Exemplo n.º 1
0
def create_preprocessing_pipeline(args,
                                  graph,
                                  source=None,
                                  processing_node=None):
    pm = Ufo.PluginManager()

    if not (args.width and args.height):
        width, height = determine_shape(args, args.projections)
        if not width:
            raise RuntimeError("Could not determine width from the input")
    if not args.width:
        args.width = width
    if not args.height:
        args.height = height - args.y

    LOG.debug('Image width x height: %d x %d', args.width, args.height)

    if source:
        current = source
    elif args.darks and args.flats:
        current = create_flat_correct_pipeline(args,
                                               graph,
                                               processing_node=processing_node)
    else:
        current = get_task('read')
        set_node_props(current, args)
        if not args.projections:
            raise RuntimeError('--projections not set')
        setup_read_task(current, args.projections, args)
        if args.absorptivity:
            absorptivity = get_task('calculate',
                                    processing_node=processing_node)
            absorptivity.props.expression = '-log(v)'
            graph.connect_nodes(current, absorptivity)
            current = absorptivity

    if args.transpose_input:
        transpose = get_task('transpose')
        graph.connect_nodes(current, transpose)
        current = transpose
        tmp = args.width
        args.width = args.height
        args.height = tmp

    if args.projection_filter != 'none':
        pf_first, pf_last = create_projection_filtering_pipeline(
            args, graph, processing_node=processing_node)
        graph.connect_nodes(current, pf_first)
        current = pf_last

    if args.energy is not None and args.propagation_distance is not None:
        pr_first, pr_last = create_phase_retrieval_pipeline(
            args, graph, processing_node=processing_node)
        graph.connect_nodes(current, pr_first)
        current = pr_last

    return current
Exemplo n.º 2
0
def get_sinogram_reader(params):
    reader = get_file_reader(params)
    setup_read_task(reader, params.sinograms, params)
    image = read_image(get_first_filename(params.sinograms))

    if len(image.shape) > 2:
        # this is a probably a multi TIFF/raw
        width, height = image.shape[2], image.shape[1]
    else:
        # this is a directory of sinograms
        width, height = image.shape[1], image.shape[0]

    return reader, width, height
Exemplo n.º 3
0
def get_sinogram_reader(params):
    reader = get_file_reader(params)
    setup_read_task(reader, params.sinograms, params)
    image = read_image(get_first_filename(params.sinograms))

    if len(image.shape) > 2:
        # this is a probably a multi TIFF/raw
        width, height = image.shape[2], image.shape[1]
    else:
        # this is a directory of sinograms
        width, height = image.shape[1], image.shape[0]

    return reader, width, height
Exemplo n.º 4
0
def _setup_source(params, pm, graph):
    from tofu.preprocess import create_flat_correct_pipeline
    from tofu.util import set_node_props, setup_read_task
    if params.dry_run:
        source = pm.get_task('dummy-data')
        source.props.number = params.number
        source.props.width = params.width
        source.props.height = params.height
    elif params.darks and params.flats:
        source = create_flat_correct_pipeline(params, graph)
    else:
        source = pm.get_task('read')
        set_node_props(source, params)
        setup_read_task(source, params.projections, params)

    return source
Exemplo n.º 5
0
def get_projection_reader(params):
    reader = get_file_reader(params)
    setup_read_task(reader, params.projections, params)
    width, height = determine_shape(params, params.projections)
    return reader, width, height
Exemplo n.º 6
0
def get_projection_reader(params):
    reader = get_file_reader(params)
    setup_read_task(reader, params.projections, params)
    width, height = determine_shape(params, params.projections)
    return reader, width, height
Exemplo n.º 7
0
def create_flat_correct_pipeline(args, graph):
    """
    Create flat field correction pipeline. All the settings are provided in
    *args*. *graph* is used for making the connections. Returns the flat field
    correction task which can be used for further pipelining.
    """
    pm = Ufo.PluginManager()

    if args.projections is None or args.flats is None or args.darks is None:
        raise RuntimeError(
            "You must specify --projections, --flats and --darks.")

    def get_task(name, **kwargs):
        """Get task *name* with properties *kwargs*."""
        task = pm.get_task(name)
        task.set_properties(**kwargs)
        return task

    reader = get_task('read')
    dark_reader = get_task('read')
    flat_before_reader = get_task('read')

    ffc = get_task('flat-field-correct',
                   dark_scale=args.dark_scale,
                   absorption_correct=args.absorptivity,
                   fix_nan_and_inf=args.fix_nan_and_inf)
    mode = args.reduction_mode.lower()
    roi_args = make_subargs(args, ['y', 'height', 'y_step'])
    set_node_props(reader, args)
    set_node_props(dark_reader, roi_args)
    set_node_props(flat_before_reader, roi_args)

    for r, path in ((reader, args.projections), (dark_reader, args.darks),
                    (flat_before_reader, args.flats)):
        setup_read_task(r, path, args)

    LOG.debug(
        "Doing flat field correction using reduction mode `{}'".format(mode))

    if args.flats2:
        flat_after_reader = get_task('read')
        setup_read_task(flat_after_reader, args.flats2, args)
        set_node_props(flat_after_reader, roi_args)
        num_files = len(get_filenames(args.projections))
        can_read = len(range(args.start, num_files, args.step))
        number = args.number if args.number else num_files
        num_read = min(can_read, number)
        flat_interpolate = get_task('interpolate', number=num_read)

    if args.resize:
        LOG.debug("Resize input data by factor of {}".format(args.resize))
        proj_bin = get_task('bin', size=args.resize)
        dark_bin = get_task('bin', size=args.resize)
        flat_bin = get_task('bin', size=args.resize)
        graph.connect_nodes(reader, proj_bin)
        graph.connect_nodes(dark_reader, dark_bin)
        graph.connect_nodes(flat_before_reader, flat_bin)

        reader, dark_reader, flat_before_reader = proj_bin, dark_bin, flat_bin

        if args.flats2:
            flat_bin = get_task('bin', size=args.resize)
            graph.connect_nodes(flat_after_reader, flat_bin)
            flat_after_reader = flat_bin

    if mode == 'median':
        dark_stack = get_task('stack', number=len(get_filenames(args.darks)))
        dark_reduced = get_task('flatten', mode='median')
        flat_before_stack = get_task('stack',
                                     number=len(get_filenames(args.flats)))
        flat_before_reduced = get_task('flatten', mode='median')

        graph.connect_nodes(dark_reader, dark_stack)
        graph.connect_nodes(dark_stack, dark_reduced)
        graph.connect_nodes(flat_before_reader, flat_before_stack)
        graph.connect_nodes(flat_before_stack, flat_before_reduced)

        if args.flats2:
            flat_after_stack = get_task('stack',
                                        number=len(get_filenames(args.flats2)))
            flat_after_reduced = get_task('flatten', mode='median')
            graph.connect_nodes(flat_after_reader, flat_after_stack)
            graph.connect_nodes(flat_after_stack, flat_after_reduced)
    elif mode == 'average':
        dark_reduced = get_task('average')
        flat_before_reduced = get_task('average')
        graph.connect_nodes(dark_reader, dark_reduced)
        graph.connect_nodes(flat_before_reader, flat_before_reduced)

        if args.flats2:
            flat_after_reduced = get_task('average')
            graph.connect_nodes(flat_after_reader, flat_after_reduced)
    else:
        raise ValueError('Invalid reduction mode')

    graph.connect_nodes_full(reader, ffc, 0)
    graph.connect_nodes_full(dark_reduced, ffc, 1)

    if args.flats2:
        graph.connect_nodes_full(flat_before_reduced, flat_interpolate, 0)
        graph.connect_nodes_full(flat_after_reduced, flat_interpolate, 1)
        graph.connect_nodes_full(flat_interpolate, ffc, 2)
    else:
        graph.connect_nodes_full(flat_before_reduced, ffc, 2)

    return ffc
Exemplo n.º 8
0
def create_flat_correct_pipeline(args, graph):
    """
    Create flat field correction pipeline. All the settings are provided in
    *args*. *graph* is used for making the connections. Returns the flat field
    correction task which can be used for further pipelining.
    """
    pm = Ufo.PluginManager()

    if args.projections is None or args.flats is None or args.darks is None:
        raise RuntimeError("You must specify --projections, --flats and --darks.")

    def get_task(name, **kwargs):
        """Get task *name* with properties *kwargs*."""
        task = pm.get_task(name)
        task.set_properties(**kwargs)
        return task

    reader = get_task('read')
    dark_reader = get_task('read')
    flat_before_reader = get_task('read')

    ffc = get_task('flat-field-correct', dark_scale=args.dark_scale,
                   absorption_correct=args.absorptivity,
                   fix_nan_and_inf=args.fix_nan_and_inf)
    mode = args.reduction_mode.lower()
    roi_args = make_subargs(args, ['y', 'height', 'y_step'])
    set_node_props(reader, args)
    set_node_props(dark_reader, roi_args)
    set_node_props(flat_before_reader, roi_args)

    for r, path in ((reader, args.projections), (dark_reader, args.darks), (flat_before_reader, args.flats)):
        setup_read_task(r, path, args)

    LOG.debug("Doing flat field correction using reduction mode `{}'".format(mode))

    if args.flats2:
        flat_after_reader = get_task('read')
        setup_read_task(flat_after_reader, args.flats2, args)
        set_node_props(flat_after_reader, roi_args)
        num_files = len(get_filenames(args.projections))
        can_read = len(range(args.start, num_files, args.step))
        number = args.number if args.number else num_files
        num_read = min(can_read, number)
        flat_interpolate = get_task('interpolate', number=num_read)

    if args.resize:
        LOG.debug("Resize input data by factor of {}".format(args.resize))
        proj_bin = get_task('bin', size=args.resize)
        dark_bin = get_task('bin', size=args.resize)
        flat_bin = get_task('bin', size=args.resize)
        graph.connect_nodes(reader, proj_bin)
        graph.connect_nodes(dark_reader, dark_bin)
        graph.connect_nodes(flat_before_reader, flat_bin)

        reader, dark_reader, flat_before_reader = proj_bin, dark_bin, flat_bin

        if args.flats2:
            flat_bin = get_task('bin', size=args.resize)
            graph.connect_nodes(flat_after_reader, flat_bin)
            flat_after_reader = flat_bin

    if mode == 'median':
        dark_stack = get_task('stack', number=len(get_filenames(args.darks)))
        dark_reduced = get_task('flatten', mode='median')
        flat_before_stack = get_task('stack', number=len(get_filenames(args.flats)))
        flat_before_reduced = get_task('flatten', mode='median')

        graph.connect_nodes(dark_reader, dark_stack)
        graph.connect_nodes(dark_stack, dark_reduced)
        graph.connect_nodes(flat_before_reader, flat_before_stack)
        graph.connect_nodes(flat_before_stack, flat_before_reduced)

        if args.flats2:
            flat_after_stack = get_task('stack', number=len(get_filenames(args.flats2)))
            flat_after_reduced = get_task('flatten', mode='median')
            graph.connect_nodes(flat_after_reader, flat_after_stack)
            graph.connect_nodes(flat_after_stack, flat_after_reduced)
    elif mode == 'average':
        dark_reduced = get_task('average')
        flat_before_reduced = get_task('average')
        graph.connect_nodes(dark_reader, dark_reduced)
        graph.connect_nodes(flat_before_reader, flat_before_reduced)

        if args.flats2:
            flat_after_reduced = get_task('average')
            graph.connect_nodes(flat_after_reader, flat_after_reduced)
    else:
        raise ValueError('Invalid reduction mode')

    graph.connect_nodes_full(reader, ffc, 0)
    graph.connect_nodes_full(dark_reduced, ffc, 1)

    if args.flats2:
        graph.connect_nodes_full(flat_before_reduced, flat_interpolate, 0)
        graph.connect_nodes_full(flat_after_reduced, flat_interpolate, 1)
        graph.connect_nodes_full(flat_interpolate, ffc, 2)
    else:
        graph.connect_nodes_full(flat_before_reduced, ffc, 2)

    return ffc
Exemplo n.º 9
0
def create_preprocessing_pipeline(args, graph, source=None, processing_node=None,
                                  cone_beam_weight=True, make_reader=True):
    """If *make_reader* is True, create a read task if *source* is None and no dark and flat fields
    are given.
    """
    import numpy as np
    if not (args.width and args.height):
        width, height = determine_shape(args, args.projections)
        if not width:
            raise RuntimeError("Could not determine width from the input")
    if not args.width:
        args.width = width
    if not args.height:
        args.height = height - args.y

    LOG.debug('Image width x height: %d x %d', args.width, args.height)

    current = None
    if source:
        current = source
    elif args.darks and args.flats:
        current = create_flat_correct_pipeline(args, graph, processing_node=processing_node)
    else:
        if make_reader:
            current = get_task('read')
            set_node_props(current, args)
            if not args.projections:
                raise RuntimeError('--projections not set')
            setup_read_task(current, args.projections, args)
        if args.absorptivity:
            absorptivity = get_task('calculate', processing_node=processing_node)
            absorptivity.props.expression = 'v <= 0 ? 0.0f : -log(v)'
            if current:
                graph.connect_nodes(current, absorptivity)
            current = absorptivity

    if args.transpose_input:
        transpose = get_task('transpose')
        if current:
            graph.connect_nodes(current, transpose)
        current = transpose
        tmp = args.width
        args.width = args.height
        args.height = tmp

    if cone_beam_weight and not np.all(np.isinf(args.source_position_y)):
        # Cone beam projection weight
        LOG.debug('Enabling cone beam weighting')
        weight = get_task('cone-beam-projection-weight', processing_node=processing_node)
        weight.props.source_distance = (-np.array(args.source_position_y)).tolist()
        weight.props.detector_distance = args.detector_position_y
        weight.props.center_position_x = args.center_position_x or [args.width / 2. + (args.width % 2) * 0.5]
        weight.props.center_position_z = args.center_position_z or [args.height / 2. + (args.height % 2) * 0.5]
        weight.props.axis_angle_x = args.axis_angle_x
        if current:
            graph.connect_nodes(current, weight)
        current = weight

    if args.energy is not None and args.propagation_distance is not None:
        pr_first, pr_last = create_phase_retrieval_pipeline(args, graph,
                                                            processing_node=processing_node)
        if current:
            graph.connect_nodes(current, pr_first)
        current = pr_last

    if args.projection_filter != 'none':
        pf_first, pf_last = create_projection_filtering_pipeline(args, graph,
                                                                 processing_node=processing_node)
        if current:
            graph.connect_nodes(current, pf_first)
        current = pf_last

    return current
Exemplo n.º 10
0
def create_preprocessing_pipeline(args,
                                  graph,
                                  source=None,
                                  processing_node=None,
                                  cone_beam_weight=True,
                                  make_reader=True):
    """If *make_reader* is True, create a read task if *source* is None and no dark and flat fields
    are given.
    """
    import numpy as np
    if not (args.width and args.height):
        width, height = determine_shape(args, args.projections)
        if not width:
            raise RuntimeError("Could not determine width from the input")
    if not args.width:
        args.width = width
    if not args.height:
        args.height = height - args.y

    LOG.debug('Image width x height: %d x %d', args.width, args.height)

    current = None
    if source:
        current = source
    elif args.darks and args.flats:
        current = create_flat_correct_pipeline(args,
                                               graph,
                                               processing_node=processing_node)
    else:
        if make_reader:
            current = get_task('read')
            set_node_props(current, args)
            if not args.projections:
                raise RuntimeError('--projections not set')
            setup_read_task(current, args.projections, args)
        if args.absorptivity:
            absorptivity = get_task('calculate',
                                    processing_node=processing_node)
            absorptivity.props.expression = 'v <= 0 ? 0.0f : -log(v)'
            if current:
                graph.connect_nodes(current, absorptivity)
            current = absorptivity

    if args.transpose_input:
        transpose = get_task('transpose')
        if current:
            graph.connect_nodes(current, transpose)
        current = transpose
        tmp = args.width
        args.width = args.height
        args.height = tmp

    if cone_beam_weight and not np.all(np.isinf(args.source_position_y)):
        # Cone beam projection weight
        LOG.debug('Enabling cone beam weighting')
        weight = get_task('cone-beam-projection-weight',
                          processing_node=processing_node)
        weight.props.source_distance = (
            -np.array(args.source_position_y)).tolist()
        weight.props.detector_distance = args.detector_position_y
        weight.props.center_position_x = args.center_position_x or [
            args.width / 2. + (args.width % 2) * 0.5
        ]
        weight.props.center_position_z = args.center_position_z or [
            args.height / 2. + (args.height % 2) * 0.5
        ]
        weight.props.axis_angle_x = args.axis_angle_x
        if current:
            graph.connect_nodes(current, weight)
        current = weight

    if args.energy is not None and args.propagation_distance is not None:
        pr_first, pr_last = create_phase_retrieval_pipeline(
            args, graph, processing_node=processing_node)
        if current:
            graph.connect_nodes(current, pr_first)
        current = pr_last

    if args.projection_filter != 'none':
        pf_first, pf_last = create_projection_filtering_pipeline(
            args, graph, processing_node=processing_node)
        if current:
            graph.connect_nodes(current, pf_first)
        current = pf_last

    return current