using System;
using System.Linq;
using QuantConnect.Indicators;
using QuantConnect.Models;

namespace QuantConnect.Algorithm.Examples
{
    /// <summary>
    /// 
    /// QuantConnect University: EMA + SMA Cross
    ///
    /// In this example we look at the canonical 20/50 day moving average cross. This algorithm
    /// will go long when the 20 crosses above the 50 and will liquidate when the 20 crosses
    /// back below the 50.
    
    // -------VATS CHANGES -----------
    // 1) Intraday - Minute
    // 2) 20/50
    // -------VATS CHANGES -----------
    
    /// </summary>
    public class QCUMovingAverageCross : QCAlgorithm
    {
        private const string Symbol = "USO";

        private ExponentialMovingAverage fast;
        private ExponentialMovingAverage slow;
        private SimpleMovingAverage[] ribbon;

        
         
         //Initialize the data and resolution you require for your strategy:
   

        public override void Initialize()
        {

            SetStartDate(2013, 01, 01);
            SetEndDate(2015, 07, 15);
			SetCash(10000);

            // request SPY data with minute resolution
            AddSecurity(SecurityType.Equity, Symbol, Resolution.Hour);

            // create a 15 day exponential moving average
            fast = EMA(Symbol, 1, Resolution.Hour);

            // create a 30 day exponential moving average
            slow = EMA(Symbol, 20, Resolution.Hour);
            SetRunMode(RunMode.Series);

            // the following lines produce a simple moving average ribbon, this isn't
            // actually used in the algorithm's logic, but shows how easy it is to make
            // indicators and plot them!
            
            // note how we can easily define these indicators to receive hourly data
            int ribbonCount = 7;
            int ribbonInterval = 15*8;
            ribbon = new SimpleMovingAverage[ribbonCount];
            
            for(int i = 0; i < ribbonCount; i++) 
            {
                ribbon[i] = SMA(Symbol, (i + 1)*ribbonInterval, Resolution.Hour);
            }
        }

        private DateTime previous;
        public void OnData(TradeBars data)
        {
            // a couple things to notice in this method:
            //  1. We never need to 'update' our indicators with the data, the engine takes care of this for us
            //  2. We can use indicators directly in math expressions
            //  3. We can easily plot many indicators at the same time

            // wait for our slow ema to fully initialize
            
            
            if (!slow.IsReady) return;

            // only once per day 
            // Commented the following line to simulate intraday - Vats
            //if (previous.Date == data.Time.Date) return;

            // define a small tolerance on our checks to avoid bouncing
            const decimal tolerance = 0.00015m;
            var holdings = Portfolio[Symbol].Quantity;
           
            
            // we only want to go long if we're currently short or flat
            if (holdings <= 0)
            {
                // if the fast is greater than the slow, we'll go long
                if (fast > slow * (1 + tolerance))
                {
                    // write qty to log for debug purposes. comment after debugging 
                    //Log("QTY >> " + Portfolio[Symbol].Quantity);
                    Log("BUY  >> " + Securities[Symbol].Price);
                    SetHoldings(Symbol, 1.0);
                }
            }

            // we only want to liquidate if we're currently long
            // if the fast is less than the slow we'll liquidate our long
            if (holdings > 0 && fast < slow)
            {
                Log("FLATTEN >> " + Securities[Symbol].Price);
                // write qty to log for debug purposes. comment after debugging 
                //Log("QTY >> " + Portfolio[Symbol].Quantity);
                Liquidate(Symbol);
                
                Log("SHORT >> " + Securities[Symbol].Price);
                SetHoldings(Symbol, -1.0);
            }

            Plot(Symbol, "Price", data[Symbol].Price);
            Plot("Ribbon", "Price", data[Symbol].Price);
            
            // easily plot indicators, the series name will be the name of the indicator
            Plot(Symbol, fast, slow);
            Plot("Ribbon", ribbon);

            previous = data.Time;
        }
    }
}