Smallfix docs

Author: miriamkw

loop_to_python_api/api.py

@@ -145,7 +145,7 @@ def add_insulin_counteraction_effect_to_df(df, basal, isf, cr, insulin_type='nov
     :param insulin_type: Which insulin profile to use to compute the insulin on board
     :param batch_size: How many samples to include in each batch operation. Might be reduced / increased, but default is optimized for general settings.
     :param overlap: How many time steps to use for computing insulin activity. Can be reduced for some types of insulin, which will improve performance.
-    :return: The input df with columns for insulin on board and insulin counteraction effects.
+    :return: The input df with columns for insulin on board and insulin counteraction effects. Unit of ICE is mg/dL*s
     """
     data = df[['basal', 'bolus', 'CGM']].copy()  # Extract only necessary data to improve performance
     data.loc[:, 'bolus'] = data['bolus'].replace(0.0, np.nan)

python_tests/tests.py

@@ -35,19 +35,19 @@ def get_dynamic_carbs_input():
 
 def test_initialize_exception_handlers():
     result = initialize_exception_handlers()
-    assert result is None  # Replace with the expected result
+    assert result is None
 
 
 def test_generate_prediction():
     prediction_input = get_generate_prediction_input()
     prediction_values = generate_prediction(prediction_input)
-    assert isinstance(prediction_values, list)  # Replace with the expected type or value
+    assert isinstance(prediction_values, list)
 
 
 def test_get_prediction_dates():
     prediction_input = get_generate_prediction_input()
     prediction_dates = get_prediction_dates(prediction_input)
-    assert isinstance(prediction_dates, list)  # Replace with the expected type or value
+    assert isinstance(prediction_dates, list)
 
 
 def test_get_prediction_values_and_dates():
@@ -64,19 +64,19 @@ def test_get_prediction_values_and_dates():
 def test_get_dose_recommendations():
     loop_algorithm_input = get_loop_algorithm_input()
     dose_recommendations = get_dose_recommendations(loop_algorithm_input)
-    assert isinstance(dose_recommendations, dict)  # Replace with the expected type or value
+    assert isinstance(dose_recommendations, dict)
 
 
 def test_get_glucose_effect_velocity():
     prediction_input = get_generate_prediction_input()
     glucose_effect_velocity = get_glucose_effect_velocity(prediction_input)
-    assert isinstance(glucose_effect_velocity, list)  # Replace with the expected type or value
+    assert isinstance(glucose_effect_velocity, list)
 
 
 def test_get_glucose_effect_velocity_dates():
     prediction_input = get_generate_prediction_input()
     glucose_effect_velocity_dates = get_glucose_effect_velocity_dates(prediction_input)
-    assert isinstance(glucose_effect_velocity_dates, list)  # Replace with the expected type or value
+    assert isinstance(glucose_effect_velocity_dates, list)
 
 
 def test_get_glucose_effect_velocity_values_and_dates():
@@ -92,33 +92,33 @@ def test_get_glucose_effect_velocity_values_and_dates():
 def test_get_active_carbs():
     loop_algorithm_input = get_loop_algorithm_input()
     active_carbs = get_active_carbs(loop_algorithm_input)
-    assert isinstance(active_carbs, float)  # Replace with the expected type or value
+    assert isinstance(active_carbs, float)
 
 
 def test_get_active_insulin():
     loop_algorithm_input = get_loop_algorithm_input()
     active_insulin = get_active_insulin(loop_algorithm_input)
-    assert isinstance(active_insulin, float)  # Replace with the expected type or value
+    assert isinstance(active_insulin, float)
 
 
 def test_percent_absorption_at_percent_time():
     result = percent_absorption_at_percent_time(0.2)
-    assert isinstance(result, float)  # Replace with the expected type or value
+    assert isinstance(result, float)
 
 
 def test_piecewise_linear_percent_rate_at_percent_time():
     result = piecewise_linear_percent_rate_at_percent_time(0.2)
-    assert isinstance(result, float)  # Replace with the expected type or value
+    assert isinstance(result, float)
 
 
 def test_linear_percent_rate_at_percent_time():
     result = linear_percent_rate_at_percent_time(0.2)
-    assert isinstance(result, float)  # Replace with the expected type or value
+    assert isinstance(result, float)
 
 
 def test_get_dynamic_carbs_on_board():
     dynamic_carbs_input = get_dynamic_carbs_input()
     dynamic_carbs_on_board = get_dynamic_carbs_on_board(dynamic_carbs_input)
-    assert isinstance(dynamic_carbs_on_board, float)  # Replace with the expected type or value
+    assert isinstance(dynamic_carbs_on_board, float)