pca.h

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#ifndef PCL_PCA_H
#define PCL_PCA_H

#include <pcl/pcl_base.h>
#include <pcl/pcl_macros.h>

namespace pcl 
{
  template <typename PointT>
  class PCA : public pcl::PCLBase <PointT>
  {
    public:
      typedef pcl::PCLBase <PointT> Base;
      typedef typename Base::PointCloud PointCloud;
      typedef typename Base::PointCloudPtr PointCloudPtr;
      typedef typename Base::PointCloudConstPtr PointCloudConstPtr;
      typedef typename Base::PointIndicesPtr PointIndicesPtr;
      typedef typename Base::PointIndicesConstPtr PointIndicesConstPtr;

      using Base::input_;
      using Base::indices_;
      using Base::initCompute;
      using Base::setInputCloud;

      enum FLAG 
      {
        increase, 
        preserve
      };
    
      PCA (bool basis_only = false)
        : Base ()
        , compute_done_ (false)
        , basis_only_ (basis_only) 
        , eigenvectors_ ()
        , coefficients_ ()
        , mean_ ()
        , eigenvalues_  ()
      {}
      
      PCL_DEPRECATED (PCA (const pcl::PointCloud<PointT>& X, bool basis_only = false), 
                      "Use PCA (bool basis_only); setInputCloud (X.makeShared ()); instead");

      PCA (PCA const & pca) 
        : Base (pca)
        , compute_done_ (pca.compute_done_)
        , basis_only_ (pca.basis_only_) 
        , eigenvectors_ (pca.eigenvectors_)
        , coefficients_ (pca.coefficients_)
        , mean_ (pca.mean_)
        , eigenvalues_  (pca.eigenvalues_)
      {}

      inline PCA& 
      operator= (PCA const & pca) 
      {
        eigenvectors_ = pca.eigenvectors;
        coefficients_ = pca.coefficients;
        eigenvalues_  = pca.eigenvalues;
        mean_         = pca.mean;
        return (*this);
      }
      
      inline void 
      setInputCloud (const PointCloudConstPtr &cloud) 
      { 
        Base::setInputCloud (cloud);
        compute_done_ = false;
      }

      inline Eigen::Vector4f& 
      getMean () 
      {
        if (!compute_done_)
          initCompute ();
        if (!compute_done_)
          PCL_THROW_EXCEPTION (InitFailedException, 
                               "[pcl::PCA::getMean] PCA initCompute failed");
        return (mean_);
      }

      inline Eigen::Matrix3f& 
      getEigenVectors () 
      {
        if (!compute_done_)
          initCompute ();
        if (!compute_done_)
          PCL_THROW_EXCEPTION (InitFailedException, 
                               "[pcl::PCA::getEigenVectors] PCA initCompute failed");
        return (eigenvectors_);
      }
      
      inline Eigen::Vector3f& 
      getEigenValues ()
      {
        if (!compute_done_)
          initCompute ();
        if (!compute_done_)
          PCL_THROW_EXCEPTION (InitFailedException, 
                               "[pcl::PCA::getEigenVectors] PCA getEigenValues failed");
        return (eigenvalues_);
      }
      
      inline Eigen::MatrixXf& 
      getCoefficients () 
      {
        if (!compute_done_)
          initCompute ();
        if (!compute_done_)
          PCL_THROW_EXCEPTION (InitFailedException, 
                               "[pcl::PCA::getEigenVectors] PCA getCoefficients failed");
        return (coefficients_);
      }
            
      inline void 
      update (const PointT& input, FLAG flag = preserve);
      
      inline void 
      project (const PointT& input, PointT& projection);

      inline void
      project (const PointCloud& input, PointCloud& projection);
      
      inline void 
      reconstruct (const PointT& projection, PointT& input);

      inline void
      reconstruct (const PointCloud& projection, PointCloud& input);

    private:
      inline bool
      initCompute ();

      bool compute_done_;
      bool basis_only_;
      Eigen::Matrix3f eigenvectors_;
      Eigen::MatrixXf coefficients_;
      Eigen::Vector4f mean_;
      Eigen::Vector3f eigenvalues_;
  }; // class PCA
} // namespace pcl

#include <pcl/common/impl/pca.hpp>

#endif // PCL_PCA_H