def test_BEDPOSTX4_outputs():
output_map = dict(bpx_out_directory=dict(),
dyads=dict(),
mean_fsamples=dict(),
mean_phsamples=dict(),
mean_thsamples=dict(),
merged_fsamples=dict(),
merged_phsamples=dict(),
merged_thsamples=dict(),
xfms_directory=dict(),
)
outputs = BEDPOSTX4.output_spec()
for key, metadata in output_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(outputs.traits()[key], metakey), value
def test_BEDPOSTX4_outputs():
output_map = dict(bpx_out_directory=dict(),
dyads=dict(),
mean_fsamples=dict(),
mean_phsamples=dict(),
mean_thsamples=dict(),
merged_fsamples=dict(),
merged_phsamples=dict(),
merged_thsamples=dict(),
xfms_directory=dict(),
)
outputs = BEDPOSTX4.output_spec()
for key, metadata in output_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(outputs.traits()[key], metakey), value
def test_BEDPOSTX4_inputs():
input_map = dict(all_ard=dict(argstr='--allard',
xor=('no_ard', 'all_ard'),
),
args=dict(argstr='%s',
),
bpx_directory=dict(argstr='%s',
usedefault=True,
),
burn_in=dict(argstr='--burnin=%d',
),
burn_in_no_ard=dict(argstr='--burninnoard=%d',
),
burn_period=dict(argstr='-b %d',
),
bvals=dict(mandatory=True,
),
bvecs=dict(mandatory=True,
),
dwi=dict(mandatory=True,
),
environ=dict(nohash=True,
usedefault=True,
),
fibres=dict(argstr='-n %d',
),
force_dir=dict(argstr='--forcedir',
usedefault=True,
),
fudge=dict(argstr='--fudge=%d',
),
gradnonlin=dict(argstr='--gradnonlin=%s',
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
jumps=dict(argstr='-j %d',
),
logdir=dict(argstr='--logdir=%s',
usedefault=True,
),
mask=dict(mandatory=True,
),
model=dict(argstr='-model %d',
),
n_fibres=dict(argstr='--nfibres=%d',
),
n_jumps=dict(argstr='--njumps=%d',
),
nlgradient=dict(argstr='-g',
),
no_ard=dict(argstr='--noard',
xor=('no_ard', 'all_ard'),
),
no_cuda=dict(argstr='-c',
),
no_spat=dict(argstr='--nospat',
xor=('no_spat', 'non_linear'),
),
non_linear=dict(argstr='--nonlinear',
xor=('no_spat', 'non_linear'),
),
output_type=dict(),
sample_every=dict(argstr='--sampleevery=%d',
),
sampling=dict(argstr='-s %d',
),
seed=dict(argstr='--seed=%d',
),
terminal_output=dict(nohash=True,
),
update_proposal_every=dict(argstr='--updateproposalevery=%d',
),
weight=dict(argstr='-w %.2f',
),
)
inputs = BEDPOSTX4.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
def test_BEDPOSTX4_inputs():
input_map = dict(
all_ard=dict(
argstr='--allard',
xor=('no_ard', 'all_ard'),
),
args=dict(argstr='%s', ),
bpx_directory=dict(
argstr='%s',
usedefault=True,
),
burn_in=dict(argstr='--burnin=%d', ),
burn_in_no_ard=dict(argstr='--burninnoard=%d', ),
burn_period=dict(argstr='-b %d', ),
bvals=dict(mandatory=True, ),
bvecs=dict(mandatory=True, ),
dwi=dict(mandatory=True, ),
environ=dict(
nohash=True,
usedefault=True,
),
fibres=dict(argstr='-n %d', ),
force_dir=dict(
argstr='--forcedir',
usedefault=True,
),
fudge=dict(argstr='--fudge=%d', ),
gradnonlin=dict(argstr='--gradnonlin=%s', ),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
jumps=dict(argstr='-j %d', ),
logdir=dict(
argstr='--logdir=%s',
usedefault=True,
),
mask=dict(mandatory=True, ),
model=dict(argstr='-model %d', ),
n_fibres=dict(argstr='--nfibres=%d', ),
n_jumps=dict(argstr='--njumps=%d', ),
nlgradient=dict(argstr='-g', ),
no_ard=dict(
argstr='--noard',
xor=('no_ard', 'all_ard'),
),
no_cuda=dict(argstr='-c', ),
no_spat=dict(
argstr='--nospat',
xor=('no_spat', 'non_linear'),
),
non_linear=dict(
argstr='--nonlinear',
xor=('no_spat', 'non_linear'),
),
output_type=dict(),
sample_every=dict(argstr='--sampleevery=%d', ),
sampling=dict(argstr='-s %d', ),
seed=dict(argstr='--seed=%d', ),
terminal_output=dict(nohash=True, ),
update_proposal_every=dict(argstr='--updateproposalevery=%d', ),
weight=dict(argstr='-w %.2f', ),
)
inputs = BEDPOSTX4.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
