Model-based command routing

bartorch moba ... and bartorch mobafit ... run as the apps moba() and mobafit() when the command line reads into an app call exactly, and as BART’s command otherwise. cli.route makes the decision after reading the input arrays; the adapters are _moba and _mobafit in src/bartorch/cli/_apps.py. An adapter raises Unsupported for any argument it does not translate, so an argument is never ignored: the whole command line goes to the command.

Agreement with the command

The apps fit BlochSim’s models in BlochSim’s bounded parameterisation and reach the minimum the command reaches by a different path, so they agree with the command to the tolerance of a fit rather than to the bit. The adapters convert the named maps back into BART’s coefficients: rates in 1/s from times in ms, the same stacking along COEFF_DIM, and the data scaling the command applies (--scale_data, --normalize_scaling, --scale_psf; under -G the coil images scaled to a norm of a hundred). The tolerances are held in tests/test_cli.py.

With the coils estimated, only the product of the amplitude and the coils is determined by the data; the two routes split it by a smooth factor, so the tests compare the product.

Models routed to the app

Command	Flags	App model
mobafit	-T, -I, -L, -G with -m 0, 1, 3 or 4, -D, -M with --init	Multi-echo decay, inversion recovery, Look-Locker recovery, water and fat, diffusion decay, Lorentzian lines
moba	-T, -L with -l2	Multi-echo decay, Look-Locker recovery
moba	-P with -l2	Look-Locker model in the flip angle, B1 under a Sobolev weighting
moba	-G with -m 0, 1, 3 or 4, without -r	Water and fat over the coil images, B0 under a Sobolev weighting
moba	-D with -m 6 or 7	Inversion recovery of a multi-echo gradient-echo train
moba	--bloch with -l2	BlochSim FLASH or IR-FLASH simulation in (R1, M0, R2, B1)

Command lines sent to BART

Argument	Reason
-i	Counts Gauss-Newton steps over BART’s own scaled coefficients; a bounded parameterisation needs more, so the count does not translate into the app’s iterations
moba -C	Counts FISTA iterations, or under -G conjugate-gradient steps stopped at a tolerance the app’s are not
moba without -l2 (-l1, the default)	A wavelet term on the maps, which the app does not carry
-G -m 2	Separate water and fat decays, which the bounded fit does not separate
Any other -m	A model on another layout, which the app does not have
moba -G -r	The proximal iteration -r puts around the gradient-echo fit
mobafit -P, --fB0-init, -M without --init, a start the bounded model has no image of, --scale, a covariance output	No app counterpart, no neutral start, a value outside the bounds, a preconditioning, an output the app does not compute
--bloch balanced SSFP, spin or spoke averaging, a slice profile, a held R1 or M0, a B1 map beside a fitted B1	A train or a held parameter the app does not play; a B1 map beside a held B1 is taken
A trajectory (-t)	The adapters read Cartesian k-space only
An input the reader cannot load, or an array with more dimensions than BART has	The command reports it

A missing input file is reported before either route runs (cli._missing), so the message is the same whichever route would have served the command.