python-code

import pandas as pd
import matplotlib.pyplot as plt
import argparse
import os

# Load and process a CSV file to compute and visualize SFRI

def load_sfri_data(file_path):
    if not os.path.exists(file_path):
        raise FileNotFoundError(f"File not found: {file_path}")
    
    df = pd.read_csv(file_path, parse_dates=['Open Time'])
    df.set_index('Open Time', inplace=True)

    # Ensure correct data types
    df['Close'] = df['Close'].astype(float)
    if 'SFRI' not in df.columns:
        if {'High', 'Low', 'Volume'}.issubset(df.columns):
            df['Price Change'] = df['Close'].diff()
            df['Spread'] = df['High'] - df['Low']
            df['Effective Flow'] = df['Volume'] * df['Price Change'].abs()
            df['SFRI'] = (df['Price Change'].abs() * df['Spread']) / (df['Effective Flow'] + 1e-6)
            df['SFRI'] *= 10000  # scale for visibility
        else:
            raise ValueError("CSV must contain either SFRI or High, Low, Volume columns to calculate it.")
    else:
        df['SFRI'] = df['SFRI'].astype(float)

    return df

# Plot SFRI values
def plot_sfri(df, title="Systemic Flow Resistance Index (SFRI)", output_file=None):
    plt.figure(figsize=(12, 6))
    plt.plot(df.index, df['SFRI'], label='SFRI', linewidth=2)
    plt.title(title)
    plt.xlabel("Time")
    plt.ylabel("SFRI (scaled)")
    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    if output_file:
        plt.savefig(output_file)
        print(f"Plot saved to {output_file}")
    else:
        plt.show()

# Main execution
if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Visualize or calculate the Systemic Flow Resistance Index (SFRI).")
    parser.add_argument("--input", required=True, help="Path to input CSV file")
    parser.add_argument("--output", help="Optional path to save the plot as an image file")
    args = parser.parse_args()

    df = load_sfri_data(args.input)
    print("Latest SFRI values:")
    print(df[['Close', 'SFRI']].tail())
    plot_sfri(df, output_file=args.output)