def test_smooth(create_files_in_directory_plus_output_type):
files, testdir, out_ext = create_files_in_directory_plus_output_type
# Get the command
smoother = fsl.IsotropicSmooth(in_file="a.nii", out_file="b.nii")
# Test the underlying command
assert smoother.cmd == "fslmaths"
# Test that smoothing kernel is mandatory
with pytest.raises(ValueError):
smoother.run()
# Test smoothing kernels
cmdline = "fslmaths a.nii -s {:.5f} b.nii"
for val in [0, 1.0, 1, 25, 0.5, 8 / 3.0]:
smoother = fsl.IsotropicSmooth(in_file="a.nii",
out_file="b.nii",
sigma=val)
assert smoother.cmdline == cmdline.format(val)
smoother = fsl.IsotropicSmooth(in_file="a.nii",
out_file="b.nii",
fwhm=val)
val = float(val) / np.sqrt(8 * np.log(2))
assert smoother.cmdline == cmdline.format(val)
# Test automatic naming
smoother = fsl.IsotropicSmooth(in_file="a.nii", sigma=5)
assert smoother.cmdline == "fslmaths a.nii -s {:.5f} {}".format(
5, os.path.join(testdir, "a_smooth{}".format(out_ext)))
def test_smooth(fsl_output_type=None):
prev_type = set_output_type(fsl_output_type)
files, testdir, origdir, out_ext = create_files_in_directory()
# Get the command
smoother = fsl.IsotropicSmooth(in_file="a.nii", out_file="b.nii")
# Test the underlying command
yield assert_equal, smoother.cmd, "fslmaths"
# Test that smoothing kernel is mandatory
yield assert_raises, ValueError, smoother.run
# Test smoothing kernels
cmdline = "fslmaths a.nii -s %.5f b.nii"
for val in [0, 1., 1, 25, 0.5, 8 / 3.]:
smoother = fsl.IsotropicSmooth(in_file="a.nii", out_file="b.nii", sigma=val)
yield assert_equal, smoother.cmdline, cmdline % val
smoother = fsl.IsotropicSmooth(in_file="a.nii", out_file="b.nii", fwhm=val)
val = float(val) / np.sqrt(8 * np.log(2))
yield assert_equal, smoother.cmdline, cmdline % val
# Test automatic naming
smoother = fsl.IsotropicSmooth(in_file="a.nii", sigma=5)
yield assert_equal, smoother.cmdline, "fslmaths a.nii -s %.5f %s" % (5, os.path.join(testdir, "a_smooth%s" % out_ext))
# Clean up our mess
clean_directory(testdir, origdir)
set_output_type(prev_type)
def smooth_img(img, fwhm):
smth = math.IsotropicSmooth()
smth.inputs.in_file = img
smth.inputs.fwhm = fwhm
smth.inputs.out_file = img
smth.inputs.output_type = 'NIFTI_GZ'
smth.inputs.ignore_exception = True
smth.run()
# define working dir for smoothing
work_dir_smooth = os.path.join(os.getcwd(), 'smooth')
if not os.path.exists(work_dir_smooth):
os.makedirs(work_dir_smooth)
os.chdir(work_dir_smooth)
# Step#1 get a brain mask for func2mni image
from nipype.interfaces import afni as afni
automask = afni.Automask()
automask.inputs.in_file = rest_mni
automask.inputs.outputtype = "NIFTI_GZ"
automask.run()
# Step#2 smooth func2mni image
from nipype.interfaces.fsl import maths
smooth = maths.IsotropicSmooth()
smooth.inputs.in_file = rest_mni
smooth.inputs.fwhm = 6
smooth.run()
## Step#3 mask the smoothed image
from nipype.interfaces.fsl import maths
maskApp = maths.ApplyMask()
maskApp.inputs.in_file = 'rest_preprocessed2mni_smooth.nii.gz'
maskApp.inputs.mask_file = 'rest_preprocessed2mni_mask.nii.gz'
maskApp.inputs.out_file = os.path.join(work_dir,
'rest_preprocessed2mni_sm.nii.gz')
maskApp.inputs.output_type = 'NIFTI_GZ'
maskApp.run()
