import json
 import os
+import xml.etree.ElementTree as ET
 from pathlib import Path
 
 import chardet
 import numpy as np
 import pandas as pd
 import requests
 from bs4 import BeautifulSoup
-from lxml import etree
 from tqdm import tqdm
 
 from databallpy.data_parsers import Metadata
@@ -165,7 +165,7 @@ def _get_tracking_data_xml(
     frames_df["start_datetime_td"] = pd.to_datetime(frames_df["start_datetime_td"])
     frames_df["end_datetime_td"] = pd.to_datetime(frames_df["end_datetime_td"])
 
-    context = etree.iterparse(tracab_loc, events=("start", "end"))
+    context = ET.iterparse(tracab_loc, events=("start", "end"))
     event, _ = next(context)
 
     frame_values = []
@@ -194,7 +194,7 @@ def _get_tracking_data_xml(
         "datetime": ["NaT"] * size_lines,
     }
 
-    context = etree.iterparse(tracab_loc, events=("start", "end"))
+    context = ET.iterparse(tracab_loc, events=("start", "end"))
     event, _ = next(context)
 
     if verbose:

databallpy/features/filters.py

@@ -49,7 +49,7 @@ def _filter_data(
 
     if filter_type == "savitzky_golay":
         try:
-            return savgol_filter(
+            return _savgol_with_nan_compat(
                 array, window_length=window_length, polyorder=polyorder, mode="interp"
             )
         except Exception as e:
@@ -128,11 +128,11 @@ def filter_tracking_data(
     ]
     for col in xy_columns:
         if filter_type == "savitzky_golay":
-            tracking_data[col] = savgol_filter(
-                tracking_data[col].values,
+            tracking_data[col] = _filter_data(
+                tracking_data[col].to_numpy(),
+                filter_type="savitzky_golay",
                 window_length=window_length,
                 polyorder=polyorder,
-                mode="interp",
             )
         elif filter_type == "moving_average":
             tracking_data[col] = np.convolve(
@@ -141,3 +141,34 @@ def filter_tracking_data(
 
     if not inplace:
         return tracking_data
+
+
+def _savgol_with_nan_compat(
+    array: np.ndarray,
+    window_length: int,
+    polyorder: int,
+    mode: str = "interp",
+) -> np.ndarray:
+    arr = np.asarray(array, dtype=float)
+
+    mask = ~np.isfinite(arr)
+
+    if not mask.any():
+        return savgol_filter(arr, window_length, polyorder, mode=mode).round(2)
+
+    valid_count = (~mask).sum()
+    if valid_count < max(window_length, polyorder + 1):
+        warnings.warn(
+            "Not enough finite samples to apply Savitzky–Golay filter; "
+            "returning original data for backward compatibility."
+        )
+        return arr
+
+    x = np.arange(arr.size)
+    arr_filled = arr.copy()
+    arr_filled[mask] = np.interp(x[mask], x[~mask], arr[~mask])
+
+    filtered = savgol_filter(arr_filled, window_length, polyorder, mode=mode).round(2)
+
+    filtered[mask] = np.nan
+    return filtered

databallpy/schemas/event_data.py

@@ -1,7 +1,7 @@
 from typing import Optional
 
 import pandas as pd
-import pandera as pa
+import pandera.pandas as pa
 
 from databallpy.utils.constants import DATABALLPY_EVENTS
 

databallpy/schemas/players.py

@@ -1,6 +1,6 @@
 from typing import Optional
 
-import pandera as pa
+import pandera.pandas as pa
 
 from databallpy.utils.constants import DATABALLPY_POSITIONS
 

databallpy/schemas/tracking_data.py

@@ -4,8 +4,8 @@
 
 import numpy as np
 import pandas as pd
-import pandera as pa
 import pandera.extensions as extensions
+import pandera.pandas as pa
 from scipy.spatial import KDTree
 
 from databallpy.features.covered_distance import (
@@ -15,7 +15,7 @@
 )
 from databallpy.features.differentiate import _differentiate
 from databallpy.features.feature_utils import _check_column_ids
-from databallpy.features.filters import savgol_filter
+from databallpy.features.filters import _filter_data
 from databallpy.features.pitch_control import get_pitch_control_single_frame
 from databallpy.features.player_possession import (
     get_ball_losses_and_updated_gain_idxs,
@@ -533,11 +533,11 @@ def filter_tracking_data(
         ]
         for col in xy_columns:
             if filter_type == "savitzky_golay":
-                self[col] = savgol_filter(
-                    self[col].values,
+                self[col] = _filter_data(
+                    self[col].to_numpy(),
+                    filter_type="savitzky_golay",
                     window_length=window_length,
                     polyorder=polyorder,
-                    mode="interp",
                 )
             elif filter_type == "moving_average":
                 self[col] = np.convolve(