Functions
void	apply_L2 (dcell *xout, const dspcell L2, const dcell *xin, real alpha)

void	apply_invpsd (dcell *xout, const void extra, const dcell *xin, real alpha, int xb, int yb)

void	apply_fractal (dcell *xout, const void extra, const dcell *xin, real alpha, int xb, int yb)

void	remove_mode (dcell x, const dcell M, const dcell *PM)
	Remove projection x = x - M * (PM * x)

void	applyW (dcell xin, const dsp W0, const dmat W1, const real wt)

dcell *	calcWmcc (const dcell A, const dcell B, const dsp W0, const dmat W1, const dmat *wt)

dsp *	nea2sp (dmat *nea, int ll, int ur, int ng)

void	nea_chol (dmat *pout, const dmat in, int ng)

void	nea_inv (dmat *pout, const dmat in, int ng, real scale)

void	nea_mm (dmat *pout, const dmat in, int ng)

void	nea_check (dmat *nea, int nsa, int ng)

void	psfr_calc (sim_t simu, dcell opdr, dcell dmpsol, dcell dmerr, dcell *dmerr_lo)

cn2est_t *	cn2est_prepare (const parms_t parms, const powfs_t powfs)

void	cn2est_isim (dcell cn2res, recon_t recon, const parms_t parms, const dcell grad, int *tomo_update)

Detailed Description

Reusable utilities for wavefront reconstruction and DM fitting, supporting recon.c

Function Documentation

◆ apply_L2()

void apply_L2	(	dcell **	xout,
		const dspcell *	L2,
		const dcell *	xin,
		real	alpha
	)

Apply Laplacian2 to xin and accumulates to xout.

◆ apply_invpsd()

void apply_invpsd	(	dcell **	xout,
		const void *	A,
		const dcell *	xin,
		real	alpha,
		int	xb,
		int	yb
	)

Apply turbulence invpsd to xin in Fourier space, scaled by alpha and add to xout. do nothing if xb != yb, since we apply to diagonal only. if xb==-1, do all blocks.

Todo:: : this is not thread safe.

◆ apply_fractal()

void apply_fractal	(	dcell **	xout,
		const void *	A,
		const dcell *	xin,
		real	alpha,
		int	xb,
		int	yb
	)

Apply fractal regularization to x, scaled by alpha. do nothing if xb != yb, since we apply to diagonal only. if xb==-1, do all blocks.

Todo:: : this is not thread safe.

◆ remove_mode()

void remove_mode	(	dcell *	x,
		const dcell *	M,
		const dcell *	PM
	)

Remove projection x = x - M * (PM * x)

Parameters

x	The vector
M	The mode
PM	The mode projection matrix

◆ applyW()

void applyW	(	dcell *	xin,
		const dsp *	W0,
		const dmat *	W1,
		const real *	wt
	)

apply weighting W0/W1 with weighting wt for each block. \(xin<-(W0-W1*W1')*xin;\)

◆ calcWmcc()

dcell * calcWmcc	(	const dcell *	A,
		const dcell *	B,
		const dsp *	W0,
		const dmat *	W1,
		const dmat *	wt
	)

Compute W0/W1 weighted dot product: \(A'*(W0-W1*W1')*B\)

◆ nea2sp()

dsp * nea2sp	(	dmat *	nea,
		int	ll,
		int	ur,
		int	ng
	)

Convert column vector nsax2 or nsax3 to sparse matrix. The third column of nea is coupling. ll: controls lower left ur: controls upper right if ng>2, treat as diagonal matrix (for raw PWFS)

◆ nea_chol()

void nea_chol	(	dmat **	pout,
		const dmat *	in,
		const int	ng
	)

Apply cholesky in a 2x2 symmetric matrix packed in [a[0,0],a[1,1],a[0,1]] as row vector. Input and output may be the same. if ng>2, treat as diagonal matrix

◆ nea_inv()

void nea_inv	(	dmat **	pout,
		const dmat *	in,
		int	ng,
		real	scale
	)

Apply matrix inversion in a 2x2 symmetrisa matrix packed in row vector [a[0,0],a[1,1],a[0,1]] Input and output may be the same.

◆ nea_mm()

void nea_mm	(	dmat **	pout,
		const dmat *	in,
		const int	ng
	)

Apply LL' to lower diagonal matrix packed in [a[0,0],a[1,1],a[0,1]] as row vector. Input and output may be the same. if ng>2, treat as diagonal matrix

◆ nea_check()

void nea_check	(	dmat *	nea,
		int	nsa,
		int	ng
	)

Check the dimension of NEA and fix if possible

◆ psfr_calc()

void psfr_calc	(	sim_t *	simu,
		dcell *	opdr,
		dcell *	dmpsol,
		dcell *	dmerr,
		dcell *	dmerr_lo
	)

Compute and save PSF reconstruction telemetry. For pseudo open loop estimations, like high order loop, we add opdr to, and subtract dmpsol from the OPD. For closed loop estimations, like ahst low order or lsr, we add dmerr_lo, and dmerr to the OPD.

◆ cn2est_prepare()

cn2est_t * cn2est_prepare	(	const parms_t *	parms,
		const powfs_t *	powfs
	)

Prepare arrays for cn2 estimation. Multiple pairs can be used to do Cn2 Estimation. The result will be an average of them.

◆ cn2est_isim()

void cn2est_isim	(	dcell *	cn2res,
		recon_t *	recon,
		const parms_t *	parms,
		const dcell *	grad,
		int *	tomo_update
	)

Wrapper of Cn2 Estimation operations in recon.c

Functions