UTILSLIB::Numerics Class Reference

Static numerical utility functions. More...

#include <numerics.h>

Public Member Functions
	~Numerics ()=default

Static Public Member Functions
static int	gcd (int iA, int iB)
static bool	issparse (Eigen::VectorXd &v)
static int	nchoose2 (int n)
static Eigen::MatrixXd	rescale (const Eigen::MatrixXd &data, const Eigen::RowVectorXf &times, const QPair< float, float > &baseline, QString mode)
static Eigen::MatrixXd	rescale (const Eigen::MatrixXd &data, const Eigen::RowVectorXf &times, const std::pair< float, float > &baseline, const std::string &mode)
template<typename T>
static double	log2 (const T d)
template<typename T>
static void	histcounts (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &matRawData, bool bMakeSymmetrical, int iClassAmount, Eigen::VectorXd &vecResultClassLimits, Eigen::VectorXi &vecResultFrequency, double dGlobalMin=0.0, double dGlobalMax=0.0)
template<typename T>
static void	histcounts (const Eigen::Matrix< T, Eigen::Dynamic, 1 > &matRawData, bool bMakeSymmetrical, int iClassAmount, Eigen::VectorXd &vecResultClassLimits, Eigen::VectorXi &vecResultFrequency, double dGlobalMin=0.0, double dGlobalMax=0.0)
template<typename T>
static void	histcounts (const Eigen::Matrix< T, 1, Eigen::Dynamic > &matRawData, bool bMakeSymmetrical, int iClassAmount, Eigen::VectorXd &vecResultClassLimits, Eigen::VectorXi &vecResultFrequency, double dGlobalMin=0.0, double dGlobalMax=0.0)

Detailed Description

Static numerical utility functions.

General numerical utility functions: GCD, log2, histograms, baseline rescaling, etc.

Definition at line 73 of file numerics.h.

Constructor & Destructor Documentation

~Numerics()

UTILSLIB::Numerics::~Numerics ( )

default

Destroys the Numerics object.

Member Function Documentation

gcd()

int Numerics::gcd ( int iA, int iB )

static

Finds the Greatest Common Divisor (GCD) of two integer values.

Parameters

[in]	iA	First input integer.
[in]	iB	Second input integer.

Returns

The Greatest Common Divisor (GCD) of iA and iB.

Definition at line 62 of file numerics.cpp.

histcounts() [1/3]

template<typename T>

void UTILSLIB::Numerics::histcounts ( const Eigen::Matrix< T, 1, Eigen::Dynamic > & matRawData, bool bMakeSymmetrical, int iClassAmount, Eigen::VectorXd & vecResultClassLimits, Eigen::VectorXi & vecResultFrequency, double dGlobalMin = 0.0, double dGlobalMax = 0.0 )

static

Definition at line 229 of file numerics.h.

histcounts() [2/3]

template<typename T>

void UTILSLIB::Numerics::histcounts ( const Eigen::Matrix< T, Eigen::Dynamic, 1 > & matRawData, bool bMakeSymmetrical, int iClassAmount, Eigen::VectorXd & vecResultClassLimits, Eigen::VectorXi & vecResultFrequency, double dGlobalMin = 0.0, double dGlobalMax = 0.0 )

static

Definition at line 213 of file numerics.h.

histcounts() [3/3]

template<typename T>

void UTILSLIB::Numerics::histcounts ( const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & matRawData, bool bMakeSymmetrical, int iClassAmount, Eigen::VectorXd & vecResultClassLimits, Eigen::VectorXi & vecResultFrequency, double dGlobalMin = 0.0, double dGlobalMax = 0.0 )

static

Creates a class and frequency distribution from data matrix.

Parameters

[in]	matRawData	Raw data matrix that needs to be analyzed.
[in]	bMakeSymmetrical	User input to turn the x-axis symmetric.
[in]	iClassAmount	User input to determine the amount of classes in the histogram.
[out]	vecResultClassLimits	The upper limit of each individual class.
[out]	vecResultFrequency	The amount of data that fits in the appropriate class ranges.
[in]	dGlobalMin	User input to determine the minimum value allowed in the histogram.
[in]	dGlobalMax	User input to determine the maximum value allowed in the histogram.

Definition at line 245 of file numerics.h.

issparse()

bool Numerics::issparse ( Eigen::VectorXd & v )

static

Determines if a given data (stored as vector v) are representing a sparse matrix.

Parameters

[in]

v

Data to be tested.

Returns

true if sparse, false otherwise.

Definition at line 73 of file numerics.cpp.

log2()

template<typename T>

double UTILSLIB::Numerics::log2 ( const T d )

inlinestatic

Compute log base 2 of a given number.

Parameters

[in]

d

Input value.

Returns

log2 of d.

Definition at line 205 of file numerics.h.

nchoose2()

int Numerics::nchoose2 ( int n )

static

Calculates the combination of n over 2 (nchoosek(n,2)).

Parameters

[in]

n

The number of elements which should be combined with each other (n over 2).

Returns

The number of combinations.

Definition at line 92 of file numerics.cpp.

rescale() [1/2]

Eigen::MatrixXd UTILSLIB::Numerics::rescale ( const Eigen::MatrixXd & data, const Eigen::RowVectorXf & times, const QPair< float, float > & baseline, QString mode )

static

Rescale (baseline correct) data.

Parameters

[in]	data	Data Matrix (m x n_time).
[in]	times	Time instants in seconds.
[in]	baseline	If baseline is (a, b) the interval is between "a (s)" and "b (s)". If a and b are equal, use interval between the beginning of the data and time 0.
[in]	mode	Baseline correction mode: "logratio" | "ratio" | "zscore" | "mean" | "percent".

Returns

Rescaled data matrix.

rescale() [2/2]

Eigen::MatrixXd UTILSLIB::Numerics::rescale ( const Eigen::MatrixXd & data, const Eigen::RowVectorXf & times, const std::pair< float, float > & baseline, const std::string & mode )

static

Rescale (baseline correct) data.

Parameters

[in]	data	Data Matrix (m x n_time).
[in]	times	Time instants in seconds.
[in]	baseline	If baseline is (a, b) the interval is between "a (s)" and "b (s)". If a and b are equal, use interval between the beginning of the data and time 0.
[in]	mode	Baseline correction mode: "logratio" | "ratio" | "zscore" | "mean" | "percent".

Returns

Rescaled data matrix.

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The documentation for this class was generated from the following files:

• src/libraries/math/numerics.h
• src/libraries/math/numerics.cpp