Welcome to FABBER v2.0
Logfile started: /tmp/fsl_V0k80d_ox_asl/basil/step1/logfile
Start time: Tue Oct 13 14:28:52 2015
FABBER release v2.0
Forward Model version:
$Id: fwdmodel_asl_grase.cc,v 1.22 2013/09/04 15:13:00 chappell Exp $
Loading mask data from '/tmp/fsl_V0k80d_ox_asl/mask'
Loading data from '/home/daan/Desktop/PIN43218_t0//nifti/diffdata.nii.gz'
Invalid_option exception caught in fabber:
An exception has been thrown
Runtime error:- Data length (10) does not match model's output length (9)!Trace: VariationalBayesInferenceTechnique::DoCalculations; FABBER main(); FABBER main (outer).
Usage: fabber <arguments>
Arguments are mandatory unless they appear in [brackets].
Use -@ argfile to read additional arguments from a text file.
[--help] : print this usage message
--output=/path/to/output : put output here (including logfile)
--method={vb|spatialvb} : use VB (or VB with spatial priors)
[--max-iterations=NN] : number of iterations of VB to use (default: 10)
[--data-order={interleave|concatenate|singlefile}] : should time points from multiple data be interleaved (e.g. TE1/TE2) or left in order? (default: interleave)
--data1=file1, [--data2=file2]. (use --data=file instead if --data-order=singlefile)
--mask=maskfile : inference will only be performed where mask value > 0
--model={quipss2|q2tips-dualecho|pcasl-dualecho} : forward model to use. For model parameters use fabber --help --model=<model_of_interest>
--noise={ar1|white} : Noise model to use
ar1: two AR(1) models (optional cross-linking between TE1 & TE2)
[--ar1-cross-terms={dual|same|none}] : two types of cross-linking, or none (default: dual)
white: white noise model, optionally with different noise variances at some data points
[--noise-pattern=<phi_index_pattern>] : repeating pattern of noise variances for each data point (e.g. --noise-pattern=12 gives odd and even data points different noise variances)
[--save-model-fit] and [--save-residuals] : Save model fit/residuals files
[--print-free-energy] : Calculate & dump F to the logfile after each update
[--allow-bad-voxels] : Skip to next voxel if a numerical exception occurs (don't stop)
For spatial priors (using --method=spatialvb):
--param-spatial-priors=<choice_of_prior_forms>: Specify a type of prior to use for each forward model parameter. One letter per parameter. S=spatial, N=nonspatial, D=Gaussian-process-based combined prior
--fwd-initial-prior=<prior_vest_file>: specify the nonspatial prior distributions on the forward model parameters. The vest file is the covariance matrix supplemented by the prior means; see the documentation for details. Very important if 'D' prior is used.