# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Common")

from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Indicators import *
from QuantConnect.Data.Market import TradeBar
import decimal as d

### <summary>
### Using rolling windows for efficient storage of historical data; which automatically clears after a period of time.
### </summary>
### <meta name="tag" content="using data" />
### <meta name="tag" content="history and warm up" />
### <meta name="tag" content="history" />
### <meta name="tag" content="warm up" />
### <meta name="tag" content="indicators" />
### <meta name="tag" content="rolling windows" />
class RollingWindowAlgorithm(QCAlgorithm):

    def Initialize(self):
        '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''

        self.SetStartDate(2000,10, 7)  #Set Start Date
        self.SetEndDate(2001,3,11)    #Set End Date
        self.SetCash(100000)           #Set Strategy Cash
        # Find more symbols here: http://quantconnect.com/data
        
        self.symbol = "NVDA"
        
        self.AddEquity(self.symbol, Resolution.Daily)

        # Creates a Rolling Window indicator to keep the 2 TradeBar
        self._bbupwindow = RollingWindow[d.Decimal](20)    # For other security types, use QuoteBar
        self._bbmidwindow = RollingWindow[d.Decimal](20)    # For other security types, use QuoteBar
        self._bblowindow = RollingWindow[d.Decimal](20)    # For other security types, use QuoteBar
        
        self._keltnerupwindow = RollingWindow[d.Decimal](20)    # For other security types, use QuoteBar
        self._keltnermidwindow = RollingWindow[d.Decimal](20)    # For other security types, use QuoteBar
        self._keltnerlowindow = RollingWindow[d.Decimal](20)    # For other security types, use QuoteBar

        self._bb = self.BB(self.symbol, 20, 1,  MovingAverageType.Exponential)
        self._keltner = self.KCH(self.symbol, 20, d.Decimal(1.51), MovingAverageType.Exponential)  #its working NOW !!! 
        
        
        
 
    def OnData(self, data):
        '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''
        
        self._bbupwindow.Add(self._bb.UpperBand.Current.Value)
        self._bbmidwindow.Add(self._bb.MiddleBand.Current.Value)
        self._bblowindow.Add(self._bb.LowerBand.Current.Value)
        
        self._keltnerupwindow.Add(self._keltner.UpperBand.Current.Value)
        self._keltnermidwindow.Add(self._keltner.MiddleBand.Current.Value)
        self._keltnerlowindow.Add(self._keltner.LowerBand.Current.Value)

        if not self._keltner.IsReady: return 
    
        #self.Log("{0} ... {1} ... {2}".format(self._bb.UpperBand.Current.Value, self._bb.MiddleBand.Current.Value, self._bb.LowerBand.Current.Value))
        #self.Log("{0} ... {1} ... {2}".format(self._keltner.UpperBand.Current.Value, self._keltner.MiddleBand.Current.Value, self._keltner.LowerBand.Current.Value))
        
        curbbupperband = self._bbupwindow[0]                     # Current bar had index zero.
        prevbbupperband = self._bbupwindow[1]                     # Past bar has index one.
        self.Log("bb: {0} -> {1}".format(prevbbupperband, curbbupperband))

        curkeltnerlowerband = self._keltnerlowindow[0]                     # Current SMA had index zero.
        lastkeltnerlowerband = self._keltnerlowindow[self._keltnerlowindow.Count-1]   # Oldest SMA has index of window count minus 1.
        self.Log("keltner:   {0} -> {1}".format(lastkeltnerlowerband, curkeltnerlowerband))