import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()

def plot_stock_data_with_signals(data):
    """
    Enhanced plotting function to display stock data, indicators, and buy/sell signals with improvements.
    
    Parameters:
    - data (DataFrame): DataFrame containing stock 'Close' prices, optional indicator values, and signals.
    """
    # Create a new figure and set the size.
    plt.figure(figsize=(14, 10))
    
    # Plotting stock prices and EMAs if they exist
    ax1 = plt.subplot(311)  # 3 rows, 1 column, 1st subplot
    data['Close'].plot(ax=ax1, color='black', lw=2., legend=True, label='Close')
    if 'EMA_Short' in data and 'EMA_Long' in data:
        data[['EMA_Short', 'EMA_Long']].plot(ax=ax1, lw=1.5, legend=True)
    ax1.set_title('Stock Price and Indicators')
    
    # Plotting Bollinger Bands if they exist
    if 'BB_Upper' in data and 'BB_Lower' in data:
        ax1.fill_between(data.index, data['BB_Lower'], data['BB_Upper'], color='grey', alpha=0.3, label='Bollinger Bands')
    
    # Highlight buy/sell signals if Combined_Signal column exists
    if 'Combined_Signal' in data:
        buy_signals = data[data['Combined_Signal'] == 'buy']
        sell_signals = data[data['Combined_Signal'] == 'sell']
        ax1.plot(buy_signals.index, buy_signals['Close'], '^', markersize=10, color='g', lw=0, label='Buy Signal')
        ax1.plot(sell_signals.index, sell_signals['Close'], 'v', markersize=10, color='r', lw=0, label='Sell Signal')
    
    ax1.legend()

    # Plotting MACD and Signal Line if they exist
    if 'MACD' in data and 'MACD_Signal_Line' in data:
        ax2 = plt.subplot(312, sharex=ax1)  # Share x-axis with ax1
        data['MACD'].plot(ax=ax2, color='blue', label='MACD', legend=True)
        data['MACD_Signal_Line'].plot(ax=ax2, color='red', label='Signal Line', legend=True)
        ax2.set_title('MACD')
        ax2.legend()

    # Plotting RSI if it exists
    if 'RSI' in data:
        ax3 = plt.subplot(313, sharex=ax1)  # Share x-axis with ax1
        data['RSI'].plot(ax=ax3, color='purple', legend=True, label='RSI')
        ax3.axhline(70, linestyle='--', alpha=0.5, color='red', label='Overbought')
        ax3.axhline(30, linestyle='--', alpha=0.5, color='green', label='Oversold')
        ax3.set_title('RSI')
        ax3.legend()

    # Improving layout, setting x-axis format for better date handling
    plt.tight_layout()
    for ax in [ax1, ax2, ax3]:
        ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
        ax.xaxis.set_major_locator(mdates.AutoDateLocator())
        plt.setp(ax.xaxis.get_majorticklabels(), rotation=45)
    
    plt.show()