better docstring and test

howso/utilities/feature_attributes/infer_feature_attributes.py

@@ -217,7 +217,9 @@ def infer_feature_attributes(data: Union[pd.DataFrame, SQLRelationalDatastorePro
         If True, the time feature will be treated as universal and future data
         is excluded while making predictions. If False, the time feature will
         not be treated as universal and only future data within the same series
-        is excluded while making predictions.
+        is excluded while making predictions. It is recommended to set this
+        value to True if there is any possibility of global relevancy of time,
+        which is the default behavior.
 
     time_series_type_default : str, default 'rate'
         (Optional) Type specifying how time series is generated.

howso/utilities/feature_attributes/tests/test_infer_time_series_attributes.py

@@ -199,3 +199,32 @@ def test_set_rate_delta_boundaries():
         assert 'rate_max' not in features['date']['time_series']
         assert 'delta_min' not in features['f3']['time_series']
         assert 'delta_max' not in features['f3']['time_series']
+
+
+@pytest.mark.parametrize(
+    ("universal_value", "expected"),
+    [
+        (True, True),
+        (False, False),
+        (None, None),
+    ]
+)
+def test_time_feature_is_universal(universal_value, expected):
+    """Validates that time_feature_is_universal is working as expected."""
+    df = pd.read_csv(data_path)
+
+    # Define time format
+    time_format = "%Y%m%d"
+    # Identify id-feature and time-feature
+    id_feature_name = "ID"
+    time_feature_name = "date"
+
+    features = infer_feature_attributes(
+        df,
+        time_feature_name=time_feature_name,
+        id_feature_name=id_feature_name,
+        datetime_feature_formats={time_feature_name: time_format},
+        time_feature_is_universal=universal_value,
+    )
+
+    assert features[time_feature_name]['time_series'].get("universal") == expected

howso/utilities/feature_attributes/time_series.py

@@ -428,7 +428,9 @@ def _process(  # noqa: C901
             If True, the time feature will be treated as universal and future data
             is excluded while making predictions. If False, the time feature will
             not be treated as universal and only future data within the same series
-            is excluded while making predictions.
+            is excluded while making predictions. It is recommended to set this
+            value to True if there is any possibility of global relevancy of time,
+            which is the default behavior.
 
         time_series_type_default : str, default 'rate'
             (Optional) Type specifying how time series is generated.