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mirror of https://github.com/aportelli/LatAnalyze.git synced 2024-09-19 21:25:36 +01:00

first implementation of samples and datasets, still need IO for samples

This commit is contained in:
Antonin Portelli 2014-02-12 18:39:17 +00:00
parent 1a0cb2459e
commit f9e355e3ea
6 changed files with 390 additions and 39 deletions

155
latan/Dataset.hpp Normal file
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@ -0,0 +1,155 @@
/*
* Dataset.hpp, part of LatAnalyze 3
*
* Copyright (C) 2013 - 2014 Antonin Portelli
*
* LatAnalyze 3 is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* LatAnalyze 3 is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with LatAnalyze 3. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef Latan_Dataset_hpp_
#define Latan_Dataset_hpp_
#include <latan/Global.hpp>
#include <latan/Io.hpp>
#include <latan/Sample.hpp>
#include <latan/RandGen.hpp>
#include <fstream>
#include <vector>
BEGIN_NAMESPACE
/******************************************************************************
* Dataset class *
******************************************************************************/
template <typename T, typename FileType>
class Dataset: public StatArray<T>
{
private:
typedef StatArray<T> Base;
public:
// constructor
Dataset(void);
Dataset(const std::string &listFileName, const std::string &dataName);
template <typename Derived>
Dataset(const Eigen::EigenBase<Derived> &dataset);
// destructor
virtual ~Dataset(void);
// IO
void load(const std::string &listFileName, const std::string &dataName);
// resampling
Sample<T> bootstrapMean(const unsigned int nSample, RandGen& generator);
private:
// mean from pointer vector for resampling
void ptVectorMean(T &m, const std::vector<const T *> &v);
private:
FileType file_;
};
/******************************************************************************
* Dataset template implementation *
******************************************************************************/
// constructor /////////////////////////////////////////////////////////////////
template <typename T, typename FileType>
Dataset<T, FileType>::Dataset(void)
{}
template <typename T, typename FileType>
Dataset<T, FileType>::Dataset(const std::string &listFileName,
const std::string &dataName)
{
load(listFileName, dataName);
}
template <typename T, typename FileType>
template <typename Derived>
Dataset<T, FileType>::Dataset(const Eigen::EigenBase<Derived> &dataset)
: Base(dataset)
{}
// destructor //////////////////////////////////////////////////////////////////
template <typename T, typename FileType>
Dataset<T, FileType>::~Dataset(void)
{}
// IO //////////////////////////////////////////////////////////////////////////
template <typename T, typename FileType>
void Dataset<T, FileType>::load(const std::string &listFileName,
const std::string &dataName)
{
std::ifstream listFile;
char dataFileNameBuf[MAX_PATH_LENGTH];
std::vector<std::string> dataFileName;
listFile.open(listFileName, std::ios::in);
while (!listFile.eof())
{
listFile.getline(dataFileNameBuf, MAX_PATH_LENGTH);
if (!std::string(dataFileNameBuf).empty())
{
dataFileName.push_back(dataFileNameBuf);
}
}
listFile.close();
this->resize(dataFileName.size());
for (unsigned int i = 0; i < dataFileName.size(); ++i)
{
file_.open(dataFileName[i], File::Mode::read);
(*this)[i] = file_.template read<T>(dataName);
file_.close();
}
}
// resampling //////////////////////////////////////////////////////////////////
template <typename T, typename FileType>
Sample<T> Dataset<T, FileType>::bootstrapMean(const unsigned int nSample,
RandGen& generator)
{
unsigned int nData = this->size();
std::vector<const T *> data(nData);
Sample<T> s(nSample);
for (unsigned int j = 0; j < nData; ++j)
{
data[j] = &((*this)[j]);
}
ptVectorMean(s[central], data);
for (unsigned int i = 0; i < nSample; ++i)
{
for (unsigned int j = 0; j < nData; ++j)
{
data[j] = &((*this)[generator.discreteUniform(nData)]);
}
ptVectorMean(s[i], data);
}
return s;
}
template <typename T, typename FileType>
void Dataset<T, FileType>::ptVectorMean(T &m, const std::vector<const T *> &v)
{
if (v.size())
{
m = *(v[0]);
for (unsigned int i = 1; i < v.size(); ++i)
{
m += *(v[i]);
}
m /= static_cast<double>(v.size());
}
}
END_NAMESPACE
#endif // Latan_Dataset_hpp_

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@ -33,10 +33,10 @@ public:
public:
enum
{
noType = 0,
dMat = 1,
sample = 2,
rgState = 3
noType = 0,
dMat = 1,
dMatSample = 2,
rgState = 3
};
};
public:

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@ -45,6 +45,7 @@ liblatan_la_SOURCES = \
liblatan_ladir = $(pkgincludedir)
liblatan_la_HEADERS = \
CompiledFunction.hpp\
Dataset.hpp \
Function.hpp \
Global.hpp \
Io.hpp \
@ -55,7 +56,8 @@ liblatan_la_HEADERS = \
ParserState.hpp \
Plot.hpp \
RandGen.hpp \
Sample.hpp
Sample.hpp \
StatArray.hpp
liblatan_la_CFLAGS = $(COM_CFLAGS)
liblatan_la_CXXFLAGS = $(COM_CXXFLAGS)

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@ -21,29 +21,10 @@
#include <latan/includes.hpp>
using namespace Latan;
using namespace std;
DSample::DSample(void)
: DSampleBase(static_cast<Index>(0))
{}
DSample::DSample(const unsigned int nSample, const unsigned int nRow,
const unsigned int nCol)
: DSampleBase(static_cast<Index>(nSample + 1))
template <>
unsigned int Sample<DMat>::getType(void) const
{
for (int s = 0; s < size(); ++s)
{
(*this)(s).resize(nRow, nCol);
}
}
DMat& DSample::operator()(const int s)
{
if (s >= 0)
{
return (*this)(s + 1);
}
else
{
return (*this)(0);
}
return IoType::dMatSample;
}

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@ -21,26 +21,98 @@
#define Latan_Sample_hpp_
#include <latan/Global.hpp>
#include <latan/IoObject.hpp>
#include <latan/Mat.hpp>
#include <latan/StatArray.hpp>
BEGIN_NAMESPACE
const int Central = -1;
const int central = -1;
typedef Eigen::Array<DMat, Eigen::Dynamic, 1> DSampleBase;
class DSample: public DSampleBase
/******************************************************************************
* Sample class *
******************************************************************************/
template <typename T>
class Sample: public StatArray<T>, public IoObject
{
private:
typedef StatArray<T> Base;
public:
// Constructors/destructor
DSample(void);
DSample(const unsigned int nSample, const unsigned int nRow,
const unsigned int nCol);
~DSample(void);
// Operators
DMat& operator()(const int s);
// constructors
Sample(void);
Sample(const unsigned int nSample);
template <typename Derived>
Sample(const Eigen::EigenBase<Derived> &s);
// destructor
virtual ~Sample(void);
// operators
T& operator[](const int s);
// IO type
virtual unsigned int getType(void) const;
private:
// index of the first element to take into account for statistics
virtual unsigned int getOffset(void) const;
};
template <>
unsigned int Sample<DMat>::getType(void) const;
// specialization aliases
typedef Sample<DMat> DMatSample;
/******************************************************************************
* Sample class template implementation *
******************************************************************************/
// constructor /////////////////////////////////////////////////////////////////
template <typename T>
Sample<T>::Sample(void)
: Base(static_cast<typename Base::Index>(getOffset()))
{}
template <typename T>
Sample<T>::Sample(const unsigned int nSample)
: Base(static_cast<typename Base::Index>(nSample + getOffset()))
{}
template <typename T>
template <typename Derived>
Sample<T>::Sample(const Eigen::EigenBase<Derived> &s)
: Base(s)
{}
// destructor //////////////////////////////////////////////////////////////////
template <typename T>
Sample<T>::~Sample(void)
{}
// operators ///////////////////////////////////////////////////////////////////
template <typename T>
T& Sample<T>::operator[](const int s)
{
if (s >= 0)
{
return Base::operator[](s + 1);
}
else
{
return Base::operator[](0);
}
}
// IO type /////////////////////////////////////////////////////////////////////
template <typename T>
unsigned int Sample<T>::getType(void) const
{
return IoType::noType;
}
// statistics //////////////////////////////////////////////////////////////////
template <typename T>
unsigned int Sample<T>::getOffset(void) const
{
return 1u;
}
END_NAMESPACE
#endif // Latan_Sample_hpp_

141
latan/StatArray.hpp Normal file
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@ -0,0 +1,141 @@
/*
* StatArray.hpp, part of LatAnalyze 3
*
* Copyright (C) 2013 - 2014 Antonin Portelli
*
* LatAnalyze 3 is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* LatAnalyze 3 is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with LatAnalyze 3. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef Latan_StatArray_hpp_
#define Latan_StatArray_hpp_
#include <latan/Global.hpp>
#include <latan/Mat.hpp>
BEGIN_NAMESPACE
/******************************************************************************
* Array class with statistics *
******************************************************************************/
template <typename T>
class StatArray: public Eigen::Array<T, Eigen::Dynamic, 1>
{
private:
typedef Eigen::Array<T, Eigen::Dynamic, 1> Base;
public:
// constructors
StatArray(void);
StatArray(const unsigned int size);
template <typename Derived>
StatArray(const Eigen::EigenBase<Derived> &s);
// destructor
virtual ~StatArray(void);
// statistics
T mean(void) const;
T variance(void) const;
private:
// index of the first element to take into account for statistics
virtual unsigned int getOffset(void) const;
// operations for reduction in statistical computations
static inline T square(const T &a);
static inline T sum(const T &a, const T &b);
};
template <>
inline DMat StatArray<DMat>::square(const DMat &a);
/******************************************************************************
* StatArray class template implementation *
******************************************************************************/
// constructors ////////////////////////////////////////////////////////////////
template <typename T>
StatArray<T>::StatArray(void)
: Base(static_cast<typename Base::Index>(1))
{}
template <typename T>
StatArray<T>::StatArray(const unsigned int size)
: Base(static_cast<typename Base::Index>(size))
{}
template <typename T>
template <typename Derived>
StatArray<T>::StatArray(const Eigen::EigenBase<Derived> &s)
: Base(s)
{}
// destructor //////////////////////////////////////////////////////////////////
template <typename T>
StatArray<T>::~StatArray(void)
{}
// statistics //////////////////////////////////////////////////////////////////
template <typename T>
T StatArray<T>::mean(void) const
{
T result;
unsigned int size = this->size() - getOffset();
if (size)
{
result = this->tail(size).redux(&StatArray<T>::sum);
}
return result/static_cast<double>(size);
}
template <typename T>
T StatArray<T>::variance(void) const
{
T s, sqs, result;
unsigned int size = this->size() - getOffset();
if (size)
{
s = this->tail(size).redux(&StatArray<T>::sum);
sqs = this->tail(size).unaryExpr(&StatArray<T>::square)
.redux(&StatArray<T>::sum);
result = sqs - square(s)/static_cast<double>(size);
}
return result/static_cast<double>(size - 1);
}
template <typename T>
inline T StatArray<T>::sum(const T &a, const T &b)
{
return a + b;
}
template <typename T>
inline T StatArray<T>::square(const T &a)
{
return a*a;
}
template <>
inline DMat StatArray<DMat>::square(const DMat &a)
{
return a.cwiseProduct(a);
}
template <typename T>
unsigned int StatArray<T>::getOffset(void) const
{
return 0u;
}
END_NAMESPACE
#endif // Latan_StatArray_hpp_