shuffle_data.hpp

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#ifndef MLPACK_CORE_MATH_SHUFFLE_DATA_HPP
#define MLPACK_CORE_MATH_SHUFFLE_DATA_HPP

#include <mlpack/prereqs.hpp>

namespace mlpack {
namespace math {

template<typename MatType, typename LabelsType>
void ShuffleData(const MatType& inputPoints,
                 const LabelsType& inputLabels,
                 MatType& outputPoints,
                 LabelsType& outputLabels,
                 const std::enable_if_t<!arma::is_SpMat<MatType>::value>* = 0,
                 const std::enable_if_t<!arma::is_Cube<MatType>::value>* = 0)
{
  // Generate ordering.
  arma::uvec ordering = arma::shuffle(arma::linspace<arma::uvec>(0,
      inputPoints.n_cols - 1, inputPoints.n_cols));

  outputPoints = inputPoints.cols(ordering);
  outputLabels = inputLabels.cols(ordering);
}

template<typename MatType, typename LabelsType>
void ShuffleData(const MatType& inputPoints,
                 const LabelsType& inputLabels,
                 MatType& outputPoints,
                 LabelsType& outputLabels,
                 const std::enable_if_t<arma::is_SpMat<MatType>::value>* = 0,
                 const std::enable_if_t<!arma::is_Cube<MatType>::value>* = 0)
{
  // Generate ordering.
  arma::uvec ordering = arma::shuffle(arma::linspace<arma::uvec>(0,
      inputPoints.n_cols - 1, inputPoints.n_cols));

  // Extract coordinate list representation.
  arma::umat locations(2, inputPoints.n_nonzero);
  arma::Col<typename MatType::elem_type> values(
      const_cast<typename MatType::elem_type*>(inputPoints.values),
      inputPoints.n_nonzero, false, true);
  typename MatType::const_iterator it = inputPoints.begin();
  size_t index = 0;
  while (it != inputPoints.end())
  {
    locations(0, index) = it.row();
    locations(1, index) = ordering[it.col()];
    ++it;
    ++index;
  }

  if (&inputPoints == &outputPoints || &inputLabels == &outputLabels)
  {
    MatType newOutputPoints(locations, values, inputPoints.n_rows,
        inputPoints.n_cols, true);
    LabelsType newOutputLabels(inputLabels.n_elem);
    newOutputLabels.cols(ordering) = inputLabels;

    outputPoints = std::move(newOutputPoints);
    outputLabels = std::move(newOutputLabels);
  }
  else
  {
    outputPoints = MatType(locations, values, inputPoints.n_rows,
        inputPoints.n_cols, true);
    outputLabels.set_size(inputLabels.n_elem);
    outputLabels.cols(ordering) = inputLabels;
  }
}

template<typename MatType, typename LabelsType>
void ShuffleData(const MatType& inputPoints,
                 const LabelsType& inputLabels,
                 MatType& outputPoints,
                 LabelsType& outputLabels,
                 const std::enable_if_t<!arma::is_SpMat<MatType>::value>* = 0,
                 const std::enable_if_t<arma::is_Cube<MatType>::value>* = 0,
                 const std::enable_if_t<arma::is_Cube<LabelsType>::value>* = 0)
{
  // Generate ordering.
  arma::uvec ordering = arma::shuffle(arma::linspace<arma::uvec>(0,
      inputPoints.n_cols - 1, inputPoints.n_cols));

  // Properly handle the case where the input and output data are the same
  // object.
  MatType* outputPointsPtr = &outputPoints;
  LabelsType* outputLabelsPtr = &outputLabels;
  if (&inputPoints == &outputPoints)
    outputPointsPtr = new MatType();
  if (&inputLabels == &outputLabels)
    outputLabelsPtr = new LabelsType();

  outputPointsPtr->set_size(inputPoints.n_rows, inputPoints.n_cols,
      inputPoints.n_slices);
  outputLabelsPtr->set_size(inputLabels.n_rows, inputLabels.n_cols,
      inputLabels.n_slices);
  for (size_t i = 0; i < ordering.n_elem; ++i)
  {
    outputPointsPtr->tube(0, ordering[i], outputPointsPtr->n_rows - 1,
        ordering[i]) = inputPoints.tube(0, i, inputPoints.n_rows - 1, i);
    outputLabelsPtr->tube(0, ordering[i], outputLabelsPtr->n_rows - 1,
        ordering[i]) = inputLabels.tube(0, i, inputLabels.n_rows - 1, i);
  }

  // Clean up memory if needed.
  if (&inputPoints == &outputPoints)
  {
    outputPoints = std::move(*outputPointsPtr);
    delete outputPointsPtr;
  }

  if (&inputLabels == &outputLabels)
  {
    outputLabels = std::move(*outputLabelsPtr);
    delete outputLabelsPtr;
  }
}

} // namespace math
} // namespace mlpack

#endif