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quantconnect--lean/Tests/Optimizer/Analysis/OptimizationAnalyzerTests.cs
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2026-07-13 13:02:50 +08:00

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C#

/*
* 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.
*
*/
using Newtonsoft.Json;
using NUnit.Framework;
using QuantConnect.Optimizer;
using QuantConnect.Optimizer.Analysis;
using QuantConnect.Optimizer.Parameters;
using QuantConnect.Orders;
using QuantConnect.Packets;
using QuantConnect.Statistics;
using System.Collections.Generic;
using System.Globalization;
using System.Linq;
namespace QuantConnect.Tests.Optimizer.Analysis
{
[TestFixture, Parallelizable(ParallelScope.Self)]
public class OptimizationAnalyzerTests
{
[Test]
public void Run_ProducesOverallSharpeStats()
{
// 3x3 grid of synthetic Sharpe values.
var sharpes = new decimal[,]
{
{ 0.10m, 0.20m, 0.30m },
{ 0.15m, 0.25m, 0.35m },
{ 0.18m, 0.28m, 0.38m }
};
var backtests = BuildGridBacktests(sharpes, totalOrders: 5);
var parameters = BuildGridParameters(xCount: 3, yCount: 3);
var analyzer = new OptimizationAnalyzer();
var analysis = analyzer.Run(new OptimizationAnalysisRunParameters(backtests, parameters));
Assert.NotNull(analysis);
Assert.AreEqual(9, analysis.BacktestCountUsed);
Assert.AreEqual(9, analysis.BacktestCountTotal);
// Mean = average of {0.10..0.38}.
Assert.That(analysis.OverallSharpe.Mean, Is.EqualTo(0.2433m).Within(0.001m));
Assert.AreEqual(0.10m, analysis.OverallSharpe.Min);
Assert.AreEqual(0.38m, analysis.OverallSharpe.Max);
}
[Test]
public void Run_BestBacktestIsArgmaxSharpe()
{
var sharpes = new decimal[,]
{
{ 0.10m, 0.20m, 0.30m },
{ 0.15m, 0.25m, 0.35m },
{ 0.18m, 0.28m, 0.99m } // peak at (2, 2)
};
var backtests = BuildGridBacktests(sharpes, totalOrders: 5);
var parameters = BuildGridParameters(xCount: 3, yCount: 3);
var analysis = new OptimizationAnalyzer().Run(new OptimizationAnalysisRunParameters(backtests, parameters));
Assert.NotNull(analysis.Best);
Assert.AreEqual(0.99m, analysis.Best.SharpeRatio);
// Parameters at (xIndex=2, yIndex=2). Grid x: {1,2,3}; y: {10,20,30}.
Assert.AreEqual(3m, analysis.Best.Parameters["x"]);
Assert.AreEqual(30m, analysis.Best.Parameters["y"]);
}
[Test]
public void Run_FindsInteriorMode()
{
// 3x3 with a single interior peak at (1, 1): should produce one mode with 4 neighbors.
var sharpes = new decimal[,]
{
{ 0.10m, 0.20m, 0.10m },
{ 0.20m, 0.99m, 0.20m },
{ 0.10m, 0.20m, 0.10m }
};
var backtests = BuildGridBacktests(sharpes, totalOrders: 5);
var parameters = BuildGridParameters(xCount: 3, yCount: 3);
var analysis = new OptimizationAnalyzer().Run(new OptimizationAnalysisRunParameters(backtests, parameters));
Assert.AreEqual(1, analysis.Modes.Count);
Assert.AreEqual(0.99m, analysis.Modes[0].SharpeRatio);
Assert.AreEqual(4, analysis.Modes[0].NeighborCount);
}
[Test]
public void Run_ClusterCountRespectsSqrtCap()
{
// 4 backtests -> ceil(sqrt(4)) = 2 -> max 2 clusters.
var sharpes = new decimal[,]
{
{ 0.10m, 0.20m },
{ 0.30m, 0.40m }
};
var backtests = BuildGridBacktests(sharpes, totalOrders: 5);
var parameters = BuildGridParameters(xCount: 2, yCount: 2);
var analysis = new OptimizationAnalyzer().Run(new OptimizationAnalysisRunParameters(backtests, parameters));
Assert.LessOrEqual(analysis.Clusters.Count, 2);
}
[Test]
public void Run_BuildsFailedBacktestSummary_FromZeroOrderBacktests()
{
// 2x2 grid; every backtest has zero orders and carries known analysis tags.
var sharpes = new decimal[,]
{
{ 0m, 0m },
{ 0m, 0m }
};
var backtests = BuildGridBacktests(
sharpes,
totalOrders: 0,
analysisNames: new[] { "FlatEquityCurveAnalysis", "ExecutionSpeedAnalysis" });
var parameters = BuildGridParameters(xCount: 2, yCount: 2);
var analysis = new OptimizationAnalyzer().Run(new OptimizationAnalysisRunParameters(backtests, parameters));
Assert.NotNull(analysis.FailedBacktests);
Assert.AreEqual(4, analysis.FailedBacktests.ZeroOrderCount);
Assert.AreEqual(4, analysis.FailedBacktests.InspectedCount);
Assert.AreEqual(4, analysis.FailedBacktests.AnalysisNameCounts["FlatEquityCurveAnalysis"]);
Assert.AreEqual(4, analysis.FailedBacktests.AnalysisNameCounts["ExecutionSpeedAnalysis"]);
}
[Test]
public void Run_OmitsFailedBacktestSummary_WhenAllBacktestsTrade()
{
var sharpes = new decimal[,]
{
{ 0.10m, 0.20m },
{ 0.30m, 0.40m }
};
var backtests = BuildGridBacktests(sharpes, totalOrders: 5);
var parameters = BuildGridParameters(xCount: 2, yCount: 2);
var analysis = new OptimizationAnalyzer().Run(new OptimizationAnalysisRunParameters(backtests, parameters));
Assert.IsNull(analysis.FailedBacktests);
}
[Test]
public void ExtractFrom_ParsesSharpeAndAnalysisNamesFromBacktestJson()
{
var parameterSet = new ParameterSet(0, new Dictionary<string, string> { ["x"] = "1", ["y"] = "10" });
var json = BuildBacktestJson(0.75m, totalOrders: 12, new[] { "FlatEquityCurveAnalysis" });
var metrics = OptimizationBacktestMetrics.ExtractFrom("bt-0", parameterSet, json);
Assert.NotNull(metrics);
Assert.NotNull(metrics.TotalPerformance?.PortfolioStatistics);
Assert.AreEqual(0.75m, metrics.SharpeRatio);
Assert.AreEqual(0.75m, metrics.TotalPerformance.PortfolioStatistics.SharpeRatio);
Assert.AreEqual(12, metrics.TotalOrders);
CollectionAssert.AreEqual(new[] { "FlatEquityCurveAnalysis" }, metrics.AnalysisNames.ToArray());
Assert.AreEqual(1m, metrics.Parameters["x"]);
Assert.AreEqual(10m, metrics.Parameters["y"]);
}
// ── helpers ──────────────────────────────────────────────────────────────
private static List<OptimizationBacktestMetrics> BuildGridBacktests(
decimal[,] sharpes,
int totalOrders,
string[] analysisNames = null)
{
var result = new List<OptimizationBacktestMetrics>();
var xCount = sharpes.GetLength(0);
var yCount = sharpes.GetLength(1);
var id = 0;
for (var i = 0; i < xCount; i++)
{
for (var j = 0; j < yCount; j++)
{
var paramSet = new ParameterSet(id, new Dictionary<string, string>
{
["x"] = (i + 1).ToString(CultureInfo.InvariantCulture),
["y"] = ((j + 1) * 10).ToString(CultureInfo.InvariantCulture)
});
var json = BuildBacktestJson(sharpes[i, j], totalOrders, analysisNames);
result.Add(OptimizationBacktestMetrics.ExtractFrom($"backtest-{id}", paramSet, json));
id++;
}
}
return result;
}
private static string BuildBacktestJson(decimal sharpe, int totalOrders, string[] analysisNames)
{
// Build a real BacktestResult and serialize through the LEAN-wide JsonSerializer
// (CamelCaseNamingStrategy) so the JSON shape matches what BacktestingResultHandler
// produces in production — which is what OptimizationBacktestMetrics.ExtractFrom
// round-trips through DeserializeJson<BacktestResult>.
var result = new QuantConnect.Packets.BacktestResult
{
TotalPerformance = new AlgorithmPerformance(),
Orders = Enumerable.Range(1, totalOrders).ToDictionary(i => i, i => (Order)new MarketOrder()),
Analysis = (analysisNames ?? System.Array.Empty<string>())
.Select(n => new QuantConnect.Analysis(n, "issue", null, null, System.Array.Empty<string>()))
.ToList()
};
result.TotalPerformance.PortfolioStatistics.SharpeRatio = sharpe;
return result.SerializeJsonToString();
}
private static HashSet<OptimizationParameter> BuildGridParameters(int xCount, int yCount)
{
return new HashSet<OptimizationParameter>
{
new OptimizationStepParameter("x", 1, xCount, 1),
new OptimizationStepParameter("y", 10, yCount * 10, 10)
};
}
}
}