def test_threshold(create_files_in_directory):
files, testdir, out_ext = create_files_in_directory
# Get the command
thresh = fsl.Threshold(in_file="a.nii", out_file="b.nii")
# Test the underlying command
assert thresh.cmd == "fslmaths"
# Test mandtory args
with pytest.raises(ValueError):
thresh.run()
# Test the various opstrings
cmdline = "fslmaths a.nii %s b.nii"
for val in [0, 0., -1, -1.5, -0.5, 0.5, 3, 400, 400.5]:
thresh.inputs.thresh = val
assert thresh.cmdline == cmdline % "-thr %.10f" % val
val = "%.10f" % 42
thresh = fsl.Threshold(in_file="a.nii", out_file="b.nii", thresh=42, use_robust_range=True)
assert thresh.cmdline == cmdline % ("-thrp " + val)
thresh.inputs.use_nonzero_voxels = True
assert thresh.cmdline == cmdline % ("-thrP " + val)
thresh = fsl.Threshold(in_file="a.nii", out_file="b.nii", thresh=42, direction="above")
assert thresh.cmdline == cmdline % ("-uthr " + val)
thresh.inputs.use_robust_range = True
assert thresh.cmdline == cmdline % ("-uthrp " + val)
thresh.inputs.use_nonzero_voxels = True
assert thresh.cmdline == cmdline % ("-uthrP " + val)
def test_threshold(fsl_output_type=None):
prev_type = set_output_type(fsl_output_type)
files, testdir, origdir, out_ext = create_files_in_directory()
# Get the command
thresh = fsl.Threshold(in_file="a.nii", out_file="b.nii")
# Test the underlying command
yield assert_equal, thresh.cmd, "fslmaths"
# Test mandtory args
yield assert_raises, ValueError, thresh.run
# Test the various opstrings
cmdline = "fslmaths a.nii %s b.nii"
for val in [0, 0., -1, -1.5, -0.5, 0.5, 3, 400, 400.5]:
thresh.inputs.thresh = val
yield assert_equal, thresh.cmdline, cmdline % "-thr %.10f" % val
val = "%.10f" % 42
thresh = fsl.Threshold(in_file="a.nii", out_file="b.nii", thresh=42, use_robust_range=True)
yield assert_equal, thresh.cmdline, cmdline % ("-thrp " + val)
thresh.inputs.use_nonzero_voxels = True
yield assert_equal, thresh.cmdline, cmdline % ("-thrP " + val)
thresh = fsl.Threshold(in_file="a.nii", out_file="b.nii", thresh=42, direction="above")
yield assert_equal, thresh.cmdline, cmdline % ("-uthr " + val)
thresh.inputs.use_robust_range = True
yield assert_equal, thresh.cmdline, cmdline % ("-uthrp " + val)
thresh.inputs.use_nonzero_voxels = True
yield assert_equal, thresh.cmdline, cmdline % ("-uthrP " + val)
# Clean up our mess
clean_directory(testdir, origdir)
set_output_type(prev_type)
def threshold_img(t1, training_mod, thresh_val, thresh_file):
"""
Threshold image using fsl maths
:param t1: input image
:param training_mod: image name
:param thresh_val: threshold value (in percentile)
:param thresh_file: output thresholded image
"""
threshold = maths.Threshold()
threshold.inputs.in_file = t1
threshold.inputs.thresh = thresh_val
threshold.inputs.use_robust_range = True
threshold.inputs.use_nonzero_voxels = True
threshold.inputs.out_file = thresh_file
if not os.path.exists(thresh_file):
print("\n pre-processing %s" % training_mod)
threshold.run()
def qap_mask_workflow(workflow, resource_pool, config):
import os
import sys
import nipype.interfaces.io as nio
import nipype.pipeline.engine as pe
import nipype.interfaces.utility as niu
import nipype.interfaces.fsl.maths as fsl
from nipype.interfaces.fsl.base import Info
from qap_workflows_utils import select_thresh, \
slice_head_mask
from workflow_utils import check_input_resources, \
check_config_settings
# check_input_resources(resource_pool, 'anatomical_reorient')
# check_input_resources(resource_pool, 'ants_affine_xfm')
if 'template_skull_for_anat' not in config:
config['template_skull_for_anat'] = Info.standard_image(
'MNI152_T1_2mm.nii.gz')
check_config_settings(config, 'template_skull_for_anat')
if 'flirt_affine_xfm' not in resource_pool.keys():
from anatomical_preproc import flirt_anatomical_linear_registration
workflow, resource_pool = \
flirt_anatomical_linear_registration(workflow, resource_pool,
config)
if 'anatomical_reorient' not in resource_pool.keys():
from anatomical_preproc import anatomical_reorient_workflow
workflow, resource_pool = \
anatomical_reorient_workflow(workflow, resource_pool, config)
select_thresh = pe.Node(niu.Function(input_names=['input_skull'],
output_names=['thresh_out'],
function=select_thresh),
name='qap_headmask_select_thresh',
iterfield=['input_skull'])
mask_skull = pe.Node(fsl.Threshold(args='-bin'),
name='qap_headmask_thresh')
dilate_node = pe.Node(
fsl.MathsCommand(args='-dilM -dilM -dilM -dilM -dilM -dilM'),
name='qap_headmask_dilate')
erode_node = pe.Node(
fsl.MathsCommand(args='-eroF -eroF -eroF -eroF -eroF -eroF'),
name='qap_headmask_erode')
slice_head_mask = pe.Node(niu.Function(
input_names=['infile', 'transform', 'standard'],
output_names=['outfile_path'],
function=slice_head_mask),
name='qap_headmask_slice_head_mask')
combine_masks = pe.Node(fsl.BinaryMaths(operation='add', args='-bin'),
name='qap_headmask_combine_masks')
if len(resource_pool['anatomical_reorient']) == 2:
node, out_file = resource_pool['anatomical_reorient']
workflow.connect([(node, select_thresh, [(out_file, 'input_skull')]),
(node, mask_skull, [(out_file, 'in_file')]),
(node, slice_head_mask, [(out_file, 'infile')])])
else:
select_thresh.inputs.input_skull = resource_pool['anatomical_reorient']
mask_skull.inputs.in_file = resource_pool['anatomical_reorient']
# convert_fsl_xfm.inputs.infile =
# resource_pool['anatomical_reorient']
slice_head_mask.inputs.infile = resource_pool['anatomical_reorient']
if len(resource_pool['flirt_affine_xfm']) == 2:
node, out_file = resource_pool['flirt_affine_xfm']
workflow.connect(node, out_file, slice_head_mask, 'transform')
else:
slice_head_mask.inputs.transform = resource_pool['flirt_affine_xfm']
# convert_fsl_xfm.inputs.standard = config['template_skull_for_anat']
slice_head_mask.inputs.standard = config['template_skull_for_anat']
workflow.connect([
(select_thresh, mask_skull, [('thresh_out', 'thresh')]),
# (convert_fsl_xfm, slice_head_mask, [('converted_xfm', 'transform')])
(mask_skull, dilate_node, [('out_file', 'in_file')]),
(dilate_node, erode_node, [('out_file', 'in_file')]),
(erode_node, combine_masks, [('out_file', 'in_file')]),
(slice_head_mask, combine_masks, [('outfile_path', 'operand_file')])
])
resource_pool['qap_head_mask'] = (combine_masks, 'out_file')
return workflow, resource_pool
