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author | Nao Pross <np@0hm.ch> | 2024-02-12 14:52:43 +0100 |
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committer | Nao Pross <np@0hm.ch> | 2024-02-12 14:52:43 +0100 |
commit | eda5bc26f44ee9a6f83dcf8c91f17296d7fc509d (patch) | |
tree | bc2efa38ff4e350f9a111ac87065cd7ae9a911c7 /src/armadillo/include/armadillo_bits/spop_var_bones.hpp | |
download | fsisotool-eda5bc26f44ee9a6f83dcf8c91f17296d7fc509d.tar.gz fsisotool-eda5bc26f44ee9a6f83dcf8c91f17296d7fc509d.zip |
Move into version control
Diffstat (limited to 'src/armadillo/include/armadillo_bits/spop_var_bones.hpp')
-rw-r--r-- | src/armadillo/include/armadillo_bits/spop_var_bones.hpp | 64 |
1 files changed, 64 insertions, 0 deletions
diff --git a/src/armadillo/include/armadillo_bits/spop_var_bones.hpp b/src/armadillo/include/armadillo_bits/spop_var_bones.hpp new file mode 100644 index 0000000..09f0e24 --- /dev/null +++ b/src/armadillo/include/armadillo_bits/spop_var_bones.hpp @@ -0,0 +1,64 @@ +// 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 spop_var +//! @{ + + + +//! Class for finding variance values of a sparse matrix +class spop_var + : public traits_op_xvec + { + public: + + template<typename T1> + inline static void apply(SpMat<typename T1::pod_type>& out, const mtSpOp<typename T1::pod_type, T1, spop_var>& in); + + template<typename T1> + inline static void apply_noalias(SpMat<typename T1::pod_type>& out, const SpProxy<T1>& p, const uword norm_type, const uword dim); + + // Calculate variance of a sparse vector, where we can directly use the memory. + template<typename T1> + inline static typename T1::pod_type var_vec(const T1& X, const uword norm_type = 0); + + // Calculate the variance directly. Because this is for sparse matrices, we + // specify both the number of elements in the array (the length of the array) + // as well as the actual number of elements when zeros are included. + template<typename eT> + inline static eT direct_var(const eT* const X, const uword length, const uword N, const uword norm_type = 0); + + // For complex numbers. + + template<typename T> + inline static T direct_var(const std::complex<T>* const X, const uword length, const uword N, const uword norm_type = 0); + + // Calculate the variance using iterators, for non-complex numbers. + template<typename T1, typename eT> + inline static eT iterator_var(T1& it, const T1& end, const uword n_zero, const uword norm_type, const eT junk1, const typename arma_not_cx<eT>::result* junk2 = nullptr); + + // Calculate the variance using iterators, for complex numbers. + template<typename T1, typename eT> + inline static typename get_pod_type<eT>::result iterator_var(T1& it, const T1& end, const uword n_zero, const uword norm_type, const eT junk1, const typename arma_cx_only<eT>::result* junk2 = nullptr); + + }; + + + +//! @} + |