本文整理汇总了C#中Simulator.OutputResult方法的典型用法代码示例。如果您正苦于以下问题：C# Simulator.OutputResult方法的具体用法？C# Simulator.OutputResult怎么用？C# Simulator.OutputResult使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类Simulator的用法示例。
在下文中一共展示了Simulator.OutputResult方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C#代码示例。
示例1: ProcessThread
//.........这里部分代码省略.........
currentEpoch = epochIndex;
List<TrialInformation> trainingMatrixTrialInformationList = new List<TrialInformation>();
foreach (MatchingInformation trainingMatchingInformation in currentTrainingMatchingInformationList)
{
List<StimuliMatrix> stimuliMatrixList = new List<StimuliMatrix>();
switch (learningSetupList[learningSetupIndex].TrainingProcessMode)
{
case ProcessMode.RandomAll:
case ProcessMode.RandomInStimuliPack:
stimuliMatrixList = simulator.StimuliPackDictionary[trainingMatchingInformation.StimuliPackName].GetMatrixStimuliData(true, true, learningSetupList[learningSetupIndex].MatrixCalculationSize);
break;
case ProcessMode.SequentialAll:
case ProcessMode.SequentialinStimuliPack:
stimuliMatrixList = simulator.StimuliPackDictionary[trainingMatchingInformation.StimuliPackName].GetMatrixStimuliData(true, false, learningSetupList[learningSetupIndex].MatrixCalculationSize);
break;
}
foreach (StimuliMatrix stimuliMatrix in stimuliMatrixList)
{
TrialInformation newTrainingTrialInformation = new TrialInformation();
newTrainingTrialInformation.Process = simulator.ProcessDictionary[trainingMatchingInformation.ProcessName];
newTrainingTrialInformation.PatternSetup = trainingMatchingInformation.PatternSetup;
newTrainingTrialInformation.StimuliMatrix = stimuliMatrix;
trainingMatrixTrialInformationList.Add(newTrainingTrialInformation);
}
}
switch (learningSetupList[learningSetupIndex].TrainingProcessMode)
{
case ProcessMode.RandomAll:
case ProcessMode.SequentialinStimuliPack:
trainingMatrixTrialInformationList = trainingMatrixTrialInformationList.OrderBy(x => (SimulatorAccessor.random.Next())).ToList();
break;
}
currentTrialInformationCount = trainingMatrixTrialInformationList.Count;
for (int trainingIndex = 0; trainingIndex < trainingMatrixTrialInformationList.Count; trainingIndex++)
{
currentProcessName = trainingMatrixTrialInformationList[trainingIndex].Process.Name;
currentStimuliPackName = trainingMatrixTrialInformationList[trainingIndex].StimuliMatrix.PackName;
simulator.Process(trainingMatrixTrialInformationList[trainingIndex], totalEpoch + epochIndex + 1);
currentTrainingIndex = trainingIndex;
}
if ((epochIndex + 1) % learningSetupList[learningSetupIndex].TestTiming == 0)
{
learningStatus = LearningStatus.Test;
if (simulator.UseWeightInformation) simulator.WeightInformationReader(totalEpoch + epochIndex + 1);
for (int testIndex = 0; testIndex < testMatrixTrialInformationList.Count; testIndex++)
{
simulator.Process(testMatrixTrialInformationList[testIndex], totalEpoch + epochIndex + 1);
}
try { this.Invoke(new MethodInvoker(delegate { TestDisplayRefresh(); })); }
catch { }
}
if (learningStatus == LearningStatus.Pausing)
{
currentEpoch = epochIndex + 1;
break;
}
currentTick = DateTime.Now.Ticks;
}
if (learningStatus == LearningStatus.Pausing)
{
if (currentEpoch >= learningSetupList[learningSetupIndex].TrainingEpoch)
{
currentEpoch = 0;
currentLearningSetupIndex = learningSetupIndex + 1;
}
if(currentLearningSetupIndex >= learningSetupList.Count)
{
currentLearningSetupIndex = 0;
currentBathDataIndex = batchIndex + 1;
}
break;
}
else
{
string resultPath = simulator.OutputResult();
simulator.WeightSave(resultPath + "Status.WDATA");
currentLearningSetupIndex = 0;
currentEpoch = 0;
totalEpoch = 0;
}
}
if (learningStatus == LearningStatus.Pausing)
{
learningStatus = LearningStatus.Paused;
break;
}
}
if (learningStatus == LearningStatus.Training || learningStatus == LearningStatus.Test) learningStatus = LearningStatus.End;
}