Update app.py

app.py

@@ -44,27 +44,42 @@ def create_bmd_and_tscore_prediction_table(df_bmd_data, drug_selected, bmd_patie
 
     return pd.DataFrame(predictions, columns=['Year', 'Predicted BMD', 'Predicted T-score'])
 
-# Step 5: Plot the BMD increase over time as a line graph and add T-score labels positioned below each point
-def plot_bmd_timeline_with_tscore(prediction_table, baseline_bmd):
-    years = ['0'] + list(prediction_table['Year'])  # Add "Year 0" as the starting point
+# 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 = [''] + list(prediction_table['Predicted T-score'])  # No T-score for Year 0
+    tscore_values = [baseline_tscore] + list(prediction_table['Predicted T-score'])
 
-    # Create a line plot for BMD values
+    # Create BMD plot
     trace_bmd = go.Scatter(x=years, y=bmd_values, mode='lines+markers', name='BMD', line=dict(color='blue'))
-    trace_tscore = go.Scatter(x=years, y=tscore_values, mode='lines+markers', name='T-score', line=dict(color='red'), yaxis='y2')
 
-    # Create layout with dual y-axes
-    layout = go.Layout(
-        title="Predicted BMD and T-score over Time",
+    # 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
+    layout_bmd = go.Layout(
+        title="Predicted BMD over Time",
         xaxis=dict(title='Years'),
-        yaxis=dict(title='BMD (g/cm²)', showgrid=False),
-        yaxis2=dict(title='T-score', overlaying='y', side='right', showgrid=False),
-        legend=dict(x=0.1, y=1.1, orientation='h'),
+        yaxis=dict(title='BMD (g/cm²)', showgrid=False)
     )
 
-    fig = go.Figure(data=[trace_bmd, trace_tscore], layout=layout)
-    st.plotly_chart(fig)
+    # Layout for T-score graph
+    layout_tscore = go.Layout(
+        title="Predicted T-score over Time",
+        xaxis=dict(title='Years'),
+        yaxis=dict(title='T-score', showgrid=False)
+    )
+
+    # Create figures
+    fig_bmd = go.Figure(data=[trace_bmd], layout=layout_bmd)
+    fig_tscore = go.Figure(data=[trace_tscore], layout=layout_tscore)
+
+    # Use Streamlit columns to place two plots side by side
+    col1, col2 = st.columns(2)
+    with col1:
+        st.plotly_chart(fig_bmd)
+    with col2:
+        st.plotly_chart(fig_tscore)
 
 # Step 6: Calculate T-score from adjusted BMD
 def calculate_tscore_from_bmd(bmd_patient, c_avg, c_sd):
@@ -87,8 +102,8 @@ def main_with_plot_tscore_labels(file_path, bmd_patient, tscore_patient, C_avg_l
     st.write("BMD and T-score Prediction Table")
     st.dataframe(prediction_table)
 
-    # Step 5: Plot the BMD increase over time with T-score labels
-    plot_bmd_timeline_with_tscore(prediction_table, bmd_patient)
+    # Step 5: Plot the BMD and T-score graphs side by side
+    plot_bmd_and_tscore_separate(prediction_table, bmd_patient, tscore_patient)
 
     # Step 6: Check if goal is achieved and show the predicted BMD and T-score for each year
     for i, row in prediction_table.iterrows():