namespace QuantConnect {
    /// <summary>
    ///     Represents the LogReturn indicator (LOGR)
    ///      - log returns are useful for identifying price convergence/divergence in a given period
    ///      - logr = log (current price / last price in period)
    /// </summary>
    public class LogReturn : WindowIndicator<IndicatorDataPoint>
    {
        /// <summary>
        ///     Initializes a new instance of the LogReturn class with the specified name and period
        /// </summary>
        /// <param name="name">The name of this indicator</param>
        /// <param name="period">The period of the LOGR</param>
        public LogReturn(string name, int period)
            : base(name, period)
        {
        }

        /// <summary>
        ///     Initializes a new instance of the LogReturn class with the default name and period
        /// </summary>
        /// <param name="period">The period of the SMA</param>
        public LogReturn(int period)
            : base("LOGR" + period, period)
        {
        }

        /// <summary>
        ///     Computes the next value for this indicator from the given state.
        ///      - logr = log (current price / last price in period)
        /// </summary>
        /// <param name="window">The window of data held in this indicator</param>
        /// <param name="input">The input value to this indicator on this time step</param>
        /// <returns>A new value for this indicator</returns>
        protected override decimal ComputeNextValue(IReadOnlyWindow<IndicatorDataPoint> window, IndicatorDataPoint input)
        {
        	decimal valuef = input;

            decimal value0 = !window.IsReady
               	? window[window.Count - 1]
               	: window.MostRecentlyRemoved;
                
            decimal logr = (decimal)Math.Log((double)(valuef / value0));
            
            return logr;
        }
	}
}

using QuantConnect.Algorithm;
using QuantConnect.Indicators;
using QuantConnect.Data;
using QuantConnect.Data.Consolidators;
using QuantConnect.Data.Market;
using System;
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Orders;
using QuantConnect.Indicators;
using QuantConnect.Securities;
using QuantConnect.Brokerages;
using System.Globalization;
using System.Text;
using System.Threading.Tasks;
using System.Collections.Concurrent;

namespace QuantConnect 
{   
    public class BasicTemplateAlgorithm : QCAlgorithm
    {
        //string symbol = "AAPL";
        //private LogReturn logr14;
        //private LogReturn logr30;
        private LogReturn lastLogr;
        
        private DateTime previous;
        Security _security;
        //RegisterIndicator(symbol, logr, null);
        
        SecurityChanges _changes = SecurityChanges.None;
    	private readonly ConcurrentDictionary<Symbol, SelectionData> _averages = new ConcurrentDictionary<Symbol, SelectionData>();
    	
    	private class SelectionData
        {
        	public LogReturn logr14;
        	public LogReturn logr30;
        	
            public SelectionData()
            {
                logr14 = new LogReturn(1);
                logr30 = new LogReturn(2);
            }
		
		
		public decimal ScaledDelta
            {
                get { return (logr14); }
            }

            // updates the EMA50 and EMA100 indicators, returning true when they're both ready
            public bool Update(DateTime time, decimal value)
            {
                return logr14.Update(time, value) && logr30.Update(time, value);
            }
        }
        
        //Initialize the data and resolution you require for your strategy:
        public override void Initialize() 
        {
            //Start and End Date range for the backtest:
            UniverseSettings.Resolution = Resolution.Daily;
            SetStartDate(2016, 2, 23);
            SetEndDate(DateTime.Now.Date.AddDays(-1));
            
            //Cash allocation
            SetCash(5000);
            
            AddUniverse(coarse =>
            {
                return (from stock in coarse
                        // grab th SelectionData instance for this 
                        let avg = _averages.GetOrAdd(stock.Symbol, sym => new SelectionData())
                        // Update returns true when the indicators are ready, so don't accept until they are
                        //where avg.Update(stock.EndTime, stock.Price)
                        // only pick symbols who have their 50 day ema over their 100 day ema
                        where stock.Price < 5 && stock.Price > 2
                        //where stock.Price > stock.Value
                        // prefer symbols with a larger delta by percentage between the two averages
                        // prefer symbols with a larger delta by percentage between the two averages
                        //orderby avg.ScaledDelta
                        // we only need to return the symbol and return 'Count' symbols
                        // we only need to return the symbol and return 'Count' symbols
                        select stock.Symbol).Take(10);
            });
            
        }

        //Data Event Handler: New data arrives here. "TradeBars" type is a dictionary of strings so you can access it by symbol.
        	// "TradeBars" object holds many "TradeBar" objects: it is a dictionary indexed by the symbol:
        	// 
        	//  e.g.  data["MSFT"] data["GOOG"]
        public void OnData(TradeBars data) 
        {   
        	foreach (var stock in _changes.AddedSecurities)
            {
            	_security = stock;
            //Add as many securities as you like. All the data will be passed into the event handler:
            AddSecurity(SecurityType.Equity, _security.Symbol, Resolution.Daily);
            
            //logr14 = new LogReturn(1);
            //logr30 = new LogReturn(2);
            //lastLogr = logr14;
        }
        	if (!Portfolio.HoldStock)
            	{
            		int quantity = (int)Math.Floor(Portfolio.Cash / data[_security.Symbol].Close);
                	Order(_security.Symbol,  100);
            	}
        	// update Indicators
        	/*decimal price = data[_security.Symbol].Close;
        	IndicatorDataPoint datum = new IndicatorDataPoint(data[_security.Symbol].Time, price);
        	Log("datum" + datum);
        	logr14.Update(datum);
        	logr30.Update(datum);
        	
        	Log("log14" + logr14);
        	Log("log30" + logr30);
        	
        	// wait for the indicators to fully initialize
            if (!logr30.IsReady) return;
            
            // stock is moving in an upwards trend
            if (logr14.Current.Value > logr30.Current.Value)
            {
            	if (!Portfolio.HoldStock)
            	{
            		int quantity = (int)Math.Floor(Portfolio.Cash / data[symbol].Close);
                	Order(symbol,  quantity);
            	}
            }
            // stock is moving in a downwards trend
            else if (logr30.Current.Value > logr14.Current.Value)
            {
            	Liquidate(symbol);
            }
            
            Plot(symbol, logr14);
            Plot(symbol, logr30);*/
        }
        public override void OnSecuritiesChanged(SecurityChanges changes)
        {
            _changes = changes;
        }
    }
}