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first implementation of samples and datasets, still need IO for samples
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155
latan/Dataset.hpp
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155
latan/Dataset.hpp
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/*
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* Dataset.hpp, part of LatAnalyze 3
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*
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* Copyright (C) 2013 - 2014 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 <latan/Global.hpp>
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#include <latan/Io.hpp>
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#include <latan/Sample.hpp>
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#include <latan/RandGen.hpp>
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#include <fstream>
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#include <vector>
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BEGIN_NAMESPACE
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/******************************************************************************
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* Dataset class *
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******************************************************************************/
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template <typename T, typename FileType>
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class Dataset: public StatArray<T>
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{
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private:
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typedef StatArray<T> Base;
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public:
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// constructor
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Dataset(void);
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Dataset(const std::string &listFileName, const std::string &dataName);
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template <typename Derived>
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Dataset(const Eigen::EigenBase<Derived> &dataset);
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// destructor
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virtual ~Dataset(void);
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// IO
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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 unsigned int nSample, RandGen& generator);
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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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private:
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FileType file_;
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};
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/******************************************************************************
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* Dataset template implementation *
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******************************************************************************/
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// constructor /////////////////////////////////////////////////////////////////
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template <typename T, typename FileType>
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Dataset<T, FileType>::Dataset(void)
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{}
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template <typename T, typename FileType>
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Dataset<T, FileType>::Dataset(const std::string &listFileName,
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const std::string &dataName)
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{
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load(listFileName, dataName);
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}
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template <typename T, typename FileType>
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template <typename Derived>
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Dataset<T, FileType>::Dataset(const Eigen::EigenBase<Derived> &dataset)
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: Base(dataset)
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{}
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// destructor //////////////////////////////////////////////////////////////////
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template <typename T, typename FileType>
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Dataset<T, FileType>::~Dataset(void)
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{}
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// IO //////////////////////////////////////////////////////////////////////////
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template <typename T, typename FileType>
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void Dataset<T, FileType>::load(const std::string &listFileName,
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const std::string &dataName)
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{
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std::ifstream listFile;
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char dataFileNameBuf[MAX_PATH_LENGTH];
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std::vector<std::string> dataFileName;
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listFile.open(listFileName, std::ios::in);
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while (!listFile.eof())
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{
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listFile.getline(dataFileNameBuf, MAX_PATH_LENGTH);
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if (!std::string(dataFileNameBuf).empty())
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{
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dataFileName.push_back(dataFileNameBuf);
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}
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}
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listFile.close();
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this->resize(dataFileName.size());
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for (unsigned int i = 0; i < 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, typename FileType>
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Sample<T> Dataset<T, FileType>::bootstrapMean(const unsigned int nSample,
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RandGen& generator)
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{
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unsigned int nData = this->size();
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std::vector<const T *> data(nData);
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Sample<T> s(nSample);
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for (unsigned int j = 0; j < nData; ++j)
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{
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data[j] = &((*this)[j]);
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}
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ptVectorMean(s[central], data);
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for (unsigned int i = 0; i < nSample; ++i)
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{
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for (unsigned int j = 0; j < nData; ++j)
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{
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data[j] = &((*this)[generator.discreteUniform(nData)]);
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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, typename FileType>
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void Dataset<T, FileType>::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_NAMESPACE
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#endif // Latan_Dataset_hpp_
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@ -33,10 +33,10 @@ public:
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public:
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enum
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{
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noType = 0,
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dMat = 1,
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sample = 2,
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rgState = 3
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noType = 0,
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dMat = 1,
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dMatSample = 2,
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rgState = 3
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};
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};
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public:
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@ -45,6 +45,7 @@ liblatan_la_SOURCES = \
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liblatan_ladir = $(pkgincludedir)
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liblatan_la_HEADERS = \
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CompiledFunction.hpp\
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Dataset.hpp \
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Function.hpp \
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Global.hpp \
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Io.hpp \
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@ -55,7 +56,8 @@ liblatan_la_HEADERS = \
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ParserState.hpp \
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Plot.hpp \
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RandGen.hpp \
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Sample.hpp
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Sample.hpp \
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StatArray.hpp
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liblatan_la_CFLAGS = $(COM_CFLAGS)
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liblatan_la_CXXFLAGS = $(COM_CXXFLAGS)
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@ -21,29 +21,10 @@
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#include <latan/includes.hpp>
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using namespace Latan;
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using namespace std;
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DSample::DSample(void)
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: DSampleBase(static_cast<Index>(0))
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{}
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DSample::DSample(const unsigned int nSample, const unsigned int nRow,
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const unsigned int nCol)
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: DSampleBase(static_cast<Index>(nSample + 1))
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template <>
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unsigned int Sample<DMat>::getType(void) const
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{
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for (int s = 0; s < size(); ++s)
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{
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(*this)(s).resize(nRow, nCol);
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}
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}
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DMat& DSample::operator()(const int s)
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{
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if (s >= 0)
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{
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return (*this)(s + 1);
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}
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else
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{
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return (*this)(0);
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}
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return IoType::dMatSample;
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}
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#define Latan_Sample_hpp_
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#include <latan/Global.hpp>
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#include <latan/IoObject.hpp>
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#include <latan/Mat.hpp>
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#include <latan/StatArray.hpp>
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BEGIN_NAMESPACE
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const int Central = -1;
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const int central = -1;
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typedef Eigen::Array<DMat, Eigen::Dynamic, 1> DSampleBase;
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class DSample: public DSampleBase
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/******************************************************************************
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* Sample class *
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******************************************************************************/
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template <typename T>
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class Sample: public StatArray<T>, public IoObject
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{
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private:
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typedef StatArray<T> Base;
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public:
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// Constructors/destructor
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DSample(void);
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DSample(const unsigned int nSample, const unsigned int nRow,
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const unsigned int nCol);
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~DSample(void);
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// Operators
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DMat& operator()(const int s);
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// constructors
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Sample(void);
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Sample(const unsigned int nSample);
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template <typename Derived>
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Sample(const Eigen::EigenBase<Derived> &s);
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// destructor
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virtual ~Sample(void);
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// operators
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T& operator[](const int s);
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// IO type
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virtual unsigned int getType(void) const;
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private:
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// index of the first element to take into account for statistics
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virtual unsigned int getOffset(void) const;
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};
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template <>
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unsigned int Sample<DMat>::getType(void) const;
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// specialization aliases
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typedef Sample<DMat> DMatSample;
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/******************************************************************************
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* Sample class template implementation *
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******************************************************************************/
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// constructor /////////////////////////////////////////////////////////////////
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template <typename T>
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Sample<T>::Sample(void)
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: Base(static_cast<typename Base::Index>(getOffset()))
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{}
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template <typename T>
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Sample<T>::Sample(const unsigned int nSample)
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: Base(static_cast<typename Base::Index>(nSample + getOffset()))
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{}
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template <typename T>
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template <typename Derived>
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Sample<T>::Sample(const Eigen::EigenBase<Derived> &s)
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: Base(s)
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{}
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// destructor //////////////////////////////////////////////////////////////////
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template <typename T>
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Sample<T>::~Sample(void)
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{}
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// operators ///////////////////////////////////////////////////////////////////
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template <typename T>
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T& Sample<T>::operator[](const int s)
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{
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if (s >= 0)
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{
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return Base::operator[](s + 1);
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}
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else
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{
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return Base::operator[](0);
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}
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}
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// IO type /////////////////////////////////////////////////////////////////////
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template <typename T>
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unsigned int Sample<T>::getType(void) const
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{
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return IoType::noType;
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}
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// statistics //////////////////////////////////////////////////////////////////
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template <typename T>
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unsigned int Sample<T>::getOffset(void) const
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{
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return 1u;
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}
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END_NAMESPACE
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#endif // Latan_Sample_hpp_
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141
latan/StatArray.hpp
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141
latan/StatArray.hpp
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/*
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* StatArray.hpp, part of LatAnalyze 3
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*
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* Copyright (C) 2013 - 2014 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_StatArray_hpp_
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#define Latan_StatArray_hpp_
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#include <latan/Global.hpp>
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#include <latan/Mat.hpp>
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BEGIN_NAMESPACE
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/******************************************************************************
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* Array class with statistics *
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******************************************************************************/
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template <typename T>
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class StatArray: public Eigen::Array<T, Eigen::Dynamic, 1>
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{
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private:
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typedef Eigen::Array<T, Eigen::Dynamic, 1> Base;
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public:
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// constructors
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StatArray(void);
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StatArray(const unsigned int size);
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template <typename Derived>
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StatArray(const Eigen::EigenBase<Derived> &s);
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// destructor
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virtual ~StatArray(void);
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// statistics
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T mean(void) const;
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T variance(void) const;
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private:
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// index of the first element to take into account for statistics
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virtual unsigned int getOffset(void) const;
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// operations for reduction in statistical computations
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static inline T square(const T &a);
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static inline T sum(const T &a, const T &b);
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};
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template <>
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inline DMat StatArray<DMat>::square(const DMat &a);
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/******************************************************************************
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* StatArray class template implementation *
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******************************************************************************/
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// constructors ////////////////////////////////////////////////////////////////
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template <typename T>
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StatArray<T>::StatArray(void)
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: Base(static_cast<typename Base::Index>(1))
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{}
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template <typename T>
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StatArray<T>::StatArray(const unsigned int size)
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: Base(static_cast<typename Base::Index>(size))
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{}
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template <typename T>
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template <typename Derived>
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StatArray<T>::StatArray(const Eigen::EigenBase<Derived> &s)
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: Base(s)
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{}
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// destructor //////////////////////////////////////////////////////////////////
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template <typename T>
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StatArray<T>::~StatArray(void)
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{}
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// statistics //////////////////////////////////////////////////////////////////
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template <typename T>
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T StatArray<T>::mean(void) const
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{
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T result;
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unsigned int size = this->size() - getOffset();
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if (size)
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{
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result = this->tail(size).redux(&StatArray<T>::sum);
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}
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return result/static_cast<double>(size);
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}
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template <typename T>
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T StatArray<T>::variance(void) const
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{
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T s, sqs, result;
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unsigned int size = this->size() - getOffset();
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if (size)
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{
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s = this->tail(size).redux(&StatArray<T>::sum);
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sqs = this->tail(size).unaryExpr(&StatArray<T>::square)
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.redux(&StatArray<T>::sum);
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result = sqs - square(s)/static_cast<double>(size);
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}
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return result/static_cast<double>(size - 1);
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}
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template <typename T>
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inline T StatArray<T>::sum(const T &a, const T &b)
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{
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return a + b;
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}
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template <typename T>
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inline T StatArray<T>::square(const T &a)
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{
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return a*a;
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}
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template <>
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inline DMat StatArray<DMat>::square(const DMat &a)
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{
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return a.cwiseProduct(a);
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}
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template <typename T>
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unsigned int StatArray<T>::getOffset(void) const
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{
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return 0u;
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}
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END_NAMESPACE
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#endif // Latan_StatArray_hpp_
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