Ethan, what code are you referring to? It's always great when you run a backtest and "share" the backtest. Without that context, it's impossible to give good advice. Thanks.

I was referencing the basic example that is in the help section of quantopian. I'll add the code to this post, I used the "code sample" input so idk why its not pretty looking like the other posts I have seen :/

# This example algorithm uses the Moving Average Crossover Divergence (MACD) indicator as a buy/sell signal.

# When the MACD signal less than 0, the stock price is trending down and it's time to sell.  
# When the MACD signal greater than 0, the stock price is trending up it's time to buy.

# Because this algorithm uses the history function, it will only run in minute mode.  
# We will constrain the trading to once per day at market open in this example.

import talib  
import numpy as np  
import pandas as pd

# Setup our variables  
def initialize(context):  
    context.stocks = symbols('MMM', 'SPY', 'GOOG_L', 'PG', 'DIA')  
    context.pct_per_stock = 1.0 / len(context.stocks)  
    # Create a variable to track the date change  
    context.date = None

def handle_data(context, data):  
    todays_date = get_datetime().date()  
    # Do nothing unless the date has changed and its a new day.  
    if todays_date == context.date:  
        return  
    # Set the new date  
    context.date = todays_date  
    # Load historical data for the stocks  
    prices = history(40, '1d', 'price')  
    # Create the MACD signal and pass in the three parameters: fast period, slow period, and the signal.  
    # This is a series that is indexed by sids.  
    macd = prices.apply(MACD, fastperiod=12, slowperiod=26, signalperiod=9)  
    # Iterate over the list of stocks  
    for stock in context.stocks:  
        current_position = context.portfolio.positions[stock].amount  
        # Close position for the stock when the MACD signal is negative and we own shares.  
        if macd[stock] < 0 and current_position > 0:  
            order_target(stock, 0)  
        # Enter the position for the stock when the MACD signal is positive and  
        # our portfolio shares are 0.  
        elif macd[stock] > 0 and current_position == 0:  
            order_target_percent(stock, context.pct_per_stock)  

    record(goog=macd[symbol('GOOG_L')],  
           spy=macd[symbol('SPY')],  
           mmm=macd[symbol('MMM')])  


# Define the MACD function  
def MACD(prices, fastperiod=12, slowperiod=26, signalperiod=9):  
    '''  
    Function to return the difference between the most recent  
    MACD value and MACD signal. Positive values are long  
    position entry signals 

    optional args:  
        fastperiod = 12  
        slowperiod = 26  
        signalperiod = 9

    Returns: macd - signal  
    '''  
    macd, signal, hist = talib.MACD(prices,  
                                    fastperiod=fastperiod,  
                                    slowperiod=slowperiod,  
                                    signalperiod=signalperiod)  
    return macd[-1] - signal[-1]  

I was confused by the MACD sample code too, but I realized that the "MACD" function is actually returning the difference between the two lines you mentioned. This is often visually displayed as the "MACD Histogram", which is what this example function should have been named.

If all you want to know is which line is on top, you can use the example function and test if the value is above zero or below zero. If you want direct access to the MACD and Signal values, you will have to adjust this function, or you can not use a function and simply use the "talib" command that exists inside the example function.

For more information on MACD and how it can be used, check this out:
http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:moving_average_convergence_divergence_macd