mirror of
https://github.com/aportelli/LatAnalyze.git
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134 lines
4.1 KiB
C++
134 lines
4.1 KiB
C++
/*
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* Dataset.hpp, part of LatAnalyze 3
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*
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* Copyright (C) 2013 - 2016 Antonin Portelli
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*
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* LatAnalyze 3 is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* LatAnalyze 3 is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with LatAnalyze 3. If not, see <http://www.gnu.org/licenses/>.
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*/
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#ifndef Latan_Dataset_hpp_
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#define Latan_Dataset_hpp_
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#include <LatAnalyze/Global.hpp>
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#include <LatAnalyze/File.hpp>
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#include <LatAnalyze/StatArray.hpp>
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BEGIN_LATAN_NAMESPACE
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/******************************************************************************
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* Dataset class *
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******************************************************************************/
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template <typename T>
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class Dataset: public StatArray<T>
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{
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public:
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typedef std::random_device::result_type SeedType;
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public:
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// constructors
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Dataset(void) = default;
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Dataset(const Index size);
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EIGEN_EXPR_CTOR(Dataset, Dataset<T>, StatArray<T>, ArrayExpr)
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// destructor
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virtual ~Dataset(void) = default;
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// IO
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template <typename FileType>
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void load(const std::string &listFileName, const std::string &dataName);
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// resampling
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Sample<T> bootstrapMean(const Index nSample, const SeedType seed);
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Sample<T> bootstrapMean(const Index nSample);
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private:
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// mean from pointer vector for resampling
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void ptVectorMean(T &m, const std::vector<const T *> &v);
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};
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/******************************************************************************
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* Dataset template implementation *
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******************************************************************************/
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// constructors ////////////////////////////////////////////////////////////////
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template <typename T>
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Dataset<T>::Dataset(const Index size)
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: StatArray<T>(size)
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{}
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// IO //////////////////////////////////////////////////////////////////////////
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template <typename T>
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template <typename FileType>
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void Dataset<T>::load(const std::string &listFileName,
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const std::string &dataName)
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{
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FileType file;
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std::vector<std::string> dataFileName;
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dataFileName = readManifest(listFileName);
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this->resize(dataFileName.size());
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for (Index i = 0; i < static_cast<Index>(dataFileName.size()); ++i)
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{
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file.open(dataFileName[i], File::Mode::read);
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(*this)[i] = file.template read<T>(dataName);
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file.close();
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}
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}
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// resampling //////////////////////////////////////////////////////////////////
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template <typename T>
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Sample<T> Dataset<T>::bootstrapMean(const Index nSample, const SeedType seed)
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{
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std::vector<const T *> data(this->size());
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Sample<T> s(nSample);
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std::mt19937 gen(seed);
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std::uniform_int_distribution<Index> dis(0, this->size() - 1);
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for (unsigned int j = 0; j < this->size(); ++j)
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{
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data[j] = &((*this)[static_cast<Index>(j)]);
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}
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ptVectorMean(s[central], data);
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for (Index i = 0; i < nSample; ++i)
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{
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for (unsigned int j = 0; j < this->size(); ++j)
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{
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data[j] = &((*this)[dis(gen)]);
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}
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ptVectorMean(s[i], data);
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}
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return s;
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}
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template <typename T>
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Sample<T> Dataset<T>::bootstrapMean(const Index nSample)
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{
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std::random_device rd;
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return bootstrapMean(nSample, rd());
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}
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template <typename T>
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void Dataset<T>::ptVectorMean(T &m, const std::vector<const T *> &v)
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{
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if (v.size())
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{
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m = *(v[0]);
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for (unsigned int i = 1; i < v.size(); ++i)
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{
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m += *(v[i]);
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}
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m /= static_cast<double>(v.size());
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}
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}
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END_LATAN_NAMESPACE
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#endif // Latan_Dataset_hpp_
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