implement load data for Libre and Dexcom devices

Author: staskh

iglu_python/extension/load_data.py

@@ -54,6 +54,9 @@ def load_libre(file_path: str) -> pd.Series:
     # Convert 'time' column to datetime
     df['time'] = pd.to_datetime(df['time'], format=format)
 
+    # Convert glucose values to numeric
+    df['glc'] = pd.to_numeric(df['glc'], errors='coerce')
+    
     # convert to mg/dL if needed
     if convert:
         df['glc'] = df['glc'] * 18.01559    

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "iglu_python"
-version = "0.2.1"
+version = "0.2.4"
 description = "Python implementation of the iglu package for continuous glucose monitoring data analysis"
 readme = "README.md"
 requires-python = ">=3.11"

tests/test_load_data.py

@@ -197,4 +197,18 @@ def test_load_dexcom_time_interval(test_data_paths):
     tolerance = pd.Timedelta(minutes=2)  # Allow some variation
     # Check that most intervals are close to expected
     close_intervals = time_diffs[abs(time_diffs - expected_interval) <= tolerance]
-    assert len(close_intervals) / len(time_diffs) > 0.8  # At least 80% should be close 
+    assert len(close_intervals) / len(time_diffs) > 0.8  # At least 80% should be close
+
+def test_load_libre_numeric_values(test_data_paths):
+    timeseries = load_libre(str(test_data_paths['libre_amer_01']))
+    # Check that all values are numeric
+    assert pd.api.types.is_numeric_dtype(timeseries)
+    # Check that there are no NaN values (all should be valid numbers)
+    assert not timeseries.isna().any()
+
+def test_load_dexcom_numeric_values(test_data_paths):
+    timeseries = load_dexcom(str(test_data_paths['dexcom_eur_01']))
+    # Check that all values are numeric
+    assert pd.api.types.is_numeric_dtype(timeseries)
+    # Check that there are no NaN values (all should be valid numbers)
+    assert not timeseries.isna().any()