Пример #1
0
    void
    factor_U(const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>& U,
             Eigen::Array<T, Eigen::Dynamic, 1>& CPCs) {
      size_t K = U.rows();
      size_t position = 0;
      size_t pull = K - 1;

      if (K == 2) {
        CPCs(0) = atanh(U(0, 1));
        return;
      }

      Eigen::Array<T, 1, Eigen::Dynamic> temp = U.row(0).tail(pull);

      CPCs.head(pull) = temp;

      Eigen::Array<T, Eigen::Dynamic, 1> acc(K);
      acc(0) = -0.0;
      acc.tail(pull) = 1.0 - temp.square();
      for (size_t i = 1; i < (K - 1); i++) {
        position += pull;
        pull--;
        temp = U.row(i).tail(pull);
        temp /= sqrt(acc.tail(pull) / acc(i));
        CPCs.segment(position, pull) = temp;
        acc.tail(pull) *= 1.0 - temp.square();
      }
      CPCs = 0.5 * ( (1.0 + CPCs) / (1.0 - CPCs) ).log();  // now unbounded
    }
Пример #2
0
    Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>
    read_corr_L(const Eigen::Array<T, Eigen::Dynamic, 1>& CPCs,  // on (-1, 1)
                size_t K) {
      Eigen::Array<T, Eigen::Dynamic, 1> temp;
      Eigen::Array<T, Eigen::Dynamic, 1> acc(K-1);
      acc.setOnes();
      // Cholesky factor of correlation matrix
      Eigen::Array<T, Eigen::Dynamic, Eigen::Dynamic> L(K, K);
      L.setZero();

      size_t position = 0;
      size_t pull = K - 1;

      L(0, 0) = 1.0;
      L.col(0).tail(pull) = temp = CPCs.head(pull);
      acc.tail(pull) = T(1.0) - temp.square();
      for (size_t i = 1; i < (K - 1); i++) {
        position += pull;
        pull--;
        temp = CPCs.segment(position, pull);
        L(i, i) = sqrt(acc(i-1));
        L.col(i).tail(pull) = temp * acc.tail(pull).sqrt();
        acc.tail(pull) *= T(1.0) - temp.square();
      }
      L(K-1, K-1) = sqrt(acc(K-2));
      return L.matrix();
    }