/// <summary>
/// Performs initialization functions common to all constructors
/// </summary>
private void Init()
{
this.PropertyChanged += PatternRecognizer_PropertyChanged;
_progressLog = new ProgressLog();
activationFunctionIdx = -1;
normalizerIdx = -1;
_converter = new ClassifToMovCodeConverter();
activationTolerance = 0.1;
}
/// <summary>
/// Worker method performing the actual validation process
/// </summary>
private void ValidationWorker()
{
/*
* WE HAVE MOVED THE VALIDATION CODE FROM THE PatternRecognizer OBJECT TO HERE.
* This was done because certain required value objects like movement lists have
* nothing to do with pattern recognising.
*/
int okCount = 0;
int failCount = 0;
int expected;
int predicted;
ClassifToMovCodeConverter c2mConverter = new ClassifToMovCodeConverter();
MovListToCodeConverter ml2cConverter = new MovListToCodeConverter(totalSingleMovements, allowedComplexMovements);
c2mConverter.multipleActivation = _patternRecognizer.multipleActivationEnabled;
c2mConverter.activationLevel = _patternRecognizer.activationLevel;
c2mConverter.activationTolerance = _patternRecognizer.activationTolerance;
c2mConverter.movementCodes = _patternRecognizer.trainingPackage.movementCodes;
Dictionary<int, Dictionary<int, int>> confusionMatrix = new Dictionary<int, Dictionary<int, int>>();
Dictionary<int, int> predictedDictionary;
progressLog.Log(ProgressLogItem.Info, "*********** VALIDATION ************");
foreach (DataSet dataSet in _patternRecognizer.trainingPackage.validationSets)
{
expected = dataSet.movementCode;
okCount = 0;
failCount = 0;
foreach (DataWindow dataWindow in dataSet.set)
{
double[] inputVector = new double[_patternRecognizer.inputDim];
for (int j = 0; j < dataWindow.features.Values.Count; j++)
{
double[] channelVector = (double[])dataWindow.features.Values.ElementAt(j);
for (int k = 0; k < channelVector.Length; k++)
inputVector[(j * channelVector.Length) + k] = channelVector[k];
}
double[] outputVector = (double[])_patternRecognizer.Classify(inputVector);
//Here we must determine which movement code corresponds better
//with the input vector. The method for doing this changes depending on
//whether we are using explicit movement codes or not, so we implement it using a converter class
if (_patternRecognizer.multipleActivationEnabled)
{
List<ushort> movementList = (List<ushort>)c2mConverter.Convert(outputVector, null, null, null);
predicted = (int)ml2cConverter.Convert(movementList.ToArray(), null, null, null);
//The following happens when several outputs went active producing an impossible composite movement
//such as "rest + open" or "open + close", for instance.
if (predicted == -1) predicted = movementList.First();
//TODO: in this case, we opt for getting the
//first movement of the list, bur we could do other things, like try and remove an element at
//a tome and see when we come to a valid combination
}
else predicted = (int)c2mConverter.Convert(outputVector, null, null, null);
//Now we check if the predicted movement matches the expected movement
if (predicted == expected) okCount++;
else failCount++;
//Additionally, we compose the confusion matrix.
if (confusionMatrix.TryGetValue(expected, out predictedDictionary))
{
int predictedCount;
if (predictedDictionary.TryGetValue(predicted, out predictedCount))
{
predictedDictionary[predicted]++;
}
else predictedDictionary.Add(predicted, 1);
}
else
{
predictedDictionary = new Dictionary<int, int>();
predictedDictionary.Add(predicted, 1);
confusionMatrix.Add(expected, predictedDictionary);
}
}
string report = "Testing movement <mov " + expected + "/> -> correct: " + Math.Round(100 * okCount / (double)(okCount + failCount), 2) + "%";
confusionMatrix.TryGetValue(expected, out predictedDictionary);
if (predictedDictionary.Keys.Count > 1)
{
report = report + "; misclassified as: ";
foreach (int prediction in predictedDictionary.Keys)
{
if (prediction != expected)
{
report = report + "<mov " + prediction + "/> " + Math.Round(100 * predictedDictionary[prediction] / (double)(okCount + failCount), 2) + "%; ";
}
}
}
progressLog.Log(ProgressLogItem.Info, report);
}
progressLog.Log(ProgressLogItem.Info, "********* VALIDATION FINISHED *********");
}
public override void Init()
{
base.Init();
_producerGuid = _objectServer.RegisterProducer();
_matchBuffer.Clear();
_lastOutput = int.MinValue;
_converter = new ClassifToMovCodeConverter();
_converter.multipleActivation = multipleActivation;
_converter.activationLevel = activationLevel;
_converter.activationTolerance = activationTolerance;
_converter.movementCodes = movementCodes;
_codeConverter = new MovListToCodeConverter(numSingleMovements,allowedComplexMovements);
if (levelControlled) movementCodeMaker = ThresholdCodeMaker;
else movementCodeMaker = PatternRecognitionCodeMaker;
}