def main():
suppress_tf_logging(tf_suppress_log_messages)
from brainreg.main import main as register
from cellfinder.tools import prep
start_time = datetime.now()
args, arg_groups, what_to_run, atlas = prep.prep_cellfinder_general()
if what_to_run.register:
# TODO: add register_part_brain option
logging.info("Registering to atlas")
args, additional_images_downsample = prep.prep_registration(args)
register(
args.atlas,
args.orientation,
args.target_brain_path,
args.brainreg_paths,
args.voxel_sizes,
arg_groups["NiftyReg registration backend options"],
sort_input_file=args.sort_input_file,
n_free_cpus=args.n_free_cpus,
additional_images_downsample=additional_images_downsample,
backend=args.backend,
debug=args.debug,
)
else:
logging.info("Skipping registration")
if len(args.signal_planes_paths) > 1:
base_directory = args.output_dir
for idx, signal_paths in enumerate(args.signal_planes_paths):
channel = args.signal_ch_ids[idx]
logging.info("Processing channel: " + str(channel))
channel_directory = os.path.join(
base_directory, "channel_" + str(channel)
)
if not os.path.exists(channel_directory):
os.makedirs(channel_directory)
# prep signal channel specific args
args.signal_planes_paths[0] = signal_paths
# TODO: don't overwrite args.output_dir - use Paths instead
args.output_dir = channel_directory
args.signal_channel = channel
# Run for each channel
run_all(args, what_to_run, atlas)
else:
args.signal_channel = args.signal_ch_ids[0]
run_all(args, what_to_run, atlas)
logging.info(
"Finished. Total time taken: {}".format(datetime.now() - start_time)
)
def main():
suppress_tf_logging(tf_suppress_log_messages)
import amap.main as register
from cellfinder.tools import prep
start_time = datetime.now()
args, what_to_run = prep.prep_cellfinder_general()
if what_to_run.register:
# TODO: add register_part_brain option
logging.info("Registering to atlas")
args, additional_images_downsample = prep.prep_registration(args)
register.main(
args.registration_config,
args.target_brain_path,
args.paths.registration_output_folder,
x_pixel_um=args.x_pixel_um,
y_pixel_um=args.y_pixel_um,
z_pixel_um=args.z_pixel_um,
orientation=args.orientation,
flip_x=args.flip_x,
flip_y=args.flip_y,
flip_z=args.flip_z,
affine_n_steps=args.affine_n_steps,
affine_use_n_steps=args.affine_use_n_steps,
freeform_n_steps=args.freeform_n_steps,
freeform_use_n_steps=args.freeform_use_n_steps,
bending_energy_weight=args.bending_energy_weight,
grid_spacing_x=args.grid_spacing_x,
smoothing_sigma_reference=args.smoothing_sigma_reference,
smoothing_sigma_floating=args.smoothing_sigma_floating,
histogram_n_bins_floating=args.histogram_n_bins_floating,
histogram_n_bins_reference=args.histogram_n_bins_reference,
sort_input_file=args.sort_input_file,
n_free_cpus=args.n_free_cpus,
save_downsampled=not (args.no_save_downsampled),
additional_images_downsample=additional_images_downsample,
boundaries=not (args.no_boundaries),
debug=args.debug,
)
else:
logging.info("Skipping registration")
if what_to_run.summarise:
args = prep.prep_atlas_conf(args)
if len(args.signal_planes_paths) > 1:
base_directory = args.output_dir
for idx, signal_paths in enumerate(args.signal_planes_paths):
channel = args.signal_ch_ids[idx]
logging.info("Processing channel: " + str(channel))
channel_directory = os.path.join(
base_directory, "channel_" + str(channel)
)
if not os.path.exists(channel_directory):
os.makedirs(channel_directory)
# prep signal channel specific args
args.signal_planes_paths[0] = signal_paths
# TODO: don't overwrite args.output_dir - use Paths instead
args.output_dir = channel_directory
args.signal_channel = channel
# Run for each channel
run_all(args, what_to_run)
else:
args.signal_channel = args.signal_ch_ids[0]
run_all(args, what_to_run)
logging.info(
"Finished. Total time taken: {}".format(datetime.now() - start_time)
)