Usage: 3dTshift [options] dataset

* Shifts voxel time series from the input dataset so that the separate
  slices are aligned to the same temporal origin.  By default, uses the
  slicewise shifting information in the dataset header (from the 'tpattern'
  input to program to3d).

Method:  detrend -> interpolate -> retrend (optionally)

* The input dataset can have a sub-brick selector attached, as documented
  in '3dcalc -help'.

* The output dataset time series will be interpolated from the input to
  the new temporal grid.  This may not be the best way to analyze your
  data, but it can be convenient.

* Slices where significant time interpolation happens will have extra
  temporal autocorrelation introduced by the interpolation. The amount
  of extra correlation along the time axis depends on the type of
  interpolation used. Higher order interpolation will produce smaller
  such 'extra' correlation; in order, from lowest (most extra correlation)
  to highest (least extra correlation):
       -linear    -cubic     -quintic   -heptic
       -wsinc5    -wsinc9    -Fourier
* The last two methods do not add much correlation in time. However, they
   have the widest interpolation 'footprint' and so the output data values
   will have contributions from data points further away in time.
* To properly account for these extra correlations, which vary in space,
   we advise you to analyze the time series using 3dREMLfit, which uses
   a voxel-dependent prewhitening (de-correlating) linear regression method,
   unlike most other FMRI time series regression software.
 ++ Or else  use '-wsinc9' interpolation, which has a footprint of 18 time points:
    9 before and 9 after the intermediate time at which the value is output.

* Please recall the phenomenon of 'aliasing': frequencies above 1/(2*TR) can't
  be properly interpolated.  For most 3D FMRI data, this means that cardiac
  and respiratory effects will not be treated properly by this program.

* The images at the beginning of a high-speed FMRI imaging run are usually
  of a different quality than the later images, due to transient effects
  before the longitudinal magnetization settles into a steady-state value.
  These images should not be included in the interpolation!  For example,
  if you wish to exclude the first 4 images, then the input dataset should
  be specified in the form 'prefix+orig[4..$]'.  Alternatively, you can
  use the '-ignore ii' option.

* It seems to be best to use 3dTshift before using 3dvolreg.
  (But this statement is controversial.)

* If the input dataset does not have any slice timing information, and
  '-tpattern' is not given, then this program just copies the input to
  the output.  [02 Nov 2011 -- formerly, it failed]

* Please consider the potential impact of 3dTshift on any subsequent
  linear regression model.  While the temporal resampling of 3dTshift is
  not exact, it is attempting to interpolate the slice timing so that it
  is as if each volume were acquired at time 'tzero' + k*TR.  So with
  -tzero 0, it becomes akin to each entire volume being acquired at the
  very beginning of its TR.  By default, the offset is the average offset
  across the slices, which for alt+z or seq is:
              (nslices-1)/nslices * TR/2
  That average approaches TR/2 as the number of slices increases.

  The new slice/volume timing is intended to be the real timing from the
  start of the run.

  How might this affect stimulus timing in 3dDeconvolve?
  3dDeconvolve creates regressors based on volume times of k*TR, matching
  tzero=0.  So an event at run time t=0 would start at the time of volume
  #0.  However using -tzero 1 (or the default, in the case of TR~=2s),
  an event at run time t=0 would then be 1s *before* the first volume.
  Note that this matches reality.  An event at time t=0 happens before
  all but the first acquired slice.  In particular, a slice acquired at
  TR offset 1s might be unaffected by 3dTshift.  And an event at run time
  t=0 seems to happen at time t=-1s from the perspective of that slice.

  To align stimulus times with the applied tzero of 3dTshift, tzero
  should be subtracted from each stimulus event time (3dDeconvolve
  effectively subtracts tzero from the EPI timing, so that should be
  applied to the event times as well).

  -verbose      = print lots of messages while program runs

  -TR ddd       = use 'ddd' as the TR, rather than the value
                  stored in the dataset header using to3d.
                  You may attach the suffix 's' for seconds,
                  or 'ms' for milliseconds.

  -tzero zzz    = align each slice to time offset 'zzz';
                  the value of 'zzz' must be between the
                  minimum and maximum slice temporal offsets.
            N.B.: The default alignment time is the average
                  of the 'tpattern' values (either from the
                  dataset header or from the -tpattern option)

  -slice nnn    = align each slice to the time offset of slice
                  number 'nnn' - only one of the -tzero and
                  -slice options can be used.

  -prefix ppp   = use 'ppp' for the prefix of the output file;
                  the default is 'tshift'.

  -ignore ii    = Ignore the first 'ii' points. (Default is ii=0.)
                  The first ii values will be unchanged in the output
                  (regardless of the -rlt option).  They also will
                  not be used in the detrending or time shifting.

  -rlt          = Before shifting, the mean and linear trend
  -rlt+         = of each time series is removed.  The default
                  action is to add these back in after shifting.
                  -rlt  means to leave both of these out of the output
                  -rlt+ means to add only the mean back into the output
                  (cf. '3dTcat -help')

  -no_detrend   = Do not remove or restore linear trend.
                  Heptic becomes the default interpolation method.

 ** Options to choose the temporal interpolation method: **
  -Fourier = Use a Fourier method (the default: most accurate; slowest).
  -linear  = Use linear (1st order polynomial) interpolation (least accurate).
  -cubic   = Use the cubic (3rd order) Lagrange polynomial interpolation.
  -quintic = Use the quintic (5th order) Lagrange polynomial interpolation.
  -heptic  = Use the heptic (7th order) Lagrange polynomial interpolation.
  -wsinc5  = Use weighted sinc interpolation - plus/minus 5 [Aug 2019].
  -wsinc9  = Use weighted sinc interpolation - plus/minus 9.

  -tpattern ttt = use 'ttt' as the slice time pattern, rather
                  than the pattern in the input dataset header;
                  'ttt' can have any of the values that would
                  go in the 'tpattern' input to to3d, described below:

   alt+z = altplus   = alternating in the plus direction
   alt+z2            = alternating, starting at slice #1 instead of #0
   alt-z = altminus  = alternating in the minus direction
   alt-z2            = alternating, starting at slice #nz-2 instead of #nz-1
   seq+z = seqplus   = sequential in the plus direction
   seq-z = seqminus  = sequential in the minus direction
   @filename         = read temporal offsets from 'filename'

  For example if nz = 5 and TR = 1000, then the inter-slice
  time is taken to be dt = TR/nz = 200.  In this case, the
  slices are offset in time by the following amounts:

             S L I C E   N U M B E R
   tpattern    0   1   2   3   4   Comment
   --------- --- --- --- --- ---   -------------------------------
   altplus     0 600 200 800 400   Alternating in the +z direction
   alt+z2    400   0 600 200 800   Alternating, but starting at #1
   altminus  400 800 200 600   0   Alternating in the -z direction
   alt-z2    800 200 600   0 400   Alternating, starting at #nz-2
   seqplus     0 200 400 600 800   Sequential  in the +z direction
   seqminus  800 600 400 200   0   Sequential  in the -z direction

  If @filename is used for tpattern, then nz ASCII-formatted numbers
  are read from the file.  These indicate the time offsets for each
  slice. For example, if 'filename' contains
     0 600 200 800 400
  then this is equivalent to 'altplus' in the above example.
  (nz = number of slices in the input dataset)

  Note that 1D format can be used with @filename.  For example, to shift
  a single voxel time series given TR=2.0, and adjusting the old toffset
  from 0.5 s to 0 s, consider:

    3dTshift -prefix new.1D -TR 2 -tzero 0 -tpattern '@1D: 0.5' old.1D\'

  For a conceptual test of 3dTshift, consider a sequence of commands:
     1deval -num 25 -expr t+10 > t0.1D
     3dTshift -linear -no_detrend -TR 1 -tzero 0 -tpattern '@1D: 0.5' \
              -prefix t.shift.1D t0.1D\'
     1dplot -one t0.1D t.shift.1D
  Recall from your memorization of the -help that 3dTshift performs the
  shift on a detrended time series.  Hence the '--linear -no_detrend'
  options are included (otherwise, the line would be unaltered).
  Also, be aware that since we are asking to interpolate the data so that
  it is as if it were acquired 0.5 seconds earlier, that is moving the
  time window to the left, and therefore the plot seems to move to the

N.B.: if you are using -tpattern, make sure that the units supplied
      match the units of TR in the dataset header, or provide a
      new TR using the -TR option.

As a test of how well 3dTshift interpolates, you can take a dataset
that was created with '-tpattern alt+z', run 3dTshift on it, and
then run 3dTshift on the new dataset with '-tpattern alt-z' -- the
effect will be to reshift the dataset back to the original time
grid.  Comparing the original dataset to the shifted-then-reshifted
output will show where 3dTshift does a good job and where it does
a bad job.

******* Voxel-Wise Shifting -- New Option [Sep 2011] *******

 -voxshift fset = Read in dataset 'fset' and use the values in there
                  to shift each input dataset's voxel's time series a
                  different amount.  The values in 'fset' are NOT in
                  units of time, but rather are fractions of a TR
                  to shift -- a positive value means to shift backwards.
                 * To compute an fset-style dataset that matches the
                   time pattern of an existing dataset, try
       set TR = 2.5
       3dcalc -a 'dset+orig[0..1]' -datum float -prefix Toff -expr "t/${TR}-l"
                   where you first set the shell variable TR to the true TR
                   of the dataset, then create a dataset Toff+orig with the
                   fractional shift of each slice stored in each voxel.  Then
                   the two commands below should give identical outputs:
       3dTshift -ignore 2 -tzero 0 -prefix Dold -heptic dset+orig
       3dTshift -ignore 2 -voxshift Toff+orig -prefix Dnew -heptic dset+orig

 Use of '-voxshift' means that options such as '-tzero' and '-tpattern' are
 ignored -- the burden is on you to encode all the shifts into the 'fset'
 dataset somehow.  (3dcalc can be your friend here.)

-- RWCox - 31 October 1999, et cetera

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'.

++ Compile date = Feb 22 2024 {AFNI_24.0.08:linux_ubuntu_16_64}