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 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 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 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)