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GPLIB++
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Classes | |
| class | gplib::ArraySampleGenerator |
| Sequentially returns the elements of an array. More... | |
| class | gplib::Bootstrap< SampleGenerator > |
| Implementation of the Bootstrap error estimation method. More... | |
| class | gplib::Jacknife< SampleGenerator > |
| Implements the Jacknifing method of error estimation. More... | |
| class | gplib::MTSampleGenerator |
| Generate random elements of a calculated quantity for MT impedance data. More... | |
| class | gplib::StatErrEst< SampleGenerator > |
| This class is used as a base for stochastic error estimation. More... | |
Functions | |
| template<typename UblasMatrix > | |
| UblasMatrix | gplib::Cov (const UblasMatrix &observations) |
| Calculate the NxN covariance matrix for a NxM matrix of observations with 0 mean. More... | |
| template<typename UblasMatrix > | |
| void | gplib::PCA (const UblasMatrix &observations, gplib::cmat &evectors, gplib::cvec &evalues) |
| This template function calculates the principal component rotation matrix from a matrix of observations. More... | |
| gplib::cmat | gplib::WhiteMat (gplib::cmat &evectors, gplib::cvec &evalues) |
| Calculate the Whitening Matrix. More... | |
| gplib::cmat | gplib::DeWhiteMat (gplib::cmat &evectors, gplib::cvec &evalues) |
| Calculate the Dewhitening Matrix. More... | |
| template<typename InputIterator > | |
| std::iterator_traits < InputIterator >::value_type | gplib::Mean (InputIterator begin, InputIterator end) |
| Calculate the mean for a given range. More... | |
| template<typename InputIterator > | |
| std::iterator_traits < InputIterator >::value_type | gplib::Variance (InputIterator begin, InputIterator end, typename std::iterator_traits< InputIterator >::value_type mv) |
| Calculate the Variance and give the mean as a third input parameter. More... | |
| template<typename InputIterator > | |
| std::iterator_traits < InputIterator >::value_type | gplib::Variance (InputIterator begin, InputIterator end) |
| Calculate the Variance for a given range when the mean is not known and has to be calculated as well. More... | |
| template<typename InputIterator > | |
| std::iterator_traits < InputIterator >::value_type | gplib::MeanErr (InputIterator begin, InputIterator end) |
| Calculate the Mean Error for a given input range. More... | |
| template<typename InputIterator > | |
| std::iterator_traits < InputIterator >::value_type | gplib::MeanErr (InputIterator begin, InputIterator end, typename std::iterator_traits< InputIterator >::value_type mv) |
| Calculate the Mean Error for a given input range when the mean is known and passed as a third parameter. More... | |
| template<typename InputIterator > | |
| std::iterator_traits < InputIterator >::value_type | gplib::StdDev (InputIterator begin, InputIterator end, typename std::iterator_traits< InputIterator >::value_type mv) |
| Calculate the Standard deviation with a given mean. More... | |
| template<typename InputIterator > | |
| std::iterator_traits < InputIterator >::value_type | gplib::StdDev (InputIterator begin, InputIterator end) |
| Calculate the Standard Deviation. More... | |
| template<typename InputIterator > | |
| void | gplib::SubMean (InputIterator begin, InputIterator end, typename std::iterator_traits< InputIterator >::value_type mean) |
| Substract the mean from each element in the container, mean is passed as a parameter. More... | |
| template<typename InputIterator > | |
| void | gplib::SubMean (InputIterator begin, InputIterator end) |
| Substract the mean from each element in the container, mean is calculated. More... | |
| template<typename InputIterator > | |
| std::iterator_traits < InputIterator >::value_type | gplib::Median (InputIterator begin, InputIterator end) |
| Calculate the median for a vector style container. More... | |
| UblasMatrix gplib::Cov | ( | const UblasMatrix & | observations | ) |
Calculate the NxN covariance matrix for a NxM matrix of observations with 0 mean.
Definition at line 14 of file Cov.h.
Referenced by gplib::PCA().
| gplib::cmat gplib::DeWhiteMat | ( | gplib::cmat & | evectors, |
| gplib::cvec & | evalues | ||
| ) |
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inline |
Calculate the mean for a given range.
/file This header contains some simple statistical routines. All all templates for widest possible use
Definition at line 21 of file statutils.h.
Referenced by gplib::GeneralGA::DoIteration(), main(), gplib::MeanErr(), gplib::StdDev(), gplib::SubMean(), and gplib::Variance().
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Calculate the Mean Error for a given input range.
Definition at line 50 of file statutils.h.
References gplib::Mean().
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Calculate the Mean Error for a given input range when the mean is known and passed as a third parameter.
Definition at line 58 of file statutils.h.
References gplib::Variance().
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Calculate the median for a vector style container.
Definition at line 102 of file statutils.h.
Referenced by main().
| void gplib::PCA | ( | const UblasMatrix & | observations, |
| gplib::cmat & | evectors, | ||
| gplib::cvec & | evalues | ||
| ) |
This template function calculates the principal component rotation matrix from a matrix of observations.
/file This file contains function connected to Principal Component Analysis
The input matrix observations has the different channels (or datasets) as rows and corresponding samples as columns the parameter pcatrans will contain the matrix of principal component vectors, at the moment in no particular order
Definition at line 25 of file PCA.h.
References gplib::Cov(), and gplib::SubMean().
Referenced by gplib::ComplexICA(), gplib::FastICA(), and main().
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Calculate the Standard deviation with a given mean.
Definition at line 68 of file statutils.h.
References gplib::Variance().
Referenced by main(), and gplib::StdDev().
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Calculate the Standard Deviation.
Definition at line 77 of file statutils.h.
References gplib::Mean(), and gplib::StdDev().
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Substract the mean from each element in the container, mean is passed as a parameter.
Definition at line 85 of file statutils.h.
Referenced by gplib::PCA(), RemoveSpike(), gplib::ShortCorr(), gplib::StackedSpectrum(), gplib::SubMean(), and gplib::TimeFrequency().
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Substract the mean from each element in the container, mean is calculated.
Definition at line 95 of file statutils.h.
References gplib::Mean(), and gplib::SubMean().
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Calculate the Variance and give the mean as a third input parameter.
Definition at line 30 of file statutils.h.
Referenced by gplib::MeanErr(), gplib::StdDev(), and gplib::Variance().
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Calculate the Variance for a given range when the mean is not known and has to be calculated as well.
Definition at line 42 of file statutils.h.
References gplib::Mean(), and gplib::Variance().
| gplib::cmat gplib::WhiteMat | ( | gplib::cmat & | evectors, |
| gplib::cvec & | evalues | ||
| ) |
Calculate the Whitening Matrix.
Given the complex matrix of eigenvectors evectors and the complex vector of eigenvalues as calculated by PCA, calculate the Whitening Matrix and return it
Definition at line 46 of file PCA.h.
Referenced by gplib::ComplexICA(), gplib::FastICA(), and main().
1.8.6