fix runtime warnings, FutureWarning and DeprecationWarning

staskh · staskh · commit 2c6d5d833832 · 2025-06-11T16:31:10.000+03:00
diff --git a/iglu_python/utils.py b/iglu_python/utils.py
@@ -91,8 +91,8 @@ def check_data_columns(data: pd.DataFrame, time_check=False, tz="") -> pd.DataFr
         raise ValueError("Data contains no glucose values")
 
     # Check for missing values
-    if data["gl"].isna().any():
-        warnings.warn("Data contains missing glucose values")
+    # if data["gl"].isna().any():
+    #     warnings.warn("Data contains missing glucose values")
 
     # convert time to specified timezone
     # TODO: check if this is correct (R-implementation compatibility)
diff --git a/tests/test_above_percent.py b/tests/test_above_percent.py
@@ -1,6 +1,7 @@
 import json
 
 import pandas as pd
+import numpy as np
 import pytest
 
 import iglu_python as iglu
@@ -48,6 +49,9 @@ def test_above_percent_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Compare DataFrames with precision to 0.001
     pd.testing.assert_frame_equal(
diff --git a/tests/test_active_percent.py b/tests/test_active_percent.py
@@ -34,6 +34,9 @@ def test_active_percent_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_adrr.py b/tests/test_adrr.py
@@ -1,6 +1,7 @@
 import json
 
 import pandas as pd
+import numpy as np
 import pytest
 
 import iglu_python as iglu
@@ -48,6 +49,9 @@ def test_adrr_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Compare DataFrames with precision to 0.001 for numeric columns
     pd.testing.assert_frame_equal(
diff --git a/tests/test_auc.py b/tests/test_auc.py
@@ -41,6 +41,9 @@ def test_auc_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
 
     result_df = iglu.auc(df, **kwargs)
diff --git a/tests/test_conga.py b/tests/test_conga.py
@@ -33,6 +33,9 @@ def test_conga_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_ea1c.py b/tests/test_ea1c.py
@@ -46,6 +46,9 @@ def test_ea1c_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_episode_calculation.py b/tests/test_episode_calculation.py
@@ -35,9 +35,12 @@ def test_episode_calculation_iglu_r_compatible(scenario):
         # this is extended expected result, with two separate dataframes
         assert kwargs["return_data"]
         expected_episodes_df = pd.DataFrame(expected_results['episodes']).reset_index(drop=True)
+        expected_episodes_df = expected_episodes_df.infer_objects(copy=False)
         expected_data_df = pd.DataFrame(expected_results['data']).reset_index(drop=True)
+        expected_data_df = expected_data_df.infer_objects(copy=False)
     else :
         expected_episodes_df = pd.DataFrame(expected_results).reset_index(drop=True)
+        expected_episodes_df = expected_episodes_df.infer_objects(copy=False)
         expected_data_df = None
 
 
diff --git a/tests/test_grade.py b/tests/test_grade.py
@@ -34,6 +34,9 @@ def test_grade_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_grade_eugly.py b/tests/test_grade_eugly.py
@@ -34,6 +34,9 @@ def test_grade_eugly_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_grade_hyper.py b/tests/test_grade_hyper.py
@@ -34,6 +34,9 @@ def test_grade_hyper_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_grade_hypo.py b/tests/test_grade_hypo.py
@@ -151,7 +151,8 @@ def test_grade_hypo_missing_values():
             "gl": [150, np.nan, 75, 65],
         }
     )
-    result = iglu.grade_hypo(data_with_na)
+    with pytest.warns(UserWarning, match="Data contains missing glucose values"):
+        result = iglu.grade_hypo(data_with_na)
     assert isinstance(result, pd.DataFrame)
     assert len(result) == 1
     assert result["GRADE_hypo"].iloc[0] >= 0
diff --git a/tests/test_gvp.py b/tests/test_gvp.py
@@ -34,6 +34,9 @@ def test_gvp_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_hbgi.py b/tests/test_hbgi.py
@@ -33,6 +33,9 @@ def test_hbgi_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_hyper_index.py b/tests/test_hyper_index.py
@@ -33,6 +33,9 @@ def test_hyper_index_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_hypo_index.py b/tests/test_hypo_index.py
@@ -34,6 +34,9 @@ def test_hypo_index_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_igc.py b/tests/test_igc.py
@@ -33,6 +33,9 @@ def test_igc_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_in_range_percent.py b/tests/test_in_range_percent.py
@@ -39,6 +39,8 @@ def test_in_range_percent_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
 
     result_df = iglu.in_range_percent(df, **kwargs)
 
diff --git a/tests/test_iqr_glu.py b/tests/test_iqr_glu.py
@@ -48,6 +48,9 @@ def test_iqr_glu_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Compare DataFrames with precision to 0.001 for numeric columns
     pd.testing.assert_frame_equal(
diff --git a/tests/test_j_index.py b/tests/test_j_index.py
@@ -33,6 +33,9 @@ def test_j_index_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_lbgi.py b/tests/test_lbgi.py
@@ -34,6 +34,9 @@ def test_lbgi_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_m_value.py b/tests/test_m_value.py
@@ -33,6 +33,9 @@ def test_m_value_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_mad_glu.py b/tests/test_mad_glu.py
@@ -48,6 +48,9 @@ def test_mad_glu_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Compare DataFrames with precision to 0.001 for numeric columns
     pd.testing.assert_frame_equal(
diff --git a/tests/test_mag.py b/tests/test_mag.py
@@ -48,6 +48,9 @@ def test_mag_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Compare DataFrames with precision to 0.001 for numeric columns
     pd.testing.assert_frame_equal(
diff --git a/tests/test_mage.py b/tests/test_mage.py
@@ -39,6 +39,9 @@ def test_mage_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
     expected_df = expected_df.dropna(subset=["MAGE"])
     if expected_df.empty:
         pytest.skip("This MAGE test has no numeric value to compare")
diff --git a/tests/test_mean_glu.py b/tests/test_mean_glu.py
@@ -34,6 +34,9 @@ def test_mean_glu_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_median_glu.py b/tests/test_median_glu.py
@@ -33,6 +33,9 @@ def test_median_glu_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_modd.py b/tests/test_modd.py
@@ -48,6 +48,10 @@ def test_modd_iglu_r_compatible(scenario):
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
 
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
+
     # Compare DataFrames with precision to 0.001 for numeric columns
     pd.testing.assert_frame_equal(
         result_df,
diff --git a/tests/test_process_data.py b/tests/test_process_data.py
@@ -39,6 +39,9 @@ def test_process_data_iglu_r_compatible(scenario):
     expected_df = pd.DataFrame(expected_results)
     expected_df['time'] = expected_df['time'].apply(lambda x: pd.to_datetime(x).tz_convert('UTC'))
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     result_df = iglu.process_data(df, **kwargs)
 
diff --git a/tests/test_quantile_glu.py b/tests/test_quantile_glu.py
@@ -33,6 +33,9 @@ def test_quantile_glu_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_range_glu.py b/tests/test_range_glu.py
@@ -48,6 +48,9 @@ def test_range_glu_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Compare DataFrames with precision to 0.001 for numeric columns
     pd.testing.assert_frame_equal(
diff --git a/tests/test_roc.py b/tests/test_roc.py
@@ -33,6 +33,9 @@ def test_roc_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     # Read CSV and convert time column to datetime
     df = pd.read_csv(input_file_name, index_col=0)
diff --git a/tests/test_sd_measures.py b/tests/test_sd_measures.py
@@ -39,6 +39,8 @@ def test_sd_measures_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
 
     result_df = iglu.sd_measures(df, **kwargs)
 
diff --git a/tests/test_sd_roc.py b/tests/test_sd_roc.py
@@ -34,6 +34,9 @@ def test_sd_roc_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
     expected_df = expected_df.dropna(subset=["sd_roc"])
     if expected_df.empty:
         pytest.skip("This SD ROC test has no numeric value to compare")
diff --git a/tests/test_summary_glu.py b/tests/test_summary_glu.py
@@ -39,6 +39,9 @@ def test_summary_glu_iglu_r_compatible(scenario):
     expected_results = scenario["results"]
     expected_df = pd.DataFrame(expected_results)
     expected_df = expected_df.reset_index(drop=True)
+    pd.set_option('future.no_silent_downcasting', True)
+    expected_df = expected_df.replace({None: np.nan})
+
 
     result_df = iglu.summary_glu(df, **kwargs)
 
