using QuantConnect.Indicators.CandlestickPatterns;

// Demonstrate a crash caused by using HMA in RSI.

namespace QuantConnect.Algorithm.CSharp
{

    public class Algo : QCAlgorithm
    {
		public static Algo Self; 
        private int WarmupPeriods = 200;
        Indicator Rsi = new RelativeStrengthIndex("foo", 14, MovingAverageType.Hull);
  		bool First = false;
        
        public override void Initialize()
        {
            SetStartDate(2018, 4, 9);  //Set Start Date
            SetEndDate(2018, 4, 25);    //Set End Date
            AddForex("GBPUSD", Resolution.Minute);
       }

        public override void OnData(Slice data)
        {
        	try {
       			var q = data.QuoteBars["GBPUSD"];
        		if (First) {
	        		var h = History<QuoteBar>(q.Symbol, WarmupPeriods+1, Resolution.Minute);  // +1 because we often get 1 less record returned than we expect.
	        		if (h.Count() < WarmupPeriods) throw new Exception(string.Format("WarmIndicators: not enough history, expected {0} got {1} for {2} {3}", WarmupPeriods, h.Count(), q.Symbol.ToString(), q.Time));
					foreach (var q2 in h) { 
						IndicatorDataPoint dp2 = new IndicatorDataPoint(q2.Time, q2.Value);
						Rsi.Update(dp2); 
					}
					First = false;
        		}
        		
				IndicatorDataPoint dp = new IndicatorDataPoint(q.Time, q.Value);
	        	Rsi.Update(dp);	

        	}
        	catch (Exception ex) {
        		Log(ex.StackTrace);
        		throw;
        	}
        }
        

    }
    
}

/*
 * 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.
*/
namespace QuantConnect.Algorithm.CSharp
{
    /// <summary>
    /// Represents the  Relative Strength Index (RSI) developed by K. Welles Wilder.
    /// You can optionally specified a different moving average type to be used in the computation
    /// </summary>
    public class MyRelativeStrengthIndex : Indicator
    {
        private IndicatorDataPoint previousInput;

        /// <summary>
        /// Gets the type of indicator used to compute AverageGain and AverageLoss
        /// </summary>
        public MovingAverageType MovingAverageType { get; private set; }

        /// <summary>
        /// Gets the EMA for the down days
        /// </summary>
        public IndicatorBase<IndicatorDataPoint> AverageLoss { get; private set; }

        /// <summary>
        /// Gets the indicator for average gain
        /// </summary>
        public IndicatorBase<IndicatorDataPoint> AverageGain { get; private set; }

        /// <summary>
        /// Initializes a new instance of the RelativeStrengthIndex class with the specified name and period
        /// </summary>
        /// <param name="period">The period used for up and down days</param>
        /// <param name="movingAverageType">The type of moving average to be used for computing the average gain/loss values</param>
        public MyRelativeStrengthIndex(int period, MovingAverageType movingAverageType = MovingAverageType.Wilders)
            : this("RSI" + period, period, movingAverageType)
        {
        }

        /// <summary>
        /// Initializes a new instance of the RelativeStrengthIndex class with the specified name and period
        /// </summary>
        /// <param name="name">The name of this indicator</param>
        /// <param name="period">The period used for up and down days</param>
        /// <param name="movingAverageType">The type of moving average to be used for computing the average gain/loss values</param>
        public MyRelativeStrengthIndex(string name, int period, MovingAverageType movingAverageType = MovingAverageType.Wilders)
            : base(name)
        {
            MovingAverageType = movingAverageType;
            AverageGain = movingAverageType.AsIndicator(name + "Up", period);
            AverageLoss = movingAverageType.AsIndicator(name + "Down", period);
        }

        /// <summary>
        /// Gets a flag indicating when this indicator is ready and fully initialized
        /// </summary>
        public override bool IsReady
        {
            get { return AverageGain.IsReady && AverageLoss.IsReady; }
        }

        /// <summary>
        /// Computes the next value of this indicator from the given state
        /// </summary>
        /// <param name="input">The input given to the indicator</param>
        /// <returns>A new value for this indicator</returns>
        protected override decimal ComputeNextValue(IndicatorDataPoint input)
        {
            decimal gain = 0m;
            decimal loss = 0m;
            
            if (previousInput != null && input.Value >= previousInput.Value)
            {
                gain = input.Value - previousInput.Value;
            }
            else if (previousInput != null && input.Value < previousInput.Value)
            {
                loss = previousInput.Value - input.Value;
            }

			decimal beforeGain = AverageGain;
			decimal beforeLoss = AverageLoss;
            AverageGain.Update(input.Time, gain);
            AverageLoss.Update(input.Time, loss);
			decimal afterGain = AverageGain;
			decimal afterLoss = AverageLoss;
            Algo.Self.Log(string.Format("this gain {0} before gain {1} after gain {2} this loss {3} before loss {4} after loss {5}", beforeGain, gain, AverageGain, beforeLoss, AverageLoss, afterLoss));
            previousInput = input;
            if (AverageLoss == 0m)
            {
                // all up days is 100
                return 100m;
            }

            var rs = AverageGain / AverageLoss;
            Algo.Self.Log(string.Format("this gain {0} this loss {1} average gain {2} ave loss {3} rs {4}", gain, loss, AverageGain, AverageLoss, rs));
            return 100m - (100m / (1 + rs));
        }

        /// <summary>
        /// Resets this indicator to its initial state
        /// </summary>
        public override void Reset()
        {
            AverageGain.Reset();
            AverageLoss.Reset();
            base.Reset();
        }
    }
}