def make_workflow_from_user_options():
"""Parser/validator for the cmd line args."""
parser = get_parser()
if len(sys.argv) < 2:
print('Too few arguments!')
parser.print_help()
parser.exit(1)
# parsing
try:
user_args = parser.parse_args()
except:
parser.exit(1)
vis_type = 'func_mri'
type_of_features = 'func_mri'
if user_args.bids_dir is not None and user_args.user_dir is None:
in_dir, in_dir_type = check_bids_dir(user_args.bids_dir)
id_list = None
name_pattern = None
images_for_id = None
elif user_args.bids_dir is None and user_args.user_dir is not None:
name_pattern = user_args.name_pattern
in_dir = realpath(user_args.user_dir)
in_dir_type = 'generic'
id_list, images_for_id = check_id_list_with_regex(user_args.id_list, in_dir, name_pattern)
else:
raise ValueError('Invalid args: specify only one of bids_dir or user_dir, not both.')
out_dir = check_out_dir(user_args.out_dir, in_dir)
no_preproc = user_args.no_preproc
views = check_views(user_args.views)
num_slices_per_view, num_rows_per_view = check_finite_int(user_args.num_slices,
user_args.num_rows)
outlier_method, outlier_fraction, \
outlier_feat_types, disable_outlier_detection = check_outlier_params(
user_args.outlier_method, user_args.outlier_fraction,
user_args.outlier_feat_types, user_args.disable_outlier_detection,
id_list, vis_type, type_of_features)
wf = FmriRatingWorkflow(in_dir, out_dir,
id_list=id_list,
images_for_id=images_for_id,
issue_list=cfg.func_mri_default_issue_list,
name_pattern=name_pattern, in_dir_type=in_dir_type,
no_preproc=no_preproc,
outlier_method=outlier_method, outlier_fraction=outlier_fraction,
outlier_feat_types=outlier_feat_types,
disable_outlier_detection=disable_outlier_detection,
prepare_first=user_args.prepare_first, vis_type=vis_type,
views=views, num_slices_per_view=num_slices_per_view,
num_rows_per_view=num_rows_per_view)
return wf
def parse_user_args():
"""Parser/validator for the cmd line args."""
parser = get_parser()
if len(sys.argv) < 2:
print('Too few arguments!')
parser.print_help()
parser.exit(1)
# parsing
try:
user_args = parser.parse_args()
except:
parser.exit(1)
# TODO methods to restore from previous runs, without having re-enter all parameters
vis_type, label_set = check_labels(user_args.vis_type, user_args.labels)
in_dir, source_of_features = check_input_dir(user_args.fs_dir,
user_args.user_dir, vis_type)
mri_name = user_args.mri_name
seg_name = user_args.seg_name
id_list, images_for_id = check_id_list(user_args.id_list, in_dir, vis_type,
mri_name, seg_name)
out_dir = check_out_dir(user_args.out_dir, in_dir)
alpha_set = check_alpha_set(user_args.alpha_set)
views = check_views(user_args.views)
num_slices, num_rows = check_finite_int(user_args.num_slices,
user_args.num_rows)
contour_color = user_args.contour_color
if not is_color_like(contour_color):
raise ValueError(
'Specified color is not valid. Choose a valid spec from\n https://matplotlib.org/users/colors.html'
)
outlier_method, outlier_fraction, outlier_feat_types, no_outlier_detection = check_outlier_params(
user_args.outlier_method, user_args.outlier_fraction,
user_args.outlier_feat_types, user_args.disable_outlier_detection,
id_list, vis_type, source_of_features)
qcw = QCWorkflow(in_dir, id_list, images_for_id, out_dir,
user_args.prepare_first, vis_type, source_of_features,
label_set, alpha_set, outlier_method, outlier_fraction,
outlier_feat_types, no_outlier_detection, views,
num_slices, num_rows, mri_name, seg_name, contour_color)
# if the workflow could be instantiated, it means things are in order!
qcw.save_cmd()
return qcw
def make_workflow_from_user_options():
"""Parser/validator for the cmd line args."""
parser = get_parser()
if len(sys.argv) < 2:
print('Too few arguments!')
parser.print_help()
parser.exit(1)
# parsing
try:
user_args = parser.parse_args()
except:
parser.exit(1)
vis_type = 'collage_t1_mri'
type_of_features = 't1_mri'
in_dir, in_dir_type = check_input_dir_T1(user_args.fs_dir, user_args.user_dir,
user_args.bids_dir)
if in_dir_type.upper() in ('BIDS', ):
mri_name = None
in_dir, bids_dir_type = check_bids_dir(in_dir)
id_list, images_for_id = find_anatomical_images_in_BIDS(in_dir)
else:
mri_name = user_args.mri_name
id_list, images_for_id = check_id_list(user_args.id_list, in_dir, vis_type,
mri_name, seg_name=None,
in_dir_type=in_dir_type)
out_dir = check_out_dir(user_args.out_dir, in_dir)
views = check_views(user_args.views)
num_slices_per_view, num_rows_per_view = check_finite_int(user_args.num_slices,
user_args.num_rows)
outlier_method, outlier_fraction, \
outlier_feat_types, disable_outlier_detection = check_outlier_params(
user_args.outlier_method,
user_args.outlier_fraction,
user_args.outlier_feat_types,
user_args.disable_outlier_detection,
id_list, vis_type, type_of_features)
wf = RatingWorkflowT1(id_list, in_dir, out_dir,
cfg.t1_mri_default_issue_list,
mri_name, in_dir_type, images_for_id,
outlier_method, outlier_fraction,
outlier_feat_types, disable_outlier_detection,
user_args.prepare_first,
vis_type,
views, num_slices_per_view, num_rows_per_view)
return wf
def make_workflow_from_user_options():
"""Parser/validator for the cmd line args."""
parser = get_parser()
if len(sys.argv) < 2:
print('Too few arguments!')
parser.print_help()
parser.exit(1)
# parsing
try:
user_args = parser.parse_args()
except:
parser.exit(1)
vis_type, label_set = check_labels(user_args.vis_type, user_args.label_set)
in_dir, source_of_features = check_input_dir(
user_args.fs_dir, None, vis_type, freesurfer_install_required=False)
mri_name = user_args.mri_name
seg_name = user_args.seg_name
id_list, images_for_id = check_id_list(user_args.id_list, in_dir, vis_type,
mri_name, seg_name)
out_dir = check_out_dir(user_args.out_dir, in_dir)
alpha_set = check_alpha_set(user_args.alpha_set)
views = check_views(user_args.views)
num_slices, num_rows = check_finite_int(user_args.num_slices,
user_args.num_rows)
contour_color = user_args.contour_color
if not is_color_like(contour_color):
raise ValueError(
'Specified color is not valid. Choose a valid spec from\n'
' https://matplotlib.org/users/colors.html')
outlier_method, outlier_fraction, outlier_feat_types, disable_outlier_detection = \
check_outlier_params(user_args.outlier_method, user_args.outlier_fraction,
user_args.outlier_feat_types,
user_args.disable_outlier_detection,
id_list, vis_type, source_of_features)
wf = FreesurferRatingWorkflow(
id_list,
images_for_id,
in_dir,
out_dir,
vis_type=vis_type,
label_set=label_set,
issue_list=cfg.default_rating_list,
mri_name=mri_name,
seg_name=seg_name,
alpha_set=alpha_set,
outlier_method=outlier_method,
outlier_fraction=outlier_fraction,
outlier_feat_types=outlier_feat_types,
disable_outlier_detection=disable_outlier_detection,
source_of_features=source_of_features,
no_surface_vis=user_args.no_surface_vis,
views=views,
num_slices_per_view=num_slices,
num_rows_per_view=num_rows)
return wf
def make_workflow_from_user_options():
"""Parser/validator for the cmd line args."""
parser = get_parser()
if len(sys.argv) < 2:
print('Too few arguments!')
parser.print_help()
parser.exit(1)
# parsing
try:
user_args = parser.parse_args()
except:
parser.exit(1)
vis_type = cfg.alignment_default_vis_type
type_of_features = 'alignment'
in_dir, in_dir_type = check_input_dir_alignment(user_args.in_dir)
image1 = user_args.image1
image2 = user_args.image2
id_list, images_for_id = check_id_list(user_args.id_list,
in_dir,
vis_type,
image1,
image2,
in_dir_type=in_dir_type)
delay_in_animation = check_time(user_args.delay_in_animation,
var_name='Delay')
out_dir = check_out_dir(user_args.out_dir, in_dir)
views = check_views(user_args.views)
num_slices_per_view, num_rows_per_view = check_finite_int(
user_args.num_slices, user_args.num_rows)
outlier_method, outlier_fraction, \
outlier_feat_types, disable_outlier_detection = check_outlier_params(
user_args.outlier_method,
user_args.outlier_fraction,
user_args.outlier_feat_types,
user_args.disable_outlier_detection,
id_list, vis_type, type_of_features)
wf = AlignmentRatingWorkflow(
id_list,
in_dir,
image1,
image2,
out_dir=out_dir,
in_dir_type=in_dir_type,
prepare_first=user_args.prepare_first,
vis_type=vis_type,
delay_in_animation=delay_in_animation,
outlier_method=outlier_method,
outlier_fraction=outlier_fraction,
outlier_feat_types=outlier_feat_types,
disable_outlier_detection=disable_outlier_detection,
views=views,
num_slices_per_view=num_slices_per_view,
num_rows_per_view=num_rows_per_view)
return wf