public override void Run()
{
for (int i = 0; i < 2; i++)
{
List<string> catalogue = GenericFactory<PatternRecognizer>.Instance.SupportedProducts;
foreach (string item in catalogue)
{
_patternRecognizer = GenericFactory<PatternRecognizer>.Instance.CreateProduct(item);
Console.Out.WriteLine(item);
}
}
}
public override void Run()
{
List<string> itemList = GenericFactory<PatternRecognizer>.Instance.SupportedProducts;
foreach (string item in itemList)
InstanceManager<PatternRecognizer>.Instance.Register(GenericFactory<PatternRecognizer>.Instance.CreateProduct(item));
//And one more time to check what happens when overwriting :)
foreach (string item in itemList)
InstanceManager<PatternRecognizer>.Instance.Register(GenericFactory<PatternRecognizer>.Instance.CreateProduct(item));
List<string> instances = InstanceManager<PatternRecognizer>.Instance.RegisteredInstances;
_patternRecognizer = InstanceManager<PatternRecognizer>.Instance.Retrieve("LDA");
}
public override void Run()
{
double[] itemToClassify = new double[2] {2.81,5.46};
double[] result = new double[27];
_trainingPackage = MakeTrainingPackage();
//Now we inintialize and train the LDAPatternRecognizer.
//Input dimension is 2 because we have 2 features per feature vector. Output dimension is 27 because
//on the final application there will be 27 possible movements including rest (movement 0)
_patternRecognizer = GenericFactory<PatternRecognizer>.Instance.CreateProduct("LDA");//new LDAPatternRecognizer(_trainingPackage, 2, 27);
//_patternRecognizer.inputDim = 2;
//_patternRecognizer.outputDim = 27;
_patternRecognizer.trainingPackage = _trainingPackage;
_patternRecognizer.activationFunctionIdx = 0;
_patternRecognizer.normalizerIdx = 0;
_patternRecognizer.RunTraining();
result = (double[])_patternRecognizer.Classify(itemToClassify);
}
void ReaModel_PropertyChanged(object sender, PropertyChangedEventArgs e)
{
switch (e.PropertyName)
{
case "thresholdRecordingConfig":
if (thresholdRecordingConfig != null)
{
LoadThesholdControls();
}
break;
case "patternRecognizer":
if (!levelControlled)
{
if (_patternRecognizer != null)
recordingConfig = _patternRecognizer.trainingPackage.recordingConfig;
else _patternRecognizer = null;
this.NotifyPropertyChanged("multipleActivationSupported");
}
break;
case "levelControlled":
if (levelControlled)
{
recordingConfig = thresholdRecordingConfig;
}
else if (_patternRecognizer != null)
{
recordingConfig = _patternRecognizer.trainingPackage.recordingConfig;
}
else recordingConfig = null;
if (_movementGenerator != null) _movementGenerator.levelControlled = levelControlled;
break;
case "multipleActivation":
if (_movementGenerator != null)
_movementGenerator.multipleActivation = multipleActivation;
break;
default:
break;
}
}