Create app.py

app.py

@@ -0,0 +1,57 @@
+import pandas as pd
+import streamlit as st
+import plotly.graph_objects as go
+from ASDM.ASDM import Structure
+
+def load_model(model_path):
+    try:
+        model = Structure(from_xmile=model_path)
+    except FileNotFoundError:
+        st.error(f"File {model_path} not found.")
+        return None
+    return model
+
+def run_simulation(model, simulation_time, re_investment):
+    model.sim_specs['initial_time'] = 0
+    model.sim_specs['current_time'] = 0
+    model.sim_specs['dt'] = 1
+    model.sim_specs['simulation_time'] = simulation_time
+    model.sim_specs['time_units'] = 'Months'
+
+    model.clear_last_run()
+
+    model.aux_equations['percentageOfSavingsSpentOnCessation'] = str(re_investment)
+
+    model.simulate()
+
+    results = model.export_simulation_result()
+    results_df = pd.DataFrame.from_dict(results)
+
+    columns_to_plot = ["Current_smokers", "Ex_smokers", "Ex_smokers_starting_again"]
+    return results_df['Months'], results_df[columns_to_plot]
+
+st.title('Smoking Cessation')
+
+st.markdown("""
+This simulation estimates the effects of various reinvestment levels in a smoking cessation service within a population of 900 smokers. 
+By varying the proportion of savings that are reinvested into the service, we can observe different outcomes in terms of current smokers, ex-smokers, 
+and ex-smokers who start smoking again over time.
+""")
+            
+st.subheader('Slide the Slider to Vary Re-Investment Levels')
+
+model = load_model('models/smoking cessation demo.stmx')
+
+if model is not None:
+    re_investment = st.slider("Proportion of Savings Spent on Cessation", 0, 100, 45)
+    simulation_time = st.slider("Select the number of months to simulate:", min_value=1, max_value=36, value=24)
+
+    x_values, y_values = run_simulation(model, simulation_time, re_investment)
+
+    st.subheader('Effects of Re-Investment on Smoking Levels')
+
+    fig = go.Figure()
+    for column in y_values.columns:
+        fig.add_trace(go.Scatter(x=x_values, y=y_values[column], mode='lines', name=column))
+    fig.update_layout(xaxis_title='Months', yaxis_title='Number of Smokers', autosize=False, width=800, height=500)
+    st.plotly_chart(fig)