split_data.hpp

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#ifndef MLPACK_CORE_DATA_SPLIT_DATA_HPP
#define MLPACK_CORE_DATA_SPLIT_DATA_HPP

#include <mlpack/prereqs.hpp>

namespace mlpack {
namespace data {

template<typename InputType>
void SplitHelper(const InputType& input,
                 InputType& train,
                 InputType& test,
                 const double testRatio,
                 const arma::uvec& order = arma::uvec())
{
  const size_t testSize = static_cast<size_t>(input.n_cols * testRatio);
  const size_t trainSize = input.n_cols - testSize;

  // Initialising the sizes of outputs if not already initialized.
  train.set_size(input.n_rows, trainSize);
  test.set_size(input.n_rows, testSize);

  // Shuffling and spliting simultaneously.
  if (!order.is_empty())
  {
    if (trainSize > 0)
    {
      for (size_t i = 0; i < trainSize; ++i)
        train.col(i) = input.col(order(i));
    }
    if (trainSize < input.n_cols)
    {
      for (size_t i = trainSize; i < input.n_cols; ++i)
        test.col(i - trainSize) = input.col(order(i));
    }
  }
  // Spliting only.
  else
  {
    if (trainSize > 0)
      train = input.cols(0, trainSize - 1);

    if (trainSize < input.n_cols)
      test = input.cols(trainSize, input.n_cols - 1);
  }
}

template<typename T, typename LabelsType,
         typename = std::enable_if_t<arma::is_arma_type<LabelsType>::value> >
void StratifiedSplit(const arma::Mat<T>& input,
                     const LabelsType& inputLabel,
                     arma::Mat<T>& trainData,
                     arma::Mat<T>& testData,
                     LabelsType& trainLabel,
                     LabelsType& testLabel,
                     const double testRatio,
                     const bool shuffleData = true)
{
  const bool typeCheck = (arma::is_Row<LabelsType>::value)
      || (arma::is_Col<LabelsType>::value);
  if (!typeCheck)
    throw std::runtime_error("data::Split(): when stratified sampling is done, "
        "labels must have type `arma::Row<>`!");
  util::CheckSameSizes(input, inputLabel, "data::Split()");
  size_t trainIdx = 0;
  size_t testIdx = 0;
  size_t trainSize = 0;
  size_t testSize = 0;
  arma::uvec labelCounts;
  arma::uvec testLabelCounts;
  typename LabelsType::elem_type maxLabel = inputLabel.max();

  labelCounts.zeros(maxLabel+1);
  testLabelCounts.zeros(maxLabel+1);

  for (typename LabelsType::elem_type label : inputLabel)
    ++labelCounts[label];

  for (arma::uword labelCount : labelCounts)
  {
    testSize += floor(labelCount * testRatio);
    trainSize += labelCount - floor(labelCount * testRatio);
  }

  trainData.set_size(input.n_rows, trainSize);
  testData.set_size(input.n_rows, testSize);
  trainLabel.set_size(inputLabel.n_rows, trainSize);
  testLabel.set_size(inputLabel.n_rows, testSize);

  if (shuffleData)
  {
    arma::uvec order = arma::shuffle(
        arma::linspace<arma::uvec>(0, input.n_cols - 1, input.n_cols));

    for (arma::uword i : order)
    {
      typename LabelsType::elem_type label = inputLabel[i];
      if (testLabelCounts[label] < floor(labelCounts[label] * testRatio))
      {
        testLabelCounts[label] += 1;
        testData.col(testIdx) = input.col(i);
        testLabel[testIdx] = inputLabel[i];
        testIdx += 1;
      }
      else
      {
        trainData.col(trainIdx) = input.col(i);
        trainLabel[trainIdx] = inputLabel[i];
        trainIdx += 1;
      }
    }
  }
  else
  {
    for (arma::uword i = 0; i < input.n_cols; i++)
    {
      typename LabelsType::elem_type label = inputLabel[i];
      if (testLabelCounts[label] < floor(labelCounts[label] * testRatio))
      {
        testLabelCounts[label] += 1;
        testData.col(testIdx) = input.col(i);
        testLabel[testIdx] = inputLabel[i];
        testIdx += 1;
      }
      else
      {
        trainData.col(trainIdx) = input.col(i);
        trainLabel[trainIdx] = inputLabel[i];
        trainIdx += 1;
      }
    }
  }
}

template<typename T, typename LabelsType,
         typename = std::enable_if_t<arma::is_arma_type<LabelsType>::value> >
void Split(const arma::Mat<T>& input,
           const LabelsType& inputLabel,
           arma::Mat<T>& trainData,
           arma::Mat<T>& testData,
           LabelsType& trainLabel,
           LabelsType& testLabel,
           const double testRatio,
           const bool shuffleData = true)
{
  util::CheckSameSizes(input, inputLabel, "data::Split()");
  if (shuffleData)
  {
    arma::uvec order = arma::shuffle(arma::linspace<arma::uvec>(0,
        input.n_cols - 1, input.n_cols));
    SplitHelper(input, trainData, testData, testRatio, order);
    SplitHelper(inputLabel, trainLabel, testLabel, testRatio, order);
  }
  else
  {
    SplitHelper(input, trainData, testData, testRatio);
    SplitHelper(inputLabel, trainLabel, testLabel, testRatio);
  }
}

template<typename T>
void Split(const arma::Mat<T>& input,
           arma::Mat<T>& trainData,
           arma::Mat<T>& testData,
           const double testRatio,
           const bool shuffleData = true)
{
  if (shuffleData)
  {
    arma::uvec order = arma::shuffle(arma::linspace<arma::uvec>(0,
        input.n_cols - 1, input.n_cols));
    SplitHelper(input, trainData, testData, testRatio, order);
  }
  else
  {
    SplitHelper(input, trainData, testData, testRatio);
  }
}

template<typename T, typename LabelsType,
         typename = std::enable_if_t<arma::is_arma_type<LabelsType>::value> >
std::tuple<arma::Mat<T>, arma::Mat<T>, LabelsType, LabelsType>
Split(const arma::Mat<T>& input,
      const LabelsType& inputLabel,
      const double testRatio,
      const bool shuffleData = true,
      const bool stratifyData = false)
{
  arma::Mat<T> trainData;
  arma::Mat<T> testData;
  LabelsType trainLabel;
  LabelsType testLabel;

  if (stratifyData)
  {
    StratifiedSplit(input, inputLabel, trainData, testData, trainLabel,
        testLabel, testRatio, shuffleData);
  }
  else
  {
    Split(input, inputLabel, trainData, testData, trainLabel, testLabel,
        testRatio, shuffleData);
  }

  return std::make_tuple(std::move(trainData),
                         std::move(testData),
                         std::move(trainLabel),
                         std::move(testLabel));
}

template<typename T>
std::tuple<arma::Mat<T>, arma::Mat<T>>
Split(const arma::Mat<T>& input,
      const double testRatio,
      const bool shuffleData = true)
{
  arma::Mat<T> trainData;
  arma::Mat<T> testData;
  Split(input, trainData, testData, testRatio, shuffleData);

  return std::make_tuple(std::move(trainData),
                         std::move(testData));
}

template <typename FieldType, typename T,
          typename = std::enable_if_t<
              arma::is_Col<typename FieldType::object_type>::value ||
              arma::is_Mat_only<typename FieldType::object_type>::value>>
void Split(const FieldType& input,
           const arma::field<T>& inputLabel,
           FieldType& trainData,
           arma::field<T>& trainLabel,
           FieldType& testData,
           arma::field<T>& testLabel,
           const double testRatio,
           const bool shuffleData = true)
{
  util::CheckSameSizes(input, inputLabel, "data::Split()");
  if (shuffleData)
  {
    arma::uvec order = arma::shuffle(arma::linspace<arma::uvec>(0,
        input.n_cols - 1, input.n_cols));
    SplitHelper(input, trainData, testData, testRatio, order);
    SplitHelper(inputLabel, trainLabel, testLabel, testRatio, order);
  }
  else
  {
    SplitHelper(input, trainData, testData, testRatio);
    SplitHelper(inputLabel, trainLabel, testLabel, testRatio);
  }
}

template <class FieldType,
          class = std::enable_if_t<
              arma::is_Col<typename FieldType::object_type>::value ||
              arma::is_Mat_only<typename FieldType::object_type>::value>>
void Split(const FieldType& input,
           FieldType& trainData,
           FieldType& testData,
           const double testRatio,
           const bool shuffleData = true)
{
  if (shuffleData)
  {
    arma::uvec order = arma::shuffle(arma::linspace<arma::uvec>(0,
        input.n_cols - 1, input.n_cols));
    SplitHelper(input, trainData, testData, testRatio, order);
  }
  else
  {
    SplitHelper(input, trainData, testData, testRatio);
  }
}

template <class FieldType, typename T,
          class = std::enable_if_t<
              arma::is_Col<typename FieldType::object_type>::value ||
              arma::is_Mat_only<typename FieldType::object_type>::value>>
std::tuple<FieldType, FieldType, arma::field<T>, arma::field<T>>
Split(const FieldType& input,
      const arma::field<T>& inputLabel,
      const double testRatio,
      const bool shuffleData = true)
{
  FieldType trainData;
  FieldType testData;
  arma::field<T> trainLabel;
  arma::field<T> testLabel;

  Split(input, inputLabel, trainData, trainLabel, testData, testLabel,
      testRatio, shuffleData);

  return std::make_tuple(std::move(trainData),
                         std::move(testData),
                         std::move(trainLabel),
                         std::move(testLabel));
}

template <class FieldType,
          class = std::enable_if_t<
              arma::is_Col<typename FieldType::object_type>::value ||
              arma::is_Mat_only<typename FieldType::object_type>::value>>
std::tuple<FieldType, FieldType>
Split(const FieldType& input,
      const double testRatio,
      const bool shuffleData = true)
{
  FieldType trainData;
  FieldType testData;
  Split(input, trainData, testData, testRatio, shuffleData);

  return std::make_tuple(std::move(trainData),
                         std::move(testData));
}

} // namespace data
} // namespace mlpack

#endif