def test_fsl_apply_transform_func_to_mni_linear_mapnode():
c, strat = configuration_strategy_mock(method='FSL')
strat.append_name('anat_mni_flirt_register_0')
# build the workflow
workflow = pe.Workflow(
name='test_fsl_apply_transform_func_to_mni_linear_mapnode')
workflow.base_dir = c.workingDirectory
workflow.config['execution'] = {
'hash_method': 'timestamp',
'crashdump_dir': os.path.abspath(c.crashLogDirectory)
}
workflow = fsl_apply_transform_func_to_mni(
workflow,
'dr_tempreg_to_standard',
'dr_tempreg_maps_files',
'template_brain_for_func_preproc',
0,
strat,
c.funcRegFSLinterpolation,
map_node=True)
workflow.run()
def test_ants_apply_warp_func_mni_symm():
test_name = 'test_ants_apply_warps_func_mni_symm'
# get the config and strat for the mock
c, strat = configuration_strategy_mock()
num_strat = 0
node, out = strat['mean_functional']
mean_functional = node.inputs.file
# build the workflow
workflow = pe.Workflow(name=test_name)
workflow.base_dir = c.workingDirectory
workflow.config['execution'] = {
'hash_method': 'timestamp',
'crashdump_dir': os.path.abspath(c.crashLogDirectory)
}
workflow = ants_apply_warps_func_mni(
workflow,
'mean_functional_to_standard_symm',
'mean_functional',
'template_brain_for_func_preproc',
num_strat,
strat,
interpolation_method=c.funcRegANTSinterpolation,
distcor=False,
map_node=False,
inverse=False,
symmetry='symmetric',
input_image_type=0,
num_ants_cores=8)
workflow = ants_apply_warps_func_mni(
workflow,
'mean_functional_standard_to_original_symm',
'mean_functional_to_standard_symm',
'mean_functional',
num_strat,
strat,
interpolation_method=c.funcRegANTSinterpolation,
distcor=False,
map_node=False,
inverse=True,
symmetry='symmetric',
input_image_type=0,
num_ants_cores=1)
retval = workflow.run()
mean_functional_after_transform = os.path.join(
c.workingDirectory, test_name,
'apply_ants_warp_mean_functional_standard_to_original_symm_inverse_0',
'sub-M10978008_ses-NFB3_task-test_bold_calc_tshift_resample_volreg_calc_tstat_antswarp_antswarp.nii.gz'
)
assert (test_utils.pearson_correlation(
mean_functional, mean_functional_after_transform) > .93)
def test_output_func_to_standard_FSL_nonlinear():
test_name = 'test_output_func_to_standard_FSL_nonlinear'
# get the config and strat for the mock
c, strat = configuration_strategy_mock(method='FSL')
strat.append_name('anat_mni_fnirt_register_0')
num_strat = 0
# build the workflow
workflow = pe.Workflow(name='test_output_func_to_standard_FSL_nonlinear')
workflow.base_dir = c.workingDirectory
workflow.config['execution'] = {
'hash_method': 'timestamp',
'crashdump_dir': os.path.abspath(c.crashLogDirectory)
}
output_func_to_standard(workflow,
'mean_functional',
'template_brain_for_func_preproc',
'mean_functional_to_standard',
strat, num_strat, c, input_image_type='func_derivative')
out1_name = os.path.join(c.workingDirectory, test_name,
'func_mni_fsl_warp_mean_functional_to_standard_0',
'sub-M10978008_ses-NFB3_task-test_bold_calc_tshift_resample_volreg_calc_tstat_warp.nii.gz')
node, out_file = strat['mean_functional']
output_func_to_standard(workflow,
(node, out_file),
'template_brain_for_func_preproc',
'mean_functional_to_standard_node',
strat, num_strat, c, input_image_type='func_derivative')
out2_name = os.path.join(c.workingDirectory, test_name,
'func_mni_fsl_warp_mean_functional_to_standard_node_0',
'sub-M10978008_ses-NFB3_task-test_bold_calc_tshift_resample_volreg_calc_tstat_warp.nii.gz')
workflow.run()
assert(test_utils.pearson_correlation(out1_name, out2_name) > .99)
def test_ants_apply_warps_func_mni_mapnode():
test_name = 'test_ants_apply_warps_func_mni_mapnode'
# get the config and strat for the mock
c, strat = configuration_strategy_mock()
num_strat = 0
node, out = strat['dr_tempreg_maps_files']
dr_spatmaps = node.inputs.file
# build the workflow
workflow = pe.Workflow(name='test_ants_apply_warps_func_mni_mapnode')
workflow.base_dir = c.workingDirectory
workflow.config['execution'] = {
'hash_method': 'timestamp',
'crashdump_dir': os.path.abspath(c.crashLogDirectory)
}
workflow = ants_apply_warps_func_mni(
workflow,
'dr_tempreg_maps_to_standard',
'dr_tempreg_maps_files',
'template_brain_for_func_preproc',
num_strat,
strat,
interpolation_method=c.funcRegANTSinterpolation,
distcor=False,
map_node=True,
inverse=False,
input_image_type=0,
num_ants_cores=1)
workflow = ants_apply_warps_func_mni(
workflow,
'dr_tempreg_maps_standard_to_original',
'dr_tempreg_maps_to_standard',
'mean_functional',
num_strat,
strat,
interpolation_method=c.funcRegANTSinterpolation,
distcor=False,
map_node=True,
inverse=True,
input_image_type=0,
num_ants_cores=8)
workflow.run()
dr_spatmaps_after_transform = [
os.path.join(
c.workingDirectory, test_name,
'apply_ants_warp_dr_tempreg_maps_standard_to_original_mapnode_inverse_0',
'mapflow',
'_apply_ants_warp_dr_tempreg_maps_standard_to_original_mapnode_inverse_0{0}'
.format(n),
'temp_reg_map_000{0}_antswarp_antswarp.nii.gz'.format(n))
for n in range(0, 10)
]
test_results = [ test_utils.pearson_correlation(orig_file, xformed_file) > 0.99 \
for orig_file, xformed_file in zip(dr_spatmaps, dr_spatmaps_after_transform)]
assert all(test_results)