def run_sinogram_generation(args):
"""Make the sinograms with arguments provided by *args*."""
if not args.height:
args.height = determine_shape(args, args.projections)[1] - args.y
step = args.y_step * args.pass_size if args.pass_size else args.height
starts = range(args.y, args.y + args.height, step) + [args.y + args.height]
def generate_partial(append=False):
pm = Ufo.PluginManager()
graph = Ufo.TaskGraph()
sched = Ufo.Scheduler()
writer = pm.get_task('write')
writer.props.filename = args.output
writer.props.append = append
sinos = create_sinogram_pipeline(args, graph)
graph.connect_nodes(sinos, writer)
sched.run(graph)
for i in range(len(starts) - 1):
args.y = starts[i]
args.height = starts[i + 1] - starts[i]
generate_partial(append=i != 0)
def run_sinogram_generation(args):
"""Make the sinograms with arguments provided by *args*."""
if not args.height:
args.height = determine_shape(args, args.projections)[1] - args.y
step = args.y_step * args.pass_size if args.pass_size else args.height
starts = range(args.y, args.y + args.height, step) + [args.y + args.height]
def generate_partial(append=False):
pm = Ufo.PluginManager()
graph = Ufo.TaskGraph()
sched = Ufo.Scheduler()
writer = pm.get_task('write')
writer.props.filename = args.output
writer.props.append = append
sinos = create_sinogram_pipeline(args, graph)
graph.connect_nodes(sinos, writer)
sched.run(graph)
for i in range(len(starts) - 1):
args.y = starts[i]
args.height = starts[i + 1] - starts[i]
generate_partial(append=i != 0)
def lamino(params):
"""Laminographic reconstruction utilizing all GPUs."""
LOG.info('Z parameter: {}'.format(params.z_parameter))
if not params.overall_angle:
params.overall_angle = 360.
LOG.info('Overall angle not specified, using 360 deg')
if not params.angle:
if params.dry_run:
if not params.number:
raise ValueError('--number must be specified by --dry-run')
num_files = params.number
else:
num_files = len(get_filenames(params.projections))
if not num_files:
raise RuntimeError("No files found in `{}'".format(
params.projections))
params.angle = params.overall_angle / num_files * params.step
LOG.info('Angle not specified, calculating from ' +
'{} projections and step {}: {} deg'.format(
num_files, params.step, params.angle))
if not (params.width and params.height):
proj_width, proj_height = determine_shape(params, params.projections)
if not proj_width:
raise RuntimeError("Could not determine width from the input")
if not params.number:
params.number = int(
np.round(np.abs(params.overall_angle / params.angle)))
if not params.width:
params.width = proj_width
if not params.height:
params.height = proj_height - params.y
if params.dry_run:
LOG.info('Dummy data W x H x N: {} x {} x {}'.format(
params.width, params.height, params.number))
params.projection_filter_scale = np.sin(np.deg2rad(params.lamino_angle))
# For now we need to make a workaround for the memory leak, which means we need to execute
# the passes in separate processes to clean up the low level code. For that we also need to
# call the region-splitting in a separate function.
# TODO: Simplify after the memory leak fix!
queue = Queue()
proc = Process(target=_create_runs, args=(
params,
queue,
))
proc.start()
proc.join()
x_region, y_region, regions, num_gpus = queue.get()
for i in range(0, len(regions), num_gpus):
z_subregion = regions[i:min(i + num_gpus, len(regions))]
LOG.info('Computing slices {}..{}'.format(z_subregion[0][0],
z_subregion[-1][1]))
proc = Process(target=_run,
args=(params, x_region, y_region, z_subregion,
i / num_gpus))
proc.start()
proc.join()
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
def lamino(params):
"""Laminographic reconstruction utilizing all GPUs."""
LOG.info('Z parameter: {}'.format(params.z_parameter))
if not params.overall_angle:
params.overall_angle = 360.
LOG.info('Overall angle not specified, using 360 deg')
if not params.angle:
if params.dry_run:
if not params.number:
raise ValueError('--number must be specified by --dry-run')
num_files = params.number
else:
num_files = len(get_filenames(params.projections))
if not num_files:
raise RuntimeError("No files found in `{}'".format(params.projections))
params.angle = params.overall_angle / num_files * params.step
LOG.info('Angle not specified, calculating from ' +
'{} projections and step {}: {} deg'.format(num_files, params.step,
params.angle))
if not (params.width and params.height):
proj_width, proj_height = determine_shape(params, params.projections)
if not proj_width:
raise RuntimeError("Could not determine width from the input")
if not params.number:
params.number = int(np.round(np.abs(params.overall_angle / params.angle)))
if not params.width:
params.width = proj_width
if not params.height:
params.height = proj_height - params.y
if params.dry_run:
LOG.info('Dummy data W x H x N: {} x {} x {}'.format(params.width,
params.height,
params.number))
# For now we need to make a workaround for the memory leak, which means we need to execute
# the passes in separate processes to clean up the low level code. For that we also need to
# call the region-splitting in a separate function.
# TODO: Simplify after the memory leak fix!
queue = Queue()
proc = Process(target=_create_runs, args=(params, queue,))
proc.start()
proc.join()
x_region, y_region, regions, num_gpus = queue.get()
for i in range(0, len(regions), num_gpus):
z_subregion = regions[i:min(i + num_gpus, len(regions))]
LOG.info('Computing slices {}..{}'.format(z_subregion[0][0], z_subregion[-1][1]))
proc = Process(target=_run, args=(params, x_region, y_region, z_subregion, i / num_gpus))
proc.start()
proc.join()
def prepare_angular_arguments(params):
if not params.overall_angle:
params.overall_angle = 360.
LOG.info('Overall angle not specified, using 360 deg')
if not params.angle:
if params.dry_run:
if not params.number:
raise ValueError('--number must be specified by --dry-run')
num_files = params.number
else:
num_files = len(get_filenames(params.projections))
if not num_files:
raise RuntimeError("No files found in `{}'".format(params.projections))
params.angle = params.overall_angle / num_files * params.step
LOG.info('Angle not specified, calculating from ' +
'{} projections and step {}: {} deg'.format(num_files, params.step,
params.angle))
determine_shape(params, params.projections, store=True)
if not params.number:
params.number = int(np.round(np.abs(params.overall_angle / params.angle)))
if params.dry_run:
LOG.info('Dummy data W x H x N: {} x {} x {}'.format(params.width,
params.height,
params.number))
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
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
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
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
