app.py

import streamlit as st
background_css = """
<style>
body {
    background-image: url("https://t4.ftcdn.net/jpg/08/51/51/19/360_F_851511987_yt28bGDYsX0iBoB7mSbyfMg4IABaCeQx.jpg");
    background-size: cover;
    background-repeat: no-repeat;
    background-attachment: fixed;
}
</style>
"""


# Define categories with detailed options, ranges, weights, and scoring criteria
categories = {
    "Window-to-Wall Ratio (WWR %)": {"range": (10, 80), "weight": 2, "criteria": [(20, 30), (10, 40), (0, 100)], "suggestion": "Consider reducing WWR to 20-30% for optimal cooling."},
    "Building Orientation (Degrees)": {"range": (0, 180), "weight": 2, "criteria": [(0, 45),(315, 360),(90,270)], "suggestion": "Align building orientation between 0-45° for better sun control."},
    "Shading Devices (Coverage %)": {"range": (0, 100), "weight": 2, "criteria": [(70, 100), (50, 69), (0, 49)], "suggestion": "Increase shading device coverage to 70-100% for effective sun protection."},
    "Roof Reflectivity (Color/Material)": {
        "options": {"Cool White": 5, "Light Grey": 3, "Dark Grey": 1},
        "weight": 1.6,
        "suggestion": "Opt for cool white roofing materials for maximum heat reflectivity."
    },
    "Wall Reflectivity (Color/Material)": {
        "options": {"Light Colors (White/Beige)": 5, "Medium Colors (Grey)": 3, "Dark Colors (Black/Brown)": 1},
        "weight": 1.6,
        "suggestion": "Use light-colored wall materials to improve thermal reflectivity."
    },
    "Tree Coverage (%)": {"range": (0, 100), "weight": 2, "criteria": [(50, 100), (30, 49), (0, 29)], "suggestion": "Increase tree coverage to 50% or more for enhanced shading and cooling."},
    "Pavement Material": {
        "options": {"Cool Pavement (Reflective)": 5, "Standard Concrete": 3, "Asphalt": 1},
        "weight": 1,
        "suggestion": "Consider using reflective cool pavements to reduce heat absorption."
    },
    "Cross Ventilation Efficiency (%)": {"range": (0, 100), "weight": 2, "criteria": [(70, 100), (50, 69), (0, 49)], "suggestion": "Ensure at least 70% efficiency in cross ventilation for optimal airflow."},
    "Stack Ventilation Efficiency (%)": {"range": (0, 100), "weight": 1, "criteria": [(50, 100), (30, 49), (0, 29)], "suggestion": "Improve stack ventilation efficiency to above 50% for enhanced cooling."},
    "Outdoor Shaded Spaces (%)": {"range": (0, 100), "weight": 1, "criteria": [(50, 100), (30, 49), (0, 29)], "suggestion": "Increase outdoor shaded spaces to at least 50% for better outdoor comfort."},
    "Ventilated or Perforated Facades (%)": {"range": (0, 100), "weight": 1, "criteria": [(70, 100), (50, 69), (0, 49)], "suggestion": "Add more ventilated or perforated facades to reach 70% or higher."},
    "Green Roof or Wall Coverage (%)": {"range": (0, 100), "weight": 1, "criteria": [(50, 100), (30, 49), (0, 29)], "suggestion": "Consider adding green roof or wall coverage of 50% or more for natural cooling."},
    "Ceiling Fans and Ventilation (%)": {"range": (0, 100), "weight": 1, "criteria": [(70, 100), (50, 69), (0, 49)], "suggestion": "Increase ceiling fan coverage to at least 70% for effective indoor cooling."},
}

def determine_score(value, criteria):
    """Determine score based on value and criteria ranges or options."""
    if isinstance(criteria, list):  # Range-based scoring
        if criteria[0][0] <= value <= criteria[0][1]:
            return 5  # Excellent
        elif criteria[1][0] <= value <= criteria[1][1]:
            return 3  # Good
        else:
            return 1  # Poor
    elif isinstance(criteria, dict):  # Option-based scoring
        return criteria.get(value, 1)  # Default to 1 (Poor) if value not in options

# Title and description
st.title("Building Design Scoring System for Hot and Humid Climates with Improvement Suggestions")
st.sidebar.title("Inputs")

# Initialize total score and suggestions
total_score = 0
suggestions = []

# Collect scores based on real input values and dropdowns
for category, details in categories.items():
    if "range" in details:  # Slider input
        min_val, max_val = details["range"]
        value = st.sidebar.slider(f"{category} (Range: {min_val}-{max_val})", min_value=float(min_val), max_value=float(max_val), value=(min_val+max_val)/2)
        score = determine_score(value, details["criteria"])
    elif "options" in details:  # Dropdown input
        options = list(details["options"].keys())
        selected_option = st.sidebar.selectbox(f"{category} - Select Option", options)
        score = determine_score(selected_option, details["options"])
    
    # Append suggestion if score is below 5
    if score < 5 and "suggestion" in details:
        suggestions.append((category, details["suggestion"]))

    # Calculate weighted score
    weighted_score = score * details["weight"]
    total_score += weighted_score

# Display the final score and rating
st.subheader("Total Score")
st.write(f"**{total_score:.2f} / 100**")

# Rating system
if total_score >= 80:
    st.success("Rating: Excellent – Highly suitable for hot and humid climates.")
elif total_score >= 60:
    st.info("Rating: Good – Effective, though with room for improvement.")
elif total_score >= 40:
    st.warning("Rating: Fair – Provides some cooling but lacks in key areas.")
else:
    st.error("Rating: Poor – Requires significant improvements for climate adaptability.")

# Display suggestions for improvement
st.subheader("Suggestions for Improvement")
if suggestions:
    st.write("Consider the following modifications to improve your building design:")
    for category, suggestion in suggestions:
        st.write(f"- **{category}**: {suggestion}")
else:
    st.write("Your design is optimized for the climate!")