1 files changed, 115 insertions, 0 deletions
diff --git a/src/armadillo/include/armadillo_bits/op_mean_bones.hpp b/src/armadillo/include/armadillo_bits/op_mean_bones.hpp
new file mode 100644
index 0000000..20a86ae
--- /dev/null
+++ b/src/armadillo/include/armadillo_bits/op_mean_bones.hpp
@@ -0,0 +1,115 @@
+// 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_mean
+//! @{
+
+
+//! Class for finding mean values of a matrix
+class op_mean
+  : public traits_op_xvec
+  {
+  public:
+  
+  // dense matrices
+  
+  template<typename T1>
+  inline static void apply(Mat<typename T1::elem_type>& out, const Op<T1,op_mean>& in);
+  
+  template<typename T1>
+  inline static void apply_noalias(Mat<typename T1::elem_type>& out, const Proxy<T1>& P, const uword dim);
+  
+  template<typename T1>
+  inline static void apply_noalias_unwrap(Mat<typename T1::elem_type>& out, const Proxy<T1>& P, const uword dim);
+  
+  template<typename T1>
+  inline static void apply_noalias_proxy(Mat<typename T1::elem_type>& out, const Proxy<T1>& P, const uword dim);
+  
+  
+  // cubes
+  
+  template<typename T1>
+  inline static void apply(Cube<typename T1::elem_type>& out, const OpCube<T1,op_mean>& in);
+  
+  template<typename T1>
+  inline static void apply_noalias(Cube<typename T1::elem_type>& out, const ProxyCube<T1>& P, const uword dim);
+  
+  template<typename T1>
+  inline static void apply_noalias_unwrap(Cube<typename T1::elem_type>& out, const ProxyCube<T1>& P, const uword dim);
+  
+  template<typename T1>
+  inline static void apply_noalias_proxy(Cube<typename T1::elem_type>& out, const ProxyCube<T1>& P, const uword dim);
+  
+  
+  //
+  
+  template<typename eT>
+  inline static eT direct_mean(const eT* const X, const uword N);
+  
+  template<typename eT>
+  inline static eT direct_mean_robust(const eT* const X, const uword N);
+  
+
+  //
+  
+  template<typename eT>
+  inline static eT direct_mean(const Mat<eT>& X, const uword row);
+  
+  template<typename eT>
+  inline static eT direct_mean_robust(const Mat<eT>& X, const uword row);
+  
+
+  //
+  
+  template<typename eT>
+  inline static eT mean_all(const subview<eT>& X);
+  
+  template<typename eT>
+  inline static eT mean_all_robust(const subview<eT>& X);
+  
+  
+  //
+  
+  template<typename eT>
+  inline static eT mean_all(const diagview<eT>& X);
+  
+  template<typename eT>
+  inline static eT mean_all_robust(const diagview<eT>& X);
+  
+  
+  //
+  
+  template<typename T1>
+  inline static typename T1::elem_type mean_all(const Op<T1,op_vectorise_col>& X);
+  
+  template<typename T1>
+  inline static typename T1::elem_type mean_all(const Base<typename T1::elem_type, T1>& X);
+  
+  
+  //
+  
+  template<typename eT>
+  arma_inline static eT robust_mean(const eT A, const eT B);
+  
+  template<typename T>
+  arma_inline static std::complex<T> robust_mean(const std::complex<T>& A, const std::complex<T>& B);
+  };
+
+
+
+//! @}