I'm working on a strategy that calculates the RSI of closing prices of ETFs.   I am going to use the (extensive!) indicators library to my make work a little simpler.   For example, in the code snippet below, I can get the RSI of the close price of SPY.

One question I have is, how do I include the current price into the calculation being done in the indicator?  If I understand the docs correctly, the 3-period RSI calculation being done below only includes data for T-3, T-2, and T-1  (T being today).   As I am estimating the close and am executing right before it, I would like my RSI calculation to include data for T, T-1 and T-2. 

Basically, my question is:
Is there an easy way to get indicators to include the current price data along with historical data in daily algorithms that execute at the close?
 

from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Indicators import *

class Strategy(QCAlgorithm):

self.SetCash(100000)


self.SetStartDate(2017, 12, 1)
self.SetEndDate(2017, 12, 20)

self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage, AccountType.Margin)

self.etfs = ['SPY']
self.rsi_data = {}

for etf in self.etfs:
self.AddEquity(etf, Resolution.Daily)
self.Securities[etf].FeeModel = ConstantFeeTransactionModel(0)
self.Securities[etf].SlippageModel = ConstantSlippageModel(0)

#add indicators here
self.rsi_data[etf] = self.RSI(etf, 3)

self.Schedule.On(self.DateRules.EveryDay('SPY'), self.TimeRules.BeforeMarketClose('SPY', 1), Action(self.Rebalance))


def OnData(self, slice):
pass

def Rebalance(self):

for etf in self.etfs:
if self.rsi_data[etf].IsReady:
self.Log(str(self.rsi_data[etf]))