Guide to madagascar programs
This guide introduces some of the most used madagascar programs and illustrates their usage with examples.
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: user/main/add.c
The first input file is either in the list or in the standard input. <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;
}
</c>
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. <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*/
</c>
A helper function check_compat checks the compatibility of input files. <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); }
}
} </c>
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. <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; </c>
The data combination program for floating point numbers is add_float. <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; }
}
} </c>
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'
|
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 for , then the RMS
value is , the mean
value is , the -norm value
is , the variance is
, 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.
Implementation: user/main/attr.c
Computations start by finding the input data (in) size (nsiz) and dimensions (dim). <c>
dim = (size_t) sf_filedims (in,n); for (nsiz=1, i=0; i < dim; i++) {
nsiz *= n[i];
}
</c>
In the main loop, we read the input data buffer by buffer.
<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; } </c>
The data attributes are accumulated in corresponding double-precision
variables.
<c>
fsum += f;
fsqr += f*f;
</c>
Finally, the attributes are reduced and printed out.
<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);
</c>
<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); </c>
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.
|
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: user/main/cat.c
The first input file is either in the list or in the standard input. <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;
}
</c>
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. <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");
</c>
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. <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; }
}
</c>
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. <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];
}
</c>
In the output, the selected axis will get extended. <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);
</c>
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. <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); } }
}
</c>
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: user/main/cmplx.c
The program flow is simple. First, get the names of the input files. <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");
}
</c>
The main part of the program reads the real and imaginary parts buffer by buffer and assembles and writes out the complex input. <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);
}
</c>
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
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 that minimizes the least-square misfit
for the given input data vector .
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.
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
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.
| |
string | format= | Format for numbers (printf-style).
| |
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=" 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 and its adjoint
. The sfdottest program is testing the equality
by using random vectors and . 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. 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 inv=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.
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.
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@
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 type= unit= output= | |||
Known functions: cos, sin, tan, acos, asin, atan, cosh, sinh, tanh, acosh, asinh, atanh, exp, log, sqrt, abs, conj (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 See also: sfheadermath. | |||
string | output= | Mathematical description of the output | |
string | type= | output data type [float,complex] | |
string | unit= |
sfmath is a versatile program for mathematical operations with RSF files. It can operate with several input file, 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 | xtpen
The first line creates a 2-D dataset that consists of 40 traces 600 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 xtpen. The plot appearing on your screen should look similar to the figure.
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.
sfpad
Pad a dataset with zeros. | |||
---|---|---|---|
sfpad < in.rsf > out.rsf [beg1= beg2= ... end1= end2=... | n1= n2 = ... | n1out= n2out= ...] | |||
begN specifies the number of zeros to add before the beginning of axis N. endN specifies the number of zeros to add after the end of axis N. Alternatively: nN or nNout specify the output length of axis N, padding occurs at the end. nN and nNout are equivalent. |
pad 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 |
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 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 regular RSF 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;
| |
bool | verb=n | [y/n] | Verbosity flag |
int | which=-1 | Which axis to reverse.
|
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).
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.
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.
sfspike
Generate simple data: spikes, boxes, planes, constants. | |||
---|---|---|---|
sfspike > spike.rsf mag= nsp=1 k#=[0,...] l#=[k1,k2,...] p#=[0,...] n#= o#=(0,...) d#=(0.004,0.1,0.1,...) label#=(Time,Distance,Distance,...) unit#=[s,km,km,...] title= | |||
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#= | dimension of #-th axis | |
int | nsp=1 | Number of spikes | |
float | o#=(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 |
This is the program for creating a RSF hypercube out of nothing. Calling sfspike without specifying the k# or l# parameters will result in a volume filled with values specified by mag. To get a file full of 1's, just give sfspike the axis values that running sfin on your desired output would produce. I.e. if you run
sfspike n1=10 d1=0.004 o1=0 label1="Time" unit1="s" n2=30 d2=0.1 o2=0 label2="Distance" unit2="km" > out.rsf
you will obtain the following file:
bash$ sfin out.rsf out.rsf: in="/var/tmp/out.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" 300 elements 1200 bytes
To create a "flat reflector" in the file above, run
sfspike n1=10 d1=0.004 o1=0 label1="Time" unit1="s" n2=30 d2=0.1 o2=0 label2="Distance" unit2="km" k1=4 k2=3 l2=28 mag=0.5> out2.rsf
Notice that the values for k and l are in samples, not in the physical units of the respective axes. The result can be visualised with
< out2.rsf sfgrey pclip=100 wantscalebar=y title="Illustration of k,l parameters" | xtpen
which produces the following plot:
The p parameters can be used to create slanted lines/planes. Specifying p2=1 means that for each lateral step, the spike will be shifted down with 1 sample. Below is the command and the corresponding graphical output it creates:
sfspike n1=10 d1=0.004 o1=0 label1="Time" unit1="s" n2=30 d2=0.1 o2=0 label2="Distance" unit2="km" k1=4 k2=3 l2=28 mag=0.5 p2=1 |\ sfgrey pclip=100 wantscalebar=y title="Effect of p2=1" | xtpen
Sfspike also supports negative and non-integer p values:
sfspike n1=10 d1=0.004 o1=0 label1="Time" unit1="s" n2=30 d2=0.1 o2=0 label2="Distance" unit2="km" k1=4 k2=3 l2=28 mag=0.5 p2=-0.15 |\ sfgrey pclip=100 wantscalebar=y allpos=y color=h title="Effect of p2=-0.15" |xtpen
When nsp is greater than the number of values for k and l parameters, the extra spikes will be piled on top of the last one, increasing its amplitude. Look at the amplitude of the last event in
sfspike n1=240 n2=192 nsp=3 k1=80,160,240 k2=0 p2=-1.25 l2=128| sfgrey pclip=100 | xtpen
and in
sfspike n1=240 n2=192 nsp=5 k1=80,160,240 k2=0 p2=-1.25 l2=128| sfgrey pclip=100 | xtpen
(pictures coming soon). This feature can easily cause a bug when the number of events is large and they have not been properly counted, or when a new spike was added on a list but nsp was not updated.
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.
sfheadermath
Mathematical operations, possibly on header keys. | |||
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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. | |||
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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=false su=false format=sf_segyformat (bhead) ns=sf_segyns (bhead) endian= tape= read= hfile= bfile= mask= tfile= | |||
Data headers and trace headers are separated from the data. Defined SEG-Y trace header key names and byte offsets: 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 previoius four entries 1 = length (meters or feet) 2 = seconds of arc (in this case, the X values are unsigned intitude 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) | |||
string | bfile= | output binary data header file | |
bool | endian= | [y/n] | big/little endian flag, the default is estimated automatically |
int | format=sf_segyformat (bhead) | [1,2,3,5] | Data format. The default is taken from binary header.
|
string | hfile= | output text data header file | |
string | mask= | optional header mask for reading only selected traces | |
int | ns=sf_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=n | [y/n] | y if input is SU, n if input is SEGY |
bool | suxdr=n | [y/n] | y, SU has XDR support |
string | tape= | ||
string | tfile= | output trace header file | |
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 hfile= 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).
- tape= specifies the input data. Stdin could not be used because sfsegyread has to work with tapes, and needs to fseek back and forth through the input file. Thankfully, output is on stdout.
- read= specifies what parts of the "Trace Blocks" will be read. It can be read=t (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.
Plotting programs
The source files for these programs can be found under plot/main in the Madagascar distribution.
THIS SECTION IS UNDER CONSTRUCTION
sfbox
Draw a balloon-style label. | |||
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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. | |||
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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. | |||
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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 | |
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. | |||
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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. | |||
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sfplas |
sfpldb
Plot Debugger - convert vplot to ascii. | |||
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sfpldb |
sfplotrays
Plot rays. | |||
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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. | |||
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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. | |||
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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 |
filt/imag 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 | xtpen
The comparison with the uninterpolated data ( < inp2remap1.rsf sfgrey allpos=y | xtpen ) is quite telling.
filt/proc 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:
| |
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/ivlad programs
sfprep4plot
Resamples a 2-D dataset to the desired picture resolution, with antialias | |||
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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:
References
- ↑ Claerbout, J., 1998, Multidimensional recursive filters via a helix: Geophysics, 63, 1532--1541.
- ↑ Claerbout, J., 1998, Multidimensional recursive filters via a helix: Geophysics, 63, 1532--1541.
- ↑ Barry, K.M., Cavers, D.A., and Kneale, C.W. 1975. Recommended standards for digital tape formats. Geophysics, 40, no. 02, 344–352.
- ↑ Norris, M.W., Faichney, A.K., Eds. 2001. SEG Y rev1 Data Exchange format. Society of Exploration Geophysicists, Tulsa, OK, 45 pp.