Types.hpp

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#pragma once
 
#include "utils/UserError.hpp"
 
#include <Eigen/Dense>
#include <string>
#include <string_view>
#include <vector>
 
// ppforest2 targets Eigen 3.4.x — the version pinned for the standalone C++
// build (see core/Dependencies.cmake) and the range RcppEigen ships for the R
// package. This is a *floor* guard: newer Eigen is allowed, but if an
// incompatible version ever appears (e.g. via an RcppEigen bump), the build
// fails here with a clear message instead of a deep template error. If a
// future Eigen release breaks the API, adjust this after validating.
#if defined(EIGEN_VERSION_AT_LEAST) && !EIGEN_VERSION_AT_LEAST(3, 4, 0)
#error "ppforest2 requires Eigen >= 3.4.0. Update Eigen (or RcppEigen for the R package)."
#endif

namespace ppforest2::types {
  using Feature = float;

  using GroupId = int;

  using Outcome = Feature;

  using FeatureMatrix = Eigen::Matrix<Feature, Eigen::Dynamic, Eigen::Dynamic>;

  using FeatureVector = Eigen::Matrix<Feature, Eigen::Dynamic, 1>;

  using GroupIdVector = Eigen::Matrix<GroupId, Eigen::Dynamic, 1>;

  using OutcomeVector = Eigen::Matrix<Outcome, Eigen::Dynamic, 1>;

  using Names = std::vector<std::string>;

  template<typename T> using Matrix = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>;

  template<typename T> using Vector = Eigen::Matrix<T, Eigen::Dynamic, 1>;

  enum class Mode : uint8_t { Classification, Regression };

  inline bool is_classification(Mode mode) {
    return mode == Mode::Classification;
  }

  inline bool is_regression(Mode mode) {
    return mode == Mode::Regression;
  }

  inline std::string to_string(Mode mode) {
    return is_regression(mode) ? "regression" : "classification";
  }

  inline Mode mode_from_string(std::string_view s) {
    if (s == "classification") {
      return Mode::Classification;
    }
 
    if (s == "regression") {
      return Mode::Regression;
    }
 
    throw UserError("Invalid mode '" + std::string(s) + "'. Expected 'classification' or 'regression'.");
  }
 
}