C++ Col类代码示例

inline
Col<typename T1::pod_type>
eigs_sym
  (
  const SpBase<typename T1::elem_type,T1>& X,
  const uword                              n_eigvals,
  const char*                              form = "lm",
  const typename T1::elem_type             tol  = 0.0,
  const typename arma_real_only<typename T1::elem_type>::result* junk = 0
  )
  {
  arma_extra_debug_sigprint();
  arma_ignore(junk);
  
  Mat<typename T1::elem_type> eigvec;
  Col<typename T1::pod_type > eigval;
  
  const bool status = sp_auxlib::eigs_sym(eigval, eigvec, X, n_eigvals, form, tol);
  
  if(status == false)
    {
    eigval.reset();
    arma_bad("eigs_sym(): failed to converge");
    }
  
  return eigval;
  }

		void expectedColClear() {
			cout << "- Compute expectedColClear() ... ";
			Col<double> expected = _genColVec;
			expected.clear();
			save<double>("Col.clear", expected);
			cout << "done." << endl;
		}

arma_warn_unused
inline
Col<uword>
find(const SpBase<typename T1::elem_type,T1>& X, const uword k = 0)
  {
  arma_extra_debug_sigprint();
  
  const SpProxy<T1> P(X.get_ref());
  
  const uword n_rows = P.get_n_rows();
  const uword n_nz   = P.get_n_nonzero();
  
  Mat<uword> tmp(n_nz,1);
  
  uword* tmp_mem = tmp.memptr();
  
  typename SpProxy<T1>::const_iterator_type it = P.begin();
  
  for(uword i=0; i<n_nz; ++i)
    {
    const uword index = it.row() + it.col()*n_rows;
    
    tmp_mem[i] = index;
    
    ++it;
    }
  
  Col<uword> out;
  
  const uword count = (k == 0) ? uword(n_nz) : uword( (std::min)(n_nz, k) );
  
  out.steal_mem_col(tmp, count);
  
  return out;
  }

		void expectedColReset() {
			cout << "- Compute expectedColReset() ... ";
			Col<double> expected = _genColVec;
			expected.reset();
			save<double>("Col.reset", expected);
			cout << "done." << endl;
		}

inline
typename enable_if2< is_supported_blas_type<typename T1::pod_type>::value, Col< std::complex<typename T1::pod_type> > >::result
eig_gen
  (
  const Base<typename T1::elem_type, T1>& expr
  )
  {
  arma_extra_debug_sigprint();
  
  typedef typename T1::pod_type     T;
  typedef typename std::complex<T> eT;
  
  Col<eT> eigvals;
  Mat<eT> eigvecs;
  
  const bool status = auxlib::eig_gen(eigvals, eigvecs, false, expr.get_ref());
  
  if(status == false)
    {
    eigvals.reset();
    arma_bad("eig_gen(): decomposition failed");
    }
  
  return eigvals;
  }

arma_warn_unused
inline
typename enable_if2< is_supported_blas_type<typename T1::pod_type>::value, Col< std::complex<typename T1::pod_type> > >::result
eig_pair
  (
  const Base<typename T1::elem_type, T1>& A_expr,
  const Base<typename T1::elem_type, T2>& B_expr
  )
  {
  arma_extra_debug_sigprint();
  
  typedef typename T1::pod_type T;
  
  Col< std::complex<T> > eigvals;
  Mat< std::complex<T> > eigvecs;
  
  const bool status = auxlib::eig_pair(eigvals, eigvecs, false, A_expr.get_ref(), B_expr.get_ref());
  
  if(status == false)
    {
    eigvals.reset();
    arma_stop_runtime_error("eig_pair(): decomposition failed");
    }
  
  return eigvals;
  }

arma_warn_unused
inline
Col<typename T1::pod_type>
eigs_sym
  (
  const SpBase<typename T1::elem_type,T1>& X,
  const uword                              n_eigvals,
  const char*                              form = "lm",
  const typename T1::elem_type             tol  = 0.0,
  const typename arma_real_only<typename T1::elem_type>::result* junk = 0
  )
  {
  arma_extra_debug_sigprint();
  arma_ignore(junk);
  
  Mat<typename T1::elem_type> eigvec;
  Col<typename T1::pod_type > eigval;
  
  const bool status = sp_auxlib::eigs_sym(eigval, eigvec, X, n_eigvals, form, tol);
  
  if(status == false)
    {
    eigval.reset();
    arma_stop_runtime_error("eigs_sym(): decomposition failed");
    }
  
  return eigval;
  }

inline
void
GenEigsSolver<eT, SelectionRule, OpType>::retrieve_ritzpair()
  {
  arma_extra_debug_sigprint();
  
  UpperHessenbergEigen<eT> decomp(fac_H);
  
  Col< std::complex<eT> > evals = decomp.eigenvalues();
  Mat< std::complex<eT> > evecs = decomp.eigenvectors();
  
  SortEigenvalue< std::complex<eT>, SelectionRule > sorting(evals.memptr(), evals.n_elem);
  std::vector<uword> ind = sorting.index();
  
  // Copy the ritz values and vectors to ritz_val and ritz_vec, respectively
  for(uword i = 0; i < ncv; i++)
    {
    ritz_val(i) = evals(ind[i]);
    ritz_est(i) = evecs(ncv - 1, ind[i]);
    }
  for(uword i = 0; i < nev; i++)
    {
    ritz_vec.col(i) = evecs.col(ind[i]);
    }
  }

inline
Col< std::complex<T> >
eig_pair
  (
  const Base< std::complex<T>, T1>& A, 
  const Base< std::complex<T>, T1>& B, 
  const typename arma_blas_type_only< std::complex<T> >::result* junk1 = 0,
  const typename        arma_cx_only< std::complex<T> >::result* junk2 = 0 
  )
  {
  arma_extra_debug_sigprint();
  arma_ignore(junk1);
  arma_ignore(junk2);
  
  Mat< std::complex<T> > l_eigvec;
  Mat< std::complex<T> > r_eigvec;
  
  Col< std::complex<T> > eigval;
  
  const bool status = auxlib::eig_pair(eigval, l_eigvec, r_eigvec, A, B, 'n');
  
  if(status == false)
    {
    eigval.reset();
    arma_bad("eig_pair(): failed to converge");
    }
  
  return eigval;
  }

inline
bool
princomp
  (
         Mat<typename T1::elem_type>&    coeff_out,
         Mat<typename T1::elem_type>&    score_out,
         Col<typename T1::pod_type>&     latent_out,
         Col<typename T1::elem_type>&    tsquared_out,
  const Base<typename T1::elem_type,T1>& X,
  const typename arma_blas_type_only<typename T1::elem_type>::result* junk = 0
  )
  {
  arma_extra_debug_sigprint();
  arma_ignore(junk);
  
  const bool status = op_princomp::direct_princomp(coeff_out, score_out, latent_out, tsquared_out, X);
  
  if(status == false)
    {
    coeff_out.reset();
    score_out.reset();
    latent_out.reset();
    tsquared_out.reset();
    
    arma_bad("princomp(): failed to converge", false);
    }
  
  return status;
  }

inline
bool
op_princomp::direct_princomp
  (
         Mat<typename T1::elem_type>&     coeff_out,
         Mat<typename T1::elem_type>&     score_out,
  const Base<typename T1::elem_type, T1>& X,
  const typename arma_not_cx<typename T1::elem_type>::result* junk
  )
  {
  arma_extra_debug_sigprint();
  arma_ignore(junk);
  
  typedef typename T1::elem_type eT;
  
  const unwrap_check<T1> Y( X.get_ref(), score_out );
  const Mat<eT>& in    = Y.M;
  
  const uword n_rows = in.n_rows;
  const uword n_cols = in.n_cols;
  
  if(n_rows > 1) // more than one sample
    {
    // subtract the mean - use score_out as temporary matrix
    score_out = in;  score_out.each_row() -= mean(in);
    
    // singular value decomposition
    Mat<eT> U;
    Col<eT> s;
    
    const bool svd_ok = svd(U, s, coeff_out, score_out);
    
    if(svd_ok == false)  { return false; }
    
    // normalize the eigenvalues
    s /= std::sqrt( double(n_rows - 1) );
    
    // project the samples to the principals
    score_out *= coeff_out;
    
    if(n_rows <= n_cols) // number of samples is less than their dimensionality
      {
      score_out.cols(n_rows-1,n_cols-1).zeros();
      
      Col<eT> s_tmp = zeros< Col<eT> >(n_cols);
      s_tmp.rows(0,n_rows-2) = s.rows(0,n_rows-2);
      s = s_tmp;
      }
    }
  else // 0 or 1 samples
    {
    coeff_out.eye(n_cols, n_cols);
    score_out.copy_size(in);
    score_out.zeros();
    }
  
  return true;
  }

inline
bool
op_princomp::direct_princomp
  (
        Mat<eT>& coeff_out,
        Mat<eT>& score_out,
  const Mat<eT>& in
  )
  {
  arma_extra_debug_sigprint();
  
  const u32 n_rows = in.n_rows;
  const u32 n_cols = in.n_cols;
  
  if(n_rows > 1) // more than one sample
    {
    // subtract the mean - use score_out as temporary matrix
    score_out = in - repmat(mean(in), n_rows, 1);
 	  
    // singular value decomposition
    Mat<eT> U;
    Col<eT> s;
    
    const bool svd_ok = svd(U,s,coeff_out,score_out);
    
    if(svd_ok == false)
      {
      return false;
      }
    
    // U.reset();
    
    // normalize the eigenvalues
    s /= std::sqrt( double(n_rows - 1) );
    
    // project the samples to the principals
    score_out *= coeff_out;
    
    if(n_rows <= n_cols) // number of samples is less than their dimensionality
      {
      score_out.cols(n_rows-1,n_cols-1).zeros();
      
      Col<eT> s_tmp = zeros< Col<eT> >(n_cols);
      s_tmp.rows(0,n_rows-2) = s.rows(0,n_rows-2);
      s = s_tmp;
      }
    }
  else // 0 or 1 samples
    {
    coeff_out.eye(n_cols, n_cols);
    score_out.copy_size(in);
    score_out.zeros();
    }
  
  return true;
  }

inline
bool
op_null::apply_direct(Mat<typename T1::elem_type>& out, const Base<typename T1::elem_type,T1>& expr, typename T1::pod_type tol)
  {
  arma_extra_debug_sigprint();
  
  typedef typename T1::elem_type eT;
  typedef typename T1::pod_type   T;
  
  arma_debug_check((tol < T(0)), "null(): tolerance must be >= 0");
  
  const unwrap<T1>   tmp(expr.get_ref());
  const Mat<eT>& X = tmp.M;
  
  Mat<eT> U;
  Col< T> s;
  Mat<eT> V;
  
  const bool status = auxlib::svd_dc(U, s, V, X);
  
  U.reset();
  
  if(status == false)  { out.reset(); return false; }
  
  if(s.is_empty())  { out.reset(); return true; }
  
  const uword s_n_elem = s.n_elem;
  const T*    s_mem    = s.memptr();
  
  // set tolerance to default if it hasn't been specified
  if(tol == T(0))  { tol = (std::max)(X.n_rows, X.n_cols) * s_mem[0] * std::numeric_limits<T>::epsilon(); }
  
  uword count = 0;
  
  for(uword i=0; i < s_n_elem; ++i)  { count += (s_mem[i] > tol) ? uword(1) : uword(0); }
  
  if(count < X.n_cols)
    {
    out = V.tail_cols(X.n_cols - count);
    
    const uword out_n_elem = out.n_elem;
          eT*   out_mem    = out.memptr();
    
    for(uword i=0; i<out_n_elem; ++i)
      {
      if(std::abs(out_mem[i]) < std::numeric_limits<T>::epsilon())  { out_mem[i] = eT(0); }
      }
    }
  else
    {
    out.set_size(X.n_cols, 0);
    }
  
  return true;
  }

bool PuzzleMaker::checkCol(int num, int col, int ypos)
{
	Col* toCheck = a->getCol(col);
	for(int i = 0; i < 9; i++)
	{
		int check = toCheck->getTile(i)->getNum();
		if( num == check && i != ypos)
			return false;
	}
	return true;
}

inline
arma_warn_unused
uword
rank
  (
  const Base<typename T1::elem_type,T1>& X,
        typename T1::pod_type            tol = 0.0,
  const typename arma_blas_type_only<typename T1::elem_type>::result* junk = 0
  )
  {
  arma_extra_debug_sigprint();
  arma_ignore(junk);
  
  typedef typename T1::pod_type T;
  
  uword  X_n_rows;
  uword  X_n_cols;
  Col<T> s;
  
  const bool  status = auxlib::svd_dc(s, X, X_n_rows, X_n_cols);
  const uword n_elem = s.n_elem;
  
  if(status == true)
    {
    if( (tol == T(0)) && (n_elem > 0) )
      {
      tol = (std::max)(X_n_rows, X_n_cols) * eop_aux::direct_eps(max(s));
      }
    
    // count non zero valued elements in s
    
    const T* s_mem = s.memptr();
    
    uword count = 0;
    
    for(uword i=0; i<n_elem; ++i)
      {
      if(s_mem[i] > tol) { ++count; }
      }
    
    return count;
    }
  else
    {
    arma_bad("rank(): failed to converge");
    
    return uword(0);
    }
  }