Update app.py

app.py

@@ -21,7 +21,7 @@ st.markdown(
 st.sidebar.header("Step 1: Upload Dataset")
 uploaded_file = st.sidebar.file_uploader("Upload your Excel file (.xlsx)", type=["xlsx"])
 
-# Initialize empty data variables
+# Initialize data containers
 fiber_impact_data = None
 transport_impact_data = None
 washing_impact_data = None
@@ -49,46 +49,6 @@ def process_excel(file):
 if uploaded_file:
     fiber_impact_data, transport_impact_data, washing_impact_data = process_excel(uploaded_file)
 
-# Sidebar for product and fiber composition inputs
-st.sidebar.header("Step 2: Input Product Details")
-product_weight = st.sidebar.number_input("Product Weight (kg)", min_value=0.01, step=0.01, value=0.5)
-
-st.sidebar.header("Material Composition (%)")
-cotton = st.sidebar.number_input("Conventional Cotton (%)", min_value=0, max_value=100, value=50, step=1, key="cotton")
-polyester = st.sidebar.number_input("Polyester (%)", min_value=0, max_value=100, value=30, step=1, key="polyester")
-nylon = st.sidebar.number_input("Nylon 6 (%)", min_value=0, max_value=100, value=10, step=1, key="nylon")
-acrylic = st.sidebar.number_input("Acrylic (%)", min_value=0, max_value=100, value=5, step=1, key="acrylic")
-viscose = st.sidebar.number_input("Viscose (%)", min_value=0, max_value=100, value=5, step=1, key="viscose")
-
-total_percentage = cotton + polyester + nylon + acrylic + viscose
-if total_percentage != 100:
-    st.sidebar.error("The total of all fiber percentages must equal 100%!")
-
-composition = {
-    "Conventional Cotton": cotton,
-    "Polyester": polyester,
-    "Nylon 6": nylon,
-    "Acrylic": acrylic,
-    "Viscose": viscose,
-}
-
-# Sidebar for lifecycle inputs
-st.sidebar.header("Step 3: Input Lifecycle Details")
-comparison_mode = st.sidebar.checkbox("Enable Comparison Mode")
-washing_cycles = st.sidebar.number_input("Number of Washing Cycles", min_value=0, step=1, value=30)
-washing_temperature = None
-use_dryer = False
-transport_mode = None
-transport_distance = 0
-
-if washing_impact_data:
-    washing_temperature = st.sidebar.selectbox("Washing Temperature", list(washing_impact_data.keys()))
-    use_dryer = st.sidebar.checkbox("Use Tumble Dryer?")
-
-if transport_impact_data:
-    transport_mode = st.sidebar.selectbox("Transport Mode", list(transport_impact_data.keys()))
-    transport_distance = st.sidebar.number_input("Transport Distance (km)", min_value=0, step=10, value=100)
-
 # Function to calculate footprints
 def calculate_footprints(weight, composition, lifecycle_inputs):
     water_fp, energy_fp, carbon_fp = 0, 0, 0
@@ -115,45 +75,102 @@ def calculate_footprints(weight, composition, lifecycle_inputs):
         energy_fp += washing_energy
         carbon_fp += washing_carbon + (dryer_carbon * lifecycle_inputs["washing_cycles"])
 
-    return water_fp, energy_fp, carbon_fp
-
-# Results display area
-st.header("Results")
-
-if uploaded_file and total_percentage == 100:
+    # Convert water footprint from liters to kiloliters for visualization
+    water_fp_kL = water_fp / 1000
+    return water_fp_kL, energy_fp, carbon_fp
+
+# Sidebar inputs for all scenarios
+def get_inputs(key_prefix):
+    st.sidebar.subheader(f"Inputs for {key_prefix}")
+    product_weight = st.sidebar.number_input(f"{key_prefix} - Product Weight (kg)", min_value=0.01, step=0.01, value=0.5, key=f"{key_prefix}_weight")
+    
+    st.sidebar.subheader(f"{key_prefix} - Material Composition (%)")
+    cotton = st.sidebar.number_input("Conventional Cotton (%)", min_value=0, max_value=100, value=50, step=1, key=f"{key_prefix}_cotton")
+    polyester = st.sidebar.number_input("Polyester (%)", min_value=0, max_value=100, value=30, step=1, key=f"{key_prefix}_polyester")
+    nylon = st.sidebar.number_input("Nylon 6 (%)", min_value=0, max_value=100, value=10, step=1, key=f"{key_prefix}_nylon")
+    acrylic = st.sidebar.number_input("Acrylic (%)", min_value=0, max_value=100, value=5, step=1, key=f"{key_prefix}_acrylic")
+    viscose = st.sidebar.number_input("Viscose (%)", min_value=0, max_value=100, value=5, step=1, key=f"{key_prefix}_viscose")
+    
+    total_percentage = cotton + polyester + nylon + acrylic + viscose
+    if total_percentage != 100:
+        st.sidebar.error(f"Total composition for {key_prefix} must be 100%!")
+    
+    composition = {
+        "Conventional Cotton": cotton,
+        "Polyester": polyester,
+        "Nylon 6": nylon,
+        "Acrylic": acrylic,
+        "Viscose": viscose,
+    }
+    
+    st.sidebar.subheader(f"{key_prefix} - Lifecycle Inputs")
+    washing_cycles = st.sidebar.number_input(f"{key_prefix} - Washing Cycles", min_value=0, step=1, value=30, key=f"{key_prefix}_wash_cycles")
+    washing_temperature = st.sidebar.selectbox(f"{key_prefix} - Washing Temperature", list(washing_impact_data.keys()), key=f"{key_prefix}_wash_temp")
+    use_dryer = st.sidebar.checkbox(f"{key_prefix} - Use Tumble Dryer?", key=f"{key_prefix}_use_dryer")
+    transport_mode = st.sidebar.selectbox(f"{key_prefix} - Transport Mode", list(transport_impact_data.keys()), key=f"{key_prefix}_transport_mode")
+    transport_distance = st.sidebar.number_input(f"{key_prefix} - Transport Distance (km)", min_value=0, step=10, value=100, key=f"{key_prefix}_transport_distance")
+    
     lifecycle_inputs = {
-        "transport_mode": transport_mode,
-        "transport_distance": transport_distance,
         "washing_temperature": washing_temperature,
         "washing_cycles": washing_cycles,
         "use_dryer": use_dryer,
+        "transport_mode": transport_mode,
+        "transport_distance": transport_distance,
     }
+    
+    return product_weight, composition, lifecycle_inputs
 
-    water_fp, energy_fp, carbon_fp = calculate_footprints(product_weight, composition, lifecycle_inputs)
-
-    st.subheader("Calculated Footprints")
-    st.markdown(f"- **Water Footprint**: {water_fp:.2f} liters")
-    st.markdown(f"- **Energy Footprint**: {energy_fp:.2f} MJ")
-    st.markdown(f"- **Carbon Footprint**: {carbon_fp:.2f} kg CO2e")
-
-    # Visualization
+# Main interface
+if uploaded_file and fiber_impact_data and transport_impact_data and washing_impact_data:
+    comparison_mode = st.sidebar.checkbox("Enable Comparison Mode")
+    
     if comparison_mode:
-        st.info("Comparison mode enabled. Results for two scenarios can be added here if required.")
+        # Input for two scenarios
+        col1, col2 = st.columns(2)
+        with col1:
+            st.subheader("Scenario 1")
+            product_weight_1, composition_1, lifecycle_inputs_1 = get_inputs("Scenario 1")
+        with col2:
+            st.subheader("Scenario 2")
+            product_weight_2, composition_2, lifecycle_inputs_2 = get_inputs("Scenario 2")
+        
+        # Calculations for both scenarios
+        water_fp_1, energy_fp_1, carbon_fp_1 = calculate_footprints(product_weight_1, composition_1, lifecycle_inputs_1)
+        water_fp_2, energy_fp_2, carbon_fp_2 = calculate_footprints(product_weight_2, composition_2, lifecycle_inputs_2)
+        
+        # Combined visualization
+        st.subheader("Comparison Results")
+        comparison_data = pd.DataFrame({
+            "Footprint Type": ["Water (kL)", "Energy (MJ)", "Carbon (kg CO2e)"],
+            "Scenario 1": [water_fp_1, energy_fp_1, carbon_fp_1],
+            "Scenario 2": [water_fp_2, energy_fp_2, carbon_fp_2],
+        })
+        fig = px.bar(
+            comparison_data, 
+            x="Footprint Type", 
+            y=["Scenario 1", "Scenario 2"], 
+            barmode="group",
+            title="Comparison of Footprints"
+        )
+        st.plotly_chart(fig)
     else:
-        # Line chart visualization
-        footprint_data = pd.DataFrame({
-            "Footprint Type": ["Water", "Energy", "Carbon"],
+        # Input for single scenario
+        st.subheader("Single Scenario")
+        product_weight, composition, lifecycle_inputs = get_inputs("Single Scenario")
+        water_fp, energy_fp, carbon_fp = calculate_footprints(product_weight, composition, lifecycle_inputs)
+        
+        # Display results
+        st.subheader("Results")
+        st.markdown(f"- **Water Footprint**: {water_fp:.2f} kL")
+        st.markdown(f"- **Energy Footprint**: {energy_fp:.2f} MJ")
+        st.markdown(f"- **Carbon Footprint**: {carbon_fp:.2f} kg CO2e")
+        
+        # Visualization
+        result_data = pd.DataFrame({
+            "Footprint Type": ["Water (kL)", "Energy (MJ)", "Carbon (kg CO2e)"],
             "Value": [water_fp, energy_fp, carbon_fp],
         })
-
-        fig = px.line(
-            footprint_data,
-            x="Footprint Type",
-            y="Value",
-            title="Footprint Trends",
-            markers=True,
-        )
+        fig = px.line(result_data, x="Footprint Type", y="Value", markers=True, title="Footprint Trends")
         st.plotly_chart(fig)
-
 else:
-    st.info("Please upload a dataset and ensure all inputs are valid.")
+    st.info("Please upload a dataset to proceed.")