def test_IsotropicSmooth_outputs():
output_map = dict(out_file=dict(), )
outputs = IsotropicSmooth.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_IsotropicSmooth_outputs():
output_map = dict(out_file=dict(),
)
outputs = IsotropicSmooth.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 smooth_volume(imf, smoothmm):
from nipype.interfaces.fsl.maths import IsotropicSmooth
if smoothmm > 0:
omf = imf + "_smooth" + str(smoothmm) + "mm.nii.gz"
isosmooth = IsotropicSmooth()
isosmooth.inputs.in_file = imf
isosmooth.inputs.fwhm = smoothmm
isosmooth.inputs.out_file = omf
isosmooth.run()
data = nib.load(omf).get_data()
os.remove(omf)
else:
data = nib.load(imf).get_data()
return data
def smooth_volume(imf, smoothmm):
from nipype.interfaces.fsl.maths import IsotropicSmooth
if smoothmm > 0:
omf = imf + '_smooth' + str(smoothmm) + 'mm.nii.gz'
isosmooth = IsotropicSmooth()
isosmooth.inputs.in_file = imf
isosmooth.inputs.fwhm = smoothmm
isosmooth.inputs.out_file = omf
isosmooth.run()
data = nib.load(omf).get_data()
os.remove(omf)
else:
data = nib.load(imf).get_data()
return data
def test_IsotropicSmooth_inputs():
input_map = dict(
args=dict(argstr='%s', ),
environ=dict(
nohash=True,
usedefault=True,
),
fwhm=dict(
argstr='-s %.5f',
mandatory=True,
position=4,
xor=['sigma'],
),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
in_file=dict(
argstr='%s',
mandatory=True,
position=2,
),
internal_datatype=dict(
argstr='-dt %s',
position=1,
),
nan2zeros=dict(
argstr='-nan',
position=3,
),
out_file=dict(
argstr='%s',
genfile=True,
hash_files=False,
position=-2,
),
output_datatype=dict(
argstr='-odt %s',
position=-1,
),
output_type=dict(),
sigma=dict(
argstr='-s %.5f',
mandatory=True,
position=4,
xor=['fwhm'],
),
terminal_output=dict(
mandatory=True,
nohash=True,
),
)
inputs = IsotropicSmooth.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_IsotropicSmooth_inputs():
input_map = dict(args=dict(argstr='%s',
),
environ=dict(nohash=True,
usedefault=True,
),
fwhm=dict(argstr='-s %.5f',
mandatory=True,
position=4,
xor=['sigma'],
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
in_file=dict(argstr='%s',
mandatory=True,
position=2,
),
internal_datatype=dict(argstr='-dt %s',
position=1,
),
nan2zeros=dict(argstr='-nan',
position=3,
),
out_file=dict(argstr='%s',
genfile=True,
hash_files=False,
position=-2,
),
output_datatype=dict(argstr='-odt %s',
position=-1,
),
output_type=dict(),
sigma=dict(argstr='-s %.5f',
mandatory=True,
position=4,
xor=['fwhm'],
),
terminal_output=dict(mandatory=True,
nohash=True,
),
)
inputs = IsotropicSmooth.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
interp="sinc",
cost='mutualinfo'),
name="coreg_to_struct_space")
# Warp whole head T1 Structural Image to MNI 152 template
warp_to_152_node = Node(legacy.GenWarpFields(similarity_metric="CC"),
name="warp152")
# coreg_to_template_space_node = Node(ApplyTransforms(reference_image=template, interpolation='BSpline'), name="coreg_to_template_space")
coreg_to_template_space_node = Node(ApplyTransforms(interpolation='BSpline'),
name="coreg_to_template_space")
merge_transforms_node = Node(Merge(2), iterfield=['in2'], name="merge")
# Spatial smoothing
iso_smooth_node = Node(IsotropicSmooth(fwhm=4, output_type="NIFTI"),
name='isoSmooth')
#TODO: Use the data sink node in the pipeline
data_sink_node = Node(nio.DataSink(base_directory="results_dir",
container='warp152_output',
infields=['tt']),
name='dataSink')
def set_template_image(template_image):
"""
Sets the template image used to register the T1 or epi images to in the coregistration nodes.
:param template_image: The path of the template image
:return:
"""
# Warp whole head T1 Structural Image to MNI 152 template
warp_to_152 = Node(legacy.GenWarpFields(reference_image=template,
similarity_metric="CC"),
name="warp152")
# 3______________________
# coreg_to_struct_space = Node(FLIRT(apply_xfm=True, reference=struct_image, interp="sinc"), name="coreg")
coreg_to_struct_space = Node(FLIRT(apply_xfm=True, interp="sinc"),
name="coreg_to_struct_space")
coreg_to_template_space = Node(ApplyTransforms(reference_image=template),
name="coreg_to_template_space")
merge_transforms_node = Node(Merge(2), iterfield=['in2'], name="merge")
# Spatial smoothing
isoSmooth = Node(IsotropicSmooth(fwhm=4, output_type="NIFTI"),
name='isoSmooth')
dataSink = Node(nio.DataSink(base_directory="results_dir",
container='warp152_output',
infields=['tt']),
name='dataSink')
# Default process
base_dir = os.path.abspath("/projects/abeetem/results") #"fmriPipeline")
if args['epi_temp'] is not None:
base_dir = os.path.abspath('/projects/abeetem/results2')
process_timeseries = Workflow(name="process_timeseries", base_dir=base_dir)
'''
process_timeseries.connect([
