#!/usr/bin/env python3
"""
Use ``reg_check`` (``rc``) from UNRAVEL to check registration QC, copies autofl_`*`um_masked_fixed_reg_input.nii.gz and atlas_in_tissue_space.nii.gz for each sample to a target dir.
Note:
- This copies main outputs from ``reg`` to a target directory (reg_check by default) for further viewing.
- Optional: To check for overmasking, this also pads the unmasked autofluo image and saves it to reg_outputs, so it can be copied to the target directory.
Next steps:
- ``reg_check_fsleyes`` to visualize the registration outputs with an atlas overlay in FSLeyes.
Usage:
------
reg_check [-td <path/target_output_dir>] [-ro reg_outputs] [-fri fixed_reg_in] [-wa warped_atlas] [-og] [-af autofl_img] [-pad pad_percent] [-d list of paths] [-p sample??] [-v]
"""
from pathlib import Path
from rich import print
from rich.live import Live
from rich.traceback import install
from unravel.core.help_formatter import RichArgumentParser, SuppressMetavar, SM
from unravel.core.config import Configuration
from unravel.core.img_io import load_nii, save_as_nii
from unravel.core.img_tools import pad
from unravel.core.utils import get_pad_percent, log_command, verbose_start_msg, verbose_end_msg, initialize_progress_bar, get_samples, copy_files
[docs]
def parse_args():
parser = RichArgumentParser(formatter_class=SuppressMetavar, add_help=False, docstring=__doc__)
opts = parser.add_argument_group('Optional arguments')
opts.add_argument('-td', '--target_dir', help='path/target_output_dir name for aggregating outputs from all samples. Default: reg_check', default='reg_check', action=SM)
opts.add_argument('-ro', '--reg_outputs', help="Name of folder w/ outputs from ``reg``. Default: reg_outputs", default="reg_outputs", action=SM)
opts.add_argument('-fri', '--fixed_reg_in', help='Fixed image from registration ``reg``. Default: autofl_50um_masked_fixed_reg_input.nii.gz', default="autofl_50um_masked_fixed_reg_input.nii.gz", action=SM)
opts.add_argument('-wa', '--warped_atlas', help='Warped atlas image from ``reg``. Default: atlas_CCFv3_2020_30um_in_tissue_space.nii.gz', default="atlas_CCFv3_2020_30um_in_tissue_space.nii.gz", action=SM)
opts = parser.add_argument_group('Optional arguments for checking the unmasked autofluo image')
opts.add_argument('-og', '--orig_autofl_img', help='Also copy the unmasked autofluo image to the target dir (to check for overmasking). Default: False', action='store_true', default=False)
opts.add_argument('-af', '--autofl_img', help='Path to unmasked autofluorescence image from ``reg_prep`` (relative to sample dir). Default: reg_inputs/autofl_50um.nii.gz', default="reg_inputs/autofl_50um.nii.gz", action=SM)
opts.add_argument('-pad', '--pad_percent', help='Padding percentage from ``reg``. Default: from parameters/pad_percent.txt or 0.25.', type=float, action=SM)
general = parser.add_argument_group('General arguments')
general.add_argument('-d', '--dirs', help='Paths to sample?? dirs and/or dirs containing them (space-separated) for batch processing. Default: current dir', nargs='*', default=None, action=SM)
general.add_argument('-p', '--pattern', help='Pattern for directories to process. Default: sample??', default='sample??', action=SM)
general.add_argument('-v', '--verbose', help='Increase verbosity. Default: False', action='store_true', default=False)
return parser.parse_args()
[docs]
@log_command
def main():
install()
args = parse_args()
Configuration.verbose = args.verbose
verbose_start_msg()
# Create the target directory for copying the selected slices
target_dir = Path(args.target_dir)
target_dir.mkdir(exist_ok=True, parents=True)
sample_paths = get_samples(args.dirs, args.pattern, args.verbose)
progress, task_id = initialize_progress_bar(len(sample_paths), "[red]Processing samples...")
with Live(progress):
for sample_path in sample_paths:
# Define input paths
source_path = sample_path / args.reg_outputs
# Copy the selected slices to the target directory
copy_files(source_path, target_dir, args.fixed_reg_in, sample_path, args.verbose)
copy_files(source_path, target_dir, args.warped_atlas, sample_path, args.verbose)
# Copy the original autofluo image if specified
if args.orig_autofl_img:
autofl_nii_pad_path = source_path / Path(args.autofl_img).name
if not autofl_nii_pad_path.exists():
autofl_path = sample_path / args.autofl_img
pad_percent = get_pad_percent(sample_path / args.reg_outputs, args.pad_percent)
autofl_img = load_nii(autofl_path)
autofl_img_pad = pad(autofl_img, pad_percent=pad_percent)
# Save the padded autofluo image
ref_nii = sample_path / args.reg_outputs / args.fixed_reg_in
save_as_nii(autofl_img_pad, autofl_nii_pad_path, reference=ref_nii)
# Copy the padded autofluo image to the target directory
copy_files(source_path, target_dir, autofl_nii_pad_path.name, sample_path, args.verbose)
progress.update(task_id, advance=1)
verbose_end_msg()
if __name__ == '__main__':
main()