Update app.py

app.py

@@ -1,16 +1,12 @@
 import streamlit as st
 import pandas as pd
-from io import BytesIO
 import plotly.graph_objects as go
 
 # Set page configurations
 st.set_page_config(page_title="GreenLens-AI", layout="wide")
 
 # Page title and description
-st.markdown(
-    "<h1 style='text-align: center; color: #4CAF50;'>GreenLens-AI</h1>",
-    unsafe_allow_html=True,
-)
+st.markdown("<h1 style='text-align: center; color: #4CAF50;'>GreenLens-AI</h1>", unsafe_allow_html=True)
 st.markdown(
     """
     <p style='text-align: center; color: #4CAF50;'> 
@@ -20,11 +16,11 @@ st.markdown(
     unsafe_allow_html=True,
 )
 
-# File uploader in the sidebar
+# Sidebar for file upload
 st.sidebar.header("Step 1: Upload Dataset")
-uploaded_file = st.sidebar.file_uploader("Upload Dataset to Initiate ", type=["xlsx"])
+uploaded_file = st.sidebar.file_uploader("Upload your Excel file (.xlsx)", type=["xlsx"])
 
-# Initialize default values for data dicts
+# Initialize empty data variables
 fiber_impact_data = None
 transport_impact_data = None
 washing_impact_data = None
@@ -32,33 +28,16 @@ washing_impact_data = None
 # Function to process the uploaded Excel file
 @st.cache_data
 def process_excel(file):
-    """Process the uploaded .xlsx file and extract required data."""
     try:
-        # Load Excel content
         excel_content = pd.ExcelFile(file)
-        
-        # Required sheet names
-        required_sheets = ["Fiber Impact Data", "Transport Impact Data", "Washing Data"]
-        if not all(sheet in excel_content.sheet_names for sheet in required_sheets):
-            raise Exception(f"Required sheets are missing. Expected: {', '.join(required_sheets)}")
-        
-        # Load and validate each sheet
         fiber_data = pd.read_excel(file, sheet_name="Fiber Impact Data")
         transport_data = pd.read_excel(file, sheet_name="Transport Impact Data")
         washing_data = pd.read_excel(file, sheet_name="Washing Data")
         
-        # Validate required columns
-        if not {"Fiber Type", "Water (L/kg)", "Energy (MJ/kg)", "Carbon (kg CO2e/kg)"}.issubset(fiber_data.columns):
-            raise Exception("Missing required columns in the 'Fiber Impact Data' sheet.")
-        if not {"Transport Mode", "CFP (kg CO2e/km)"}.issubset(transport_data.columns):
-            raise Exception("Missing required columns in the 'Transport Impact Data' sheet.")
-        if not {"Washing Temperature", "Energy Use (MJ/wash)", "Carbon (kg CO2e/wash)", "Dryer CFP (kg CO2e/cycle)"}.issubset(washing_data.columns):
-            raise Exception("Missing required columns in the 'Washing Data' sheet.")
-        
-        # Convert data into dictionaries for dynamic calculations
+        # Convert into dictionaries for dynamic calculations
         fiber_impact_data = fiber_data.set_index("Fiber Type")[["Water (L/kg)", "Energy (MJ/kg)", "Carbon (kg CO2e/kg)"]].to_dict(orient="index")
         transport_impact_data = transport_data.set_index("Transport Mode")["CFP (kg CO2e/km)"].to_dict()
-        washing_impact_data = washing_data.set_index("Washing Temperature")[["Energy Use (MJ/wash)", "Carbon (kg CO2e/wash)", "Dryer CFP (kg CO2e/cycle)"]].to_dict(orient="index")
+        washing_impact_data = washing_data.set_index("Washing Temperature")[["Water (L/kg)", "Energy Use (MJ/wash)", "Carbon (kg CO2e/wash)", "Dryer CFP (kg CO2e/cycle)"]].to_dict(orient="index")
         
         return fiber_impact_data, transport_impact_data, washing_impact_data
     except Exception as e:
@@ -69,117 +48,114 @@ def process_excel(file):
 if uploaded_file:
     fiber_impact_data, transport_impact_data, washing_impact_data = process_excel(uploaded_file)
 
-# Sidebar for user inputs
-st.sidebar.header("Step 2: Input Product Details")
-
-# Product-specific inputs (static values available before dataset upload)
-product_type = st.sidebar.selectbox("Product Type", ["T-shirt", "Jeans", "Shirt", "Carpet"])
-product_weight = st.sidebar.number_input("Product Weight (kg)", min_value=0.01, step=0.01, value=0.5)
-
-# Fiber composition inputs (static values)
-st.sidebar.subheader("Material Composition (%)")
-cotton_percent = st.sidebar.slider("Conventional Cotton (%)", 0, 100, 50)
-polyester_percent = st.sidebar.slider("Polyester (%)", 0, 100, 30)
-nylon_percent = st.sidebar.slider("Nylon 6 (%)", 0, 100, 10)
-acrylic_percent = st.sidebar.slider("Acrylic (%)", 0, 100, 5)
-viscose_percent = st.sidebar.slider("Viscose (%)", 0, 100, 5)
-
-# Validate composition percentages
-total_percentage = cotton_percent + polyester_percent + nylon_percent + acrylic_percent + viscose_percent
-if total_percentage != 100:
-    st.sidebar.error("The total of all fiber percentages must equal 100%!")
-
-st.sidebar.write(f"Total Material Percentage: {total_percentage}%")
-
-# Lifecycle inputs (dynamic inputs added only if data is available)
-if washing_impact_data and transport_impact_data:
-    st.sidebar.header("Step 3: Input Lifecycle Details")
-    washing_temperature = st.sidebar.selectbox("Washing Temperature", list(washing_impact_data.keys()))
-    washing_cycles = st.sidebar.number_input("Number of Washing Cycles", min_value=0, step=10, value=30)
-    use_dryer = st.sidebar.checkbox("Use Tumble Dryer?")
-    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=50)
-
-    # Function to calculate footprints
-    def calculate_footprints(weight, composition, lifecycle_inputs):
-        try:
-            water_footprint = 0
-            energy_footprint = 0
-            carbon_footprint = 0
-
-            # Fiber contributions
-            for fiber, percentage in composition.items():
-                if fiber in fiber_impact_data:
-                    data = fiber_impact_data[fiber]
-                    fraction = percentage / 100
-                    water_footprint += data["Water (L/kg)"] * weight * fraction
-                    energy_footprint += data["Energy (MJ/kg)"] * weight * fraction
-                    carbon_footprint += data["Carbon (kg CO2e/kg)"] * weight * fraction
-
-            # Transport impacts
-            transport_factor = transport_impact_data.get(lifecycle_inputs["transport_mode"], 0)
-            carbon_footprint += transport_factor * lifecycle_inputs["transport_distance"] * weight
-
-            # Washing impacts
-            washing_data = washing_impact_data.get(lifecycle_inputs["washing_temperature"], {})
-            washing_energy = washing_data.get("Energy Use (MJ/wash)", 0) * lifecycle_inputs["washing_cycles"]
-            washing_carbon = washing_data.get("Carbon (kg CO2e/wash)", 0) * lifecycle_inputs["washing_cycles"]
-            dryer_carbon = washing_data.get("Dryer CFP (kg CO2e/cycle)", 0) if lifecycle_inputs["use_dryer"] else 0
-            energy_footprint += washing_energy
-            carbon_footprint += washing_carbon + (dryer_carbon * lifecycle_inputs["washing_cycles"])
-
-            return water_footprint, energy_footprint, carbon_footprint
-        except Exception as e:
-            st.error(f"Error in calculations: {e}")
-            return None, None, None
-
-    # Composition dictionary
-    composition = {
-        "Conventional Cotton": cotton_percent,
-        "Polyester": polyester_percent,
-        "Nylon 6": nylon_percent,
-        "Acrylic": acrylic_percent,
-        "Viscose": viscose_percent,
+# Sidebar settings
+st.sidebar.header("Optional: Enable Comparison")
+comparison_mode = st.sidebar.checkbox("Enable Comparison Mode")
+
+# Function to calculate footprints
+def calculate_footprints(weight, composition, lifecycle_inputs):
+    water_footprint = 0
+    energy_footprint = 0
+    carbon_footprint = 0
+    
+    for fiber, percentage in composition.items():
+        if fiber in fiber_impact_data:
+            data = fiber_impact_data[fiber]
+            fraction = percentage / 100
+            water_footprint += data["Water (L/kg)"] * weight * fraction
+            energy_footprint += data["Energy (MJ/kg)"] * weight * fraction
+            carbon_footprint += data["Carbon (kg CO2e/kg)"] * weight * fraction
+    
+    transport_factor = transport_impact_data.get(lifecycle_inputs["transport_mode"], 0)
+    carbon_footprint += transport_factor * lifecycle_inputs["transport_distance"] * weight
+
+    washing_data = washing_impact_data.get(lifecycle_inputs["washing_temperature"], {})
+    washing_water = washing_data.get("Water (L/kg)", 0) * lifecycle_inputs["washing_cycles"]
+    washing_energy = washing_data.get("Energy Use (MJ/wash)", 0) * lifecycle_inputs["washing_cycles"]
+    washing_carbon = washing_data.get("Carbon (kg CO2e/wash)", 0) * lifecycle_inputs["washing_cycles"]
+    dryer_carbon = washing_data.get("Dryer CFP (kg CO2e/cycle)", 0) if lifecycle_inputs["use_dryer"] else 0
+    
+    water_footprint += washing_water
+    energy_footprint += washing_energy
+    carbon_footprint += washing_carbon + (dryer_carbon * lifecycle_inputs["washing_cycles"])
+
+    return water_footprint, energy_footprint, carbon_footprint
+
+# Composition input function
+def composition_input():
+    st.subheader("Material Composition (%)")
+    cotton = st.number_input("Conventional Cotton (%)", min_value=0, max_value=100, value=50, step=1)
+    polyester = st.number_input("Polyester (%)", min_value=0, max_value=100, value=30, step=1)
+    nylon = st.number_input("Nylon 6 (%)", min_value=0, max_value=100, value=10, step=1)
+    acrylic = st.number_input("Acrylic (%)", min_value=0, max_value=100, value=5, step=1)
+    viscose = st.number_input("Viscose (%)", min_value=0, max_value=100, value=5, step=1)
+
+    total = cotton + polyester + nylon + acrylic + viscose
+    if total != 100:
+        st.error("Total fiber composition must equal 100%!")
+    return {"Conventional Cotton": cotton, "Polyester": polyester, "Nylon 6": nylon, "Acrylic": acrylic, "Viscose": viscose} if total == 100 else None
+
+# Inputs for lifecycle details
+def lifecycle_input():
+    st.subheader("Lifecycle Details")
+    washing_cycles = st.number_input("Number of Washing Cycles", min_value=0, value=30, step=1)
+    washing_temperature = st.selectbox("Washing Temperature", list(washing_impact_data.keys()))
+    use_dryer = st.checkbox("Use Tumble Dryer?")
+    transport_mode = st.selectbox("Transport Mode", list(transport_impact_data.keys()))
+    transport_distance = st.number_input("Transport Distance (km)", min_value=0, step=10, value=100)
+    return {
+        "washing_cycles": washing_cycles,
+        "washing_temperature": washing_temperature,
+        "use_dryer": use_dryer,
+        "transport_mode": transport_mode,
+        "transport_distance": transport_distance,
     }
 
-    # Perform calculations
-    if total_percentage == 100:
-        water_fp, energy_fp, carbon_fp = calculate_footprints(
-            product_weight,
-            composition,
-            {
-                "transport_mode": transport_mode,
-                "transport_distance": transport_distance,
-                "washing_temperature": washing_temperature,
-                "washing_cycles": washing_cycles,
-                "use_dryer": use_dryer,
-            },
-        )
-
-        if water_fp is not None:
-            st.subheader("Calculated Results")
-            st.markdown(
-                f"""
-                - **Water Footprint**: {water_fp:.2f} liters
-                - **Energy Footprint**: {energy_fp:.2f} MJ
-                - **Carbon Footprint**: {carbon_fp:.2f} kgCO2e
-                """
-            )
-
-            # Visualization
+# Main calculation logic
+if uploaded_file and fiber_impact_data and transport_impact_data and washing_impact_data:
+    if comparison_mode:
+        # Comparison mode enabled
+        st.header("Scenario 1")
+        composition1 = composition_input()
+        lifecycle1 = lifecycle_input()
+        
+        st.header("Scenario 2")
+        composition2 = composition_input()
+        lifecycle2 = lifecycle_input()
+        
+        if composition1 and composition2:
+            water_fp1, energy_fp1, carbon_fp1 = calculate_footprints(1, composition1, lifecycle1)
+            water_fp2, energy_fp2, carbon_fp2 = calculate_footprints(1, composition2, lifecycle2)
+
+            # Display results side by side
+            col1, col2 = st.columns(2)
+            with col1:
+                st.subheader("Scenario 1 Results")
+                st.markdown(f"- **Water Footprint**: {water_fp1:.2f} liters")
+                st.markdown(f"- **Energy Footprint**: {energy_fp1:.2f} MJ")
+                st.markdown(f"- **Carbon Footprint**: {carbon_fp1:.2f} kg CO2e")
+            with col2:
+                st.subheader("Scenario 2 Results")
+                st.markdown(f"- **Water Footprint**: {water_fp2:.2f} liters")
+                st.markdown(f"- **Energy Footprint**: {energy_fp2:.2f} MJ")
+                st.markdown(f"- **Carbon Footprint**: {carbon_fp2:.2f} kg CO2e")
+
+            # Visual comparison
             fig = go.Figure()
-            fig.add_trace(
-                go.Bar(
-                    x=["Water Footprint", "Energy Footprint", "Carbon Footprint"],
-                    y=[water_fp, energy_fp, carbon_fp],
-                    text=[f"{water_fp:.2f} L", f"{energy_fp:.2f} MJ", f"{carbon_fp:.2f} kgCO2e"],
-                    textposition="auto",
-                    marker=dict(color=["blue", "orange", "green"]),
-                )
-            )
-            fig.update_layout(
-                title="Footprint Breakdown", xaxis_title="Footprint Type", yaxis_title="Value"
-            )
+            fig.add_trace(go.Bar(name="Scenario 1", x=["Water", "Energy", "Carbon"], y=[water_fp1, energy_fp1, carbon_fp1]))
+            fig.add_trace(go.Bar(name="Scenario 2", x=["Water", "Energy", "Carbon"], y=[water_fp2, energy_fp2, carbon_fp2]))
+            fig.update_layout(barmode="group", title="Comparison of Scenarios")
             st.plotly_chart(fig)
+    else:
+        # Single calculation
+        composition = composition_input()
+        lifecycle = lifecycle_input()
+
+        if composition:
+            water_fp, energy_fp, carbon_fp = calculate_footprints(1, composition, lifecycle)
+            st.subheader("Results")
+            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")
 else:
-    st.info("Please upload a valid Dataset to begin.")
+    st.info("Please upload a dataset to proceed.")