Update app.py

app.py

@@ -2,13 +2,20 @@ import streamlit as st
 import pandas as pd
 import plotly.graph_objs as go
 
-# Step 1: Load the cleaned sheet "Clean TH avg rise BMD" and display it
-def load_clean_bmd_data(file_path):
-    sheet_clean_th_avg_rise = 'Clean TH avg rise BMD'
-    df_clean_th_avg_rise = pd.read_excel(file_path, sheet_name=sheet_clean_th_avg_rise)
+# Step 1: Load the cleaned sheet based on the selected site
+def load_clean_bmd_data(file_path, site):
+    sheet_name = ''
+    if site == 'Total Hip':
+        sheet_name = 'Clean TH avg rise BMD'
+    elif site == 'Femoral Neck':
+        sheet_name = 'clean FN avg rise BMD'
+    elif site == 'Lumbar Spine (L1-L4)':
+        sheet_name = 'clean LS avg rise BMD'
+
+    df_clean_bmd_data = pd.read_excel(file_path, sheet_name=sheet_name)
 
     # Select relevant columns: Drug names and BMD percentage increases
-    df_cleaned = df_clean_th_avg_rise[['Unnamed: 0', '1st', '2nd', '3rd', '4th', '5th', '6th', '8th', '10th']]
+    df_cleaned = df_clean_bmd_data[['Unnamed: 0', '1st', '2nd', '3rd', '4th', '5th', '6th', '8th', '10th']]
 
     # Rename the first column to 'Drug'
     df_cleaned.columns = ['Drug', '1st', '2nd', '3rd', '4th', '5th', '6th', '8th', '10th']
@@ -95,9 +102,9 @@ def calculate_tscore_from_bmd(bmd_patient, c_avg, c_sd):
     return (bmd_patient - c_avg) / c_sd
 
 # Main function to load data, run the application, and plot results with T-score labels
-def main_with_separate_tables(file_path, bmd_patient, tscore_patient, C_avg_lunar, C_sd_lunar, selected_drugs):
-    # Step 1: Load and clean BMD data from the Excel sheet
-    df_bmd_data = load_clean_bmd_data(file_path)
+def main_with_separate_tables(file_path, bmd_patient, tscore_patient, C_avg_lunar, C_sd_lunar, selected_drugs, site):
+    # Step 1: Load and clean BMD data from the selected site (Total Hip, Femoral Neck, Lumbar Spine)
+    df_bmd_data = load_clean_bmd_data(file_path, site)
 
     # Step 2: Adjust constants based on the patient's data
     c_avg_new, c_sd_new = adjust_constants(bmd_patient, tscore_patient, C_avg_lunar, C_sd_lunar)
@@ -119,6 +126,10 @@ 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)
 
+    # Site options (Total Hip, Femoral Neck, Lumbar Spine)
+    site_options = ['Total Hip', 'Femoral Neck', 'Lumbar Spine (L1-L4)']
+    site = st.selectbox("Select site", site_options)
+
     # Drug options
     drug_options = ['Teriparatide', 'Teriparatide + Denosumab', 'Denosumab', 'Denosumab + Teriparatide',
                     'Romosozumab', 'Romosozumab + Denosumab', 'Romosozumab + Alendronate',
@@ -128,9 +139,16 @@ def main():
     # Add option to select multiple drugs
     selected_drugs = st.multiselect("Select drugs to compare", drug_options)
 
-    # 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)
-    C_sd_lunar = 0.12   # Example: SD for Total Hip (Lunar)
+    # Set constants for each site
+    if site == 'Total Hip':
+        C_avg_lunar = 0.95  # Example: Average BMD for Total Hip from Excel (Lunar)
+        C_sd_lunar = 0.12   # Example: SD for Total Hip (Lunar)
+    elif site == 'Femoral Neck':
+        C_avg_lunar = 0.905  # Example: Average BMD for Femoral Neck from Excel (Lunar)
+        C_sd_lunar = 0.116   # Example: SD for Femoral Neck (Lunar)
+    elif site == 'Lumbar Spine (L1-L4)':
+        C_avg_lunar = 1.097  # Example: Average BMD for Lumbar Spine (L1-L4) from Excel (Lunar)
+        C_sd_lunar = 0.128   # Example: SD for Lumbar Spine (L1-L4) (Lunar)
 
     # Example file path
     file_path = "BMD constant calculator.xlsx"
@@ -141,7 +159,7 @@ def main():
     else:
         # Run prediction and plot results
         if st.button("Predict"):
-            main_with_separate_tables(file_path, bmd_patient, tscore_patient, C_avg_lunar, C_sd_lunar, selected_drugs)
+            main_with_separate_tables(file_path, bmd_patient, tscore_patient, C_avg_lunar, C_sd_lunar, selected_drugs, site)
 
 if __name__ == "__main__":
-    main()
+    main()