ConvolutionEngine1D.cc
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ConvolutionEngine1D.cc
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	#include <cassert>

	#include "npstat/nm/ConvolutionEngine1D.hh"

	namespace npstat {
	ConvolutionEngine1D::ConvolutionEngine1D(
	const unsigned dataLen, const unsigned optimization)
	: dataLen_(dataLen),
	validFilter_(false)
	{
	if (!dataLen) throw std::invalid_argument(
	"In npstat::ConvolutionEngine1D constructor: "
	"expected data length must be positive");

	// fftw_malloc ensures optimal alignment of the allocated buffers
	in = static_cast<double *>(fftw_malloc(
	dataLen * sizeof(double)));
	assert(in);
	out = static_cast<fftw_complex *>(fftw_malloc(
	(dataLen/2 + 1) * sizeof(fftw_complex)));
	assert(out);
	filterImage = static_cast<fftw_complex *>(fftw_malloc(
	(dataLen/2 + 1) * sizeof(fftw_complex)));
	assert(filterImage);

	const unsigned plannerFlags = optimization \| FFTW_DESTROY_INPUT;
	pf = fftw_plan_dft_r2c_1d(dataLen, in, out, plannerFlags);
	pb = fftw_plan_dft_c2r_1d(dataLen, out, in, plannerFlags);
	assert(pf);
	assert(pb);
	}

	ConvolutionEngine1D::~ConvolutionEngine1D()
	{
	fftw_destroy_plan(pb);
	fftw_destroy_plan(pf);
	fftw_free(filterImage);
	fftw_free(out);
	fftw_free(in);

	for (FilterMap::iterator it = filterMap_.begin();
	it != filterMap_.end(); ++it)
	delete it->second;
	}

	bool ConvolutionEngine1D::discardFilter(const unsigned long id)
	{
	FilterMap::iterator it = filterMap_.find(id);
	if (it != filterMap_.end())
	{
	delete it->second;
	filterMap_.erase(it);
	return true;
	}
	else
	return false;
	}
	}