#Configuration file tracula
# 
# FreeSurfer SUBJECTS_DIR
# T1 images and FreeSurfer segmentations are expected to be found here
# 
setenv SUBJECTS_DIR /home/rita/Desktop/test/diffusion_recons

# Output directory where trac-all results will be saved
# Default: Same as SUBJECTS_DIR
#
set dtroot = /home/rita/Desktop/test/diffusion_output

# Subject IDs
# Default: Run analysis on all subjects; add set run list specify sub

set subjlist = (MRI_20160226_2_PHD003)

# Input diffusion DICOMs (file names relative to dcmroot)
#
set dcmroot = /home/rita/Desktop/test/diffusion_dcm
set dcmlist = (MRI_20160226_2_PHD003/MRI_20160226_2_PHD003_dwi.nii.gz)

# Diffusion gradient tables (if there is a different one for each scan)
# Default: Read from DICOM header
#
set bvecfile = /home/rita/Desktop/test/diffusion_dcm/MRI_20160226_2_PHD003/MRI_20160226_2_PHD003_bvecs.txt

# Diffusion b-value tables (if there is a different one for each scan)
# Default: Read from DICOM header

set bvalfile = /home/rita/Desktop/test/diffusion_dcm/MRI_20160226_2_PHD003/MRI_20160226_2_PHD003_bvals.txt
#
set nb0 = 1

# Perform registration-based eddy-current compensation?
# Default: 1 (yes)
#
set doeddy = 1

# Rotate diffusion gradient vectors to match eddy-current compensation?
# Default: 1 (yes)
#
set dorotbvecs = 1

# Fractional intensity threshold for BET mask extraction from low-b images (create a mask from the DWIs using FSL's BET) Default: 1 (use T1)

set usemaskanat = 0

set thrbet = 0.25

# Perform diffusion-to-T1 registration by flirt?
# Default: 0 (no)
#
set doregflt = 1

# Perform diffusion-to-T1 registration by bbregister?
# Default: 1 (yes)
#
set doregbbr = 0

# Perform registration of T1 to MNI template?
# Default: 1 (yes)
#
set doregmni = 1

# MNI template
set mnitemp = $FSLDIR/data/standard/MNI152_T1_1mm_brain.nii.gz

# Perform registration of T1 to CVS template?
# Default: 0 (no)
#
set doregcvs = 0

# Use brain mask extracted from T1 image instead of low-b diffusion image?
# Has no effect if there is no T1 data
# Default: 1 (yes)
#
set usemaskanat = 0

# Paths to reconstruct
#
set pathlist = (fminor_PP \
                 lh.slfp_PP rh.slfp_PP \
                 lh.slft_PP rh.slft_PP)

# Number of path control points
# It can be a single number for all paths or a different number for each of the
# paths specified in pathlist
# Default: 7 for the forceps major, 6 for the corticospinal tract,
#          4 for the angular bundle, and 5 for all other paths
#
set ncpts = 5

# List of training subjects
# This text file lists the locations of training subject directories
# Default: $FREESURFER_HOME/trctrain/trainlist.txt
#
set trainfile = $FREESURFER_HOME/trctrain/trainlist.txt

# Number of "sticks" (anisotropic diffusion compartments) in the bedpostx
# ball-and-stick model
# Default: 2
#
set nstick = 2

# Number of MCMC burn-in iterations
# (Path samples drawn initially by MCMC algorithm and discarded)
# Default: 200
#
set nburnin = 200

# Number of MCMC iterations
# (Path samples drawn by MCMC algorithm and used to estimate path distribution)
# Default: 7500
#
set nsample = 7500

# Frequency with which MCMC path samples are retained for path distribution
# Default: 5 (keep every 5th sample)
#
set nkeep = 5

# Reinitialize path reconstruction?
# This is an option of last resort, to be used only if one of the reconstructed
# pathway distributions looks like a single curve. This is a sign that the
# initial guess for the pathway was problematic, perhaps due to poor alignment
# between the individual and the atlas. Setting the reinit parameter to 1 and
# rerunning "trac-all -prior" and "trac-all -path", only for the specific
# subjects and pathways that had this problem, will attempt to reconstruct them
# with a different initial guess.
# Default: 0 (do not reinitialize)
#
set reinit = 0