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diff --git a/src/armadillo/include/armadillo_bits/op_sqrtmat_meat.hpp b/src/armadillo/include/armadillo_bits/op_sqrtmat_meat.hpp
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@@ -0,0 +1,549 @@
+// SPDX-License-Identifier: Apache-2.0
+// 
+// Copyright 2008-2016 Conrad Sanderson (http://conradsanderson.id.au)
+// Copyright 2008-2016 National ICT Australia (NICTA)
+// 
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+// http://www.apache.org/licenses/LICENSE-2.0
+// 
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+// ------------------------------------------------------------------------
+
+
+//! \addtogroup op_sqrtmat
+//! @{
+
+
+//! implementation partly based on:
+//! N. J. Higham.
+//! A New sqrtm for Matlab.
+//! Numerical Analysis Report No. 336, January 1999.
+//! Department of Mathematics, University of Manchester.
+//! ISSN 1360-1725
+//! http://www.maths.manchester.ac.uk/~higham/narep/narep336.ps.gz
+
+
+template<typename T1>
+inline
+void
+op_sqrtmat::apply(Mat< std::complex<typename T1::elem_type> >& out, const mtOp<std::complex<typename T1::elem_type>,T1,op_sqrtmat>& in)
+  {
+  arma_extra_debug_sigprint();
+  
+  const bool status = op_sqrtmat::apply_direct(out, in.m);
+  
+  if(status == false)
+    {
+    arma_debug_warn_level(3, "sqrtmat(): given matrix is singular; may not have a square root");
+    }
+  }
+
+
+
+template<typename T1>
+inline
+bool
+op_sqrtmat::apply_direct(Mat< std::complex<typename T1::elem_type> >& out, const Op<T1,op_diagmat>& expr)
+  {
+  arma_extra_debug_sigprint();
+  
+  typedef typename T1::elem_type T;
+  
+  const diagmat_proxy<T1> P(expr.m);
+  
+  arma_debug_check( (P.n_rows != P.n_cols), "sqrtmat(): given matrix must be square sized" );
+  
+  const uword N = P.n_rows;
+  
+  out.zeros(N,N);
+  
+  bool singular = false;
+  
+  for(uword i=0; i<N; ++i)
+    {
+    const T val = P[i];
+    
+    if(val >= T(0))
+      {
+      singular = (singular || (val == T(0)));
+      
+      out.at(i,i) = std::sqrt(val);
+      }
+    else
+      {
+      out.at(i,i) = std::sqrt( std::complex<T>(val) );
+      }
+    }
+  
+  return (singular) ? false : true;
+  }
+
+
+
+template<typename T1>
+inline
+bool
+op_sqrtmat::apply_direct(Mat< std::complex<typename T1::elem_type> >& out, const Base<typename T1::elem_type,T1>& expr)
+  {
+  arma_extra_debug_sigprint();
+  
+  typedef typename T1::elem_type       in_T;
+  typedef typename std::complex<in_T> out_T;
+  
+  const quasi_unwrap<T1> expr_unwrap(expr.get_ref());
+  const Mat<in_T>& A   = expr_unwrap.M;
+  
+  arma_debug_check( (A.is_square() == false), "sqrtmat(): given matrix must be square sized" );
+  
+  if(A.n_elem == 0)
+    {
+    out.reset();
+    return true;
+    }
+  else
+  if(A.n_elem == 1)
+    {
+    out.set_size(1,1);
+    out[0] = std::sqrt( std::complex<in_T>( A[0] ) );
+    return true;
+    }
+  
+  if(A.is_diagmat())
+    {
+    arma_extra_debug_print("op_sqrtmat: detected diagonal matrix");
+    
+    const uword N = A.n_rows;
+    
+    out.zeros(N,N);  // aliasing can't happen as op_sqrtmat is defined as cx_mat = op(mat)
+    
+    for(uword i=0; i<N; ++i)
+      {
+      const in_T val = A.at(i,i);
+      
+      if(val >= in_T(0))
+        {
+        out.at(i,i) = std::sqrt(val);
+        }
+      else
+        {
+        out.at(i,i) = std::sqrt( out_T(val) );
+        }
+      }
+    
+    return true;
+    }
+  
+  const bool try_sympd = arma_config::optimise_sym && sym_helper::guess_sympd(A);
+  
+  if(try_sympd)
+    {
+    arma_extra_debug_print("op_sqrtmat: attempting sympd optimisation");
+    
+    // if matrix A is sympd, all its eigenvalues are positive
+    
+    Col<in_T> eigval;
+    Mat<in_T> eigvec;
+    
+    const bool eig_status = eig_sym_helper(eigval, eigvec, A, 'd', "sqrtmat()");
+    
+    if(eig_status)
+      {
+      // ensure each eigenvalue is > 0
+      
+      const uword N          = eigval.n_elem;
+      const in_T* eigval_mem = eigval.memptr();
+      
+      bool all_pos = true;
+      
+      for(uword i=0; i<N; ++i)  { all_pos = (eigval_mem[i] <= in_T(0)) ? false : all_pos; }
+      
+      if(all_pos)
+        {
+        eigval = sqrt(eigval);
+        
+        out = conv_to< Mat<out_T> >::from( eigvec * diagmat(eigval) * eigvec.t() );
+        
+        return true;
+        }
+      }
+    
+    arma_extra_debug_print("op_sqrtmat: sympd optimisation failed");
+    
+    // fallthrough if eigen decomposition failed or an eigenvalue is <= 0
+    }
+  
+  
+  Mat<out_T> U;
+  Mat<out_T> S(A.n_rows, A.n_cols, arma_nozeros_indicator());
+  
+  const  in_T* Amem = A.memptr();
+        out_T* Smem = S.memptr();
+  
+  const uword n_elem = A.n_elem;
+  
+  for(uword i=0; i<n_elem; ++i)
+    {
+    Smem[i] = std::complex<in_T>( Amem[i] );
+    }
+  
+  const bool schur_ok = auxlib::schur(U,S);
+  
+  if(schur_ok == false)
+    {
+    arma_extra_debug_print("sqrtmat(): schur decomposition failed");
+    out.soft_reset();
+    return false;
+    }
+  
+  const bool status = op_sqrtmat_cx::helper(S);
+  
+  const Mat<out_T> X = U*S;
+  
+  S.reset();
+  
+  out = X*U.t();
+  
+  return status;
+  }
+
+
+
+template<typename T1>
+inline
+void
+op_sqrtmat_cx::apply(Mat<typename T1::elem_type>& out, const Op<T1,op_sqrtmat_cx>& in)
+  {
+  arma_extra_debug_sigprint();
+  
+  const bool status = op_sqrtmat_cx::apply_direct(out, in.m);
+  
+  if(status == false)
+    {
+    arma_debug_warn_level(3, "sqrtmat(): given matrix is singular; may not have a square root");
+    }
+  }
+
+
+
+template<typename T1>
+inline
+bool
+op_sqrtmat_cx::apply_direct(Mat<typename T1::elem_type>& out, const Op<T1,op_diagmat>& expr)
+  {
+  arma_extra_debug_sigprint();
+  
+  typedef typename T1::elem_type eT;
+  
+  const diagmat_proxy<T1> P(expr.m);
+  
+  bool status = false;
+  
+  if(P.is_alias(out))
+    {
+    Mat<eT> tmp;
+    
+    status = op_sqrtmat_cx::apply_direct_noalias(tmp, P);
+    
+    out.steal_mem(tmp);
+    }
+  else
+    {
+    status = op_sqrtmat_cx::apply_direct_noalias(out, P);
+    }
+  
+  return status;
+  }
+
+
+
+template<typename T1>
+inline
+bool
+op_sqrtmat_cx::apply_direct_noalias(Mat<typename T1::elem_type>& out, const diagmat_proxy<T1>& P)
+  {
+  arma_extra_debug_sigprint();
+  
+  typedef typename T1::elem_type eT;
+  
+  arma_debug_check( (P.n_rows != P.n_cols), "sqrtmat(): given matrix must be square sized" );
+  
+  const uword N = P.n_rows;
+  
+  out.zeros(N,N);
+  
+  const eT zero = eT(0);
+  
+  bool singular = false;
+  
+  for(uword i=0; i<N; ++i)
+    {
+    const eT val = P[i];
+    
+    singular = (singular || (val == zero));
+    
+    out.at(i,i) = std::sqrt(val);
+    }
+  
+  return (singular) ? false : true;
+  }
+
+
+
+template<typename T1>
+inline
+bool
+op_sqrtmat_cx::apply_direct(Mat<typename T1::elem_type>& out, const Base<typename T1::elem_type,T1>& expr)
+  {
+  arma_extra_debug_sigprint();
+  
+  typedef typename T1::pod_type   T;
+  typedef typename T1::elem_type eT;
+  
+  Mat<eT> U;
+  Mat<eT> S = expr.get_ref();
+  
+  arma_debug_check( (S.n_rows != S.n_cols), "sqrtmat(): given matrix must be square sized" );
+  
+  if(S.n_elem == 0)
+    {
+    out.reset();
+    return true;
+    }
+  else
+  if(S.n_elem == 1)
+    {
+    out.set_size(1,1);
+    out[0] = std::sqrt(S[0]);
+    return true;
+    }
+  
+  if(S.is_diagmat())
+    {
+    arma_extra_debug_print("op_sqrtmat_cx: detected diagonal matrix");
+    
+    const uword N = S.n_rows;
+    
+    out.zeros(N,N);  // aliasing can't happen as S is generated
+    
+    for(uword i=0; i<N; ++i)  { out.at(i,i) = std::sqrt( S.at(i,i) ); }
+    
+    return true;
+    }
+  
+  const bool try_sympd = arma_config::optimise_sym && sym_helper::guess_sympd(S);
+  
+  if(try_sympd)
+    {
+    arma_extra_debug_print("op_sqrtmat_cx: attempting sympd optimisation");
+    
+    // if matrix S is sympd, all its eigenvalues are positive
+    
+    Col< T> eigval;
+    Mat<eT> eigvec;
+    
+    const bool eig_status = eig_sym_helper(eigval, eigvec, S, 'd', "sqrtmat()");
+    
+    if(eig_status)
+      {
+      // ensure each eigenvalue is > 0
+      
+      const uword N          = eigval.n_elem;
+      const T*    eigval_mem = eigval.memptr();
+      
+      bool all_pos = true;
+      
+      for(uword i=0; i<N; ++i)  { all_pos = (eigval_mem[i] <= T(0)) ? false : all_pos; }
+      
+      if(all_pos)
+        {
+        eigval = sqrt(eigval);
+        
+        out = eigvec * diagmat(eigval) * eigvec.t();
+        
+        return true;
+        }
+      }
+    
+    arma_extra_debug_print("op_sqrtmat_cx: sympd optimisation failed");
+    
+    // fallthrough if eigen decomposition failed or an eigenvalue is <= 0
+    }
+  
+  const bool schur_ok = auxlib::schur(U, S);
+  
+  if(schur_ok == false)
+    {
+    arma_extra_debug_print("sqrtmat(): schur decomposition failed");
+    out.soft_reset();
+    return false;
+    }
+  
+  const bool status = op_sqrtmat_cx::helper(S);
+  
+  const Mat<eT> X = U*S;
+  
+  S.reset();
+  
+  out = X*U.t();
+  
+  return status;
+  }
+
+
+
+template<typename T>
+inline
+bool
+op_sqrtmat_cx::helper(Mat< std::complex<T> >& S)
+  {
+  typedef typename std::complex<T> eT;
+  
+  if(S.is_empty())  { return true; }
+  
+  const uword N = S.n_rows;
+  
+  const eT zero = eT(0);
+  
+  eT& S_00 = S[0];
+  
+  bool singular = (S_00 == zero);
+  
+  S_00 = std::sqrt(S_00);
+  
+  for(uword j=1; j < N; ++j)
+    {
+    eT* S_j = S.colptr(j);
+    
+    eT& S_jj = S_j[j];
+    
+    singular = (singular || (S_jj == zero));
+    
+    S_jj = std::sqrt(S_jj);
+    
+    for(uword ii=0; ii <= (j-1); ++ii)
+      {
+      const uword i = (j-1) - ii;
+      
+      const eT* S_i = S.colptr(i);
+      
+      //S_j[i] /= (S_i[i] + S_j[j]);
+      S_j[i] /= (S_i[i] + S_jj);
+      
+      for(uword k=0; k < i; ++k)
+        {
+        S_j[k] -= S_i[k] * S_j[i];
+        }
+      }
+    }
+  
+  return (singular) ? false : true;
+  }
+
+
+
+template<typename T1>
+inline
+void
+op_sqrtmat_sympd::apply(Mat<typename T1::elem_type>& out, const Op<T1,op_sqrtmat_sympd>& in)
+  {
+  arma_extra_debug_sigprint();
+  
+  const bool status = op_sqrtmat_sympd::apply_direct(out, in.m);
+  
+  if(status == false)
+    {
+    out.soft_reset();
+    arma_stop_runtime_error("sqrtmat_sympd(): transformation failed");
+    }
+  }
+
+
+
+template<typename T1>
+inline
+bool
+op_sqrtmat_sympd::apply_direct(Mat<typename T1::elem_type>& out, const Base<typename T1::elem_type,T1>& expr)
+  {
+  arma_extra_debug_sigprint();
+  
+  #if defined(ARMA_USE_LAPACK)
+    {
+    typedef typename T1::elem_type eT;
+    typedef typename T1::pod_type   T;
+    
+    const unwrap<T1>   U(expr.get_ref());
+    const Mat<eT>& X = U.M;
+    
+    arma_debug_check( (X.is_square() == false), "sqrtmat_sympd(): given matrix must be square sized" );
+    
+    if((arma_config::debug) && (is_cx<eT>::yes) && (sym_helper::check_diag_imag(X) == false))
+      {
+      arma_debug_warn_level(1, "sqrtmat_sympd(): imaginary components on the diagonal are non-zero");
+      }
+    
+    if(is_op_diagmat<T1>::value || X.is_diagmat())
+      {
+      arma_extra_debug_print("op_sqrtmat_sympd: detected diagonal matrix");
+      
+      out = X;
+      
+      eT* colmem = out.memptr();
+      
+      const uword N = X.n_rows;
+      
+      for(uword i=0; i<N; ++i)
+        {
+        eT& out_ii      = colmem[i];
+         T  out_ii_real = access::tmp_real(out_ii);
+        
+        if(out_ii_real < T(0))  { return false; }
+        
+        out_ii = std::sqrt(out_ii);
+        
+        colmem += N;
+        }
+      
+      return true;
+      }
+    
+    Col< T> eigval;
+    Mat<eT> eigvec;
+    
+    const bool status = eig_sym_helper(eigval, eigvec, X, 'd', "sqrtmat_sympd()");
+    
+    if(status == false)  { return false; }
+    
+    const uword N          = eigval.n_elem;
+    const T*    eigval_mem = eigval.memptr();
+    
+    bool all_pos = true;
+    
+    for(uword i=0; i<N; ++i)  { all_pos = (eigval_mem[i] < T(0)) ? false : all_pos; }
+    
+    if(all_pos == false)  { return false; }
+    
+    eigval = sqrt(eigval);
+    
+    out = eigvec * diagmat(eigval) * eigvec.t();
+    
+    return true;
+    }
+  #else
+    {
+    arma_ignore(out);
+    arma_ignore(expr);
+    arma_stop_logic_error("sqrtmat_sympd(): use of LAPACK must be enabled");
+    return false;
+    }
+  #endif
+  }
+
+
+
+//! @}