/* * 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> #include <iostream> BEGIN_NAMESPACE /****************************************************************************** * Array class with statistics * ******************************************************************************/ template <typename T, unsigned int offset = 0> class StatArray: public Array<T, dynamic, 1> { private: typedef Array<T, dynamic, 1> Base; public: // constructors StatArray(void); explicit StatArray(const Index size); EIGEN_EXPR_CTOR(StatArray, unique_arg(StatArray<T, offset>), Base, ArrayBase) // destructor virtual ~StatArray(void) = default; // access Index size(void) const; // operators T & operator[](const Index s); const T & operator[](const Index s) const; // statistics void bin(Index binSize); T mean(const Index pos, const Index n) const; T mean(void) const; T variance(const Index pos, const Index n) const; T variance(void) const; }; // reduction operations namespace ReducOp { template <typename T> inline T square(const T &a); template <typename T> inline T sum(const T &a, const T &b); template <> inline DMat square(const DMat &a); } /****************************************************************************** * StatArray class template implementation * ******************************************************************************/ // constructors //////////////////////////////////////////////////////////////// template <typename T, unsigned int offset> StatArray<T, offset>::StatArray(void) : Base(static_cast<typename Base::Index>(offset)) {} template <typename T, unsigned int offset> StatArray<T, offset>::StatArray(const Index size) : Base(static_cast<typename Base::Index>(size + offset)) {} // access ////////////////////////////////////////////////////////////////////// template <typename T, unsigned int offset> Index StatArray<T, offset>::size(void) const { return Base::size() - offset; } // operators /////////////////////////////////////////////////////////////////// template <typename T, unsigned int offset> T & StatArray<T, offset>::operator[](const Index s) { return Base::operator[](s + offset); } template <typename T, unsigned int offset> const T & StatArray<T, offset>::operator[](const Index s) const { return Base::operator[](s + offset); } // statistics ////////////////////////////////////////////////////////////////// template <typename T, unsigned int offset> void StatArray<T, offset>::bin(Index binSize) { Index q = size()/binSize, r = size()%binSize; for (Index i = 0; i < q; ++i) { (*this)[i] = mean(i*binSize, binSize); } if (r != 0) { (*this)[q] = mean(q*binSize, r); this->conservativeResize(offset + q + 1); } else { this->conservativeResize(offset + q); } } template <typename T, unsigned int offset> T StatArray<T, offset>::mean(const Index pos, const Index n) const { T result; if (n) { result = this->segment(pos+offset, n).redux(&ReducOp::sum<T>); } return result/static_cast<double>(n); } template <typename T, unsigned int offset> T StatArray<T, offset>::mean(void) const { return mean(0, size()); } template <typename T, unsigned int offset> T StatArray<T, offset>::variance(const Index pos, const Index n) const { T s, sqs, result; if (n) { s = this->segment(pos+offset, n).redux(&ReducOp::sum<T>); sqs = this->segment(pos+offset, n).unaryExpr(&ReducOp::square<T>) .redux(&ReducOp::sum<T>); result = sqs - ReducOp::square(s)/static_cast<double>(n); } return result/static_cast<double>(n - 1); } template <typename T, unsigned int offset> T StatArray<T, offset>::variance(void) const { return variance(0, size()); } // reduction operations //////////////////////////////////////////////////////// template <typename T> inline T ReducOp::sum(const T &a, const T &b) { return a + b; } template <typename T> inline T ReducOp::square(const T &a) { return a*a; } template <> inline DMat ReducOp::square(const DMat &a) { return a.cwiseProduct(a); } END_NAMESPACE #endif // Latan_StatArray_hpp_