def test_MS_LDA_outputs():
output_map = dict(vol_synth_file=dict(), weight_file=dict())
outputs = MS_LDA.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_MS_LDA_outputs():
output_map = dict(vol_synth_file=dict(),
weight_file=dict(),
)
outputs = MS_LDA.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_MS_LDA_inputs():
input_map = dict(ignore_exception=dict(nohash=True,
usedefault=True,
),
conform=dict(argstr='-conform',
),
weight_file=dict(mandatory=True,
argstr='-weight %s',
),
lda_labels=dict(mandatory=True,
sep=' ',
argstr='-lda %s',
),
output_synth=dict(new_name='vol_synth_file',
mandatory=True,
xor=['vol_synth_file', 'output_synth'],
deprecated='0.8',
argstr='-synth %s',
),
vol_synth_file=dict(mandatory=True,
argstr='-synth %s',
xor=['vol_synth_file', 'output_synth'],
),
shift=dict(argstr='-shift %d',
),
args=dict(argstr='%s',
),
mask_file=dict(argstr='-mask %s',
),
terminal_output=dict(mandatory=True,
nohash=True,
),
environ=dict(nohash=True,
usedefault=True,
),
label_file=dict(argstr='-label %s',
),
subjects_dir=dict(),
images=dict(copyfile=False,
mandatory=True,
position=-1,
argstr='%s',
),
use_weights=dict(argstr='-W',
),
)
inputs = MS_LDA.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_MS_LDA_inputs():
input_map = dict(args=dict(argstr='%s',
),
conform=dict(argstr='-conform',
),
environ=dict(nohash=True,
usedefault=True,
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
images=dict(argstr='%s',
copyfile=False,
mandatory=True,
position=-1,
),
label_file=dict(argstr='-label %s',
),
lda_labels=dict(argstr='-lda %s',
mandatory=True,
sep=' ',
),
mask_file=dict(argstr='-mask %s',
),
shift=dict(argstr='-shift %d',
),
subjects_dir=dict(),
terminal_output=dict(mandatory=True,
nohash=True,
),
use_weights=dict(argstr='-W',
),
vol_synth_file=dict(argstr='-synth %s',
mandatory=True,
),
weight_file=dict(argstr='-weight %s',
mandatory=True,
),
)
inputs = MS_LDA.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_MS_LDA_inputs():
input_map = dict(
args=dict(argstr="%s"),
conform=dict(argstr="-conform"),
environ=dict(nohash=True, usedefault=True),
ignore_exception=dict(nohash=True, usedefault=True),
images=dict(argstr="%s", copyfile=False, mandatory=True, position=-1),
label_file=dict(argstr="-label %s"),
lda_labels=dict(argstr="-lda %s", mandatory=True, sep=" "),
mask_file=dict(argstr="-mask %s"),
shift=dict(argstr="-shift %d"),
subjects_dir=dict(),
terminal_output=dict(mandatory=True, nohash=True),
use_weights=dict(argstr="-W"),
vol_synth_file=dict(argstr="-synth %s", mandatory=True),
weight_file=dict(argstr="-weight %s", mandatory=True),
)
inputs = MS_LDA.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 CreateFreeSurferWorkflow_custom(projectid, subjectid, sessionid, WFname, CLUSTER_QUEUE, CLUSTER_QUEUE_LONG, RunAllFSComponents=True, RunMultiMode=True, constructed_FS_SUBJECTS_DIR='/never_use_this'):
freesurferWF = pe.Workflow(name=GenerateWFName(projectid, subjectid, sessionid, WFname))
inputsSpec = pe.Node(interface=IdentityInterface(fields=['subj_session_id', 'T1_files', 'T2_files', 'subjects_dir',
'wm_prob', 'label_file', 'mask_file']), name='inputspec')
outputsSpec = pe.Node(interface=IdentityInterface(fields=['full_path_FS_output', 'processed_output_name', 'cnr_optimal_image']), name='outputspec')
### HACK: the nipype interface requires that this environmental variable is set before running
print "HACK SETTING SUBJECTS_DIR {0}".format(constructed_FS_SUBJECTS_DIR)
os.environ['SUBJECTS_DIR'] = constructed_FS_SUBJECTS_DIR
inputsSpec.inputs.subjects_dir = constructed_FS_SUBJECTS_DIR # HACK
if RunMultiMode:
mergeT1T2 = pe.Node(interface=Merge(2), name="Merge_T1T2")
freesurferWF.connect(inputsSpec, 'T1_files', mergeT1T2, 'in1')
freesurferWF.connect(inputsSpec, 'T2_files', mergeT1T2, 'in2')
# Some constants based on assumpts about the label_file from BRAINSABC
white_label = 1
grey_label = 2
msLDA_GenerateWeights = pe.Node(interface=MS_LDA(), name="MS_LDA")
MSLDA_sge_options_dictionary = {'qsub_args': '-S /bin/bash -pe smp 4 -l h_vmem=12G,mem_free=2G -o /dev/null -e /dev/null ' + CLUSTER_QUEUE, 'overwrite': True}
msLDA_GenerateWeights.plugin_args = MSLDA_sge_options_dictionary
msLDA_GenerateWeights.inputs.lda_labels = [white_label, grey_label]
msLDA_GenerateWeights.inputs.weight_file = 'weights.txt'
msLDA_GenerateWeights.inputs.use_weights = False
msLDA_GenerateWeights.inputs.vol_synth_file = 'synth_out.nii.gz'
# msLDA_GenerateWeights.inputs.vol_synth_file = 'synth_out.nii.gz'
# msLDA_GenerateWeights.inputs.shift = 0 # value to shift by
freesurferWF.connect(mergeT1T2, 'out', msLDA_GenerateWeights, 'images')
# freesurferWF.connect(inputsSpec,'subjects_dir', msLDA_GenerateWeights,'subjects_dir')
freesurferWF.connect(inputsSpec, 'label_file', msLDA_GenerateWeights, 'label_file')
# freesurferWF.connect(inputsSpec,'mask_file', msLDA_GenerateWeights,'mask_file') ## Mask file MUST be unsigned char
freesurferWF.connect(msLDA_GenerateWeights, 'vol_synth_file', outputsSpec, 'cnr_optimal_image')
if RunAllFSComponents == True:
print("""Run FreeSurfer ReconAll at""")
fs_reconall = pe.Node(interface=fswrap.FSScript(), name="FS52_cross_" + str(sessionid))
freesurfer_sge_options_dictionary = {'qsub_args': '-S /bin/bash -pe smp 4 -l h_vmem=10G,mem_free=10G ' + CLUSTER_QUEUE, 'overwrite': True}
fs_reconall.plugin_args = freesurfer_sge_options_dictionary
fs_reconall.inputs.subcommand = 'autorecon'
# fs_reconall.inputs.directive = 'all'
# fs_reconall.inputs.fs_env_script = '' # NOTE: NOT NEEDED HERE 'FreeSurferEnv.sh'
# fs_reconall.inputs.fs_home = '' # NOTE: NOT NEEDED HERE
freesurferWF.connect(inputsSpec, 'subj_session_id', fs_reconall, 'subj_session_id')
if RunMultiMode:
## Use the output of the synthesized T1 with maximized contrast
## HACK: REMOVE FOR NOW - NEEDS FURTHER TESTING
## freesurferWF.connect(msLDA_GenerateWeights, 'vol_synth_file', fs_reconall, 'T1_files')
freesurferWF.connect(inputsSpec, 'T1_files', fs_reconall, 'T1_files')
## END HACK
else:
## Use the output of the T1 only image
freesurferWF.connect(inputsSpec, 'T1_files', fs_reconall, 'T1_files')
freesurferWF.connect(inputsSpec, 'label_file', fs_reconall, 'brainmask')
freesurferWF.connect(inputsSpec, 'subjects_dir', fs_reconall, 'subjects_dir')
freesurferWF.connect(fs_reconall, 'outDir', outputsSpec, 'full_path_FS_output')
freesurferWF.connect(fs_reconall, 'processed_output_name', outputsSpec, 'processed_output_name')
return freesurferWF
def create_free_surfer_workflow_custom(
projectid,
subjectid,
sessionid,
WFname,
CLUSTER_QUEUE,
CLUSTER_QUEUE_LONG,
RunAllFSComponents=True,
RunMultiMode=True,
constructed_FS_SUBJECTS_DIR="/never_use_this",
):
"""
This function...
:param projectid:
:param subjectid:
:param sessionid:
:param WFname:
:param CLUSTER_QUEUE:
:param CLUSTER_QUEUE_LONG:
:param RunAllFSComponents: True
:param RunMultiMode: True
:param constructed_FS_SUBJECTS_DIR: '/never_use_this'
:return:
"""
freesurferWF = pe.Workflow(
name=generate_wf_name(projectid, subjectid, sessionid, WFname))
inputsSpec = pe.Node(
interface=IdentityInterface(fields=[
"subj_session_id",
"T1_files",
"T2_files",
"subjects_dir",
"wm_prob",
"label_file",
"mask_file",
]),
name="inputspec",
)
outputsSpec = pe.Node(
interface=IdentityInterface(fields=[
"full_path_FS_output", "processed_output_name", "cnr_optimal_image"
]),
name="outputspec",
)
### HACK: the nipype interface requires that this environmental variable is set before running
print(
("HACK SETTING SUBJECTS_DIR {0}".format(constructed_FS_SUBJECTS_DIR)))
os.environ["SUBJECTS_DIR"] = constructed_FS_SUBJECTS_DIR
inputsSpec.inputs.subjects_dir = constructed_FS_SUBJECTS_DIR # HACK
if RunMultiMode:
mergeT1T2 = pe.Node(interface=Merge(2), name="Merge_T1T2")
freesurferWF.connect(inputsSpec, "T1_files", mergeT1T2, "in1")
freesurferWF.connect(inputsSpec, "T2_files", mergeT1T2, "in2")
# Some constants based on assumpts about the label_file from BRAINSABC
white_label = 1
grey_label = 2
msLDA_GenerateWeights = pe.Node(interface=MS_LDA(), name="MS_LDA")
MSLDA_sge_options_dictionary = {
"qsub_args": modify_qsub_args(CLUSTER_QUEUE, 2, 1, 1),
"overwrite": True,
}
msLDA_GenerateWeights.plugin_args = MSLDA_sge_options_dictionary
msLDA_GenerateWeights.inputs.lda_labels = [white_label, grey_label]
msLDA_GenerateWeights.inputs.weight_file = "weights.txt"
msLDA_GenerateWeights.inputs.use_weights = False
msLDA_GenerateWeights.inputs.vol_synth_file = "synth_out.nii.gz"
# msLDA_GenerateWeights.inputs.vol_synth_file = 'synth_out.nii.gz'
# msLDA_GenerateWeights.inputs.shift = 0 # value to shift by
freesurferWF.connect(mergeT1T2, "out", msLDA_GenerateWeights, "images")
# freesurferWF.connect(inputsSpec,'subjects_dir', msLDA_GenerateWeights,'subjects_dir')
freesurferWF.connect(inputsSpec, "label_file", msLDA_GenerateWeights,
"label_file")
# freesurferWF.connect(inputsSpec,'mask_file', msLDA_GenerateWeights,'mask_file') ## Mask file MUST be unsigned char
freesurferWF.connect(msLDA_GenerateWeights, "vol_synth_file",
outputsSpec, "cnr_optimal_image")
if RunAllFSComponents == True:
print("""Run FreeSurfer ReconAll at""")
fs_reconall = pe.Node(interface=fswrap.FSScript(),
name="FS52_cross_" + str(sessionid))
freesurfer_sge_options_dictionary = {
"qsub_args": modify_qsub_args(CLUSTER_QUEUE, 8, 4, 4),
"overwrite": True,
}
fs_reconall.plugin_args = freesurfer_sge_options_dictionary
fs_reconall.inputs.subcommand = "autorecon"
# fs_reconall.inputs.directive = 'all'
# fs_reconall.inputs.fs_env_script = '' # NOTE: NOT NEEDED HERE 'FreeSurferEnv.sh'
# fs_reconall.inputs.fs_home = '' # NOTE: NOT NEEDED HERE
freesurferWF.connect(inputsSpec, "subj_session_id", fs_reconall,
"subj_session_id")
if RunMultiMode:
## Use the output of the synthesized T1 with maximized contrast
## HACK: REMOVE FOR NOW - NEEDS FURTHER TESTING
## freesurferWF.connect(msLDA_GenerateWeights, 'vol_synth_file', fs_reconall, 'T1_files')
freesurferWF.connect(inputsSpec, "T1_files", fs_reconall,
"T1_files")
## END HACK
else:
## Use the output of the T1 only image
freesurferWF.connect(inputsSpec, "T1_files", fs_reconall,
"T1_files")
freesurferWF.connect(inputsSpec, "label_file", fs_reconall,
"brainmask")
freesurferWF.connect(inputsSpec, "subjects_dir", fs_reconall,
"subjects_dir")
freesurferWF.connect(fs_reconall, "outDir", outputsSpec,
"full_path_FS_output")
freesurferWF.connect(fs_reconall, "processed_output_name", outputsSpec,
"processed_output_name")
return freesurferWF
