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