/**
* Convenience method to provide an isolated copy of
* this <see cref="IInference"/>
*
* @return
*/
internal ManualInput Copy()
{
ManualInput retVal = new ManualInput();
retVal._classifierInput = new Map <string, NamedTuple>(this._classifierInput);
retVal._classifiers = new NamedTuple(this._classifiers.GetKeys(), this._classifiers.Values().ToArray());
retVal._layerInput = this._layerInput;
retVal._sdr = Arrays.CopyOf(this._sdr, this._sdr.Length);
retVal._encoding = Arrays.CopyOf(this._encoding, this._encoding.Length);
retVal._feedForwardActiveColumns = Arrays.CopyOf(this._feedForwardActiveColumns, this._feedForwardActiveColumns.Length);
retVal._feedForwardSparseActives = Arrays.CopyOf(this._feedForwardSparseActives, this._feedForwardSparseActives.Length);
retVal._previousPredictiveCells = new HashSet <Cell>(this._previousPredictiveCells);
retVal._predictiveCells = new HashSet <Cell>(this._predictiveCells);
retVal._classification = new Map <string, Classification <object> >(this._classification);
retVal._anomalyScore = this._anomalyScore;
retVal._customObject = this._customObject;
retVal._activeCells = new HashSet <Cell>(this._activeCells);
return(retVal);
}
/**
* Connects the output of the specified {@code Region} to the
* input of this Region
*
* @param inputRegion the Region who's emissions will be observed by
* this Region.
* @return
*/
public Region Connect(Region inputRegion)
{
ManualInput localInf = new ManualInput();
inputRegion.Observe().Subscribe(output =>
{
localInf.SetSdr(output.GetSdr()).SetRecordNum(output.GetRecordNum()).SetClassifierInput(output.GetClassifierInput()).SetLayerInput(output.GetSdr());
if (output.GetSdr().Length > 0)
{
((Layer <IInference>)tail).Compute(localInf);
}
}, Console.WriteLine, () =>
{
tail.NotifyComplete();
});
//inputRegion.Observe().Subscribe(new Observer<IInference>() {
//ManualInput localInf = new ManualInput();
//@Override public void onCompleted()
//{
//tail.notifyComplete();
//}
//@Override public void onError(Throwable e) { e.printStackTrace(); }
//@SuppressWarnings("unchecked")
// @Override public void onNext(IInference i)
//{
//localInf.sdr(i.getSDR()).recordNum(i.getRecordNum()).classifierInput(i.getClassifierInput()).layerInput(i.getSDR());
//if (i.getSDR().length > 0)
//{
// ((Layer<IInference>)tail).compute(localInf);
//}
//}
//});
// Set the upstream region
this.upstreamRegion = inputRegion;
inputRegion.downstreamRegion = this;
return(this);
}
public override object PostDeSerialize(object manualInput)
{
ManualInput mi = (ManualInput)manualInput;
ManualInput retVal = new ManualInput();
retVal._activeCells = mi._activeCells;
retVal._anomalyScore = mi._anomalyScore;
retVal._classification = mi._classification;
retVal._classifierInput = mi._classifierInput;
retVal._classifiers = mi._classifiers;
retVal._customObject = mi._customObject;
retVal._encoding = mi._encoding;
retVal._feedForwardActiveColumns = mi._feedForwardActiveColumns;
retVal._feedForwardSparseActives = mi._feedForwardSparseActives;
retVal._layerInput = mi._layerInput;
retVal._predictiveCells = mi._predictiveCells;
retVal._previousPredictiveCells = mi._previousPredictiveCells;
retVal._sdr = mi._sdr;
return(retVal);
}
public override bool Equals(Object obj)
{
if (this == obj)
{
return(true);
}
if (obj == null)
{
return(false);
}
if (!typeof(IInference).IsAssignableFrom(obj.GetType()))
{
return(false);
}
ManualInput other = (ManualInput)obj;
if (_activeCells == null)
{
if (other._activeCells != null)
{
return(false);
}
}
else if (!_activeCells.Equals(other._activeCells))
{
return(false);
}
if (BitConverter.DoubleToInt64Bits(_anomalyScore) != BitConverter.DoubleToInt64Bits(other._anomalyScore))
{
return(false);
}
if (_classification == null)
{
if (other._classification != null)
{
return(false);
}
}
else if (!_classification.Equals(other._classification))
{
return(false);
}
if (_classifierInput == null)
{
if (other._classifierInput != null)
{
return(false);
}
}
else if (!_classifierInput.Equals(other._classifierInput))
{
return(false);
}
if (_computeCycle == null)
{
if (other._computeCycle != null)
{
return(false);
}
}
else if (!_computeCycle.Equals(other._computeCycle))
{
return(false);
}
if (!Arrays.AreEqual(_encoding, other._encoding) && _encoding != null && other._encoding != null)
{
return(false);
}
if (!Arrays.AreEqual(_feedForwardActiveColumns, other._feedForwardActiveColumns) && _feedForwardActiveColumns != null && other._feedForwardActiveColumns != null)
{
return(false);
}
if (!Arrays.AreEqual(_feedForwardSparseActives, other._feedForwardSparseActives) && _feedForwardSparseActives != null && other._feedForwardSparseActives != null)
{
return(false);
}
if (_predictiveCells == null)
{
if (other._predictiveCells != null)
{
return(false);
}
}
else if (!_predictiveCells.Equals(other._predictiveCells))
{
return(false);
}
if (_previousPredictiveCells == null)
{
if (other._previousPredictiveCells != null)
{
return(false);
}
}
else if (!_previousPredictiveCells.Equals(other._previousPredictiveCells))
{
return(false);
}
if (_recordNum != other._recordNum)
{
return(false);
}
if (!Arrays.AreEqual(_sdr, other._sdr) && _sdr != null && other._sdr != null)
{
return(false);
}
return(true);
}
/**
* Called internally to "connect" two {@link Layer} <see cref="IObservable{T}"/>s
* taking care of other connection details such as passing the inference
* up the chain and any possible encoder.
*
* @param in the sink end of the connection between two layers
* @param out the source end of the connection between two layers
* @throws IllegalStateException if Region is already closed
*/
private void Connect <I, O>(I @in, O @out) // <I extends Layer<IInference>, O extends Layer<IInference>>
where I : Layer <IInference>
where O : Layer <IInference>
{
if (assemblyClosed)
{
throw new InvalidOperationException("Cannot add Layers when Region has already been closed.");
}
HashSet <Layer <IInference> > all = new HashSet <Layer <IInference> >(sources);
foreach (var sink in sinks)
{
all.Add(sink);
}
//all.addAll(sinks);
LayerMask inMask = @in.GetMask();
LayerMask outMask = @out.GetMask();
if (!all.Contains(@out))
{
layersDistinct = (int)(flagAccumulator & outMask) < 1;
flagAccumulator |= outMask;
}
if (!all.Contains(@in))
{
layersDistinct = (int)(flagAccumulator & inMask) < 1;
flagAccumulator |= inMask;
}
sources.Add(@out);
sinks.Add(@in);
ManualInput localInf = new ManualInput();
@out.Subscribe(Observer.Create <IInference>(i =>
{
if (layersDistinct)
{
@in.Compute(i);
}
else
{
localInf.SetSdr(i.GetSdr()).SetRecordNum(i.GetRecordNum()).SetLayerInput(i.GetSdr());
@in.Compute(localInf);
}
}, Console.WriteLine, () =>
{
@in.NotifyComplete();
}));
// @out.subscribe(new Subscriber<IInference>() {
// ManualInput localInf = new ManualInput();
// @Override public void onCompleted() { in.notifyComplete(); }
// @Override public void onError(Throwable e) { e.printStackTrace(); }
// @Override public void onNext(IInference i)
// {
// if (layersDistinct)
// {
// in.compute(i);
// }
// else {
// localInf.sdr(i.getSDR()).recordNum(i.getRecordNum()).layerInput(i.getSDR());
// in.compute(localInf);
// }
// }
//});
}
