Guide to madagascar programs

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This guide introduces some of the most used madagascar programs and illustrates their usage with examples.

Contents

Main programs

The source files for these programs can be found under system/main in the Madagascar distribution. The "main" programs perform general-purpose operations on RSF hypercubes regardless of the data dimensionality or physical dimensions.

sfadd

Add, multiply, or divide RSF datasets.
sfadd > out.rsf scale= add= sqrt= abs= log= exp= mode= [< file0.rsf] file1.rsf file2.rsf ...
The various operations, if selected, occur in the following order:

(1) Take absolute value, abs=
(2) Add a scalar, add=
(3) Take the natural logarithm, log=
(4) Take the square root, sqrt=
(5) Multiply by a scalar, scale=
(6) Compute the base-e exponential, exp=
(7) Add, multiply, or divide the data sets, mode=

sfadd operates on integer, float, or complex data, but all the input
and output files must be of the same data type.

An alternative to sfadd is sfmath, which is more versatile, but may be
less efficient.
bools abs= If true take absolute value [nin]
floats add= Scalar values to add to each dataset [nin]
bools exp= If true compute exponential [nin]
bools log= If true take logarithm [nin]
string mode= 'a' means add (default),
'p' or 'm' means multiply,
'd' means divide
floats scale= Scalar values to multiply each dataset with [nin]
bools sqrt= If true take square root [nin]

sfadd is useful for combining (adding, dividing, or multiplying) several datasets. What if you want to subtract two datasets? Easy. Use the scale parameter as follows:

bash$ sfadd data1.rsf data2.rsf scale=1,-1 > diff.rsf

or

bash$ sfadd < data1.rsf data2.rsf scale=1,-1 > diff.rsf

The same task can be accomplished with the more general sfmath program:

bash$ sfmath one=data1.rsf two=data2.rsf output='one-two' > diff.rsf

or

bash$ sfmath < data1.rsf two=data2.rsf output='input-two' > diff.rsf

In both cases, the size and shape of data1.rsf and data2.rsf hypercubes should be the same, and a warning message is printed out if the the axis sampling parameters (such as o1 or d1) in these files are different.

Implementation: system/main/add.c

The first input file is either in the list or in the standard input. <syntaxhighlight lang="c">

   /* find number of input files */
   if (isatty(fileno(stdin))) { 
       /* no input file in stdin */

nin=0;

   } else {

in[0] = sf_input("in"); nin=1;

   }

</syntaxhighlight>

Collect input files in the in array from all command-line parameters that don't contain an "=" sign. The total number of input files in nin. <syntaxhighlight lang="c">

   for (i=1; i< argc; i++) { /* collect inputs */

if (NULL != strchr(argv[i],'=')) continue; in[nin] = sf_input(argv[i]); nin++;

   }
   if (0==nin) sf_error ("no input");
   /* nin = no of input files*/

</syntaxhighlight>

A helper function check_compat checks the compatibility of input files. <syntaxhighlight lang="c"> static void check_compat (sf_datatype type /* data type */, size_t nin /* number of files */, sf_file* in /* input files [nin] */, int dim /* file dimensionality */, const int* n /* dimensions [dim] */) /* Check that the input files are compatible.

  Issue error for type mismatch or size mismatch.
  Issue warning for grid parameters mismatch. */

{

   int ni, id;
   size_t i;
   float d, di, o, oi;
   char key[3];
   const float tol=1.e-5; /* tolerance for comparison */
   
   for (i=1; i < nin; i++) {

if (sf_gettype(in[i]) != type) sf_error ("type mismatch: need %d",type); for (id=1; id <= dim; id++) { (void) snprintf(key,3,"n%d",id); if (!sf_histint(in[i],key,&ni) || ni != n[id-1]) sf_error("%s mismatch: need %d",key,n[id-1]); (void) snprintf(key,3,"d%d",id); if (sf_histfloat(in[0],key,&d)) { if (!sf_histfloat(in[i],key,&di) || (fabsf(di-d) > tol*fabsf(d))) sf_warning("%s mismatch: need %g",key,d); } else { d = 1.; } (void) snprintf(key,3,"o%d",id); if (sf_histfloat(in[0],key,&o) && (!sf_histfloat(in[i],key,&oi) || (fabsf(oi-o) > tol*fabsf(d)))) sf_warning("%s mismatch: need %g",key,o); }

   }

} </syntaxhighlight>

Finally, we enter the main loop, where input data are getting read buffer by buffer and combined in the total product depending on the data type. <syntaxhighlight lang="c">

   for (nbuf /= sf_esize(in[0]); nsiz > 0; nsiz -= nbuf) {

if (nbuf > nsiz) nbuf=nsiz;

for (j=0; j < nin; j++) { collect = (bool) (j != 0); switch(type) { case SF_FLOAT: sf_floatread((float*) bufi, nbuf, in[j]); add_float(collect, nbuf, (float*) buf, (const float*) bufi, cmode, scale[j], add[j], abs_flag[j], log_flag[j], sqrt_flag[j], exp_flag[j]); break; </syntaxhighlight>

The data combination program for floating point numbers is add_float. <syntaxhighlight lang="c"> static void add_float (bool collect, /* if collect */ size_t nbuf, /* buffer size */ float* buf, /* output [nbuf] */ const float* bufi, /* input [nbuf] */ char cmode, /* operation */ float scale, /* scale factor */ float add, /* add factor */ bool abs_flag, /* if abs */ bool log_flag, /* if log */ bool sqrt_flag, /* if sqrt */ bool exp_flag /* if exp */) /* Add floating point numbers */ {

   size_t j;
   float f;
   for (j=0; j < nbuf; j++) {

f = bufi[j]; if (abs_flag) f = fabsf(f); f += add; if (log_flag) f = logf(f); if (sqrt_flag) f = sqrtf(f); if (1. != scale) f *= scale; if (exp_flag) f = expf(f); if (collect) { switch (cmode) { case 'p': /* product */ case 'm': /* multiply */ buf[j] *= f; break; case 'd': /* delete */ if (f != 0.) buf[j] /= f; break; default: /* add */ buf[j] += f; break; } } else { buf[j] = f; }

   }

} </syntaxhighlight>

sfattr

Display dataset attributes.
sfattr < in.rsf want=

Sample output from "sfspike n1=100 | sfbandpass fhi=60 | sfattr"
*******************************************
rms = 0.992354
mean value = 0.987576
2-norm value = 9.92354
variance = 0.00955481
standard deviation = 0.0977487
maximum value = 1.12735 at 97
minimum value = 0.151392 at 100
number of nonzero samples = 100
total number of samples = 100
*******************************************

rms = sqrt[ sum(data^2) / n ]
mean = sum(data) / n
norm = sum(abs(data)^lval)^(1/lval)
variance = [ sum(data^2) - n*mean^2 ] / [ n-1 ]
standard deviation = sqrt [ variance ]
int lval=2 norm option, lval is a non-negative integer, computes the vector lval-norm
string want= 'all'(default),'rms','mean','norm','var','std','max','min','nonzero','samples','short'
want= 'rms' displays the root mean square
want= 'norm' displays the square norm, otherwise specified by lval.
want= 'var' displays the variance
want= 'std' displays the standard deviation
want= 'nonzero' displays number of nonzero samples
want= 'samples' displays total number of samples
want= 'short' displays a short one-line version


sfattr is a useful diagnostic program. It reports certain statistical values for an RSF dataset: RMS (root-mean-square) amplitude, mean value, vector norm value, variance, standard deviation, maximum and minimum values, number of nonzero samples, and the total number of samples. If we denote data values as d_i for i=0,1,2,\ldots,n, then the RMS value is \sqrt{\frac{1}{n}\,\sum\limits_{i=0}^n d_i^2}, the mean value is \frac{1}{n}\,\sum\limits_{i=0}^n d_i, the L_2-norm value is \sqrt{\sum\limits_{i=0}^n d_i^2}, the variance is \frac{1}{n-1}\,\left[\sum\limits_{i=0}^n d_i^2 - \frac{1}{n}\left(\sum\limits_{i=0}^n d_i\right)^2\right], and the standard deviation is the square root of the variance. Using sfattr is a quick way to see the distribution of data values and check it for anomalies.

The output can be parsed using utilities such as awk, to extract only a numeric value for feeding it as a parameter value into a command line interface. Notice the backticks in the example below:

sfgrey <vel.rsf allpos=y bias=`sfattr <vel.rsf want=min | awk '{print $4}'` | sfpen

Implementation: system/main/attr.c

Computations start by finding the input data (in) size (nsiz) and dimensions (dim). <syntaxhighlight lang="c">

   dim = (size_t) sf_filedims (in,n);
   for (nsiz=1, i=0; i < dim; i++) {

nsiz *= n[i];

   }

</syntaxhighlight>


In the main loop, we read the input data buffer by buffer. <syntaxhighlight lang="c">

   for (nleft=nsiz; nleft > 0; nleft -= nbuf) {

nbuf = (bufsiz < nleft)? bufsiz: nleft; switch (type) { case SF_FLOAT: sf_floatread((float*) buf,nbuf,in); break; case SF_INT: sf_intread((int*) buf,nbuf,in); break; case SF_COMPLEX: sf_complexread((sf_complex*) buf,nbuf,in); break; case SF_UCHAR: sf_ucharread((unsigned char*) buf,nbuf,in); break; case SF_CHAR: default: sf_charread(buf,nbuf,in); break; } </syntaxhighlight>


The data attributes are accumulated in corresponding double-precision variables. <syntaxhighlight lang="c"> fsum += f; fsqr += f*f; </syntaxhighlight>


Finally, the attributes are reduced and printed out. <syntaxhighlight lang="c">

   fmean = fsum/nsiz;
   if (lval==2)      fnorm = sqrt(fsqr);
   else if (lval==0) fnorm = nsiz-nzero;
   else              fnorm = pow(flval,1./lval);
   frms = sqrt(fsqr/nsiz);
   if (nsiz > 1) fvar = (fsqr-nsiz*fmean*fmean)/(nsiz-1);
   else          fvar = 0.0;
   fstd = sqrt(fvar);

</syntaxhighlight>

<syntaxhighlight lang="c">

   if(NULL==want || 0==strcmp(want,"rms"))

printf("rms = %g \n",(float) frms);

   if(NULL==want || 0==strcmp(want,"mean"))

printf("mean value = %g \n",(float) fmean);

   if(NULL==want || 0==strcmp(want,"norm"))

printf("%d-norm value = %g \n",lval,(float) fnorm);

   if(NULL==want || 0==strcmp(want,"var"))

printf("variance = %g \n",(float) fvar);

   if(NULL==want || 0==strcmp(want,"std"))

printf("standard deviation = %g \n",(float) fstd); </syntaxhighlight>

sfcat

Concatenate datasets.
sfcat > out.rsf space= axis=3 nspace=(int) (ni/(20*nin) + 1) [<file0.rsf] file1.rsf file2.rsf ...
sfmerge inserts additional space between merged data.
int axis=3 Axis being merged
int nspace=(int) (ni/(20*nin) + 1) if space=y, number of traces to insert
bool space= [y/n] Insert additional space.
y is default for sfmerge, n is default for sfcat


sfcat and sfmerge concatenate two or more files together along a particular axis. It is the same program, only sfcat has the default space=n and sfmerge has the default space=y. Example of sfcat:

bash$ sfspike n1=2 n2=3 > one.rsf
bash$ sfin one.rsf
one.rsf:
    in="/tmp/one.rsf@"
    esize=4 type=float form=native
    n1=2           d1=0.004       o1=0          label1="Time" unit1="s"
    n2=3           d2=0.1         o2=0          label2="Distance" unit2="km"
        6 elements 24 bytes
bash$ sfcat one.rsf one.rsf axis=1 > two.rsf
bash$ sfin two.rsf
two.rsf:
    in="/tmp/two.rsf@"
    esize=4 type=float form=native
    n1=4           d1=0.004       o1=0          label1="Time" unit1="s"
    n2=3           d2=0.1         o2=0          label2="Distance" unit2="km"
        12 elements 48 bytes

Example of sfmerge:

bash$ sfmerge one.rsf one.rsf axis=2 > two.rsf
bash$ sfin two.rsf
two.rsf:
    in="/tmp/two.rsf@"
    esize=4 type=float form=native
    n1=2           d1=0.004       o1=0          label1="Time" unit1="s"
    n2=7           d2=0.1         o2=0          label2="Distance" unit2="km"
        14 elements 56 bytes

In this case, an extra empty trace is inserted between the two merged files. The axes that are not being merged are checked for consistency:

bash$ sfcat one.rsf two.rsf > three.rsf
sfcat: n2 mismatch: need 3

Implementation: system/main/cat.c

The first input file is either in the list or in the standard input. <syntaxhighlight lang="c">

   in = (sf_file*) sf_alloc ((size_t) argc,sizeof(sf_file));
   if (!sf_stdin()) { /* no input file in stdin */

nin=0;

   } else {

in[0] = sf_input("in"); nin=1;

   }

</syntaxhighlight>

Everything on the command line that does not contain a "=" sign is treated as a file name, and the corresponding file object is added to the list. <syntaxhighlight lang="c">

   for (i=1; i< argc; i++) { /* collect inputs */

if (NULL != strchr(argv[i],'=')) continue; /* not a file */ in[nin] = sf_input(argv[i]); nin++;

   }
   if (0==nin) sf_error ("no input");

</syntaxhighlight>

As explained above, if the space= parameter is not set, it is inferred from the program name: sfmerge corresponds to space=y and sfcat corresponds to space=n. <syntaxhighlight lang="c">

   if (!sf_getbool("space",&space)) {

/* Insert additional space. y is default for sfmerge, n is default for sfcat */ prog = sf_getprog(); if (NULL != strstr (prog, "merge")) { space = true; } else if (NULL != strstr (prog, "cat")) { space = false; } else { sf_warning("%s is neither merge nor cat," " assume merge",prog); space = true; }

   }

</syntaxhighlight>

Find the axis for the merging (from the command line axis= argument) and figure out two sizes: n1 for everything after the axis and n2 for everything before the axis. <syntaxhighlight lang="c">

   n1=1;
   n2=1;
   for (i=1; i <= dim; i++) {

if (i < axis) n1 *= n[i-1]; else if (i > axis) n2 *= n[i-1];

   }

</syntaxhighlight>

In the output, the selected axis will get extended. <syntaxhighlight lang="c">

   /* figure out the length of extended axis */
   ni = 0;
   for (j=0; j < nin; j++) {

ni += naxis[j];

   }
   if (space) {

if (!sf_getint("nspace",&nspace)) nspace = (int) (ni/(20*nin) + 1); /* if space=y, number of traces to insert */ ni += nspace*(nin-1);

   } 
   (void) snprintf(key,3,"n%d",axis);
   sf_putint(out,key,(int) ni);

</syntaxhighlight>

The rest is simple: loop through the datasets reading and writing the data in buffer-size chunks and adding extra empty chunks if space=y. <syntaxhighlight lang="c">

   for (i2=0; i2 < n2; i2++) {

for (j=0; j < nin; j++) { for (ni = n1*naxis[j]*esize; ni > 0; ni -= nbuf) { nbuf = (BUFSIZ < ni)? BUFSIZ: ni; sf_charread (buf,nbuf,in[j]); sf_charwrite (buf,nbuf,out); } if (!space || j == nin-1) continue; /* Add spaces */ memset(buf,0,BUFSIZ); for (ni = n1*nspace*esize; ni > 0; ni -= nbuf) { nbuf = (BUFSIZ < ni)? BUFSIZ: ni; sf_charwrite (buf,nbuf,out); } }

   }

</syntaxhighlight>

sfcdottest

Generic dot-product test for complex linear operators with adjoints
sfcdottest mod=mod.rsf dat=dat.rsf > pip.rsf
file dat= auxiliary input file name
file mod= auxiliary input file name

A simple demonstration of the program can be made taking advantage that the complex-to-complex FFT is a linear operator:

sfspike n1=100 | sfrtoc > spike.rsf
< spike.rsf sffft axis=1 pad=1 > spike2.rsf
sfcdottest sffft mod=spike.rsf dat=spike2.rsf axis=1 pad=1

The output should show values identical down to the last decimal:

sfcdottest:  L[m]*d=(3.73955,-1.86955)
sfcdottest: L'[d]*m=(3.73955,-1.86955)

sfcmplx

Create a complex dataset from its real and imaginary parts.
sfcmplx > cmplx.rsf real.rsf imag.rsf
There has to be only two input files specified and no additional parameters.


sfcmplx simply creates a complex dataset from its real and imaginary parts. The reverse operation can be accomplished with sfreal and sfimag. Example of sfcmplx:

bash$ sfspike n1=2 n2=3 > one.rsf
bash$ sfin one.rsf
one.rsf:
    in="/tmp/one.rsf@"
    esize=4 type=float form=native
    n1=2           d1=0.004       o1=0          label1="Time" unit1="s"
    n2=3           d2=0.1         o2=0          label2="Distance" unit2="km"
        6 elements 24 bytes
bash$ sfcmplx one.rsf one.rsf > cmplx.rsf
bash$ sfin cmplx.rsf
cmplx.rsf:
    in="/tmp/cmplx.rsf@"
    esize=8 type=complex form=native
    n1=2           d1=0.004       o1=0          label1="Time" unit1="s"
    n2=3           d2=0.1         o2=0          label2="Distance" unit2="km"
        6 elements 48 bytes

Implementation: system/main/cmplx.c

The program flow is simple. First, get the names of the input files. <syntaxhighlight lang="c">

   /* the first two non-parameters are real and imaginary files */
   for (i=1; i< argc; i++) { 

if (NULL == strchr(argv[i],'=')) { if (NULL == real) { real = sf_input (argv[i]); } else { imag = sf_input (argv[i]); break; } }

   }
   if (NULL == imag) {

if (NULL == real) sf_error ("not enough input"); /* if only one input, real is in stdin */ imag = real; real = sf_input("in");

   }

</syntaxhighlight>

The main part of the program reads the real and imaginary parts buffer by buffer and assembles and writes out the complex input. <syntaxhighlight lang="c">

   for (nleft= (size_t) (rsize*resize); nleft > 0; nleft -= nbuf) {

nbuf = (BUFSIZ < nleft)? BUFSIZ: nleft; sf_charread(rbuf,nbuf,real); sf_charread(ibuf,nbuf,imag); for (i=0; i < nbuf; i += resize) { memcpy(cbuf+2*i, rbuf+i,(size_t) resize); memcpy(cbuf+2*i+resize,ibuf+i,(size_t) resize); } sf_charwrite(cbuf,2*nbuf,cmplx);

   }

</syntaxhighlight>

sfconjgrad

Generic conjugate-gradient solver for linear inversion
sfconjgrad < dat.rsf mod=mod.rsf > to.rsf < from.rsf > out.rsf niter=1
int niter=1 number of iterations

sfconjgrad is a generic program for least-squares linear inversion with the conjugate-gradient method. Suppose you have an executable program <prog> that takes an RSF file from the standard input and produces an RSF file in the standard output. It may take any number of additional parameters but one of them must be adj= that sets the forward (adj=0) or adjoint (adj=1) operations. The program <prog> is typically an RSF program but it could be anything (a script, a multiprocessor MPI program, etc.) as long as it implements a linear operator \mathbf{L} and its adjoint. There are no restrictions on the data size or shape. You can easily test the adjointness with sfdottest. The sfconjgrad program searches for a vector \mathbf{m} that minimizes the least-square misfit \|\mathbf{d - L\,m}\|^2 for the given input data vector \mathbf{d}.

The pseudocode for sfconjgrad is given at the end of the "Model fitting with least squares" chapter of Imaging Estimation by Example by Jon Claerbout, with the earliest form published in "Conjugate Gradient Tutorial" (SEP-48, 1986, same author). A simple toy implementation with a small matrix shows that this is algorithm produces the same steps as the algorithm described in equations 45-49 of "An introduction to the Conjugate Gradient Method Without the Agonizing Pain" by J.R. Shewchuk, 1994, when the equation A^T A x = A^T b (in Shewchuk's notation) is solved. Multiplying with the transpose ensures a correct solution even when matrix A is square but not symmetric, or not square at all. The program sfcconjgrad implements this algorithm for the case when inputs are complex.

Here is an example. The sfhelicon program implements Claerbout's multidimensional helical filtering (Claerbout, 1998[1]). It requires a filter to be specified in addition to the input and output vectors. We create a helical 2-D filter using the Unix echo command.

bash$ echo 1 19 20 n1=3 n=20,20 data_format=ascii_int in=lag.rsf > lag.rsf
bash$ echo 1 1 1 a0=-3 n1=3 data_format=ascii_float in=flt.rsf > flt.rsf

Next, we create an example 2-D model and data vector with sfspike.

bash$ sfspike n1=50 n2=50 > vec.rsf

The sfdottest program can perform the dot product test to check that the adjoint mode works correctly.

bash$ sfdottest sfhelicon filt=flt.rsf lag=lag.rsf mod=vec.rsf dat=vec.rsf
sfdottest:  L[m]*d=5.28394
sfdottest: L'[d]*m=5.28394

Your numbers may be different because sfdottest generates new random input on each run. Next, let us make some random data with sfnoise.

bash$ sfnoise seed=2005 rep=y < vec.rsf > dat.rsf

and try to invert the filtering operation using sfconjgrad:

bash$ sfconjgrad sfhelicon filt=flt.rsf lag=lag.rsf mod=vec.rsf < dat.rsf > mod.rsf niter=10
sfconjgrad: iter 1 of 10
sfconjgrad: grad=3253.65
sfconjgrad: iter 2 of 10
sfconjgrad: grad=289.421
sfconjgrad: iter 3 of 10
sfconjgrad: grad=92.3481
sfconjgrad: iter 4 of 10
sfconjgrad: grad=36.9417
sfconjgrad: iter 5 of 10
sfconjgrad: grad=18.7228
sfconjgrad: iter 6 of 10
sfconjgrad: grad=11.1794
sfconjgrad: iter 7 of 10
sfconjgrad: grad=7.26941
sfconjgrad: iter 8 of 10
sfconjgrad: grad=5.15945
sfconjgrad: iter 9 of 10
sfconjgrad: grad=4.23055
sfconjgrad: iter 10 of 10
sfconjgrad: grad=3.57495

The output shows that, in 10 iterations, the norm of the gradient vector decreases by almost 1000. We can check the residual misfit before

bash$ < dat.rsf sfattr want=norm
norm value = 49.7801

and after

bash$ sfhelicon filt=flt.rsf lag=lag.rsf < mod.rsf | sfadd scale=1,-1 dat.rsf | sfattr want=norm
norm value = 5.73563

In 10 iterations, the misfit decreased by an order of magnitude. The result can be improved by running the program for more iterations.

An equivalent implementation for complex-valued inputs is sfcconjgrad. A simple, lightweight Python implementation can be found in $PYTHONPATH/rsf/conjgrad.py.

sfcp

Copy or move a dataset.
sfcp in.rsf out.rsf
sfcp - copy, sfmv - move.
Mimics standard Unix commands.


The sfcp and sfmv command imitate the Unix cp and mv commands and serve for copying and moving RSF files. Example:

bash$ sfspike n1=2 n2=3 > one.rsf
bash$ sfin one.rsf
one.rsf:
    in="/tmp/one.rsf@"
    esize=4 type=float form=native
    n1=2           d1=0.004       o1=0          label1="Time" unit1="s"
    n2=3           d2=0.1         o2=0          label2="Distance" unit2="km"
        6 elements 24 bytes
bash$ sfcp one.rsf two.rsf
bash$ sfin two.rsf
two.rsf:
    in="/tmp/two.rsf@"
    esize=4 type=float form=native
    n1=2           d1=0.004       o1=0          label1="Time" unit1="s"
    n2=3           d2=0.1         o2=0          label2="Distance" unit2="km"
        6 elements 24 bytes

Implementation: system/main/cp.c

First, we look for the two first command-line arguments that don't have the "=" character in them and consider them as the names of the input and the output files. <syntaxhighlight lang="c">

   /* the first two non-parameters are in and out files */
   for (i=1; i< argc; i++) { 

if (NULL == strchr(argv[i],'=')) { if (NULL == in) { infile = argv[i]; in = sf_input (infile); } else { out = sf_output (argv[i]); break; } }

   }
   if (NULL == in || NULL == out)

sf_error ("not enough input"); </syntaxhighlight>

Next, we use library functions sf_cp and sf_rm to do the actual work. <syntaxhighlight lang="c">

   sf_cp(in,out);
   if (NULL != strstr (sf_getprog(),"mv")) 

sf_rm(infile,false,false,false); </syntaxhighlight>

sfcut

Zero a portion of the dataset.
sfcut < in.rsf > out.rsf verb=n [j1=1 j2=1 ... f1=0 f2=0 ... n1=n1 n2=n2 ... max1= max2= ... min1= min2= ...]
jN defines the jump in N-th dimension
fN is the window start
nN is the window size
minN and maxN is the maximum and minimum in N-th dimension

Reverse of window.
bool verb=n [y/n] Verbosity flag


The sfcut command is related to sfwindow and has the same set of arguments only instead of extracting the selected window, it fills it with zeroes. The size of the input data is preserved. Examples:

bash$ sfspike n1=5 n2=5 > in.rsf
bash$ < in.rsf sfdisfil
   0:             1            1            1            1            1
   5:             1            1            1            1            1
  10:             1            1            1            1            1
  15:             1            1            1            1            1
  20:             1            1            1            1            1
bash$ < in.rsf sfcut n1=2 f1=1 n2=3 f2=2 | sfdisfil
   0:             1            1            1            1            1
   5:             1            1            1            1            1
  10:             1            0            0            1            1
  15:             1            0            0            1            1
  20:             1            0            0            1            1
bash$ < in.rsf sfcut j1=2 | sfdisfil
   0:             0            1            0            1            0
   5:             0            1            0            1            0
  10:             0            1            0            1            0
  15:             0            1            0            1            0
  20:             0            1            0            1            0

sfdd

Convert between different formats.
sfdd < in.rsf > out.rsf line=8 form= type= format=
string form= ascii, native, xdr
string format= Element format (for conversion to ASCII)
int line=8 Number of numbers per line (for conversion to ASCII)
string type= int, float, complex


The sfdd program is used to change either the form (ascii, xdr, native) or the type (complex, float, int, char) of the input dataset. In the example below, we create a plain text (ASCII) file with numbers and then use sfdd to generate an RSF file in xdr form with complex numbers.

bash$ cat test.txt
1 2 3 4 5 6
bash$ echo n1=6 data_format=ascii_int in=test.txt > test.rsf
bash$ sfin test.rsf
test.rsf:
    in="test.txt"
    esize=0 type=int form=ascii
    n1=6           d1=?           o1=?
        6 elements
bash$ sfdd < test.rsf form=xdr type=complex > test2.rsf
bash$ sfin test2.rsf
test2.rsf:
    in="/tmp/test2.rsf@"
    esize=8 type=complex form=xdr
    n1=3           d1=?           o1=?
        3 elements 24 bytes
bash$ sfdisfil < test2.rsf
   0:          1,         2i         3,         4i         5,         6i

To learn more about the RSF data format, consult the guide to RSF format.

sfdisfil

Print out data values.
sfdisfil < in.rsf number=y col=0 format= header= trailer=

Alternatively, use sfdd and convert to ASCII form.
int col=0 Number of columns.
The default depends on the data type:
10 for int and char,
5 for float,
3 for complex
string format= Format for numbers (printf-style).
The default depends on the data type:
"%4d " for int and char,
"%13.4g" for float,
"%10.4g,%10.4gi" for complex
string header= Optional header string to output before data
bool number=y [y/n] If number the elements
string trailer= Optional trailer string to output after data


The sfdisfil program simply dumps the data contents to the standard output in a text form. It is used mostly for debugging purposes to quickly examine RSF files. Here is an example:

bash$ sfmath o1=0 d1=2 n1=12 output=x1 > test.rsf
bash$ < test.rsf sfdisfil
   0:             0            2            4            6            8
   5:            10           12           14           16           18
  10:            20           22

The output format is easily configurable.

bash$ < test.rsf sfdisfil col=6 number=n format="%5.1f"
  0.0  2.0  4.0  6.0  8.0 10.0
 12.0 14.0 16.0 18.0 20.0 22.0

Along with sfdd, sfdisfil provides a simple way to convert RSF data to an ASCII form.

sfdottest

Generic dot-product test for linear operators with adjoints
sfdottest mod=mod.rsf dat=dat.rsf > pip.rsf


sfdottest is a generic dot-product test program for testing linear operators. Suppose there is an executable program <prog> that takes an RSF file from the standard input and produces an RSF file in the standard output. It may take any number of additional parameters but one of them must be adj= that sets the forward (adj=0) or adjoint (adj=1) operations. The program <prog> is typically an RSF program but it could be anything (a script, a multiprocessor MPI program, etc.) as long as it implements a linear operator \mathbf{L} and its adjoint \mathbf{L}^T. The sfdottest program is testing the equality


d^T\,L\,m = m^T\,L^T\,d

by using random vectors \mathbf{m} and \mathbf{d}. You can invoke it with

bash$ sfdottest <prog> [optional aruments] mod=mod.rsf dat=dat.rsf

where mod.rsf and dat.rsf are RSF files that represent vectors from the model and data spaces. Pay attention to the dimension and size of these vectors! If the program does not respond for a very long time, it is quite possible that the dimension and size of the vectors are inconsistent with the requirement of the program to be tested. sfdottest does not create any temporary files and does not have any restrictive limitations on the size of the vectors. Here is an example. We first setup a vector with 100 elements using sfspike and then run sfdottest to test the sfcausint program. sfcausint implements a linear operator of causal integration and its adjoint, the anti-causal integration.

bash$ sfspike n1=100 > vec.rsf
bash$ sfdottest sfcausint mod=vec.rsf dat=vec.rsf
sfdottest:  L[m]*d=1410.2
sfdottest: L'[d]*m=1410.2
bash$ sfdottest sfcausint mod=vec.rsf dat=vec.rsf
sfdottest:  L[m]*d=1165.87
sfdottest: L'[d]*m=1165.87

The numbers are different on subsequent runs because of changing seed in the random number generator. Here is a somewhat more complicated example. The sfhelicon program implements Claerbout's multidimensional helical filtering (Claerbout, 1998[2]). It requires a filter to be specified in addition to the input and output vectors. We create a helical 2-D filter using the Unix echo command.

bash$ echo 1 19 20 n1=3 n=20,20 data_format=ascii_int in=lag.rsf > lag.rsf
bash$ echo 1 1 1 a0=-3 n1=3 data_format=ascii_float in=flt.rsf > flt.rsf

Next, we create an example 2-D model and data vector with sfspike.

bash$ sfspike n1=50 n2=50 > vec.rsf

Now the sfdottest program can perform the dot product test.

bash$ sfdottest sfhelicon filt=flt.rsf lag=lag.rsf \
> mod=vec.rsf dat=vec.rsf
sfdottest:  L[m]*d=8.97375
sfdottest: L'[d]*m=8.97375

Here is the same program tested in the inverse filtering mode:

bash$ sfdottest sfhelicon filt=flt.rsf lag=lag.rsf \
> mod=vec.rsf dat=vec.rsf div=y
sfdottest:  L[m]*d=15.0222
sfdottest: L'[d]*m=15.0222

sfget

Output parameters from the header.
sfget < in.rsf parform=y par1 par2 ...
bool parform=y [y/n] If y, print out parameter=value. If n, print out value.


The sfget program extracts a parameter value from an RSF file. It is useful mostly for scripting. Here is, for example, a quick calculation of the maximum value on the first axis in an RSF dataset (the output of sfspike) using the standard Unix bc calculator.

bash$ ( sfspike n1=100 | sfget n1 d1 o1; echo "o1+(n1-1)*d1" ) | bc
.396

See also sfput.

Implementation: system/main/get.c

The implementation is trivial. Loop through all command-line parameters that contain the "=" character. <syntaxhighlight lang="c">

   for (i = 1; i < argc; i++) {

key = argv[i]; if (NULL != strchr(key,'=')) continue; </syntaxhighlight>

Get the parameter value (as string) and output it as either key=value or value, depending on the parform parameter. <syntaxhighlight lang="c"> string = sf_histstring(in,key); if (NULL == string) { sf_warning("No key %s",key); } else { if (parform) printf ("%s=",key); printf("%s\n",string); } </syntaxhighlight>

sfheadercut

Zero a portion of a dataset based on a header mask.
sfheadercut mask=head.rsf < in.rsf > out.rsf

The input data is a collection of traces n1xn2,
mask is an integer array of size n2.


sfheadercut is close to sfheaderwindow but instead of windowing the dataset, it fills the traces specified by the header mask with zeroes. The size of the input data is preserved. Here is an example of using sfheaderwindow for zeroing every other trace in the input file. First, let us create an input file with ten traces:

bash$ sfmath n1=5 n2=10 output=x2+1 > input.rsf
bash$ < input.rsf sfdisfil
   0:             1            1            1            1            1
   5:             2            2            2            2            2
  10:             3            3            3            3            3
  15:             4            4            4            4            4
  20:             5            5            5            5            5
  25:             6            6            6            6            6
  30:             7            7            7            7            7
  35:             8            8            8            8            8
  40:             9            9            9            9            9
  45:            10           10           10           10           10

Next, we can create a mask with alternating ones and zeros using sfinterleave.

bash$ sfspike n1=5 mag=1 | sfdd type=int > ones.rsf
bash$ sfspike n1=5 mag=0 | sfdd type=int > zeros.rsf
bash$ sfinterleave axis=1 ones.rsf zeros.rsf > mask.rsf
bash$ sfdisfil < mask.rsf
   0:    1    0    1    0    1    0    1    0    1    0

Finally, sfheadercut zeros the input traces.

bash$ sfheadercut < input.rsf mask=mask.rsf > output.rsf
bash$ sfdisfil < output.rsf 
   0:             1            1            1            1            1
   5:             0            0            0            0            0
  10:             3            3            3            3            3
  15:             0            0            0            0            0
  20:             5            5            5            5            5
  25:             0            0            0            0            0
  30:             7            7            7            7            7
  35:             0            0            0            0            0
  40:             9            9            9            9            9
  45:             0            0            0            0            0


sfheadersort

Sort a dataset according to a header key.
sfheadersort < in.rsf > out.rsf head=
string head= header file


sfheadersort is used to sort traces in the input file according to trace header information. Here is an example of using sfheadersort for randomly shuffling traces in the input file. First, let us create an input file with seven traces:

bash$ sfmath n1=5 n2=7 output=x2+1 > input.rsf
bash$ < input.rsf sfdisfil
   0:             1            1            1            1            1
   5:             2            2            2            2            2
  10:             3            3            3            3            3
  15:             4            4            4            4            4
  20:             5            5            5            5            5
  25:             6            6            6            6            6
  30:             7            7            7            7            7 

Next, we can create a random file with seven header values using sfnoise.

bash$ sfspike n1=7 | sfnoise rep=y type=n > random.rsf
bash$ < random.rsf sfdisfil
   0:       0.05256      -0.2879       0.1487       0.4097       0.1548
   5:        0.4501       0.2836

If you reproduce this example, your numbers will most likely be different, because, in the absence of seed= parameter, sfnoise uses a random seed value to generate pseudo-random numbers. Finally, we apply sfheadersort to shuffle the input traces.

bash$ < input.rsf sfheadersort head=random.rsf > output.rsf
bash$ < output.rsf sfdisfil
   0:             2            2            2            2            2
   5:             1            1            1            1            1
  10:             3            3            3            3            3
  15:             5            5            5            5            5
  20:             7            7            7            7            7
  25:             4            4            4            4            4
  30:             6            6            6            6            6

As expected, the order of traces in the output file corresponds to the order of values in the header. Thanks to the separation between headers and data, the operation of sfheadersort is optimally efficient. It first sorts the headers and only then accesses the data, reading each data trace only once.

sfheaderwindow

Window a dataset based on a header mask.
sfheaderwindow mask=head.rsf < in.rsf > out.rsf

The input data is a collection of traces n1xn2,
mask is an integer array os size n2, windowed is n1xm2,
where m2 is the number of nonzero elements in mask.


sfheaderwindow is used to window traces in the input file according to trace header information. Here is an example of using sfheaderwindow for randomly selecting part of the traces in the input file. First, let us create an input file with ten traces:

bash$ sfmath n1=5 n2=10 output=x2+1 > input.rsf
bash$ < input.rsf sfdisfil
   0:             1            1            1            1            1
   5:             2            2            2            2            2
  10:             3            3            3            3            3
  15:             4            4            4            4            4
  20:             5            5            5            5            5
  25:             6            6            6            6            6
  30:             7            7            7            7            7
  35:             8            8            8            8            8
  40:             9            9            9            9            9
  45:            10           10           10           10           10

Next, we can create a random file with ten header values using sfnoise.

bash$ sfspike n1=10 | sfnoise rep=y type=n > random.rsf
bash$ < random.rsf sfdisfil
   0:     -0.005768      0.02258     -0.04331      -0.4129      -0.3909
   5:      -0.03582       0.4595      -0.3326        0.498      -0.3517

If you reproduce this example, your numbers will most likely be different, because, in the absence of seed= parameter, sfnoise uses a random seed value to generate pseudo-random numbers. Finally, we apply sfheaderwindow to window the input traces selecting only those for which the header is greater than zero.

bash$ < random.rsf sfmask min=0 > mask.rsf
bash$ < mask.rsf sfdisfil
   0:    0    1    0    0    0    0    1    0    1    0
bash$ < input.rsf sfheaderwindow mask=mask.rsf > output.rsf
bash$ < output.rsf sfdisfil
   0:             2            2            2            2            2
   5:             7            7            7            7            7
  10:             9            9            9            9            9

In this case, only three traces are selected for the output. Thanks to the separation between headers and data, the operation of sfheaderwindow is optimally efficient.

sfin

Display basic information about RSF files.
sfin info=y check=2. trail=y file1.rsf file2.rsf ...
n1,n2,... are data dimensions
o1,o2,... are axis origins
d1,d2,... are axis sampling intervals
label1,label2,... are axis labels
unit1,unit2,... are axis units
float check=2. Portion of the data (in Mb) to check for zero values.
bool info=y [y/n] If n, only display the name of the data file.
bool trail=y [y/n] If n, skip trailing dimensions of one


sfin is one of the most useful programs for operating with RSF files. It produces quick information on the file hypercube dimensions and checks the consistency of the associated data file. Here is an example. Let us create an RSF file and examine it with sfin.

bash$ sfspike n1=100 n2=20 > spike.rsf
bash$ sfin spike.rsf
spike.rsf:
    in="/tmp/spike.rsf@"
    esize=4 type=float form=native
    n1=100         d1=0.004       o1=0          label1="Time" unit1="s"
    n2=20          d2=0.1         o2=0          label2="Distance" unit2="km"
        2000 elements 8000 bytes

sfin reports the following information:

  • location of the data file (/tmp/spike.rsf\@)
  • element size (4 bytes)
  • element type (floating point)
  • element form (native)
  • hypercube dimensions (100 by 20)
  • axes scale (0.004 and 0.1)
  • axes origin (0 and 0)
  • axes labels
  • axes units
  • total number of elements
  • total number of bytes in the data file

Suppose that the file got corrupted by a buggy program and reports incorrect dimensions. The sfin program should be able to catch the discrepancy.

bash$ echo n2=100 >> spike.rsf
bash$ sfin spike.rsf > /dev/null
sfin:           Actually 8000 bytes, 20% of expected.

sfin also checks the first records in the file for zeros.

bash$ sfspike n1=100 n2=100 k2=99 > spike2.rsf
bash$ sfin spike2.rsf >/dev/null
sfin: The first 32768 bytes are all zeros

The number of bytes to check is adjustable

bash$ sfin spike2.rsf check=0.01 >/dev/null
sfin: The first 16384 bytes are all zeros

You can also output only the location of the data file. This is sometimes handy in scripts.

bash$ sfin spike.rsf spike2.rsf info=n
/tmp/spike.rsf@ /tmp/spike2.rsf@

An alternative is to use sfget, as follows:

bash$ sfget parform=n in < spike.rsf
/tmp/spike.rsf@

To actually eliminate annoying trailing dimensions of length one (not just stop displaying them with trail=n), you may use sed. Example for eliminating axis 6:

sed -i 's/n6=1//g' file.rsf

sfinterleave

Combine several datasets by interleaving.
sfinterleave > out.rsf axis=3 [< file0.rsf] file1.rsf file2.rsf ...
int axis=3 Axis for interleaving


sfinterleave combines two or more datasets by interleaving them on one of the axes. Here is a quick example:

bash$ sfspike n1=5 n2=5 > one.rsf
bash$ sfdisfil < one.rsf
   0:             1            1            1            1            1
   5:             1            1            1            1            1
  10:             1            1            1            1            1
  15:             1            1            1            1            1
  20:             1            1            1            1            1
bash$ sfscale < one.rsf dscale=2 > two.rsf
bash$ sfdisfil < two.rsf
   0:             2            2            2            2            2
   5:             2            2            2            2            2
  10:             2            2            2            2            2
  15:             2            2            2            2            2
  20:             2            2            2            2            2
bash$ sfinterleave one.rsf two.rsf axis=1 | sfdisfil
   0:             1            2            1            2            1
   5:             2            1            2            1            2
  10:             1            2            1            2            1
  15:             2            1            2            1            2
  20:             1            2            1            2            1
  25:             2            1            2            1            2
  30:             1            2            1            2            1
  35:             2            1            2            1            2
  40:             1            2            1            2            1
  45:             2            1            2            1            2
bash$ sfinterleave < one.rsf two.rsf axis=2 | sfdisfil
   0:             1            1            1            1            1
   5:             2            2            2            2            2
  10:             1            1            1            1            1
  15:             2            2            2            2            2
  20:             1            1            1            1            1
  25:             2            2            2            2            2
  30:             1            1            1            1            1
  35:             2            2            2            2            2
  40:             1            1            1            1            1
  45:             2            2            2            2            2

sfmask

Create a mask.
sfmask < in.rsf > out.rsf min=-FLT_MAX max=+FLT_MAX

Mask is an integer data with ones and zeros.
Ones correspond to input values between min and max.

The output can be used with sfheaderwindow.
float max=+FLT_MAX maximum header value
float min=-FLT_MAX minimum header value


sfmask creates an integer output of ones and zeros comparing the values of the input data to specified min= and max= parameters. It is useful for sfheaderwindow and in many other applications. Here is a quick example:

bash$ sfmath n1=10 output="sin(x1)" > sin.rsf
bash$ < sin.rsf sfdisfil
   0:             0       0.8415       0.9093       0.1411      -0.7568
   5:       -0.9589      -0.2794        0.657       0.9894       0.4121
bash$ < sin.rsf sfmask min=-0.5 max=0.5 | sfdisfil
   0:    1    0    0    1    0    0    1    0    0    1

sfmath

Mathematical operations on data files.
sfmath > out.rsf n#= d#=(1,1,...) o#=(0,0,...) label#= unit#= type= label= unit= output=

Known functions:
cos, sin, tan, acos, asin, atan,
cosh, sinh, tanh, acosh, asinh, atanh,
exp, log, sqrt, abs,
erf, erfc (for float data),
arg, conj, real, imag (for complex data).

sfmath will work on float or complex data, but all the input and output
files must be of the same data type.

An alternative to sfmath is sfadd, which may be more efficient, but is
less versatile.

Examples:

sfmath x=file1.rsf y=file2.rsf power=file3.rsf output='sin((x+2*y)^power)' > out.rsf
sfmath < file1.rsf tau=file2.rsf output='exp(tau*input)' > out.rsf
sfmath n1=100 type=complex output="exp(I*x1)" > out.rsf

Arguments which are not treated as variables in mathematical expressions:
datapath=, type=, out=

See also: sfheadermath.
float d#=(1,1,...) sampling on #-th axis
string label= data label
string label#= label on #-th axis
largeint n#= size of #-th axis
float o#=(0,0,...) origin on #-th axis
string output= Mathematical description of the output
string type= output data type [float,complex]
string unit= data unit
string unit#= unit on #-th axis

sfmath is a versatile program for mathematical operations with RSF files. It can operate with several input files, all of the same dimensions and data type. The data type can be real (floating point) or complex. Here is an example that demonstrates several features of sfmath.

bash$ sfmath n1=629 d1=0.01 o1=0 n2=40 d2=1 o2=5 \
output="x2*(8+sin(6*x1+x2/10))" > rad.rsf
bash$ < rad.rsf sfrtoc | sfmath output="input*exp(I*x1)" > rose.rsf
bash$ < rose.rsf sfgraph title=Rose screenratio=1 wantaxis=n | sfpen

The first line creates a 2-D dataset that consists of 40 traces 629 samples each. The values of the data are computed with the formula "x2*(8+sin(6*x1+x2/10))", where x1 refers to the coordinate on the first axis, and x2 is the coordinate of the second axis. In the second line, we convert the data from real to complex using sfrtoc and produce a complex dataset using formula "input*exp(I*x1)", where input refers to the input file. Finally, we plot the complex data as a collection of parametric curves using sfgraph and display the result using sfpen. The plot appearing on your screen should look similar to the figure.

This figure was created with sfmath.

One possible alternative to the second line above is

bash$ < rad.rsf sfmath output=x1 > ang.rsf
bash$ sfmath r=rad.rsf a=ang.rsf output="r*cos(a)" > cos.rsf
bash$ sfmath r=rad.rsf a=ang.rsf output="r*sin(a)" > sin.rsf
bash$ sfcmplx cos.rsf sin.rsf > rose.rsf

Here we refer to input files by names (r and a) and combine the names in a formula.

Functions can be nested and combined, and variable names, as well as the the input keyword may be combined with the axes keywords x1, x2, etc. Here is an example that shifts a wavelet -0.4s to t=0, computes the frequency-domain complex square root (equivalent to the convolutional square root in time), and shifts the result back to t=0.4s:

pi=3.14159265
tshift=0.4
 
sfspike n1=256 k1=101 |\
sfbandpass flo=4 fhi=30 |\
sffft1 opt=n sym=y |\
sfmath output="sqrt(input*exp(2*$pi*$tshift*x1*I))*exp(-2*$pi*$tshift*x1*I)" |\
sffft1 opt=n sym=y inv=y |\
sfgraph |\
sfpen

sfpad

Pad a dataset with zeros.
sfpad < in.rsf > out.rsf beg#=0 end#=0 n#=

n#out is equivalent to n#, both of them overwrite end#.
int beg#=0 the number of zeros to add before the beginning of #-th axis
int end#=0 the number of zeros to add after the end of #-th axis
int n#= the output length of #-th axis - padding at the end

sfpad increases the dimensions of the input dataset by padding the data with zeroes. Here are some simple examples.

bash$ sfspike n1=5 n2=3 > one.rsf
bash$ sfdisfil < one.rsf
   0:             1            1            1            1            1
   5:             1            1            1            1            1
  10:             1            1            1            1            1
bash$ < one.rsf sfpad n2=5 | sfdisfil
   0:             1            1            1            1            1
   5:             1            1            1            1            1
  10:             1            1            1            1            1
  15:             0            0            0            0            0
  20:             0            0            0            0            0
bash$ < one.rsf sfpad beg2=2 | sfdisfil
   0:             0            0            0            0            0
   5:             0            0            0            0            0
  10:             1            1            1            1            1
  15:             1            1            1            1            1
  20:             1            1            1            1            1
bash$ < one.rsf sfpad beg2=1 end2=1 | sfdisfil
   0:             0            0            0            0            0
   5:             1            1            1            1            1
  10:             1            1            1            1            1
  15:             1            1            1            1            1
  20:             0            0            0            0            0
bash$ < one.rsf sfwindow n1=3 | sfpad n1=5 n2=5 beg1=1 beg2=1 | sfdisfil
   0:             0            0            0            0            0
   5:             0            1            1            1            0
  10:             0            1            1            1            0
  15:             0            1            1            1            0
  20:             0            0            0            0            0

You can use sfcat to pad data with values other than zeroes.

sfput

Input parameters into a header.
sfput < in.rsf > out.rsf [parameter=value list]


sfput is a very simple program. It simply appends parameters from the command line to the output RSF file. One can achieve similar results with editing the file by hand or with standard Unix utilities like sed and echo. sfput is sometimes more convenient because it handles input/output operations similarly to other Madagascar programs.

bash$ sfspike n1=10 > spike.rsf
bash$ sfin spike.rsf
spike.rsf:
    in="/tmp/spike.rsf@"
    esize=4 type=float form=native
    n1=10          d1=0.004       o1=0          label1="Time" unit1="s"
        10 elements 40 bytes
bash$ sfput < spike.rsf d1=25 label1=Depth unit1=m > spike2.rsf
bash$ sfin spike2.rsf
spike2.rsf:
    in="/tmp/spike2.rsf@"
    esize=4 type=float form=native
    n1=10          d1=25          o1=0          label1="Depth" unit1="m"
        10 elements 40 bytes

sfreal

Extract real (sfreal) or imaginary (sfimag) part of a complex dataset.
sfreal < cmplx.rsf > real.rsf


sfreal extracts the real part of a complex type dataset. The imaginary part can be extracted with sfimag, an the real and imaginary part can be combined together with sfcmplx. Here is a simple example. Let us first create a complex dataset with sfmath

bash$ sfmath n1=10 type=complex output="(2+I)*x1" > cmplx.rsf
bash$ fdisfil < cmplx.rsf
   0:          0,         0i         2,         1i         4,         2i
   3:          6,         3i         8,         4i        10,         5i
   6:         12,         6i        14,         7i        16,         8i
   9:         18,         9i

Extracting the real part with sfreal:

bash$ sfreal < cmplx.rsf | sfdisfil
   0:             0            2            4            6            8
   5:            10           12           14           16           18

Extracting the imaginary part with sfimag:

bash$ sfimag < cmplx.rsf | sfdisfil
   0:             0            1            2            3            4
   5:             5            6            7            8            9

sfreverse

Reverse one or more axes in the data hypercube.
sfreverse < in.rsf > out.rsf which=-1 verb=false memsize=sf_memsize() opt=
int memsize=sf_memsize() Max amount of RAM (in Mb) to be used
string opt= If y, change o and d parameters on the reversed axis;
if i, don't change o and d
bool verb=n [y/n] Verbosity flag
int which=-1 Which axis to reverse.
To reverse a given axis, start with 0,
add 1 to number to reverse n1 dimension,
add 2 to number to reverse n2 dimension,
add 4 to number to reverse n3 dimension, etc.
Thus, which=7 would reverse the first three dimensions,
which=5 just n1 and n3, etc.
which=0 will just pass the input on through unchanged.

Here is an example of using sfreverse. First, let us create a 2-D dataset.

bash$ sfmath n1=5 d1=1 n2=3 d2=1 output=x1+x2 > test.rsf
bash$ < test.rsf sfdisfil
   0:             0            1            2            3            4
   5:             1            2            3            4            5
  10:             2            3            4            5            6

Reversing the first axis:

bash$ < test.rsf sfreverse which=1 | sfdisfil
   0:             4            3            2            1            0
   5:             5            4            3            2            1
  10:             6            5            4            3            2

Reversing the second axis:

bash$ < test.rsf sfreverse which=2 | sfdisfil
   0:             2            3            4            5            6
   5:             1            2            3            4            5
  10:             0            1            2            3            4

Reversing both the first and the second axis:

bash$ < test.rsf sfreverse which=3 | sfdisfil
   0:             2            3            4            5            6
   5:             1            2            3            4            5
  10:             0            1            2            3            4

As you can see, the which= parameter controls the axes that are being reversed by encoding them into one number. When an axis is reversed, what happens with its axis origin and sampling parameters? This behavior is controlled by opt=. In our example,

bash$ < test.rsf sfget n1 o1 d1
n1=5
o1=0
d1=1
bash$ < test.rsf sfreverse which=1 | sfget o1 d1
o1=4
d1=-1

The default behavior (equivalent to opt=y) puts the origin o1 at the end of the axis and reverses the sampling parameter d1. Using opt=n preserves the sampling but reverses the origin.

bash$ < test.rsf sfreverse which=1 opt=n | sfget o1 d1
o1=-4
d1=1

Using opt=i preserves both the sampling and the origin while reversing the axis.

bash$ < test.rsf sfreverse which=1 opt=i | sfget o1 d1
o1=0
d1=1

One of the three possible behaviors may be desirable depending on the application.

sfrm

Remove RSF files together with their data.
sfrm file1.rsf [file2.rsf ...] [-i] [-v] [-f]
Mimics the standard Unix rm command.

See also: sfmv, sfcp.

sfrm is a program for removing RSF files. Its arguments mimic the arguments of the standard Unix rm utility: -v for verbosity, -i for interactive inquiry, -f for force removal of suspicious files. Unlike the Unix rm, sfrm removes both the RSF header files and the binary files that the headers point to. Example:

bash$ sfspike n1=10 > spike.rsf datapath=./
bash$ sfget in < spike.rsf
in=./spike.rsf@
bash$ ls spike*
spike.rsf  spike.rsf@
bash$ sfrm -v spike.rsf
sfrm: sf_rm: Removing header spike.rsf
sfrm: sf_rm: Removing data ./spike.rsf@
bash$ ls spike*
ls: No match.

sfrotate

Rotate a portion of one or more axes in the data hypercube.
sfrotate < in.rsf > out.rsf verb=n memsize=sf_memsize() rot#=(0,0,...)
int memsize=sf_memsize() Max amount of RAM (in Mb) to be used
int rot#=(0,0,...) length of #-th axis that is moved to the end
bool verb=n [y/n] Verbosity flag

sfrotate modifies the input dataset by splitting it into parts and putting the parts back in a different order. Here is a quick example.

bash$ sfmath n1=5 d1=1 n2=3 d2=1 output=x1+x2 > test.rsf
bash$ < test.rsf sfdisfil
   0:             0            1            2            3            4
   5:             1            2            3            4            5
  10:             2            3            4            5            6

Rotating the first axis by putting the last two columns in front:

bash$ < test.rsf sfrotate rot1=2 | sfdisfil
   0:             3            4            0            1            2
   5:             4            5            1            2            3
  10:             5            6            2            3            4

Rotating the second axis by putting the last row in front:

bash$ < test.rsf sfrotate rot2=1 | sfdisfil
   0:             2            3            4            5            6
   5:             0            1            2            3            4
  10:             1            2            3            4            5

Rotating both the first and the second axis:

bash$ < test.rsf sfrotate rot1=3 rot2=1 | sfdisfil
   0:             4            5            6            2            3
   5:             2            3            4            0            1
  10:             3            4            5            1            2

The transformation is shown schematically in Figure~(fig:rotate).

Schematic transformation of data with sfrotate.

sfrtoc

Convert real data to complex (by adding zero imaginary part).
sfrtoc < real.rsf > cmplx.rsf

See also: sfcmplx

The input to sfrtoc can be any type=float dataset:

bash$ sfspike n1=10 n2=20 n3=30 >real.rsf
bash$ sfin real.rsf
real.rsf:
    in="/var/tmp/real.rsf@"
    esize=4 type=float form=native 
    n1=10          d1=0.004       o1=0          label1="Time" unit1="s" 
    n2=20          d2=0.1         o2=0          label2="Distance" unit2="km" 
    n3=30          d3=0.1         o3=0          label3="Distance" unit3="km" 
        6000 elements 24000 bytes

The output dataset will have type=complex, and its binary will be twice the size of the input:

bash$ <real.rsf sfrtoc >complex.rsf
bash$ sfin complex.rsf 
complex.rsf:
    in="/var/tmp/complex.rsf@"
    esize=8 type=complex form=native 
    n1=10          d1=0.004       o1=0          label1="Time" unit1="s" 
    n2=20          d2=0.1         o2=0          label2="Distance" unit2="km" 
    n3=30          d3=0.1         o3=0          label3="Distance" unit3="km" 
        6000 elements 48000 bytes

sfscale

Scale data.
sfscale < in.rsf > out.rsf axis=0 rscale=0. dscale=1.

To scale by a constant factor, you can also use sfmath or sfheadermath.
int axis=0 Scale by maximum in the dimensions up to this axis.
float dscale=1. Scale by this factor (works if rscale=0)
float rscale=0. Scale by this factor.

sfscale scales the input dataset by a factor. Here are some simple examples. First, let us create a test dataset.

bash$ sfmath n1=5 n2=3 o1=1 o2=1 output="x1*x2" > test.rsf
bash$ < test.rsf sfdisfil   
   0:             1            2            3            4            5
   5:             2            4            6            8           10
  10:             3            6            9           12           15

Scale every data point by 2:

bash$ < test.rsf sfscale dscale=2 | sfdisfil
   0:             2            4            6            8           10
   5:             4            8           12           16           20
  10:             6           12           18           24           30

Divide every trace by its maximum value:

bash$ < test.rsf sfscale axis=1 | sfdisfil
   0:           0.2          0.4          0.6          0.8            1
   5:           0.2          0.4          0.6          0.8            1
  10:           0.2          0.4          0.6          0.8            1

Divide by the maximum value in the whole 2-D dataset:

bash$ < test.rsf sfscale axis=2 | sfdisfil
   0:       0.06667       0.1333          0.2       0.2667       0.3333
   5:        0.1333       0.2667          0.4       0.5333       0.6667
  10:           0.2          0.4          0.6          0.8            1

The rscale= parameter is synonymous to dscale= except when it is equal to zero. With sfscale dscale=0, the dataset gets multiplied by zero. If using rscale=0, the other parameters are used to define scaling. Thus, sfscale rscale=0 axis=1 is equivalent to sfscale axis=1, and sfscale rscale=0 is equivalent to sfscale dscale=1.




sfspike

Generate simple data: spikes, boxes, planes, constants.
sfspike > spike.rsf mag= nsp=1 k#=[0,...] l#=[k1,k2,...] p#=[0,...] n#= o#=[0,0,...] d#=[0.004,0.1,0.1,...] label#=[Time,Distance,Distance,...] unit#=[s,km,km,...] title=

Spike positioning is given in samples and starts with 1.
float d#=[0.004,0.1,0.1,...] sampling on #-th axis
ints k#=[0,...] spike starting position [nsp]
ints l#=[k1,k2,...] spike ending position [nsp]
string label#=[Time,Distance,Distance,...] label on #-th axis
floats mag= spike magnitudes [nsp]
int n#= size of #-th axis
int nsp=1 Number of spikes
float o#=[0,0,...] origin on #-th axis
floats p#=[0,...] spike inclination (in samples) [nsp]
string title= title for plots
string unit#=[s,km,km,...] unit on #-th axis

sfspike takes no input and generates an output with "spikes". It is an easy way to create data. Here is an example:

bash$ sfspike n1=5 n2=3 k1=4 k2=1 | sfdisfil
   0:             0            0            0            1            0
   5:             0            0            0            0            0
  10:             0            0            0            0            0

The spike location is specified by parameters k1=4 and k2=1. Note that the locations are numbered starting from 1. If one of the parameters is omitted or given the value of zero, the spike in the corresponding direction becomes a plane:

bash$ sfspike n1=5 n2=3 k1=4 | sfdisfil   
   0:             0            0            0            1            0
   5:             0            0            0            1            0
  10:             0            0            0            1            0

If no spike parameters are given, the whole dataset is filled with ones:

bash$ sfspike n1=5 n2=3 | sfdisfil
   0:             1            1            1            1            1
   5:             1            1            1            1            1
  10:             1            1            1            1            1

To create several spikes, use the nsp= parameter and give a comma-separated list of values to k#= arguments:

bash$ sfspike n1=5 n2=3 nsp=3 k1=1,3,4 k2=1,2,3 | sfdisfil
   0:             1            0            0            0            0
   5:             0            0            1            0            0
  10:             0            0            0            1            0

If the number of values in the list is smaller than nsp, the last value gets repeated, and the spikes add on top of each other, creating larger amplitudes:

bash$ sfspike n1=5 n2=3 nsp=3 k1=1,3 k2=1,2 | sfdisfil
   0:             1            0            0            0            0
   5:             0            0            2            0            0
  10:             0            0            0            0            0

The magnitude of the spikes can be controlled explicitly with the mag= parameter:

bash$ sfspike n1=5 n2=3 nsp=3 k1=1,3,4 k2=1,2,3 mag=1,4,2 | sfdisfil
   0:             1            0            0            0            0
   5:             0            0            4            0            0
  10:             0            0            0            2            0

You can create boxes instead of spikes by using l#= parameters:

bash$ sfspike n1=5 n2=3 k1=2 l1=4 k2=2 mag=8 | sfdisfil
   0:             0            0            0            0            0
   5:             0            8            8            8            0
  10:             0            0            0            0            0

In this case, k1=2 specifies the box start, and l1=4 specifies the box end. Finally, multi-dimensional planes can be given an inclination by using p#= parameters:

bash$ sfspike n1=5 n2=3 k1=2 p2=1 | sfdisfil
   0:             0            1            0            0            0
   5:             0            0            1            0            0
  10:             0            0            0            1            0

Note that sfspike interprets the p#= parameters in stepout from sample to sample, not in terms of axes units (i.e. s/m).

More than one p parameter can be specified. In this case, a (hyper) plane will be created.

When the inclination value is not integer, simple linear interpolation is used:

bash$ sfspike n1=5 n2=3 k1=2 p2=0.7 | sfdisfil
   0:             0            1            0            0            0
   5:             0          0.3          0.7            0            0
  10:             0            0          0.6          0.4            0

sfspike supplies default dimensions and labels to all axis:

bash$ sfspike n1=5 n2=3 n3=4 > spike.rsf
bash$ sfin spike.rsf
spike.rsf:
    in="/var/tmp/spike.rsf@"
    esize=4 type=float form=native 
    n1=5           d1=0.004       o1=0          label1="Time" unit1="s" 
    n2=3           d2=0.1         o2=0          label2="Distance" unit2="km" 
    n3=4           d3=0.1         o3=0          label3="Distance" unit3="km" 
	60 elements 240 bytes

As you can see, the first axis is assumed to be time, with sampling of 0.004 seconds. All other axes are assumed to be distance, with sampling of 0.1 kilometers. All these parameters can be changed on the command line.

bash$ sfspike n1=5 n2=3 n3=4 label3=Offset unit3=ft d3=20 > spike.rsf
bash$ sfin spike.rsf
spike.rsf:
    in="/var/tmp/spike.rsf@"
    esize=4 type=float form=native 
    n1=5           d1=0.004       o1=0          label1="Time" unit1="s" 
    n2=3           d2=0.1         o2=0          label2="Distance" unit2="km" 
    n3=4           d3=20          o3=0          label3="Offset" unit3="ft" 
	60 elements 240 bytes

sfspray

Extend a dataset by duplicating in the specified axis dimension.
sfspray < in.rsf > out.rsf axis=2 n= d= o= label= unit=
This operation is adjoint to sfstack.
int axis=2 which axis to spray
float d= Sampling of the newly created dimension
string label= Label of the newly created dimension
int n= Size of the newly created dimension
float o= Origin of the newly created dimension
string unit= Units of the newly created dimension

sfspray extends the input hypercube by replicating the data in one of the dimensions. The output dataset acquires one additional dimension. Here is an example: Start with a 2-D dataset

bash$ sfmath n1=5 n2=2 output=x1+x2 > test.rsf
bash$ sfin test.rsf
test.rsf:
    in="/var/tmp/test.rsf@"
    esize=4 type=float form=native 
    n1=5           d1=1           o1=0          
    n2=2           d2=1           o2=0          
        10 elements 40 bytes
bash$ < test.rsf sfdisfil
   0:             0            1            2            3            4
   5:             1            2            3            4            5

Extend the data in the second dimension

bash$ < test.rsf sfspray axis=2 n=3 > test2.rsf
bash$ sfin test2.rsf
test2.rsf:
    in="/var/tmp/test2.rsf@"
    esize=4 type=float form=native 
    n1=5           d1=1           o1=0          
    n2=3           d2=1           o2=0          
    n3=2           d3=1           o3=0          
        30 elements 120 bytes
bash$ < test2.rsf sfdisfil
   0:             0            1            2            3            4
   5:             0            1            2            3            4
  10:             0            1            2            3            4
  15:             1            2            3            4            5
  20:             1            2            3            4            5
  25:             1            2            3            4            5

The output is three-dimensional, with traces from the original data duplicated along the second axis. Extend the data in the third dimension

bash$ < test.rsf sfspray axis=3 n=2 > test3.rsf
bash$ sfin test3.rsf
test3.rsf:
    in="/var/tmp/test3.rsf@"
    esize=4 type=float form=native 
    n1=5           d1=1           o1=0          
    n2=2           d2=1           o2=0          
    n3=2           d3=?           o3=?          
        20 elements 80 bytes
bash$ < test3.rsf sfdisfil
   0:             0            1            2            3            4
   5:             1            2            3            4            5
  10:             0            1            2            3            4
  15:             1            2            3            4            5

The output is also three-dimensional, with the original data replicated along the third axis.

sfstack

Stack a dataset over one of the dimensions.
sfstack < in.rsf > out.rsf axis=2 rms=n norm=y min=n max=n

This operation is adjoint to sfspray.
int axis=2 which axis to stack
bool max=n [y/n] If y, find maximum instead of stack. Ignores rms and norm.
bool min=n [y/n] If y, find minimum instead of stack. Ignores rms and norm.
bool norm=y [y/n] If y, normalize by fold.
bool rms=n [y/n] If y, compute the root-mean-square instead of stack.

While sfspray adds a dimension to a hypercube, sfstack effectively removes one of the dimensions by stacking over it. Here are some examples:

bash$ sfmath n1=5 n2=3 output=x1+x2 > test.rsf
bash$ < test.rsf sfdisfil
   0:             0            1            2            3            4
   5:             1            2            3            4            5
  10:             2            3            4            5            6
bash$ < test.rsf sfstack axis=2 | sfdisfil
   0:           1.5            2            3            4            5
bash$ < test.rsf sfstack axis=1 | sfdisfil
   0:           2.5            3            4

Why is the first value not 1 (in the first case) or 2 (in the second case)? By default, sfstack normalizes the stack by the fold (the number of non-zero entries). To avoid normalization, use norm=n, as follows:

bash$ < test.rsf sfstack norm=n | sfdisfil 
   0:             3            6            9           12           15

sfstack can also compute root-mean-square values as well as minimum and maximum values.

bash$ < test.rsf sfstack rms=y | sfdisfil
   0:         1.581         2.16        3.109        4.082        5.066
bash$ < test.rsf sfstack min=y | sfdisfil
   0:             0            1            2            3            4
bash$ < test.rsf sfstack axis=1 max=y | sfdisfil 
   0:             4            5            6

sftransp

Transpose two axes in a dataset.
sftransp < in.rsf > out.rsf memsize=sf_memsize() plane=

If you get a "Cannot allocate memory" error, give the program a
memsize=1 command-line parameter to force out-of-core operation.
int memsize=sf_memsize() Max amount of RAM (in Mb) to be used
int plane= Two-digit number with axes to transpose. The default is 12

The sftransp program transposes the input hypercube exchanging the two axes specified by the plane= parameter.

bash$ sfspike n1=10 n2=20 n3=30 > orig123.rsf
bash$ sfin orig123.rsf 
orig123.rsf:
    in="/var/tmp/orig123.rsf@"
    esize=4 type=float form=native 
    n1=10          d1=0.004       o1=0          label1="Time" unit1="s" 
    n2=20          d2=0.1         o2=0          label2="Distance" unit2="km" 
    n3=30          d3=0.1         o3=0          label3="Distance" unit3="km" 
        6000 elements 24000 bytes
bash$ <orig123.rsf sftransp plane=23 >out132.rsf
bash$ sfin out132.rsf 
out132.rsf:
    in="/var/tmp/out132.rsf@"
    esize=4 type=float form=native 
    n1=10          d1=0.004       o1=0          label1="Time" unit1="s" 
    n2=30          d2=0.1         o2=0          label2="Distance" unit2="km" 
    n3=20          d3=0.1         o3=0          label3="Distance" unit3="km" 
        6000 elements 24000 bytes
bash$ <orig123.rsf sftransp plane=13 >out321.rsf
bash$ sfin out321.rsf 
out321.rsf:
    in="/var/tmp/out132.rsf@"
    esize=4 type=float form=native 
    n1=30          d1=0.1         o1=0          label1="Distance" unit1="km" 
    n2=20          d2=0.1         o2=0          label2="Distance" unit2="km" 
    n3=10          d3=0.004       o3=0          label3="Time" unit3="s" 
        6000 elements 24000 bytes

sftransp tries to fit the dataset in memory to transpose it there but, if not enough memory is available, it performs a slower transpose out of core using disk operations. You can control the amount of available memory using the memsize= parameter or the RSFMEMSIZE environmental variable.

sfwindow

Window a portion of the dataset.
sfwindow < in.rsf > out.rsf verb=n squeeze=y j#=(1,...) d#=(d1,d2,...) f#=(0,...) min#=(o1,o2,,...) n#=(0,...) max#=(o1+(n1-1)*d1,o2+(n1-1)*d2,,...)
float d#=(d1,d2,...) sampling in #-th dimension
int f#=(0,...) window start in #-th dimension
int j#=(1,...) jump in #-th dimension
float max#=(o1+(n1-1)*d1,o2+(n1-1)*d2,,...) maximum in #-th dimension
float min#=(o1,o2,,...) minimum in #-th dimension
int n#=(0,...) window size in #-th dimension
bool squeeze=y [y/n] if y, squeeze dimensions equal to 1 to the end
bool verb=n [y/n] Verbosity flag


sfwindow is used to window a portion of the dataset. Here is a quick example: Start by creating some data.

bash$ sfmath n1=5 n2=3 o1=1 o2=1 output="x1*x2" > test.rsf
bash$ < test.rsf sfdisfil
   0:             1            2            3            4            5
   5:             2            4            6            8           10
  10:             3            6            9           12           15

Now window the first two rows:

bash$ < test.rsf sfwindow n2=2 | sfdisfil
   0:             1            2            3            4            5
   5:             2            4            6            8           10

Window the first three columns:

bash$ < test.rsf sfwindow n1=3 | sfdisfil
   0:             1            2            3            2            4
   5:             6            3            6            9

Window the middle row:

bash$ < test.rsf sfwindow f2=1 n2=1 | sfdisfil
   0:             2            4            6            8           10

You can interpret the f# and n# parameters as meaning "skip that many rows/columns" and "select that many rows/columns" correspondingly. Window the middle point in the dataset:

bash$ < test.rsf sfwindow f1=2 n1=1 f2=1 n2=1 | sfdisfil
   0:             6

Window every other column:

bash$ < test.rsf sfwindow j1=2 | sfdisfil
   0:             1            3            5            2            6
   5:            10            3            9           15

Window every third column:

bash$ < test.rsf sfwindow j1=3 | sfdisfil
   0:             1            4            2            8            3
   5:            12

Alternatively, sfwindow can use the minimum and maximum parameters to select a window. In the following example, we are creating a dataset with sfspike and then windowing a portion of it between 1 and 2 seconds in time and sampled at 8 miliseconds.

bash$ sfspike n1=1000 n2=10 > spike.rsf         
bash$ sfin spike.rsf
spike.rsf:
    in="/var/tmp/spike.rsf@"
    esize=4 type=float form=native 
    n1=1000        d1=0.004       o1=0          label1="Time" unit1="s" 
    n2=10          d2=0.1         o2=0          label2="Distance" unit2="km" 
        10000 elements 40000 bytes
bash$ < spike.rsf sfwindow min1=1 max1=2 d1=0.008 > window.rsf
bash$ sfin window.rsf
window.rsf:
    in="/var/tmp/window.rsf@"
    esize=4 type=float form=native 
    n1=126         d1=0.008       o1=1          label1="Time" unit1="s" 
    n2=10          d2=0.1         o2=0          label2="Distance" unit2="km" 
        1260 elements 5040 bytes

By default, sfwindow "squeezes" the hypercube dimensions that are equal to one toward the end of the dataset. Here is an example of taking a time slice:

bash$ < spike.rsf sfwindow n1=1 min1=1 > slice.rsf
bash$ sfin slice.rsf 
slice.rsf:
    in="/var/tmp/slice.rsf@"
    esize=4 type=float form=native 
    n1=10          d1=0.1         o1=0          label1="Distance" unit1="km" 
    n2=1           d2=0.004       o2=1          label2="Time" unit2="s" 
        10 elements 40 bytes

You can change this behavior by specifying squeeze=n.

bash$ < spike.rsf sfwindow n1=1 min1=1 squeeze=n > slice.rsf
bash$ sfin slice.rsf 
slice.rsf:
    in="/var/tmp/slice.rsf@"
    esize=4 type=float form=native 
    n1=1           d1=0.004       o1=1          label1="Time" unit1="s" 
    n2=10          d2=0.1         o2=0          label2="Distance" unit2="km" 
        10 elements 40 bytes

Seismic programs

Programs in this category are specific for operations on seismic data. The source files for these programs can be found under system/seismic in the Madagascar distribution.

sffkamo

Computes Azimuth Move-Out (AMO) operator in the f-k log-stretch domain
sffkamo < in.rsf > out.rsf h1= h2= f1= f2= maxe=10.
float f1= input azimuth in degrees
float f2= output azimuth in degrees
float h1= input offset
float h2= output offset
float maxe=10. stability constraint

Sample workflow from SEP-110, 63-70 (2001), with the addition of a bandpass for the input:

Create input -- a (t,x,y) common-offset cube:

sfspike \
n1=128 o1=0.4 d1=0.0032 k1=65 label1=t \
n2=256 o2=-1.536 d2=0.012 k2=129 label2=x \
n3=128 o3=-1.024 d3=0.016 k3=65 label3=y | \
sfbandpass flo=5 fhi=60 > spikebps.rsf

Apply log-stretch FFT:

<spikebps.rsf sfstretch rule=L dens=4 |\
sffft1 |\
sffft3 axis=2 |\
sffft3 axis=3 > spikefft3.rsf

Compute AMO operator for a file of the dimensions of spikefft3.rsf. The only information taken from stdin are the n, o, d parameters:

<spikefft3.rsf sffkamo h2=2 f2=10 h1=1.8 f1=30 >oper.rsf

Apply the operator by multiplication and fft back to (t, mx, my):

< spikefft3.rsf sfadd mode=prod oper.rsf |\
sffft3 axis=3 inv=y |\
sffft3 axis=2 inv=y |\
sffft1 inv=y |\
sfstretch rule=L dens=4 inv=y > spikeamo.rsf

Prepare for 8-bit greyscale visualization:

< spikeamo.rsf sfbyte pclip=100 gainpanel=a > spikebyte.rsf

Picture from the middle of the impulse response:

<spikebyte.rsf sfgrey3 frame1=65 frame2=129 frame3=65 \
point1=0.333 title='AMO saddle, no f-k filter' | sfpen &

Picture illustrating the artifacts (i.e. need for f-k filter):

< spikebyte.rsf sfgrey3 frame1=65 frame2=97 frame3=97 \
point1=0.333 title='No f-k filter' | sfpen &

Apply the f-k filter and (in this case) visualize:

< spikeamo.rsf sffft1 |\
sffft3 axis=2 |\
sffft3 axis=3 |\
sfdipfilter v1=-2.5 v2=-1.5 v3=1.5 v4=2.5 taper=2 pass=0 dim=3 |\
sffft3 axis=3 inv=y |\
sffft3 axis=2 inv=y |\
sffft1 inv=y |\
sfbyte pclip=100 gainpanel=a |\
sfgrey3 frame1=65 frame2=97 frame3=97 point1=0.333 title='With f-k filter' |\
sfpen &

sfheaderattr

Integer header attributes.
sfheaderattr < head.rsf

Only nonzero values are reported.

The sfheaderattr examines the contents of a trace header file, typically generated by sfsegyread. In the example below, we examine trace headers in the output of suplane, a program from Seismic Unix.

bash$ suplane > plane.su
bash$ sfsegyread tape=plane.su su=y tfile=tfile.rsf > plane.rsf
bash$ sfheaderattr < tfile.rsf
*******************************************
71 headers, 32 traces
key[0]="tracl"      min[0]=1            max[31]=32          mean=16.5
key[1]="tracr"      min[0]=1            max[31]=32          mean=16.5
key[11]="offset"    min[0]=400          max[31]=400         mean=400
key[38]="ns"        min[0]=64           max[31]=64          mean=64
key[39]="dt"        min[0]=4000         max[31]=4000        mean=4000
*******************************************

For different standard keywords, a minimum, maximum, and mean values are reported unless they are identically zero. This quick inspection can help in identifying meaningful keywords set in the data. The input data type must be int.

sfheadermath

Mathematical operations, possibly on header keys.
sfheadermath < in.rsf > out.rsf memsize=sf_memsize() output=

Known functions: cos, sin, tan, acos, asin, atan,
cosh, sinh, tanh, acosh, asinh, atanh,
exp, log, sqrt, abs

See also sfmath.

An addition operation can be performed by sfstack.
int memsize=sf_memsize() Max amount of RAM (in Mb) to be used
string output= Describes the output in a mathematical notation.

sfheadermath is a versatile program for mathematical operations on rows of the input file. If the input file is an n1 by n2 matrix, the output will be a 1 by n2 matrix that contains one row made out of mathematical operations on the other rows. sfheadermath can identify a row by number or by a standard SEGY keyword. The latter is useful for processing headers extracted from SEGY or SU files. Here is an example. First, we create an SU file with suplane and convert it to RSF using sfsegyread.

bash$ suplane > plane.su
bash$ sfsegyread tape=plane.su su=y tfile=tfile.rsf > plane.rsf

The trace header information is saved in tfile.rsf. It contains 71 headers for 32 traces in integer format.

bash$ sfin tfile.rsf
tfile.rsf:
    in="/tmp/tfile.rsf@"
    esize=4 type=int form=native
    n1=71          d1=?           o1=?
    n2=32          d2=?           o2=?
        2272 elements 9088 bytes

Next, we will convert tfile.rsf to a floating-point format and run sfheadermath to create a new header.

bash$ < tfile.rsf sfdd type=float | \
sfheadermath myheader=1 output="sqrt(myheader+(2+10*offset^2))" > new.rsf
bash$ sfin new.rsf
new.rsf:
    in="/tmp/new.rsf@"
    esize=4 type=float form=native
    n1=1           d1=?           o1=?
    n2=32          d2=?           o2=?
        32 elements 128 bytes

We defined "myheader" as being the row number 1 in the input (note that numbering starts with 0) and combined it with "offset", which is a standard SEGY keyword that denotes row number 11 (see the output of sfheaderattr above.) A variety of mathematical expressions can be defined in the output= string. The expression processing engine is shared with sfmath.

sfsegyheader

Make a trace header file for segywrite.
sfsegyheader < in.rsf > out.rsf n1= d1=

Use the output for tfile= argument in segywrite.
float d1= trace sampling
int n1= number of samples in a trace

sfsegyread

Convert a SEG-Y or SU dataset to RSF.
sfsegyread mask=msk.rsf > out.rsf tfile=hdr.rsf verb=n su= suxdr=n endian=y format=segyformat (bhead) ns=segyns (bhead) tape= read= hfile= bfile=

Data headers and trace headers are separated from the data.

"suread" is equivalent to "segyread su=y"

SEGY key names:

tracl: trace sequence number within line 0

tracr: trace sequence number within reel 4

fldr: field record number 8

tracf: trace number within field record 12

ep: energy source point number 16

cdp: CDP ensemble number 20

cdpt: trace number within CDP ensemble 24

trid: trace identification code:
1 = seismic data
2 = dead
3 = dummy
4 = time break
5 = uphole
6 = sweep
7 = timing
8 = water break
9---, N = optional use (N = 32,767) 28

nvs: number of vertically summed traces 30

nhs: number of horizontally summed traces 32

duse: data use:
1 = production
2 = test 34

offset: distance from source point to receiver
group (negative if opposite to direction
in which the line was shot) 36

gelev: receiver group elevation from sea level
(above sea level is positive) 40

selev: source elevation from sea level
(above sea level is positive) 44

sdepth: source depth (positive) 48

gdel: datum elevation at receiver group 52

sdel: datum elevation at source 56

swdep: water depth at source 60

gwdep: water depth at receiver group 64

scalel: scale factor for previous 7 entries
with value plus or minus 10 to the
power 0, 1, 2, 3, or 4 (if positive,
multiply, if negative divide) 68

scalco: scale factor for next 4 entries
with value plus or minus 10 to the
power 0, 1, 2, 3, or 4 (if positive,
multiply, if negative divide) 70

sx: X source coordinate 72

sy: Y source coordinate 76

gx: X group coordinate 80

gy: Y group coordinate 84

counit: coordinate units code:
for previous four entries
1 = length (meters or feet)
2 = seconds of arc (in this case, the
X values are unsigned longitude and the Y values
are latitude, a positive value designates
the number of seconds east of Greenwich
or north of the equator 88

wevel: weathering velocity 90

swevel: subweathering velocity 92

sut: uphole time at source 94

gut: uphole time at receiver group 96

sstat: source static correction 98

gstat: group static correction 100

tstat: total static applied 102

laga: lag time A, time in ms between end of 240-
byte trace identification header and time
break, positive if time break occurs after
end of header, time break is defined as
the initiation pulse which maybe recorded
on an auxiliary trace or as otherwise
specified by the recording system 104

lagb: lag time B, time in ms between the time
break and the initiation time of the energy source,
may be positive or negative 106

delrt: delay recording time, time in ms between
initiation time of energy source and time
when recording of data samples begins
(for deep water work if recording does not
start at zero time) 108

muts: mute time--start 110

mute: mute time--end 112

ns: number of samples in this trace 114

dt: sample interval, in micro-seconds 116

gain: gain type of field instruments code:
1 = fixed
2 = binary
3 = floating point
4 ---- N = optional use 118

igc: instrument gain constant 120

igi: instrument early or initial gain 122

corr: correlated:
1 = no
2 = yes 124

sfs: sweep frequency at start 126

sfe: sweep frequency at end 128

slen: sweep length in ms 130

styp: sweep type code:
1 = linear
2 = cos-squared
3 = other 132

stas: sweep trace length at start in ms 134

stae: sweep trace length at end in ms 136

tatyp: taper type: 1=linear, 2=cos^2, 3=other 138

afilf: alias filter frequency if used 140

afils: alias filter slope 142

nofilf: notch filter frequency if used 144

nofils: notch filter slope 146

lcf: low cut frequency if used 148

hcf: high cut frequncy if used 150

lcs: low cut slope 152

hcs: high cut slope 154

year: year data recorded 156

day: day of year 158

hour: hour of day (24 hour clock) 160

minute: minute of hour 162

sec: second of minute 164

timbas: time basis code:
1 = local
2 = GMT
3 = other 166

trwf: trace weighting factor, defined as 1/2^N
volts for the least sigificant bit 168

grnors: geophone group number of roll switch
position one 170

grnofr: geophone group number of trace one within
original field record 172

grnlof: geophone group number of last trace within
original field record 174

gaps: gap size (total number of groups dropped) 176

otrav: overtravel taper code:
1 = down (or behind)
2 = up (or ahead) 178

cdpx: X coordinate of CDP 180

cdpy: Y coordinate of CDP 184

iline: in-line number 188

xline: cross-line number 192

shnum: shotpoint number 196

shsca: shotpoint scalar 200

tval: trace value meas. 202

tconst4: transduction const 204

tconst2: transduction const 208

tunits: transduction units 210

device: device identifier 212

tscalar: time scalar 214

stype: source type 216

sendir: source energy dir. 218

unknown: unknown 222

smeas4: source measurement 224

smeas2: source measurement 228

smeasu: source measurement unit 230

unass1: unassigned 232

unass2: unassigned 236
string bfile= output binary data header file
bool endian=y [y/n] Whether to automatically estimate endianness or not
int format=segyformat (bhead) [1,2,3,5] Data format. The default is taken from binary header.
1 is IBM floating point
2 is 4-byte integer
3 is 2-byte integer
5 is IEEE floating point
string hfile= output text data header file
string mask= optional header mask for reading only selected traces (auxiliary input file name)
int ns=segyns (bhead) Number of samples. The default is taken from binary header
string read= what to read: h - header, d - data, b - both (default)
bool su= [y/n] y if input is SU, n if input is SEGY
bool suxdr=n [y/n] y, SU has XDR support
string tape= input data
string tfile= output trace header file (auxiliary output file name)
bool verb=n [y/n] Verbosity flag

The SEG Y format is an open standard for the exchange of geophysical data. It is controlled by the non-profit SEG Technical Standards Committee. There are two versions of this standard: rev0 (1975)[3] and rev1 (2002)[4]. The implementation in sfsegyread is a mixture of rev0 (i.e. no checks for Extended Textual Headers) and rev1 (IEEE floating point format allowed for trace data samples).

A SEG-Y file as understood by sfsegyread contains a "Reel Identification Header" (3200 bytes in EBCDIC followed by 400 bytes in a binary encoding), followed by a number of "Trace Blocks". Each "Trace Block" contains a 240-byte "Trace Header" (binary) followed by "Trace Data" -- a sequence of ns samples. Binary values in both reel headers and trace headers are two's complement integers, either two bytes or four bytes long. There are no floating-point values defined in the headers. Trace Data samples can have various encodings, either floating point or integer, described further down, but they are all big-endian. To convert from SEG-Y to RSF, sfsegyread will strip the tape reel EBCDIC header and convert it to ASCII, will extract the reel binary header without changing it, and will put the trace headers into one RSF file, and the traces themselves on another.

SEG-Y Trace Headers

In the SEG-Y standard, only the first 180 bytes of the 240-byte trace header are defined; bytes 181-240 are reserved for non-standard header information, and these locations are increasingly used in modern SEG-Y files and its variants. The standard provides for a total of 71 4-byte and 2-byte predefined header words. These 71 standard words have defined lengths and byte offsets, and only these words and byte locations are read using segyread and output to the RSF header file with the tfile= option. The user may remap these predefined keywords to a different byte offsets.

SU File Format

An SU file is nothing more than a SEG-Y file without the reel headers, and with the Trace Data samples in the native encoding of the CPU the file was created on (Attention -- limited portability!). So, to convert from SU to RSF, sfsegyread will just separate headers and traces into two RSF files.

SEG-Y specific parameters

  • hfile= specifies the name of the file in which the EBCDIC reel header will be put after conversion to ASCII. If you are certain there is no useful information in it, hfile=/dev/null works just fine. If you do not specify anything for this parameter you will get an ASCII file named header in the current directory. If you want to quickly preview this header before running sfsegyread, use
    dd if=input.segy count=40 bs=80 cbs=80 conv=unblock,ascii
  • bfile= specifies name of the file in which the binary reel header (the 400-bytes thing following the 3600-bytes EBCDIC) will be put without any conversion. The default name is "binary". Unless you have software that knows how to read exactly this special type of file, it will be completely useless, so do bfile=/dev/null
  • format= specifies the format in which the trace data samples are in the SEG-Y input file. This is read from the binary reel header of the SEG-Y file. Valid values are 1(IBM floating point), 2 (4-byte integer), 3 (2-byte integer) and 5 (IEEE floating point). If the input file is SU, the format will be assumed to be the native float format.
  • keyname= specifies the byte offset to remap a header using the trace header key names shown above. For example, if the CDP locations have been placed in bytes 181-184 instead of the standard 21-24, cdp=180 will remap the trace header to that location.

SU-specific parameters

  • suxdr= specifies whether the input file was created with a SU package with XDR support enabled. If you have access to the source code of your SU install (try $CWPROOT/src), type: grep 'XDRFLAG =' $CWPROOT/src/Makefile.config and look at the last uncommented entry. If no value is given for XDRFLAG, the package was not compiled with XDR support.

Common parameters

  • su= specifies if the input file is SU or SEG-Y. Default is su=n (SEG-Y file).
  • read= specifies what parts of the "Trace Blocks" will be read. It can be read=d (only trace data is read), read=h (only trace headers are read) or read=b (both are read).
  • tfile= gives the name of the RSF file to which trace headers are written. Obviously, it should be only specified with read=h or read=b.
  • mask= is an optional parameter specifying the name of a mask that says which traces will be read. The mask is a 1-D RSF file with integers. The number of samples in the mask is the same as the number of traces in the unmasked SEG-Y. In places corresponding to unwanted traces there should be zeros in the mask.
  • ns= specifies the number of samples in a trace. For SEG-Y files, the default is taken from the binary reel header, and for SU files, from the header of the first trace. This parameter is however critical enough that a command line override was given for it.
  • verbose= is the verbosity flag. Can be y or n.
  • endian= is a y/n flag (default y), specifying whether to automatically estimate or not if samples in the Trace Data blocks are big-endian or little-endian. Try it if you are in trouble and do not know what else to do, otherwise let the automatic estimation do its job.

sfsegywrite

Convert an RSF dataset to SEGY or SU.
sfsegywrite < in.rsf tfile=hdr.rsf verb=false su=false endian=sf_endian() tape= hfile= bfile=

Merges trace headers with data.
string bfile= input binary data header file
bool endian=sf_endian() [y/n] big/little endian flag. The default is estimated automatically
string hfile= input text data header file
bool su=n [y/n] y if output is SU, n if output is SEGY
string tape=
bool verb=n [y/n] Verbosity flag

Please see sfsegyread for a complete description of parameter meanings and background issues. Parameters bfile and hfile should only be given values when the desired file is SEG-Y (default). The output file is specified by the tape= tag.

Generic programs

Programs in this category are general signal and image processing programs. The source files for these programs can be found under system/generic in the Madagascar distribution.

sfnoise

Add random noise to the data.
sfnoise < in.rsf > out.rsf seed=time(NULL) type=y var= range= mean=0 rep=n
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

See the Program of the Month blog entry.

Plotting programs (stable)

The source files for these programs can be found under plot/main in the Madagascar distribution.

sfbox

Draw a balloon-style label.
sfbox lab_color=VP_WHITE lab_fat=0 pscale=1. pointer=y reverse=n lat=0. long=90. angle=0. x0=0. y0=0. scale0=1. xt=2. yt=0. x_oval=0. y_oval=0. boxit=y length= scalet= size=.25 label= > out.vpl
float angle=0. longitude of floating label in 3-D
bool boxit=y [y/n] if y, create a box around text
int lab_color=VP_WHITE label color
int lab_fat=0 label fatness
string label= text for label
float lat=0.
float length= normalization for xt and yt
float long=90. latitude and longitude of viewpoint in 3-D
bool pointer=y [y/n] if y, create arrow pointer
float pscale=1. scale factor for width of pointer
bool reverse=n [y/n]
float scale0=1. scale factor for x0 and y0
float scalet=
float size=.25 text height in inches
float x0=0.
float x_oval=0.
float xt=2.
float y0=0. position of the pointer tip
float y_oval=0. size of the oval around pointer
float yt=0. relative position of text

sfcontour

Contour plot.
sfcontour < in.rsf c= min1=o1 min2=o2 max1=o1+(n1-1)*d1 max2=o2+(n2-1)*d2 nc=50 dc= c0= transp=y minval= maxval= allpos=y barlabel= > plot.vpl
Run "sfdoc stdplot" for more parameters.
bool allpos=y [y/n] contour positive values only
string barlabel=
floats c= [nc]
float c0= first contour
float dc= contour increment
float max1=o1+(n1-1)*d1
float max2=o2+(n2-1)*d2 data window to plot
float maxval= maximum value for scalebar (default is the data maximum)
float min1=o1
float min2=o2
float minval= minimum value for scalebar (default is the data minimum)
int nc=50 number of contours
bool transp=y [y/n] if y, transpose the axes

sfdots

Plot signal with lollipops.
sfdots < in.rsf labels= dots=(n1 <= 130)? 1: 0 seemean=(bool) (n2 <= 30) strings=(bool) (n1 <= 400) connect=1 corners= silk=n gaineach=y labelsz=8 yreverse=n constsep=n seedead=n transp=n xxscale=1. yyscale=1. clip=-1. overlap=0.9 screenratio=VP_SCREEN_RATIO screenht=VP_STANDARD_HEIGHT screenwd=screenhigh / screenratio radius=dd1/3 label1= unit1= title= > plot.vpl
float clip=-1. data clip
int connect=1 connection type: 1 - diagonal, 2 - bar, 4 - only for non-zero data
bool constsep=n [y/n] if y, use constant trace separation
int corners= number of polygon corners (default is 6)
int dots=(n1 <= 130)? 1: 0 type of dots: 1 - baloon, 0 - no dots, 2 - only for non-zero data
bool gaineach=y [y/n] if y, gain each trace independently
string label1=
strings labels= trace labels [n2]
int labelsz=8 label size
float overlap=0.9 trace overlap
float radius=dd1/3 dot radius
float screenht=VP_STANDARD_HEIGHT screen height
float screenratio=VP_SCREEN_RATIO screen aspect ratio
float screenwd=screenhigh / screenratio screen width
bool seedead=n [y/n] if y, show zero traces
bool seemean=(bool) (n2 <= 30) [y/n] if y, draw axis lines
bool silk=n [y/n] if y, silky plot
bool strings=(bool) (n1 <= 400) [y/n] if y, draw strings
string title=
bool transp=n [y/n] if y, transpose the axis
string unit1=
float xxscale=1. x scaling
bool yreverse=n [y/n] if y, reverse y axis
float yyscale=1. y scaling

sfgraph3

Generate 3-D cube plot for surfaces.
sfgraph3 < in.rsf orient=1 min= max= point1=0.5 point2=0.5 frame1=0.5*(min+max) frame2=n1-1 frame3=0 movie=0 dframe=1 n1pix=n1/point1+n3/(1.-point1) n2pix=n2/point2+n3/(1.-point2) flat=y > plot.vpl
float dframe=1 frame increment in a movie
bool flat=y [y/n] if n, display perspective view
float frame1=0.5*(min+max)
int frame2=n1-1
int frame3=0 frame numbers for cube faces
float max= maximum function value
float min= minimum function value
int movie=0 0: no movie, 1: movie over axis 1, 2: axis 2, 3: axis 3
int n1pix=n1/point1+n3/(1.-point1) number of vertical pixels
int n2pix=n2/point2+n3/(1.-point2) number of horizontal pixels
int orient=1 function orientation
float point1=0.5 fraction of the vertical axis for front face
float point2=0.5 fraction of the horizontal axis for front face

sfgraph

Graph plot.
sfgraph < in.rsf symbolsz= pclip=100. transp=n symbol= > plot.vpl
Run "sfdoc stdplot" for more parameters.
float pclip=100. clip percentile
string symbol= if set, plot with symbols instead of lines
floats symbolsz= symbol size (default is 2) [n2]
bool transp=n [y/n] if y, transpose the axes

sfgrey3

Generate 3-D cube plot.
sfgrey3 < in.rsf point1=0.5 point2=0.5 frame1=0 frame2=n2-1 frame3=0 movie=0 dframe=1 n1pix=n1/point1+n3/(1.-point1) n2pix=n2/point2+n3/(1.-point2) flat=y scalebar=n minval= maxval= barreverse=n nreserve=8 bar= color= > plot.vpl
Requires an "unsigned char" input (the output of sfbyte).
string bar= file for scalebar data
bool barreverse=n [y/n] if y, go from small to large on the bar scale
string color= color scheme (default is i)
int dframe=1 frame increment in a movie
bool flat=y [y/n] if n, display perspective view
int frame1=0
int frame2=n2-1
int frame3=0 frame numbers for cube faces
float maxval= maximum value for scalebar (default is the data maximum)
float minval= minimum value for scalebar (default is the data minimum)
int movie=0 0: no movie, 1: movie over axis 1, 2: axis 2, 3: axis 3
int n1pix=n1/point1+n3/(1.-point1) number of vertical pixels
int n2pix=n2/point2+n3/(1.-point2) number of horizontal pixels
int nreserve=8 reserved colors
float point1=0.5 fraction of the vertical axis for front face
float point2=0.5 fraction of the horizontal axis for front face
bool scalebar=n [y/n] if y, draw scalebar

Different color schemes are available for sfgrey and sfgrey3. Examples are in the book at rsf/rsf/sfgrey.

sfgrey

Generate raster plot.
sfgrey < in.rsf > out.rsf bar=bar.rsf transp=y yreverse=y xreverse=n gpow= phalf= clip= pclip= gainstep=0.5+n1/256. allpos=n bias=0. polarity=n verb=n scalebar=n minval= maxval= barreverse=n wantframenum=(bool) (n3 > 1) nreserve=8 gainpanel= bar= color= > (plot.vpl | char.rsf)
Can input char values.
If called "byte", outputs char values.

Run "sfdoc stdplot" for more parameters.
bool allpos=n [y/n] if y, assume positive data
string bar= file for scalebar data
bool barreverse=n [y/n] if y, go from small to large on the bar scale
float bias=0. subtract bias from data
float clip=
string color= color scheme (default is i)
string gainpanel= gain reference: 'a' for all, 'e' for each, or number
int gainstep=0.5+n1/256. subsampling for gpow and clip estimation
float gpow=
float maxval= maximum value for scalebar (default is the data maximum)
float minval= minimum value for scalebar (default is the data minimum)
int nreserve=8 reserved colors
float pclip= data clip percentile (default is 99)
float phalf= percentage for estimating gpow
bool polarity=n [y/n] if y, reverse polarity (white is high by default)
bool scalebar=n [y/n]
bool transp=y [y/n] if y, transpose the display axes
bool verb=n [y/n] verbosity flag
bool wantframenum=(bool) (n3 > 1) [y/n] if y, display third axis position in the corner
bool xreverse=n [y/n] if y, reverse the horizontal axis
bool yreverse=y [y/n] if y, reverse the vertical axis

Different color schemes are available and examples are in the book at rsf/rsf/sfgrey.

sfplas

Plot Assembler - convert ascii to vplot.
sfplas

sfpldb

Plot Debugger - convert vplot to ascii.
sfpldb

sfplotrays

Plot rays.
sfplotrays frame=frame.rsf nt=n1*n2 jr=1 frame= < rays.rsf > plot.vpl
Run "sfdoc stdplot" for more parameters.
string frame=
int jr=1 skip rays
int nt=n1*n2 maximum ray length

sfthplot

Hidden-line surface plot.
sfthplot < in.rsf uflag=y dflag=y alpha=45. titlsz=9 axissz=6 plotfat=0 titlefat=2 axisfat=2 plotcolup=VP_YELLOW plotcoldn=VP_RED axis=y axis1=y axis2=y axis3=y clip=0. pclip=100. gainstep=0.5+nx/256. bias=0. dclip=1. norm=y xc=1.5 zc=3 ratio=5. zmax= zmin= sz=6. label#= unit#= tpow=0 epow=0 gpow=1 title= > plot.vpl
float alpha=45. alpha| < 89
bool axis=y [y/n]
bool axis1=y [y/n]
bool axis2=y [y/n]
bool axis3=y [y/n] plot axis
int axisfat=2 axes fatness
int axissz=6 axes size
float bias=0. subtract bias from data
float clip=0. data clip
float dclip=1. change the clip: clip *= dclip
bool dflag=y [y/n] if y, plot down side of the surface
float epow=0 exponential gain
int gainstep=0.5+nx/256. subsampling for gpow and clip estimation
float gpow=1 power gain
string label#= label on #-th axis
bool norm=y [y/n] normalize by the clip
float pclip=100. data clip percentile
int plotcoldn=VP_RED color of the lower side
int plotcolup=VP_YELLOW color of the upper side
int plotfat=0 line fatness
float ratio=5. plot adjustment
float sz=6. vertical scale
string title=
int titlefat=2 title fatness
int titlsz=9 title size
string tpow=0 time power gain
bool uflag=y [y/n] if y, plot upper side of the surface
string unit#= unit on #-th axis
float xc=1.5
float zc=3 lower left corner of the plot
float zmax=
float zmin=

sfwiggle

Plot data with wiggly traces.
sfwiggle < in.rsf xpos=xpos.rsf xmax= xmin= poly=n fatp=1 xmask=1 ymask=1 pclip=98. zplot=0.75 clip=0. seemean=n verb=n transp=n yreverse=n xreverse=n xpos= > plot.vpl
Run "sfdoc stdplot" for more parameters.
float clip=0. data clip (estimated from pclip by default
int fatp=1
float pclip=98. clip percentile
bool poly=n [y/n]
bool seemean=n [y/n] if y, plot mean lines of traces
bool transp=n [y/n] if y, transpose the axes
bool verb=n [y/n] verbosity flag
int xmask=1
float xmax= maximum trace position (if using xpos)
float xmin= minimum trace position (if using xpos)
string xpos= optional header file with trace positions
bool xreverse=n [y/n] if y, reverse the horizontal axis
int ymask=1
bool yreverse=n [y/n] if y, reverse the vertical axis
float zplot=0.75

Plotting programs (development)

sfplsurf

sfplsurf utilizes PLplot's surface rendering capabilities. Output is dumped to stdout in VPLOT format, so it can easily be used in the same way as sfgrey or other plotting programs. It also supports animation, if n3 > 1 in the input file. A SConstruct usage example can be found below. A movie of the output is available as well.

<syntaxhighlight lang="python"> from rsf.proj import *

  1. x & y dimensions

o1=-2 o2=-2 n1=41 n2=41 d1=0.1 d2=0.1

  1. z dimension

o3=-1 n3=21 d3=0.1

Flow('membrane',None,

   
   math o1=%g o2=%g n1=%d n2=%d d1=%g d2=%g
         o3=%g n3=%d d3=%g
         output="x3*cos(x1*x1+x2*x2)*exp(-0.1*(x1*x1+x2*x2))"
    % (o1,o2,n1,n2,d1,d2,o3,n3,d3))

Result('membrane',

     
     plsurf title="Membrane" mesh=n color=j
             minval=%g maxval=%g
      % (o3,o3 + d3*(n3-1)))

End() </syntaxhighlight>

system/generic programs

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

To give an example of usage, we will create an input for sfremap1 with:

sfmath n1=11 n2=11 d1=1 d2=1 o1=-5 o2=-5 output="x1*x1+x2*x2" > inp2remap1.rsf

Let us interpolate the data across both dimensions, then display it:

< inp2remap1.rsf sfremap1 n1=1001 d1=0.01 | sftransp | \
sfremap1 n1=1001 d1=0.01 | sftransp | sfgrey allpos=y | sfpen

The comparison with the uninterpolated data ( < inp2remap1.rsf sfgrey allpos=y | sfpen ) is quite telling.

system/seismic programs

sfstretch

Stretch of the time axis.
sfstretch < in.rsf > out.rsf datum=dat.rsf inv=n dens=1 v0= half=y delay= tdelay= hdelay= nout=dens*n1 extend=4 mute=0 maxstr=0 rule=
file datum= auxiliary input file name
float delay= time delay for rule=lmo
int dens=1 axis stretching factor
int extend=4 trace extension
bool half=y [y/n] if y, the second axis is half-offset instead of full offset
float hdelay= offset delay for rule=rad
bool inv=n [y/n] if y, do inverse stretching
float maxstr=0 maximum stretch
int mute=0 tapering size
int nout=dens*n1 output axis length (if inv=n)
string rule= Stretch rule:
n - normal moveout (nmostretch), default
l - linear moveout (lmostretch)
L - logarithmic stretch (logstretch)
2 - t^2 stretch (t2stretch)
c - t^2 chebyshev stretch (t2chebstretch)
r - radial moveout (radstretch)
d - datuming (datstretch)
float tdelay= time delay for rule=rad
float v0= moveout velocity

sfstretch rule=d (aka sfdatstretch) can be used to apply statics. Here is a synthetic example, courtesy of Alessandro Frigeri:

# generate a dataset with 'flat' signals
sfmath n1=200 n2=100 output="sin(0.5*x1)" type=float > scan.rsf

# generate a sinusoidal elevation correction
sfmath n1=100 output="3*sin(x1)" type=float > statics.rsf

# apply statics, producing a 'wavy' output.
sfstretch < scan.rsf > out.rsf datum=statics.rsf rule=d

user/fomels programs

sfpick

Automatic picking from semblance-like panels.
sfpick < scn.rsf > pik.rsf vel0=o2 niter=100 an=1. gate=3 smooth=y rect#=(1,1,...) rect1=1 rect2=1 ...
rectN defines the size of the smoothing stencil in N-th dimension.

Theory in Appendix B of:
S. Fomel, 2009,
Velocity analysis using AB semblance: Geophysical Prospecting, v. 57, 311-321.
Reproducible version in RSFSRC/book/jsg/avo
float an=1. axes anisotropy
int gate=3 picking gate
int niter=100 number of iterations
int rect#=(1,1,...) smoothing radius on #-th axis
bool smooth=y [y/n] if apply smoothing
float vel0=o2 surface velocity

Short description of the algorithm:

  1. Start from the top (first time slice), pick an initial (source) point, evaluate all other points with the direct traveltime.
  2. At each grid point at the next level, find the traveltime to points at the previous level, add the traveltimes from the previous level, and select minimum. The search radius is limited by the aperture (gate= parameter in sfpick).
  3. Repeat step 2 until reaching the bottom.
  4. Pick the minimum traveltime at the bottom and track the ray back to the source by following the traveltime gradient direction.
  5. Postprocessing (smooth= parameter in sfpick): smooth the picked ray path using shaping regularization.

The algorithm was discovered and rediscovered by many people. The best reference is probably V. Meshbey, E. Ragoza, D. Kosloff, U. Egozi, and D. Wexler, 2002, Three-dimensional Travel-time Calculation Based on Fermat's Principle: Pure and Applied Geophysics, v. 159, 1563-1582.

user/ivlad programs

sfprep4plot

Resamples a 2-D dataset to the desired picture resolution, with antialias
sfprep4plot inp= out= verb=n h=none w=none unit= ppi= prar=y
Only one of the h and w parameters needs to be specified.
If prar=n, no action will be taken on axis for which h/w was not specified
If prar=y and only one par (h or w) is specified, the picture will scale
along both axes until it is of the specified dimension.
int h=none output height
string inp= input file
string out= output file
int ppi= output resolution (px/in). Necessary when unit!=px
bool prar=y [y/n] if y, PReserve Aspect Ratio of input
string unit= unit of h and w. Can be: px(default), mm, cm, in
bool verb=n [y/n] if y, print system commands, outputs
int w=none output width

For a figure that does not need the aspect ratio preserved, and needs to fill a 1280x1024 projector display:

sfprep4plot inp=file1.rsf out=file2.rsf w=1280 h=1024 prar=n

For a print figure that has to fit in a 6x8in box at a resolution of 250 dpi, preserving the aspect ratio:

sfprep4plot inp=file1.rsf out=file2.rsf w=6 h=8 unit=in ppi=250

A comparison of images before and after the application of sfprep4plot, courtesy of Joachim Mispel, is shown below:

Sf prep4plot.jpg

sfcsv2rsf

Convert a delimited-text ASCII file to RSF binary floating point or int.
sfcsv2rsf help=n delimiter=, dtype=float verb=n debug=n trunc=n o1=0. o2=0. d1=1. d2=1. unit1=unknown unit2=unknown label1=unknown label2=unknown
Zeros will be added if number of elements is not the same in each row.
n1 and n2 are computed automatically. For consistency with sfdisfil and
sfmatmult, output is C-style order (row-first), i.e. rows in input file
become dimension-1 columns in output. Output encoding is native.
float d1=1.
float d2=1.
bool debug=n [y/n] Extra verbosity for debugging
string delimiter=, Separator between values in input file
string dtype=float Input type
bool help=n [y/n]
string label1=unknown
string label2=unknown
float o1=0.
float o2=0.
bool trunc=n [y/n] Truncate or add zeros if nr elems in rows differs
string unit1=unknown
string unit2=unknown
bool verb=n [y/n] Whether to echo n1, n2, infill/truncation

A small usage example follow below. First, create an input file:

$ echo -e '5,6,8,9.2\n11,124,5,0,1' | tee file.csv
5,6,8,9.2
11,124,5,0,1

You may notice that the number of values in each row is different.

Run sfcsv2rsf. Notice that no options are needed. By default, zeros will be appended to make the rows equal length:

$ <file.csv sfcsv2rsf > junk.rsf ; sfdisfil < junk.rsf 
   0:             5            6            8          9.2            0
   5:            11          124            5            0            1

Notice that sfdisfil displays in column order (i.e. matrix is transposed if the number of rows is right). The dimensions of the file are actually transposed on disk:

$ sfin junk.rsf junk.rsf:

   in="/data/path/junk.rsf@"
   esize=4 type=float form=native 
   n1=5           d1=1           o1=0          unit1="unknown" 
   n2=2           d2=1           o2=0          unit2="unknown" 

10 elements 40 bytes </bash>

You may want to run the output through sftransp, depending on your needs. However, if creating an input for sfmatmult, this will not be necessary, because sfmatmult is made to work with matrices that are displayed with sfdisfil, and takes as input a transpose matrix.

Pipes can be used, of course, to skip the creation of intermediary files:

$ <file.csv sfcsv2rsf | sfdisfil
   0:             5            6            8          9.2            0
   5:            11          124            5            0            1

Note that since this program does not need any arguments (just stdin and stdout), when called with no arguments it will not display the man page. In order to consult the automatically generated documentation, you need to pass the option help=y .

user/jennings programs

sfsizes

Display the size of RSF files.
sfsizes files=y human=n file1.rsf file2.rsf ...
Prints the element size, number of elements, and number of bytes
for a list of RSF files. Non-RSF files are ignored.
bool files=y [y/n] If y, print size of each file. If n, print only total.
bool human=n [y/n] If y, print human-readable file size. If n, print byte count.


This program computes the "theoretical" size in bytes of the data fork of RSF files. The actual space occupied on disk may be different and machine dependent due to disk blocking factors, etc. This theoretical array size should be reproducible. It is also fast because the program only reads the RSF headers files, not the actual data.

For example, to get the total size of all RSF files in a directory, in human readable format, without listing each file:

sfsizes files=n human=y *.rsf

This will also work because sfsizes simply skips any non-RSF file:

sfsizes files=n human=y *

sffiglist

Compare Vplot files in Fig and Lock directories
sffiglist figdir= lockdir= list= show=

Parameter figdir is path to Fig directory, default is ./Fig.


Parameter lockdir is path to Lock directory:
If figdir is in $RSFSRC/book/[book]/[chapter]/[section],
then default lockdir is $RSFFIGS/[book]/[chapter]/[section].
If figdir is not in $RSFSRC/book/[book]/[chapter]/[section],
then default lockdir is $RSFALTFIGS/[book]/[chapter]/[section].


Parameter list controls files to list, default is all.
Parameter show controls files to flip with sfpen, default is none.


list|show = none (No files, print only summary.)
list|show = diff (Files that are different, determined by sfvplotdiff.)
list|show = miss (Files missing from figdir or lockdir, and different files.)
list|show = all (All files.)


File list codes:
space indicates files that are the same.
- indicates file in lockdir that is missing from figdir.
+ indicates extra file in figdir that is missing from lockdir.
number is return code from sfvplotdiff indicating different files.

string figdir= fig directory, default = ./Fig
string list= how much to list [none,diff,miss,all], default = all
string lockdir= lock directory, default = lock counterpart of figdir
string show= how much to show [none,diff,miss,all], default = none


This tool lists Vplot files in "Fig" and "Lock" directories and compares them using sfvplotdiff.

The Fig directory defaults to ./Fig and the Lock directory defaults to the corresponding directory where "scons lock" puts things, but either default can be overridden with the user parameters figdir and lockdir so that, for example, files in two different Fig directories can be compared.

The default for the Lock directory has some logic to look in $RSFFIGS when Fig is in $RSFSRC/book, or to look in $RSFALTFIGS when Fig is not in $RSFSRC/book because I like to keep two different Lock directories: one for stuff in book and another for my own stuff that is not in book. However, I tried to make the code default to reasonable things if any of these environment variables are not defined.

The tool gives a summary count of files that are the same, files that are different, files in Fig that are missing from Lock, and files in Lock that are missing from Fig.

The parameters list (default=all) and show (default=none) control which files are listed or "flipped" with sfpen. The file listing indicates which files are the same, which are different, and which are missing from Fig or Lock.

For example, to list all the Vplot files in Fig and Lock:

sffiglist list=all

To list all Vplot files and flip only files that are different:

sffiglist list=all show=diff

user/psava programs

sfawefd2d

acoustic time-domain FD modeling
sfawefd < Fwav.rsf vel=Fvel.rsf sou=Fsou.rsf rec=Frec.rsf wfl=Fwfl.rsf > Fdat.rsf den=Fden.rsf ompchunk=1 ompnth=0 verb=n snap=n free=n expl=n jdata=1 jsnap=nt nq1=sf_n(a1) nq2=sf_n(a2) oq1=sf_o(a1) oq2=sf_o(a2)
file den= auxiliary input file name
bool expl=n [y/n] "exploding reflector"
bool free=n [y/n] free surface flag
int jdata=1
int jsnap=nt save wavefield every *jsnap* time steps
int nq1=sf_n(a1)
int nq2=sf_n(a2)
int ompchunk=1 OpenMP data chunk size
int ompnth=0 OpenMP available threads
float oq1=sf_o(a1)
float oq2=sf_o(a2)
file rec= auxiliary input file name
bool snap=n [y/n] wavefield snapshots flag
file sou= auxiliary input file name
file vel= auxiliary input file name
bool verb=n [y/n] verbosity flag
file wfl= auxiliary output file name

An example will be demonstrated below on a model with nx=nz=200, dx=dz=4m (size: 800x800m). There are two layers: the first one is 100x200 samples in (z,x) and the velocity is 1500m/s; the second layer has the same dimension and the velocity is 3000m/s. Density is set to 1 for the whole grid. A source and a receiver are co-located at x=400 and z=100. The full wavefield for the entire model aperture will be saved every 10th time step.

# Velocity model:
sfspike >Fvel.rsf mag=1500,3000 nsp=2 k1=1,101 l1=100,200 d1=4 d2=4 \
label1=z label2=x n1=200 n2=200 o1=2 o2=2 unit1=m unit2=m
 
# Density model:
sfspike >Fden.rsf mag=1 nsp=1 k1=1 l1=200 d1=4 d2=4 label1=z \
label2=x n1=200 n2=200 o1=2 o2=2 unit1=m unit2=m
 
# Source position (x,z):
sfspike n1=2 nsp=2 k1=1,2 mag=400,100 o1=0 o2=0 >Fsou.rsf
 
# Receiver position (x,z):
sfspike n1=2 nsp=2 k1=1,2 mag=400,100 o1=0 o2=0 >Frec.rsf
 
# Source wavelet:
sfspike nsp=1 n1=2000 d1=0.0005 k1=200 | sfricker1 frequency=20 |\
sftransp >Fwav.rsf
 
# Creating data at specified receiver + saving full wavefield every 10th step:
sfawefd2d <Fwav.rsf vel=Fvel.rsf sou=Fsou.rsf rec=Frec.rsf wfl=Fwfl.rsf \
den=Fden.rsf >Fdat.rsf verb=y free=y expl=y snap=y dabc=y jdata=1 jsnap=10
echo 'label1=z unit1=m label2=x unit2=m' >> Fwfl.rsf
 
# View the wavefield movie:
< Fwfl.rsf sfgrey gainpanel=a pclip=99 color=j scalebar=y | sfpen 
 
# View a wavefield snapshot:
< Fwfl.rsf sfwindow f3=80 n3=1 |\
sfgrey pclip=99 color=j title='snapshot at t=0.4s' |\
sfpen 
 
# View the data recorded at receiver:
<Fdat.rsf sfwindow |\
sfgraph title='Data recorded at receiver' unit2='' label2=amplitude |\
sfpen
sfawefd wavefield screenshot
sfawefd data screenshot

Attention: time steps that are too large can result in numerical instability.

sfsrmig3

3-D S/R migration with extended SSF
sfsrmig3 slo=Fs_s.rsf sls=Fs_r.rsf < Fw_s.rsf rwf=Fw_r.rsf > Fi.rsf cig=Fc.rsf ompchunk=1 ompnth=0 verb=y eps=0.01 twoway=n nrmax=1 dtmax=0.004 pmx=0 pmy=0 tmx=0 tmy=0 vpvs=1. hsym=n nht=1 oht=0 dht=0.1 nht=1 oht=0 dht=0.1 hsym=n nhh=1 ohh=0 dhh=0.1 nha=180 oha=0 dha=2.0 nhb=180 ohb=0 dhb=2.0 itype=
file cig= auxiliary output file name
float dha=2.0
float dhb=2.0
float dhh=0.1
float dht=0.1
float dtmax=0.004 max time error
float eps=0.01 stability parameter
bool hsym=n [y/n]
string itype= imaging condition type
o = zero lag (default)
e = extended
x = space-lags
h = space-lags magnitude
t = time-lag
int nha=180
int nhb=180
int nhh=1
int nht=1
int nrmax=1 max number of refs
float oha=0
float ohb=0
float ohh=0
float oht=0
int ompchunk=1 OpenMP data chunk size
int ompnth=0 OpenMP available threads
int pmx=0 padding on x
int pmy=0 padding on y
file rwf= auxiliary input file name
file slo= auxiliary input file name
string sls= auxiliary input file name
int tmx=0 taper on x
int tmy=0 taper on y
bool twoway=n [y/n] two-way traveltime
bool verb=y [y/n] verbosity flag
float vpvs=1. Vp/Vs ratio

This program performs 3-D and 2-D shot-record (a.k.a. shot-profile) migration with an extended Split-Step Fourier (SSF) extrapolator with multiple reference velocities (hence "extended"). It takes as input a shot wavefield (stdin), receiver wavefield (rwf=) and slowness model (slo=). Outputs are an image (stdout) and a cube of Common Image Gathers (cig=). An important parameter is nrmax, the number of reference velocities. Its default value is 1, but for reasonable results it should be 5 or so. It is also good to specify nonzero taper values (tmx and, for 3-D, tmy as well). The values of padding parameters pmx and pmy are split in two by the program, i.e. if your data x axis is 501-points long, specify pmx=11 to get a value of 512 that will result in fast Fourier Transforms.

The program will also migrate converted-wave data if a file with the S-wave slowness model (sls=) is provided.

The vpvs parameter is only used when itype=h. Do not specify a vpvs value unless you know really well what you are doing.

Usage example

The commands below, slightly modified from RSFSRC/book/data/sigsbee/ptest, show how to prepare the Sigsbee 2A data and velocity for migration.

Convert input data (shots) from SEG-Y to RSF:

sfsegyread tape=sigsbee2a_nfs.segy tfile=tdata.rsf hfile=/dev/null bfile=/dev/null > ddata.rsf

Convert trace headers to float (required by sfheadermath):

< tdata.rsf sfdd type=float > trchdr.rsf

Shot positions:

< trchdr.rsf sfheadermath output="fldr + 10925/150" | sfwindow squeeze=y > tsi.rsf

Extract offset positions from the trace header files, eliminate length-1 axis, scale, create a header for binning (required by sfintbin):

< trchdr.rsf sfheadermath output="offset" |\
sfwindow squeeze=y |\
sfmath output="input/75" |\
sfcat axis=2 space=n tsi.rsf |\
sftransp |\
sfdd type=int > tos.rsf

Binning and muting:

< ddata.rsf sfintbin head=tos.rsf xkey=0 ykey=1 |\
sfput label1=Time unit1=s d2=0.075 o2=0.0 label2=hx d3=0.150 o3=10.925 label3=sx |\
sfmutter half=false t0=1.0 v0=6.0 |\
sfput d2=0.02286 o2=0 unit2=km d3=0.04572 o3=3.32994 unit3=km > shots.rsf

Keeping only 20 shots so that this 1-node job will not take forever, FFT-ing, decimating frequency slices (same as shortening the time axis), and creating y and hy axes of length 1:

< shots.rsf sfwindow n3=20 f3=10 j3=20 |\
sffft1 |\
sfwindow n1=200 min1=1 j1=3 |\
sfspray axis=3 n=1 o=0 d=1 label=hy |\
sfspray axis=5 n=1 o=0 d=1 label=sy > rfft.rsf

The dimensions of the cube thus created are:

$ sfin rfft.rsf trail=n
rfft.rsf:
    in="/var/tmp/rfft.rsf@"
    esize=8 type=complex form=native
    n1=200         d1=0.25        o1=1          label1="Frequency" unit1="Hz"
    n2=348         d2=0.02286     o2=0          label2="hx" unit2="km"
    n3=1           d3=1           o3=0          label3="hy" unit3="km"
    n4=20          d4=0.9144      o4=3.78714    label4="sx" unit4="km"
        1392000 elements 11136000 bytes

Create the source wavelet (limited to the same frequency band as the data) and Fourier transform it:

sfspike k1=1 n1=1500 d1=0.008 |\
sfbandpass flo=15 fhi=25 |\
sffft1 |\
sfwindow n1=200 min1=1 j1=3 |\
sfput label1=freq > sfft.rsf

This creates a frequency-domain wavelet:

$ sfin sfft.rsf
sfft.rsf:
    in="/var/tmp/sfft.rsf@"
    esize=8 type=complex form=native
    n1=200         d1=0.25        o1=1          label1="freq" unit1="Hz"
        200 elements 1600 bytes

Create "synched" source and receiver wavefields with srsyn from wavelet and data frequency slices. Basically both the receiver and shot frequency slices are "placed" at the right location and padded with zeros up to the dimension of the x axis specified below.

< rfft.rsf sfsrsyn nx=1067 dx=0.02286 ox=3.05562 wav=sfft.rsf swf=swav.rsf > rwav.rsf

This creates frequency slices ready for migration for both source and receiver, only axis 1 (frequency) must become axis 3, for both datasets:

< swav.rsf sftransp plane=12 | sftransp plane=23 > stra.rsf
< rwav.rsf sftransp plane=12 | sftransp plane=23 > rtra.rsf

This creates a surface receiver wavefield ready for input to migration. Axis 4 is shot number. The values of axis 4 are arbitrary because each shot has been padded with zeros so that it covers the entire velocity model. Therefore the aperture of the downward continuation for each shot will be as large as the survey.

sfin trail=n rtra.rsf
rtra.rsf:
    in="/var/tmp/rtra.rsf@"
    esize=8 type=complex form=native
    n1=1067        d1=0.02286     o1=3.05562    label1="x" unit1="km"
    n2=1           d2=1           o2=0          label2="y" unit2="km"
    n3=200         d3=0.25        o3=1          label3="w" unit3="Hz"
    n4=20          d4=1           o4=0          label4="e" unit4="km"
        4268000 elements 34144000 bytes

Convert the velocity model from SEG-Y to RSF, decimate, convert from feet to km, transpose, convert to slowness and insert an additional axis:

sfsegyread tape=sigsbee2a_migvel.sgy tfile=/dev/null hfile=/dev/null bfile=/dev/null |\
sfput o1=0 d1=0.00762 label1=z unit1=km o2=3.05562 d2=0.01143 label2=x unit2=km |\
sfwindow j1=4 j2=2 |\
sfscale rscale=0.0003048 |\
sftransp |\
sfmath output="1/input" |\
sfspray axis=2 n=1 d=1 o=0 |\
sfput label2=y > slow.rsf

This creates a slowness file ready for input to migration, with an x axis identical to the x axis of the wavefield files:

$ sfin slow.rsf
slow.rsf:
    in="/var/tmp/slow.rsf@"
    esize=4 type=float form=native
    n1=1067        d1=0.02286     o1=3.05562    label1="x" unit1="km"
    n2=1           d2=1           o2=0          label2="y" unit2="km"
    n3=301         d3=0.03048     o3=0          label3="z" unit3="km"
        321167 elements 1284668 bytes

Finally, the migration command (for a 4-processor machine, hence the ompnth value). We choose not to compute any image gathers (itype=o), but due to the construction of the program we still have to explicitly assign the cig tag, or else a RSF file with the name of the tag and no rsf extension will be created:

< stra.rsf sfsrmig3 nrmax=20 dtmax=5e-05 eps=0.01 verb=y ompnth=4 \
tmx=16 rwf=rtra.rsf slo=slow.rsf itype=o cig=/dev/null > img.rsf

The migration of 20 shots takes approximately 3 hours on a 4-processor machine (1 shot=9 minutes). Without the frequency slice decimation by a factor of 3 and the depth axis decimation by a factor of 4, it would have taken twelve times as much. The resulting image has a y axis of length 1:

$ sfin img.rsf trail=n
img.rsf:
    in="/var/tmp/img.rsf@"
    esize=4 type=float form=native
    n1=1067        d1=0.02286     o1=3.05562    label1="x" unit1="km"
    n2=1           d2=1           o2=0          label2="y" unit2="km"
    n3=301         d3=0.03048     o3=0          label3="z" unit3="km"
        321167 elements 1284668 bytes

To properly visualize the image, we need to eliminate the axis of length 1, then transpose the x and z axes to their natural position:

<img.rsf sfwindow squeeze=y | sftransp | sfgrey > img.vpl

References

  1. Claerbout, J., 1998, Multidimensional recursive filters via a helix: Geophysics, 63, 1532--1541.
  2. Claerbout, J., 1998, Multidimensional recursive filters via a helix: Geophysics, 63, 1532--1541.
  3. Barry, K.M., Cavers, D.A., and Kneale, C.W. 1975. Recommended standards for digital tape formats. Geophysics, 40, no. 02, 344–352.
  4. Norris, M.W., Faichney, A.K., Eds. 2001. SEG Y rev1 Data Exchange format. Society of Exploration Geophysicists, Tulsa, OK, 45 pp.