Last edit: 05-09-15 Graham Wideman
| Last edit: 05-09-15 Graham Wideman |
Brain |
| AFNI -- All Helps on One Page Article created: 2003-01-20 |
The NIMH AFNI home site provides a listing of the results of the -help option for all approx 230 AFNI programs, which is an excellent service. I wanted them all on one page for quick browsing, searching en masse etc, which is what is assembled here.
Special Request: If you anticipate using this page frequently, please save me some bandwidth, and yourself some time, by saving the page on your local computer. (File > Save As or similar).
| Topic | Discussion |
| Version | See bottom line of each help output where "auto-generated" date indicates date that this info was produced by the AFNI team. Note that I do not recreate this page frequently. |
| Listing Order | The listing order is alphabetical, ignoring case, and ignoring initial "@" character on some AFNI commands/scripts. |
| Improved handling of brackets | In a few cases this listing is slightly improved over the AFNI site: some AFNI programs emit help with angle brackets (greater-than/less-than ) as part of their "Usage" line. Where these should appear in the web version of AFNI documentation, these fool browsers into reading the brackets and enclosed text as unknown HTML tags, causing the browser not to show that text (eg: as in SUMA_AlignToExperiment <EXPERIMENT Anatomy> <SURFACE Anatomy> ). The listing below handles this problem by translating these brackets to their "character entity" form. |
| 1dcat |
Usage: 1dcat a.1D b.1D ...
where each file a.1D, b.1D, etc. is an ASCII file of numbers
arranged in rows and columns.
The row-by-row catenation of these files is written to stdout.
TIMESERIES (1D) INPUT
---------------------
A timeseries file is in the form of a 1D or 2D table of ASCII numbers;
for example: 3 5 7
2 4 6
0 3 3
7 2 9
This example has 3 rows and 4 columns. Each column is considered as
a timeseries in AFNI. The convention is to store this type of data
in a filename ending in '.1D'.
When specifying a timeseries file to an command-line AFNI program, you
can select a subset of columns using the '[...]' notation:
'fred.1D[5]' ==> use only column #5
'fred.1D[5,9,17]' ==> use columns #5, #9, and #12
'fred.1D[5..8]' ==> use columns #5, #6, #7, and #8
'fred.1D[5..13(2)]' ==> use columns #5, #7, #9, #11, and #13
Sub-brick indexes start at 0. You can use the character '$'
to indicate the last sub-brick in a dataset; for example, you
can select every third sub-brick by using the selection list
'fred.1D[0..$(3)]' ==> use columns #0, #3, #6, #9, ....
Similarly, you select a subset of the rows using the '{...}' notation:
'fred.1D{0..$(2)}' ==> use rows #0, #2, #4, ....
You can also use both notations together, as in
'fred.1D[1,3]{1..$(2)}' ==> columns #1 and #3; rows #1, #3, #5, ....
You can also input a 1D time series 'dataset' directly on the command
line, without an external file. The 'filename' for such input has the
general format
'1D:n_1@val_1,n_2@val_2,n_3@val_3,...'
where each 'n_i' is an integer and each 'val_i' is a float. For
example
-a '1D:5@0,10@1,5@0,10@1,5@0'
specifies that variable 'a' be assigned to a 1D time series of 35,
alternating in blocks between values 0 and value 1.
This page auto-generated on Thu Aug 25 16:49:35 EDT 2005
|
| 1ddot |
Usage: 1ddot [options] 1Dfile 1Dfile ... - Prints out correlation matrix of the 1D files and their inverse correlation matrix. - Output appears on stdout. Options: -one = Make 1st vector be all 1's.This page auto-generated on Thu Aug 25 16:49:35 EDT 2005 |
| 1deval |
Usage: 1deval [options] -expr 'expression'
Evaluates the expression and writes the result to stdout.
Any single letter from a-z can be used as the independent
variable in the expression.
Options:
-del d = Use 'd' as the step for the variable in the
expression [default = 1.0]
-num n = Evaluate the expression 'n' times.
If -num is not used, then the length of an
input time series is used. If there are no
time series input, then -num is required.
-a q.1D = Read time series file q.1D and assign it
to the symbol 'a' (as in 3dcalc).
-index i.1D = Read index column from file i.1D and
write it out as 1st column of output.
This option is useful when working with
surface data.
Examples:
1deval -expr 'sin(2*PI*t)' -del 0.01 -num 101 > sin.1D
1deval -expr 'a*b*x' -a fred.1D -b ethel.1D > x.1D
TIMESERIES (1D) INPUT
---------------------
A timeseries file is in the form of a 1D or 2D table of ASCII numbers;
for example: 3 5 7
2 4 6
0 3 3
7 2 9
This example has 3 rows and 4 columns. Each column is considered as
a timeseries in AFNI. The convention is to store this type of data
in a filename ending in '.1D'.
When specifying a timeseries file to an command-line AFNI program, you
can select a subset of columns using the '[...]' notation:
'fred.1D[5]' ==> use only column #5
'fred.1D[5,9,17]' ==> use columns #5, #9, and #12
'fred.1D[5..8]' ==> use columns #5, #6, #7, and #8
'fred.1D[5..13(2)]' ==> use columns #5, #7, #9, #11, and #13
Sub-brick indexes start at 0. You can use the character '$'
to indicate the last sub-brick in a dataset; for example, you
can select every third sub-brick by using the selection list
'fred.1D[0..$(3)]' ==> use columns #0, #3, #6, #9, ....
Similarly, you select a subset of the rows using the '{...}' notation:
'fred.1D{0..$(2)}' ==> use rows #0, #2, #4, ....
You can also use both notations together, as in
'fred.1D[1,3]{1..$(2)}' ==> columns #1 and #3; rows #1, #3, #5, ....
You can also input a 1D time series 'dataset' directly on the command
line, without an external file. The 'filename' for such input has the
general format
'1D:n_1@val_1,n_2@val_2,n_3@val_3,...'
where each 'n_i' is an integer and each 'val_i' is a float. For
example
-a '1D:5@0,10@1,5@0,10@1,5@0'
specifies that variable 'a' be assigned to a 1D time series of 35,
alternating in blocks between values 0 and value 1.
This page auto-generated on Thu Aug 25 16:49:35 EDT 2005
|
| 1dfft |
Usage: 1dfft [options] infile outfile
where infile is an AFNI *.1D file (ASCII list of numbers arranged
in columns); outfile will be a similar file, with the absolute
value of the FFT of the input columns. The length of the file
will be 1+(FFT length)/2.
Options:
-ignore sss = Skip the first 'sss' lines in the input file.
[default = no skipping]
-use uuu = Use only 'uuu' lines of the input file.
[default = use them all, Frank]
-nfft nnn = Set FFT length to 'nnn'.
[default = length of data (# of lines used)]
-tocx = Save Re and Im parts of transform in 2 columns.
-fromcx = Convert 2 column complex input into 1 column
real output.
-hilbert = When -fromcx is used, the inverse FFT will
do the Hilbert transform instead.
-nodetrend = Skip the detrending of the input.
Nota Bene:
* Each input time series has any quadratic trend of the
form 'a+b*t+c*t*t' removed before the FFT, where 't'
is the line number.
* The FFT length will be a power-of-2 times at most one
factor of 3 and one factor of 5. The smallest such
length >= to the specified FFT length will be used.
* If the FFT length is longer than the file length, the
data is zero-padded to make up the difference.
* Do NOT call the output of this program the Power Spectrum!
That is something else entirely.
* If 'outfile' is '-', the output appears on stdout.
This page auto-generated on Thu Aug 25 16:49:35 EDT 2005
|
| 1dgrayplot |
Usage: 1dgrayplot [options] tsfile
Graphs the columns of a *.1D type time series file to the screen,
sort of like 1dplot, but in grayscale.
Options:
-install = Install a new X11 colormap (for X11 PseudoColor)
-ignore nn = Skip first 'nn' rows in the input file
[default = 0]
-flip = Plot x and y axes interchanged.
[default: data columns plotted DOWN the screen]
-sep = Separate scales for each column.
-use mm = Plot 'mm' points
[default: all of them]
-ps = Don't draw plot in a window; instead, write it
to stdout in PostScript format.
N.B.: If you view this result in 'gv', you should
turn 'anti-alias' off, and switch to
landscape mode.
TIMESERIES (1D) INPUT
---------------------
A timeseries file is in the form of a 1D or 2D table of ASCII numbers;
for example: 3 5 7
2 4 6
0 3 3
7 2 9
This example has 3 rows and 4 columns. Each column is considered as
a timeseries in AFNI. The convention is to store this type of data
in a filename ending in '.1D'.
When specifying a timeseries file to an command-line AFNI program, you
can select a subset of columns using the '[...]' notation:
'fred.1D[5]' ==> use only column #5
'fred.1D[5,9,17]' ==> use columns #5, #9, and #12
'fred.1D[5..8]' ==> use columns #5, #6, #7, and #8
'fred.1D[5..13(2)]' ==> use columns #5, #7, #9, #11, and #13
Sub-brick indexes start at 0. You can use the character '$'
to indicate the last sub-brick in a dataset; for example, you
can select every third sub-brick by using the selection list
'fred.1D[0..$(3)]' ==> use columns #0, #3, #6, #9, ....
Similarly, you select a subset of the rows using the '{...}' notation:
'fred.1D{0..$(2)}' ==> use rows #0, #2, #4, ....
You can also use both notations together, as in
'fred.1D[1,3]{1..$(2)}' ==> columns #1 and #3; rows #1, #3, #5, ....
You can also input a 1D time series 'dataset' directly on the command
line, without an external file. The 'filename' for such input has the
general format
'1D:n_1@val_1,n_2@val_2,n_3@val_3,...'
where each 'n_i' is an integer and each 'val_i' is a float. For
example
-a '1D:5@0,10@1,5@0,10@1,5@0'
specifies that variable 'a' be assigned to a 1D time series of 35,
alternating in blocks between values 0 and value 1.
This page auto-generated on Thu Aug 25 16:49:35 EDT 2005
|
| 1dnorm |
Usage: 1dnorm infile outfile where infile is an AFNI *.1D file (ASCII list of numbers arranged in columns); outfile will be a similar file, with each column being L2 normalized.This page auto-generated on Thu Aug 25 16:49:35 EDT 2005 |
| 1dplot |
Usage: 1dplot [options] tsfile ...
Graphs the columns of a *.1D type time series file to the screen.
Options:
-install = Install a new X11 colormap.
-sep = Plot each column in a separate sub-graph.
-one = Plot all columns together in one big graph.
[default = -sep]
-dx xx = Spacing between points on the x-axis is 'xx'
[default = 1]
-xzero zz = Initial x coordinate is 'zz' [default = 0]
-nopush = Don't 'push' axes ranges outwards.
-ignore nn = Skip first 'nn' rows in the input file
[default = 0]
-use mm = Plot 'mm' points [default = all of them]
-xlabel aa = Put string 'aa' below the x-axis
[default = no axis label]
-ylabel aa = Put string 'aa' to the left of the y-axis
[default = no axis label]
-stdin = Don't read from tsfile; instead, read from
stdin and plot it. You cannot combine input
from stdin and tsfile(s). If you want to do
so, see program 1dcat.
-ps = Don't draw plot in a window; instead, write it
to stdout in PostScript format.
N.B.: If you view this result in 'gv', you should
turn 'anti-alias' off, and switch to
landscape mode.
-xaxis b:t:n:m = Set the x-axis to run from value 'b' to
value 't', with 'n' major divisions and
'm' minor tic marks per major division.
For example:
-xaxis 0:100:5:20
Setting 'n' to 0 means no tic marks or labels.
-yaxis b:t:n:m = Similar to above, for the y-axis. These
options override the normal autoscaling
of their respective axes.
-ynames aa bb ... = Use the strings 'aa', 'bb', etc., as
labels to the right of the graphs,
corresponding to each input column.
These strings CANNOT start with the
'-' character.
-volreg = Makes the 'ynames' be the same as the
6 labels used in plug_volreg for
Roll, Pitch, Yaw, I-S, R-L, and A-P
movements, in that order.
You may also select a subset of columns to display using
a tsfile specification like 'fred.1D[0,3,5]', indicating
that columns #0, #3, and #5 will be the only ones plotted.
For more details on this selection scheme, see the output
of '3dcalc -help'.
Example: graphing a 'dfile' output by 3dvolreg, when TR=5:
1dplot -volreg -dx 5 -xlabel Time 'dfile[1..6]'
You can also input more than one tsfile, in which case the files
will all be plotted. However, if the files have different column
lengths, the shortest one will rule.
The colors for the line graphs cycle between black, red, green, and
blue. You can alter these colors by setting Unix environment
variables of the form AFNI_1DPLOT_COLOR_xx -- cf. README.environment.
You can alter the thickness of the lines by setting the variable
AFNI_1DPLOT_THIK to a value between 0.00 and 0.05 -- the units are
fractions of the page size.
TIMESERIES (1D) INPUT
---------------------
A timeseries file is in the form of a 1D or 2D table of ASCII numbers;
for example: 3 5 7
2 4 6
0 3 3
7 2 9
This example has 3 rows and 4 columns. Each column is considered as
a timeseries in AFNI. The convention is to store this type of data
in a filename ending in '.1D'.
When specifying a timeseries file to an command-line AFNI program, you
can select a subset of columns using the '[...]' notation:
'fred.1D[5]' ==> use only column #5
'fred.1D[5,9,17]' ==> use columns #5, #9, and #12
'fred.1D[5..8]' ==> use columns #5, #6, #7, and #8
'fred.1D[5..13(2)]' ==> use columns #5, #7, #9, #11, and #13
Sub-brick indexes start at 0. You can use the character '$'
to indicate the last sub-brick in a dataset; for example, you
can select every third sub-brick by using the selection list
'fred.1D[0..$(3)]' ==> use columns #0, #3, #6, #9, ....
Similarly, you select a subset of the rows using the '{...}' notation:
'fred.1D{0..$(2)}' ==> use rows #0, #2, #4, ....
You can also use both notations together, as in
'fred.1D[1,3]{1..$(2)}' ==> columns #1 and #3; rows #1, #3, #5, ....
You can also input a 1D time series 'dataset' directly on the command
line, without an external file. The 'filename' for such input has the
general format
'1D:n_1@val_1,n_2@val_2,n_3@val_3,...'
where each 'n_i' is an integer and each 'val_i' is a float. For
example
-a '1D:5@0,10@1,5@0,10@1,5@0'
specifies that variable 'a' be assigned to a 1D time series of 35,
alternating in blocks between values 0 and value 1.
This page auto-generated on Thu Aug 25 16:49:35 EDT 2005
|
| 1dsum |
Usage: 1dsum [options] a.1D b.1D ... where each file a.1D, b.1D, etc. is an ASCII file of numbers arranged in rows and columns. The sum of each column is written to stdout. Options: -ignore nn = skip the first nn rows of each file -use mm = use only mm rows from each fileThis page auto-generated on Thu Aug 25 16:49:35 EDT 2005 |
| 1dsvd |
Usage: 1dsvd [options] 1Dfile 1Dfile ...
- Computes SVD of the matrix formed by the 1D file(s).
- Output appears on stdout; to save it, use '>' redirection.
Options:
-one = Make 1st vector be all 1's.
-cond = Only print condition number (ratio of extremes)
-sing = Only print singular values
-1Dright = Only output right eigenvectors, in a .1D format
This can be useful for reducing the number of
columns in a design matrix. The singular values
are printed at the top of each vector column.
This page auto-generated on Thu Aug 25 16:49:35 EDT 2005
|
| 1dtranspose |
Usage: 1dtranspose infile outfile where infile is an AFNI *.1D file (ASCII list of numbers arranged in columns); outfile will be a similar file, but transposed. You can use a column subvector selector list on infile, as in 1dtranspose 'fred.1D[0,3,7]' ethel.1D * This program may produce files with lines longer than a text editor can handle. * If 'outfile' is '-' (or missing entirely), output goes to stdout.This page auto-generated on Thu Aug 25 16:49:35 EDT 2005 |
| 24swap |
Usage: 24swap [options] file ...
Swaps bytes pairs and/or quadruples on the files listed.
Options:
-q Operate quietly
-pattern pat 'pat' determines the pattern of 2 and 4
byte swaps. Each element is of the form
2xN or 4xN, where N is the number of
bytes to swap as pairs (for 2x) or
as quadruples (for 4x). For 2x, N must
be divisible by 2; for 4x, N must be
divisible by 4. The whole pattern is
made up of elements separated by colons,
as in '-pattern 4x39984:2x0'. If bytes
are left over after the pattern is used
up, the pattern starts over. However,
if a byte count N is zero, as in the
example below, then it means to continue
until the end of file.
N.B.: You can also use 1xN as a pattern, indicating to
skip N bytes without any swapping.
N.B.: A default pattern can be stored in the Unix
environment variable AFNI_24SWAP_PATTERN.
If no -pattern option is given, the default
will be used. If there is no default, then
nothing will be done.
N.B.: If there are bytes 'left over' at the end of the file,
they are written out unswapped. This will happen
if the file is an odd number of bytes long.
N.B.: If you just want to swap pairs, see program 2swap.
For quadruples only, see program 4swap.
N.B.: This program will overwrite the input file!
You might want to test it first.
Example: 24swap -pat 4x8:2x0 fred
If fred contains 'abcdabcdabcdabcdabcd' on input,
then fred has 'dcbadcbabadcbadcbadc' on output.
This page auto-generated on Thu Aug 25 16:49:35 EDT 2005
|
| 2dImReg |
Program: 2dImReg
Initial Release: 04 Feb 1998
Latest Revision: 02 Dec 2002
This program performs 2d image registration. Image alignment is
performed on a slice-by-slice basis for the input 3d+time dataset,
relative to a user specified base image.
Usage:
2dImReg
-input fname Filename of input 3d+time dataset to process
-basefile fname Filename of 3d+time dataset for base image
(default = current input dataset)
-base num Time index for base image (0 <= num)
(default: num = 3)
-nofine Deactivate fine fit phase of image registration
(default: fine fit is active)
-fine blur dxy dphi Set fine fit parameters
where:
blur = FWHM of blurring prior to registration (in pixels)
(default: blur = 1.0)
dxy = Convergence tolerance for translations (in pixels)
(default: dxy = 0.07)
dphi = Convergence tolerance for rotations (in degrees)
(default: dphi = 0.21)
-prefix pname Prefix name for output 3d+time dataset
-dprefix dname Write files 'dname'.dx, 'dname'.dy, 'dname'.psi
containing the registration parameters for each
slice in chronological order.
File formats:
'dname'.dx: time(sec) dx(pixels)
'dname'.dy: time(sec) dy(pixels)
'dname'.psi: time(sec) psi(degrees)
-dmm Change dx and dy output format from pixels to mm
-rprefix rname Write files 'rname'.oldrms and 'rname'.newrms
containing the volume RMS error for the original
and the registered datasets, respectively.
File formats:
'rname'.oldrms: volume(number) rms_error
'rname'.newrms: volume(number) rms_error
-debug Lots of additional output to screen
This page auto-generated on Thu Aug 25 16:49:35 EDT 2005
|
| 2swap |
Usage: 2swap [-q] file ... -- Swaps byte pairs on the files listed. The -q option means to work quietly.This page auto-generated on Thu Aug 25 16:49:35 EDT 2005 |
| 3dAFNIto3D |
Usage: 3dAFNIto3D [options] dataset
Reads in an AFNI dataset, and writes it out as a 3D file.
OPTIONS:
-prefix ppp = Write result into file ppp.3D;
default prefix is same as AFNI dataset's.
-bin = Write data in binary format, not text.
-txt = Write data in text format, not binary.
NOTES:
* At present, all bricks are written out in float format.
This page auto-generated on Thu Aug 25 16:49:35 EDT 2005
|
| 3dAFNItoANALYZE |
Usage: 3dAFNItoANALYZE [-4D] [-orient code] aname dset
Writes AFNI dataset 'dset' to 1 or more ANALYZE 7.5 format
.hdr/.img file pairs (one pair for each sub-brick in the
AFNI dataset). The ANALYZE files will be named
aname_0000.hdr aname_0000.img for sub-brick #0
aname_0001.hdr aname_0001.img for sub-brick #1
and so forth. Each file pair will contain a single 3D array.
* If the AFNI dataset does not include sub-brick scale
factors, then the ANALYZE files will be written in the
datum type of the AFNI dataset.
* If the AFNI dataset does have sub-brick scale factors,
then each sub-brick will be scaled to floating format
and the ANALYZE files will be written as floats.
* The .hdr and .img files are written in the native byte
order of the computer on which this program is executed.
Options
-------
-4D [30 Sep 2002]:
If you use this option, then all the data will be written to
one big ANALYZE file pair named aname.hdr/aname.img, rather
than a series of 3D files. Even if you only have 1 sub-brick,
you may prefer this option, since the filenames won't have
the '_0000' appended to 'aname'.
-orient code [19 Mar 2003]:
This option lets you flip the dataset to a different orientation
when it is written to the ANALYZE files. The orientation code is
formed as follows:
The code must be 3 letters, one each from the
pairs {R,L} {A,P} {I,S}. The first letter gives
the orientation of the x-axis, the second the
orientation of the y-axis, the third the z-axis:
R = Right-to-Left L = Left-to-Right
A = Anterior-to-Posterior P = Posterior-to-Anterior
I = Inferior-to-Superior S = Superior-to-Inferior
For example, 'LPI' means
-x = Left +x = Right
-y = Posterior +y = Anterior
-z = Inferior +z = Superior
* For display in SPM, 'LPI' or 'RPI' seem to work OK.
Be careful with this: you don't want to confuse L and R
in the SPM display!
* If you DON'T use this option, the dataset will be written
out in the orientation in which it is stored in AFNI
(e.g., the output of '3dinfo dset' will tell you this.)
* The dataset orientation is NOT stored in the .hdr file.
* AFNI and ANALYZE data are stored in files with the x-axis
varying most rapidly and the z-axis most slowly.
* Note that if you read an ANALYZE dataset into AFNI for
display, AFNI assumes the LPI orientation, unless you
set environment variable AFNI_ANALYZE_ORIENT.
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|
| 3dAFNItoMINC |
Usage: 3dAFNItoMINC [options] dataset
Reads in an AFNI dataset, and writes it out as a MINC file.
OPTIONS:
-prefix ppp = Write result into file ppp.mnc;
default prefix is same as AFNI dataset's.
-floatize = Write MINC file in float format.
NOTES:
* Multi-brick datasets are written as 4D (x,y,z,t) MINC
files.
* If the dataset has complex-valued sub-bricks, then this
program won't write the MINC file.
* If any of the sub-bricks have floating point scale
factors attached, then the output will be in float
format (regardless of the presence of -floatize).
* This program uses the MNI program 'rawtominc' to create
the MINC file; rawtominc must be in your path. If you
don't have rawtominc, you must install the MINC tools
software package from MNI. (But if you don't have the
MINC tools already, why do you want to convert to MINC
format anyway?)
* At this time, you can find the MINC tools at
ftp://ftp.bic.mni.mcgill.ca/pub/minc/
You need the latest version of minc-*.tar.gz and also
of netcdf-*.tar.gz.
-- RWCox - April 2002
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|
| 3dAFNItoNIFTI |
++ Program 3dAFNItoNIFTI: AFNI version=AFNI_2005_08_24_1751
Usage: 3dAFNItoNIFTI [options] dataset
Reads an AFNI dataset, writes it out as a NIfTI-1.1 (.nii) file.
NOTES:
* The nifti_tool program can be used to manipulate
the contents of a NIfTI-1.1 file.
* The input dataset can actually be in any input format
that AFNI can read directly (e.g., MINC-1).
* There is no 3dNIFTItoAFNI program, since AFNI programs
can directly read .nii files. If you wish to make such
a conversion anyway, one way to do so is like so:
3dcalc -a ppp.nii -prefix ppp -expr 'a'
OPTIONS:
-prefix ppp = Write the NIfTI-1.1 file as 'ppp.nii'.
Default: the dataset's prefix is used.
If you want a compressed file, try
using a prefix like 'ppp.nii.gz'.
-verb = Be verbose = print progress messages.
Repeating this increases the verbosity
(maximum setting is 3 '-verb' options).
-float = Force the output dataset to be 32-bit
floats. This option should be used when
the input AFNI dataset has different
float scale factors for different sub-bricks,
an option that NIfTI-1.1 does not support.
The following options affect the contents of the AFNI extension
field that is written by default into the NIfTI-1.1 header:
-pure = Do NOT write an AFNI extension field into
the output file. Only use this option if
needed. You can also use the 'nifti_tool'
program to strip extensions from a file.
-denote = When writing the AFNI extension field, remove
text notes that might contain subject
identifying information.
-oldid = Give the new dataset the input dataset's
AFNI ID code.
-newid = Give the new dataset a new AFNI ID code, to
distinguish it from the input dataset.
**** N.B.: -newid is now the default action.
This page auto-generated on Thu Aug 25 16:49:35 EDT 2005
|
| 3dAFNItoNIML |
Usage: 3dAFNItoNIML [options] dset
Dumps AFNI dataset header information to stdout in NIML format.
Mostly for debugging and testing purposes!
OPTIONS:
-data == Also put the data into the output (will be huge).
-tcp:host:port == Instead of stdout, send the dataset to a socket.
(implies '-data' as well)
-- RWCox - Mar 2005
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|
| 3dAFNItoRaw |
Usage: 3dAFNItoRaw [options] dataset
Convert an AFNI brik file with multiple sub-briks to a raw file with
each sub-brik voxel concatenated voxel-wise.
For example, a dataset with 3 sub-briks X,Y,Z with elements x1,x2,x3,...,xn,
y1,y2,y3,...,yn and z1,z2,z3,...,zn will be converted to a raw dataset with
elements x1,y1,z1, x2,y2,z2, x3,y3,z3, ..., xn,yn,zn
The dataset is kept in the original data format (float/short/int)
Options:
-output / -prefix = name of the output file (not an AFNI dataset prefix)
the default output name will be rawxyz.dat
-datum float = force floating point output. Floating point forced if any
sub-brik scale factors not equal to 1.
INPUT DATASET NAMES
-------------------
This program accepts datasets that are modified on input according to the
following schemes:
'r1+orig[3..5]' {sub-brick selector}
'r1+orig<100.200>' {sub-range selector}
'r1+orig[3..5]<100..200>' {both selectors}
'3dcalc( -a r1+orig -b r2+orig -expr 0.5*(a+b) )' {calculation}
For the gruesome details, see the output of 'afni -help'.
This page auto-generated on Thu Aug 25 16:49:36 EDT 2005
|
| 3dANALYZEtoAFNI |
** DON'T USE THIS PROGRAM! REALLY!
USE 3dcopy OR to3d INSTEAD.
IF YOU CHOOSE TO USE IT ANYWAY, PERHAPS
BECAUSE IT WORKS BETTER ON YOUR 12th
CENTURY PLANTAGENET ANALYZE FILES,
ADD THE OPTION -OK TO YOUR COMMAND
LINE.
Usage: 3dANALYZEtoAFNI [options] file1.hdr file2.hdr ...
This program constructs a 'volumes' stored AFNI dataset
from the ANALYZE-75 files file1.img file2.img ....
In this type of dataset, there is only a .HEAD file; the
.BRIK file is replaced by the collection of .img files.
- Other AFNI programs can read (but not write) this type
of dataset.
- The advantage of using this type of dataset vs. one created
with to3d is that you don't have to duplicate the image data
into a .BRIK file, thus saving disk space.
- The disadvantage of using 'volumes' for a multi-brick dataset
is that all the .img files must be kept with the .HEAD file
if you move the dataset around.
- The .img files must be in the same directory as the .HEAD file.
- Note that you put the .hdr files on the command line, but it is
the .img files that will be named in the .HEAD file.
- After this program is run, you must keep the .img files with
the output .HEAD file. AFNI doesn't need the .hdr files, but
other programs (e.g., FSL, SPM) will want them as well.
Options:
-prefix ppp = Save the dataset with the prefix name 'ppp'.
[default='a2a']
-view vvv = Save the dataset in the 'vvv' view, where
'vvv' is one of 'orig', 'acpc', or 'tlrc'.
[default='orig']
-TR ttt = For multi-volume datasets, create it as a
3D+time dataset with TR set to 'ttt'.
-fbuc = For multi-volume datasets, create it as a
functional bucket dataset.
-abuc = For multi-volume datasets, create it as an
anatomical bucket dataset.
** If more than one ANALYZE file is input, and none of the
above options is given, the default is as if '-TR 1s'
was used.
** For single volume datasets (1 ANALYZE file input), the
default is '-abuc'.
-geomparent g = Use the .HEAD file from dataset 'g' to set
the geometry of this dataset.
** If you don't use -geomparent, then the following options
can be used to specify the geometry of this dataset:
-orient code = Tells the orientation of the 3D volumes. The code
must be 3 letters, one each from the pairs {R,L}
{A,P} {I,S}. The first letter gives the orientation
of the x-axis, the second the orientation of the
y-axis, the third the z-axis:
R = right-to-left L = left-to-right
A = anterior-to-posterior P = posterior-to-anterior
I = inferior-to-superior S = superior-to-inferior
-zorigin dz = Puts the center of the 1st slice off at the
given distance ('dz' in mm). This distance
is in the direction given by the corresponding
letter in the -orient code. For example,
-orient RAI -zorigin 30
would set the center of the first slice at
30 mm Inferior.
** If the above options are NOT used to specify the geometry
of the dataset, then the default is '-orient RAI', and the
z origin is set to center the slices about z=0.
It is likely that you will want to patch up the .HEAD file using
program 3drefit.
-- RWCox - June 2002.
** DON'T USE THIS PROGRAM! REALLY!
USE 3dcopy OR to3d INSTEAD.
IF YOU CHOOSE TO USE IT ANYWAY, PERHAPS
BECAUSE IT WORKS BETTER ON YOUR 12th
CENTURY PLANTAGENET ANALYZE FILES,
ADD THE OPTION -OK TO YOUR COMMAND
LINE.-- KRH - April 2005.
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|
| 3dAnatNudge |
Usage: 3dAnatNudge [options]
Moves the anat dataset around to best overlap the epi dataset.
OPTIONS:
-anat aaa = aaa is an 'scalped' (3dIntracranial) high-resolution
anatomical dataset [a mandatory option]
-epi eee = eee is an EPI dataset [a mandatory option]
The first [0] sub-brick from each dataset is used,
unless otherwise specified on the command line.
-prefix ppp = ppp is the prefix of the output dataset;
this dataset will differ from the input only
in its name and its xyz-axes origin
[default=don't write new dataset]
-step sss = set the step size to be sss times the voxel size
in the anat dataset [default=1.0]
-x nx = search plus and minus nx steps along the EPI
-y ny dataset's x-axis; similarly for ny and the
-z nz y-axis, and for nz and the z-axis
[default: nx=1 ny=5 nz=0]
-verb = print progress reports (this is a slow program)
NOTES
*Systematically moves the anat dataset around and find the shift
that maximizes overlap between the anat dataset and the EPI
dataset. No rotations are done.
*Note that if you use -prefix, a new dataset will be created that
is a copy of the anat, except that it's origin will be shifted
and it will have a different ID code than the anat. If you want
to use this new dataset as the anatomy parent for the EPI
datasets, you'll have to use
3drefit -apar ppp+orig eee1+orig eee2+orig ...
*If no new dataset is written (no -prefix option), then you
can use the 3drefit command emitted at the end to modify
the origin of the anat dataset. (Assuming you trust the
results - visual inspection is recommended!)
*The reason the default search grid is mostly along the EPI y-axis
is that axis is usually the phase-encoding direction, which is
most subject to displacement due to off-resonance effects.
*Note that the time this program takes will be proportional to
(2*nx+1)*(2*ny+1)*(2*nz+1), so using a very large search grid
will result in a very large usage of CPU time.
*Recommended usage:
+ Make a 1-brick function volume from a typical EPI dataset:
3dbucket -fbuc -prefix epi_fb epi+orig
+ Use 3dIntracranial to scalp a T1-weighted volume:
3dIntracranial -anat spgr+orig -prefix spgr_st
+ Use 3dAnatNudge to produce a shifted anat dataset
3dAnatNudge -anat spgr_st+orig -epi epi_fb+orig -prefix spgr_nudge
+ Start AFNI and look at epi_fb overlaid in color on the
anat datasets spgr_st+orig and spgr_nudge+orig, to see if the
nudged dataset seems like a better fit.
+ Delete the nudged dataset spgr_nudge.
+ If the nudged dataset DOES look better, then apply the
3drefit command output by 3dAnatNudge to spgr+orig.
*Note that the x-, y-, and z-axes for the epi and anat datasets
may point in different directions (e.g., axial SPGR and
coronal EPI). The 3drefit command applies to the anat
dataset, NOT to the EPI dataset.
*If the program runs successfully, the only thing set to stdout
will be the 3drefit command string; all other messages go to
stderr. This can be useful if you want to capture the command
to a shell variable and then execute it, as in the following
csh fragment:
set cvar = `3dAnatNudge ...`
if( $cvar[1] == "3drefit" ) $cvar
The test on the first sub-string in cvar allows for the
possibility that the program fails, or that the optimal
nudge is zero.
This page auto-generated on Thu Aug 25 16:49:36 EDT 2005
|
| 3dAnhist |
Usage: 3dAnhist [options] dataset
Input dataset is a T1-weighted high-res of the brain (shorts only).
Output is a list of peaks in the histogram, to stdout, in the form
( datasetname #peaks peak1 peak2 ... )
In the C-shell, for example, you could do
set anhist = `3dAnhist -q -w1 dset+orig`
Then the number of peaks found is in the shell variable $anhist[2].
Options:
-q = be quiet (don't print progress reports)
-h = dump histogram data to Anhist.1D and plot to Anhist.ps
-F = DON'T fit histogram with stupid curves.
-w = apply a Winsorizing filter prior to histogram scan
(or -w7 to Winsorize 7 times, etc.)
-2 = Analyze top 2 peaks only, for overlap etc.
-label xxx = Use 'xxx' for a label on the Anhist.ps plot file
instead of the input dataset filename.
-fname fff = Use 'fff' for the filename instead of 'Anhist'.
If the '-2' option is used, AND if 2 peaks are detected, AND if
the -h option is also given, then stdout will be of the form
( datasetname 2 peak1 peak2 thresh CER CJV count1 count2 count1/count2)
where 2 = number of peaks
thresh = threshold between peak1 and peak2 for decision-making
CER = classification error rate of thresh
CJV = coefficient of joint variation
count1 = area under fitted PDF for peak1
count2 = area under fitted PDF for peak2
count1/count2 = ratio of the above quantities
NOTA BENE
---------
* If the input is a T1-weighted MRI dataset (the usual case), then
peak 1 should be the gray matter (GM) peak and peak 2 the white
matter (WM) peak.
* For the definitions of CER and CJV, see the paper
Method for Bias Field Correction of Brain T1-Weighted Magnetic
Resonance Images Minimizing Segmentation Error
JD Gispert, S Reig, J Pascau, JJ Vaquero, P Garcia-Barreno,
and M Desco, Human Brain Mapping 22:133-144 (2004).
* Roughly speaking, CER is the ratio of the overlapping area of the
2 peak fitted PDFs to the total area of the fitted PDFS. CJV is
(sigma_GM+sigma_WM)/(mean_WM-mean_GM), and is a different, ad hoc,
measurement of how much the two PDF overlap.
* The fitted PDFs are NOT Gaussians. They are of the form
f(x) = b((x-p)/w,a), where p=location of peak, w=width, 'a' is
a skewness parameter between -1 and 1; the basic distribution
is defined by b(x)=(1-x^2)^2*(1+a*x*abs(x)) for -1 < x < 1.
-- RWCox - November 2004
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|
| 3dANOVA |
++ Program 3dANOVA: AFNI version=AFNI_2005_08_24_1751
This program performs single factor Analysis of Variance (ANOVA)
on 3D datasets
---------------------------------------------------------------
Usage:
-----
3dANOVA
-levels r : r = number of factor levels
-dset 1 filename : data set for factor level 1
. . . . . .
-dset 1 filename data set for factor level 1
. . . . . .
-dset r filename data set for factor level r
. . . . . .
-dset r filename data set for factor level r
[-voxel num] : screen output for voxel # num
[-diskspace] : print out disk space required for
program execution
The following commands generate individual AFNI 2-sub-brick datasets:
(In each case, output is written to the file with the specified
prefix file name.)
[-ftr prefix] : F-statistic for treatment effect
[-mean i prefix] : estimate of factor level i mean
[-diff i j prefix] : difference between factor levels
[-contr c1...cr prefix] : contrast in factor levels
The following command generates one AFNI 'bucket' type dataset:
[-bucket prefix] : create one AFNI 'bucket' dataset whose
sub-bricks are obtained by
concatenating the above output files;
the output 'bucket' is written to file
with prefix file name
N.B.: For this program, the user must specify 1 and only 1 sub-brick
with each -dset command. That is, if an input dataset contains
more than 1 sub-brick, a sub-brick selector must be used,
e.g., -dset 2 'fred+orig[3]'
Example of 3dANOVA:
------------------
Example is based on a study with one factor (independent variable)
called 'Pictures', with 3 levels:
(1) Faces, (2) Houses, and (3) Donuts
The ANOVA is being conducted on subject Fred's data:
3dANOVA -levels 3 \
-dset 1 fred_Faces+tlrc \
-dset 2 fred_Houses+tlrc \
-dset 3 fred_Donuts+tlrc \
-ftr Pictures \
-mean 1 Faces \
-mean 2 Houses \
-mean 3 Donuts \
-diff 1 2 FvsH \
-diff 2 3 HvsD \
-diff 1 3 FvsD \
-contr 1 1 -1 FHvsD \
-contr -1 1 1 FvsHD \
-contr 1 -1 1 FDvsH \
-bucket fred_ANOVA
INPUT DATASET NAMES
-------------------
This program accepts datasets that are modified on input according to the
following schemes:
'r1+orig[3..5]' {sub-brick selector}
'r1+orig<100.200>' {sub-range selector}
'r1+orig[3..5]<100..200>' {both selectors}
'3dcalc( -a r1+orig -b r2+orig -expr 0.5*(a+b) )' {calculation}
For the gruesome details, see the output of 'afni -help'.
---------------------------------------------------
Also see HowTo#5 - Group Analysis on the AFNI website:
http://afni.nimh.nih.gov/pub/dist/HOWTO/howto/ht05_group/html/index.shtml
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|
| 3dANOVA2 |
Program: 3dANOVA2
Author: B. Douglas Ward
Initial Release: 09 Dec 1996
Latest Revision: 02 Aug 2005
This program performs two-factor ANOVA on 3D data sets
Usage:
3dANOVA2
-type k type of ANOVA model to be used:
k=1 fixed effects model (A and B fixed)
k=2 random effects model (A and B random)
k=3 mixed effects model (A fixed, B random)
-alevels a a = number of levels of factor A
-blevels b b = number of levels of factor B
-dset 1 1 filename data set for level 1 of factor A
and level 1 of factor B
. . . . . .
-dset i j filename data set for level i of factor A
and level j of factor B
. . . . . .
-dset a b filename data set for level a of factor A
and level b of factor B
[-voxel num] screen output for voxel # num
[-diskspace] print out disk space required for
program execution
The following commands generate individual AFNI 2 sub-brick datasets:
(In each case, output is written to the file with the specified
prefix file name.)
[-ftr prefix] F-statistic for treatment effect
[-fa prefix] F-statistic for factor A effect
[-fb prefix] F-statistic for factor B effect
[-fab prefix] F-statistic for interaction
[-amean i prefix] estimate mean of factor A level i
[-bmean j prefix] estimate mean of factor B level j
[-xmean i j prefix] estimate mean of cell at level i of
factor A, level j of factor B
[-adiff i j prefix] difference between levels i and j of
factor A
[-bdiff i j prefix] difference between levels i and j of
factor B
[-xdiff i j k l prefix] difference between cell mean at A=i,B=j
and cell mean at A=k,B=l
[-acontr c1 ... ca prefix] contrast in factor A levels
[-bcontr c1 ... cb prefix] contrast in factor B levels
[-xcontr c11 ... c1b c21 ... c2b ... ca1 ... cab prefix]
contrast in cell means
The following command generates one AFNI 'bucket' type dataset:
[-bucket prefix] create one AFNI 'bucket' dataset whose
sub-bricks are obtained by concatenating
the above output files; the output 'bucket'
is written to file with prefix file name
N.B.: For this program, the user must specify 1 and only 1 sub-brick
with each -dset command. That is, if an input dataset contains
more than 1 sub-brick, a sub-brick selector must be used, e.g.:
-dset 2 4 'fred+orig[3]'
INPUT DATASET NAMES
-------------------
This program accepts datasets that are modified on input according to the
following schemes:
'r1+orig[3..5]' {sub-brick selector}
'r1+orig<100.200>' {sub-range selector}
'r1+orig[3..5]<100..200>' {both selectors}
'3dcalc( -a r1+orig -b r2+orig -expr 0.5*(a+b) )' {calculation}
For the gruesome details, see the output of 'afni -help'.
This page auto-generated on Thu Aug 25 16:49:36 EDT 2005
|
| 3dANOVA3 |
Program: 3dANOVA3
Author: B. Douglas Ward
Initial Release: 29 Jan 1997
Latest Revision: 19 Jul 2004
This program performs three-factor ANOVA on 3D data sets.
Usage:
3dANOVA3
-type k type of ANOVA model to be used:
k = 1 A,B,C fixed; AxBxC
k = 2 A,B,C random; AxBxC
k = 3 A fixed; B,C random; AxBxC
k = 4 A,B fixed; C random; AxBxC
k = 5 A,B fixed; C random; AxB,BxC,C(A)
-alevels a a = number of levels of factor A
-blevels b b = number of levels of factor B
-clevels c c = number of levels of factor C
-dset 1 1 1 filename data set for level 1 of factor A
and level 1 of factor B
and level 1 of factor C
. . . . . .
-dset i j k filename data set for level i of factor A
and level j of factor B
and level k of factor C
. . . . . .
-dset a b c filename data set for level a of factor A
and level b of factor B
and level c of factor C
[-voxel num] screen output for voxel # num
[-diskspace] print out disk space required for
program execution
The following commands generate individual AFNI 2 sub-brick datasets:
(In each case, output is written to the file with the specified
prefix file name.)
[-fa prefix] F-statistic for factor A effect
[-fb prefix] F-statistic for factor B effect
[-fc prefix] F-statistic for factor C effect
[-fab prefix] F-statistic for A*B interaction
[-fac prefix] F-statistic for A*C interaction
[-fbc prefix] F-statistic for B*C interaction
[-fabc prefix] F-statistic for A*B*C interaction
[-amean i prefix] estimate of factor A level i mean
[-bmean i prefix] estimate of factor B level i mean
[-cmean i prefix] estimate of factor C level i mean
[-xmean i j k prefix] estimate mean of cell at factor A level i,
factor B level j, factor C level k
[-adiff i j prefix] difference between factor A levels i and j
[-bdiff i j prefix] difference between factor B levels i and j
[-cdiff i j prefix] difference between factor C levels i and j
[-xdiff i j k l m n prefix] difference between cell mean at A=i,B=j,
C=k, and cell mean at A=l,B=m,C=n
[-acontr c1...ca prefix] contrast in factor A levels
[-bcontr c1...cb prefix] contrast in factor B levels
[-ccontr c1...cc prefix] contrast in factor C levels
The following command generates one AFNI 'bucket' type dataset:
[-bucket prefix] create one AFNI 'bucket' dataset whose
sub-bricks are obtained by concatenating
the above output files; the output 'bucket'
is written to file with prefix file name
N.B.: For this program, the user must specify 1 and only 1 sub-brick
with each -dset command. That is, if an input dataset contains
more than 1 sub-brick, a sub-brick selector must be used, e.g.:
-dset 2 4 5 'fred+orig[3]'
INPUT DATASET NAMES
-------------------
This program accepts datasets that are modified on input according to the
following schemes:
'r1+orig[3..5]' {sub-brick selector}
'r1+orig<100.200>' {sub-range selector}
'r1+orig[3..5]<100..200>' {both selectors}
'3dcalc( -a r1+orig -b r2+orig -expr 0.5*(a+b) )' {calculation}
For the gruesome details, see the output of 'afni -help'.
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|
| 3dAttribute |
Usage: 3dAttribute [options] aname dset
Prints (to stdout) the value of the attribute 'aname' from
the header of dataset 'dset'. If the attribute doesn't exist,
prints nothing and sets the exit status to 1.
Options:
-name = Include attribute name in printout
-all = Print all attributes [don't put aname on command line]
Also implies '-name'. Attributes print in whatever order
they are in the .HEAD file, one per line. You may want
to do '3dAttribute -all elvis+orig | sort' to get them
in alphabetical order.
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|
| 3dAutobox |
Usage: 3dAutobox dataset Computes size of a box that fits around the volume.This page auto-generated on Thu Aug 25 16:49:36 EDT 2005 |
| 3dAutomask |
Usage: 3dAutomask [options] dataset
Input dataset is EPI 3D+time.
Output dataset is a brain-only mask dataset.
Method:
+ Uses 3dClipLevel algorithm to find clipping level.
+ Keeps only the largest connected component of the
supra-threshold voxels, after an erosion/dilation step.
+ Writes result as a 'fim' type of functional dataset.
Options:
-prefix ppp = Write mask into dataset with prefix 'ppp'.
[default='automask']
-q = Don't write progress messages (i.e., be quiet).
-eclip = After creating the mask, remove exterior
voxels below the clip threshold.
-dilate nd = Dilate the mask outwards 'nd' times.
-SI hh = After creating the mask, find the most superior
voxel, then zero out everything more than 'hh'
millimeters inferior to that. hh=130 seems to
be decent (for human brains).
This page auto-generated on Thu Aug 25 16:49:36 EDT 2005
|
| 3dAutoTcorrelate |
Usage: 3dAutoTcorrelate [options] dset
Computes the correlation coefficient between each pair of
voxels in the input dataset, and stores the output into
a new anatomical bucket dataset.
Options:
-pearson = Correlation is the normal Pearson (product moment)
correlation coefficient [default].
-spearman = Correlation is the Spearman (rank) correlation
coefficient.
-quadrant = Correlation is the quadrant correlation coefficient.
-polort m = Remove polynomical trend of order 'm', for m=-1..3.
[default is m=1; removal is by least squares].
Using m=-1 means no detrending; this is only useful
for data/information that has been pre-processed.
-autoclip = Clip off low-intensity regions in the dataset,
-automask = so that the correlation is only computed between
high-intensity (presumably brain) voxels. The
intensity level is determined the same way that
3dClipLevel works.
-prefix p = Save output into dataset with prefix 'p'
[default prefix is 'ATcorr'].
-time = Save output as a 3D+time dataset instead
of a anat bucket.
Notes:
* The output dataset is anatomical bucket type of shorts.
* The output file might be gigantic and you might run out
of memory running this program. Use at your own risk!
* The program prints out an estimate of its memory usage
when it starts. It also prints out a progress 'meter'
of 1 dot per 10 output sub-bricks.
* This is a quick hack for Peter Bandettini. Now pay up.
-- RWCox - Jan 31 2002
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|
| 3daxialize |
Usage: 3daxialize [options] dataset
Purpose: Read in a dataset and write it out as a new dataset
with the data brick oriented as axial slices.
The input dataset must have a .BRIK file.
One application is to create a dataset that can
be used with the AFNI volume rendering plugin.
Options:
-prefix ppp = Use 'ppp' as the prefix for the new dataset.
[default = 'axialize']
-verb = Print out a progress report.
The following options determine the order/orientation
in which the slices will be written to the dataset:
-sagittal = Do sagittal slice order [-orient ASL]
-coronal = Do coronal slice order [-orient RSA]
-axial = Do axial slice order [-orient RAI]
This is the default AFNI axial order, and
is the one currently required by the
volume rendering plugin; this is also
the default orientation output by this
program (hence the program's name).
-orient code = Orientation code for output.
The code must be 3 letters, one each from the
pairs {R,L} {A,P} {I,S}. The first letter gives
the orientation of the x-axis, the second the
orientation of the y-axis, the third the z-axis:
R = Right-to-left L = Left-to-right
A = Anterior-to-posterior P = Posterior-to-anterior
I = Inferior-to-superior S = Superior-to-inferior
If you give an illegal code (e.g., 'LPR'), then
the program will print a message and stop.
N.B.: 'Neurological order' is -orient LPI
INPUT DATASET NAMES
-------------------
This program accepts datasets that are modified on input according to the
following schemes:
'r1+orig[3..5]' {sub-brick selector}
'r1+orig<100.200>' {sub-range selector}
'r1+orig[3..5]<100..200>' {both selectors}
'3dcalc( -a r1+orig -b r2+orig -expr 0.5*(a+b) )' {calculation}
For the gruesome details, see the output of 'afni -help'.
This page auto-generated on Thu Aug 25 16:49:36 EDT 2005
|
| 3dBRAIN_VOYAGERtoAFNI |
Usage: 3dBRAIN_VOYAGERtoAFNI -input BV_VOLUME.vmr
Converts a BrainVoyager vmr dataset to AFNI's BRIK format
The conversion is based on information from BrainVoyager's
website: www.brainvoyager.com. Sample data and information
provided by Adam Greenberg and Nikolaus Kriegeskorte.
Common Debugging Options:
[-trace]: Turns on In/Out debug and Memory tracing.
For speeding up the tracing log, I recommend
you redirect stdout to a file when using this option.
For example, if you were running suma you would use:
suma -spec lh.spec -sv ... > TraceFile
This option replaces the old -iodbg and -memdbg.
[-TRACE]: Turns on extreme tracing.
[-nomall]: Turn off memory tracing.
[-yesmall]: Turn on memory tracing (default).
[-novolreg]: Ignore any Volreg or Tagalign transformations
present in the Surface Volume.
NOTE: For programs that output results to stdout
(that is to your shell/screen), the debugging info
might get mixed up with your results.
++ SUMA version 2004_12_29
CVS tag:
SUMA_2005_04_29_1733
Compile Date:
Aug 25 2005
Ziad S. Saad SSCC/NIMH/NIH ziad@nih.gov
This page auto-generated on Thu Aug 25 16:49:36 EDT 2005
|
| 3dbuc2fim |
Program: 3dbuc2fim
Author: B. D. Ward
Initial Release: 18 March 1998
Latest Revision: 15 August 2001
This program converts bucket sub-bricks to fim (fico, fitt, fift, ...)
type dataset.
Usage:
3dbuc2fim -prefix pname d1+orig[index]
This produces a fim dataset.
-or-
3dbuc2fim -prefix pname d1+orig[index1] d2+orig[index2]
This produces a fico (fitt, fift, ...) dataset,
depending on the statistic type of the 2nd subbrick,
with d1+orig[index1] -> intensity sub-brick of pname
d2+orig[index2] -> threshold sub-brick of pname
-or-
3dbuc2fim -prefix pname d1+orig[index1,index2]
This produces a fico (fitt, fift, ...) dataset,
depending on the statistic type of the 2nd subbrick,
with d1+orig[index1] -> intensity sub-brick of pname
d1+orig[index2] -> threshold sub-brick of pname
where the options are:
-prefix pname = Use 'pname' for the output dataset prefix name.
OR -output pname [default='buc2fim']
-session dir = Use 'dir' for the output dataset session directory.
[default='./'=current working directory]
-verb = Print out some verbose output as the program
proceeds
Command line arguments after the above are taken as input datasets.
A dataset is specified using one of these forms:
'prefix+view', 'prefix+view.HEAD', or 'prefix+view.BRIK'.
Sub-brick indexes start at 0.
N.B.: The sub-bricks are output in the order specified, which may
not be the order in the original datasets. For example, using
fred+orig[5,3]
will cause the sub-brick #5 in fred+orig to be output as the intensity
sub-brick, and sub-brick #3 to be output as the threshold sub-brick
in the new dataset.
N.B.: The '$', '(', ')', '[', and ']' characters are special to
the shell, so you will have to escape them. This is most easily
done by putting the entire dataset plus selection list inside
single quotes, as in 'fred+orig[5,9]'.
This page auto-generated on Thu Aug 25 16:49:36 EDT 2005
|
| 3dbucket |
Concatenate sub-bricks from input datasets into one big
'bucket' dataset.
Usage: 3dbucket options
where the options are:
-prefix pname = Use 'pname' for the output dataset prefix name.
OR -output pname [default='buck']
-session dir = Use 'dir' for the output dataset session directory.
[default='./'=current working directory]
-glueto fname = Append bricks to the end of the 'fname' dataset.
This command is an alternative to the -prefix
and -session commands.
-dry = Execute a 'dry run'; that is, only print out
what would be done. This is useful when
combining sub-bricks from multiple inputs.
-verb = Print out some verbose output as the program
proceeds (-dry implies -verb).
-fbuc = Create a functional bucket.
-abuc = Create an anatomical bucket. If neither of
these options is given, the output type is
determined from the first input type.
Command line arguments after the above are taken as input datasets.
A dataset is specified using one of these forms:
'prefix+view', 'prefix+view.HEAD', or 'prefix+view.BRIK'.
You can also add a sub-brick selection list after the end of the
dataset name. This allows only a subset of the sub-bricks to be
included into the output (by default, all of the input dataset
is copied into the output). A sub-brick selection list looks like
one of the following forms:
fred+orig[5] ==> use only sub-brick #5
fred+orig[5,9,17] ==> use #5, #9, and #12
fred+orig[5..8] or [5-8] ==> use #5, #6, #7, and #8
fred+orig[5..13(2)] or [5-13(2)] ==> use #5, #7, #9, #11, and #13
Sub-brick indexes start at 0. You can use the character '$'
to indicate the last sub-brick in a dataset; for example, you
can select every third sub-brick by using the selection list
fred+orig[0..$(3)]
N.B.: The sub-bricks are output in the order specified, which may
not be the order in the original datasets. For example, using
fred+orig[0..$(2),1..$(2)]
will cause the sub-bricks in fred+orig to be output into the
new dataset in an interleaved fashion. Using
fred+orig[$..0]
will reverse the order of the sub-bricks in the output.
N.B.: Bucket datasets have multiple sub-bricks, but do NOT have
a time dimension. You can input sub-bricks from a 3D+time dataset
into a bucket dataset. You can use the '3dinfo' program to see
how many sub-bricks a 3D+time or a bucket dataset contains.
N.B.: The '$', '(', ')', '[', and ']' characters are special to
the shell, so you will have to escape them. This is most easily
done by putting the entire dataset plus selection list inside
single quotes, as in 'fred+orig[5..7,9]'.
N.B.: In non-bucket functional datasets (like the 'fico' datasets
output by FIM, or the 'fitt' datasets output by 3dttest), sub-brick
[0] is the 'intensity' and sub-brick [1] is the statistical parameter
used as a threshold. Thus, to create a bucket dataset using the
intensity from dataset A and the threshold from dataset B, and
calling the output dataset C, you would type
3dbucket -prefix C -fbuc 'A+orig[0]' -fbuc 'B+orig[1]'
WARNING: using this program, it is possible to create a dataset that
has different basic datum types for different sub-bricks
(e.g., shorts for brick 0, floats for brick 1).
Do NOT do this! Very few AFNI programs will work correctly
with such datasets!
This page auto-generated on Thu Aug 25 16:49:36 EDT 2005
|
| 3dcalc |
Program: 3dcalc
Author: RW Cox et al
3dcalc - AFNI's calculator program
This program does voxel-by-voxel arithmetic on 3D datasets
(limited to inter-voxel computation).
The program assumes that the voxel-by-voxel computations are being
performed on datasets that occupy the same space and have the same
orientations.
------------------------------------------------------------------------
Usage:
-----
3dcalc -a dsetA [-b dsetB...] \
-expr EXPRESSION \
[options]
Examples:
--------
1. Average datasets together, on a voxel-by-voxel basis:
3dcalc -a fred+tlrc -b ethel+tlrc -c lucy+tlrc \
-expr '(a+b+c)/3' -prefix subjects_mean
2. Perform arithmetic calculations between the sub-bricks of a single
dataset by noting the sub-brick number on the command line:
3dcalc -a 'func+orig[2]' -b 'func+orig[4]' -expr 'sqrt(a*b)'
3. Create a simple mask that consists only of values in sub-brick #0
that are greater than 3.14159:
3dcalc -a 'func+orig[0]' -expr 'ispositive(a-3.14159)' \
-prefix mask
4. Normalize subjects' time series datasets to percent change values in
preparation for group analysis:
Voxel-by-voxel, the example below divides each intensity value in
the time series (epi_r1+orig) with the voxel's mean value (mean+orig)
to get a percent change value. The 'ispositive' command will ignore
voxels with mean values less than 167 (i.e., they are labeled as
'zero' in the output file 'percent_change+orig') and are most likely
background/noncortical voxels.
3dcalc -a epi_run1+orig -b mean+orig \
-expr '100 * a/b * ispositive(b-167)' -prefix percent_chng
5. Create a compound mask from a statistical dataset, where 3 stimuli
show activation.
NOTE: 'step' and 'ispositive' are identical expressions that can
be used interchangeably:
3dcalc -a 'func+orig[12]' -b 'func+orig[15]' -c 'func+orig[18]' \
-expr 'step(a-4.2)*step(b-2.9)*step(c-3.1)' \
-prefix compound_mask
6. Same as example #5, but this time create a mask of 8 different values
showing all combinations of activations (i.e., not only where
everything is active, but also each stimulus individually, and all
combinations). The output mask dataset labels voxel values as such:
0 = none active 1 = A only active 2 = B only active
3 = A and B only 4 = C only active 5 = A and C only
6 = B and C only 7 = all A, B, and C active
3dcalc -a 'func+orig[12]' -b 'func+orig[15]' -c 'func+orig[18]' \
-expr 'step(a-4.2)+2*step(b-2.9)+4*step(c-3.1)' \
-prefix mask_8
7. Create a region-of-interest mask comprised of a 3-dimensional sphere.
Values within the ROI sphere will be labeled as '1' while values
outside the mask will be labeled as '0'. Statistical analyses can
then be done on the voxels within the ROI sphere.
The example below puts a solid ball (sphere) of radius 3=sqrt(9)
about the point with coordinates (x,y,z)=(20,30,70):
3dcalc -a anat+tlrc \
-expr 'step((9-(x-20)*(x-20)-(y-30)*(y-30)-(z-70)*(z-70))'\
-prefix ball
8. Some datsets are 'short' (16 bit) integers with a scalar attached,
which allow them to be smaller than float datasets and to contain
fractional values.
Dataset 'a' is always used as a template for the output dataset. For
the examples below, assume that datasets d1+orig and d2+orig consist
of small integers.
a) When dividing 'a' by 'b', the result should be scaled, so that a
value of 2.4 is not truncated to '2'. To avoid this truncation,
force scaling with the -fscale option:
3dcalc -a d1+orig -b d2+orig -expr 'a/b' -prefix quot -fscale
b) If it is preferable that the result is of type 'float', then set
the output data type (datum) to float:
3dcalc -a d1+orig -b d2+orig -expr 'a/b' -prefix quot \
-datum float
c) Perhaps an integral division is desired, so that 9/4=2, not 2.24.
Force the results not to be scaled (opposite of example 8b) using
the -nscale option:
3dcalc -a d1+orig -b d2+orig -expr 'a/b' -prefix quot -nscale
------------------------------------------------------------------------
ARGUMENTS for 3dcalc (must be included on command line):
-------------------- ----
-a dname = Read dataset 'dname' and call the voxel values 'a' in the
expression (-expr) that is input below. Up to 24 dnames
(-a, -b, -c, ... -z) can be included in a single 3dcalc
calculation/expression.
** If some letter name is used in the expression, but
not present in one of the dataset options here, then
that variable is set to 0.
** If the letter is followed by a number, then that
number is used to select the sub-brick of the dataset
which will be used in the calculations.
E.g., '-b3 dname' specifies that the variable 'b'
refers to sub-brick '3' of that dataset
(indexes in AFNI start at 0).
-expr = Apply the expression - within quotes - to the input
datasets (dnames), one voxel at time, to produce the
output dataset.
------------------------------------------------------------------------
OPTIONS for 3dcalc:
-------
-verbose = Makes the program print out various information as it
progresses.
-datum type= Coerce the output data to be stored as the given type,
which may be byte, short, or float.
[default = datum of first input dataset]
-fscale = Force scaling of the output to the maximum integer
range. This only has effect if the output datum is byte
or short (either forced or defaulted). This option is
often necessary to eliminate unpleasant truncation
artifacts.
[The default is to scale only if the computed values
seem to need it -- are all <= 1.0 or there is at
least one value beyond the integer upper limit.]
** In earlier versions of 3dcalc, scaling (if used) was
applied to all sub-bricks equally -- a common scale
factor was used. This would cause trouble if the
values in different sub-bricks were in vastly
different scales. In this version, each sub-brick
gets its own scale factor. To override this behavior,
use the '-gscale' option.
-gscale = Same as '-fscale', but also forces each output sub-brick
to get the same scaling factor. This may be desirable
for 3D+time datasets, for example.
-nscale = Don't do any scaling on output to byte or short datasets.
This may be especially useful when operating on mask
datasets whose output values are only 0's and 1's.
** Another way to achieve the effect of '-b3' is described
below in the dataset 'INPUT' specification section.
-prefix pname = Use 'pname' for the output dataset prefix name.
[default='calc']
-session dir = Use 'dir' for the output dataset session directory.
[default='./'=current working directory]
-dt tstep = Use 'tstep' as the TR for manufactured 3D+time datasets.
-TR tstep = If not given, defaults to 1 second.
-taxis N = If only 3D datasets are input (no 3D+time or .1D files),
*OR* then normally only a 3D dataset is calculated. With
-taxis N:tstep: this option, you can force the creation of a time axis
of length 'N', optionally using time step 'tstep'. In
such a case, you will probably want to use the pre-
defined time variables 't' and/or 'k' in your
expression, or each resulting sub-brick will be
identical. For example:
'-taxis 121:0.1' will produce 121 points in time,
spaced with TR 0.1.
N.B.: You can also specify the TR using the -dt option.
N.B.: You can specify 1D input datasets using the
'1D:n@val,n@val' notation to get a similar effect.
For example:
-dt 0.1 -w '1D:121@0'
will have pretty much the same effect as
-taxis 121:0.1
N.B.: For both '-dt' and '-taxis', the 'tstep' value is in
seconds. You can suffix it with 'ms' to specify that
the value is in milliseconds instead; e.g., '-dt 2000ms'.
-rgbfac A B C = For RGB input datasets, the 3 channels (r,g,b) are
collapsed to one for the purposes of 3dcalc, using the
formula value = A*r + B*g + C*b
The default values are A=0.299 B=0.587 C=0.114, which
gives the grayscale intensity. To pick out the Green
channel only, use '-rgbfac 0 1 0', for example. Note
that each channel in an RGB dataset is a byte in the
range 0..255. Thus, '-rgbfac 0.001173 0.002302 0.000447'
will compute the intensity rescaled to the range 0..1.0
(i.e., 0.001173=0.299/255, etc.)
------------------------------------------------------------------------
DATASET TYPES:
-------------
The most common AFNI dataset types are 'byte', 'short', and 'float'.
A byte value is an 8-bit signed integer (0..255), a short value ia a
16-bit signed integer (-32768..32767), and a float value is a 32-bit
real number. A byte value has almost 3 decimals of accuracy, a short
has almost 5, and a float has approximately 7 (from a 23+1 bit
mantissa).
Datasets can also have a scalar attached to each sub-brick. The main
use of this is allowing a short type dataset to take on non-integral
values, while being half the size of a float dataset.
As an example, consider a short dataset with a scalar of 0.0001. This
could represent values between -32.768 and +32.767, at a resolution of
0.001. One could represnt the difference between 4.916 and 4.917, for
instance, but not 4.9165. Each number has 15 bits of accuracy, plus a
sign bit, which gives 4-5 decimal places of accuracy. If this is not
enough, then it makes sense to use the larger type, float.
------------------------------------------------------------------------
3D+TIME DATASETS:
----------------
This version of 3dcalc can operate on 3D+time datasets. Each input
dataset will be in one of these conditions:
(A) Is a regular 3D (no time) dataset; or
(B) Is a 3D+time dataset with a sub-brick index specified ('-b3'); or
(C) Is a 3D+time dataset with no sub-brick index specified ('-b').
If there is at least one case (C) dataset, then the output dataset will
also be 3D+time; otherwise it will be a 3D dataset with one sub-brick.
When producing a 3D+time dataset, datasets in case (A) or (B) will be
treated as if the particular brick being used has the same value at each
point in time.
Multi-brick 'bucket' datasets may also be used. Note that if multi-brick
(bucket or 3D+time) datasets are used, the lowest letter dataset will
serve as the template for the output; that is, '-b fred+tlrc' takes
precedence over '-c wilma+tlrc'. (The program 3drefit can be used to
alter the .HEAD parameters of the output dataset, if desired.)
------------------------------------------------------------------------
INPUT DATASET NAMES
-------------------
An input dataset is specified using one of these forms:
'prefix+view', 'prefix+view.HEAD', or 'prefix+view.BRIK'.
You can also add a sub-brick selection list after the end of the
dataset name. This allows only a subset of the sub-bricks to be
read in (by default, all of a dataset's sub-bricks are input).
A sub-brick selection list looks like one of the following forms:
fred+orig[5] ==> use only sub-brick #5
fred+orig[5,9,17] ==> use #5, #9, and #12
fred+orig[5..8] or [5-8] ==> use #5, #6, #7, and #8
fred+orig[5..13(2)] or [5-13(2)] ==> use #5, #7, #9, #11, and #13
Sub-brick indexes start at 0. You can use the character '$'
to indicate the last sub-brick in a dataset; for example, you
can select every third sub-brick by using the selection list
fred+orig[0..$(3)]
N.B.: The sub-bricks are read in the order specified, which may
not be the order in the original dataset. For example, using
fred+orig[0..$(2),1..$(2)]
will cause the sub-bricks in fred+orig to be input into memory
in an interleaved fashion. Using
fred+orig[$..0]
will reverse the order of the sub-bricks.
N.B.: You may also use the syntax <A..B> after the name of an input
dataset to restrict the range of values read in to the numerical
values in a..b, inclusive. For example,
fred+orig[5..7]<100..200>
creates a 3 sub-brick dataset with values less than 100 or
greater than 200 from the original set to zero.
If you use the <> sub-range selection without the [] sub-brick
selection, it is the same as if you had put [0..$] in front of
the sub-range selection.
N.B.: Datasets using sub-brick/sub-range selectors are treated as:
- 3D+time if the dataset is 3D+time and more than 1 brick is chosen
- otherwise, as bucket datasets (-abuc or -fbuc)
(in particular, fico, fitt, etc datasets are converted to fbuc!)
N.B.: The characters '$ ( ) [ ] < >' are special to the shell,
so you will have to escape them. This is most easily done by
putting the entire dataset plus selection list inside forward
single quotes, as in 'fred+orig[5..7,9]', or double quotes "x".
** WARNING: you cannot combine sub-brick selection of the form
-b3 bambam+orig (the old method)
with sub-brick selection of the form
-b 'bambam+orig[3]' (the new method)
If you try, the Doom of Mandos will fall upon you!
------------------------------------------------------------------------
1D TIME SERIES:
--------------
You can also input a '*.1D' time series file in place of a dataset.
In this case, the value at each spatial voxel at time index n will be
the same, and will be the n-th value from the time series file.
At least one true dataset must be input. If all the input datasets
are 3D (single sub-brick) or are single sub-bricks from multi-brick
datasets, then the output will be a 'manufactured' 3D+time dataset.
For example, suppose that 'a3D+orig' is a 3D dataset:
3dcalc -a a3D+orig -b b.1D -expr "a*b"
The output dataset will 3D+time with the value at (x,y,z,t) being
computed by a3D(x,y,z)*b(t). The TR for this dataset will be set
to 'tstep' seconds -- this could be altered later with program 3drefit.
Another method to set up the correct timing would be to input an
unused 3D+time dataset -- 3dcalc will then copy that dataset's time
information, but simply do not use that dataset's letter in -expr.
If the *.1D file has multiple columns, only the first read will be
used in this program. You can select a column to be the first by
using a sub-vector selection of the form 'b.1D[3]', which will
choose the 4th column (since counting starts at 0).
'{...}' row selectors can also be used - see the output of '1dcat -help'
for more details on these. Note that if multiple timeseries or 3D+time
or 3D bucket datasets are input, they must all have the same number of
points along the 'time' dimension.
------------------------------------------------------------------------
'1D:' INPUT:
-----------
You can input a 1D time series 'dataset' directly on the command line,
without an external file. The 'filename for such input takes the
general format
'1D:n_1@val_1,n_2@val_2,n_3@val_3,...'
where each 'n_i' is an integer and each 'val_i' is a float. For
example
-a '1D:5@0,10@1,5@0,10@1,5@0'
specifies that variable 'a' be assigned to a 1D time series of 35,
alternating in blocks between values 0 and value 1.
------------------------------------------------------------------------
'I:*.1D' and 'J:*.1D' and 'K:*.1D' INPUT:
----------------------------------------
You can input a 1D time series 'dataset' to be defined as spatially
dependent instead of time dependent using a syntax like:
-c I:fred.1D
This indicates that the n-th value from file fred.1D is to be associated
with the spatial voxel index i=n (respectively j=n and k=n for 'J: and
K: input dataset names). This technique can be useful if you want to
scale each slice by a fixed constant; for example:
-a dset+orig -b K:slicefactor.1D -expr 'a*b'
In this example, the '-b' value only varies in the k-index spatial
direction.
------------------------------------------------------------------------
COORDINATES and PREDEFINED VALUES:
---------------------------------
If you don't use '-x', '-y', or '-z' for a dataset, then the voxel
spatial coordinates will be loaded into those variables. For example,
the expression 'a*step(x*x+y*y+z*z-100)' will zero out all the voxels
inside a 10 mm radius of the origin x=y=z=0.
Similarly, the '-t' value, if not otherwise used by a dataset or *.1D
input, will be loaded with the voxel time coordinate, as determined
from the header file created for the OUTPUT. Please note that the units
of this are variable; they might be in milliseconds, seconds, or Hertz.
In addition, slices of the dataset might be offset in time from one
another, and this is allowed for in the computation of 't'. Use program
3dinfo to find out the structure of your datasets, if you are not sure.
If no input datasets are 3D+time, then the effective value of TR is
tstep in the output dataset, with t=0 at the first sub-brick.
Similarly, the '-i', '-j', and '-k' values, if not otherwise used,
will be loaded with the voxel spatial index coordinates. The '-l'
(letter 'ell') value will be loaded with the temporal index coordinate.
Otherwise undefined letters will be set to zero. In the future,
new default values for other letters may be added.
NOTE WELL: By default, the coordinate order of (x,y,z) is the order in
********* which the data array is stored on disk; this order is output
by 3dinfo. The options below control can change this order:
-dicom }= Sets the coordinates to appear in DICOM standard (RAI) order,
-RAI }= (the AFNI standard), so that -x=Right, -y=Anterior , -z=Inferior,
+x=Left , +y=Posterior, +z=Superior.
-SPM }= Sets the coordinates to appear in SPM (LPI) order,
-LPI }= so that -x=Left , -y=Posterior, -z=Inferior,
+x=Right, +y=Anterior , +z=Superior.
------------------------------------------------------------------------
DIFFERENTIAL SUBSCRIPTS [22 Nov 1999]:
-----------------------
Normal calculations with 3dcalc are strictly on a per-voxel basis:
there is no 'cross-talk' between spatial or temporal locations.
The differential subscript feature allows you to specify variables
that refer to different locations, relative to the base voxel.
For example,
-a fred+orig -b 'a[1,0,0,0]' -c 'a[0,-1,0,0]' -d 'a[0,0,2,0]'
means: symbol 'a' refers to a voxel in dataset fred+orig,
symbol 'b' refers to the following voxel in the x-direction,
symbol 'c' refers to the previous voxel in the y-direction
symbol 'd' refers to the 2nd following voxel in the z-direction
To use this feature, you must define the base dataset (e.g., 'a')
first. Then the differentially subscripted symbols are defined
using the base dataset symbol followed by 4 integer subscripts,
which are the shifts in the x-, y-, z-, and t- (or sub-brick index)
directions. For example,
-a fred+orig -b 'a[0,0,0,1]' -c 'a[0,0,0,-1]' -expr 'median(a,b,c)'
will produce a temporal median smoothing of a 3D+time dataset (this
can be done more efficiently with program 3dTsmooth).
Note that the physical directions of the x-, y-, and z-axes depend
on how the dataset was acquired or constructed. See the output of
program 3dinfo to determine what direction corresponds to what axis.
For convenience, the following abbreviations may be used in place of
some common subscript combinations:
[1,0,0,0] == +i [-1, 0, 0, 0] == -i
[0,1,0,0] == +j [ 0,-1, 0, 0] == -j
[0,0,1,0] == +k [ 0, 0,-1, 0] == -k
[0,0,0,1] == +l [ 0, 0, 0,-1] == -l
The median smoothing example can thus be abbreviated as
-a fred+orig -b a+l -c a-l -expr 'median(a,b,c)'
When a shift calls for a voxel that is outside of the dataset range,
one of three things can happen:
STOP => shifting stops at the edge of the dataset
WRAP => shifting wraps back to the opposite edge of the dataset
ZERO => the voxel value is returned as zero
Which one applies depends on the setting of the shifting mode at the
time the symbol using differential subscripting is defined. The mode
is set by one of the switches '-dsSTOP', '-dsWRAP', or '-dsZERO'. The
default mode is STOP. Suppose that a dataset has range 0..99 in the
x-direction. Then when voxel 101 is called for, the value returned is
STOP => value from voxel 99 [didn't shift past edge of dataset]
WRAP => value from voxel 1 [wrapped back through opposite edge]
ZERO => the number 0.0
You can set the shifting mode more than once - the most recent setting
on the command line applies when a differential subscript symbol is
encountered.
------------------------------------------------------------------------
PROBLEMS:
--------
* Complex-valued datasets cannot be processed.
* This program is not very efficient (but is faster than it once was).
* Differential subscripts slow the program down even more.
------------------------------------------------------------------------
EXPRESSIONS:
-----------
Arithmetic expressions are allowed, using + - * / ** and parentheses.
As noted above, datasets are referred to by single letter variable names.
At this time, C relational, boolean, and conditional expressions are
NOT implemented. Built in functions include:
sin , cos , tan , asin , acos , atan , atan2,
sinh , cosh , tanh , asinh , acosh , atanh , exp ,
log , log10, abs , int , sqrt , max , min ,
J0 , J1 , Y0 , Y1 , erf , erfc , qginv, qg ,
rect , step , astep, bool , and , or , mofn ,
sind , cosd , tand , median, lmode , hmode , mad ,
gran , uran , iran , eran , lran , orstat,
mean , stdev, sem , Pleg
where:
* qg(x) = reversed cdf of a standard normal distribution
* qginv(x) = inverse function to qg
* min, max, atan2 each take 2 arguments ONLY
* J0, J1, Y0, Y1 are Bessel functions (see Watson)
* Pleg(m,x) is the m'th Legendre polynomial evaluated at x
* erf, erfc are the error and complementary error functions
* sind, cosd, tand take arguments in degrees (vs. radians)
* median(a,b,c,...) computes the median of its arguments
* mad(a,b,c,...) computes the MAD of its arguments
* mean(a,b,c,...) computes the mean of its arguments
* stdev(a,b,c,...) computes the standard deviation of its arguments
* sem(a,b,c,...) computes the standard error of the mean of its arguments,
where sem(n arguments) = stdev(same)/sqrt(n)
* orstat(n,a,b,c,...) computes the n-th order statistic of
{a,b,c,...} - that is, the n-th value in size, starting
at the bottom (e.g., orstat(1,a,b,c) is the minimum)
* lmode(a,b,c,...) and hmode(a,b,c,...) compute the mode
of their arguments - lmode breaks ties by choosing the
smallest value with the maximal count, hmode breaks ties by
choosing the largest value with the maximal count
[median,lmode,hmode take a variable number of arguments]
* gran(m,s) returns a Gaussian deviate with mean=m, stdev=s
* uran(r) returns a uniform deviate in the range [0,r]
* iran(t) returns a random integer in the range [0..t]
* eran(s) returns an exponentially distributed deviate
* lran(t) returns a logistically distributed deviate
You may use the symbol 'PI' to refer to the constant of that name.
This is the only 2 letter symbol defined; all input files are
referred to by 1 letter symbols. The case of the expression is
ignored (in fact, it is converted to uppercase as the first step
in the parsing algorithm).
The following functions are designed to help implement logical
functions, such as masking of 3D volumes against some criterion:
step(x) = {1 if x>0 , 0 if x<=0},
astep(x,y) = {1 if abs(x) > y , 0 otherwise} = step(abs(x)-y)
rect(x) = {1 if abs(x)<=0.5, 0 if abs(x)>0.5},
bool(x) = {1 if x != 0.0 , 0 if x == 0.0},
notzero(x) = bool(x),
iszero(x) = 1-bool(x) = { 0 if x != 0.0, 1 if x == 0.0 },
equals(x,y) = 1-bool(x-y) = { 1 if x == y , 0 if x != y },
ispositive(x) = { 1 if x > 0; 0 if x <= 0 },
isnegative(x) = { 1 if x < 0; 0 if x >= 0 },
and(a,b,...,c) = {1 if all arguments are nonzero, 0 if any are zero}
or(a,b,...,c) = {1 if any arguments are nonzero, 0 if all are zero}
mofn(m,a,...,c) = {1 if at least 'm' arguments are nonzero, 0 otherwise}
argmax(a,b,...) = index of largest argument; = 0 if all args are 0
argnum(a,b,...) = number of nonzero arguments
[These last 5 functions take a variable number of arguments.]
The following 27 new [Mar 1999] functions are used for statistical
conversions, as in the program 'cdf':
fico_t2p(t,a,b,c), fico_p2t(p,a,b,c), fico_t2z(t,a,b,c),
fitt_t2p(t,a) , fitt_p2t(p,a) , fitt_t2z(t,a) ,
fift_t2p(t,a,b) , fift_p2t(p,a,b) , fift_t2z(t,a,b) ,
fizt_t2p(t) , fizt_p2t(p) , fizt_t2z(t) ,
fict_t2p(t,a) , fict_p2t(p,a) , fict_t2z(t,a) ,
fibt_t2p(t,a,b) , fibt_p2t(p,a,b) , fibt_t2z(t,a,b) ,
fibn_t2p(t,a,b) , fibn_p2t(p,a,b) , fibn_t2z(t,a,b) ,
figt_t2p(t,a,b) , figt_p2t(p,a,b) , figt_t2z(t,a,b) ,
fipt_t2p(t,a) , fipt_p2t(p,a) , fipt_t2z(t,a) .
See the output of 'cdf -help' for documentation on the meanings of
and arguments to these functions. (After using one of these, you
may wish to use program '3drefit' to modify the dataset statistical
auxiliary parameters.)
Computations are carried out in double precision before being
truncated to the final output 'datum'.
Note that the quotes around the expression are needed so the shell
doesn't try to expand * characters, or interpret parentheses.
(Try the 'ccalc' program to see how the expression evaluator works.
The arithmetic parser and evaluator is written in Fortran-77 and
is derived from a program written long ago by RW Cox to facilitate
compiling on an array processor hooked up to a VAX. It's a mess,
but it works - somewhat slowly.)
This page auto-generated on Thu Aug 25 16:49:36 EDT 2005
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| 3dClipLevel |
Usage: 3dClipLevel [options] dataset
Estimates the value at which to clip the anatomical dataset so
that background regions are set to zero.
Method:
Find the median of all positive values >= clip value.
Set the clip value to 0.50 of this median.
Repeat until the clip value doesn't change.
Options:
-mfrac ff = Use the number ff instead of 0.50 in the algorithm.
-verb = The clip value is always printed to stdout. If
this option is used to select verbose output,
progress reports are printed to stderr as well.
N.B.: This program only works with byte- and short-valued
datasets, and prints a warning message if any input
voxels are negative. If the dataset has more than one
sub-brick, all sub-bricks are used to build the histogram.
N.B.: Use at your own risk! You might want to use the AFNI Histogram
plugin to see if the results are reasonable. This program is
likely to produce bad results on images gathered with local
RF coils, or with pulse sequences with unusual contrasts.
A csh command line for the truly adventurous:
afni -dset "v1:time+orig<`3dClipLevel 'v1:time+orig[4]'` .. 10000>"
(the dataset is from the 'sample96.tgz' data samples). Can you
figure out what this does?
(Hint: each type of quote "'` means something different to csh.)
This page auto-generated on Thu Aug 25 16:49:36 EDT 2005
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| 3dclust |
Program: 3dclust
Author: RW Cox et al
Date: 21 Jul 2005
3dclust - performs simple-minded cluster detection in 3D datasets
This program can be used to find clusters of 'active' voxels and
print out a report about them.
* 'Active' refers to nonzero voxels that survive the threshold
that you (the user) have specified
* Clusters are defined by a connectivity radius parameter 'rmm'
Note: by default, this program clusters on the absolute values
of the voxels
-----------------------------------------------------------------------
Usage: 3dclust [editing options] [other options] rmm vmul dset ...
-----
Examples:
--------
3dclust -1clip 0.3 5 2000 func+orig'[1]'
3dclust -1noneg -1thresh 0.3 5 2000 func+orig'[1]'
3dclust -1noneg -1thresh 0.3 5 2000 func+orig'[1]' func+orig'[3]
3dclust -noabs -1clip 0.5 -dxyz=1 1 10 func+orig'[1]'
3dclust -noabs -1clip 0.5 5 700 func+orig'[1]'
3dclust -noabs -2clip 0 999 -dxyz=1 1 10 func+orig'[1]'
3dclust -1clip 0.3 5 3000 func+orig'[1]'
3dclust -quiet -1clip 0.3 5 3000 func+orig'[1]'
3dclust -summarize -quiet -1clip 0.3 5 3000 func+orig'[1]'
-----------------------------------------------------------------------
Arguments (must be included on command line):
---------
rmm : cluster connection radius (in millimeters).
All nonzero voxels closer than rmm millimeters
(center-to-center distance) to the given voxel are
included in the cluster.
* If rmm = 0, then clusters are defined by nearest-
neighbor connectivity
vmul : minimum cluster volume (micro-liters)
i.e., determines the size of the volume cluster.
* If vmul = 0, then all clusters are kept.
* If vmul < 0, then the absolute vmul is the minimum
number of voxels allowed in a cluster.
dset : input dataset (more than one allowed, but only the
first sub-brick of the dataset)
The results are sent to standard output (i.e., the screen)
-----------------------------------------------------------------------
Options:
-------
* Editing options are as in 3dmerge (see 3dmerge -help)
(including -1thresh, -1dindex, -1tindex, -dxyz=1 options)
* -noabs => Use the signed voxel intensities (not the absolute
value) for calculation of the mean and Standard
Error of the Mean (SEM)
* -summarize => Write out only the total nonzero voxel
count and volume for each dataset
* -nosum => Suppress printout of the totals
* -verb => Print out a progress report (to stderr)
as the computations proceed
* -quiet => Suppress all non-essential output
* -mni => If the input dataset is in +tlrc coordinates, this
option will stretch the output xyz-coordinates to the
MNI template brain.
N.B.1: The MNI template brain is about 5 mm higher (in S),
10 mm lower (in I), 5 mm longer (in PA), and tilted
about 3 degrees backwards, relative to the Talairach-
Tournoux Atlas brain. For more details, see
http://www.mrc-cbu.cam.ac.uk/Imaging/mnispace.html
N.B.2: If the input dataset is not in +tlrc coordinates,
then the only effect is to flip the output coordinates
to the 'LPI' (neuroscience) orientation, as if you
gave the '-orient LPI' option.)
* -isovalue => Clusters will be formed only from contiguous (in the
rmm sense) voxels that also have the same value.
N.B.: The normal method is to cluster all contiguous
nonzero voxels together.
* -isomerge => Clusters will be formed from each distinct value
in the dataset; spatial contiguity will not be
used (but you still have to supply rmm and vmul
on the command line).
N.B.: 'Clusters' formed this way may well have components
that are widely separated!
* -prefix ppp => Write a new dataset that is a copy of the
input, but with all voxels not in a cluster
set to zero; the new dataset's prefix is 'ppp'
N.B.: Use of the -prefix option only affects the
first input dataset
-----------------------------------------------------------------------
E.g., 3dclust -1clip 0.3 5 3000 func+orig'[1]'
The above command tells 3dclust to find potential cluster volumes for
dataset func+orig, sub-brick #1, where the threshold has been set
to 0.3 (i.e., ignore voxels with an activation threshold of >0.3 or
<-0.3. Voxels must be no more than 5 mm apart, and the cluster volume
must be at least 3000 micro-liters in size.
Explanation of 3dclust Output:
-----------------------------
Volume : Number of voxels that make up the volume cluster
CM RL : Center of mass (CM) for the cluster in the Right-Left
direction (i.e., the coordinates for the CM)
CM AP : Center of mass for the cluster in the
Anterior-Posterior direction
CM IS : Center of mass for the cluster in the
Inferior-Superior direction
minRL, maxRL : Bounding box for the cluster, min and max
coordinates in the Right-Left direction
minAP, maxAP : Min and max coordinates in the Anterior-Posterior
direction of the volume cluster
minIS, max IS: Min and max coordinates in the Inferior-Superior
direction of the volume cluster
Mean : Mean value for the volume cluster
SEM : Standard Error of the Mean for the volume cluster
Max Int : Maximum Intensity value for the volume cluster
MI RL : Maximum Intensity value in the Right-Left
direction of the volume cluster
MI AP : Maximum Intensity value in the Anterior-Posterior
direction of the volume cluster
MI IS : Maximum Intensity value in the Inferior-Superior
direction of the volume cluster
-----------------------------------------------------------------------
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