コード例 #1
0
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
コード例 #2
0
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
コード例 #3
0
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
コード例 #4
0
def parse_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)

    vis_type, label_set = check_labels(user_args.vis_type, user_args.labels)

    in_dir = 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 = 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'
        )

    return in_dir, id_list, out_dir, vis_type, label_set, \
           alpha_set, views, num_slices, num_rows, mri_name, seg_name, contour_color
コード例 #5
0
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
コード例 #6
0
ファイル: alignment.py プロジェクト: roopa-pai/visualqc
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