[med-svn] [Git][med-team/bart][master] update commands.txt added in Debian patch

Martin Uecker (@uecker-guest) gitlab at salsa.debian.org
Sun Sep 25 14:30:51 BST 2022



Martin Uecker pushed to branch master at Debian Med / bart


Commits:
0e2fe50c by Martin Uecker at 2022-09-25T15:25:10+02:00
update commands.txt added in Debian patch

- - - - -


1 changed file:

- debian/patches/0005-do-not-update-doc-commands.txt-automatically.patch


Changes:

=====================================
debian/patches/0005-do-not-update-doc-commands.txt-automatically.patch
=====================================
@@ -4,8 +4,8 @@ Subject: do not update doc/commands.txt automatically
 
 ---
  Makefile         |    4 +-
- doc/commands.txt | 1403 ++++++++++++++++++++++++++++++++++++++++++++++++++++++
- 2 files changed, 1405 insertions(+), 2 deletions(-)
+ doc/commands.txt | 1593 ++++++++++++++++++++++++++++++++++++++++++++++++++++++
+ 2 files changed, 1595 insertions(+), 2 deletions(-)
  create mode 100644 doc/commands.txt
 
 diff --git a/Makefile b/Makefile
@@ -32,1218 +32,1407 @@ index 46a8891..15dd73b 100644
  	touch isclean
 diff --git a/doc/commands.txt b/doc/commands.txt
 new file mode 100644
-index 0000000..2650973
+index 0000000..10676f7
 --- /dev/null
 +++ b/doc/commands.txt
-@@ -0,0 +1,1403 @@
+@@ -0,0 +1,1593 @@
 +AUTOGENERATED. DO NOT EDIT.
 +
 +
 +--avg--
 +
-+Usage: avg [-w] <bitmask> <input> <output>
++Usage: avg [-w] bitmask <input> <output> 
 +
 +Calculates (weighted) average along dimensions specified by bitmask.
 +
-+-w		weighted average
-+-h		help
++-w    weighted average
++-h    help
 +
 +
 +--bench--
 +
-+Usage: bench [-T] [-S] [-s d] [<output>]
++Usage: bench [-T] [-S] [-s d] [<output>] 
 +
 +Performs a series of micro-benchmarks.
 +
-+-T		varying number of threads
-+-S		varying problem size
-+-s flags      	select benchmarks
-+-h		help
++-T          varying number of threads
++-S          varying problem size
++-s flags    select benchmarks
++-h          help
 +
 +
 +--bin--
 +
-+Usage: bin [-l d] [-o] [-R d] [-C d] [-r ...] [-c ...] [-a d] [-A d] [-x <string>] <label> <src> <dst>
++Usage: bin [-l d] [-o] [-R d] [-C d] [-a d] [-O f:f] [-M] <label> <src> <dst> 
 +
 +Binning
 +
-+
-+-l dim      	Bin according to labels: Specify cluster dimension
-+-o		Reorder according to labels
-+-R n_resp      	Quadrature Binning: Number of respiratory labels
-+-C n_card      	Quadrature Binning: Number of cardiac labels
-+-r x:y      	(Respiration: Eigenvector index)
-+-c x:y      	(Cardiac motion: Eigenvector index)
-+-a window      	Quadrature Binning: Moving average
-+-A window      	(Quadrature Binning: Cardiac moving average window)
-+-x file      	(Output filtered cardiac EOFs)
-+-h		help
++-l dim         Bin according to labels: Specify cluster dimension
++-o             Reorder according to labels
++-R n_resp      Quadrature Binning: Number of respiratory labels
++-C n_card      Quadrature Binning: Number of cardiac labels
++-a window      Quadrature Binning: Moving average
++-O [r:c]deg    Quadrature Binning: Angle offset for resp and card.
++-M             Amplitude binning
++-h             help
 +
 +
 +--bitmask--
 +
-+Usage: bitmask [-b] -b <bitmask> | <dim1> ... <dimN>
++Usage: bitmask [-b] [dim1 ... dimN ] 
 +
 +Convert between a bitmask and set of dimensions.
 +
-+-b		dimensions from bitmask
-+-h		help
++-b    dimensions from bitmask, use with exactly one argument
++-h    help
 +
 +
 +--cabs--
 +
-+Usage: cabs <input> <output>
++Usage: cabs <input> <output> 
 +
 +Absolute value of array (|<input>|).
 +
-+-h		help
++-h  help
 +
 +
 +--caldir--
 +
-+Usage: caldir cal_size <input> <output>
++Usage: caldir cal_size <input> <output> 
 +
 +Estimates coil sensitivities from the k-space center using
 +a direct method (McKenzie et al.). The size of the fully-sampled
 +calibration region is automatically determined but limited by
 +{cal_size} (e.g. in the readout direction).
 +
-+-h		help
++-h  help
 +
 +
 +--calmat--
 +
-+Usage: calmat [-k ...] [-r ...] <kspace> <calibration matrix>
++Usage: calmat [-k d:d:d] [-r d:d:d] <kspace> <calibration_matrix> 
 +
 +Compute calibration matrix.
 +
-+-k ksize      	kernel size
-+-r cal_size      	Limits the size of the calibration region.
-+-h		help
++-k ksize       kernel size
++-r cal_size    Limits the size of the calibration region.
++-h             help
 +
 +
 +--carg--
 +
-+Usage: carg <input> <output>
++Usage: carg <input> <output> 
 +
 +Argument (phase angle).
 +
-+-h		help
++-h  help
 +
 +
 +--casorati--
 +
-+Usage: casorati dim1 kern1 dim2 kern2 ... dimn kernn <input> <output>
-+
-+Casorati matrix with kernel (kern1, ..., kernn) along dimensions (dim1, ..., dimn).
++Usage: casorati dim1 kern1 ... dimN kernN <input> <output> 
 +
++Casorati matrix with kernel (kern1, ..., kernN) along dimensions (dim1, ..., dimN).
 +
-+-h		help
++-h  help
 +
 +
 +--cc--
 +
-+Usage: cc [-p d] [-M] [-r ...] [-A] [-S ...] [-G ...] [-E ...] <kspace> <coeff>|<proj_kspace>
++Usage: cc [-p d] [-M] [-r d:d:d] [-A] [-S] [-G] [-E] <kspace> <coeff|proj_kspace> 
 +
 +Performs coil compression.
 +
-+-p N      	perform compression to N virtual channels
-+-M		output compression matrix
-+-r S      	size of calibration region
-+-A		use all data to compute coefficients
-+-S		type: SVD
-+-G		type: Geometric
-+-E		type: ESPIRiT
-+-h		help
++-p N    perform compression to N virtual channels
++-M      output compression matrix
++-r S    size of calibration region
++-A      use all data to compute coefficients
++-S      type: SVD
++-G      type: Geometric
++-E      type: ESPIRiT
++-h      help
 +
 +
 +--ccapply--
 +
-+Usage: ccapply [-p d] [-u] [-t] [-S ...] [-G ...] [-E ...] <kspace> <cc_matrix> <proj_kspace>
++Usage: ccapply [-p d] [-u] [-t] [-S] [-G] [-E] <kspace> <cc_matrix> <proj_kspace> 
 +
 +Apply coil compression forward/inverse operation.
 +
-+-p N      	perform compression to N virtual channels
-+-u		apply inverse operation
-+-t		don't apply FFT in readout
-+-S		type: SVD
-+-G		type: Geometric
-+-E		type: ESPIRiT
-+-h		help
++-p N    perform compression to N virtual channels
++-u      apply inverse operation
++-t      don't apply FFT in readout
++-S      type: SVD
++-G      type: Geometric
++-E      type: ESPIRiT
++-h      help
 +
 +
 +--cdf97--
 +
-+Usage: cdf97 [-i] bitmask <input> <output>
++Usage: cdf97 [-i] bitmask <input> <output> 
 +
 +Perform a wavelet (cdf97) transform.
 +
-+
-+-i		inverse
-+-h		help
++-i    inverse
++-h    help
 +
 +
 +--circshift--
 +
-+Usage: circshift dim shift <input> <output>
++Usage: circshift dim shift <input> <output> 
 +
 +Perform circular shift along {dim} by {shift} elements.
 +
-+-h		help
++-h  help
 +
 +
 +--conj--
 +
-+Usage: conj <input> <output>
++Usage: conj <input> <output> 
 +
 +Compute complex conjugate.
 +
-+-h		help
++-h  help
 +
 +
 +--conv--
 +
-+Usage: conv bitmask <input> <kernel> <output>
++Usage: conv bitmask <input> <kernel> <output> 
 +
 +Performs a convolution along selected dimensions.
 +
-+-h		help
++-h  help
 +
 +
 +--conway--
 +
-+Usage: conway [-P] [-n d] <input> <output>
++Usage: conway [-P] [-n d] <input> <output> 
 +
 +Conway's game of life.
 +
-+
-+-P		periodic boundary conditions
-+-n #      	nr. of iterations
-+-h		help
++-P      periodic boundary conditions
++-n #    nr. of iterations
++-h      help
 +
 +
 +--copy--
 +
-+Usage: copy [dim1 pos1 ... dimn posn] <input> <output>
++Usage: copy [dim1 pos1 ... dimN posN ] <input> <output> 
 +
 +Copy an array (to a given position in the output file - which then must exist).
 +
-+-h		help
++-h  help
 +
 +
 +--cpyphs--
 +
-+Usage: cpyphs <input> <output
++Usage: cpyphs <input> <output> 
 +
 +Copy phase from <input> to <output>.
 +
-+-h		help
++-h  help
 +
 +
 +--creal--
 +
-+Usage: creal <input> <output>
++Usage: creal <input> <output> 
 +
 +Real value.
 +
-+-h		help
++-h  help
 +
 +
 +--crop--
 +
-+Usage: crop dimension size <input> <output>
++Usage: crop dimension size <input> <output> 
 +
 +Extracts a sub-array corresponding to the central part of {size} along {dimension}
 +
-+-h		help
++-h  help
 +
 +
 +--delta--
 +
-+Usage: delta dims flags size out
++Usage: delta dims flags size <out> 
 +
 +Kronecker delta.
 +
-+-h		help
++-h  help
 +
 +
 +--ecalib--
 +
-+Usage: ecalib [-t f] [-c f] [-k ...] [-r ...] [-m d] [-S] [-W] [-I] [-1] [-P] [-v f] [-a] [-d d] <kspace> <sensitivites> [<ev-maps>]
++Usage: ecalib [-t f] [-c f] [-k d:d:d] [-r d:d:d] [-m d] [-S] [-W] [-I] [-1] [-P] [-v f] [-a] [-d d] <kspace> <sensitivities> [<ev-maps>] 
 +
 +Estimate coil sensitivities using ESPIRiT calibration.
 +Optionally outputs the eigenvalue maps.
 +
-+-t threshold      	This determined the size of the null-space.
-+-c crop_value      	Crop the sensitivities if the eigenvalue is smaller than {crop_value}.
-+-k ksize      	kernel size
-+-r cal_size      	Limits the size of the calibration region.
-+-m maps      	Number of maps to compute.
-+-S		create maps with smooth transitions (Soft-SENSE).
-+-W		soft-weighting of the singular vectors.
-+-I		intensity correction
-+-1		perform only first part of the calibration
-+-P		Do not rotate the phase with respect to the first principal component
-+-v variance      	Variance of noise in data.
-+-a		Automatically pick thresholds.
-+-d level      	Debug level
-+-h		help
++-t threshold     This determined the size of the null-space.
++-c crop_value    Crop the sensitivities if the eigenvalue is smaller than {crop_value}.
++-k ksize         kernel size
++-r cal_size      Limits the size of the calibration region.
++-m maps          Number of maps to compute.
++-S               create maps with smooth transitions (Soft-SENSE).
++-W               soft-weighting of the singular vectors.
++-I               intensity correction
++-1               perform only first part of the calibration
++-P               Do not rotate the phase with respect to the first principal component
++-v variance      Variance of noise in data.
++-a               Automatically pick thresholds.
++-d level         Debug level
++-h               help
 +
 +
 +--ecaltwo--
 +
-+Usage: ecaltwo [-c f] [-m d] [-S] x y z <input> <sensitivities> [<ev_maps>]
++Usage: ecaltwo [-c f] [-m d] [-S] x y z <input> <sensitivities> [<ev-maps>] 
 +
 +Second part of ESPIRiT calibration.
 +Optionally outputs the eigenvalue maps.
 +
-+-c crop_value      	Crop the sensitivities if the eigenvalue is smaller than {crop_value}.
-+-m maps      	Number of maps to compute.
-+-S		Create maps with smooth transitions (Soft-SENSE).
-+-h		help
++-c crop_value    Crop the sensitivities if the eigenvalue is smaller than {crop_value}.
++-m maps          Number of maps to compute.
++-S               Create maps with smooth transitions (Soft-SENSE).
++-h               help
++
++
++--epg--
++
++Usage: epg [-C] [-M] [-H] [-F] [-S] [-B] [-1 f] [-2 f] [-b f] [-o f] [-r f] [-e f] [-f f] [-s d] [-n d] [-u d] [-v d] <signal intensity> [<configuration states>] [<(rel.) signal derivatives>] [<configuration derivatives>] 
++
++Simulate MR pulse sequence based on Extended Phase Graphs (EPG)
++
++-C        CPMG
++-M        fmSSFP
++-H        Hyperecho
++-F        FLASH
++-S        Spinecho
++-B        bSSFP
++-1 T1     T1 [units of time]
++-2 T2     T2 [units of time]
++-b B1     relative B1 [unitless]
++-o OFF    off-resonance [units of inverse time]
++-r TR     repetition time [units of time]
++-e TE     echo time [units of time]
++-f FA     flip angle [degrees]
++-s SP     spoiling (0: ideal, 1: conventional RF, 2: random RF)
++-n N      number of pulses
++-u U      unknowns as bitmask (0: T1, 1: T2, 2: B1, 3: off-res)
++-v V      verbosity level
++-h        help
 +
 +
 +--estdelay--
 +
-+Usage: estdelay [-R] [-p d] [-n d] [-r f] <trajectory> <data> [<qf>]
++Usage: estdelay [-R] [-p d] [-n d] [-r f] <trajectory> <data> [<qf>] 
 +
 +Estimate gradient delays from radial data.
 +
-+-R		RING method
-+-p p      	[RING] Padding
-+-n n      	[RING] Number of intersecting spokes
-+-r r      	[RING] Central region size
-+-h		help
++-R      RING method
++-p p    [RING] Padding
++-n n    [RING] Number of intersecting spokes
++-r r    [RING] Central region size
++-h      help
 +
 +
 +--estdims--
 +
-+Usage: estdims <traj>
++Usage: estdims <traj> 
 +
 +Estimate image dimension from non-Cartesian trajectory.
 +Assume trajectory scaled to -DIM/2 to DIM/2 (ie dk=1/FOV=1)
 +
-+-h		help
++-h  help
 +
 +
 +--estshift--
 +
-+Usage: estshift flags <arg1> <arg2>
++Usage: estshift flags <arg1> <arg2> 
 +
 +Estimate sub-pixel shift.
 +
-+-h		help
++-h  help
 +
 +
 +--estvar--
 +
-+Usage: estvar [-k ...] [-r ...] <kspace>
++Usage: estvar [-k d:d:d] [-r d:d:d] <kspace> 
 +
 +Estimate the noise variance assuming white Gaussian noise.
 +
-+-k ksize      	kernel size
-+-r cal_size      	Limits the size of the calibration region.
-+-h		help
++-k ksize       kernel size
++-r cal_size    Limits the size of the calibration region.
++-h             help
 +
 +
 +--extract--
 +
-+Usage: extract dim1 start1 end1 ... dimn startn endn <input> <output>
++Usage: extract dim1 start1 end1 ... dimN startN endN <input> <output> 
 +
 +Extracts a sub-array along dims from index start to (not including) end..
 +
-+
-+-h		help
++-h  help
 +
 +
 +--fakeksp--
 +
-+Usage: fakeksp [-r] <image> <kspace> <sens> <output>
++Usage: fakeksp [-r] <image> <kspace> <sens> <output> 
 +
 +Recreate k-space from image and sensitivities.
 +
-+-r		replace measured samples with original values
-+-h		help
++-r    replace measured samples with original values
++-h    help
 +
 +
 +--fft--
 +
-+Usage: fft [-u] [-i] [-n] bitmask <input> <output>
++Usage: fft [-u] [-i] [-n] bitmask <input> <output> 
 +
 +Performs a fast Fourier transform (FFT) along selected dimensions.
 +
-+-u		unitary
-+-i		inverse
-+-n		un-centered
-+-h		help
++-u    unitary
++-i    inverse
++-n    un-centered
++-h    help
 +
 +
 +--fftmod--
 +
-+Usage: fftmod [-i] bitmask <input> <output>
++Usage: fftmod [-i] bitmask <input> <output> 
 +
 +Apply 1 -1 modulation along dimensions selected by the {bitmask}.
 +
-+
-+-i		inverse
-+-h		help
++-i    inverse
++-h    help
 +
 +
 +--fftrot--
 +
-+Usage: fftrot dim1 dim2 theta <input> <output>
++Usage: fftrot dim1 dim2 theta <input> <output> 
 +
 +Performs a rotation using Fourier transform (FFT) along selected dimensions.
 +
-+-h		help
++-h  help
 +
 +
 +--fftshift--
 +
-+Usage: fftshift bitmask <input> <output>
++Usage: fftshift [-b] bitmask <input> <output> 
 +
 +Apply fftshift along dimensions selected by the {bitmask}.
 +
-+-h		help
++-b    apply ifftshift
++-h    help
 +
 +
 +--filter--
 +
-+Usage: filter [-m d] [-l d] <input> <output>
++Usage: filter [-m d] [-l d] [-G] [-a d] <input> <output> 
 +
 +Apply filter.
 +
-+
-+-m dim      	median filter along dimension dim
-+-l len      	length of filter
-+-h		help
++-m dim    median filter along dimension dim
++-l len    length of filter
++-G        geometric median
++-a dim    Moving average filter along dimension dim
++-h        help
 +
 +
 +--flatten--
 +
-+Usage: flatten <input> <output>
++Usage: flatten <input> <output> 
 +
 +Flatten array to one dimension.
 +
-+-h		help
++-h  help
 +
 +
 +--flip--
 +
-+Usage: flip bitmask <input> <output>
++Usage: flip bitmask <input> <output> 
 +
 +Flip (reverse) dimensions specified by the {bitmask}.
 +
-+-h		help
++-h  help
 +
 +
 +--fmac--
 +
-+Usage: fmac [-A] [-C] [-s d] <input1> [<input2>] <output>
++Usage: fmac [-A] [-C] [-s d] <input1> [<input2>] <output> 
 +
 +Multiply <input1> and <input2> and accumulate in <output>.
 +If <input2> is not specified, assume all-ones.
 +
-+-A		add to existing output (instead of overwriting)
-+-C		conjugate input2
-+-s b      	squash dimensions selected by bitmask b
-+-h		help
++-A      add to existing output (instead of overwriting)
++-C      conjugate input2
++-s b    squash dimensions selected by bitmask b
++-h      help
++
++
++--fovshift--
++
++Usage: fovshift [-t <file>] [-s f:f:f] <input> <output> 
++
++Shifts FOV.
++
++-t file     k-space trajectory
++-s X:Y:Z    FOV shift
++-h          help
 +
 +
 +--homodyne--
 +
-+Usage: homodyne [-r f] [-I] [-C] [-P <string>] [-n] dim fraction <input> <output>
++Usage: homodyne [-r f] [-I] [-C] [-P <file>] [-n] dim fraction <input> <output> 
 +
 +Perform homodyne reconstruction along dimension dim.
 +
-+-r alpha      	Offset of ramp filter, between 0 and 1. alpha=0 is a full ramp, alpha=1 is a horizontal line
-+-I		Input is in image domain
-+-C		Clear unacquired portion of kspace
-+-P phase_ref>      	Use <phase_ref> as phase reference
-+-n		use uncentered ffts
-+-h		help
++-r alpha         Offset of ramp filter, between 0 and 1. alpha=0 is a full ramp, alpha=1 is a horizontal line
++-I               Input is in image domain
++-C               Clear unacquired portion of kspace
++-P phase_ref>    Use <phase_ref> as phase reference
++-n               use uncentered ffts
++-h               help
++
++
++--ictv--
++
++Usage: ictv [-i d] [-u f] lambda flags flags <input> <output> 
++
++Infimal convolution of total variation along dims specified by flags.
++
++-i i      max. iterations
++-u rho    rho in ADMM
++-h        help
 +
 +
 +--index--
 +
-+Usage: index dim size name
++Usage: index dim size <name> 
 +
 +Create an array counting from 0 to {size-1} in dimensions {dim}.
 +
-+-h		help
++-h  help
 +
 +
 +--invert--
 +
-+Usage: invert <input> <output>
++Usage: invert <input> <output> 
 +
 +Invert array (1 / <input>). The output is set to zero in case of divide by zero.
 +
-+-h		help
++-h  help
 +
 +
 +--itsense--
 +
-+Usage: itsense alpha <sensitivities> <kspace> <pattern> <image>
++Usage: itsense alpha <sensitivities> <kspace> <pattern> <output> 
 +
 +A simplified implementation of iterative sense reconstruction
 +with l2-regularization.
 +
-+-h		help
++-h  help
 +
 +
 +--join--
 +
-+Usage: join [-a] dimension <input1> ... <inputn> <output>
++Usage: join [-a] dimension <input>1> ... <input>N> <output> 
 +
 +Join input files along {dimensions}. All other dimensions must have the same size.
 +	 Example 1: join 0 slice_001 slice_002 slice_003 full_data
 +	 Example 2: join 0 `seq -f "slice_%%03g" 0 255` full_data
 +
-+
-+-a		append - only works for cfl files!
-+-h		help
++-a    append - only works for cfl files!
++-h    help
 +
 +
 +--looklocker--
 +
-+Usage: looklocker [-t f] [-D f] <input> <output>
++Usage: looklocker [-t f] [-D f] <input> <output> 
 +
 +Compute T1 map from M_0, M_ss, and R_1*.
 +
-+
-+-t threshold      	Pixels with M0 values smaller than {threshold} are set to zero.
-+-D delay      	Time between the middle of inversion pulse and the first excitation.
-+-h		help
++-t threshold    Pixels with M0 values smaller than {threshold} are set to zero.
++-D delay        Time between the middle of inversion pulse and the first excitation.
++-h              help
 +
 +
 +--lrmatrix--
 +
-+Usage: lrmatrix [-d] [-i d] [-m d] [-f d] [-j d] [-k d] [-N] [-s] [-l d] [-o <string>] <input> <output>
++Usage: lrmatrix [-d] [-i d] [-m d] [-f d] [-j d] [-k d] [-N] [-s] [-l d] [-o <file>] <input> <output> 
 +
 +Perform (multi-scale) low rank matrix completion
 +
-+-d		perform decomposition instead, ie fully sampled
-+-i iter      	maximum iterations.
-+-m flags      	which dimensions are reshaped to matrix columns.
-+-f flags      	which dimensions to perform multi-scale partition.
-+-j scale      	block size scaling from one scale to the next one.
-+-k size      	smallest block size
-+-N		add noise scale to account for Gaussian noise.
-+-s		perform low rank + sparse matrix completion.
-+-l size      	perform locally low rank soft thresholding with specified block size.
-+-o out2      	summed over all non-noise scales to create a denoised output.
-+-h		help
++-d          perform decomposition instead, ie fully sampled
++-i iter     maximum iterations.
++-m flags    which dimensions are reshaped to matrix columns.
++-f flags    which dimensions to perform multi-scale partition.
++-j scale    block size scaling from one scale to the next one.
++-k size     smallest block size
++-N          add noise scale to account for Gaussian noise.
++-s          perform low rank + sparse matrix completion.
++-l size     perform locally low rank soft thresholding with specified block size.
++-o out2     summed over all non-noise scales to create a denoised output.
++-h          help
 +
 +
 +--mandelbrot--
 +
-+Usage: mandelbrot [-s d] [-n d] [-t f] [-z f] [-r f] [-i f] output
++Usage: mandelbrot [-s d] [-n d] [-t f] [-z f] [-r f] [-i f] <output> 
 +
 +Compute mandelbrot set.
 +
++-s size    image size
++-n #       nr. of iterations
++-t t       threshold for divergence
++-z z       zoom
++-r r       offset real
++-i i       offset imag
++-h         help
 +
-+-s size      	image size
-+-n #      	nr. of iterations
-+-t t      	threshold for divergence
-+-z z      	zoom
-+-r r      	offset real
-+-i i      	offset imag
-+-h		help
++
++--measure--
++
++Usage: measure [--mse] [--mse-mag] [--ssim] [--psnr] <reference> <input> [<output>] 
++
++
++
++--mse        mse
++--mse-mag    mse of rss (over coil dim)
++--ssim       ssim of rss (over coil dim) and mean over other dims
++--psnr       psnr of rss (over coil dim) and mean over other dims
++-h           help
 +
 +
 +--mip--
 +
-+Usage: mip [-m] [-a] bitmask <input> <output>
++Usage: mip [-m] [-a] bitmask <input> <output> 
 +
 +Maximum (minimum) intensity projection (MIP) along dimensions specified by bitmask.
 +
++-m    minimum
++-a    do absolute value first
++-h    help
++
++
++--mnist--
++
++Usage: mnist [-a,--apply] [-t,--train] [-g,--gpu] <input> <weights> <ref/output> 
 +
-+-m		minimum
-+-a		do absolute value first
-+-h		help
++Trains or applies a MNIST network.
++This network is to demonstrate how a neural network can be implemented in BART.
++
++-a,--apply    apply nnet
++-t,--train    trains network
++-g,--gpu      run on gpu
++-h            help
 +
 +
 +--moba--
 +
-+Usage: moba [-r ...] [-L ...] [-F ...] [-G ...] [-m d] [-l d] [-i d] [-R f] [-T f] [-j f] [-u f] [-C d] [-s f] [-B f] [-b ...] [-d d] [-f f] [-p <string>] [-J] [-M] [-g] [-I <string>] [-t <string>] [-o f] [-k] [--kfilter-1 ...] [--kfilter-2 ...] [-n] [--fat_spec_0 ...] <kspace> <TI/TE> <output> [<sensitivities>]
++Usage: moba [-r ...] [-L] [-P] [-F] [-G] [--bloch] [-m d] [-l d] [-i d] [-R,--reduction f] [-T f] [-j f] [-u f] [-C d] [-s f] [-B f] [-b f:f] [-d d] [-f f] [-p <file>] [-J] [-M] [-g] [--multi-gpu d] [-I <file>] [-t <file>] [-o f] [--img_dims d:d:d] [-k] [--kfilter-1] [--kfilter-2] [-e f] [--fat_spec_0] [--scale_data f] [--seq ...] [--sim ...] [--other ...] <kspace> <TI/TE> <output> [<sensitivities>] 
 +
 +Model-based nonlinear inverse reconstruction
 +
-+
-+-r <T>:A:B:C	generalized regularization options (-rh for help)
-+-L		T1 mapping using model-based look-locker
-+-F		T2 mapping using model-based Fast Spin Echo
-+-G		T2* mapping using model-based multiple gradient echo
-+-m model      	Select the MGRE model from enum { WF = 0, WFR2S, WF2R2S, R2S, PHASEDIFF } [default: WFR2S]
-+-l reg      	1/-l2	toggle l1-wavelet or l2 regularization.
-+-i iter      	Number of Newton steps
-+-R redu      	reduction factor
-+-T damp      	damping on temporal frames
-+-j minreg      	Minimum regu. parameter
-+-u rho      	ADMM rho [default: 0.01]
-+-C iter      	inner iterations
-+-s step      	step size
-+-B bound      	lower bound for relaxivity
-+-b SMO:SC      	B0 field: spatial smooth level; scaling [default: 222.; 1.]
-+-d level      	Debug level
-+-f FOV      	
-+-p PSF      	
-+-J		Stack frames for joint recon
-+-M		Simultaneous Multi-Slice reconstruction
-+-g		use gpu
-+-I init      	File for initialization
-+-t Traj      	
-+-o os      	Oversampling factor for gridding [default: 1.25]
-+-k		k-space edge filter for non-Cartesian trajectories
-+--kfilter-1		k-space edge filter 1
-+--kfilter-2		k-space edge filter 2
-+-n		disable normlization of parameter maps for thresholding
-+--fat_spec_0		select fat spectrum from ISMRM fat-water tool
-+-h		help
++-r <T>:A:B:C           generalized regularization options (-rh for help)
++-L                     T1 mapping using model-based look-locker
++-P                     T1 mapping using reparameterized (M0, R1, alpha) model-based look-locker (TR required!)
++-F                     T2 mapping using model-based Fast Spin Echo
++-G                     T2* mapping using model-based multiple gradient echo
++--bloch                Bloch model-based reconstruction
++-m model               Select the MGRE model from enum { WF = 0, WFR2S, WF2R2S, R2S, PHASEDIFF } [default: WFR2S]
++-l 1/-l2                toggle l1-wavelet or l2 regularization.
++-i iter                Number of Newton steps
++-R,--reduction redu    reduction factor
++-T damp                damping on temporal frames
++-j minreg              Minimum regularization parameter
++-u rho                 ADMM rho [default: 0.01]
++-C iter                inner iterations
++-s step                step size
++-B bound               lower bound for relaxation
++-b SMO:SC              B0 field: spatial smooth level; scaling [default: 222.; 1.]
++-d level               Debug level
++-f FOV                 
++-p PSF                 
++-J                     Stack frames for joint recon
++-M                     Simultaneous Multi-Slice reconstruction
++-g                     use gpu
++--multi-gpu num        number of gpus to use
++-I init                File for initialization
++-t traj                K-space trajectory
++-o os                  Oversampling factor for gridding [default: 1.]
++--img_dims x:y:z       dimensions
++-k                     k-space edge filter for non-Cartesian trajectories
++--kfilter-1            k-space edge filter 1
++--kfilter-2            k-space edge filter 2
++-e kfilter_strength    strength for k-space edge filter [default: 2e-3]
++--fat_spec_0           select fat spectrum from ISMRM fat-water tool
++--scale_data f         scaling factor for data
++--seq ...              configure sequence parameters
++--sim ...              configure simulation parameters
++--other ...            configure other parameters
++-h                     help
 +
 +
 +--mobafit--
 +
-+Usage: mobafit [-G ...] [-m d] [-i d] [-p ...] [-g] <TE> <echo images> <parameters>
++Usage: mobafit [-T] [-G] [-D] [-m d] [-i d] [-g] <enc> <echo/contrast images> [<coefficients>] 
++
++Pixel-wise fitting of physical signal models.
++
++-T          TSE
++-G          MGRE
++-D          diffusion
++-m model    Select the MGRE model from enum { WF = 0, WFR2S, WF2R2S, R2S, PHASEDIFF } [default: WFR2S]
++-i iter     Number of IRGNM steps
++-g          use gpu
++-h          help
++
++
++--morphop--
++
++Usage: morphop [-e] [-d] [-o] [-c] mask_size <binary input> [<binary output>] 
++
++Perform morphological operators on binary data with odd mask sizes.
 +
-+Pixel-wise fitting of sequence models.
++-e    EROSION (default)
++-d    DILATION
++-o    OPENING
++-c    CLOSING
++-h    help
 +
-+-G		MGRE
-+-m model      	Select the MGRE model from enum { WF = 0, WFR2S, WF2R2S, R2S, PHASEDIFF } [default: WFR2S]
-+-i iter      	Number of IRGNM steps
-+-p px,py,pz      	(patch size)
-+-g		use gpu
-+-h		help
++
++--multicfl--
++
++Usage: multicfl [-s] <cfl>1> ... <cfl>N> 
++
++Combine/Split multiple cfl files to one multi-cfl file.
++In normal usage, the last argument is the combined multi-cfl,
++with '-s', the first argument is the multi-cfl that is split up
++
++-s    separate
++-h    help
 +
 +
 +--nlinv--
 +
-+Usage: nlinv [-i d] [-d d] [-c] [-N] [-m d] [-U] [-f f] [-p <string>] [-t <string>] [-I <string>] [-g] [-S] [--lowmem] <kspace> <output> [<sensitivities>]
++Usage: nlinv [-i d] [-d d] [-c] [-N] [-m d] [-U] [-f f] [-p <file>] [-t <file>] [-I <file>] [-g] [-S] [--lowmem] <kspace> <output> [<sensitivities>] 
 +
 +Jointly estimate image and sensitivities with nonlinear
 +inversion using {iter} iteration steps. Optionally outputs
 +the sensitivities.
 +
-+-i iter      	Number of Newton steps
-+-d level      	Debug level
-+-c		Real-value constraint
-+-N		Do not normalize image with coil sensitivities
-+-m nmaps      	Number of ENLIVE maps to use in reconstruction
-+-U		Do not combine ENLIVE maps in output
-+-f FOV      	restrict FOV
-+-p file      	pattern / transfer function
-+-t file      	kspace trajectory
-+-I file      	File for initialization
-+-g		use gpu
-+-S		Re-scale image after reconstruction
-+--lowmem		Use low-mem mode of the nuFFT
-+-h		help
++-i iter     Number of Newton steps
++-d level    Debug level
++-c          Real-value constraint
++-N          Do not normalize image with coil sensitivities
++-m nmaps    Number of ENLIVE maps to use in reconstruction
++-U          Do not combine ENLIVE maps in output
++-f FOV      restrict FOV
++-p file     pattern / transfer function
++-t file     kspace trajectory
++-I file     File for initialization
++-g          use gpu
++-S          Re-scale image after reconstruction
++--lowmem    Use low-mem mode of the nuFFT
++-h          help
++
++
++--nnet--
++
++Usage: nnet [-a,--apply] [-e,--eval] [-t,--train] [-g,--gpu] [-b,--batch-size d] [-l,--load <file>] [-N,--network ...] [-U,--unet-segm ...] [--train-loss ...] [--valid-loss ...] [--valid-data ...] [-T,--train-algo ...] [--adam ...] [--load-memory] [--export-graph <string>] <input> <weights> <ref/output> 
++
++Trains or applies a neural network.
++
++-a,--apply                   apply nnet
++-e,--eval                    evaluate nnet
++-t,--train                   trains network
++-g,--gpu                     run on gpu
++-b,--batch-size batchsize    size of mini batches
++-l,--load <weights-init>     load weights for continuing training
++-N,--network ...             select neural network
++-U,--unet-segm ...           configure U-Net for segmentation
++--train-loss ...             configure the training loss
++--valid-loss ...             configure the validation loss
++--valid-data ...             provide validation data
++-T,--train-algo ...          configure general training parmeters
++--adam ...                   configure Adam
++--load-memory                load files into memory
++--export-graph <file.dot>    export graph for visualization
++-h                           help
 +
 +
 +--noise--
 +
-+Usage: noise [-s d] [-r] [-n f] <input> <output>
++Usage: noise [-s d] [-r] [-n f] <input> <output> 
 +
 +Add noise with selected variance to input.
 +
-+-s random seed initialization
-+-r		real-valued input
-+-n variance      	DEFAULT: 1.0
-+-h		help
++-s d           random seed initialization
++-r             real-valued input
++-n variance    DEFAULT: 1.0
++-h             help
 +
 +
 +--normalize--
 +
-+Usage: normalize flags <input> <output>
++Usage: normalize [-b] flags <input> <output> 
 +
 +Normalize along selected dimensions.
 +
-+-h		help
++-b    l1
++-h    help
 +
 +
 +--nrmse--
 +
-+Usage: nrmse [-t f] [-s] <reference> <input>
++Usage: nrmse [-t f] [-s] <reference> <input> 
 +
 +Output normalized root mean square error (NRMSE),
 +i.e. norm(input - ref) / norm(ref)
 +
-+-t eps      	compare to eps
-+-s		automatic (complex) scaling
-+-h		help
++-t eps    compare to eps
++-s        automatic (complex) scaling
++-h        help
 +
 +
 +--nufft--
 +
-+Usage: nufft [-a] [-i] [-d ...] [-t] [-r] [-c] [-l f] [-P] [-s] [-g] [-1] [--lowmem] <traj> <input> <output>
++Usage: nufft [-a] [-i] [-d d:d:d] [-t] [-r] [-c] [-l f] [-P] [-s] [-g] [-1] [--lowmem] <traj> <input> <output> 
 +
 +Perform non-uniform Fast Fourier Transform.
 +
-+-a		adjoint
-+-i		inverse
-+-d x:y:z      	dimensions
-+-t		Toeplitz embedding for inverse NUFFT
-+-r		turn-off Toeplitz embedding for inverse NUFFT
-+-c		Preconditioning for inverse NUFFT
-+-l lambda      	l2 regularization
-+-P		periodic k-space
-+-s		DFT
-+-g		GPU (only inverse)
-+-1		use/return oversampled grid
-+--lowmem		Use low-mem mode of the nuFFT
-+-h		help
++-a           adjoint
++-i           inverse
++-d x:y:z     dimensions
++-t           Toeplitz embedding for inverse NUFFT
++-r           turn-off Toeplitz embedding for inverse NUFFT
++-c           Preconditioning for inverse NUFFT
++-l lambda    l2 regularization
++-P           periodic k-space
++-s           DFT
++-g           GPU (only inverse)
++-1           use/return oversampled grid
++--lowmem     Use low-mem mode of the nuFFT
++-h           help
++
++
++--onehotenc--
++
++Usage: onehotenc [-r] [-i d] <input> <output> 
++
++Transforms class labels to one-hot-encoded classes
++
++
++-r          get class label by maximum entry
++-i index    select dimension
++-h          help
 +
 +
 +--ones--
 +
-+Usage: ones dims dim1 ... dimn name
++Usage: ones dims dim1 ... dimN <output> 
 +
 +Create an array filled with ones with {dims} dimensions of size {dim1} to {dimn}.
 +
-+-h		help
++-h  help
 +
 +
 +--pattern--
 +
-+Usage: pattern [-s d] <kspace> <pattern>
++Usage: pattern [-s d] <kspace> <pattern> 
 +
 +Compute sampling pattern from kspace
 +
-+
-+-s bitmask      	Squash dimensions selected by bitmask
-+-h		help
++-s bitmask    Squash dimensions selected by bitmask
++-h            help
 +
 +
 +--phantom--
 +
-+Usage: phantom [-s d] [-S d] [-k] [-t <string>] [-G ...] [-T ...] [-N d] [-B ...] [-x d] [-g d] [-3] [-b] [-r d] <output>
++Usage: phantom [-s d] [-S d] [-k] [-t <file>] [-G] [-T] [--NIST] [--SONAR] [-N d] [-B] [-x d] [-g d] [-3] [-b] [-r d] [--rotation-angle f] [--rotation-steps d] <output> 
 +
 +Image and k-space domain phantoms.
 +
-+-s nc      	nc sensitivities
-+-S nc      	Output nc sensitivities
-+-k		k-space
-+-t file      	trajectory
-+-G		geometric object phantom
-+-T		tubes phantom
-+-N num      	Random tubes phantom and number
-+-B		BART logo
-+-x n      	dimensions in y and z
-+-g n=1,2      	select geometry for object phantom
-+-3		3D
-+-b		basis functions for geometry
-+-r seed      	random seed initialization
-+-h		help
++-s nc                     nc sensitivities
++-S nc                     Output nc sensitivities
++-k                        k-space
++-t file                   trajectory
++-G                        geometric object phantom
++-T                        tubes phantom
++--NIST                    NIST phantom (T2 sphere)
++--SONAR                   Diagnostic Sonar phantom
++-N num                    Random tubes phantom and number
++-B                        BART logo
++-x n                      dimensions in y and z
++-g n=1,2,3                select geometry for object phantom
++-3                        3D
++-b                        basis functions for geometry
++-r seed                   random seed initialization
++--rotation-angle [deg]    Angle of Rotation
++--rotation-steps          Number of rotation steps
++-h                        help
 +
 +
 +--pics--
 +
-+Usage: pics [-l ...] [-r f] [-R ...] [-c] [-s f] [-i d] [-t <string>] [-n] [-N] [-g] [-G d] [-p <string>] [-I ...] [-b d] [-e] [-T <string>] [-W <string>] [-d d] [-O d] [-o f] [-u f] [-C d] [-q f] [-f f] [-m ...] [-w f] [-S] [-L d] [-K] [-B <string>] [-P f] [-a ...] [-M] [-U,--lowmem] <kspace> <sensitivities> <output>
++Usage: pics [-l ...] [-r f] [-R ...] [-c] [-s f] [-i d] [-t <file>] [-n] [-N] [-g] [-G d] [-p <file>] [-I] [-b d] [-e] [-W <file>] [-d d] [-u f] [-C d] [-f f] [-m] [-w f] [-S] [-L d] [-K] [-B <file>] [-P f] [-a] [-M] [-U,--lowmem] [--psf_export <file>] [--psf_import <file>] [--wavelet <string>] <kspace> <sensitivities> <output> 
 +
 +Parallel-imaging compressed-sensing reconstruction.
 +
-+-l1/-l2		toggle l1-wavelet or l2 regularization.
-+-r lambda      	regularization parameter
-+-R <T>:A:B:C	generalized regularization options (-Rh for help)
-+-c		real-value constraint
-+-s step      	iteration stepsize
-+-i iter      	max. number of iterations
-+-t file      	k-space trajectory
-+-n		disable random wavelet cycle spinning
-+-N		do fully overlapping LLR blocks
-+-g		use GPU
-+-G gpun      	use GPU device gpun
-+-p file      	pattern or weights
-+-I		select IST
-+-b blk      	Lowrank block size
-+-e		Scale stepsize based on max. eigenvalue
-+-T file      	(truth file)
-+-W <img>      	Warm start with <img>
-+-d level      	Debug level
-+-O rwiter      	(reweighting)
-+-o gamma      	(reweighting)
-+-u rho      	ADMM rho
-+-C iter      	ADMM max. CG iterations
-+-q cclambda      	(cclambda)
-+-f rfov      	restrict FOV
-+-m		select ADMM
-+-w val      	inverse scaling of the data
-+-S		re-scale the image after reconstruction
-+-L flags      	batch-mode
-+-K		randshift for NUFFT
-+-B file      	temporal (or other) basis
-+-P eps      	Basis Pursuit formulation, || y- Ax ||_2 <= eps
-+-a		select Primal Dual
-+-M		Simultaneous Multi-Slice reconstruction
-+-U,--lowmem		Use low-mem mode of the nuFFT
-+-h		help
++
++-l 1/-l2              toggle l1-wavelet or l2 regularization.
++-r lambda            regularization parameter
++-R <T>:A:B:C         generalized regularization options (-Rh for help)
++-c                   real-value constraint
++-s step              iteration stepsize
++-i iter              max. number of iterations
++-t file              k-space trajectory
++-n                   disable random wavelet cycle spinning
++-N                   do fully overlapping LLR blocks
++-g                   use GPU
++-G gpun              use GPU device gpun
++-p file              pattern or weights
++-I                   select IST
++-b blk               Lowrank block size
++-e                   Scale stepsize based on max. eigenvalue
++-W <img>             Warm start with <img>
++-d level             Debug level
++-u rho               ADMM rho
++-C iter              ADMM max. CG iterations
++-f rfov              restrict FOV
++-m                   select ADMM
++-w f                 inverse scaling of the data
++-S                   re-scale the image after reconstruction
++-L flags             batch-mode
++-K                   randshift for NUFFT
++-B file              temporal (or other) basis
++-P eps               Basis Pursuit formulation, || y- Ax ||_2 <= eps
++-a                   select Primal Dual
++-M                   Simultaneous Multi-Slice reconstruction
++-U,--lowmem          Use low-mem mode of the nuFFT
++--psf_export file    Export PSF to file
++--psf_import file    Import PSF from file
++--wavelet name       wavelet type (haar,dau2,cdf44)
++-h                   help
 +
 +
 +--pocsense--
 +
-+Usage: pocsense [-i d] [-r f] [-l d] <kspace> <sensitivities> <output>
++Usage: pocsense [-i d] [-r f] [-l d] <kspace> <sensitivities> <output> 
 +
 +Perform POCSENSE reconstruction.
 +
-+-i iter      	max. number of iterations
-+-r alpha      	regularization parameter
-+-l 1/-l2      	toggle l1-wavelet or l2 regularization
-+-h		help
++-i iter     max. number of iterations
++-r alpha    regularization parameter
++-l 1/-l2    toggle l1-wavelet or l2 regularization
++-h          help
 +
 +
 +--poisson--
 +
-+Usage: poisson [-Y d] [-Z d] [-y f] [-z f] [-C d] [-v] [-e] [-s d] <outfile>
++Usage: poisson [-Y d] [-Z d] [-y f] [-z f] [-C d] [-v] [-e] [-s d] <output> 
 +
 +Computes Poisson-disc sampling pattern.
 +
-+-Y size      	size dimension 1
-+-Z size      	size dimension 2
-+-y acc      	acceleration dim 1
-+-z acc      	acceleration dim 2
-+-C size      	size of calibration region
-+-v		variable density
-+-e		elliptical scanning
-+-s seed      	random seed
-+-h		help
++-Y size    size dimension 1
++-Z size    size dimension 2
++-y acc     acceleration dim 1
++-z acc     acceleration dim 2
++-C size    size of calibration region
++-v         variable density
++-e         elliptical scanning
++-s seed    random seed
++-h         help
 +
 +
 +--pol2mask--
 +
-+Usage: pol2mask [-X d] [-Y d] <poly> <output>
++Usage: pol2mask [-X d] [-Y d] <poly> <output> 
 +
 +Compute masks from polygons.
 +
-+-X size      	size dimension 0
-+-Y size      	size dimension 1
-+-h		help
++-X size    size dimension 0
++-Y size    size dimension 1
++-h         help
 +
 +
 +--poly--
 +
-+Usage: poly L N a_0 a_1 ... a_N output
-+
-+Evaluate polynomial p(x) = a_0 + a_1 x + a_2 x^2 ... a_N x^N at x = {0, 1, ... , L - 1} where a_i are floats.
-+
-+-h		help
++Usage: poly L N a_1 ... a_N <output> 
++
++Evaluate polynomial p(x) = a_1 + a_2 x + a_3 x^2 ... a_(N+1) x^N at x = {0, 1, ... , L - 1} where a_i are floats.
++
++-h  help
++
++
++--reconet--
++
++Usage: reconet [-t,--train] [-e,--eval] [-a,--apply] [-g,--gpu] [-l,--load <file>] [-b,--batch-size d] [-I,--iterations d] [-n,--normalize] [-N,--network ...] [--resnet-block ...] [--varnet-block ...] [--unet ...] [--data-consistency ...] [--initial-reco ...] [--shared-weights] [--no-shared-weights] [--shared-lambda] [--no-shared-lambda] [--rss-norm] [--trajectory <file>] [--pattern <file>] [--mask <file>] [--valid-data ...] [--train-loss ...] [--valid-loss ...] [-T,--train-algo ...] [--adam ...] [--iPALM ...] [--load-memory] [--lowmem] [--test] [--export-graph <string>] <kspace> <sensitivities> <weights> <ref/out> 
++
++Trains or appplies a neural network for reconstruction.
++
++-t,--train                   train reconet
++-e,--eval                    evaluate reconet
++-a,--apply                   apply reconet
++-g,--gpu                     run on gpu
++-l,--load <weights-init>     load weights for continuing training
++-b,--batch-size d            size of mini batches
++-I,--iterations d            number of unrolled iterations
++-n,--normalize               normalize data with maximum magnitude of adjoint reconstruction
++-N,--network ...             select neural network
++--resnet-block ...           configure residual block
++--varnet-block ...           configure variational block
++--unet ...                   configure U-Net block
++--data-consistency ...       configure data-consistency method
++--initial-reco ...           configure initialization
++--shared-weights             share weights across iterations
++--no-shared-weights          share weights across iterations
++--shared-lambda              share lambda across iterations
++--no-shared-lambda           share lambda across iterations
++--rss-norm                   scale output image to rss normalization
++--trajectory <traj>          trajectory
++--pattern <pattern>          sampling pattern / psf in kspace
++--mask <mask>                mask for computation of loss
++--valid-data ...             provide validation data
++--train-loss ...             configure the training loss
++--valid-loss ...             configure the validation loss
++-T,--train-algo ...          configure general training parmeters
++--adam ...                   configure Adam
++--iPALM ...                  configure iPALM
++--load-memory                copy training data into memory
++--lowmem                     reduce memory usage by checkpointing
++--test                       very small network for tests
++--export-graph <file.dot>    export graph for visualization
++-h                           help
 +
 +
 +--repmat--
 +
-+Usage: repmat dimension repetitions <input> <output>
++Usage: repmat dimension repetitions <input> <output> 
 +
 +Repeat input array multiple times along a certain dimension.
 +
-+-h		help
++-h  help
 +
 +
 +--reshape--
 +
-+Usage: reshape flags dim1 ... dimN <input> <output>
++Usage: reshape flags dim1 ... dimN <input> <output> 
 +
 +Reshape selected dimensions.
 +
-+
-+-h		help
++-h  help
 +
 +
 +--resize--
 +
-+Usage: resize [-c] dim1 size1 ... dimn sizen <input> <output>
++Usage: resize [-c] dim1 size1 ... dimN sizeN <input> <output> 
 +
-+Resizes an array along dimensions to sizes by truncating or zero-padding.
++Resizes an array along dimensions to sizes by truncating or zero-padding. Please see doc/resize.txt for examples.
 +
-+-c		center
-+-h		help
++-c    center
++-h    help
 +
 +
 +--rmfreq--
 +
-+Usage: rmfreq [-N d] <traj> <k> <k_cor>
++Usage: rmfreq [-N d] [-M <string>] <traj> <k> <k_cor> 
 +
 +Remove angle-dependent frequency
 +
-+
-+-N #      	Number of harmonics [Default: 5]
-+-h		help
++-N #       Number of harmonics [Default: 5]
++-M file    Contrast modulation file
++-h         help
 +
 +
 +--rof--
 +
-+Usage: rof <lambda> <flags> <input> <output>
++Usage: rof lambda flags <input> <output> 
 +
 +Perform total variation denoising along dims <flags>.
 +
-+-h		help
++-h  help
 +
 +
 +--roistat--
 +
-+Usage: roistat [-b] [-C ...] [-S ...] [-M ...] [-D ...] [-E ...] [-V ...] <roi> <input> [<output>]
++Usage: roistat [-b] [-C] [-S] [-M] [-D] [-E] [-V] <roi> <input> [<output>] 
 +
 +Compute ROI statistics.
 +
-+-b		Bessel's correction, i.e. 1 / (n - 1)
-+-C		voxel count
-+-S		sum
-+-M		mean
-+-D		standard deviation
-+-E		energy
-+-V		variance
-+-h		help
++-b    Bessel's correction, i.e. 1 / (n - 1)
++-C    voxel count
++-S    sum
++-M    mean
++-D    standard deviation
++-E    energy
++-V    variance
++-h    help
 +
 +
 +--rss--
 +
-+Usage: rss bitmask <input> <output>
++Usage: rss bitmask <input> <output> 
 +
 +Calculates root of sum of squares along selected dimensions.
 +
-+-h		help
++-h  help
 +
 +
 +--rtnlinv--
 +
-+Usage: rtnlinv [-i d] [-d d] [-c] [-N] [-m d] [-U] [-f f] [-p <string>] [-t <string>] [-I <string>] [-g] [-S] [-T f] [-x ...] <kspace> <output> [<sensitivities>]
++Usage: rtnlinv [-i d] [-d d] [-c] [-N] [-m d] [-U] [-f f] [-p <file>] [-t <file>] [-I <file>] [-g] [-S] [-T f] [-x d:d:d] <kspace> <output> [<sensitivities>] 
 +
 +Jointly estimate a time-series of images and sensitivities with nonlinear
 +inversion using {iter} iteration steps. Optionally outputs
 +the sensitivities.
 +
-+-i iter      	Number of Newton steps
-+-d level      	Debug level
-+-c		Real-value constraint
-+-N		Do not normalize image with coil sensitivities
-+-m nmaps      	Number of ENLIVE maps to use in reconstruction
-+-U		Do not combine ENLIVE maps in output
-+-f FOV      	restrict FOV
-+-p file      	pattern / transfer function
-+-t file      	kspace trajectory
-+-I file      	File for initialization
-+-g		use gpu
-+-S		Re-scale image after reconstruction
-+-T temp_damp      	temporal damping [default: 0.9]
-+-x x:y:z      	Explicitly specify image dimensions
-+-h		help
++-i iter         Number of Newton steps
++-d level        Debug level
++-c              Real-value constraint
++-N              Do not normalize image with coil sensitivities
++-m nmaps        Number of ENLIVE maps to use in reconstruction
++-U              Do not combine ENLIVE maps in output
++-f FOV          restrict FOV
++-p file         pattern / transfer function
++-t file         kspace trajectory
++-I file         File for initialization
++-g              use gpu
++-S              Re-scale image after reconstruction
++-T temp_damp    temporal damping [default: 0.9]
++-x x:y:z        Explicitly specify image dimensions
++-h              help
 +
 +
 +--sake--
 +
-+Usage: sake [-i d] [-s f] <kspace> <output>
++Usage: sake [-i d] [-s f] <kspace> <output> 
 +
 +Use SAKE algorithm to recover a full k-space from undersampled
 +data using low-rank matrix completion.
 +
-+-i iter      	tnumber of iterations
-+-s size      	rel. size of the signal subspace
-+-h		help
++-i iter    number of iterations
++-s size    rel. size of the signal subspace
++-h         help
 +
 +
 +--saxpy--
 +
-+Usage: saxpy scale <input1> <input2> <output>
++Usage: saxpy scale <input1> <input2> <output> 
 +
 +Multiply input1 with scale factor and add input2.
 +
-+-h		help
++-h  help
 +
 +
 +--scale--
 +
-+Usage: scale factor <input> <output>
++Usage: scale factor <input> <output> 
 +
 +Scale array by {factor}. The scale factor can be a complex number.
 +
-+-h		help
++-h  help
 +
 +
 +--sdot--
 +
-+Usage: sdot <input1> <input2>
++Usage: sdot <input1> <input2> 
 +
 +Compute dot product along selected dimensions.
 +
-+-h		help
++-h  help
 +
 +
 +--show--
 +
-+Usage: show [-m] [-d d] [-s <string>] [-f <string>] <input>
++Usage: show [-m] [-d d] [-s <string>] [-f <string>] <input> 
 +
 +Outputs values or meta data.
 +
-+-m		show meta data
-+-d dim      	show size of dimension
-+-s sep      	use <sep> as the separator
-+-f format      	use <format> as the format. Default: "%%+.6e%%+.6ei"
-+-h		help
++-m           show meta data
++-d dim       show size of dimension
++-s sep       use <sep> as the separator
++-f format    use <format> as the format. Default: "%%+.6e%%+.6ei"
++-h           help
 +
 +
 +--signal--
 +
-+Usage: signal [-F ...] [-B ...] [-T ...] [-M ...] [-G ...] [--fat] [-I] [-s] [-0 ...] [-1 ...] [-2 ...] [-3 ...] [-r f] [-e f] [-f f] [-t f] [-n d] [-b d] <basis-functions>
++Usage: signal [-F] [-B] [-T] [-M] [-G] [--fat] [-I] [-s] [-0 f:f:f] [-1 f:f:f] [-2 f:f:f] [-3 f:f:f] [-r f] [-e f] [-f f] [-t f] [-n d] [-b d] [--av-spokes d] <basis-functions> 
 +
 +Analytical simulation tool.
 +
-+-F		FLASH
-+-B		bSSFP
-+-T		TSE
-+-M		MOLLI
-+-G		MGRE
-+--fat		Simulate additional fat component.
-+-I		inversion recovery
-+-s		inversion recovery starting from steady state
-+-0 min:max:N      	range of off-resonance frequency (Hz)
-+-1 min:max:N      	range of T1s (s)
-+-2 min:max:N      	range of T2s (s)
-+-3 min:max:N      	range of Mss
-+-r TR      	repetition time
-+-e TE      	echo time
-+-f FA      	flip ange
-+-t T1 relax      	T1 relax period (second) for MOLLI
-+-n n      	number of measurements
-+-b heart beats      	number of heart beats for MOLLI
-+-h		help
++-F                FLASH
++-B                bSSFP
++-T                TSE
++-M                MOLLI
++-G                MGRE
++--fat             Simulate additional fat component.
++-I                inversion recovery
++-s                inversion recovery starting from steady state
++-0 min:max:N      range of off-resonance frequency (Hz)
++-1 min:max:N      range of T1s (s)
++-2 min:max:N      range of T2s (s)
++-3 min:max:N      range of Mss
++-r TR             repetition time
++-e TE             echo time
++-f FA             flip ange
++-t T1 relax       T1 relax period (second) for MOLLI
++-n n              number of measurements
++-b heart beats    number of heart beats for MOLLI
++--av-spokes d     Number of averaged consecutive spokes
++-h                help
++
++
++--sim--
++
++Usage: sim [-1,--T1 f:f:f] [-2,--T2 f:f:f] [--ROT] [--ODE] [--STM] [--split-dim] [--seq ...] [--other ...] <signal: Mxy> [<Partial derivatives: dR1, dM0, dR2, dB1>] 
++
++simulation tool
++
++-1,--T1 min:max:N    range of T1 values
++-2,--T2 min:max:N    range of T2 values
++--ROT                homogeneously discretized simulation based on rotational matrices
++--ODE                full ordinary differential equation solver based simulation (default)
++--STM                state-transition matrix based simulation
++--split-dim          Split output in x, y, and z dimensional parts
++--seq ...            configure sequence parameter
++--other ...          configure other parameters
++-h                   help
 +
 +
 +--slice--
 +
-+Usage: slice dim1 pos1 ... dimn posn <input> <output>
++Usage: slice dim1 pos1 ... dimN posN <input> <output> 
 +
 +Extracts a slice from positions along dimensions.
 +
-+
-+-h		help
++-h  help
 +
 +
 +--spow--
 +
-+Usage: spow exponent <input> <output>
++Usage: spow exponent <input> <output> 
 +
 +Raise array to the power of {exponent}. The exponent can be a complex number.
 +
-+-h		help
++-h  help
 +
 +
 +--sqpics--
 +
-+Usage: sqpics [-l ...] [-r f] [-R ...] [-s f] [-i d] [-t <string>] [-n] [-g] [-p <string>] [-b d] [-e] [-T <string>] [-W <string>] [-d d] [-u f] [-C d] [-f f] [-m ...] [-w f] [-S] <kspace> <sensitivities> <output>
++Usage: sqpics [-l ...] [-r f] [-R ...] [-s f] [-i d] [-t <file>] [-n] [-g] [-p <file>] [-b d] [-e] [-W <file>] [-d d] [-u f] [-C d] [-f f] [-m] [-w f] [-S] <kspace> <sensitivities> <output> 
 +
 +Parallel-imaging compressed-sensing reconstruction.
 +
-+-l1/-l2		toggle l1-wavelet or l2 regularization.
-+-r lambda      	regularization parameter
-+-R <T>:A:B:C	generalized regularization options (-Rh for help)
-+-s step      	iteration stepsize
-+-i iter      	max. number of iterations
-+-t file      	k-space trajectory
-+-n		disable random wavelet cycle spinning
-+-g		use GPU
-+-p file      	pattern or weights
-+-b blk      	Lowrank block size
-+-e		Scale stepsize based on max. eigenvalue
-+-T file      	(truth file)
-+-W <img>      	Warm start with <img>
-+-d level      	Debug level
-+-u rho      	ADMM rho
-+-C iter      	ADMM max. CG iterations
-+-f rfov      	restrict FOV
-+-m		Select ADMM
-+-w val      	scaling
-+-S		Re-scale the image after reconstruction
-+-h		help
++-l 1/-l2         toggle l1-wavelet or l2 regularization.
++-r lambda       regularization parameter
++-R <T>:A:B:C    generalized regularization options (-Rh for help)
++-s step         iteration stepsize
++-i iter         max. number of iterations
++-t file         k-space trajectory
++-n              disable random wavelet cycle spinning
++-g              use GPU
++-p file         pattern or weights
++-b blk          Lowrank block size
++-e              Scale stepsize based on max. eigenvalue
++-W <img>        Warm start with <img>
++-d level        Debug level
++-u rho          ADMM rho
++-C iter         ADMM max. CG iterations
++-f rfov         restrict FOV
++-m              Select ADMM
++-w val          scaling
++-S              Re-scale the image after reconstruction
++-h              help
 +
 +
 +--squeeze--
 +
-+Usage: squeeze <input> <output>
++Usage: squeeze <input> <output> 
 +
 +Remove singleton dimensions of array.
 +
-+-h		help
++-h  help
 +
 +
 +--ssa--
 +
-+Usage: ssa [-w d] [-z] [-m d] [-n d] [-r d] [-g d] <src> <EOF> [<S>] [<backprojection>]
++Usage: ssa [-w d] [-z] [-m d] [-n d] [-r d] [-g d] <src> <EOF> [<S>] [<backprojection>] 
 +
 +Perform SSA-FARY or Singular Spectrum Analysis. <src>: [samples, coordinates]
 +
-+
-+-w window      	Window length
-+-z		Zeropadding [Default: True]
-+-m 0/1      	Remove mean [Default: True]
-+-n 0/1      	Normalize [Default: False]
-+-r rank      	Rank for backprojection. r < 0: Throw away first r components. r > 0: Use only first r components.
-+-g bitmask      	Bitmask for Grouping (long value!)
-+-h		help
++-w window     Window length
++-z            Zeropadding [Default: True]
++-m 0/1        Remove mean [Default: True]
++-n 0/1        Normalize [Default: False]
++-r rank       Rank for backprojection. r < 0: Throw away first r components. r > 0: Use only first r components.
++-g bitmask    Bitmask for Grouping (long value!)
++-h            help
 +
 +
 +--std--
 +
-+Usage: std bitmask <input> <output>
++Usage: std bitmask <input> <output> 
 +
 +Compute standard deviation along selected dimensions specified by the {bitmask}
 +
-+-h		help
++-h  help
 +
 +
 +--svd--
 +
-+Usage: svd [-e] <input> <U> <S> <VH>
++Usage: svd [-e] <input> <U> <S> <VH> 
 +
 +Compute singular-value-decomposition (SVD).
 +
-+
-+-e		econ
-+-h		help
++-e    econ
++-h    help
 +
 +
 +--tgv--
 +
-+Usage: tgv <lambda> <flags> <input> <output>
++Usage: tgv lambda flags <input> <output> 
 +
-+Perform total generalized variation denoising along dims <flags>.
++Perform total generalized variation denoising along dims specified by flags.
 +
-+-h		help
++-h  help
 +
 +
 +--threshold--
 +
-+Usage: threshold [-H ...] [-W ...] [-L ...] [-D ...] [-B ...] [-j d] [-b d] lambda <input> <output>
++Usage: threshold [-H] [-W] [-L] [-D] [-B] [-j d] [-b d] lambda <input> <output> 
 +
 +Perform (soft) thresholding with parameter lambda.
 +
-+-H		hard thresholding
-+-W		daubechies wavelet soft-thresholding
-+-L		locally low rank soft-thresholding
-+-D		divergence-free wavelet soft-thresholding
-+-B		thresholding with binary output
-+-j bitmask      	joint soft-thresholding
-+-b blocksize      	locally low rank block size
-+-h		help
++-H              hard thresholding
++-W              daubechies wavelet soft-thresholding
++-L              locally low rank soft-thresholding
++-D              divergence-free wavelet soft-thresholding
++-B              thresholding with binary output
++-j bitmask      joint soft-thresholding
++-b blocksize    locally low rank block size
++-h              help
 +
 +
 +--toimg--
 +
-+Usage: toimg [-g f] [-c f] [-w f] [-d] [-m] [-W] [-h] <input> <output_prefix>
++Usage: toimg [-g f] [-c f] [-w f] [-d] [-m] [-W] <input> <output prefix> 
 +
 +Create magnitude images as png or proto-dicom.
 +The first two non-singleton dimensions will
 +be used for the image, and the other dimensions
 +will be looped over.
 +
-+
-+-g gamma      	gamma level
-+-c contrast      	contrast level
-+-w window      	window level
-+-d		write to dicom format (deprecated, use extension .dcm)
-+-m		re-scale each image
-+-W		use dynamic windowing
-+-h		help
++-g gamma       gamma level
++-c contrast    contrast level
++-w window      window level
++-d             write to dicom format (deprecated, use extension .dcm)
++-m             re-scale each image
++-W             use dynamic windowing
++-h             help
 +
 +
 +--traj--
 +
-+Usage: traj [-x d] [-y d] [-d d] [-e d] [-a d] [-t d] [-m d] [-l] [-g] [-r] [-G] [-H] [-s d] [-D] [-R f] [-q ...] [-Q ...] [-O] [-3] [-c] [-E] [-z ...] [-C <string>] [-V <string>] <output>
++Usage: traj [-x d] [-y d] [-d d] [-e d] [-a d] [-t d] [-m d] [-l] [-g] [-r] [-G] [-H] [-s d] [-D] [-o f] [-R f] [-q f:f:f] [-O] [-3] [-c] [-E] [-z d:d] [-C <file>] <output> 
 +
 +Computes k-space trajectories.
 +
-+-x x      	readout samples
-+-y y      	phase encoding lines
-+-d d      	full readout samples
-+-e e      	number of echoes
-+-a a      	acceleration
-+-t t      	turns
-+-m mb      	SMS multiband factor
-+-l		aligned partition angle
-+-g		golden angle in partition direction
-+-r		radial
-+-G		golden-ratio sampling
-+-H		halfCircle golden-ratio sampling
-+-s # Tiny GA      	tiny golden angle
-+-D		projection angle in [0,360°), else in [0,180°)
-+-R phi      	rotate
-+-q delays      	gradient delays: x, y, xy
-+-Q delays      	(gradient delays: z, xz, yz)
-+-O		correct transverse gradient error for radial tajectories
-+-3		3D
-+-c		asymmetric trajectory [DC sampled]
-+-E		multi-echo multi-spoke trajectory
-+-z Ref:Acel      	Undersampling in z-direction.
-+-C file      	custom_angle file [phi + i * psi]
-+-V file      	(custom_gdelays)
-+-h		help
++-x x            readout samples
++-y y            phase encoding lines
++-d d            full readout samples
++-e e            number of echoes
++-a a            acceleration
++-t t            turns
++-m mb           SMS multiband factor
++-l              aligned partition angle
++-g              golden angle in partition direction
++-r              radial
++-G              golden-ratio sampling
++-H              halfCircle golden-ratio sampling
++-s # Tiny GA    tiny golden angle
++-D              projection angle in [0,360°), else in [0,180°)
++-o o            oversampling factor
++-R phi          rotate
++-q delays       gradient delays: x, y, xy
++-O              correct transverse gradient error for radial tajectories
++-3              3D
++-c              asymmetric trajectory [DC sampled]
++-E              multi-echo multi-spoke trajectory
++-z Ref:Acel     Undersampling in z-direction.
++-C file         custom_angle file [phi + i * psi]
++-h              help
 +
 +
 +--transpose--
 +
-+Usage: transpose dim1 dim2 <input> <output>
++Usage: transpose dim1 dim2 <input> <output> 
 +
 +Transpose dimensions {dim1} and {dim2}.
 +
-+-h		help
++-h  help
 +
 +
 +--twixread--
 +
-+Usage: twixread [-x d] [-r d] [-y d] [-z d] [-s d] [-v d] [-c d] [-n d] [-a d] [-A] [-L] [-P] [-M] <dat file> <output>
++Usage: twixread [-x d] [-r d] [-y d] [-z d] [-s d] [-v d] [-c d] [-n d] [-a d] [-A] [-L] [-P] [-M] [-d d] <dat file> <output> 
 +
 +Read data from Siemens twix (.dat) files.
 +
-+-x X      	number of samples (read-out)
-+-r R      	radial lines
-+-y Y      	phase encoding steps
-+-z Z      	partition encoding steps
-+-s S      	number of slices
-+-v V      	number of averages
-+-c C      	number of channels
-+-n N      	number of repetitions
-+-a A      	total number of ADCs
-+-A		automatic [guess dimensions]
-+-L		use linectr offset
-+-P		use partctr offset
-+-M		MPI mode
-+-h		help
++-x X        number of samples (read-out)
++-r R        radial lines
++-y Y        phase encoding steps
++-z Z        partition encoding steps
++-s S        number of slices
++-v V        number of averages
++-c C        number of channels
++-n N        number of repetitions
++-a A        total number of ADCs
++-A          automatic [guess dimensions]
++-L          use linectr offset
++-P          use partctr offset
++-M          MPI mode
++-d level    Debug level
++-h          help
 +
 +
 +--upat--
 +
-+Usage: upat [-Y d] [-Z d] [-y d] [-z d] [-c d] output
++Usage: upat [-Y d] [-Z d] [-y d] [-z d] [-c d] <output> 
 +
 +Create a sampling pattern.
 +
-+
-+-Y Y      	size Y
-+-Z Z      	size Z
-+-y uy      	undersampling y
-+-z uz      	undersampling z
-+-c cen      	size of k-space center
-+-h		help
++-Y Y      size Y
++-Z Z      size Z
++-y uy     undersampling y
++-z uz     undersampling z
++-c cen    size of k-space center
++-h        help
 +
 +
 +--var--
 +
-+Usage: var bitmask <input> <output>
++Usage: var bitmask <input> <output> 
 +
 +Compute variance along selected dimensions specified by the {bitmask}
 +
-+-h		help
++-h  help
 +
 +
 +--vec--
 +
-+Usage: vec val1 val2 ... valN name
++Usage: vec val1 ... valN <output> 
 +
 +Create a vector of values.
 +
-+-h		help
++-h  help
 +
 +
 +--version--
 +
-+Usage: version [-t <string>] [-V] [-h]
++Usage: version [-t <string>] [-V] 
 +
 +Print BART version. The version string is of the form
 +TAG or TAG-COMMITS-SHA as produced by 'git describe'. It
@@ -1252,26 +1441,25 @@ index 0000000..2650973
 +the abbreviated hash of the last commit (SHA). If there
 +are local changes '-dirty' is added at the end.
 +
-+
-+-t version      	Check minimum version
-+-V		Output verbose info
-+-h		help
++-t version    Check minimum version
++-V            Output verbose info
++-h            help
 +
 +
 +--walsh--
 +
-+Usage: walsh [-r ...] [-b ...] <input> <output>
++Usage: walsh [-r d:d:d] [-b d:d:d] <input> <output> 
 +
 +Estimate coil sensitivities using walsh method (use with ecaltwo).
 +
-+-r cal_size      	Limits the size of the calibration region.
-+-b block_size      	Block size.
-+-h		help
++-r cal_size      Limits the size of the calibration region.
++-b block_size    Block size.
++-h               help
 +
 +
 +--wave--
 +
-+Usage: wave [-r f] [-b d] [-i d] [-s f] [-c f] [-t f] [-e f] [-g] [-f] [-H] [-v] [-w] [-l] <maps> <wave> <kspace> <output>
++Usage: wave [-r f] [-b d] [-i d] [-s f] [-c f] [-t f] [-e f] [-g] [-f] [-H] [-v] [-w] [-l] <maps> <wave> <kspace> <output> 
 +
 +Perform a wave-caipi reconstruction.
 +
@@ -1288,35 +1476,38 @@ index 0000000..2650973
 +  * kspace  - ( wx, sy, sz, nc,  1)
 +  * output  - ( sx, sy, sz,  1, md)
 +
-+-r lambda      	Soft threshold lambda for wavelet or locally low rank.
-+-b blkdim      	Block size for locally low rank.
-+-i mxiter      	Maximum number of iterations.
-+-s stepsz      	Step size for iterative method.
-+-c cntnu      	Continuation value for IST/FISTA.
-+-t toler      	Tolerance convergence condition for iterative method.
-+-e eigvl      	Maximum eigenvalue of normal operator, if known.
-+-g		use GPU
-+-f		Reconstruct using FISTA instead of IST.
-+-H		Use hogwild in IST/FISTA.
-+-v		Split result to real and imaginary components.
-+-w		Use wavelet.
-+-l		Use locally low rank across the real and imaginary components.
-+-h		help
++-r lambda    Soft threshold lambda for wavelet or locally low rank.
++-b blkdim    Block size for locally low rank.
++-i mxiter    Maximum number of iterations.
++-s stepsz    Step size for iterative method.
++-c cntnu     Continuation value for IST/FISTA.
++-t toler     Tolerance convergence condition for iterative method.
++-e eigvl     Maximum eigenvalue of normal operator, if known.
++-g           use GPU
++-f           Reconstruct using FISTA instead of IST.
++-H           Use hogwild in IST/FISTA.
++-v           Split result to real and imaginary components.
++-w           Use wavelet.
++-l           Use locally low rank across the real and imaginary components.
++-h           help
 +
 +
 +--wavelet--
 +
-+Usage: wavelet [-a] flags [dims] <input> <output>
++Usage: wavelet [-a] [-H] [-D] [-C] bitmask [dim1 ... dimN ] <input> <output> 
 +
 +Perform wavelet transform.
 +
-+-a		adjoint (specify dims)
-+-h		help
++-a    adjoint (specify dims)
++-H    type: Haar
++-D    type: Dau2
++-C    type: CDF44
++-h    help
 +
 +
 +--wavepsf--
 +
-+Usage: wavepsf [-c] [-x d] [-y d] [-r f] [-a d] [-t f] [-g f] [-s f] [-n d] <output>
++Usage: wavepsf [-c] [-x d] [-y d] [-r f] [-a d] [-t f] [-g f] [-s f] [-n d] <output> 
 +
 +Generate a wave PSF in hybrid space.
 +- Assumes the first dimension is the readout dimension.
@@ -1329,44 +1520,44 @@ index 0000000..2650973
 +bart reshape 7 wZ 768 1 128 wZ wZ
 +bart fmac wY wZ wYZ
 +
-+-c		Set to use a cosine gradient wave
-+-x RO_dim      	Number of readout points
-+-y PE_dim      	Number of phase encode points
-+-r PE_res      	Resolution of phase encode in cm
-+-a ADC_T      	Readout duration in microseconds.
-+-t ADC_dt      	ADC sampling rate in seconds
-+-g gMax      	Maximum gradient amplitude in Gauss/cm
-+-s sMax      	Maximum gradient slew rate in Gauss/cm/second
-+-n ncyc      	Number of cycles in the gradient wave
-+-h		help
++-c           Set to use a cosine gradient wave
++-x RO_dim    Number of readout points
++-y PE_dim    Number of phase encode points
++-r PE_res    Resolution of phase encode in cm
++-a ADC_T     Readout duration in microseconds.
++-t ADC_dt    ADC sampling rate in seconds
++-g gMax      Maximum gradient amplitude in Gauss/cm
++-s sMax      Maximum gradient slew rate in Gauss/cm/second
++-n ncyc      Number of cycles in the gradient wave
++-h           help
 +
 +
 +--whiten--
 +
-+Usage: whiten [-o <string>] [-c <string>] [-n] <input> <ndata> <output> [<optmat_out>] [<covar_out>]
++Usage: whiten [-o <file>] [-c <file>] [-n] <input> <ndata> <output> [<optmat_out>] [<covar_out>] 
 +
 +Apply multi-channel noise pre-whitening on <input> using noise data <ndata>.
 +Optionally output whitening matrix and noise covariance matrix
 +
-+-o <optmat_in>      	use external whitening matrix <optmat_in>
-+-c <covar_in>      	use external noise covariance matrix <covar_in>
-+-n		normalize variance to 1 using noise data <ndata>
-+-h		help
++-o <optmat_in>    use external whitening matrix <optmat_in>
++-c <covar_in>     use external noise covariance matrix <covar_in>
++-n                normalize variance to 1 using noise data <ndata>
++-h                help
 +
 +
 +--window--
 +
-+Usage: window [-H] flags <input> <output>
++Usage: window [-H] flags <input> <output> 
 +
 +Apply Hamming (Hann) window to <input> along dimensions specified by flags
 +
-+-H		Hann window
-+-h		help
++-H    Hann window
++-h    help
 +
 +
 +--wshfl--
 +
-+Usage: wshfl [-R ...] [-b d] [-i d] [-j d] [-s f] [-e f] [-F <string>] [-O <string>] [-t f] [-g] [-K] [-H] [-v] <maps> <wave> <phi> <reorder> <table> <output>
++Usage: wshfl [-R ...] [-b d] [-i d] [-j d] [-s f] [-e f] [-F <file>] [-O <file>] [-t f] [-g] [-K] [-H] [-v] <maps> <wave> <phi> <reorder> <table> <output> 
 +
 +Perform a wave-shuffling reconstruction.
 +
@@ -1405,37 +1596,36 @@ index 0000000..2650973
 +  * reorder - (    n,  3,  1,  1,  1,  1,  1)
 +  * table   - (   wx, nc,  n,  1,  1,  1,  1)
 +
-+-R<T>:A:B:C	Generalized regularization options. (-Rh for help)
-+-b blkdim      	Block size for locally low rank.
-+-i mxiter      	Maximum number of iterations.
-+-j cgiter      	Maximum number of CG iterations in ADMM.
-+-s admrho      	ADMM Rho value.
-+-e eigval      	Eigenvalue to scale step size. (Optional.)
-+-F frwrd      	Go from shfl-coeffs to data-table. Pass in coeffs path.
-+-O initl      	Initialize reconstruction with guess.
-+-t toler      	Tolerance convergence condition for FISTA.
-+-g		Use GPU.
-+-K		Go from data-table to shuffling basis k-space.
-+-H		Use hogwild.
-+-v		Split coefficients to real and imaginary components.
-+-h		help
++-R <T>:A:B:C    Generalized regularization options. (-Rh for help)
++-b blkdim       Block size for locally low rank.
++-i mxiter       Maximum number of iterations.
++-j cgiter       Maximum number of CG iterations in ADMM.
++-s admrho       ADMM Rho value.
++-e eigval       Eigenvalue to scale step size. (Optional.)
++-F frwrd        Go from shfl-coeffs to data-table. Pass in coeffs path.
++-O initl        Initialize reconstruction with guess.
++-t toler        Tolerance convergence condition for FISTA.
++-g              Use GPU.
++-K              Go from data-table to shuffling basis k-space.
++-H              Use hogwild.
++-v              Split coefficients to real and imaginary components.
++-h              help
 +
 +
 +--zeros--
 +
-+Usage: zeros dims dim1 ... dimn name
++Usage: zeros dims dim1 ... dimN <output> 
 +
 +Create a zero-filled array with {dims} dimensions of size {dim1} to {dimn}.
 +
-+-h		help
++-h  help
 +
 +
 +--zexp--
 +
-+Usage: zexp [-i] <input> <output>
++Usage: zexp [-i] <input> <output> 
 +
 +Point-wise complex exponential.
 +
-+
-+-i		imaginary
-+-h		help
++-i    imaginary
++-h    help



View it on GitLab: https://salsa.debian.org/med-team/bart/-/commit/0e2fe50cf896543e98001b6c723de9efe0a213c0

-- 
View it on GitLab: https://salsa.debian.org/med-team/bart/-/commit/0e2fe50cf896543e98001b6c723de9efe0a213c0
You're receiving this email because of your account on salsa.debian.org.


-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://alioth-lists.debian.net/pipermail/debian-med-commit/attachments/20220925/245bf061/attachment-0001.htm>


More information about the debian-med-commit mailing list