pca.hpp

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#pragma once
 
// Dependency:
#include "../glm.hpp"
#include "../ext/scalar_relational.hpp"
 
#ifndef GLM_ENABLE_EXPERIMENTAL
#       error "GLM: GLM_GTX_pca is an experimental extension and may change in the future. Use #define GLM_ENABLE_EXPERIMENTAL before including it, if you really want to use it."
#elif GLM_MESSAGES == GLM_ENABLE && !defined(GLM_EXT_INCLUDED)
#       pragma message("GLM: GLM_GTX_pca extension included")
#endif
 
namespace glm {
 
        template<length_t D, typename T, qualifier Q>
        GLM_INLINE mat<D, D, T, Q> computeCovarianceMatrix(vec<D, T, Q> const* v, size_t n);
 
        template<length_t D, typename T, qualifier Q>
        GLM_INLINE mat<D, D, T, Q> computeCovarianceMatrix(vec<D, T, Q> const* v, size_t n, vec<D, T, Q> const& c);
 
        template<length_t D, typename T, qualifier Q, typename I>
        GLM_FUNC_DECL mat<D, D, T, Q> computeCovarianceMatrix(I const& b, I const& e);
 
        template<length_t D, typename T, qualifier Q, typename I>
        GLM_FUNC_DECL mat<D, D, T, Q> computeCovarianceMatrix(I const& b, I const& e, vec<D, T, Q> const& c);
 
        template<length_t D, typename T, qualifier Q>
        GLM_FUNC_DECL unsigned int findEigenvaluesSymReal
        (
                mat<D, D, T, Q> const& covarMat,
                vec<D, T, Q>& outEigenvalues,
                mat<D, D, T, Q>& outEigenvectors
        );
 
        template<typename T, qualifier Q>
        GLM_FUNC_DECL void sortEigenvalues(vec<2, T, Q>& eigenvalues, mat<2, 2, T, Q>& eigenvectors);
 
        template<typename T, qualifier Q>
        GLM_FUNC_DECL void sortEigenvalues(vec<3, T, Q>& eigenvalues, mat<3, 3, T, Q>& eigenvectors);
 
        template<typename T, qualifier Q>
        GLM_FUNC_DECL void sortEigenvalues(vec<4, T, Q>& eigenvalues, mat<4, 4, T, Q>& eigenvectors);
 
}//namespace glm
 
#include "pca.inl"