Usage: 3dRetinoPhase [-prefix ppp]  dataset
   where dataset is a time series from a retinotpy stimulus

 -exp EXP: These four options specify the type of retinotpy
 -con CON: stimulus. EXP and CON are for expanding and
 -clw CLW : contracting rings, respectively. CLW and CCW are
 -ccw CCW: for clockwise and counter clockwise moving polar
           polar angle mapping stimuli. You can specify one,
           or all stimuli in one command. When all are specified
           polar angle stimuli, and eccentricity stimuli of
           opposite directions are combined.
 -prefix PREF: Prefix of output datasets.
           PREF is suffixed with the following:
           .ecc+ for positive (expanding) eccentricity (EXP)
           .ecc- for negative (contracting) eccentricity (CON)
           .pol+ for clockwise polar angle mapping (CLW)
           .pol- for counterclockwise polar angle mapping (CCW)
  At a minimum each input gets a phase dataset output. It contains
     response phase (or delay) in degrees.
     If both directions are given for polar and/or eccentricity
     then a visual field angle data set is created.
     The visual field angle is obtained by averaging phases of opposite
     direction stimuli. The hemodynamic offset is half the phase difference.

  Each output also contains a thresholding sub-brick. Its type
     depends on the phase estimation method (-phase_estimate).

                 Note on the thresholding sub-bricks
  Both FFT and DELAY values of -phase_estimate produce thresholding
     sub-bricks with the phase estimates. Those thresholds have associated
     significance levels, but they should be taken with a grain of
     salt. There is no correction for autocorrelation, so the DOFs
     are generous.
  The program also attaches a thresholding sub-brick to the
     visual field angle datasets which are estimated by averaging the phase
     estimates in order to remove the hemodynamic offset. This composite
     thresholding sub-brick contains at each voxel/node, the maximum
     threshold from the datasets of stimli of opposite direction.
  This thresholding sub-brick is for convenience, allowing you to
     threshold with a mask that is the union of the individual
     thresholded maps. Significance levels are purposefully not
     attached. I don't know how to compute them properly.

 -spectra: Output amplitude and phase spectra datasets.
 -Tstim T: Period of stimulus in seconds. This parameter does
           not depend on the number of wedges or rings (Nr/Nw).
           It is the duration of a full cycle of the stimulus.
           Use -Tpol TPOL, and -Tecc TECC, to specify periods
           for each stimulus type separately. -Tstim sets both
           periods to T.
 -nrings Nr: Nr is the number of rings in the stimulus.
              The default is 1.
 -nwedges Nw: Nw is the number of wedges in the stimulus.
              The default is 1.
 -ort_adjust: Number of DOF lost in detrending outside of this
 -pre_stim PRE: Blank period, in seconds, before stimulus began
 -sum_adjust y/n: Adjust sum of angles for wrapping based on the
                  angle difference. Default is 'y'
 -phase_estimate METH: Select method of phase estimation
       METH == FFT  uses the phase of the fundamental frequency.
       METH == DELAY uses the 3ddelay approach for estimating
                     the phase. This requires the use of option
                     -ref_ts . See references [3] and [4] below.
       The DELAY option appears to be good as the FFT for high SNR
          and high duty cycle. See results produced by @Proc.PK.All_D
          in the demo archive AfniRetinoDemo.tgz.
       However,the DELAY option seems much better for low duty cycle stimuli.
       It is not set as the default for backward compatibility. Positive and
          negative feedback about this option are welcome.

     Thanks to Ikuko Mukai and Masaki Fukunaga for making the case
        for DELAY's addition; they were right.

 -ref_ts REF_TS: 0 lag reference time series of response. This is
                 needed for the DELAY phase estimation method.
      With the DELAY method, the phase results are comparable to
        what you'd get with the following 3ddelay command:
        For illustration, say you have stimuli of 32 second periods
        with the polar stimuli having two wedges. After creating
        the reference time series with waver (32 sec. block period
        eccentricity, 32/2=16 sec. block period for polar), run
        4 3ddelay commands as such:
                      for an expanding ring of 32 second period:
           3ddelay  -input exp.niml.dset \
                    -ideal_file ECC.1D   \
                    -fs 0.5  -T 32 \
                    -uD -nodsamp \
                    -phzreverse -phzscale 1.0 \
                    -prefix ecc+.del.niml.dset\n
              Repeat for contracting ring, remove -phzreverse

                       for clockwise two wedge of 32 second period:
           3ddelay  -input clw.niml.dset \
                    -ideal_file POL.1D   \
                    -fs 0.5  -T 16 \
                    -uD -nodsamp \
                    -phzreverse -phzscale 0.5 \
                    -prefix pol+.del.niml.dset\n
              Repeat for counterclockwise remove -phzreverse
     Instead of the 3ddelay mess, all you do is run 3dRetinoPhase with the
        following extra options:               -phase_estimate DELAY -ref_ts ECC.1D
        or    -phase_estimate DELAY -ref_ts POL.1D

     If you are not familiar with the use of program 'waver' for creating
     reference time series, take a look at demo script @Proc.PK.All_D in

 -multi_ref_ts MULTI_REF_TS: Multiple 0 lag reference time series.
                             This allows you to test multiple regressors.
                             The program will run a separate analysis for
                             each regressor (column), and combine the results
                             in the output dataset this way:
       ([.] denotes output sub-brick)
       [0]: Phase from regressor that yields the highest correlation coeff.
       [1]: Maximum correlation coefficient.
       [2]: Number of regressor that yields the highest correlation coeff.
            Counting begins at 1 (not 0)
       [3]: Phase from regressor 1
       [4]: Correlation coefficient from regressor 1
       [5]: Phase from regressor 2
       [6]: Correlation coefficient from regressor 2
       ... etc.
       In general, for regressor k (k starts at 1)
          [2*k+1] contains the Phase and [2*k+2] the Correlation coefficient

  N.B: If MULTI_REF_TS has only one timeseries, -multi_ref_ts produces
       an output identical to that of -ref_ts.

  See usage in @RetinoProc and demo data in

References for this program:
   [1] RW Cox.  AFNI: Software for analysis and visualization of functional
                      magnetic resonance neuroimages.
                      Computers and Biomedical Research, 29: 162-173, 1996.
   [2] Saad Z.S., et al.  SUMA: An Interface For Surface-Based Intra- And
                      Inter-Subject Analysis With AFNI.
     Proc. 2004 IEEE International Symposium on Biomedical Imaging, 1510-1513
   If you use the DELAY method:
   [3] Saad, Z.S., et al. Analysis and use of FMRI response delays.
         Hum Brain Mapp, 2001. 13(2): p. 74-93.
   [4] Saad, Z.S., E.A. DeYoe, and K.M. Ropella, Estimation of FMRI
         Response Delays.  Neuroimage, 2003. 18(2): p. 494-504.

++ Compile date = Jan 21 2020 {AFNI_20.0.01:linux_ubuntu_16_64}