cfacm

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

def load_data(csv_file_path):
    """Load carbon emission data from a CSV file."""
    df = pd.read_csv(csv_file_path)
    return df

def calculate_overlaps(df):
    """Calculate overlapping emission points based on atomic weight and emission value."""
    atomic_weights = df['atomic_weight'].values
    emissions = df['emission_value'].values
    
    # Normalize emission values for comparison
    normalized_emissions = (emissions - np.min(emissions)) / (np.max(emissions) - np.min(emissions))
    
    # Define a threshold for overlap
    threshold = 0.5
    overlapping_points = [(aw, em) for aw, em in zip(atomic_weights, normalized_emissions) if em > threshold]
    
    return overlapping_points

def visualize_points(points):
    """Visualize the overlapping points in a 2D scatter plot."""
    atomic_weights, emissions = zip(*points)
    
    plt.scatter(atomic_weights, emissions, c='blue', label='Overlapping Points')
    plt.xlabel('Atomic Weight')
    plt.ylabel('Normalized Emission Value')
    plt.title('Carbon Emission Overlapping Points')
    plt.legend()
    plt.grid(True)
    plt.show()

def visualize_3d_points(points):
    """Visualize the overlapping points in a 3D scatter plot."""
    atomic_weights, emissions, extra_dimension = zip(*points)  # Assuming 3rd dimension data
    
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')
    ax.scatter(atomic_weights, emissions, extra_dimension, c='green', label='3D Overlapping Points')
    
    ax.set_xlabel('Atomic Weight')
    ax.set_ylabel('Normalized Emission Value')
    ax.set_zlabel('Extra Dimension')
    ax.set_title('3D Mapping of Carbon Emission Points')
    ax.legend()
    plt.show()

def main():
    # Load data
    csv_file_path = 'carbon_emissions.csv'  # Path to your CSV file
    data = load_data(csv_file_path)
    
    # Calculate overlaps
    overlapping_points = calculate_overlaps(data)
    
    # Visualize 2D points
    visualize_points(overlapping_points)
    
    # Add extra dimension for 3D visualization (example)
    extra_points = [(aw, em, np.sin(aw)) for aw, em in overlapping_points]  # Dummy extra dimension
    visualize_3d_points(extra_points)

if __name__ == "__main__":
    main()