Update app.py

app.py

@@ -26,9 +26,9 @@ data1 = {'ratio':[0.053910],
          'illuminance':[10646.052788] ,
          'Kitchen_night_illuminance':[76.282996],
          'Lounge_night_illuminance':[83.069952] ,
-         'Bathroom_night_temperature':[20.639559], 
+         'Kitchen_morning_temperature' :[83.069952] ,
          'Bathroom_evening_temperature':[21.449295],
-          'Bathroom_night_activity':[19.367503], 
+        'Bathroom_night_activity':[19.367503], 
          'number_transitions':[222.017461], 
          'temperature_ratio':[2.004192],
          'awake_ratio':[0.207502],
@@ -48,8 +48,8 @@ data2 = {'ratio' :[0.030281],
          'illuminance': [7337.315382],
          'Kitchen_night_illuminance': [54.300962],
          'Lounge_night_illuminance' :[116.355455], 
-         'Bathroom_night_temperature':[2.007301],
-            'Bathroom_evening_temperature':[2.087516], 
+        'Bathroom_evening_temperature':[2.087516], 
+         'Kitchen_morning_temperature': [54.300962],
          'Bathroom_night_activity':[35.206093] ,
          'number_transitions':[94.177603], 
          'temperature_ratio':[4.045142],
@@ -100,7 +100,7 @@ top_features= ['ratio',
  'illuminance',
  'Kitchen_night_illuminance',
  'Lounge_night_illuminance',
- 'Bathroom_night_temperature',
+ 'Bathroom_morning_temperature',
  'Bathroom_evening_temperature',
  'Bathroom_night_activity',
  'number_transitions',
@@ -121,10 +121,10 @@ def update_sliders(example_df):
     Lounge_night_illuminance = example_data['Lounge_night_illuminance'].astype(float).iloc[-1]
     ratio = example_data['ratio'].astype(float).iloc[-1] 
     Kitchen_night_temperature= example_data['Kitchen_night_temperature'].astype(float).iloc[-1]
-    Bathroom_night_temperature= example_data['Bathroom_night_temperature'].astype(float).iloc[-1]
+    Kitchen_morning_temperature= example_data['Kitchen_morning_temperature'].astype(float).iloc[-1]
     Bathroom_evening_temperature= example_data['Bathroom_evening_temperature'].astype(float).iloc[-1] 
     temperature_ratio = example_data['temperature_ratio'].astype(float).iloc[-1] 
-    return Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio
+    return Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio
 
 
 # %%
@@ -133,7 +133,7 @@ blue = sns.color_palette()[0]
 red = sns.color_palette()[1]
 
 # %%
-def predict(example_df,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio):
+def predict(example_df,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio):
     example_data = example_df
     example_df_norm = normalize(example_data, mean_df, std_df, top_features)
     feature_values = example_df_norm[top_features].iloc[0]
@@ -198,7 +198,7 @@ def predict(example_df,Kitchen_afternoon_illuminance, Lounge_night_illuminance,
             else:
                 statement= "The temperature in the bathroom in the evening was lower than usual."
                 statements.append(statement)
-        elif feature == "Bathroom_night_temperature":
+        elif feature == "Kitchen_morning_temperature":
             if feature_direction == "positive":
                 statement= "The temperature in the bathroom in the night was higher than usual."
                 statements.append(statement)
@@ -320,7 +320,7 @@ def predict(example_df,Kitchen_afternoon_illuminance, Lounge_night_illuminance,
 import shap
 import matplotlib.pyplot as plt
 
-def interpret(example_df,Lounge_night_illuminance, Kitchen_night_illuminance, Kitchen_afternoon_illuminance, ratio, temperature_ratio, Bathroom_night_temperature, Bathroom_evening_temperature, Kitchen_night_temperature):
+def interpret(example_df,Lounge_night_illuminance, Kitchen_night_illuminance, Kitchen_afternoon_illuminance, ratio, temperature_ratio, Kitchen_morning_temperature, Bathroom_evening_temperature, Kitchen_night_temperature):
     # Read the example data
     example_data = example_df
 
@@ -395,13 +395,13 @@ def interpret(example_df,Lounge_night_illuminance, Kitchen_night_illuminance, Ki
 
 
 # %%
-def update_data(example_df, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio):
+def update_data(example_df, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio):
     example_data = example_df
     example_data['Lounge_night_illuminance'].iloc[0] = Lounge_night_illuminance
     example_data['Kitchen_night_illuminance'].iloc[0] = Kitchen_night_illuminance
     example_data['Kitchen_afternoon_illuminance'].iloc[0] = Kitchen_afternoon_illuminance
     example_data['ratio'].iloc[0] = ratio
-    example_data['Bathroom_night_temperature'].iloc[0] = Bathroom_night_temperature
+    example_data['Kitchen_morning_temperature'].iloc[0] = Kitchen_morning_temperature
     example_data['Bathroom_evening_temperature'].iloc[0] = Bathroom_evening_temperature
     example_data['Kitchen_night_temperature'].iloc[0] = Kitchen_night_temperature
     example_data['temperature_ratio'].iloc[0] = temperature_ratio
@@ -475,7 +475,7 @@ def update_data(example_df, Kitchen_afternoon_illuminance, Lounge_night_illumina
             else:
                 statement= "The temperature in the bathroom in the evening was lower than usual."
                 statements.append(statement)
-        elif feature == "Bathroom_night_temperature":
+        elif feature == "Kitchen_morning_temperature":
             if feature_direction == "positive":
                 statement= "The temperature in the bathroom in the night was higher than usual."
                 statements.append(statement)
@@ -517,7 +517,7 @@ def update_data(example_df, Kitchen_afternoon_illuminance, Lounge_night_illumina
             else:
                 statement="The indoor light exposure in the kitchen at night was lower than usual."
                 statements.append(statement)
-        elif feature == "Bathroom_night_temperature":
+        elif feature == "Kitchen_morning_temperature":
             if feature_direction == "positive":
                 statement="The temperature in the bathroom at night was higher than usual."
                 statements.append(statement)
@@ -679,7 +679,7 @@ def generate_data():
     df['Kitchen_afternoon_illuminance'] = np.random.uniform(0, 5000)
     df['ratio'] = np.random.uniform(0, 15)
     df['temperature_ratio'] = np.random.uniform(-1.5, 1.5)
-    df['Bathroom_night_temperature'] = np.random.uniform(0, 40)  # Random value between 0 and 40
+    df['Kitchen_morning_temperature'] = np.random.uniform(0, 40)  # Random value between 0 and 40
     df['Bathroom_evening_temperature'] = np.random.uniform(0, 40)
     df['Kitchen_night_temperature'] = np.random.uniform(0, 40)     
     df['number_transitions'] = np.random.uniform(0,500)
@@ -692,11 +692,11 @@ def generate_data():
     Lounge_night_illuminance = df['Lounge_night_illuminance'].astype(float).iloc[-1]
     ratio = df['ratio'].astype(float).iloc[-1] 
     Kitchen_night_temperature= df['Kitchen_night_temperature'].astype(float).iloc[-1]
-    Bathroom_night_temperature= df['Bathroom_night_temperature'].astype(float).iloc[-1]
+    Kitchen_morning_temperature= df['Kitchen_morning_temperature'].astype(float).iloc[-1]
     Bathroom_evening_temperature= df['Bathroom_evening_temperature'].astype(float).iloc[-1] 
     temperature_ratio = df['temperature_ratio'].astype(float).iloc[-1] 
     
-    return df,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio
+    return df,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio
 
 # %%
 import pandas as pd
@@ -709,7 +709,7 @@ def return_original(example_df):
     Kitchen_afternoon_illuminance = example_data['Kitchen_afternoon_illuminance'].astype(float).iloc[-1]
     ratio = example_data['ratio'].astype(float).iloc[-1] 
     temperature_ratio = example_data['temperature_ratio'].astype(float).iloc[-1] 
-    Bathroom_night_temperature= example_data['Bathroom_night_temperature'].astype(float).iloc[-1]
+    Kitchen_morning_temperature= example_data['Kitchen_morning_temperature'].astype(float).iloc[-1]
     Bathroom_evening_temperature= example_data['Bathroom_evening_temperature'].astype(float).iloc[-1] 
     Kitchen_night_temperature= example_data['Kitchen_night_temperature'].astype(float).iloc[-1]
     example_df_norm = normalize(example_data, mean_df, std_df, top_features)
@@ -783,12 +783,12 @@ def return_original(example_df):
             else:
                 statement= "The temperature in the bathroom in the evening was lower than usual."
                 statements.append(statement)
-        elif feature == "Bathroom_night_temperature":
+        elif feature == "Kitchen_morning_temperature":
             if feature_direction == "positive":
-                statement= "The temperature in the bathroom in the night was higher than usual."
+                statement= "The temperature in the kitchen in the morning was higher than usual."
                 statements.append(statement)
             else:
-                statement= "The temperature in the bathroom in the night was lower than usual."
+                statement= "The temperature in the kitchen in the morning was lower than usual."
                 statements.append(statement)
         elif feature == "Kitchen_afternoon_illuminance":
             if feature_direction == "positive":
@@ -937,7 +937,7 @@ def return_original(example_df):
         plt.yticks(fontsize=28)
         plt.tight_layout()
         
-        return {"Agitated": float(proba[0][1]), "Non-agitated": float(proba[0][0])}, formatted_statements, plot,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio
+        return {"Agitated": float(proba[0][1]), "Non-agitated": float(proba[0][0])}, formatted_statements, plot,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio
         
     
     # Plotting for negative class predictions (class label 0)
@@ -964,18 +964,18 @@ def return_original(example_df):
         plt.yticks(fontsize=28)
         plt.tight_layout()
 
-        return {"Agitated": float(proba[0][1]), "Non-agitated": float(proba[0][0])}, formatted_statements, plot, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio
+        return {"Agitated": float(proba[0][1]), "Non-agitated": float(proba[0][0])}, formatted_statements, plot, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio
 
 
     
-def save_file(example_df,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio):
+def save_file(example_df,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio):
         example_data = example_df
         example_data['Lounge_night_illuminance'] = Lounge_night_illuminance
         example_data['Kitchen_night_illuminance'] = Kitchen_night_illuminance
         example_data['Kitchen_afternoon_illuminance'] = Kitchen_afternoon_illuminance
         example_data['ratio'] = ratio
         example_data['temperature_ratio'] = temperature_ratio
-        example_data['Bathroom_night_temperature'] = Bathroom_night_temperature
+        example_data['Kitchen_morning_temperature'] = Kitchen_morning_temperature
         example_data['Bathroom_evening_temperature'] = Bathroom_evening_temperature
         example_data['Kitchen_night_temperature'] = Kitchen_night_temperature
         current_path = os.getcwd()
@@ -1003,7 +1003,7 @@ with gr.Blocks(theme=gr.themes.Default(spacing_size="md", primary_hue="red", sec
     with gr.Row():
         with gr.Column():
             generate = gr.Button(value="Generate synthetic patient data")
-            csv_file = gr.DataFrame(headers=['ratio', 'sunset_minutes', 'Kitchen_night_temperature', 'uvindex', 'visibility','illuminance','Kitchen_night_illuminance','Lounge_night_illuminance','Bathroom_night_temperature','Bathroom_evening_temperature', 'Bathroom_night_activity', 'number_transitions', 'temperature_ratio', 'awake_ratio','rr_min','To_bed', 'Lounge_afternoon_activity','rr_average',"rr_min_std",'Kitchen_afternoon_illuminance'],row_count=1 , col_count=20, datatype = "number", interactive=False)
+            csv_file = gr.DataFrame(headers=['ratio', 'sunset_minutes', 'Kitchen_night_temperature', 'uvindex', 'visibility','illuminance','Kitchen_night_illuminance','Lounge_night_illuminance','Kitchen_morning_temperature','Bathroom_evening_temperature', 'Bathroom_night_activity', 'number_transitions', 'temperature_ratio', 'awake_ratio','rr_min','To_bed', 'Lounge_afternoon_activity','rr_average',"rr_min_std",'Kitchen_afternoon_illuminance'],row_count=1 , col_count=20, datatype = "number", interactive=False)
             modif = gr.Button(value="Change the modifiable parameters to see how agitation risk changes")
             gr.Markdown("""<p style="margin-top: 20px; font-size: 16px; font-weight: bold;"> Light exposure </p>""")
             Kitchen_afternoon_illuminance = gr.Slider(label="Mean afternoon illuminance in kitchen", minimum=0, maximum=3000, step=100)
@@ -1011,7 +1011,7 @@ with gr.Blocks(theme=gr.themes.Default(spacing_size="md", primary_hue="red", sec
             Lounge_night_illuminance = gr.Slider(label="Mean night illuminance in lounge", minimum=0, maximum=3000, step=100, every=True)
             ratio = gr.Slider(label="Ratio (indoor:outdoor illuminance)", minimum=0, maximum=0.35, step=0.1)
             gr.Markdown("""<p style="margin-top: 20px; font-size: 16px; font-weight: bold;"> Ambient temperature </p>""")
-            Bathroom_night_temperature = gr.Slider(label="Mean night temperature in bathroom", minimum=-10, maximum=45, step=0.5)
+            Kitchen_morning_temperature = gr.Slider(label="Mean morning temperature in kitchen", minimum=-10, maximum=45, step=0.5)
             Bathroom_evening_temperature = gr.Slider(label="Mean evening temperature in bathroom", minimum=-10, maximum=45, step=0.5)
             Kitchen_night_temperature = gr.Slider(label="Mean night temperature in kitchen", minimum=-10, maximum=45, step=0.5)
             temperature_ratio = gr.Slider(label="Ratio (indoor:outdoor temperature)", minimum=-500, maximum=60, step=0.1)
@@ -1026,21 +1026,21 @@ with gr.Blocks(theme=gr.themes.Default(spacing_size="md", primary_hue="red", sec
             plot = gr.Plot(scale=2, label="Interpretation")
         
             with gr.Row():
-                generate.click(generate_data, outputs=[csv_file,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio])
-                Lounge_night_illuminance.input(update_data, inputs=[csv_file, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text, plot])
-                Kitchen_night_illuminance.input(update_data, inputs=[csv_file, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text, plot])
-                Kitchen_afternoon_illuminance.input(update_data, inputs=[csv_file,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text,plot])
-                Bathroom_night_temperature.input(update_data, inputs=[csv_file,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text,plot])
-                ratio.input(update_data, inputs=[csv_file,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text,plot])
-                temperature_ratio.input(update_data, inputs=[csv_file, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text,plot])
-                Bathroom_night_temperature.input(update_data, inputs=[csv_file, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text,plot])
-                Bathroom_evening_temperature.input(update_data, inputs=[csv_file, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text,plot])
-                Kitchen_night_temperature.input(update_data, inputs=[csv_file, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio, Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text,plot])
+                generate.click(generate_data, outputs=[csv_file,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio])
+                Lounge_night_illuminance.input(update_data, inputs=[csv_file, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text, plot])
+                Kitchen_night_illuminance.input(update_data, inputs=[csv_file, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text, plot])
+                Kitchen_afternoon_illuminance.input(update_data, inputs=[csv_file,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text,plot])
+                Kitchen_morning_temperature.input(update_data, inputs=[csv_file,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text,plot])
+                ratio.input(update_data, inputs=[csv_file,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text,plot])
+                temperature_ratio.input(update_data, inputs=[csv_file, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text,plot])
+                Kitchen_morning_temperature.input(update_data, inputs=[csv_file, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text,plot])
+                Bathroom_evening_temperature.input(update_data, inputs=[csv_file, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text,plot])
+                Kitchen_night_temperature.input(update_data, inputs=[csv_file, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio, Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio], outputs= [label,html_text,plot])
         
                 predict_btn.click(
                     predict,
                     inputs=[
-                   csv_file, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio
+                   csv_file, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio
                     ],
                     outputs=[label,html_text]
                     )
@@ -1048,7 +1048,7 @@ with gr.Blocks(theme=gr.themes.Default(spacing_size="md", primary_hue="red", sec
                 interpret_btn.click(
                     interpret,
                     inputs=[
-                    csv_file,  Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio
+                    csv_file,  Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio
                     ],
                     outputs=[plot],
                     )
@@ -1058,12 +1058,12 @@ with gr.Blocks(theme=gr.themes.Default(spacing_size="md", primary_hue="red", sec
                     inputs=[
                     csv_file
                     ],
-                    outputs=[label,html_text, plot, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio],
+                    outputs=[label,html_text, plot, Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio],
                     )
 
                 flag.click(
                     save_file,
-                    inputs= [csv_file,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Bathroom_night_temperature, Bathroom_evening_temperature, temperature_ratio],
+                    inputs= [csv_file,Kitchen_afternoon_illuminance, Lounge_night_illuminance, Kitchen_night_illuminance, ratio,  Kitchen_night_temperature, Kitchen_morning_temperature, Bathroom_evening_temperature, temperature_ratio],
                     )
     with gr.Row():
         gr.Markdown("<img src='https://ukdri.ac.uk/assets/img/logo.svg' alt='UKDRI' width='250' style='margin-top: 50px;'>")