Documentation:system/generic

Let us improve self-documentation of Madagascar programs!

Listed below are selfdocs for programs in system/generic (generated with sfdoc). Please edit the descriptions to make them more complete and/or easier to understand.

sfagc

Automatic gain control.
sfagc < in.rsf > out.rsf repeat=1 rect#=(125,1,1,...)
October 2011 program of the month: http://ahay.org/rsflog/index.php?/archives/271-Program-of-the-month-sfagc.html
int	rect#=(125,1,1,...)		smoothing radius on #-th axis
int	repeat=1		repeat filtering several times

sfaliasp

Aliasing test.
sfaliasp > out.rsf n1=600 n2=24 cycles=10. ix0=0 slow=0.1
float	cycles=10.		wave frequency
int	ix0=0		central trace
int	n1=600
int	n2=24		dimensions
float	slow=0.1		slowness

sfbandpass

Bandpass filtering.
sfbandpass < in.rsf > out.rsf flo= fhi= phase=n verb=n nplo=6 nphi=6
November 2012 program of the month: http://ahay.org/rsflog/index.php?/archives/313-Program-of-the-month-sfbandpass.html
float	fhi=		High frequency in band, default is Nyquist
float	flo=		Low frequency in band, default is 0
int	nphi=6		number of poles for high cutoff
int	nplo=6		number of poles for low cutoff
bool	phase=n	[y/n]	y: minimum phase, n: zero phase
bool	verb=n	[y/n]	verbosity flag

sfbin

Data binning in 2-D slices.
sfbin < in.rsf > out.rsf fold=fold.rsf xkey=0 ykey=1 xmax= xmin= ymax= ymin= x0=xmin y0=ymin nx=(int) (xmax - xmin + 1.) ny=(int) (ymax - ymin + 1.) dx= dy= interp=1 norm=y clip=FLT_EPSILON head=
float	clip=FLT_EPSILON		clip for fold normalization
float	dx=		bin size in x
float	dy=		bin size in y
string	fold=		output file for fold (optional) (auxiliary output file name)
string	head=		header file
int	interp=1	[0,1,2]	interpolation method; 0: median, 1: nearest neighbor, 2: bi-linear,
bool	norm=y	[y/n]	if normalize
int	nx=(int) (xmax - xmin + 1.)		Number of bins in x
int	ny=(int) (ymax - ymin + 1.)		Number of bins in y
float	x0=xmin		x origin
int	xkey=0		x key number
float	xmax=		x maximum
float	xmin=		x minimum
float	y0=ymin		y origin
int	ykey=1		y key number
float	ymax=		y maximum
float	ymin=		y minimum

sfbin1

Data binning in 1-D slices.
sfbin1 < in.rsf > out.rsf pattern=pattern.rsf fold=fold.rsf xmin= xmax= nx= x0=xmin dx= interp=1 clip=FLT_EPSILON head=
float	clip=FLT_EPSILON		clip for fold normalization
float	dx=		grid spacing
string	fold=		output fold file (optional) (auxiliary output file name)
string	head=
int	interp=1	[1,2]	interpolation method, 1: nearest neighbor, 2: linear
int	nx=		Number of bins
string	pattern=		auxiliary input file name
float	x0=xmin		grid origin
float	xmax=
float	xmin=		grid dimensions

sfboxsmooth

Multi-dimensional smoothing with boxes.
sfboxsmooth < in.rsf > out.rsf repeat=1 rect#=(1,1,...)
int	rect#=(1,1,...)		smoothing radius on #-th axis
int	repeat=1		repeat filtering several times

sfcanny

Canny-like edge detector.
sfcanny < in.rsf > out.rsf min=5.0 max=95.0
float	max=95.0		maximum threshold
float	min=5.0		minimum threshold

sfcausint

Causal integration on the first axis.
sfcausint < in.rsf > out.rsf adj=n
bool	adj=n	[y/n]	if y, do adjoint integration

sfclip

Clip the data.
sfclip < in.rsf > out.rsf clip=
The output is clip if input > clip -clip if input < -clip input if |input| < clip See also sfclip2. September 2011 program of the month: http://ahay.org/rsflog/index.php?/archives/269-Program-of-the-month-sfclip.html
float	clip=		clip value

sfcmatmult

Simple matrix multiplication for complex matrices
sfcmatmult < in.rsf > out.rsf mat=mat.rsf adj=n
bool	adj=n	[y/n]
file	mat=		auxiliary input file name

sfcmatmult2

Multiplication of two complex matrices
sfcmatmult2 < in.rsf > out.rsf mat=mat.rsf
file	mat=		auxiliary input file name

sfcosft

Multi-dimensional cosine transform.
sfcosft < in.rsf > out.rsf sign#=0
The input and output are real and have the same dimensions. Pad the data if you need to suppress wrap-around effects.
int	sign#=0		transform along #-th dimension [+1 forward or -1 backward]

sfcostaper

Cosine taper around the borders (N-D).
sfcostaper < in.rsf > out.rsf nw#=0
int	nw#=0		tapering on #-th axis

sfderiv

First derivative with a maximally linear FIR differentiator.
sfderiv < in.rsf > out.rsf order=6 scale=n
May 2012 program of the month: http://ahay.org/rsflog/index.php?/archives/290-Program-of-the-month-sfderiv.html
int	order=6		filter order
bool	scale=n	[y/n]	if scale by 1/dx

sfdipfilter

Filter data based on dip in 2-D or 3-D.
sfdipfilter < in.rsf > out.rsf dim=2 angle=n v=-1. ang1=-50. ang2=-45. ang3=45. ang4=50. v1=0. v2=0.1 v3=99999. v4=999999. pass=y
float	ang1=-50.
float	ang2=-45.
float	ang3=45.
float	ang4=50.		Angle gate (in degrees)
bool	angle=n	[y/n]	Filter based on angle (or velocity)
int	dim=2	[2,3]	Dimensionality: filter 2-D planes or 3-D cubes
bool	pass=y	[y/n]	Pass or reject band
float	v=-1.		constant velocity (if angle-y) The default is d(frequency)/d(wavenumber)
float	v1=0.
float	v2=0.1
float	v3=99999.
float	v4=999999.		Velocity gate

sfdwt

1-D digital wavelet transform
sfdwt < in.rsf > out.rsf inv=n adj=n unit=n type=
bool	adj=n	[y/n]	if y, do adjoint transform
bool	inv=n	[y/n]	if y, do inverse transform
string	type=		[haar,linear,biorthogonal] wavelet type, the default is linear
bool	unit=n	[y/n]	if y, use unitary scaling

sfenoint2

ENO interpolation in 2-D slices.
sfenoint2 < in.rsf > out.rsf head=head.rsf xkey= ykey= interp=2
file	head=		auxiliary input file name
int	interp=2		interpolation order
int	xkey=		x key number
int	ykey=		y key number

sfequal

Image enhancement by histogram equalization.
sfequal < in.rsf > out.rsf

sfextract

Forward interpolation in 2-D slices.
sfextract < in.rsf > out.rsf head=head.rsf xkey=0 ykey=1 interp=2
file	head=		auxiliary input file name
int	interp=2	[1,2]	interpolation method, 1: nearest neighbor, 2: bi-linear
int	xkey=0		x key number
int	ykey=1		y key number

sffern

Generate fractal fern.
sffern > out.rsf n=1000 seed=time(NULL) angle=y
bool	angle=y	[y/n]	if y, use more angular fern
int	n=1000		number of points
int	seed=time(NULL)		random seed

sffft1

Fast Fourier Transform along the first axis.
sffft1 < in.rsf > out.rsf inv=n sym=n opt=y
bool	inv=n	[y/n]	if y, perform inverse transform
bool	opt=y	[y/n]	if y, determine optimal size for efficiency
bool	sym=n	[y/n]	if y, apply symmetric scaling to make the FFT operator Hermitian

sffft3

FFT transform on extra axis.
sffft3 < in.rsf > out.rsf inv=n sym=n sign=inv? 1: 0 opt=y axis=2 pad=2
Input and output are complex data. The input is padded by factor pad. July 2012 program of the month: http://ahay.org/rsflog/index.php?/archives/298-Program-of-the-month-sffft3.html
int	axis=2		Axis to transform
bool	inv=n	[y/n]	if y, perform inverse transform
bool	opt=y	[y/n]	if y, determine optimal size for efficiency
int	pad=2		padding factor
int	sign=inv? 1: 0		transform sign (0 or 1)
bool	sym=n	[y/n]	if y, apply symmetric scaling to make the FFT operator Hermitian

sfgrad2

2-D smooth gradient.
sfgrad2 < in.rsf > out.rsf

sfgrad3

3-D smooth gradient.
sfgrad3 < in.rsf > out.rsf

sfheat

Finite-difference solution of 2-D heat-flow equation
sfheat > out.rsf impl=n alpha=1.
float	alpha=1.
bool	impl=n	[y/n]	if y, use implicit scheme

sfhistogram

Compute a histogram of integer- or float-valued input data.
sfhistogram < in.rsf > out.rsf n1= o1= d1=
The output grid is not centered on the bins; it marks their "left edge". I.e., the first sample holds the number of values between o1 and o1+d1.
float	d1=		histogram sampling
int	n1=		number of histogram samples
float	o1=		histogram origin

sfigrad

Gradient on the first axis.
sfigrad < in.rsf > out.rsf square=n adj=n
bool	adj=n	[y/n]	adjoint flag
bool	square=n	[y/n]	if y, use gradient squared

sfimpl1

1-D anisotropic diffusion.
sfimpl1 < in.rsf > out.rsf rect1= tau=0.1 pclip=50. up=n
float	pclip=50.		percentage clip for the gradient
float	rect1=		smoothing radius
float	tau=0.1		smoothing time
bool	up=n	[y/n]	smoothing style

sfimpl2

2-D anisotropic diffusion.
sfimpl2 < in.rsf > out.rsf rect1= rect2= tau=0.1 pclip=50. up=n verb=n nsnap=1 lin=n adj=n dist= snap=
bool	adj=n	[y/n]	adjoint flag
string	dist=		inverse distance file (input)
bool	lin=n	[y/n]	if linear operator
int	nsnap=1		number of snapshots
float	pclip=50.		percentage clip for the gradient
float	rect1=		vertical smoothing
float	rect2=		horizontal smoothing
string	snap=		snapshot file (output)
float	tau=0.1		smoothing time
bool	up=n	[y/n]	smoothing style
bool	verb=n	[y/n]	verbosity flag

sfimpl3

3-D anisotropic diffusion.
sfimpl3 < in.rsf > out.rsf rect1= rect2= rect3= tau=0.1 pclip=50. up=n verb=n nsnap=1 dist= snap=
string	dist=		inverse distance file (input)
int	nsnap=1		number of snapshots
float	pclip=50.		percentage clip for the gradient
float	rect1=
float	rect2=
float	rect3=		smoothing radius
string	snap=		snapshot file (output)
float	tau=0.1		smoothing time
bool	up=n	[y/n]	smoothing style
bool	verb=n	[y/n]	verbosity flag

sfintshow

Output interpolation filter.
sfintshow > filt.rsf nw= x= kai=4.0 interp=
See also: inttest1.
string	interp=		interpolation (lagrange,cubic,kaiser,lanczos,cosine,welch,spline,mom)
float	kai=4.0		Kaiser window parameter
int	nw=		interpolator size
float	x=		interpolation shift

sfinttest1

Interpolation from a regular grid in 1-D.
sfinttest1 < in.rsf > out.rsf coord=crd.rsf nw= kai=4.0 interp=
file	coord=		auxiliary input file name
string	interp=		interpolation (lagrange,cubic,kaiser,lanczos,cosine,welch,spline,mom)
float	kai=4.0		Kaiser window parameter
int	nw=		interpolator size

sfinttest2

Interpolation from a regular grid in 2-D.
sfinttest2 < in.rsf > out.rsf coord=crd.rsf nw= kai=4.0 interp=
file	coord=		auxiliary input file name
string	interp=		interpolation (lagrange,cubic,kaiser,lanczos,cosine,welch,spline)
float	kai=4.0		Kaiser window parameter
int	nw=		interpolator size

sfjacobi

Find eigenvalues of a symmetric matrix by Jacobi's iteration.
sfjacobi < mat.rsf > val.rsf eig=eig.rsf niter=10
string	eig=		auxiliary output file name
int	niter=10

sfjacobi2

Find eigenvalues of a general complex matrix by Jacobi-like iteration.
sfjacobi2 < mat.rsf > val.rsf niter=10
int	niter=10

sflapfill

Missing data interpolation in 2-D by Laplacian regularization.
sflapfill < in.rsf > out.rsf mask=mask.rsf niter=200 grad=n
bool	grad=n	[y/n]	if y, use gradient instead of laplacian
string	mask=		optional mask file with zeroes for missing data locations (auxiliary input file name)
int	niter=200		number of iterations

sflaplac

2-D finite-difference Laplacian operation.
sflaplac < in.rsf > out.rsf adj=n
bool	adj=n	[y/n]	adjoint flag

sflinear

1-D linear interpolation.
sflinear < in.rsf > out.rsf pattern=pattern.rsf sort=n niter=0 rect=1 nw=2
Specify either n1= o1= d1= or pattern=
int	niter=0		number of iterations
int	nw=2		interpolator size
string	pattern=		auxiliary input file name
int	rect=1		smoothing regularization
bool	sort=n	[y/n]	if y, the coordinates need sorting

sflinefit

Fit a line to a set of points in 2-D.
sflinefit < in.rsf > out.rsf pattern=pattern.rsf
string	pattern=		auxiliary input file name

sflorenz

Generate Lorenz attractor.
sflorenz > out.rsf niter=1000 n=niter rho=28.00 sigma=10.00 beta=8.00/3.00 x0=3.051522 y0=1.582542 z0=15.62388 dt=0.0001
double	beta=8.00/3.00		Beta reference
double	dt=0.0001		time step
int	n=niter		set maximum
int	niter=1000		number of iterations
double	rho=28.00		Rayleigh number
double	sigma=10.00		Prandtl number
double	x0=3.051522		intial x coordinate
double	y0=1.582542		intial y coordinate
double	z0=15.62388		intial z coordinate

sflpad

Pad and interleave traces.
sflpad < in.rsf > out.rsf mask=mask.rsf jump=2
Each initial trace is followed by I<jump> zero traces, the same for planes.
int	jump=2		aliasing
file	mask=		auxiliary output file name

sfmandelbrot

Generate Mandelbrot set.
sfmandelbrot > out.rsf n1=512 n2=512 x0=-2. y0=-1. xmax=0.5 ymax=1. niter=1000 dx=(xmax-x0)/(n1-1) dy=(ymax-y0)/(n2-1)
float	dx=(xmax-x0)/(n1-1)
float	dy=(ymax-y0)/(n2-1)
int	n1=512
int	n2=512		dimensions
int	niter=1000		number of iterations
float	x0=-2.
float	xmax=0.5
float	y0=-1.		set origin
float	ymax=1.		set maximum

sfmatmult

Simple matrix multiplication
sfmatmult < in.rsf > out.rsf mat=mat.rsf adj=n
bool	adj=n	[y/n]
file	mat=		auxiliary input file name

sfmax1

Picking local maxima on the first axis.
sfmax1 < in.rsf > out.rsf min=o1 max=o1+(n1-1)*d1 np=n1
Outputs complex numbers (time,amplitude) sorted by amplitude.
float	max=o1+(n1-1)*d1		maximum value of time
float	min=o1		minimum value of time
int	np=n1		maximum number of picks

sfmiss2

2-D missing data interpolation.
sfmiss2 < in.rsf > out.rsf mask=mask.rsf niter=100 nliter=1 filt1=3. filt2=filt1 eps=0.0001 shape=n force=y
float	eps=0.0001		regularization parameter
float	filt1=3.
float	filt2=filt1		smoothing radius
bool	force=y	[y/n]	if y, keep known values
string	mask=		optional input mask file for known data (auxiliary input file name)
int	niter=100		Number of iterations
int	nliter=1		Number of reweighting iterations
bool	shape=n	[y/n]	if y, estimate shaping

sfmonof

Mono-frequency wavelet estimation.
sfmonof < in.rsf > out.rsf ma=ma.rsf a0=1. niter=100 verb=n
float	a0=1.		starting sharpness
file	ma=		auxiliary output file name
int	niter=100		number of iterations
bool	verb=n	[y/n]	verbosity flag

sfmonof2

Gaussian wavelet estimation in 2-D.
sfmonof2 < in.rsf > out.rsf ma=ma.rsf a0=1. b0=0. c0=1. niter=100 nliter=1 verb=n
float	a0=1.		starting sharpness in xx
float	b0=0.		starting sharpness in xy
float	c0=1.		starting sharpness in yy
file	ma=		auxiliary output file name
int	niter=100		number of iterations
int	nliter=1		number of reweighting iterations
bool	verb=n	[y/n]	verbosity flag

sfmutter

Muting.
sfmutter < in.rsf > out.rsf offset=offset.rsf half=y nan=n tp=0.150 t0=0. v0=1.45 slope0=1./v0 slopep=slope0 x0=0. abs=y inner=n hyper=n
Data is smoothly weighted inside the mute zone. The weight is zero for t < (x-x0) * slope0 The weight is one for t > tp + (x-x0) * slopep The signs are reversed for inner=y.
bool	abs=y	[y/n]	x-x0|
bool	half=y	[y/n]	if y, the second axis is half-offset instead of full offset
bool	hyper=n	[y/n]	if y, do hyperbolic mute
bool	inner=n	[y/n]	if y, do inner muter
bool	nan=n	[y/n]	if y, put nans instead of zeros
string	offset=		auxiliary input file name
float	slope0=1./v0		slope
float	slopep=slope0		end slope
float	t0=0.		starting time
float	tp=0.150		end time
float	v0=1.45		velocity
float	x0=0.		starting space

sfnoise

Add random noise to the data.
sfnoise < in.rsf > out.rsf seed=time(NULL) type=y var= range= mean=0 rep=n
July 2011 program of the month: http://ahay.org/rsflog/index.php?/archives/262-Program-of-the-month-sfnoise.html
float	mean=0		noise mean
float	range=		noise range (default=1)
bool	rep=n	[y/n]	if y, replace data with noise
int	seed=time(NULL)		random seed
bool	type=y	[y/n]	noise distribution, y: normal, n: uniform
float	var=		noise variance

sfotsu

Compute a threshold value from histogram using Otsu's algorithm.
sfotsu < in.rsf

sfpolymask

Mask a polygon.
sfpolymask < inp.rsf > out.rsf poly=poly.rsf
file	poly=		auxiliary input file name

sfpostfilter2

Convert B-spline coefficients to data in 2-D.
sfpostfilter2 < in.rsf > out.rsf nw= vert=y horz=y
bool	horz=y	[y/n]	include filter on the second axis
int	nw=		filter size
bool	vert=y	[y/n]	include filter on the first axis

sfpow

Apply power gain.
sfpow < in.rsf > out.rsf tpow=0. pow#=(0,0,...)
float	pow#=(0,0,...)		power on #-th axis
float	tpow=0.		power on the first axis

sfreg2tri

Decimate a regular grid to triplets for triangulation.
sfreg2tri < in.rsf > out.rsf edgeout=edge.rsf nt= zero=0.
string	edgeout=		auxiliary output file name
int	nt=		number of triplets
float	zero=0.		level surface

sfremap1

1-D ENO interpolation.
sfremap1 < in.rsf > out.rsf pattern=pattern.rsf n1=n1 d1=d1 o1=o1 order=3
float	d1=d1		Output sampling
int	n1=n1		Number of output samples
float	o1=o1		Output origin
int	order=3		Interpolation order
string	pattern=		auxiliary input file name

sfroots

Find roots of a complex polynomial.
sfroots < poly.rsf > root.rsf niter=10 tol=1.0e-6 verb=y sort=
int	niter=10		number of iterations
string	sort=		attribute for sorting
float	tol=1.0e-6		tolerance for convergence
bool	verb=y	[y/n]	verbosity flag

sfshapebin

Data binning in 2-D slices by inverse interpolation.
sfshapebin < in.rsf > out.rsf pattern=pattern.rsf pin=pin.rsf pout=pout.rsf xkey= ykey= nx= ny= xmin= xmax= ymin= ymax= x0=xmin y0=ymin dx= dy= interp=2 niter=nm nliter=1 eps=1./nd gauss=n shape=y verb=y filt1=3. filt2=filt1 head=
float	dx=		bin size in x
float	dy=		bin size in y
float	eps=1./nd		regularization parameter
float	filt1=3.
float	filt2=filt1		smoothing length for shaping
bool	gauss=n	[y/n]	if y, use gaussian shaping (estimated from the data)
string	head=
int	interp=2		interpolation length
int	niter=nm		number of iterations
int	nliter=1		number of reweighting iterations
int	nx=		Number of bins in x
int	ny=		Number of bins in y
string	pattern=		auxiliary input file name
string	pin=		auxiliary input file name
string	pout=		auxiliary output file name
bool	shape=y	[y/n]	if y, use shaping regularization
bool	verb=y	[y/n]	verbosity flag
float	x0=xmin
int	xkey=		x key number
float	xmax=
float	xmin=
float	y0=ymin		grid origin
int	ykey=		y key number
float	ymax=
float	ymin=		Grid dimensions

sfshapebin1

1-D inverse interpolation with shaping regularization.
sfshapebin1 < in.rsf > out.rsf verb=y nx= xmin= xmax= x0=xmin dx= interp=2 filter=3. niter=nx eps=1./nd pef=n gauss=n pad=0 head=
float	dx=		grid sampling
float	eps=1./nd		regularization parameter
float	filter=3.		smoothing length
bool	gauss=n	[y/n]	if y, use Gaussian shaping
string	head=
int	interp=2	[1,2]	forward interpolation method, 1: nearest neighbor, 2: linear
int	niter=nx		number of conjugate-gradient iterations
int	nx=		number of bins
int	pad=0		padding for Gaussian shaping
bool	pef=n	[y/n]	if y, use monofrequency regularization
bool	verb=y	[y/n]	verbosity flag
float	x0=xmin		grid origin
float	xmax=
float	xmin=		grid size

sfsharpen

Sharpening operator
sfsharpen < in.rsf > out.rsf other=other.rsf perc=50.0
string	other=		auxiliary input file name
float	perc=50.0		percentage for sharpening

sfslice

Extract a slice using picked surface (usually from a stack or a semblance).
sfslice < in.rsf pick=pick.rsf > out.rsf
See also: sfpick.
file	pick=		auxiliary input file name

sfsmooth

Multi-dimensional triangle smoothing.
sfsmooth < in.rsf > out.rsf repeat=1 adj=n rect#=(1,1,...) diff#=(n,n,...)
January 2012 program of the month: http://ahay.org/rsflog/index.php?/archives/280-Program-of-the-month-sfsmooth.html
bool	adj=n	[y/n]	run in the adjoint mode
bool	diff#=(n,n,...)	[y/n]	differentiation on #-th axis
int	rect#=(1,1,...)		smoothing radius on #-th axis
int	repeat=1		repeat filtering several times

sfsmoothder

Smooth first derivative on the first axis.
sfsmoothder < in.rsf > der.rsf eps=0.2
Applies D/(I + eps*D'D)
float	eps=0.2		smoothness parameter

sfsmoothreg2

Smoothing in 2-D by simple regularization.
sfsmoothreg2 < in.rsf > smooth.rsf eps=1. repeat=1
float	eps=1.		smoothness parameter
int	repeat=1		repeat smoothing

sfspectra

Frequency spectra.
sfspectra < in.rsf > out.rsf all=n opt=y
March 2012 program of the month: http://ahay.org/rsflog/index.php?/archives/285-Program-of-the-month-sfspectra.html
bool	all=n	[y/n]	if y, compute average spectrum for all traces
bool	opt=y	[y/n]	if y, determine optimal size for efficiency

sfspectra2

Frequency spectra in 2-D.
sfspectra2 < in.rsf > out.rsf all=n
bool	all=n	[y/n]	if y, compute average spectrum for all traces

sfspline

1-D cubic spline interpolation.
sfspline < in.rsf > out.rsf pattern=pattern.rsf fp= sort=n
Specify either n1= o1= d1= or pattern=
floats	fp=		end-point derivatives [2]
string	pattern=		auxiliary input file name
bool	sort=n	[y/n]	if y, the coordinates need sorting

sfsplinefilter

Convert data to B-spline coefficients.
sfsplinefilter < in.rsf > out.rsf nw=
int	nw=		filter size

sfswtdenoise

Denoising using stationary wavelet transform.
sfswtdenoise < in.rsf > out.rsf ratio=1. len_filter=2 n_layer=2
int	len_filter=2		filter length
int	n_layer=2		number of wavelet transform layers
float	ratio=1.		ratio for denoising

sfthreshold

Soft thresholding.
sfthreshold < in.rsf > out.rsf pclip=
float	pclip=		percentage to clip

sftrapez

Convolution with a trapezoidal filter.
sftrapez < in.rsf > out.rsf frequency=
floats	frequency=		frequencies (in Hz), default: (0.1,0.15,0.45,0.5)*Nyquist [4]

sftri2reg

Interpolate triangulated triplets to a regular grid.
sftri2reg < in.rsf > out.rsf pattern=pattern.rsf edgein=edge.rsf nodeout=out2.rsf edgeout=edge2.rsf n1= n2= d1=1. d2=1. o1=0. o2=0. zero=0. nr=0
float	d1=1.
float	d2=1.
string	edgein=		input edge file (auxiliary input file name)
string	edgeout=		auxiliary output file name
int	n1=
int	n2=
string	nodeout=		auxiliary output file name
int	nr=0		number of refinements
float	o1=0.
float	o2=0.
string	pattern=		pattern file for output dimensions (auxiliary input file name)
float	zero=0.		level surface

sftrirand

Edit points for triangulation by removing similar and randomizing.
sftrirand < in.rsf > out.rsf

sftrishape

2-D irregular data interpolation using triangulation and shaping regularization.
sftrishape < in.rsf > out.rsf pattern=pattern.rsf n1= n2= d1=1. d2=1. o1=0. o2=0. zero=0. niter=0 rect1=1 rect2=1 nw=2
float	d1=1.
float	d2=1.
int	n1=
int	n2=
int	niter=0		number of iterations
int	nw=2		interpolator size
float	o1=0.
float	o2=0.
string	pattern=		pattern file for output dimensions (auxiliary input file name)
int	rect1=1
int	rect2=1		smoothing regularization
float	zero=0.		level surface

sfunif2

Generate 2-D layered velocity model from specified interfaces.
sfunif2 < surface.rsf > model.rsf x0= z0= v00= dvdx= dvdz= n1= d1= o1=0. label1= unit1=
In each layer, velocity is a linear function of position. Inspired by SU's unif2.
float	d1=		Sampling of the depth axis
floats	dvdx=		[ninf]
floats	dvdz=		[ninf]
string	label1=		depth axis label
int	n1=		Number of samples on the depth axis
float	o1=0.		Origin of the depth axis
string	unit1=
floats	v00=		[ninf]
floats	x0=		[ninf]
floats	z0=		[ninf]

sfunif3

Generate 3-D layered velocity model from specified interfaces.
sfunif3 < surface.rsf > model.rsf x0= y0= z0= v00= dvdx= dvdy= dvdz= n1= d1= o1=0. layers=
Unless layers= is specified, velocity is a linear function of position inside each layer. Inspired by SU's unif2.
float	d1=		Sampling of the depth axis
floats	dvdx=		[ninf]
floats	dvdy=		[ninf]
floats	dvdz=		[ninf]
string	layers=		file with layer properties
int	n1=		Number of samples on the depth axis
float	o1=0.		Origin of the depth axis
floats	v00=		[ninf]
floats	x0=		[ninf]
floats	y0=		[ninf]
floats	z0=		[ninf]