def writeCVSubsetFile( environment, experiment, pipeline, cluster, csv_file, test_size, hasHeader):
from utilities.misc import add_dict
master_config = {}
for configDict in [environment, experiment, pipeline, cluster]:
master_config = add_dict(master_config, configDict)
"""
read in csv file
"""
import csv
csv_data=[]
with open(csv_file, mode='r') as infile:
reader = csv.DictReader(infile, skipinitialspace=True)
for row in reader:
csv_data.append(row)
print csv_data
totalSampleSize = len(csv_data)
print totalSampleSize
cv_subsets = subsample_crossValidationSet( totalSampleSize, test_size)
"""
global variable
"""
BASE_DATA_GRABBER_DIR='/Shared/johnsonhj/HDNI/Neuromorphometrics/20141116_Neuromorphometrics_base_Results/Neuromorphometrics/2012Subscription'
#master_config = {'queue':'HJ',
# 'long_q':'HJ'}
"""
workflow
"""
import nipype.pipeline.engine as pe
import nipype.interfaces.io as nio
from WorkupT1T2MALF import CreateMALFWorkflow
CV_MALF_WF = pe.Workflow(name="CV_MALF")
CV_MALF_WF.base_dir = master_config['cachedir']
subset_no = 1
for subset in cv_subsets:
print "-"*80
print " Creat a subset workflow Set " + str(subset_no)
print "-"*80
trainData = [ csv_data[i] for i in subset['train'] ]
testData = [ csv_data[i] for i in subset['test'] ]
print [ (trainData[i])['id'] for i in range( len(trainData))]
def run(argv, environment, experiment, pipeline, cluster):
from utilities.configFileParser import nipype_options
from utilities.misc import add_dict
from utilities.distributed import create_global_sge_script
print "Getting subjects from database..."
subjects = get_subjects(argv, experiment['cachedir'], environment['prefix'], experiment['dbfile']) # Build database before parallel section
if environment['cluster']:
print "Creating SGE template string..."
node_template = create_global_sge_script(cluster, environment)
else:
node_template = None
print "Copying Atlas directory and determining appropriate Nipype options..."
pipeline = nipype_options(argv, pipeline, cluster, node_template, experiment) # Generate Nipype options
master_config = {}
for configDict in [environment, experiment, pipeline, cluster]:
master_config = add_dict(master_config, configDict)
print "Dispatching jobs to the system..."
return dispatcher(master_config, subjects)
def run(argv, environment, experiment, pipeline, cluster):
from utilities.configFileParser import nipype_options
from utilities.misc import add_dict
from utilities.distributed import create_global_sge_script
print "Getting subjects from database..."
subjects = get_subjects(
argv, experiment['cachedir'], environment['prefix'],
experiment['dbfile']) # Build database before parallel section
if environment['cluster']:
print "Creating SGE template string..."
node_template = create_global_sge_script(cluster, environment)
else:
node_template = None
print "Copying Atlas directory and determining appropriate Nipype options..."
pipeline = nipype_options(argv, pipeline, cluster, node_template,
experiment) # Generate Nipype options
master_config = {}
for configDict in [environment, experiment, pipeline, cluster]:
master_config = add_dict(master_config, configDict)
print "Dispatching jobs to the system..."
return dispatcher(master_config, subjects)
def createAndRun(sessions, environment, experiment, pipeline, cluster):
from baw_exp import OpenSubjectDatabase
from utilities.misc import add_dict
master_config = {}
for configDict in [environment, experiment, pipeline, cluster]:
master_config = add_dict(master_config, configDict)
database = OpenSubjectDatabase(experiment['cachedir'], ['all'], environment['prefix'], experiment['dbfile'])
database.open_connection()
try:
all_sessions = database.getAllSessions()
if not set(sessions) <= set(all_sessions) and 'all' not in sessions:
missing = set(sessions) - set(all_sessions)
assert len(missing) == 0, "Requested sessions are missing from the database: {0}".format(missing)
elif 'all' in sessions:
sessions = set(all_sessions)
else:
sessions = set(sessions)
for session in sessions:
_dict = {}
_dict['session'] = session
_dict['project'] = database.getProjFromSession(session)
_dict['subject'] = database.getSubjFromSession(session)
_dict['T1s'] = database.getFilenamesByScantype(session, ['T1-15', 'T1-30'])
_dict['T2s'] = database.getFilenamesByScantype(session, ['T2-15', 'T2-30'])
_dict['PDs'] = database.getFilenamesByScantype(session, ['PD-15', 'PD-30'])
_dict['FLs'] = database.getFilenamesByScantype(session, ['FL-15', 'FL-30'])
_dict['OTs'] = database.getFilenamesByScantype(session, ['OTHER-15', 'OTHER-30'])
workflow = create_singleSession(_dict, master_config, 'Linear', 'singleSession_{0}_{1}'.format(_dict['subject'], _dict['session']))
workflow.run(plugin='SGEGraph', plugin_args=master_config['plugin_args'])
except:
raise
finally:
try:
database.close_connection()
except:
pass
def createAndRun(sessions, environment, experiment, pipeline, cluster, useSentinal, dryRun):
from baw_exp import OpenSubjectDatabase
from utilities.misc import add_dict
from workflows.utils import run_workflow
master_config = {}
for configDict in [environment, experiment, pipeline, cluster]:
master_config = add_dict(master_config, configDict)
database = OpenSubjectDatabase(experiment['cachedir'], ['all'], environment['prefix'], experiment['dbfile'])
database.open_connection()
try:
all_sessions = database.getAllSessions()
if not set(sessions) <= set(all_sessions) and 'all' not in sessions:
missing = set(sessions) - set(all_sessions)
assert len(missing) == 0, "Requested sessions are missing from the database: {0}\n\n{1}".format(missing,all_sessions)
elif 'all' in sessions:
sessions = set(all_sessions)
else:
sessions = set(sessions)
print("!=" * 40)
print("Doing sessions {0}".format(sessions))
print("!=" * 40)
for session in sessions:
_dict = {}
subject = database.getSubjFromSession(session)
_dict['session'] = session
_dict['project'] = database.getProjFromSession(session)
_dict['subject'] = subject
_dict['T1s'] = database.getFilenamesByScantype(session, ['T1-15', 'T1-30'])
_dict['T2s'] = database.getFilenamesByScantype(session, ['T2-15', 'T2-30'])
_dict['PDs'] = database.getFilenamesByScantype(session, ['PD-15', 'PD-30'])
_dict['FLs'] = database.getFilenamesByScantype(session, ['FL-15', 'FL-30'])
_dict['OTs'] = database.getFilenamesByScantype(session, ['OTHER-15', 'OTHER-30'])
sentinal_file_basedir = os.path.join(
master_config['resultdir'],
_dict['project'],
_dict['subject'],
_dict['session']
)
sentinal_file_list = list()
sentinal_file_list.append(os.path.join(sentinal_file_basedir))
if 'denoise' in master_config['components']:
# # NO SENTINAL FILE
pass
# # Use t1 average sentinal file if specified.
if 'landmark' in master_config['components']:
sentinal_file_list.append(os.path.join(
sentinal_file_basedir,
"ACPCAlign",
"landmarkInitializer_atlas_to_subject_transform.h5"
))
if 'tissue_classify' in master_config['components']:
for tc_file in ["complete_brainlabels_seg.nii.gz", "t1_average_BRAINSABC.nii.gz"]:
sentinal_file_list.append(os.path.join(
sentinal_file_basedir,
"TissueClassify",
tc_file
))
if 'warp_atlas_to_subject' in master_config['components']:
sentinal_file_list.append(os.path.join(
sentinal_file_basedir,
"WarpedAtlas2Subject",
"rho.nii.gz"
))
sentinal_file_list.append(os.path.join(
sentinal_file_basedir,
"WarpedAtlas2Subject",
"left_hemisphere_wm.nii.gz"
))
if 'malf_2012_neuro' in master_config['components']:
sentinal_file_list.append(os.path.join(
sentinal_file_basedir,
"TissueClassify",
"MALF_HDAtlas20_2015_fs_standard_label.nii.gz"
))
sentinal_file_list.append(os.path.join(
sentinal_file_basedir,
"TissueClassify",
"MALF_HDAtlas20_2015_label.nii.gz"
))
sentinal_file_list.append(os.path.join(
sentinal_file_basedir,
"TissueClassify",
"MALF_HDAtlas20_2015_lobar_label.nii.gz"
))
sentinal_file_list.append(os.path.join(
sentinal_file_basedir,
"TissueClassify",
"MALF_HDAtlas20_2015_CSFVBInjected_label.nii.gz"
))
if 'malf_2015_wholebrain' in master_config['components']:
pass
if master_config['workflow_phase'] == 'atlas-based-reference':
atlasDirectory = os.path.join(master_config['atlascache'], 'spatialImages', 'rho.nii.gz')
else:
atlasDirectory = os.path.join(master_config['previousresult'], subject, 'Atlas', 'AVG_rho.nii.gz')
if os.path.exists(atlasDirectory):
print("LOOKING FOR DIRECTORY {0}".format(atlasDirectory))
else:
print("MISSING REQUIRED ATLAS INPUT {0}".format(atlasDirectory))
print("SKIPPING: {0} prerequisites missing".format(session))
continue
## Use different sentinal file if segmentation specified.
from workflows.baseline import DetermineIfSegmentationShouldBeDone
do_BRAINSCut_Segmentation = DetermineIfSegmentationShouldBeDone(master_config)
if do_BRAINSCut_Segmentation:
sentinal_file_list.append(os.path.join(
sentinal_file_basedir,
"CleanedDenoisedRFSegmentations",
"allLabels_seg.nii.gz"
))
def allPathsExists(list_of_paths):
is_missing = False
for ff in list_of_paths:
if not os.path.exists(ff):
is_missing = True
print("MISSING: {0}".format(ff))
return not is_missing
if useSentinal and allPathsExists(sentinal_file_list):
print("SKIPPING: {0} exists".format(sentinal_file_list))
else:
print("PROCESSING INCOMPLETE: at least 1 required file does not exists")
if dryRun == False:
workflow = _create_singleSession(_dict, master_config, 'Linear',
'singleSession_{0}_{1}'.format(_dict['subject'], _dict['session']))
print("Starting session {0}".format(session))
# HACK Hard-coded to SGEGraph, but --wfrun is ignored completely
run_workflow(workflow, plugin=master_config['plugin_name'],
plugin_args=master_config['plugin_args'])
else:
print("EXITING WITHOUT WORK DUE TO dryRun flag")
except:
raise
finally:
try:
database.close_connection()
except:
pass
def write_cvsubset_file(
environment, experiment, pipeline, cluster, csv_file, test_size, hasHeader
):
"""
This function...
:param environment:
:param experiment:
:param pipeline:
:param cluster:
:param csv_file:
:param test_size:
:param hasHeader:
:return:
"""
from utilities.misc import add_dict
from collections import (
OrderedDict,
) # Need OrderedDict internally to ensure consistent ordering
master_config = OrderedDict()
for configDict in [environment, experiment, pipeline, cluster]:
master_config = add_dict(master_config, configDict)
"""
read in csv file
"""
import csv
csv_data = []
with open(csv_file, mode="r") as infile:
reader = csv.DictReader(infile, skipinitialspace=True)
for row in reader:
csv_data.append(row)
print(csv_data)
totalSampleSize = len(csv_data)
print(totalSampleSize)
cv_subsets = sample_crossvalidation_set(totalSampleSize, test_size)
"""
global variable
"""
## HACK FOR NOW SHOULD BE MORE ELEGANT FROM THE .config file
BASE_DATA_GRABBER_DIR = (
"/Shared/johnsonhj/HDNI/ReferenceData/Neuromorphometrics/2012Subscription"
)
# master_config = {'queue':'HJ',
# 'long_q':'HJ'}
"""
workflow
"""
import nipype.pipeline.engine as pe
import nipype.interfaces.io as nio
from .WorkupJointFusion import create_joint_fusion_workflow
CV_JointFusion_WF = pe.Workflow(name="CV_JointFusion")
CV_JointFusion_WF.base_dir = master_config["cachedir"]
subset_no = 1
for subset in cv_subsets:
print(("-" * 80))
print((" Creat a subset workflow Set " + str(subset_no)))
print(("-" * 80))
trainData = [csv_data[i] for i in subset["train"]]
testData = [csv_data[i] for i in subset["test"]]
print([(trainData[i])["id"] for i in range(len(trainData))])
for testSession in testData:
JointFusionWFName = "JointFusion_Set{0}_{1}".format(
subset_no, testSession["id"]
)
myJointFusion = create_joint_fusion_workflow(
JointFusionWFName,
master_config,
[(trainData[i])["id"] for i in range(len(trainData))],
BASE_DATA_GRABBER_DIR,
runFixFusionLabelMap=False,
)
testSessionName = "testSessionSpec_Set{0}_{1}".format(
subset_no, testSession["id"]
)
testSessionSpec = pe.Node(
interface=IdentityInterface(
fields=[
"t1_average",
"tissueLabel",
"template_leftHemisphere",
"landmarkInACPCAlignedSpace",
"template_weights_50Lmks_wts",
"labelFilename",
]
),
run_without_submitting=True,
name=testSessionName,
)
CV_JointFusion_WF.connect(
testSessionSpec, "t1_average", myJointFusion, "inputspec.subj_t1_image"
)
CV_JointFusion_WF.connect(
testSessionSpec,
"tissueLabel",
myJointFusion,
"inputspec.subj_fixed_head_labels",
)
CV_JointFusion_WF.connect(
testSessionSpec,
"template_leftHemisphere",
myJointFusion,
"inputspec.subj_left_hemisphere",
)
CV_JointFusion_WF.connect(
testSessionSpec,
"landmarkInACPCAlignedSpace",
myJointFusion,
"inputspec.subj_lmks",
)
CV_JointFusion_WF.connect(
testSessionSpec,
"template_weights_50Lmks_wts",
myJointFusion,
"inputspec.atlasWeightFilename",
)
CV_JointFusion_WF.connect(
testSessionSpec,
"labelFilename",
myJointFusion,
"inputspec.labelBaseFilename",
)
""" set test image information
"""
print(testSession)
testSessionSpec.inputs.t1_average = testSession["t1"]
testSessionSpec.inputs.tissueLabel = testSession["fixed_head_label"]
testSessionSpec.inputs.template_leftHemisphere = testSession[
"warpedAtlasLeftHemisphere"
]
testSessionSpec.inputs.landmarkInACPCAlignedSpace = testSession["lmk"]
testSessionSpec.inputs.template_weights_50Lmks_wts = "/Shared/sinapse/scratch/eunyokim/src/NamicExternal/build_Mac_201501/bin/Atlas/Atlas_20131115/20141004_BCD/template_landmarks_50Lmks.fcsv"
testSessionSpec.inputs.labelFilename = "FS_wmparc.nii.gz"
"""
DataSink
"""
dsName = "DataSink_DS_Set{0}_{1}".format(subset_no, testSession["id"])
DataSink = pe.Node(name=dsName, interface=nio.DataSink())
DataSink.overwrite = master_config["ds_overwrite"]
DataSink.inputs.container = "CV_Set{0}/{1}".format(
subset_no, testSession["id"]
)
DataSink.inputs.base_directory = master_config["resultdir"]
CV_JointFusion_WF.connect(
myJointFusion,
"outputspec.JointFusion_neuro2012_labelmap",
DataSink,
"Segmentation.@JointFusion_neuro2012_labelmap",
)
subset_no = subset_no + 1
# CV_JointFusion_WF.write_graph()
CV_JointFusion_WF.run(
plugin=master_config["plugin_name"], plugin_args=master_config["plugin_args"]
)
def createAndRun(sessions, environment, experiment, pipeline, cluster,
useSentinal, dryRun):
from baw_exp import OpenSubjectDatabase
from utilities.misc import add_dict
from workflows.utils import run_workflow
master_config = {}
for configDict in [environment, experiment, pipeline, cluster]:
master_config = add_dict(master_config, configDict)
database = OpenSubjectDatabase(experiment['cachedir'], ['all'],
environment['prefix'], experiment['dbfile'])
database.open_connection()
try:
all_sessions = database.getAllSessions()
if not set(sessions) <= set(all_sessions) and 'all' not in sessions:
missing = set(sessions) - set(all_sessions)
assert len(
missing
) == 0, "Requested sessions are missing from the database: {0}\n\n{1}".format(
missing, all_sessions)
elif 'all' in sessions:
sessions = set(all_sessions)
else:
sessions = set(sessions)
print("!=" * 40)
print("Doing sessions {0}".format(sessions))
print("!=" * 40)
for session in sessions:
_dict = {}
subject = database.getSubjFromSession(session)
_dict['session'] = session
_dict['project'] = database.getProjFromSession(session)
_dict['subject'] = subject
_dict['T1s'] = database.getFilenamesByScantype(
session, ['T1-15', 'T1-30'])
_dict['T2s'] = database.getFilenamesByScantype(
session, ['T2-15', 'T2-30'])
_dict['PDs'] = database.getFilenamesByScantype(
session, ['PD-15', 'PD-30'])
_dict['FLs'] = database.getFilenamesByScantype(
session, ['FL-15', 'FL-30'])
_dict['OTs'] = database.getFilenamesByScantype(
session, ['OTHER-15', 'OTHER-30'])
sentinal_file_basedir = os.path.join(master_config['resultdir'],
_dict['project'],
_dict['subject'],
_dict['session'])
sentinal_file_list = list()
sentinal_file_list.append(os.path.join(sentinal_file_basedir))
if 'denoise' in master_config['components']:
# # NO SENTINAL FILE
pass
# # Use t1 average sentinal file if specified.
if 'landmark' in master_config['components']:
sentinal_file_list.append(
os.path.join(
sentinal_file_basedir, "ACPCAlign",
"landmarkInitializer_atlas_to_subject_transform.h5"))
if 'tissue_classify' in master_config['components']:
for tc_file in [
"complete_brainlabels_seg.nii.gz",
"t1_average_BRAINSABC.nii.gz"
]:
sentinal_file_list.append(
os.path.join(sentinal_file_basedir, "TissueClassify",
tc_file))
if 'warp_atlas_to_subject' in master_config['components']:
sentinal_file_list.append(
os.path.join(sentinal_file_basedir, "WarpedAtlas2Subject",
"rho.nii.gz"))
sentinal_file_list.append(
os.path.join(sentinal_file_basedir, "WarpedAtlas2Subject",
"left_hemisphere_wm.nii.gz"))
if 'malf_2012_neuro' in master_config['components']:
sentinal_file_list.append(
os.path.join(
sentinal_file_basedir, "TissueClassify",
"MALF_HDAtlas20_2015_fs_standard_label.nii.gz"))
sentinal_file_list.append(
os.path.join(sentinal_file_basedir, "TissueClassify",
"MALF_HDAtlas20_2015_label.nii.gz"))
sentinal_file_list.append(
os.path.join(sentinal_file_basedir, "TissueClassify",
"MALF_HDAtlas20_2015_lobar_label.nii.gz"))
sentinal_file_list.append(
os.path.join(
sentinal_file_basedir, "TissueClassify",
"MALF_HDAtlas20_2015_CSFVBInjected_label.nii.gz"))
if 'malf_2015_wholebrain' in master_config['components']:
pass
if master_config['workflow_phase'] == 'atlas-based-reference':
atlasDirectory = os.path.join(master_config['atlascache'],
'spatialImages', 'rho.nii.gz')
else:
atlasDirectory = os.path.join(master_config['previousresult'],
subject, 'Atlas',
'AVG_rho.nii.gz')
if os.path.exists(atlasDirectory):
print("LOOKING FOR DIRECTORY {0}".format(atlasDirectory))
else:
print(
"MISSING REQUIRED ATLAS INPUT {0}".format(atlasDirectory))
print("SKIPPING: {0} prerequisites missing".format(session))
continue
## Use different sentinal file if segmentation specified.
from workflows.baseline import DetermineIfSegmentationShouldBeDone
do_BRAINSCut_Segmentation = DetermineIfSegmentationShouldBeDone(
master_config)
if do_BRAINSCut_Segmentation:
sentinal_file_list.append(
os.path.join(sentinal_file_basedir,
"CleanedDenoisedRFSegmentations",
"allLabels_seg.nii.gz"))
def allPathsExists(list_of_paths):
is_missing = False
for ff in list_of_paths:
if not os.path.exists(ff):
is_missing = True
print("MISSING: {0}".format(ff))
return not is_missing
if useSentinal and allPathsExists(sentinal_file_list):
print("SKIPPING: {0} exists".format(sentinal_file_list))
else:
print(
"PROCESSING INCOMPLETE: at least 1 required file does not exists"
)
if dryRun == False:
workflow = _create_singleSession(
_dict, master_config, 'Linear',
'singleSession_{0}_{1}'.format(_dict['subject'],
_dict['session']))
print("Starting session {0}".format(session))
# HACK Hard-coded to SGEGraph, but --wfrun is ignored completely
run_workflow(workflow,
plugin=master_config['plugin_name'],
plugin_args=master_config['plugin_args'])
else:
print("EXITING WITHOUT WORK DUE TO dryRun flag")
except:
raise
finally:
try:
database.close_connection()
except:
pass
def createAndRun(sessions, environment, experiment, pipeline, cluster,
useSentinal, dryRun):
from baw_exp import OpenSubjectDatabase
from utilities.misc import add_dict
from collections import OrderedDict
import sys
from workflows.utils import run_workflow
master_config = {}
for configDict in [environment, experiment, pipeline, cluster]:
master_config = add_dict(master_config, configDict)
database = OpenSubjectDatabase(experiment['cachedir'], ['all'],
environment['prefix'], experiment['dbfile'])
database.open_connection()
try:
all_sessions = database.getAllSessions()
if not set(sessions) <= set(all_sessions) and 'all' not in sessions:
missing = set(sessions) - set(all_sessions)
assert len(
missing
) == 0, "Requested sessions are missing from the database: {0}\n\n{1}".format(
missing, all_sessions)
elif 'all' in sessions:
sessions = set(all_sessions)
else:
sessions = set(sessions)
print("!=" * 40)
print("Doing sessions {0}".format(sessions))
print("!=" * 40)
for session in sessions:
_dict = OrderedDict()
t1_list = database.getFilenamesByScantype(session,
['T1-15', 'T1-30'])
if len(t1_list) == 0:
print(
"ERROR: Skipping session {0} for subject {1} due to missing T1's"
.format(session, subject))
print("REMOVE OR FIX BEFORE CONTINUING")
continue
subject = database.getSubjFromSession(session)
_dict['session'] = session
_dict['project'] = database.getProjFromSession(session)
_dict['subject'] = subject
_dict['T1s'] = t1_list
_dict['T2s'] = database.getFilenamesByScantype(
session, ['T2-15', 'T2-30'])
_dict['BadT2'] = False
if _dict['T2s'] == database.getFilenamesByScantype(
session, ['T2-15']):
print("This T2 is not going to be used for JointFusion")
print("This T2 is not going to be used for JointFusion")
print("This T2 is not going to be used for JointFusion")
print("This T2 is not going to be used for JointFusion")
print(_dict['T2s'])
_dict['BadT2'] = True
_dict['PDs'] = database.getFilenamesByScantype(
session, ['PD-15', 'PD-30'])
_dict['FLs'] = database.getFilenamesByScantype(
session, ['FL-15', 'FL-30'])
_dict['EMSP'] = database.getFilenamesByScantype(session, ['EMSP'])
_dict['OTHERs'] = database.getFilenamesByScantype(
session, ['OTHER-15', 'OTHER-30'])
sentinal_file_basedir = os.path.join(master_config['resultdir'],
_dict['project'],
_dict['subject'],
_dict['session'])
sentinal_file_list = list()
sentinal_file_list.append(os.path.join(sentinal_file_basedir))
if 'denoise' in master_config['components']:
# # NO SENTINAL FILE
pass
# # Use t1 average sentinal file if specified.
if 'landmark' in master_config['components']:
sentinal_file_list.append(
os.path.join(
sentinal_file_basedir, "ACPCAlign",
"landmarkInitializer_atlas_to_subject_transform.h5"))
if 'tissue_classify' in master_config['components']:
for tc_file in [
"complete_brainlabels_seg.nii.gz",
"t1_average_BRAINSABC.nii.gz"
]:
sentinal_file_list.append(
os.path.join(sentinal_file_basedir, "TissueClassify",
tc_file))
if 'warp_atlas_to_subject' in master_config['components']:
warp_atlas_file_list = [
"hncma_atlas.nii.gz", "l_accumben_ProbabilityMap.nii.gz",
"l_caudate_ProbabilityMap.nii.gz",
"l_globus_ProbabilityMap.nii.gz",
"l_hippocampus_ProbabilityMap.nii.gz",
"l_putamen_ProbabilityMap.nii.gz",
"l_thalamus_ProbabilityMap.nii.gz",
"left_hemisphere_wm.nii.gz", "phi.nii.gz",
"r_accumben_ProbabilityMap.nii.gz",
"r_caudate_ProbabilityMap.nii.gz",
"r_globus_ProbabilityMap.nii.gz",
"r_hippocampus_ProbabilityMap.nii.gz",
"r_putamen_ProbabilityMap.nii.gz",
"r_thalamus_ProbabilityMap.nii.gz", "rho.nii.gz",
"right_hemisphere_wm.nii.gz",
"template_WMPM2_labels.nii.gz",
"template_headregion.nii.gz",
"template_leftHemisphere.nii.gz",
"template_nac_labels.nii.gz",
"template_rightHemisphere.nii.gz",
"template_ventricles.nii.gz", "theta.nii.gz"
]
for ff in warp_atlas_file_list:
sentinal_file_list.append(
os.path.join(sentinal_file_basedir,
"WarpedAtlas2Subject", ff))
if 'jointfusion_2015_wholebrain' in master_config['components']:
sentinal_file_list.append(
os.path.join(
sentinal_file_basedir, "TissueClassify",
"JointFusion_HDAtlas20_2015_lobar_label.nii.gz"))
sentinal_file_list.append(
os.path.join(sentinal_file_basedir, "TissueClassify",
"lobeVolumes_JSON.json"))
if master_config['workflow_phase'] == 'atlas-based-reference':
atlasDirectory = os.path.join(master_config['atlascache'],
'spatialImages', 'rho.nii.gz')
sentinal_file_list.append(atlasDirectory)
else:
atlasDirectory = os.path.join(master_config['previousresult'],
subject, 'Atlas',
'AVG_rho.nii.gz')
sentinal_file_list.append(atlasDirectory)
sentinal_file_list.append(
os.path.join(master_config['previousresult'], subject,
'Atlas', 'AVG_template_headregion.nii.gz'))
if os.path.exists(atlasDirectory):
print("LOOKING FOR DIRECTORY {0}".format(atlasDirectory))
else:
print(
"MISSING REQUIRED ATLAS INPUT {0}".format(atlasDirectory))
print("SKIPPING: {0} prerequisites missing".format(session))
continue
## Use different sentinal file if segmentation specified.
from workflows.baseline import DetermineIfSegmentationShouldBeDone
do_BRAINSCut_Segmentation = DetermineIfSegmentationShouldBeDone(
master_config)
if do_BRAINSCut_Segmentation:
sentinal_file_list.append(
os.path.join(sentinal_file_basedir,
"CleanedDenoisedRFSegmentations",
"allLabels_seg.nii.gz"))
def allPathsExists(list_of_paths):
is_missing = False
for ff in list_of_paths:
if not os.path.exists(ff):
is_missing = True
print("MISSING: {0}".format(ff))
return not is_missing
if useSentinal and allPathsExists(sentinal_file_list):
print("SKIPPING: {0} exists".format(sentinal_file_list))
else:
print(
"PROCESSING INCOMPLETE: at least 1 required file does not exists"
)
if dryRun == False:
workflow = _create_singleSession(
_dict, master_config, 'Linear',
'singleSession_{0}_{1}'.format(_dict['subject'],
_dict['session']))
print("Starting session {0}".format(session))
# HACK Hard-coded to SGEGraph, but --wfrun is ignored completely
run_workflow(workflow,
plugin=master_config['plugin_name'],
plugin_args=master_config['plugin_args'])
else:
print("EXITING WITHOUT WORK DUE TO dryRun flag")
except:
raise
finally:
try:
database.close_connection()
except:
pass
def writeCVSubsetFile(environment, experiment, pipeline, cluster, csv_file,
test_size, hasHeader):
from utilities.misc import add_dict
master_config = {}
for configDict in [environment, experiment, pipeline, cluster]:
master_config = add_dict(master_config, configDict)
"""
read in csv file
"""
import csv
csv_data = []
with open(csv_file, mode='r') as infile:
reader = csv.DictReader(infile, skipinitialspace=True)
for row in reader:
csv_data.append(row)
print(csv_data)
totalSampleSize = len(csv_data)
print(totalSampleSize)
cv_subsets = subsample_crossValidationSet(totalSampleSize, test_size)
"""
global variable
"""
## HACK FOR NOW SHOULD BE MORE ELEGANT FROM THE .config file
BASE_DATA_GRABBER_DIR = '/Shared/johnsonhj/HDNI/ReferenceData/Neuromorphometrics/2012Subscription'
#master_config = {'queue':'HJ',
# 'long_q':'HJ'}
"""
workflow
"""
import nipype.pipeline.engine as pe
import nipype.interfaces.io as nio
from .WorkupJointFusion import CreateJointFusionWorkflow
CV_JointFusion_WF = pe.Workflow(name="CV_JointFusion")
CV_JointFusion_WF.base_dir = master_config['cachedir']
subset_no = 1
for subset in cv_subsets:
print("-" * 80)
print(" Creat a subset workflow Set " + str(subset_no))
print("-" * 80)
trainData = [csv_data[i] for i in subset['train']]
testData = [csv_data[i] for i in subset['test']]
print([(trainData[i])['id'] for i in range(len(trainData))])
for testSession in testData:
JointFusionWFName = "JointFusion_Set{0}_{1}".format(
subset_no, testSession['id'])
myJointFusion = CreateJointFusionWorkflow(
JointFusionWFName,
master_config,
[(trainData[i])['id'] for i in range(len(trainData))],
BASE_DATA_GRABBER_DIR,
runFixFusionLabelMap=False)
testSessionName = "testSessionSpec_Set{0}_{1}".format(
subset_no, testSession['id'])
testSessionSpec = pe.Node(interface=IdentityInterface(fields=[
't1_average', 'tissueLabel', 'template_leftHemisphere',
'landmarkInACPCAlignedSpace', 'template_weights_50Lmks_wts',
'labelFilename'
]),
run_without_submitting=True,
name=testSessionName)
CV_JointFusion_WF.connect(testSessionSpec, 't1_average',
myJointFusion, 'inputspec.subj_t1_image')
CV_JointFusion_WF.connect(testSessionSpec, 'tissueLabel',
myJointFusion,
'inputspec.subj_fixed_head_labels')
CV_JointFusion_WF.connect(testSessionSpec,
'template_leftHemisphere', myJointFusion,
'inputspec.subj_left_hemisphere')
CV_JointFusion_WF.connect(testSessionSpec,
'landmarkInACPCAlignedSpace',
myJointFusion, 'inputspec.subj_lmks')
CV_JointFusion_WF.connect(testSessionSpec,
'template_weights_50Lmks_wts',
myJointFusion,
'inputspec.atlasWeightFilename')
CV_JointFusion_WF.connect(testSessionSpec, 'labelFilename',
myJointFusion,
'inputspec.labelBaseFilename')
""" set test image information
"""
print(testSession)
testSessionSpec.inputs.t1_average = testSession['t1']
testSessionSpec.inputs.tissueLabel = testSession[
'fixed_head_label']
testSessionSpec.inputs.template_leftHemisphere = testSession[
'warpedAtlasLeftHemisphere']
testSessionSpec.inputs.landmarkInACPCAlignedSpace = testSession[
'lmk']
testSessionSpec.inputs.template_weights_50Lmks_wts = "/Shared/sinapse/scratch/eunyokim/src/NamicExternal/build_Mac_201501/bin/Atlas/Atlas_20131115/20141004_BCD/template_landmarks_50Lmks.fcsv"
testSessionSpec.inputs.labelFilename = 'FS_wmparc.nii.gz'
"""
DataSink
"""
dsName = "DataSink_DS_Set{0}_{1}".format(subset_no,
testSession['id'])
DataSink = pe.Node(name=dsName, interface=nio.DataSink())
DataSink.overwrite = master_config['ds_overwrite']
DataSink.inputs.container = 'CV_Set{0}/{1}'.format(
subset_no, testSession['id'])
DataSink.inputs.base_directory = master_config['resultdir']
CV_JointFusion_WF.connect(
myJointFusion, 'outputspec.JointFusion_neuro2012_labelmap',
DataSink, 'Segmentation.@JointFusion_neuro2012_labelmap')
subset_no = subset_no + 1
#CV_JointFusion_WF.write_graph()
CV_JointFusion_WF.run(plugin=master_config['plugin_name'],
plugin_args=master_config['plugin_args'])
def writeCVSubsetFile( environment, experiment, pipeline, cluster, csv_file, test_size, hasHeader):
from utilities.misc import add_dict
master_config = {}
for configDict in [environment, experiment, pipeline, cluster]:
master_config = add_dict(master_config, configDict)
"""
read in csv file
"""
import csv
csv_data=[]
with open(csv_file, mode='r') as infile:
reader = csv.DictReader(infile, skipinitialspace=True)
for row in reader:
csv_data.append(row)
print(csv_data)
totalSampleSize = len(csv_data)
print(totalSampleSize)
cv_subsets = subsample_crossValidationSet( totalSampleSize, test_size)
"""
global variable
"""
## HACK FOR NOW SHOULD BE MORE ELEGANT FROM THE .config file
BASE_DATA_GRABBER_DIR='/Shared/johnsonhj/HDNI/ReferenceData/Neuromorphometrics/2012Subscription'
#master_config = {'queue':'HJ',
# 'long_q':'HJ'}
"""
workflow
"""
import nipype.pipeline.engine as pe
import nipype.interfaces.io as nio
from .WorkupJointFusion import CreateJointFusionWorkflow
CV_JointFusion_WF = pe.Workflow(name="CV_JointFusion")
CV_JointFusion_WF.base_dir = master_config['cachedir']
subset_no = 1
for subset in cv_subsets:
print("-"*80)
print(" Creat a subset workflow Set " + str(subset_no))
print("-"*80)
trainData = [ csv_data[i] for i in subset['train'] ]
testData = [ csv_data[i] for i in subset['test'] ]
print([ (trainData[i])['id'] for i in range( len(trainData))])
for testSession in testData:
JointFusionWFName = "JointFusion_Set{0}_{1}".format(subset_no, testSession['id'])
myJointFusion = CreateJointFusionWorkflow( JointFusionWFName,
master_config,
[ (trainData[i])['id'] for i in range( len(trainData))],
BASE_DATA_GRABBER_DIR,
runFixFusionLabelMap=False)
testSessionName= "testSessionSpec_Set{0}_{1}".format(subset_no, testSession['id'])
testSessionSpec = pe.Node( interface=IdentityInterface( fields=['t1_average',
'tissueLabel',
'template_leftHemisphere',
'landmarkInACPCAlignedSpace',
'template_weights_50Lmks_wts',
'labelFilename']),
run_without_submitting = True,
name=testSessionName)
CV_JointFusion_WF.connect(testSessionSpec,'t1_average', myJointFusion,'inputspec.subj_t1_image')
CV_JointFusion_WF.connect(testSessionSpec,'tissueLabel',myJointFusion,'inputspec.subj_fixed_head_labels')
CV_JointFusion_WF.connect(testSessionSpec,'template_leftHemisphere', myJointFusion,'inputspec.subj_left_hemisphere')
CV_JointFusion_WF.connect(testSessionSpec,'landmarkInACPCAlignedSpace', myJointFusion,'inputspec.subj_lmks')
CV_JointFusion_WF.connect(testSessionSpec,'template_weights_50Lmks_wts', myJointFusion,'inputspec.atlasWeightFilename')
CV_JointFusion_WF.connect(testSessionSpec, 'labelFilename', myJointFusion, 'inputspec.labelBaseFilename')
""" set test image information
"""
print(testSession)
testSessionSpec.inputs.t1_average = testSession['t1']
testSessionSpec.inputs.tissueLabel = testSession['fixed_head_label']
testSessionSpec.inputs.template_leftHemisphere = testSession['warpedAtlasLeftHemisphere']
testSessionSpec.inputs.landmarkInACPCAlignedSpace = testSession['lmk']
testSessionSpec.inputs.template_weights_50Lmks_wts = "/Shared/sinapse/scratch/eunyokim/src/NamicExternal/build_Mac_201501/bin/Atlas/Atlas_20131115/20141004_BCD/template_landmarks_50Lmks.fcsv"
testSessionSpec.inputs.labelFilename='FS_wmparc.nii.gz'
"""
DataSink
"""
dsName = "DataSink_DS_Set{0}_{1}".format(subset_no,testSession['id'])
DataSink = pe.Node(name=dsName, interface=nio.DataSink())
DataSink.overwrite = master_config['ds_overwrite']
DataSink.inputs.container = 'CV_Set{0}/{1}'.format(subset_no, testSession['id'])
DataSink.inputs.base_directory = master_config['resultdir']
CV_JointFusion_WF.connect(myJointFusion, 'outputspec.JointFusion_neuro2012_labelmap',
DataSink, 'Segmentation.@JointFusion_neuro2012_labelmap')
subset_no=subset_no+1
#CV_JointFusion_WF.write_graph()
CV_JointFusion_WF.run( plugin=master_config['plugin_name'],
plugin_args=master_config['plugin_args'])
def createAndRun(sessions, environment, experiment, pipeline, cluster, useSentinal, dryRun):
from baw_exp import OpenSubjectDatabase
from utilities.misc import add_dict
from collections import OrderedDict
import sys
from workflows.utils import run_workflow
master_config = {}
for configDict in [environment, experiment, pipeline, cluster]:
master_config = add_dict(master_config, configDict)
database = OpenSubjectDatabase(experiment['cachedir'], ['all'], environment['prefix'], experiment['dbfile'])
database.open_connection()
try:
all_sessions = database.getAllSessions()
if not set(sessions) <= set(all_sessions) and 'all' not in sessions:
missing = set(sessions) - set(all_sessions)
assert len(missing) == 0, "Requested sessions are missing from the database: {0}\n\n{1}".format(missing,
all_sessions)
elif 'all' in sessions:
sessions = set(all_sessions)
else:
sessions = set(sessions)
print("!=" * 40)
print("Doing sessions {0}".format(sessions))
print("!=" * 40)
for session in sessions:
_dict = OrderedDict()
t1_list = database.getFilenamesByScantype(session, ['T1-15', 'T1-30'])
if len(t1_list) == 0:
print("ERROR: Skipping session {0} for subject {1} due to missing T1's".format(session, subject))
print("REMOVE OR FIX BEFORE CONTINUING")
continue
subject = database.getSubjFromSession(session)
_dict['session'] = session
_dict['project'] = database.getProjFromSession(session)
_dict['subject'] = subject
_dict['T1s'] = t1_list
_dict['T2s'] = database.getFilenamesByScantype(session, ['T2-15', 'T2-30'])
_dict['BadT2'] = False
if _dict['T2s'] == database.getFilenamesByScantype(session, ['T2-15']):
print("This T2 is not going to be used for JointFusion")
print("This T2 is not going to be used for JointFusion")
print("This T2 is not going to be used for JointFusion")
print("This T2 is not going to be used for JointFusion")
print(_dict['T2s'])
_dict['BadT2'] = True
_dict['PDs'] = database.getFilenamesByScantype(session, ['PD-15', 'PD-30'])
_dict['FLs'] = database.getFilenamesByScantype(session, ['FL-15', 'FL-30'])
_dict['EMSP'] = database.getFilenamesByScantype(session, ['EMSP'])
_dict['OTHERs'] = database.getFilenamesByScantype(session, ['OTHER-15', 'OTHER-30'])
sentinal_file_basedir = os.path.join(
master_config['resultdir'],
_dict['project'],
_dict['subject'],
_dict['session']
)
sentinal_file_list = list()
sentinal_file_list.append(os.path.join(sentinal_file_basedir))
if 'denoise' in master_config['components']:
# # NO SENTINAL FILE
pass
# # Use t1 average sentinal file if specified.
if 'landmark' in master_config['components']:
sentinal_file_list.append(os.path.join(
sentinal_file_basedir,
"ACPCAlign",
"landmarkInitializer_atlas_to_subject_transform.h5"
))
if 'tissue_classify' in master_config['components']:
for tc_file in ["complete_brainlabels_seg.nii.gz", "t1_average_BRAINSABC.nii.gz"]:
sentinal_file_list.append(os.path.join(
sentinal_file_basedir,
"TissueClassify",
tc_file
))
if 'warp_atlas_to_subject' in master_config['components']:
warp_atlas_file_list = [
"hncma_atlas.nii.gz",
"l_accumben_ProbabilityMap.nii.gz",
"l_caudate_ProbabilityMap.nii.gz",
"l_globus_ProbabilityMap.nii.gz",
"l_hippocampus_ProbabilityMap.nii.gz",
"l_putamen_ProbabilityMap.nii.gz",
"l_thalamus_ProbabilityMap.nii.gz",
"left_hemisphere_wm.nii.gz",
"phi.nii.gz",
"r_accumben_ProbabilityMap.nii.gz",
"r_caudate_ProbabilityMap.nii.gz",
"r_globus_ProbabilityMap.nii.gz",
"r_hippocampus_ProbabilityMap.nii.gz",
"r_putamen_ProbabilityMap.nii.gz",
"r_thalamus_ProbabilityMap.nii.gz",
"rho.nii.gz",
"right_hemisphere_wm.nii.gz",
"template_WMPM2_labels.nii.gz",
"template_headregion.nii.gz",
"template_leftHemisphere.nii.gz",
"template_nac_labels.nii.gz",
"template_rightHemisphere.nii.gz",
"template_ventricles.nii.gz",
"theta.nii.gz"
]
for ff in warp_atlas_file_list:
sentinal_file_list.append(os.path.join(
sentinal_file_basedir,
"WarpedAtlas2Subject",
ff
))
if 'jointfusion_2015_wholebrain' in master_config['components']:
sentinal_file_list.append(os.path.join(
sentinal_file_basedir,
"TissueClassify",
"JointFusion_HDAtlas20_2015_lobar_label.nii.gz"
))
sentinal_file_list.append(os.path.join(
sentinal_file_basedir,
"TissueClassify",
"lobeVolumes_JSON.json"
))
if master_config['workflow_phase'] == 'atlas-based-reference':
atlasDirectory = os.path.join(master_config['atlascache'], 'spatialImages', 'rho.nii.gz')
sentinal_file_list.append(atlasDirectory)
else:
atlasDirectory = os.path.join(master_config['previousresult'], subject, 'Atlas', 'AVG_rho.nii.gz')
sentinal_file_list.append(atlasDirectory)
sentinal_file_list.append(
os.path.join(master_config['previousresult'], subject, 'Atlas', 'AVG_template_headregion.nii.gz'))
if os.path.exists(atlasDirectory):
print("LOOKING FOR DIRECTORY {0}".format(atlasDirectory))
else:
print("MISSING REQUIRED ATLAS INPUT {0}".format(atlasDirectory))
print("SKIPPING: {0} prerequisites missing".format(session))
continue
## Use different sentinal file if segmentation specified.
from workflows.baseline import DetermineIfSegmentationShouldBeDone
do_BRAINSCut_Segmentation = DetermineIfSegmentationShouldBeDone(master_config)
if do_BRAINSCut_Segmentation:
sentinal_file_list.append(os.path.join(
sentinal_file_basedir,
"CleanedDenoisedRFSegmentations",
"allLabels_seg.nii.gz"
))
def allPathsExists(list_of_paths):
is_missing = False
for ff in list_of_paths:
if not os.path.exists(ff):
is_missing = True
print("MISSING: {0}".format(ff))
return not is_missing
if useSentinal and allPathsExists(sentinal_file_list):
print("SKIPPING: {0} exists".format(sentinal_file_list))
else:
print("PROCESSING INCOMPLETE: at least 1 required file does not exists")
if dryRun == False:
workflow = _create_singleSession(_dict, master_config, 'Linear',
'singleSession_{0}_{1}'.format(_dict['subject'], _dict['session']))
print("Starting session {0}".format(session))
# HACK Hard-coded to SGEGraph, but --wfrun is ignored completely
run_workflow(workflow, plugin=master_config['plugin_name'],
plugin_args=master_config['plugin_args'])
else:
print("EXITING WITHOUT WORK DUE TO dryRun flag")
except:
raise
finally:
try:
database.close_connection()
except:
pass
