7.1.163. 3dTsmooth

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Usage: 3dTsmooth [options] dataset Smooths each voxel time series in a 3D+time dataset and produces as output a new 3D+time dataset (e.g., lowpass filter in time).

* Also see program 3dBandpass *

General Options:

-prefix ppp = Sets the prefix of the output dataset to be ‘ppp’.
[default = ‘smooth’]
-datum type = Coerce output dataset to be stored as the given type.
[default = input data type]

Three Point Filtering Options [07 July 1999]

The following options define the smoothing filter to be used. All these filters use 3 input points to compute one output point:

Let a = input value before the current point

b = input value at the current point c = input value after the current point

[at the left end, a=b; at the right end, c=b]
-lin = 3 point linear filter: 0.15*a + 0.70*b + 0.15*c
[This is the default smoother]
-med = 3 point median filter: median(a,b,c)
-osf = 3 point order statistics filter:
0.15*min(a,b,c) + 0.70*median(a,b,c) + 0.15*max(a,b,c)
-3lin m = 3 point linear filter: 0.5*(1-m)*a + m*b + 0.5*(1-m)*c
Here, ‘m’ is a number strictly between 0 and 1.

General Linear Filtering Options [03 Mar 2001]

-hamming N = Use N point Hamming or Blackman windows.
-blackman N (N must be odd and bigger than 1.)
-custom coeff_filename.1D (odd # of coefficients must be in a
single column in ASCII file)
(-custom added Jan 2003)
WARNING: If you use long filters, you do NOT want to include the
large early images in the program. Do something like
3dTsmooth -hamming 13 ‘fred+orig[4..$]’

to eliminate the first 4 images (say).

The following options determing how the general filters treat time points before the beginning and after the end:

-EXTEND = BEFORE: use the first value; AFTER: use the last value
-ZERO = BEFORE and AFTER: use zero
-TREND = compute a linear trend, and extrapolate BEFORE and AFTER

The default is -EXTEND. These options do NOT affect the operation of the 3 point filters described above, which always use -EXTEND.

Adaptive Mean Filtering option [03 Oct 2014]

-adaptive N = use adaptive mean filtering of width N
(where N must be odd and bigger than 3).
  • This filter is similar to the ‘AdptMean9’ 1D filter in the AFNI GUI, except that the end points are treated differently.

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’.

++ Compile date = Dec 16 2015

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