def methods_write_json_redcap_swi_instrument(input_dir, verbose):
""" Write MagTrans Instrument to JSON output file"""
cenc_dirs = cenc.directories(input_dir)
swir = os.path.join(cenc_dirs['swi']['dirs']['register'], 'swir.nii.gz')
labels = [
os.path.join(cenc_dirs['swi']['dirs']['input'],
'gm.cerebral_cortex.nii.gz'),
os.path.join(cenc_dirs['swi']['dirs']['input'],
'gm.subcortical.nii.gz'),
os.path.join(cenc_dirs['swi']['dirs']['input'], 'wm.cerebral.nii.gz'),
os.path.join(cenc_dirs['swi']['dirs']['input'],
'wmlesions_lpa_mask.nii.gz')
]
pandas.set_option('expand_frame_repr', False)
df_stats_gm_cortical = iw_labels.measure_image_stats(labels[0], swir)
df_stats_gm_subcortical = iw_labels.measure_image_stats(labels[1], swir)
df_stats_wm_cerebral = iw_labels.measure_image_stats(labels[2], swir)
df_stats_wm_lesions = iw_labels.measure_image_stats(labels[3], swir)
dict_redcap = OrderedDict(
(('subject_id', cenc_dirs['cenc']['id']), ('swi_analyst',
getpass.getuser()),
('swi_datetime',
'{:%Y-%b-%d %H:%M:%S}'.format(datetime.datetime.now())),
('swi_gm_cortical_mean',
'{0:4.3f}'.format(df_stats_gm_cortical['mean'].values[0])),
('swi_gm_cortical_std',
'{0:4.3f}'.format(df_stats_gm_cortical['std'].values[0])),
('swi_gm_subcortical_mean',
'{0:4.3f}'.format(df_stats_gm_subcortical['mean'].values[0])),
('swi_gm_subcortical_std',
'{0:4.3f}'.format(df_stats_gm_subcortical['std'].values[0])),
('swi_wm_cortical_mean',
'{0:4.3f}'.format(df_stats_wm_cerebral['mean'].values[0])),
('swi_wm_cortical_std',
'{0:4.3f}'.format(df_stats_wm_cerebral['std'].values[0])),
('swi_wmlesions_mean',
'{0:4.3f}'.format(df_stats_wm_lesions['mean'].values[0])),
('swi_wmlesions_std',
'{0:4.3f}'.format(df_stats_wm_lesions['std'].values[0]))))
magtrans_json_filename = os.path.join(cenc_dirs['swi']['dirs']['results'],
'magtrans.json')
with open(magtrans_json_filename, 'w') as outfile:
json.dump(dict_redcap,
outfile,
indent=4,
ensure_ascii=True,
sort_keys=False)
if verbose:
cenc.print_json_redcap_instrument(magtrans_json_filename)
return
def results( input_dir ):
""" Gather results and write the MagTran JSON output file"""
cenc_dirs = cenc.directories( input_dir )
mt_input_dir = cenc_dirs['mt']['dirs']['input']
mt_01_register_dir = cenc_dirs['mt']['dirs']['register']
mt_results_dir = cenc_dirs['mt']['dirs']['results']
util.mkcd_dir( [ mt_results_dir ], True)
result_files = [ [ os.path.join( cenc_dirs['mt']['dirs']['register'], 'mt_Affine_nu__mt_m0_Warped.nii.gz'),
os.path.join( cenc_dirs['mt']['dirs']['results'], 'mt_Affine_nu__mt_m0.nii.gz')],
[ os.path.join( cenc_dirs['mt']['dirs']['register'], 'mt_Affine_nu__mt_m1_Warped.nii.gz'),
os.path.join( cenc_dirs['mt']['dirs']['results'], 'mt_Affine_nu__mt_m1.nii.gz')],
[ os.path.join( cenc_dirs['mt']['dirs']['02-stats'], 'magtrans.json'),
os.path.join( cenc_dirs['mt']['dirs']['results'], 'magtrans.json') ],
[ os.path.join( cenc_dirs['mt']['dirs']['register'], 'mtr.nii.gz'),
os.path.join( cenc_dirs['mt']['dirs']['results'], 'mtr.nii.gz') ],
[ os.path.join( cenc_dirs['mt']['dirs']['input'], 'nu.nii.gz'),
os.path.join( cenc_dirs['mt']['dirs']['results'], 'nu.nii.gz') ],
[ os.path.join( cenc_dirs['mt']['dirs']['register'], 'mtr.nii.gz'),
os.path.join( cenc_dirs['results']['dirs']['images'], 'mtr.nii.gz') ]
]
for ii in result_files:
util.force_hard_link( ii[0], ii[1])
return
def qa_results(in_dir, verbose=False):
cenc_dirs = cenc.directories(in_dir)
cenc.print_json_redcap_instrument( os.path.join(cenc_dirs['mt']['dirs']['results'],'magtrans.json'))
result_files = [os.path.join(cenc_dirs['mt']['dirs']['results'], 'nu.nii.gz') + ':colormap=grayscale',
os.path.join(cenc_dirs['mt']['dirs']['results'],
'mt_Affine_nu__mt_m0.nii.gz') + ':colormap=grayscale:visible=0',
os.path.join(cenc_dirs['mt']['dirs']['results'],
'mt_Affine_nu__mt_m1.nii.gz') + ':colormap=grayscale:visible=0',
os.path.join(cenc_dirs['mt']['dirs']['results'],
'mtr.nii.gz') + ':colormap=jet:colorscale=0,0.6:opacity=0.5'
]
qa_command = ['freeview', '-v'] + result_files
if verbose:
print
print(' '.join(qa_command))
print
DEVNULL = open(os.devnull, 'wb')
pipe = subprocess.Popen([' '.join(qa_command)], shell=True,
stdin=DEVNULL, stdout=DEVNULL, stderr=DEVNULL, close_fds=True)
def methods_02_lpa(input_dir, verbose):
cenc_dirs = cenc.directories(input_dir)
wm_lesions_dir = cenc_dirs['wmlesions']['dirs']['root']
wm_lesions_lpa_dir = cenc_dirs['wmlesions']['dirs']['lpa']
util.mkcd_dir([cenc_dirs['wmlesions']['dirs']['lpa']], True)
util.copy_inputs([
os.path.join(cenc_dirs['wmlesions']['dirs']['register'],
't2flair_Affine_nu__t2flair_Warped.nii.gz')
], cenc_dirs['wmlesions']['dirs']['lpa'])
glob_files = glob.glob('*.gz')
for ii in glob_files:
os.system('gunzip ' + ii)
os.chmod(str.replace(ii, '.gz', ''),
stat.S_IRUSR | stat.S_IRGRP | stat.S_IWUSR | stat.S_IWGRP)
# Run Matlab
command = ['cenc_wmlesions_run.sh', cenc_dirs['wmlesions']['dirs']['lpa']]
util.iw_subprocess(command, verbose, verbose, False)
os.chdir(cenc_dirs['wmlesions']['dirs']['lpa'])
for ii in glob.glob('*.nii'):
os.system('gzip ' + ii)
os.chmod(str.replace(ii, '.nii', '.nii.gz'),
stat.S_IRUSR | stat.S_IRGRP | stat.S_IWUSR | stat.S_IWGRP)
def qa_results(in_dir, verbose=False):
cenc_dirs = cenc.directories(in_dir)
cenc.print_json_redcap_instrument(
os.path.join(cenc_dirs['wmlesions']['dirs']['results'],
'wmlesions.json'))
result_files = [
os.path.join(cenc_dirs['wmlesions']['dirs']['results'], 'nu.nii.gz') +
':colormap=grayscale:visible=0',
os.path.join(cenc_dirs['wmlesions']['dirs']['results'],
'wmlesions_lpa_t2flair.nii.gz') + ':colormap=grayscale',
os.path.join(cenc_dirs['wmlesions']['dirs']['results'],
'wmlesions_lpa_pmap.nii.gz') +
':colormap=jet:visible=0:opacity=0.5',
os.path.join(cenc_dirs['wmlesions']['dirs']['results'],
'wmlesions_lpa_labels.nii.gz') +
':colormap=jet:opacity=0.5'
]
qa_command = ['freeview', '-v'] + result_files
if verbose:
print(' ')
print(' '.join(qa_command))
print(' ')
DEVNULL = open(os.devnull, 'wb')
pipe = subprocess.Popen([' '.join(qa_command)],
shell=True,
stdin=DEVNULL,
stdout=DEVNULL,
stderr=DEVNULL,
close_fds=True)
def status_results(input_dir, verbose):
cenc_dirs = cenc.directories(input_dir)
result_files = [
os.path.join(cenc_dirs['results']['dirs']['labels'],
'gm.cerebral_cortex.nii.gz'),
os.path.join(cenc_dirs['results']['dirs']['labels'],
'gm.cerebellum.nii.gz'),
os.path.join(cenc_dirs['results']['dirs']['labels'],
'wm.cerebral.nii.gz'),
os.path.join(cenc_dirs['results']['dirs']['labels'],
'wm.cerebellum.nii.gz'),
os.path.join(cenc_dirs['results']['dirs']['labels'],
'ventricles.nii.gz'),
os.path.join(cenc_dirs['results']['dirs']['labels'], 'nu.nii.gz'),
os.path.join(cenc_dirs['results']['dirs']['images'], 'nu.nii.gz'),
os.path.join(cenc_dirs['results']['dirs']['images'], 'nu_brain.nii.gz')
]
freesurfer_status_results = util.check_files(result_files, False)
if verbose:
print(cenc_dirs['cenc']['id'] + ', cenc_freesurfer, results, ' +
str(freesurfer_status_results))
return freesurfer_status_results
def methods_write_json_redcap_instrument(in_dir, labels_stats_csv,
labels_pmap_stats_csv, verbose):
""" Writes out REdCap instrument measures to a JSON file"""
cenc_dirs = cenc.directories(in_dir)
df_label_stats = pandas.read_csv(labels_stats_csv)
df_pmap_stats = pandas.read_csv(labels_pmap_stats_csv)
number_of_lesions, _ = df_label_stats.shape
if number_of_lesions > 0:
total_lesion_volume = df_label_stats['volume_mm3'].sum()
mean_lesion_volume = df_label_stats['volume_mm3'].mean()
std_lesion_volume = df_label_stats['volume_mm3'].std()
min_lesion_volume = df_label_stats['volume_mm3'].min()
max_lesion_volume = df_label_stats['volume_mm3'].max()
min_lesion_probability = df_pmap_stats['min'].min()
max_lesion_probability = df_pmap_stats['max'].max()
else:
total_lesion_volume = 0
mean_lesion_volume = 0
std_lesion_volume = 0
min_lesion_volume = 0
max_lesion_volume = 0
min_lesion_probability = 0
max_lesion_probability = 0
dict_redcap = OrderedDict(
(('subject_id', cenc_dirs['cenc']['id']), ('wm_lesions_analyst',
getpass.getuser()),
('wm_lesions_datetime',
'{:%Y-%b-%d %H:%M:%S}'.format(datetime.datetime.now())),
('wm_lesions_number', '{0:d}'.format(int(number_of_lesions))),
('wm_lesions_total_volume_mm3',
'{0:5.1f}'.format(total_lesion_volume)),
('wm_lesions_mean_volume_mm3', '{0:5.1f}'.format(mean_lesion_volume)),
('wm_lesions_std_volume_mm3', '{0:5.1f}'.format(std_lesion_volume)),
('wm_lesions_min_lesion_volume_mm3',
'{0:5.1f}'.format(min_lesion_volume)),
('wm_lesions_max_lesion_volume_mm3',
'{0:5.1f}'.format(max_lesion_volume)),
('wm_lesions_min_lesion_probability',
'{0:5.4f}'.format(min_lesion_probability)),
('wm_lesions_max_lesion_probability',
'{0:5.4f}'.format(max_lesion_probability))))
wmlesions_json_filename = os.path.join(os.path.dirname(labels_stats_csv),
'wmlesions.json')
with open(wmlesions_json_filename, 'w') as outfile:
json.dump(dict_redcap,
outfile,
indent=4,
ensure_ascii=True,
sort_keys=False)
if verbose:
cenc.print_json_redcap_instrument(wmlesions_json_filename)
def mt_link_inputs( input_dir, link_to_dir, change_to_dir = True ):
cenc_dirs = cenc.directories( input_dir )
util.mkcd_dir( [ link_to_dir ], change_to_dir )
input_files = cenc_dirs['mt']['inputs']
label_files = cenc_dirs['mt']['labels']
util.link_inputs( input_files + label_files, link_to_dir )
def methods_02_stats(input_dir, verbose=False):
# Register MT images to nu.nii.gz
cenc_dirs = cenc.directories(input_dir)
util.mkcd_dir([cenc_dirs['mt']['dirs']['02-stats']], True)
methods_write_json_redcap_mt_instrument(input_dir, verbose)
return
def status_run( input_dir, verbose ):
cenc_dirs = cenc.directories( input_dir )
result_files = [ os.path.join( cenc_dirs['freesurfer']['mri'], 'wmparc.mgz') ]
freesurfer_status_run = util.check_files(result_files, False)
if verbose:
print( cenc_dirs['cenc']['id'] + ', cenc_freesurfer, run, ' + str(freesurfer_status_run) )
return freesurfer_status_run
def status_methods_02_stats( input_dir, verbose=False ):
cenc_dirs = cenc.directories( input_dir )
result_files = [ os.path.join( cenc_dirs['mt']['dirs']['02-stats'], 'magtrans.json') ]
mt_status = util.check_files(result_files, False)
if verbose:
print( cenc_dirs['cenc']['id'] + ', cenc_mt, ' + 'methods_02_stats' + ', ' + str(mt_status) )
return mt_status
def status_prepare( input_dir, verbose=False ):
cenc_dirs = cenc.directories( input_dir )
input_files = cenc_dirs['mt']['inputs']
label_files = cenc_dirs['mt']['labels']
mt_status = util.check_files(input_files + label_files, False)
if verbose:
print( cenc_dirs['cenc']['id'] + ', cenc_mt, ' + 'prepare' + ', ' + str(mt_status) )
return mt_status
def prepare(input_dir, verbose=False):
if verbose:
print('Entering cenc_swi.py prepare')
swi_info = cenc.directories(input_dir)
input_files = swi_info['swi']['inputs']
label_files = swi_info['swi']['labels']
swi_link_inputs(input_dir, swi_info['swi']['dirs']['input'])
swi_link_inputs(input_dir, swi_info['swi']['dirs']['input'])
return
def prepare( input_dir ):
cenc_dirs = cenc.directories( input_dir )
util.mkcd_dir( [ cenc_dirs['freesurfer']['input'] ])
input_files = [ os.path.join( cenc_dirs['cenc']['reorient'], 't1w.nii.gz'),
os.path.join( cenc_dirs['cenc']['reorient'], 't2flair.nii.gz'),
os.path.join( cenc_dirs['cenc']['reorient'], 't2tse.nii.gz')
]
util.link_inputs( input_files, cenc_dirs['freesurfer']['input'] )
return
def status_inputs(input_dir, stdout=False, verbose=False):
cenc_dirs = cenc.directories(input_dir)
input_files = cenc_dirs['mt']['inputs']
label_files = cenc_dirs['mt']['labels']
mt_status = util.check_files(input_files + label_files, verbose)
if stdout:
print(cenc_dirs['cenc']['id'] + ', cenc_mt, ' + 'input' + ', ' +
str(mt_status))
return mt_status
def recon_all(input_dir):
cenc_dirs = cenc.directories(input_dir)
freesurfer_command = [
'recon-all', '-sd', cenc_dirs['cenc']['freesurfer_subjects_dir'],
'-subjid', cenc_dirs['cenc']['id'], '-all', '-i', 't1w.nii.gz',
'-qcache', '-measure', 'thickness', '-measure', 'curv', '-measure',
'sulc', '-measure', 'area', '-measure', 'jacobian_white'
]
util.iw_subprocess(freesurfer_command, True, True, True)
return
def prepare( input_dir, verbose=False ):
if verbose:
print('Entering cenc_mt.py prepare')
cenc_dirs = cenc.directories( input_dir )
input_files = cenc_dirs['mt']['inputs']
label_files = cenc_dirs['mt']['labels']
mt_link_inputs( input_dir, cenc_dirs['mt']['dirs']['input'] )
mt_link_inputs( input_dir, cenc_dirs['mt']['dirs']['input'] )
return
def status_inputs(input_dir, verbose=False):
cenc_dirs = cenc.directories(input_dir)
input_files = cenc_dirs['swi']['inputs']
label_files = cenc_dirs['swi']['labels']
swi_status = util.check_files(input_files + label_files, False)
if verbose:
print(cenc_dirs['cenc']['id'] + ', cenc_swi, ' + 'input' + ', ' +
str(swi_status))
return swi_status
def status_methods_01_register(input_dir, verbose=False):
cenc_dirs = cenc.directories(input_dir)
result_files = [os.path.join(cenc_dirs['mt']['dirs']['register'], 'mt_Affine_nu__mt_m0_Warped.nii.gz'),
os.path.join(cenc_dirs['mt']['dirs']['register'], 'mt_Affine_nu__mt_m1_Warped.nii.gz'),
os.path.join(cenc_dirs['mt']['dirs']['register'], 'mtr.nii.gz')
]
mt_status = util.check_files(result_files, False)
if verbose:
print(cenc_dirs['cenc']['id'] + ', cenc_mt, ' + 'methods_01_register' + ', ' + str(mt_status))
return mt_status
def status_results(input_dir, verbose=False):
cenc_dirs = cenc.directories( input_dir)
result_files = [ os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_t2flair.nii.gz'),
os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'nu.nii.gz'),
os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_pmap.nii.gz'),
os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_labels.nii.gz')
]
wmlesions_status = util.check_files(result_files, False)
if verbose:
print( cenc_dirs['cenc']['id'] + ', cenc_wmlesions, results,' + str(wmlesions_status) )
return wmlesions_status
def status_methods_02_stats(input_dir, verbose=False):
cenc_info = cenc.directories(input_dir)
result_files = [
os.path.join(cenc_info['swi']['dirs']['results'], 'magtrans.json')
]
swi_status = util.check_files(result_files, False)
if verbose:
print(cenc_info['cenc']['id'] + ', cenc_swi, ' + 'methods_02_stats' +
', ' + str(swi_status))
return swi_status
def methods_01_register(input_dir, verbose=False):
# Register SWI images to nu.nii.gz
cenc_dirs = cenc.directories(input_dir)
swi_link_inputs(input_dir, cenc_dirs['swi']['dirs']['register'])
ants_register('swi_magnitude')
util.force_hard_link('swi_Affine_nu__swi_magnitude_Warped.nii.gz',
'swi_Affine_nu__swi_magnitude.nii.gz')
ants_apply_transform('swi')
ants_apply_transform('swi_phase')
return
def methods_01_register( input_dir, verbose=False):
# Register MT images to nu.nii.gz
cenc_dirs = cenc.directories( input_dir )
mt_link_inputs( input_dir, cenc_dirs['mt']['dirs']['register'] )
ants_register('mt_m0')
ants_register('mt_m1')
# Calculate MTR image
command = ['ImageMath', 3, 'mtr.nii.gz', 'MTR', 'mt_Affine_nu__mt_m0_Warped.nii.gz',
'mt_Affine_nu__mt_m1_Warped.nii.gz', 'nu_brain.nii.gz']
util.iw_subprocess( command, verbose, verbose, False)
return
def status_results( input_dir, verbose=False ):
cenc_dirs = cenc.directories( input_dir )
result_files = [ os.path.join( cenc_dirs['mt']['dirs']['results'], 'mt_Affine_nu__mt_m0.nii.gz'),
os.path.join( cenc_dirs['mt']['dirs']['results'], 'mt_Affine_nu__mt_m1.nii.gz'),
os.path.join( cenc_dirs['mt']['dirs']['results'], 'mtr.nii.gz'),
os.path.join( cenc_dirs['mt']['dirs']['results'], 'nu.nii.gz'),
os.path.join( cenc_dirs['results']['dirs']['images'], 'mtr.nii.gz')
]
mt_status = util.check_files(result_files, False)
if verbose:
print( cenc_dirs['cenc']['id'] + ', cenc_mt, ' + 'results' + ', ' + str(mt_status) )
return mt_status
def prepare( input_dir ):
cenc_dirs = cenc.directories( input_dir)
wm_lesions_dir = cenc_dirs['wmlesions']['dirs']['root']
wm_lesions_input_dir = cenc_dirs['wmlesions']['dirs']['input']
wm_lesions_lpa_dir = cenc_dirs['wmlesions']['dirs']['lpa']
# Create Input Directory if it doesn't exist and link files
files = [ os.path.abspath( os.path.join( cenc_dirs['results']['dirs']['images'], 'nu.nii.gz')),
os.path.abspath( os.path.join( cenc_dirs['results']['dirs']['labels'], 'mask.nii.gz')),
os.path.abspath( os.path.join( cenc_dirs['cenc']['reorient'], 't2flair.nii.gz'))
]
util.mkcd_dir( os.path.join( wm_lesions_input_dir ) )
util.link_inputs( files, wm_lesions_input_dir )
def prepare(input_dir):
cenc_dirs = cenc.directories(input_dir)
util.mkcd_dir([cenc_dirs['freesurfer']['input']])
input_files = [os.path.join(cenc_dirs['cenc']['reorient'], 't1w.nii.gz')]
# Preliminary testing of Freesurfer with the T2FLAIR and T2_TSE has not been very successful.
# Removing them from the workflow.
#
# input_files = [ os.path.join( cenc_dirs['cenc']['reorient'], 't2flair.nii.gz'),
# os.path.join( cenc_dirs['cenc']['reorient'], 't2tse.nii.gz')
# ]
util.link_inputs(input_files, cenc_dirs['freesurfer']['input'])
return
def methods_01_register( input_dir, verbose ):
cenc_dirs = cenc.directories( input_dir)
wm_lesions_dir = cenc_dirs['wmlesions']['dirs']['root']
wm_lesions_lpa_dir = cenc_dirs['wmlesions']['dirs']['lpa']
# Register
util.mkcd_dir( [ cenc_dirs['wmlesions']['dirs']['register'] ], True)
files = [ os.path.join( cenc_dirs['wmlesions']['dirs']['input'], 'nu.nii.gz'),
os.path.join( cenc_dirs['wmlesions']['dirs']['input'], 't2flair.nii.gz'),
os.path.join( cenc_dirs['results']['dirs']['labels'], 'mask.nii.gz')
]
util.link_inputs( files, cenc_dirs['wmlesions']['dirs']['register'] )
ants_register('t2flair')
def results( input_dir):
cenc_dirs = cenc.directories( input_dir)
util.mkcd_dir( [ cenc_dirs['wmlesions']['dirs']['results'] ], True)
# Link Files
link_result_files = [ [ os.path.join( cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_t2flair.nii.gz'),
os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_t2flair.nii.gz') ],
[ os.path.join( cenc_dirs['wmlesions']['dirs']['input'], 'nu.nii.gz'),
os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'nu.nii.gz') ],
[ os.path.join( cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_pmap.nii.gz'),
os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_pmap.nii.gz')],
[ os.path.join( cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions.json'),
os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions.json')],
[os.path.join(cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_labels.nii.gz'),
os.path.join(cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_labels.nii.gz')],
[os.path.join(cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_labels.csv'),
os.path.join(cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_labels.csv')],
[ os.path.join( cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_mask.nii.gz'),
os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_mask.nii.gz')],
[ os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_pmap.nii.gz'),
os.path.join( cenc_dirs['results']['dirs']['images'], 'wmlesions_lpa_pmap.nii.gz')],
[ os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_mask.nii.gz'),
os.path.join( cenc_dirs['results']['dirs']['labels'], 'wmlesions_lpa_mask.nii.gz')],
[ os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_labels.nii.gz'),
os.path.join( cenc_dirs['results']['dirs']['labels'], 'wmlesions_lpa_labels.nii.gz')
]
]
for ii in link_result_files:
util.force_hard_link( ii[0], ii[1])
def status_results(input_dir, verbose=False):
cenc_info = cenc.directories(input_dir)
result_files = [
os.path.join(cenc_info['swi']['dirs']['results'],
'swi_Affine_nu__swi_m0.nii.gz'),
os.path.join(cenc_info['swi']['dirs']['results'],
'swi_Affine_nu__swi_m1.nii.gz'),
os.path.join(cenc_info['swi']['dirs']['results'], 'swir.nii.gz'),
os.path.join(cenc_info['swi']['dirs']['results'], 'nu.nii.gz'),
os.path.join(cenc_info['results']['dirs']['images'], 'swir.nii.gz')
]
swi_status = util.check_files(result_files, False)
if verbose:
print(cenc_info['cenc']['id'] + ', cenc_swi, ' + 'results' + ', ' +
str(swi_status))
return swi_status
def status_methods_01_register(config, verbose=False):
input_dir = config['dirs']['input']
cenc_dirs = cenc.directories(input_dir)
result_files = [
os.path.join(cenc_dirs['swi']['dirs']['register'],
'swi_Affine_nu__swi_magnitude.nii.gz'),
os.path.join(cenc_dirs['swi']['dirs']['register'],
'swi_Affine_nu__swi_phase.nii.gz'),
os.path.join(cenc_dirs['swi']['dirs']['register'],
'swi_Affine_nu__swi.nii.gz')
]
swi_status = util.check_files(result_files, False)
if verbose:
print(cenc_dirs['cenc']['id'] + ', cenc_swi, ' +
'methods_01_register' + ', ' + str(swi_status))
return swi_status
