main.py

"""
main.py

This script runs the PoLN tokenomics simulation and outputs the results.
It reads the configuration parameters from 'config.json', runs the simulation,
saves the results to CSV files, generates plots, and prints a summary of results.

Usage:
    python main.py
"""

import json
import os
import matplotlib.pyplot as plt
from simulation import simulate


def main():
    """
    Main function to execute the tokenomics simulation and handle output.
    """
    # Load configuration
    with open('config.json', 'r', encoding='utf-8') as config_file:
        config = json.load(config_file)

    # Improved directory creation
    os.makedirs('results', exist_ok=True)

    # Run simulations for each specified duration
    for years in config['simulation_years']:
        simulation_months = years * config['months_per_year']
        df = simulate(simulation_months, config)

        # Save results to CSV
        csv_filename = f'results/simulation_data_{years}yrs.csv'
        df.to_csv(csv_filename, index=False)

        # Plot results in landscape orientation
        plt.figure(figsize=(20, 10))  # Wider figure for landscape orientation

        # Subplot arrangement: 2 rows x 3 columns
        # Subplot 1: Token Price
        plt.subplot(2, 3, 1)
        plt.plot(df['Month'], df['Token Price'],
                 label='Token Price', color='blue')
        plt.title(f'Token Price Over {years} Years')
        plt.xlabel('Month')
        plt.ylabel('Token Price ($)')
        plt.grid(True)
        plt.legend()

        # Subplot 2: Circulating Supply and Total Burnt Tokens
        plt.subplot(2, 3, 2)
        plt.plot(df['Month'], df['Circulating Supply'],
                 label='Circulating Supply', color='orange')
        plt.plot(df['Month'], df['Total Burnt Tokens'],
                 label='Total Burnt Tokens', color='green')
        plt.title('Circulating Supply and Total Burnt Tokens')
        plt.xlabel('Month')
        plt.ylabel('Tokens')
        plt.grid(True)
        plt.legend()

        # Subplot 3: Market Sentiment Index (MSI)
        plt.subplot(2, 3, 3)
        plt.plot(df['Month'], df['Market Sentiment Index'],
                 label='Market Sentiment Index', color='purple')
        plt.title(f'Market Sentiment Index Over {years} Years')
        plt.xlabel('Month')
        plt.ylabel('MSI')
        plt.grid(True)
        plt.legend()

        # Subplot 4: Missions Conducted
        plt.subplot(2, 3, 4)
        plt.plot(df['Month'], df['Missions'],
                 label='Missions Conducted', color='red')
        plt.title('Missions Conducted')
        plt.xlabel('Month')
        plt.ylabel('Number of Missions')
        plt.grid(True)
        plt.legend()

        # Subplot 5: DAO Treasury
        plt.subplot(2, 3, 5)
        plt.plot(df['Month'], df['DAO Treasury'],
                 label='DAO Treasury', color='cyan')
        plt.title('DAO Treasury')
        plt.xlabel('Month')
        plt.ylabel('Tokens')
        plt.grid(True)
        plt.legend()

        # Subplot 6: Initiator Rewards Pool
        plt.subplot(2, 3, 6)
        plt.plot(df['Month'], df['Initiator Rewards Pool'],
                 label='Initiator Rewards Pool', color='brown')
        plt.title('Initiator Rewards Pool')
        plt.xlabel('Month')
        plt.ylabel('Tokens')
        plt.grid(True)
        plt.legend()

        # Adjust layout
        plt.tight_layout()

        # Save plot
        plot_filename = f'results/simulation_{years}yrs.png'
        plt.savefig(plot_filename)
        plt.close()

        # Interpretation of Results
        print(f"\n--- \033[7;32mInterpretation after {years} years\033[0m ---")
        final_price = df['Token Price'].iloc[-1]
        final_supply = df['Circulating Supply'].iloc[-1]
        final_total_supply = df['Total Supply'].iloc[-1]
        total_burnt = df['Total Burnt Tokens'].iloc[-1]
        dao_balance = df['DAO Treasury'].iloc[-1]
        print(f"Final Token Price: ${final_price:.2f}")
        print(f"Final Total Supply: {final_total_supply:,.2f} tokens")
        print(f"Final Circulating Supply: {final_supply:,.2f} tokens")
        print(f"Total Tokens Burnt: {total_burnt:,.2f} tokens")
        print(f"DAO Treasury Balance: {dao_balance:,.2f} tokens")
        print("----------------------------------------")


if __name__ == '__main__':
    main()