I get an error for specifying fbot ftop as 0.01 and 0.1 respectively in 3dRSFC. same bandpass works fine in Instacorr for the time series used. any insights? I am suspecting program may not expect in Hz even though the manual says so. error message below

++ 3dRSFC (from 3dBandpass by RW Cox): version THETA: AFNI version=AFNI_16.1.06 (Apr 19 2016) [64-bit]
++ Authored by: PA Taylor
++ Data length = 7680 FFT length = 7680

  • bandpass: ntime=7680 nFFT=7680 dt=2.5 dFreq=5.20833e-05 Nyquist=0.2 passband indexes=192…1920
    ++ Loading input dataset time series
    ++ Number of voxels in automask = 31784
    ++ Checking dataset for initial transients [use ‘-notrans’ to skip this test]
  • No widespread initial positive transient detected :slight_smile:
    ++ Bandpassing data time series
    ++ Creating output dataset in memory, then writing it
    ++ Output dataset ./RSFC_dspk_detrend_pct_tcat_in_D99_errts_censorkmeans_rbebase+tlrc.BRIK
    ++ Bandpassing data time series
    ** ERROR: bandpass: fbot and ftop too close ==> jbot=0 jtop=-2147483648 (df=0.000052)
    ++ Creating output dataset 2 in memory
    ++ Starting the (f)ALaFFel calcs

OK, I think I’ve found the issue: there was a variable in 3dRSFC initialized to be “frequency greater than Nyquist” in order to provide an upper limit of the “full band” denominator in the fALFF calculation. This number was very big, so dividing by such a small df (=1/(TR * Nt), where Nt was very large in this time series), produced a numerical error. I’ve set the initialized frequency to be smaller, but still greater than Nyquist, so this problem won’t occur.

I’ve push in the changes, so in the next update, this problem should be solved. Let me know if there are further issues with it.


ps: that’s a really long duration time series-- what patient subjects you must have!

→ I just tried updating my binaries:
$ @update.afni.binaries -d

and 3dRSFC in the new AFNI v16.2.07 (“afni -ver”) didn’t complain at me, so it should be good to go.