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help_text_outlier_detection_method = textwrap.dedent("""
Method used to detect the outliers.
For more info, read http://scikit-learn.org/stable/modules/outlier_detection.html
Default: {}.
\n""".format(cfg.default_outlier_detection_method))
help_text_outlier_fraction = textwrap.dedent("""
Fraction of outliers expected in the given sample. Must be >= 1/n and <= (n-1)/n,
where n is the number of samples in the current sample.
For more info, read http://scikit-learn.org/stable/modules/outlier_detection.html
Default: {}.
\n""".format(cfg.default_outlier_fraction))
help_text_outlier_feat_types = textwrap.dedent("""
Type of features to be employed in training the outlier detection method. It could be one of
'cortical' (aparc.stats: mean thickness and other geometrical features from each cortical label),
'subcortical' (aseg.stats: volumes of several subcortical structures),
or 'both' (using both aseg and aparc stats).
Default: {}.
\n""".format(cfg.t1_mri_features_OLD))
help_text_disable_outlier_detection = textwrap.dedent("""
This flag disables outlier detection and alerts altogether.
\n""")
in_out = parser.add_argument_group('Input and output', ' ')
default=cfg.default_contour_face_color, required=False,
help=help_text_contour_color)
vis_args.add_argument("-a", "--alpha_set", action="store", dest="alpha_set",
metavar='alpha', nargs=2,
default=default_alpha_set,
required=False, help=help_text_alphas)
outliers = parser.add_argument_group('Outlier detection',
'options related to automatically detecting possible outliers')
outliers.add_argument("-olm", "--outlier_method", action="store", dest="outlier_method",
default=cfg.default_outlier_detection_method, required=False,
help=help_text_outlier_detection_method)
outliers.add_argument("-olf", "--outlier_fraction", action="store", dest="outlier_fraction",
default=cfg.default_outlier_fraction, required=False,
help=help_text_outlier_fraction)
outliers.add_argument("-olt", "--outlier_feat_types", action="store", dest="outlier_feat_types",
default=cfg.freesurfer_features_outlier_detection, required=False,
help=help_text_outlier_feat_types)
outliers.add_argument("-old", "--disable_outlier_detection", action="store_true", dest="disable_outlier_detection",
required=False, help=help_text_disable_outlier_detection)
layout = parser.add_argument_group('Layout options', ' ')
layout.add_argument("-w", "--views", action="store", dest="views",
default=default_views, required=False, nargs='+',
help=help_text_views)
layout.add_argument("-s", "--num_slices", action="store", dest="num_slices",
default=default_num_slices, required=False,
preproc = parser.add_argument_group('Preprocessing',
'options related to preprocessing before review')
preproc.add_argument("-np", "--no_preproc", action="store_true", dest="no_preproc",
required=False, help=help_text_no_preproc)
outliers = parser.add_argument_group('Outlier detection',
'options related to automatically detecting possible outliers')
outliers.add_argument("-olm", "--outlier_method", action="store",
dest="outlier_method",
default=cfg.default_outlier_detection_method, required=False,
help=help_text_outlier_detection_method)
outliers.add_argument("-olf", "--outlier_fraction", action="store",
dest="outlier_fraction",
default=cfg.default_outlier_fraction, required=False,
help=help_text_outlier_fraction)
outliers.add_argument("-olt", "--outlier_feat_types", action="store",
dest="outlier_feat_types",
default=cfg.func_mri_features_OLD, required=False,
help=help_text_outlier_feat_types)
outliers.add_argument("-old", "--disable_outlier_detection", action="store_true",
dest="disable_outlier_detection",
required=False, help=help_text_disable_outlier_detection)
layout = parser.add_argument_group('Layout options',
'Slice layout arragement when zooming in on a time point,\n'
' or show to the std. dev plot.')
layout.add_argument("-w", "--views", action="store", dest="views",
default=cfg.default_views, required=False, nargs='+',
help_text_outlier_detection_method = textwrap.dedent("""
Method used to detect the outliers.
For more info, read http://scikit-learn.org/stable/modules/outlier_detection.html
Default: {}.
\n""".format(cfg.default_outlier_detection_method))
help_text_outlier_fraction = textwrap.dedent("""
Fraction of outliers expected in the given sample. Must be >= 1/n and <= (n-1)/n,
where n is the number of samples in the current sample.
For more info, read http://scikit-learn.org/stable/modules/outlier_detection.html
Default: {}.
\n""".format(cfg.default_outlier_fraction))
help_text_outlier_feat_types = textwrap.dedent("""
Type of features to be employed in training the outlier detection method. It could be one of
'cortical' (aparc.stats: mean thickness and other geometrical features from each cortical label),
'subcortical' (aseg.stats: volumes of several subcortical structures),
or 'both' (using both aseg and aparc stats).
Default: {}.
\n""".format(cfg.func_mri_features_OLD))
help_text_disable_outlier_detection = textwrap.dedent("""
This flag disables outlier detection and alerts altogether.
\n""")
in_out = parser.add_argument_group('Input and output', ' ')
help_text_outlier_detection_method = textwrap.dedent("""
Method used to detect the outliers.
For more info, read http://scikit-learn.org/stable/modules/outlier_detection.html
Default: {}.
\n""".format(cfg.default_outlier_detection_method))
help_text_outlier_fraction = textwrap.dedent("""
Fraction of outliers expected in the given sample. Must be >= 1/n and <= (n-1)/n,
where n is the number of samples in the current sample.
For more info, read http://scikit-learn.org/stable/modules/outlier_detection.html
Default: {}.
\n""".format(cfg.default_outlier_fraction))
help_text_outlier_feat_types = textwrap.dedent("""
Type of features to be employed in training the outlier detection method.
It could be one of .
Default: {}.
\n""".format(cfg.alignment_features_OLD))
help_text_disable_outlier_detection = textwrap.dedent("""
This flag disables outlier detection and alerts altogether.
\n""")
in_out = parser.add_argument_group('Input and output', ' ')
in_out.add_argument("-d", "--in_dir", action="store", dest="in_dir",
default=cfg.default_user_dir,
vis.add_argument("-dl", "--delay_in_animation", action="store",
dest="delay_in_animation",
default=cfg.delay_in_animation, required=False,
help=help_text_delay_in_animation)
outliers = parser.add_argument_group('Outlier detection',
'options related to automatically detecting possible outliers')
outliers.add_argument("-olm", "--outlier_method", action="store",
dest="outlier_method",
default=cfg.default_outlier_detection_method, required=False,
help=help_text_outlier_detection_method)
outliers.add_argument("-olf", "--outlier_fraction", action="store",
dest="outlier_fraction",
default=cfg.default_outlier_fraction, required=False,
help=help_text_outlier_fraction)
outliers.add_argument("-olt", "--outlier_feat_types", action="store",
dest="outlier_feat_types",
default=cfg.diffusion_mri_features_OLD, required=False,
help=help_text_outlier_feat_types)
# outliers.add_argument("-old", "--disable_outlier_detection", action="store_true",
# dest="disable_outlier_detection",
# required=False, help=help_text_disable_outlier_detection)
# TODO re-enable it when OLD is ready for DWI
outliers.add_argument("-old", "--disable_outlier_detection", action="store_false",
dest="disable_outlier_detection",
required=False, help=help_text_disable_outlier_detection)
vis_args.add_argument("-a", "--alpha_set", action="store", dest="alpha_set",
metavar='alpha', nargs=2,
default=cfg.default_alpha_set,
required=False, help=help_text_alphas)
outliers = parser.add_argument_group('Outlier detection',
'options related to automatically detecting possible outliers')
outliers.add_argument("-olm", "--outlier_method", action="store",
dest="outlier_method",
default=cfg.default_outlier_detection_method, required=False,
help=help_text_outlier_detection_method)
outliers.add_argument("-olf", "--outlier_fraction", action="store",
dest="outlier_fraction",
default=cfg.default_outlier_fraction, required=False,
help=help_text_outlier_fraction)
outliers.add_argument("-olt", "--outlier_feat_types", action="store",
dest="outlier_feat_types",
default=cfg.freesurfer_features_outlier_detection,
required=False, help=help_text_outlier_feat_types)
outliers.add_argument("-old", "--disable_outlier_detection", action="store_true",
dest="disable_outlier_detection",
required=False, help=help_text_disable_outlier_detection)
layout = parser.add_argument_group('Layout options', ' ')
layout.add_argument("-w", "--views", action="store", dest="views",
default=cfg.default_views, required=False, nargs='+',
help=help_text_views)
'options related to outputs')
out_spec.add_argument("-o", "--out_dir", action="store", dest="out_dir",
required=False, help=help_text_out_dir,
default=None)
outliers = parser.add_argument_group('Outlier detection',
'options related to automatically detecting possible outliers')
outliers.add_argument("-olm", "--outlier_method", action="store",
dest="outlier_method",
default=cfg.default_outlier_detection_method, required=False,
help=help_text_outlier_detection_method)
outliers.add_argument("-olf", "--outlier_fraction", action="store",
dest="outlier_fraction",
default=cfg.default_outlier_fraction, required=False,
help=help_text_outlier_fraction)
outliers.add_argument("-olt", "--outlier_feat_types", action="store",
dest="outlier_feat_types",
default=cfg.t1_mri_features_OLD, required=False,
help=help_text_outlier_feat_types)
outliers.add_argument("-old", "--disable_outlier_detection", action="store_true",
dest="disable_outlier_detection",
required=False, help=help_text_disable_outlier_detection)
layout = parser.add_argument_group('Layout options', ' ')
layout.add_argument("-w", "--views", action="store", dest="views",
default=cfg.default_views, required=False, nargs='+',
help=help_text_views)