Is it possible to get historical indicators in the algorithm environment?  In the research environment the following works:

import datetime as dt
import QuantConnect.Indicators as qci

start_date = dt.datetime(2019, 6, 1)
end_date = dt.datetime(2019, 12, 31)

qb = QuantBook()
spy = qb.AddEquity("SPY")
history = qb.History(qb.Securities.Keys, 360, Resolution.Daily)

bb = qci.BollingerBands(30, 2)
bb_df = qb.Indicator(bb, spy.Symbol, start_date, end_date, Resolution.Daily)
bb_df.drop('standarddeviation', 1).plot()

I would now like to get historical indicators in a pandas dataframe during backtest initialisation.  In the algo environment I set:

qb = self

And do the same as above (without the plot), however I get the following error:

During the algorithm initialization, the following exception has occurred: AttributeError : 'MyAlgo' object has no attribute 'Indicator'
at Initialize in main.py:line 54
at calc_indicators in main.py:line 92
AttributeError : 'MyAlgo' object has no attribute 'Indicator'

Any help would be appreciated.  Thanks!