Function prototypes for linear autoregressive prediction. More...

Functions
int_fast8_t	init_linARfilterPred ()

2. I/O TOOLS
int	NBwords (const char sentence[])

long	LINARFILTERPRED_LoadASCIIfiles (double tstart, double dt, long NBpt, long NBfr, const char *IDoutname)
	load ascii file(s) into image cube More...

long	LINARFILTERPRED_SelectBlock (const char IDin_name, const char IDblknb_name, long blkNB, const char *IDout_name)

3. BUILD PREDICTIVE FILTER
long	LINARFILTERPRED_Build_LinPredictor (const char IDin_name, long PForder, float PFlag, double SVDeps, double RegLambda, const char IDoutPF_name, int outMode, int LOOPmode, float LOOPgain)
	Build predictive filter. More...

4. APPLY PREDICTIVE FILTER
long	LINARFILTERPRED_Apply_LinPredictor_RT (const char IDfilt_name, const char IDin_name, const char *IDout_name)

long	LINARFILTERPRED_Apply_LinPredictor (const char IDfilt_name, const char IDin_name, float PFlag, const char *IDout_name)

long	LINARFILTERPRED_PF_updatePFmatrix (const char IDPF_name, const char IDPFM_name, float alpha)

long	LINARFILTERPRED_PF_RealTimeApply (const char IDmodevalOL_name, long IndexOffset, int semtrig, const char IDPFM_name, long NBPFstep, const char *IDPFout_name, int nbGPU, long loop, long NBiter, int SAVEMODE, float tlag, long PFindex)

5. MISC TOOLS, DIAGNOSTICS
float	LINARFILTERPRED_ScanGain (char *IDin_name, float multfact, float framelag)

Detailed Description

Function prototypes for linear autoregressive prediction.

Implements Empirical Orthogonal Functions

Function Documentation

int_fast8_t init_linARfilterPred ( )

long LINARFILTERPRED_Apply_LinPredictor	(	const char *	IDfilt_name,
		const char *	IDin_name,
		float	PFlag,
		const char *	IDout_name
	)

long LINARFILTERPRED_Apply_LinPredictor_RT	(	const char *	IDfilt_name,
		const char *	IDin_name,
		const char *	IDout_name
	)

long LINARFILTERPRED_Build_LinPredictor	(	const char *	IDin_name,
		long	PForder,
		float	PFlag,
		double	SVDeps,
		double	RegLambda,
		const char *	IDoutPF_name,
		int	outMode,
		int	LOOPmode,
		float	LOOPgain
	)

Build predictive filter.

Parameters

[in]	IDin_name	Input telemetry, can be a 2D or 3D image
[in]	PForder	Filter order: number of time steps in filter
[in]	SVDeps	Cutoff limit on singular values
[in]	RegLambda	Regularization parameter
[out]	IDoutPF_name	Output predictive filter name
[in]	outMode	Output mode. 0: do not write individual files, 1: write individual files (note: output filter cube is always written)
[in]	LOOPmode	1 if running in infinite loop waiting for input telemetry
[in]	LOOPgain	if running in loop, mixing coefficient between previous and current filter

Optional pixel masks select input and output variables: "inmask" and "outmask"

if LOOPmode = 1, operate in a loop, and re-run filter computation everytime IDin_name changes

IDin_name is a 2D or 3D image

Optional input and output pixel masks select active input & output

< 1 if regularization

< use MAGMA library if available

< 1 if average value of each mode is removed

measure time

long LINARFILTERPRED_LoadASCIIfiles	(	double	tstart,
		double	dt,
		long	NBpt,
		long	NBfr,
		const char *	IDoutname
	)

load ascii file(s) into image cube

resamples sequence(s) of data points INPUT FILES HAVE TO BE NAMED seq000.dat, seq001.dat etc...

file starts at tstart, sampling = dt NBpt per file NBfr files

long LINARFILTERPRED_PF_RealTimeApply	(	const char *	IDmodevalOL_name,
		long	IndexOffset,
		int	semtrig,
		const char *	IDPFM_name,
		long	NBPFstep,
		const char *	IDPFout_name,
		int	nbGPU,
		long	loop,
		long	NBiter,
		int	SAVEMODE,
		float	tlag,
		long	PFindex
	)

measure time

long LINARFILTERPRED_PF_updatePFmatrix	(	const char *	IDPF_name,
		const char *	IDPFM_name,
		float	alpha
	)

float LINARFILTERPRED_ScanGain	(	char *	IDin_name,
		float	multfact,
		float	framelag
	)

long LINARFILTERPRED_SelectBlock	(	const char *	IDin_name,
		const char *	IDblknb_name,
		long	blkNB,
		const char *	IDout_name
	)

int NBwords ( const char sentence[] )