Update app.py

app.py

@@ -176,9 +176,9 @@ def forecast_time_series(df, model_type, freq, horizon, max_steps=200):
 
 @st.cache_data
 def load_default():
-    df = AirPassengersDf.copy()
+    df = AirPassengersDF.copy()
     return df
-    
+
 def transfer_learning_forecasting():
     st.title("Transfer Learning Forecasting")
 
@@ -192,7 +192,7 @@ def transfer_learning_forecasting():
     # Model selection and forecasting
     st.subheader("Model Selection and Forecasting")
     model_choice = st.selectbox("Select model", ["NHITS", "TimesNet", "LSTM", "TFT"])
-    horizon = st.slider("Forecast horizon", 1, 100, 10)
+    horizon = st.number_input("Forecast horizon", value=18)
 
     # Determine frequency of data
     frequency = determine_frequency(df)
@@ -219,33 +219,33 @@ def transfer_learning_forecasting():
     time_taken = end_time - start_time
     st.success(f"Time taken for {model_choice} forecast: {time_taken:.2f} seconds")
 
- def dynamic_forecasting():
+def dynamic_forecasting():
     st.title("Dynamic Forecasting")
-
+    
     # Upload dataset
     uploaded_file = st.file_uploader("Upload your time series data (CSV)", type=["csv"])
     if uploaded_file:
         df = pd.read_csv(uploaded_file)
     else:
         df = load_default()
-
+    
     # Dynamic forecasting
     st.subheader("Dynamic Model Selection and Forecasting")
     dynamic_model_choice = st.selectbox("Select model for dynamic forecasting", ["NHITS", "TimesNet", "LSTM", "TFT"], key="dynamic_model_choice")
-    dynamic_horizon = st.slider("Forecast horizon for dynamic forecasting", 1, 100, 10, key="dynamic_horizon")
-
+    dynamic_horizon = st.number_input("Forecast horizon", value=18)
+    
     # Determine frequency of data
     frequency = determine_frequency(df)
     st.write(f"Detected frequency: {frequency}")
-
-    forecast_time_series(df, dynamic_model_choice, frequency, dynamic_horizon
-                         
+    
+    forecast_time_series(df, dynamic_model_choice, frequency, dynamic_horizon)
+    
 # Define the main navigation
 pg = st.navigation({
     "Overview": [
         # Load pages from functions
-        st.Page(transfer_learning_forecasting, title="Transfer Learning Forecasting", default=True, icon=":material/library_books:"),
-        st.Page(dynamic_forecasting, title="Dynamic Forecasting", icon=":material/person:"),
+        st.Page(transfer_learning_forecasting, title="Transfer Learning Forecasting", default=True, icon=":material/query_stats:"),
+        st.Page(dynamic_forecasting, title="Dynamic Forecasting", icon=":material/monitoring:"),
     ]
 })