// This is the main DLL file.

#include "stdafx.h"

#include "netsvm.h"

namespace netsvm
{
    SparseVector::SparseVector() {
        impl_ = new pcsvm::SparseVector();
    }
	
	SparseVector::SparseVector(pcsvm::SparseVector *v)
	{
			impl_ = v;
	}

	SparseVector::~SparseVector() {
        delete impl_;
    }

	float SparseVector::get(int i)
	{   
		return impl_->get(i);   
	}
	void SparseVector::put(int i, float v) 
	{  
		impl_->put(i,v); 
	}
        

	String * SparseVector::to_str() {
			std::string  w =impl_->to_str();
			return new String(w.c_str());
	}
		
	void     SparseVector::prune(float eps)
	{
		impl_->prune(eps);
	}

	void SparseVector::push_back(float v)
	{
		int idx = impl_->lastIndex();
		impl_->put(idx+1, v);
		
	}


    int      SparseVector::lastIndex()
	{
		return impl_->lastIndex();
	}

	int      SparseVector::entries()
	{
		return impl_->entries();
	}

	void     SparseVector::clear()
	{
		impl_->clear();
	}

	bool     SparseVector::empty()
	{
		return impl_->empty();
	}
	
	std::vector<float> * SparseVector::toVector(int index1, int index2)
	{ 
		std::vector<float> * rv = new std::vector<float>(impl_->toVector(index1,index2));
		return rv;
		
	}

    ClassificationExample* ClassificationProblem::at(int i)
    {
		ClassificationExample *rv = new ClassificationExample();
		pcsvm::ClassificationExample ex = impl_->get(i);

		pcsvm::SparseVector *temp = new pcsvm::SparseVector(ex.vector);
		// SparseVector übernimmt pointerverwaltung:
		rv->vector = new SparseVector(temp);
		rv->label = ex.label;

		return rv;
	}
	
	void ClassificationProblem::push_back(SparseVector *sv, bool label)
	{
		pcsvm::ClassificationExample ex(*(sv->impl_), label);
		impl_->push_back(ex);
	}

	void ClassificationProblem::push_back(ClassificationExample *ex)
	{
		pcsvm::ClassificationExample tex(*(ex->vector->impl_), ex->label);
		impl_->push_back(tex);
	}

	ClassifierCSVM::ClassifierCSVM(ClassificationProblem *p, KernelBase *k)
	{
		impl_ = new pcsvm::ClassifierCSVM(p->impl_, k->impl_);
	};
	
	CSVMTrainInfo* ClassifierCSVM::train(float cp, float cn)
	{
		pcsvm::CSVMTrainInfo inf = impl_->train(cp, cn);
		CSVMTrainInfo * tinf = new CSVMTrainInfo();
		tinf->numIter = inf.numIter;
		tinf->numSV   = inf.numSV;

		pcsvm::SparseVector *temp = new pcsvm::SparseVector(inf.svWeights);
		tinf->svWeights = new SparseVector(temp);

		return tinf;

	}
	
	float ClassifierCSVM::classify(SparseVector *s)
	{
		return impl_->operator ()(*(s->impl_));
	}



}