Update app.py

app.py

@@ -35,44 +35,55 @@ def create_bmd_and_tscore_prediction_table(df_bmd_data, drug_selected, bmd_patie
     years = ['1st', '2nd', '3rd', '4th', '5th', '6th', '8th', '10th']
     predictions = []
 
-    for year in years:
-        if not pd.isna(df_bmd_data.loc[df_bmd_data['Drug'] == drug_selected, year].values[0]):
-            percent_increase = df_bmd_data.loc[df_bmd_data['Drug'] == drug_selected, year].values[0]
-            bmd_new = calculate_bmd_increase(bmd_patient, percent_increase)  # Use baseline BMD
-            tscore_new = calculate_tscore_from_bmd(bmd_new, c_avg_new, c_sd_new)  # Calculate predicted T-score
-            predictions.append((year, bmd_new, tscore_new))
+    for drug in drug_selected:
+        for year in years:
+            if not pd.isna(df_bmd_data.loc[df_bmd_data['Drug'] == drug, year].values[0]):
+                percent_increase = df_bmd_data.loc[df_bmd_data['Drug'] == drug, year].values[0]
+                bmd_new = calculate_bmd_increase(bmd_patient, percent_increase)  # Use baseline BMD
+                tscore_new = calculate_tscore_from_bmd(bmd_new, c_avg_new, c_sd_new)  # Calculate predicted T-score
+                predictions.append((drug, year, bmd_new, tscore_new))
 
-    return pd.DataFrame(predictions, columns=['Year', 'Predicted BMD', 'Predicted T-score'])
+    return pd.DataFrame(predictions, columns=['Drug', 'Year', 'Predicted BMD', 'Predicted T-score'])
 
 # Step 5: Plot BMD and T-score as separate graphs side by side
 def plot_bmd_and_tscore_separate(prediction_table, baseline_bmd, baseline_tscore):
-    years = ['0'] + list(prediction_table['Year'])
-    bmd_values = [baseline_bmd] + list(prediction_table['Predicted BMD'])
-    tscore_values = [baseline_tscore] + list(prediction_table['Predicted T-score'])
-
-    # Create BMD plot
-    trace_bmd = go.Scatter(x=years, y=bmd_values, mode='lines+markers', name='BMD', line=dict(color='blue'))
-
-    # Create T-score plot
-    trace_tscore = go.Scatter(x=years, y=tscore_values, mode='lines+markers', name='T-score', line=dict(color='green'))
-
-    # Layout for BMD graph
+    years = ['0'] + list(prediction_table['Year'].unique())
+    
+    # Plot for BMD
+    traces_bmd = []
+    for drug in prediction_table['Drug'].unique():
+        df_drug = prediction_table[prediction_table['Drug'] == drug]
+        bmd_values = [baseline_bmd] + list(df_drug['Predicted BMD'])
+        trace_bmd = go.Scatter(x=years, y=bmd_values, mode='lines+markers', name=drug + ' (BMD)')
+        traces_bmd.append(trace_bmd)
+
+    # Plot for T-score
+    traces_tscore = []
+    for drug in prediction_table['Drug'].unique():
+        df_drug = prediction_table[prediction_table['Drug'] == drug]
+        tscore_values = [baseline_tscore] + list(df_drug['Predicted T-score'])
+        trace_tscore = go.Scatter(x=years, y=tscore_values, mode='lines+markers', name=drug + ' (T-score)', yaxis='y2')
+        traces_tscore.append(trace_tscore)
+
+    # Create BMD layout
     layout_bmd = go.Layout(
         title="Predicted BMD over Time",
         xaxis=dict(title='Years'),
-        yaxis=dict(title='BMD (g/cm²)', showgrid=False)
+        yaxis=dict(title='BMD (g/cm²)', showgrid=False),
+        legend=dict(x=0.1, y=1.1, orientation='h')
     )
 
-    # Layout for T-score graph
+    # Create T-score layout
     layout_tscore = go.Layout(
         title="Predicted T-score over Time",
         xaxis=dict(title='Years'),
-        yaxis=dict(title='T-score', showgrid=False)
+        yaxis2=dict(title='T-score', overlaying='y', side='right', showgrid=False),
+        legend=dict(x=0.1, y=1.1, orientation='h')
     )
 
-    # Create figures
-    fig_bmd = go.Figure(data=[trace_bmd], layout=layout_bmd)
-    fig_tscore = go.Figure(data=[trace_tscore], layout=layout_tscore)
+    # Create BMD and T-score figures
+    fig_bmd = go.Figure(data=traces_bmd, layout=layout_bmd)
+    fig_tscore = go.Figure(data=traces_tscore, layout=layout_tscore)
 
     # Use Streamlit columns to place two plots side by side
     col1, col2 = st.columns(2)
@@ -109,8 +120,8 @@ def main_with_plot_tscore_labels(file_path, bmd_patient, tscore_patient, C_avg_l
     for i, row in prediction_table.iterrows():
         st.write(f"Year {row['Year']}: BMD = {row['Predicted BMD']:.3f}, T-score = {row['Predicted T-score']:.2f}")
 
-        # Check if the goal of BMD >= -2.49 is achieved
-        if row['Predicted T-score'] >= -2.49:
+        # Check if the goal of BMD >= -2.4 is achieved
+        if row['Predicted T-score'] >= -2.4:
             st.success(f"Goal achieved at year {row['Year']}")
             break
 
@@ -122,12 +133,16 @@ def main():
     bmd_patient = st.number_input("Initial BMD", min_value=0.0, max_value=2.0, value=0.635, step=0.001)
     tscore_patient = st.number_input("Initial T-score", min_value=-5.0, max_value=2.0, value=-2.5, step=0.01)
 
-    # Select drug
+    # Drug options
     drug_options = ['Teriparatide', 'Teriparatide + Denosumab', 'Denosumab', 'Denosumab + Teriparatide',
                     'Romosozumab', 'Romosozumab + Denosumab', 'Romosozumab + Alendronate',
                     'Romosozumab + Ibandronate', 'Romosozumab + Zoledronate', 'Alendronate',
                     'Risedronate', 'Ibandronate oral', 'Ibandronate IV (3mg)', 'Zoledronate']
-    drug_selected = st.selectbox("Select a drug", drug_options)
+
+    # Add option to select all medications
+    selected_drugs = st.multiselect("Select drugs to compare", drug_options, default=None)
+    if "All Medications" in selected_drugs:
+        selected_drugs = drug_options  # If "All Medications" is selected, include all drugs
 
     # Set C_avg and C_sd for Lunar device (example values)
     C_avg_lunar = 0.95  # Example: Average BMD for Total Hip from Excel (Lunar)
@@ -136,9 +151,13 @@ def main():
     # Example file path
     file_path = "BMD constant calculator.xlsx"
 
-    # Run prediction and plot results
-    if st.button("Predict"):
-        main_with_plot_tscore_labels(file_path, bmd_patient, tscore_patient, C_avg_lunar, C_sd_lunar, drug_selected)
+    # ตรวจสอบว่ามีการเลือกยาแล้วหรือไม่
+    if len(selected_drugs) == 0:
+        st.warning("Please select at least one drug to compare.")
+    else:
+        # Run prediction and plot results
+        if st.button("Predict"):
+            main_with_plot_tscore_labels(file_path, bmd_patient, tscore_patient, C_avg_lunar, C_sd_lunar, selected_drugs)
 
 if __name__ == "__main__":
     main()