Update appbackup.py

appbackup.py

@@ -32,8 +32,14 @@ def generate_predictions(medication_data, site, bmd, mu, sigma):
     
     for _, row in site_data.iterrows():
         drug = row['Medication']
-        predictions = {'Year': ['0'], 'Predicted BMD': [round(bmd, 3)], 'Predicted T-score': [round(calculate_tscore(bmd, mu, sigma), 1)]}
+        predictions = {
+            'Year': ['0'], 
+            'Year Index': [0],  # Numeric x-axis for plotting
+            'Predicted BMD': [round(bmd, 3)], 
+            'Predicted T-score': [round(calculate_tscore(bmd, mu, sigma), 1)]
+        }
         
+        year_index = 1
         for year in row.index[1:-1]:  # Skip 'Medication' and 'Site' columns
             if not pd.isna(row[year]):
                 percentage_increase = row[year]
@@ -41,12 +47,15 @@ def generate_predictions(medication_data, site, bmd, mu, sigma):
                 predicted_tscore = calculate_tscore(predicted_bmd, mu, sigma)
                 
                 predictions['Year'].append(year.replace(" Year", ""))  # Simplify year label
+                predictions['Year Index'].append(year_index)  # Numeric x-axis
                 predictions['Predicted BMD'].append(round(predicted_bmd, 3))
                 predictions['Predicted T-score'].append(round(predicted_tscore, 1))
+                year_index += 1
         
         all_results.append({'Drug': drug, 'Predictions': predictions})
     return all_results
 
+
 # Display results as table and plots
 def display_results(predictions, site):
     st.subheader(f"Predictions for {site}")
@@ -59,13 +68,13 @@ def display_results(predictions, site):
         st.write(f"### {drug}")
         st.dataframe(pd.DataFrame(predictions))
         
-        # Plot BMD and T-score
+        # Plot BMD and T-score using Year Index
         bmd_plot = go.Scatter(
-            x=predictions['Year'], y=predictions['Predicted BMD'], mode='lines+markers',
+            x=predictions['Year Index'], y=predictions['Predicted BMD'], mode='lines+markers',
             name='Predicted BMD', line=dict(color='blue')
         )
         tscore_plot = go.Scatter(
-            x=predictions['Year'], y=predictions['Predicted T-score'], mode='lines+markers',
+            x=predictions['Year Index'], y=predictions['Predicted T-score'], mode='lines+markers',
             name='Predicted T-score', line=dict(color='green')
         )
         
@@ -73,11 +82,13 @@ def display_results(predictions, site):
         col1, col2 = st.columns(2)
         with col1:
             st.plotly_chart(go.Figure(data=[bmd_plot], layout=go.Layout(
-                title=f"{drug} - Predicted BMD", xaxis_title="Year", yaxis_title="BMD (g/cm²)"
+                title=f"{drug} - Predicted BMD", xaxis_title="Year", yaxis_title="BMD (g/cm²)",
+                xaxis=dict(tickmode='array', tickvals=predictions['Year Index'], ticktext=predictions['Year'])
             )))
         with col2:
             st.plotly_chart(go.Figure(data=[tscore_plot], layout=go.Layout(
-                title=f"{drug} - Predicted T-score", xaxis_title="Year", yaxis_title="T-score"
+                title=f"{drug} - Predicted T-score", xaxis_title="Year", yaxis_title="T-score",
+                xaxis=dict(tickmode='array', tickvals=predictions['Year Index'], ticktext=predictions['Year'])
             )))
 
 # Streamlit UI