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quantconnect--lean/Optimizer/Strategies/StepBaseOptimizationStrategy.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 System;
using System.Collections.Generic;
using System.Globalization;
using System.Linq;
using QuantConnect.Optimizer.Objectives;
using QuantConnect.Optimizer.Parameters;
namespace QuantConnect.Optimizer.Strategies
{
/// <summary>
/// Base class for any optimization built on top of brute force optimization method
/// </summary>
public abstract class StepBaseOptimizationStrategy : IOptimizationStrategy
{
private int _i;
/// <summary>
/// Indicates was strategy initialized or no
/// </summary>
protected bool Initialized { get; set; }
/// <summary>
/// Optimization parameters
/// </summary>
protected HashSet<OptimizationParameter> OptimizationParameters { get; set; }
/// <summary>
/// Optimization target, i.e. maximize or minimize
/// </summary>
protected Target Target { get; set; }
/// <summary>
/// Optimization constraints; if it doesn't comply just drop the backtest
/// </summary>
protected IEnumerable<Constraint> Constraints { get; set; }
/// <summary>
/// Keep the best found solution - lean computed job result and corresponding parameter set
/// </summary>
public OptimizationResult Solution { get; protected set; }
/// <summary>
/// Advanced strategy settings
/// </summary>
public OptimizationStrategySettings Settings { get; protected set; }
/// <summary>
/// Fires when new parameter set is generated
/// </summary>
public event EventHandler<ParameterSet> NewParameterSet;
/// <summary>
/// Initializes the strategy using generator, extremum settings and optimization parameters
/// </summary>
/// <param name="target">The optimization target</param>
/// <param name="constraints">The optimization constraints to apply on backtest results</param>
/// <param name="parameters">Optimization parameters</param>
/// <param name="settings">Optimization strategy settings</param>
public virtual void Initialize(Target target, IReadOnlyList<Constraint> constraints, HashSet<OptimizationParameter> parameters, OptimizationStrategySettings settings)
{
if (Initialized)
{
throw new InvalidOperationException($"GridSearchOptimizationStrategy.Initialize: can not be re-initialized.");
}
Target = target;
Constraints = constraints;
OptimizationParameters = parameters;
Settings = settings;
foreach (var optimizationParameter in OptimizationParameters.OfType<OptimizationStepParameter>())
{
// if the Step optimization parameter does not provide a step to use, we calculate one based on settings
if (!optimizationParameter.Step.HasValue)
{
var stepSettings = Settings as StepBaseOptimizationStrategySettings;
if (stepSettings == null)
{
throw new ArgumentException($"OptimizationStrategySettings is not of {nameof(StepBaseOptimizationStrategySettings)} type", nameof(settings));
}
CalculateStep(optimizationParameter, stepSettings.DefaultSegmentAmount);
}
}
Initialized = true;
}
/// <summary>
/// Checks whether new lean compute job better than previous and run new iteration if necessary.
/// </summary>
/// <param name="result">Lean compute job result and corresponding parameter set</param>
public abstract void PushNewResults(OptimizationResult result);
/// <summary>
/// Calculate number of parameter sets within grid
/// </summary>
/// <returns>Number of parameter sets for given optimization parameters</returns>
public int GetTotalBacktestEstimate()
{
var total = 1;
foreach (var arg in OptimizationParameters)
{
total *= Estimate(arg);
}
return total;
}
/// <summary>
/// Calculates number od data points for step based optimization parameter based on min/max and step values
/// </summary>
private int Estimate(OptimizationParameter parameter)
{
if (parameter is StaticOptimizationParameter)
{
return 1;
}
var stepParameter = parameter as OptimizationStepParameter;
if (stepParameter == null)
{
throw new InvalidOperationException($"Cannot estimate parameter of type {parameter.GetType().FullName}");
}
if (!stepParameter.Step.HasValue)
{
throw new InvalidOperationException("Optimization parameter cannot be estimated due to step value is not initialized");
}
return (int)Math.Floor((stepParameter.MaxValue - stepParameter.MinValue) / stepParameter.Step.Value) + 1;
}
/// <summary>
/// Handles new parameter set
/// </summary>
/// <param name="parameterSet">New parameter set</param>
protected virtual void OnNewParameterSet(ParameterSet parameterSet)
{
NewParameterSet?.Invoke(this, parameterSet);
}
protected virtual void ProcessNewResult(OptimizationResult result)
{
// check if the incoming result is not the initial seed
if (result.Id > 0)
{
if (Constraints?.All(constraint => constraint.IsMet(result.JsonBacktestResult)) != false)
{
if (Target.MoveAhead(result.JsonBacktestResult))
{
Solution = result;
Target.CheckCompliance();
}
}
}
}
/// <summary>
/// Enumerate all possible arrangements
/// </summary>
/// <param name="args"></param>
/// <returns>Collection of possible combinations for given optimization parameters settings</returns>
protected IEnumerable<ParameterSet> Step(HashSet<OptimizationParameter> args)
{
foreach (var step in Recursive(new Queue<OptimizationParameter>(args)))
{
yield return new ParameterSet(
++_i,
step.ToDictionary(kvp => kvp.Key, kvp => kvp.Value));
}
}
/// <summary>
/// Calculate step and min step values based on default number of fragments
/// </summary>
private void CalculateStep(OptimizationStepParameter parameter, int defaultSegmentAmount)
{
if (defaultSegmentAmount < 1)
{
throw new ArgumentException($"Number of segments should be positive number, but specified '{defaultSegmentAmount}'", nameof(defaultSegmentAmount));
}
parameter.Step = Math.Abs(parameter.MaxValue - parameter.MinValue) / defaultSegmentAmount;
parameter.MinStep = parameter.Step / 10;
}
private IEnumerable<Dictionary<string, string>> Recursive(Queue<OptimizationParameter> args)
{
if (args.Count == 1)
{
var optimizationParameterLast = args.Dequeue();
using (var optimizationParameterLastEnumerator = GetEnumerator(optimizationParameterLast))
{
while (optimizationParameterLastEnumerator.MoveNext())
{
yield return new Dictionary<string, string>()
{
{optimizationParameterLast.Name, optimizationParameterLastEnumerator.Current}
};
}
}
yield break;
}
var optimizationParameter = args.Dequeue();
using (var optimizationParameterEnumerator = GetEnumerator(optimizationParameter))
{
while (optimizationParameterEnumerator.MoveNext())
{
foreach (var inner in Recursive(new Queue<OptimizationParameter>(args)))
{
inner.Add(optimizationParameter.Name, optimizationParameterEnumerator.Current);
yield return inner;
}
}
}
}
private IEnumerator<string> GetEnumerator(OptimizationParameter parameter)
{
var staticOptimizationParameter = parameter as StaticOptimizationParameter;
if (staticOptimizationParameter != null)
{
return new List<string> { staticOptimizationParameter.Value }.GetEnumerator();
}
var stepParameter = parameter as OptimizationStepParameter;
if (stepParameter == null)
{
throw new InvalidOperationException("");
}
return new OptimizationStepParameterEnumerator(stepParameter);
}
}
}