77 lines
2.2 KiB
C++
77 lines
2.2 KiB
C++
// SPDX-License-Identifier: Apache-2.0
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//
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// Copyright 2008-2016 Conrad Sanderson (http://conradsanderson.id.au)
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// Copyright 2008-2016 National ICT Australia (NICTA)
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// ------------------------------------------------------------------------
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//! \addtogroup op_mean
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//! @{
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//! Class for finding mean values of a matrix
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class op_mean
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: public traits_op_xvec
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{
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public:
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// dense matrices
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template<typename T1>
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inline static void apply(Mat<typename T1::elem_type>& out, const Op<T1,op_mean>& in);
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template<typename eT>
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inline static void apply_noalias(Mat<eT>& out, const Mat<eT>& X, const uword dim);
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// cubes
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template<typename T1>
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inline static void apply(Cube<typename T1::elem_type>& out, const OpCube<T1,op_mean>& in);
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template<typename eT>
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inline static void apply_noalias(Cube<eT>& out, const Cube<eT>& X, const uword dim);
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//
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template<typename eT>
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inline static eT direct_mean(const eT* X_mem, const uword N);
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template<typename eT>
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inline static eT direct_mean_robust(const eT old_mean, const eT* X_mem, const uword N);
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//
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template<typename T1>
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inline static typename T1::elem_type mean_all(const T1& X);
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template<typename T1>
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inline static typename T1::elem_type mean_all(const Op<T1, op_omit>& X);
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template<typename eT, typename functor>
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inline static eT mean_all_omit(const eT* X_mem, const uword N, functor is_omitted);
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//
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template<typename eT>
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arma_inline static eT robust_mean(const eT A, const eT B);
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template<typename T>
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arma_inline static std::complex<T> robust_mean(const std::complex<T>& A, const std::complex<T>& B);
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};
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//! @}
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