How to use the prophet.analyze.default_analyzers function in prophet

def test_quickstart():
    prophet = Prophet()
    prophet.set_universe(['AAPL', 'XOM'])

    price_generator = YahooData('Adj Close', 'prices', cache_path=CACHE_PATH)
    prophet.register_data_generators(price_generator)
    prophet.set_order_generator(OrderGenerator())
    backtest = prophet.run_backtest(start=datetime(2010, 1, 1),
                                    end=datetime(2014, 11, 21))

    prophet.register_portfolio_analyzers(default_analyzers)
    analysis = prophet.analyze_backtest(backtest)
    assert round(analysis['sharpe'], 10) == 1.0970973495
    assert round(analysis['average_return'], 10) == 0.0010547843
    assert round(analysis['cumulative_return'], 10) == 2.1688171559
    assert round(analysis['volatility'], 10) == 0.0152622562

    today = datetime(2014, 11, 10)
    expected_orders = Orders(Order(symbol='AAPL', shares=100))
    assert prophet.generate_orders(today) == expected_orders

# You will have to adjust the portfolio analyzers
# The homework solution's analyzers start the analysis
# when the first trade is conducted instead of the entire
# duration of the backtest.
prophet = Prophet()
symbols = ["AAPL", "XOM", "SPX"]
prophet.set_universe(symbols)

prophet.register_data_generators(YahooCloseData(),
                                 BollingerData(),
                                 BollingerEventStudy())
prophet.set_order_generator(OrderGenerator())
backtest = prophet.run_backtest(start=dt.datetime(2008, 1, 1),
                                end=dt.datetime(2009, 12, 31), lookback=20)

prophet.register_portfolio_analyzers(default_analyzers)
analysis = prophet.analyze_backtest(backtest)
print(analysis)
# +----------------------------------------+
# | sharpe            |    -0.851247401074 |
# | average_return    | -2.04368321273e-07 |
# | cumulative_return |          -0.000103 |
# | volatility        |  3.81116761073e-06 |
# +----------------------------------------+


# Generate orders for your to execute today
# Using Nov, 10 2014 as the date because there might be no data for today's
# date (Market might not be open) and we don't want a examples to fail.
today = dt.datetime(2009, 12, 31)
print(prophet.generate_orders(today, lookback=20))

if (prices.loc[timestamp, symbol] * 100) < cash:
            orders.add_order(symbol, 100)

        return orders


prophet = Prophet()
prophet.set_universe(['AAPL', 'XOM'])

price_generator = YahooData('Adj Close', 'prices')

prophet.register_data_generators(price_generator)
prophet.set_order_generator(OrderGenerator())
backtest = prophet.run_backtest(start=datetime(2010, 1, 1))

prophet.register_portfolio_analyzers(default_analyzers)
analysis = prophet.analyze_backtest(backtest)
print(analysis)
# +--------------------------------------+
# | sharpe            |    1.09754359611 |
# | average_return    | 0.00105478425027 |
# | cumulative_return |         2.168833 |
# | volatility        |  0.0152560508189 |
# +--------------------------------------+

# Generate orders for you to execute today
# Using Nov, 10 2014 as the date because there might be no data for today's
# date (Market might not be open) and we don't want examples to fail.
today = datetime(2014, 11, 10)
print(prophet.generate_orders(today))
# Orders[Order(symbol='AAPL', shares=100)]