def test_Level1Design_inputs():
input_map = dict(
bases=dict(field="bases", mandatory=True),
factor_info=dict(field="fact"),
global_intensity_normalization=dict(field="global"),
ignore_exception=dict(nohash=True, usedefault=True),
interscan_interval=dict(field="timing.RT", mandatory=True),
mask_image=dict(field="mask"),
mask_threshold=dict(usedefault=True),
matlab_cmd=dict(),
mfile=dict(usedefault=True),
microtime_onset=dict(field="timing.fmri_t0"),
microtime_resolution=dict(field="timing.fmri_t"),
model_serial_correlations=dict(field="cvi"),
paths=dict(),
session_info=dict(field="sess", mandatory=True),
spm_mat_dir=dict(field="dir"),
timing_units=dict(field="timing.units", mandatory=True),
use_mcr=dict(),
use_v8struct=dict(min_ver="8", usedefault=True),
volterra_expansion_order=dict(field="volt"),
)
inputs = Level1Design.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_Level1Design_outputs():
output_map = dict(spm_mat_file=dict())
outputs = Level1Design.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_Level1Design_outputs():
output_map = dict(spm_mat_file=dict(), )
outputs = Level1Design.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_Level1Design_inputs():
input_map = dict(
bases=dict(
field='bases',
mandatory=True,
),
factor_info=dict(field='fact', ),
global_intensity_normalization=dict(field='global', ),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
interscan_interval=dict(
field='timing.RT',
mandatory=True,
),
mask_image=dict(field='mask', ),
mask_threshold=dict(usedefault=True, ),
matlab_cmd=dict(),
mfile=dict(usedefault=True, ),
microtime_onset=dict(field='timing.fmri_t0', ),
microtime_resolution=dict(field='timing.fmri_t', ),
model_serial_correlations=dict(field='cvi', ),
paths=dict(),
session_info=dict(
field='sess',
mandatory=True,
),
spm_mat_dir=dict(field='dir', ),
timing_units=dict(
field='timing.units',
mandatory=True,
),
use_mcr=dict(),
use_v8struct=dict(
min_ver='8',
usedefault=True,
),
volterra_expansion_order=dict(field='volt', ),
)
inputs = Level1Design.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
l1model = Node(SpecifySPMModel(), name="l1model")
# input: concatenate runs to a single session (boolean, default: False):
l1model.inputs.concatenate_runs = False
# input: units of event onsets and durations (secs or scans):
l1model.inputs.input_units = 'secs'
# input: units of design event onsets and durations (secs or scans):
l1model.inputs.output_units = 'secs'
# input: time of repetition (a float):
l1model.inputs.time_repetition = time_repetition
# high-pass filter cutoff in secs (a float, default = 128 secs):
l1model.inputs.high_pass_filter_cutoff = 128
# ======================================================================
# DEFINE NODE: LEVEL 1 DESIGN (GENERATE AN SPM DESIGN MATRIX)
# ======================================================================
# function: generate an SPM design matrix
l1design = Node(Level1Design(), name="l1design")
# input: (a dictionary with keys which are 'hrf' or 'fourier' or
# 'fourier_han' or 'gamma' or 'fir' and with values which are any value)
l1design.inputs.bases = {'hrf': {'derivs': [0, 0]}}
# input: units for specification of onsets ('secs' or 'scans'):
l1design.inputs.timing_units = 'secs'
# input: interscan interval / repetition time in secs (a float):
l1design.inputs.interscan_interval = time_repetition
# input: Model serial correlations AR(1), FAST or none:
l1design.inputs.model_serial_correlations = 'AR(1)'
# input: number of time-bins per scan in secs (an integer):
l1design.inputs.microtime_resolution = 16
# input: the onset/time-bin in seconds for alignment (a float):
l1design.inputs.microtime_onset = 1
# set expected thread and memory usage for the node:
l1design.interface.num_threads = 1
# input: units of design event onsets and durations (secs or scans):
# l1model.inputs.output_units = 'secs'
# input: time of repetition (a float):
# l1model.inputs.time_repetition = TR
# high-pass filter cutoff in secs (a float, default = 128 secs):
# l1model.inputs.high_pass_filter_cutoff = 128
# ======================================================================
# DEFINE NODE: LEVEL 1 DESIGN (GENERATE AN SPM DESIGN MATRIX)
# ======================================================================
# function: generate an SPM design matrix
# Level1Design - Generates an SPM design matrix
level1design = Node(Level1Design(bases={'hrf': {
'derivs': [0, 0]
}},
timing_units='secs',
interscan_interval=TR,
model_serial_correlations='AR(1)'),
name="level1design")
l1design = Node(Level1Design(), name="l1design")
# input: (a dictionary with keys which are 'hrf' or 'fourier' or
# 'fourier_han' or 'gamma' or 'fir' and with values which are any value)
l1design.inputs.bases = {'hrf': {'derivs': [0, 0]}}
# input: units for specification of onsets ('secs' or 'scans'):
l1design.inputs.timing_units = 'secs'
# input: interscan interval / repetition time in secs (a float):
l1design.inputs.interscan_interval = TR
# input: Model serial correlations AR(1), FAST or none:
l1design.inputs.model_serial_correlations = 'AR(1)'
# input: number of time-bins per scan in secs (an integer):
