TPwcDistribution1D.h

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#pragma once
 
#include <type_traits>
#include <vector>
 
namespace ph::math
{
 
template<typename T>
class TPwcDistribution1D final
{
    static_assert(std::is_floating_point_v<T>);
 
public:
    TPwcDistribution1D(T min, T max, const T* weights, std::size_t numWeights);
    TPwcDistribution1D(T min, T max, const std::vector<T>& weights);
 
    explicit TPwcDistribution1D(const std::vector<T>& weights);
 
    TPwcDistribution1D();
 
    T sampleContinuous(T sample) const;
    T sampleContinuous(T sample, T* out_pdf) const;
    T sampleContinuous(T sample, T* out_pdf, std::size_t* out_straddledColumn) const;
 
    std::size_t sampleDiscrete(T sample) const;
    // TODO: a sample resued version
 
    T pdfContinuous(T value) const;
 
    T pdfContinuous(std::size_t columnIndex) const;
 
    T pdfDiscrete(std::size_t columnIndex) const;
 
    std::size_t continuousToDiscrete(T value) const;
 
    std::size_t numColumns() const;
 
private:
    // Range of the distribution
    T m_min, m_max;
 
    // Size of each interval
    T m_delta;
 
    // Recording first non-zero column index to avoid sampling column with
    // zero PDF.
    std::size_t m_firstNonZeroPdfColumn;
 
    // Piecewise constant weights will result in piecewise linear CDF.
    // CDF values are stored on all turning points of the function. 
    std::vector<T> m_cdf;
 
    T continuouslySampleValue(T sample, std::size_t straddledColumn) const;
};
 
}// end namespace ph::math
 
#include "Math/Random/TPwcDistribution1D.ipp"