e294b3c3e2
- Adding new `AlgorithmSettings` Min and Max absolute portfolio target percentage - Adding new `PortfolioConstructionModel.FilterInvalidInsightMagnitude()` helper method that will be used by the `BlackLitterman` and `MeanVariance` optiomization portfolio construction models to skip insights with extreme magnitudes that will cause exceptions - `PortfolioTarget.Percentage()` will now verify requested percent is withing the settings values
216 lines
9.2 KiB
C#
216 lines
9.2 KiB
C#
/*
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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*
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*/
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using System;
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using System.Collections.Generic;
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using QuantConnect.Algorithm.Framework.Alphas;
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using QuantConnect.Algorithm.Framework.Alphas.Analysis;
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using QuantConnect.Interfaces;
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using QuantConnect.Logging;
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namespace QuantConnect.Lean.Engine.Alphas
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{
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/// <summary>
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/// Manages alpha charting responsibilities.
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/// </summary>
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public class ChartingInsightManagerExtension : IInsightManagerExtension
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{
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/// <summary>
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/// The string name used for the Alpha Assets chart
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/// </summary>
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public const string AlphaAssets = "Alpha Assets";
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private readonly bool _liveMode;
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private readonly StatisticsInsightManagerExtension _statisticsManager;
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private const int BacktestChartSamples = 1000;
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private DateTime _lastInsightCountSampleDateUtc;
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private DateTime _nextChartSampleAlgorithmTimeUtc;
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private readonly Chart _totalInsightCountPerSymbolChart = new Chart(AlphaAssets); // Heatmap chart
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private readonly Series _totalInsightCountSeries = new Series("Count", SeriesType.Bar, "#");
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private int _dailyCount;
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private readonly Dictionary<Symbol, int> _totalInsightCountPerSymbol = new Dictionary<Symbol, int>();
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private readonly Dictionary<InsightScoreType, Series> _insightScoreSeriesByScoreType = new Dictionary<InsightScoreType, Series>();
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/// <summary>
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/// Gets or sets the interval at which alpha charts are updated. This is in realtion to algorithm time.
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/// </summary>
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protected TimeSpan SampleInterval { get; set; } = TimeSpan.FromMinutes(1);
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/// <summary>
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/// Initializes a new instance of the <see cref="ChartingInsightManagerExtension"/> class
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/// </summary>
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/// <param name="algorithm">The algorithm instance. This is only used for adding the charts
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/// to the algorithm. We purposefully do not save a reference to avoid potentially inconsistent reads</param>
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/// <param name="statisticsManager">Statistics manager used to access mean population scores for charting</param>
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public ChartingInsightManagerExtension(IAlgorithm algorithm, StatisticsInsightManagerExtension statisticsManager)
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{
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_statisticsManager = statisticsManager;
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_liveMode = algorithm.LiveMode;
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// chart for average scores over sample period
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var scoreChart = new Chart("Alpha");
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foreach (var scoreType in InsightManager.ScoreTypes)
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{
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var series = new Series($"{scoreType} Score", SeriesType.Line, "%");
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scoreChart.AddSeries(series);
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_insightScoreSeriesByScoreType[scoreType] = series;
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}
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// chart for insight count over sample period
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var insightCount = new Chart("Insight Count");
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insightCount.AddSeries(_totalInsightCountSeries);
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algorithm.AddChart(scoreChart);
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algorithm.AddChart(insightCount);
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algorithm.AddChart(_totalInsightCountPerSymbolChart);
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}
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/// <summary>
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/// Invokes the manager at the end of the time step.
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/// Samples and plots insight counts and population score.
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/// </summary>
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/// <param name="frontierTimeUtc">The current frontier time utc</param>
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public void Step(DateTime frontierTimeUtc)
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{
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// sample insight/symbol counts each utc day change
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if (frontierTimeUtc.Date > _lastInsightCountSampleDateUtc)
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{
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_lastInsightCountSampleDateUtc = frontierTimeUtc.Date;
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// add sum of daily insight counts to the total insight count series
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_totalInsightCountSeries.AddPoint(frontierTimeUtc.Date, _dailyCount);
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// Create the pie chart every minute or so
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PopulateChartWithSeriesPerSymbol(_totalInsightCountPerSymbol, _totalInsightCountPerSymbolChart, SeriesType.Treemap, frontierTimeUtc);
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// Resetting our storage
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_dailyCount = 0;
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}
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// sample average population scores
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if (frontierTimeUtc >= _nextChartSampleAlgorithmTimeUtc)
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{
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try
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{
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// verify these scores have been computed before taking the first sample
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if (_statisticsManager.RollingAverageIsReady)
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{
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// sample the rolling averaged population scores
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foreach (var scoreType in InsightManager.ScoreTypes)
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{
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var score = 100 * _statisticsManager.Statistics.RollingAveragedPopulationScore.GetScore(scoreType);
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_insightScoreSeriesByScoreType[scoreType].AddPoint(frontierTimeUtc, score.SafeDecimalCast());
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}
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_nextChartSampleAlgorithmTimeUtc = frontierTimeUtc + SampleInterval;
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}
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}
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catch (Exception err)
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{
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Log.Error(err);
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}
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}
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}
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/// <summary>
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/// Invoked after <see cref="IAlgorithm.Initialize"/> has been called.
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/// Determines chart sample interval and initial sample times
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/// </summary>
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/// <remarks>
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/// While the algorithm instance is provided, it's highly recommended to not maintain
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/// a direct reference to it as there is no way to guarantee consistence reads.
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/// </remarks>
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/// <param name="algorithmStartDate">The start date of the algorithm</param>
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/// <param name="algorithmEndDate">The end date of the algorithm</param>
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/// <param name="algorithmUtcTime">The algorithm's current utc time</param>
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public void InitializeForRange(DateTime algorithmStartDate, DateTime algorithmEndDate, DateTime algorithmUtcTime)
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{
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if (_liveMode)
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{
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// live mode we'll sample each minute
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SampleInterval = Time.OneMinute;
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}
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else
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{
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// space out backtesting samples evenly
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var backtestPeriod = algorithmEndDate - algorithmStartDate;
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SampleInterval = TimeSpan.FromTicks(backtestPeriod.Ticks / BacktestChartSamples);
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}
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_nextChartSampleAlgorithmTimeUtc = algorithmUtcTime + SampleInterval;
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_lastInsightCountSampleDateUtc = algorithmUtcTime.RoundDown(Time.OneDay);
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}
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/// <summary>
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/// Handles the <see cref="IAlgorithm.InsightsGenerated"/> event.
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/// Keep daily and total count of insights by symbol
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/// </summary>
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/// <param name="context">The newly generated insight analysis context</param>
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public void OnInsightGenerated(InsightAnalysisContext context)
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{
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if (!_totalInsightCountPerSymbol.ContainsKey(context.Symbol))
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{
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_totalInsightCountPerSymbol[context.Symbol] = 1;
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}
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else
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{
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// track total count per symbol
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_totalInsightCountPerSymbol[context.Symbol] += 1;
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}
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_dailyCount++;
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}
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/// <summary>
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/// NOP - Charting is more concerned with population vs individual insights
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/// </summary>
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/// <param name="context">Context whose insight has just completed analysis</param>
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public void OnInsightClosed(InsightAnalysisContext context)
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{
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}
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/// <summary>
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/// NOP - Charting is more concerned with population vs individual insights
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/// </summary>
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/// <param name="context">Context whose insight has just completed analysis</param>
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public void OnInsightAnalysisCompleted(InsightAnalysisContext context)
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{
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}
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/// <summary>
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/// Creates series for each symbol and adds a value corresponding to the specified data
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/// </summary>
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private void PopulateChartWithSeriesPerSymbol(Dictionary<Symbol, int> data, Chart chart, SeriesType seriesType, DateTime frontierTimeUtc)
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{
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foreach (var kvp in data)
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{
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var symbol = kvp.Key;
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var count = kvp.Value;
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Series series;
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if (!chart.Series.TryGetValue(symbol.Value, out series))
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{
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series = new Series(symbol.Value, seriesType, null);
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chart.Series.Add(series.Name, series);
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}
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series.AddPoint(frontierTimeUtc, count);
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}
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}
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}
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}
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