//----------------------------------------------------------------
//
// NAME: GetNumberOutput
//
//
// DESCRIPTION:
//
// Return the number of output units in a --SIMPLE-- local_net
// By simple we mean that there is only one output layer and it is the last
// layer.
// After some thought, decided to return 0 as the number if it cannot
// figure what the input layer (ie default return value is 0)
//---------------------------------------------------------------
int CNeuralNet::GetOutputCount()
{
ULONG cOutput = 0;
HRESULT hr = GetNumClasses(&cOutput);
if (FAILED(hr))
{
return 0;
}
return (int)cOutput;
}
virtual void Merge(std::shared_ptr<AbstractStatistics> OtherStats) override
{
std::shared_ptr<StructDataStats> DerivedOtherStats = std::dynamic_pointer_cast<StructDataStats>(OtherStats);
if(DerivedOtherStats->GetNumClasses() != GetNumClasses())
throw std::runtime_error("Cannot merge statistics. Number of classes don't match. Exiting.");
// std::cout << DerivedOtherStats->GetNumClasses() << std::endl;
// std::cout << GetNumClasses() << std::endl;
// if(isAggregated() != true || DerivedOtherStats->isAggregated() != true)
// throw std::runtime_error("Cannot merge statistics. One of them is not aggregated yet. Exiting.");
if(DerivedOtherStats == nullptr)
throw std::runtime_error("Incoming statistics is null. Please check input. Exiting.");
m_nDataPoints += DerivedOtherStats->GetNumDataPoints();
for(int i = 0; i < m_nClassesPerDim; ++i)
m_DimClassBins[i] += DerivedOtherStats->GetBins()[i];
m_isAggregated = true;
};
