Namespaces
namespace	psdFilterTypes

namespace	window

Classes
struct	autocorrelationFromPSD
	Functor for calculating the autocorrelation given a PSD. More...

class	averagePeriodogram
	Calculate the average periodogram of a time-series. More...

class	circularBufferBase
	CRTP base class for all circular buffers, providing the underlying memory management and accessors. More...

class	circularBufferBranch
	Circular buffer which wraps with an if statement (branching) [faster than mod, less memory than index]. More...

class	circularBufferIndex
	Circular buffer which wraps with a pre-populated indices array [generally fastest]. More...

class	circularBufferMod
	Circular buffer which wraps with the mod opoerator [very slow]. More...

struct	fourierModeDef
	Structure to contain the parameters of a Fourier mode. More...

struct	linearPredictor
	A class to support linear prediction. More...

class	psdFilter

class	psdFilter< _realT, 1 >
	A class for filtering noise with PSDs using CUDA cuFFT. More...

class	psdFilter< _realT, _rank, 0 >
	A class for filtering noise with PSDs. More...

struct	psdVarMean
	Calculate the variance of the mean for a process given its PSD. More...

struct	psdVarMeanParams
	Parameters for calculating the variance of the mean from a numerical PSD. More...

Functions
template<typename realT >
realT	ar1FreqPhase (realT f, realT fsamp)
	Get the phase of a given frequency.

template<typename realT >
realT	ar1PSDNorm (realT beta, realT alpha, realT fpole, realT fsamp)
	Calculate the norm of an AR1 PSD.

template<typename realT >
void	ar1PSD (std::vector< realT > &psd, const std::vector< realT > &f, realT beta, realT alpha, realT fpole)
	Generate an AR1 PSD.

template<typename realT >
void	ar1PSD (std::vector< realT > &psd, const std::vector< realT > &f, realT beta, std::complex< realT > alpha)
	Generate an AR1 PSD.

template<typename realT >
void	arNPSD (std::vector< realT > &psd, const std::vector< realT > &f, realT fmax, realT var, std::vector< realT > alphaMag, std::vector< realT > alphaPhase)

template<typename T >
void	autocorrelation (T ac, size_t Nac, T sig, size_t Nsig)
	Calculate the autocorrelation of a time-series.

template<typename T >
void	autocorrelation (std::vector< T > &ac, std::vector< T > &sig)
	Calculate the autocorrelation of a time-series.

template<typename realT >
int	basisMask (improc::eigenCube< realT > &modes, improc::eigenImage< realT > &mask)
	Mask a basis set.

template<typename realT >
int	basisMeanSub (improc::eigenCube< realT > &modes, improc::eigenImage< realT > &mask, bool postMult=true)
	Mean-subtract a basis set.

template<typename realT >
int	basisNormalize (improc::eigenCube< realT > &modes, improc::eigenImage< realT > &mask)
	Normalize a basis set.

template<typename realT >
int	basisAmplitudes (std::vector< realT > &amps, improc::eigenImage< realT > &im, improc::eigenCube< realT > &modes, improc::eigenImage< realT > &mask, bool subtract=false, int meanIgnore=0, int N=-1)
	Measure the amplitudes of a set of basis modes fit to an image. Optionally subtract them.

template<int progress = 0, typename eigenTout , typename eigenTin >
void	gramSchmidt (eigenTout &out, const eigenTin &in, bool normalize=true)
	Perform Gram-Schmidt ortogonalization of a basis set, and normalize the result.

template<int progress = 0, typename eigenTout , typename eigenTin , typename eigenTWin >
void	gramSchmidt (eigenTout &out, const eigenTin &in, const eigenTWin &window)
	Perform Gram-Schmidt ortogonalization of a basis set on a window, and normalize the result.

template<int progress = 0, typename eigenT >
void	baseSpectrum (eigenT &bspect, eigenT &gsspect)

template<int progress = 0, typename eigenTout , typename eigenTout2 , typename eigenTin >
void	gramSchmidtSpectrum (eigenTout &out, eigenTout2 &spect, const eigenTin &in, typename eigenTin::Scalar normPix=0.0)
	Perform Gram-Schmidt ortogonalization of a basis set, and normalize the result, while recording the spectrum.

template<typename paramsT >
paramsT::realT	psdVarMeanFunc (typename paramsT::realT k, void *params)
	Integration worker function for psdVarMean::operator()

int	noll_j (unsigned int n, int m)

int	nZernRadOrd (unsigned int n)

Function Documentation

◆ arNPSD()

template<typename realT >

void mx::sigproc::arNPSD	(	std::vector< realT > &	psd,
		const std::vector< realT > &	f,
		realT	fmax,
		realT	var,
		std::vector< realT >	alphaMag,
		std::vector< realT >	alphaPhase
	)

Definition at line 150 of file arpsd.hpp.

References mx::math::six_fifths().

◆ baseSpectrum()

template<int progress = 0, typename eigenT >

void mx::sigproc::baseSpectrum	(	eigenT &	bspect,
		eigenT &	gsspect
	)

Definition at line 139 of file gramSchmidt.hpp.

Referenced by gramSchmidtSpectrum().

◆ noll_j()

int mx::sigproc::noll_j	(	unsigned int	n,
		int	m
	)

Definition at line 52 of file zernike.cpp.

◆ nZernRadOrd()

int mx::sigproc::nZernRadOrd ( unsigned int n )

Definition at line 70 of file zernike.cpp.

References noll_j().

◆ psdVarMeanFunc()

template<typename paramsT >

paramsT::realT mx::sigproc::psdVarMeanFunc	(	typename paramsT::realT	k,
		void *	params
	)

Integration worker function for psdVarMean::operator()

Template Parameters

paramsT the type of the parameter structure. See psdVarMean.

Returns: the value of the integrand at k

Parameters

[in]	k	the scaled frequency coordinate
[in]	params	pointer to the parameter structure

Definition at line 137 of file psdVarMean.hpp.