private Algorithm RunIteration()
{
// create algorithm instance to run
Algorithm instanceToRun = MasterInstance.Clone();
// mark this as an optimizer run
instanceToRun.IsOptimizing = true;
// create result entry
OptimizerResult result = new OptimizerResult();
foreach (OptimizerParam parameter in MasterInstance.OptimizerParams.Values)
{
result.Parameters[parameter.Name] = parameter.Value;
}
result.Fitness = null;
Results.Add(result);
// run algorithm with these values
_jobQueue.QueueJob(() =>
{
instanceToRun.Run();
result.NetAssetValue = instanceToRun.NetAssetValue[0];
result.MaxDrawdown = instanceToRun.NetAssetValueMaxDrawdown;
result.Fitness = instanceToRun.FitnessValue;
instanceToRun = null;
lock (_optimizerLock)
{
_numIterationsCompleted++;
TimeSpan t = DateTime.Now - _startTime;
TimeSpan eta = TimeSpan.FromSeconds(
(_numIterationsTotal - _numIterationsCompleted)
* t.TotalSeconds / _numIterationsCompleted);
_maxFitness = Math.Max(_maxFitness, (double)result.Fitness);
Output.WriteLine("GridOptimizer: {0} of {1} iterations completed, max fitness = {2:F4}, eta = {3}h{4}m{5}s",
_numIterationsCompleted, _numIterationsTotal, _maxFitness,
Math.Floor(eta.TotalHours), eta.Minutes, eta.Seconds);
}
});
return(instanceToRun);
}
private void RunIteration()
{
if (!MasterInstance.CheckParametersValid())
{
// parameters are invalid. skip this iteration
_numIterationsTotal--;
return;
}
// create algorithm instance to run
Algorithm instanceToRun = MasterInstance.Clone();
// mark this as an optimizer run
instanceToRun.IsOptimizing = true;
// create result entry
OptimizerResult result = new OptimizerResult();
foreach (OptimizerParam parameter in MasterInstance.OptimizerParams.Values)
{
result.Parameters[parameter.Name] = parameter.Value;
}
result.Fitness = null;
Results.Add(result);
// run algorithm with these values
_jobQueue.QueueJob(() =>
{
try
{
// make sure to enter the extended Run method
// the default implementation will forward
// to the simple Run method, if required
// also, we need to convert the result to a list,
// in order to circumvent lazy execution
var noLazyExec = instanceToRun.Run(_algoStart, _algoEnd)
.ToList();
result.NetAssetValue = instanceToRun.NetAssetValue[0];
result.MaxDrawdown = instanceToRun.NetAssetValueMaxDrawdown;
result.Fitness = instanceToRun.FitnessValue;
instanceToRun = null;
}
catch (Exception e)
{
// we ignore any exeption while running the algo
lock (_optimizerLock)
{
if (_verbose)
{
Output.WriteLine("{0}: Iteration failed. {1}", this.GetType().Name, e.Message);
}
}
}
finally
{
lock (_optimizerLock)
{
_numIterationsCompleted++;
TimeSpan t = DateTime.Now - _optimizationStart;
TimeSpan eta = TimeSpan.FromSeconds(
(_numIterationsTotal - _numIterationsCompleted)
* t.TotalSeconds / _numIterationsCompleted);
if (result.Fitness != null)
{
_maxFitness = _maxFitness != null
? Math.Max((double)_maxFitness, (double)result.Fitness)
: (double)result.Fitness;
}
if (_verbose)
{
Output.WriteLine("GridOptimizer: {0} of {1} iterations completed, max fitness = {2:F4}, eta = {3}h{4}m{5}s",
_numIterationsCompleted, _numIterationsTotal, _maxFitness,
Math.Floor(eta.TotalHours), eta.Minutes, eta.Seconds);
}
}
}
});
}
/// <summary>
/// Run sub-classed algorithm and return bars as enumerable.
/// </summary>
/// <param name="startTime">start of load range</param>
/// <param name="endTime">end of load range</param>
/// <returns>bars created from sub-classed algo</returns>
public override IEnumerable <Bar> LoadData(DateTime startTime, DateTime endTime)
{
#if true
_algo.IsDataSource = true;
if (_algo.CanRunAsChild && Info.ContainsKey(DataSourceParam.allowSync))
{
// for child algorithms, we bypass the cache and run the
// child bar-for-bar and in sync with its parent
// we don't want to rely on the algorithm to provide a unique name.
// therefore, we replace the bar symbol with the algorithm's hash
var algoHashHex = string.Format("{0:X}", _algo.Name, _algo.GetHashCode());
foreach (var bar in _algo.Run(startTime, endTime))
{
var bar2 = new Bar(
algoHashHex,
bar.Time,
bar.Open, bar.High, bar.Low, bar.Close, bar.Volume, bar.HasOHLC,
bar.Bid, bar.Ask, bar.BidVolume, bar.AskVolume, bar.HasBidAsk,
bar.OptionExpiry, bar.OptionStrike, bar.OptionIsPut);
yield return(bar2);
if (!_algo.IsLastBar)
{
// the simulator core needs to know the next bar's
// timestamp. at the same time, we want to avoid
// child algorithms from running one bar ahead of
// the main algo. we fix this issue by returning
// a dummy bar, announcing the next timestamp.
var dummy = Bar.NewValue(
null, _algo.NextSimTime, 0.0);
yield return(dummy);
}
}
yield break;
}
else
{
// for all other algorithms, we run the algo
// all at once and save the result in the cache
var algoNick = Info[DataSourceParam.nickName];
var cacheKey = new CacheId().AddParameters(
algoNick.GetHashCode(), // _algoName.GetHashCode(),
startTime.GetHashCode(),
endTime.GetHashCode());
List <Bar> retrievalFunction()
{
try
{
DateTime t1 = DateTime.Now;
Output.WriteLine(string.Format("DataSourceAlgorithm: generating data for {0}...", Info[DataSourceParam.nickName]));
var bars = _algo.Run(startTime, endTime)
.ToList();
DateTime t2 = DateTime.Now;
Output.WriteLine(string.Format("DataSourceAlgorithm: finished after {0:F1} seconds", (t2 - t1).TotalSeconds));
return(bars);
}
catch
{
throw new Exception("DataSourceAlgorithm: failed to run sub-classed algorithm " + algoNick);
}
}
List <Bar> data = Cache <List <Bar> > .GetData(cacheKey, retrievalFunction, true);
if (data.Count == 0)
{
throw new Exception(string.Format("DataSourceAlgorithm: no data for {0}", Info[DataSourceParam.nickName]));
}
CachedData = data;
foreach (var bar in data)
{
yield return(bar);
}
}
#else
var algoNick = Info[DataSourceParam.nickName];
var cacheKey = new CacheId(null, "", 0,
algoNick.GetHashCode(), // _algoName.GetHashCode(),
startTime.GetHashCode(),
endTime.GetHashCode());
List <Bar> retrievalFunction()
{
try
{
DateTime t1 = DateTime.Now;
Output.WriteLine(string.Format("DataSourceAlgorithm: generating data for {0}...", Info[DataSourceParam.nickName]));
_algo.StartTime = startTime;
_algo.EndTime = endTime;
_algo.ParentDataSource = this;
_algo.SubclassedData = new List <Bar>();;
_algo.Run();
DateTime t2 = DateTime.Now;
Output.WriteLine(string.Format("DataSourceAlgorithm: finished after {0:F1} seconds", (t2 - t1).TotalSeconds));
return(_algo.SubclassedData);
}
catch
{
throw new Exception("DataSourceAlgorithm: failed to run sub-classed algorithm " + algoNick);
}
}
List <Bar> data = Cache <List <Bar> > .GetData(cacheKey, retrievalFunction, true);
if (data.Count == 0)
{
throw new Exception(string.Format("DataSourceAlgorithm: no data for {0}", Info[DataSourceParam.nickName]));
}
Data = data;
#endif
}
/// <summary>
/// Run sub-classed algorithm and return bars as enumerable.
/// </summary>
/// <param name="startTime">start of load range</param>
/// <param name="endTime">end of load range</param>
/// <returns>bars created from sub-classed algo</returns>
public override IEnumerable <Bar> LoadData(DateTime startTime, DateTime endTime)
{
#if true
_algo.IsDataSource = true;
if (_algo.IsChildAlgorithm)
{
// for child algorithms, we bypass the cache and run the
// child bar-for-bar and in sync with its parent
foreach (var bar in _algo.Run(startTime, endTime))
{
yield return(bar);
}
yield break;
}
else
{
// for all other algorithms, we run the algo
// all at once and save the result in the cache
var algoNick = Info[DataSourceParam.nickName];
var cacheKey = new CacheId(null, "", 0,
algoNick.GetHashCode(), // _algoName.GetHashCode(),
startTime.GetHashCode(),
endTime.GetHashCode());
List <Bar> retrievalFunction()
{
try
{
DateTime t1 = DateTime.Now;
Output.WriteLine(string.Format("DataSourceAlgorithm: generating data for {0}...", Info[DataSourceParam.nickName]));
var bars = _algo.Run(startTime, endTime)
.ToList();
DateTime t2 = DateTime.Now;
Output.WriteLine(string.Format("DataSourceAlgorithm: finished after {0:F1} seconds", (t2 - t1).TotalSeconds));
return(bars);
}
catch
{
throw new Exception("DataSourceAlgorithm: failed to run sub-classed algorithm " + algoNick);
}
}
List <Bar> data = Cache <List <Bar> > .GetData(cacheKey, retrievalFunction, true);
if (data.Count == 0)
{
throw new Exception(string.Format("DataSourceAlgorithm: no data for {0}", Info[DataSourceParam.nickName]));
}
CachedData = data;
foreach (var bar in data)
{
yield return(bar);
}
}
#else
var algoNick = Info[DataSourceParam.nickName];
var cacheKey = new CacheId(null, "", 0,
algoNick.GetHashCode(), // _algoName.GetHashCode(),
startTime.GetHashCode(),
endTime.GetHashCode());
List <Bar> retrievalFunction()
{
try
{
DateTime t1 = DateTime.Now;
Output.WriteLine(string.Format("DataSourceAlgorithm: generating data for {0}...", Info[DataSourceParam.nickName]));
_algo.StartTime = startTime;
_algo.EndTime = endTime;
_algo.ParentDataSource = this;
_algo.SubclassedData = new List <Bar>();;
_algo.Run();
DateTime t2 = DateTime.Now;
Output.WriteLine(string.Format("DataSourceAlgorithm: finished after {0:F1} seconds", (t2 - t1).TotalSeconds));
return(_algo.SubclassedData);
}
catch
{
throw new Exception("DataSourceAlgorithm: failed to run sub-classed algorithm " + algoNick);
}
}
List <Bar> data = Cache <List <Bar> > .GetData(cacheKey, retrievalFunction, true);
if (data.Count == 0)
{
throw new Exception(string.Format("DataSourceAlgorithm: no data for {0}", Info[DataSourceParam.nickName]));
}
Data = data;
#endif
}
