def main():
parser = _build_args_parser()
args = parser.parse_args()
assert_inputs_exist(parser, [args.tractogram])
assert_outputs_exist(parser, args, [], [args.save])
tracts_format = detect_format(args.tractogram)
if tracts_format is not TrkFile:
raise ValueError("Invalid input streamline file format " +
"(must be trk): {0}".format(args.tractogram_filename))
# Load files and data
trk = TrkFile.load(args.tractogram)
tractogram = trk.tractogram
streamlines = tractogram.streamlines
if 'seeds' not in tractogram.data_per_streamline:
parser.error('Tractogram does not contain seeds')
seeds = tractogram.data_per_streamline['seeds']
# Make display objects
streamlines_actor = actor.line(streamlines)
points = actor.dots(seeds, color=(1., 1., 1.))
# Add display objects to canvas
r = window.Renderer()
r.add(streamlines_actor)
r.add(points)
# Show and record if needed
if args.save is not None:
window.record(r, out_path=args.save, size=(1000, 1000))
window.show(r)
def read_s3fs_nib(paths, lazy, block_size, bfile="read_file.bench"):
fs = S3FileSystem()
fs.invalidate_cache()
for path in paths:
with fs.open(path, "rb", block_size=block_size) as f:
streamlines = TrkFile.load(f, lazy_load=lazy).streamlines
def read_trk(f, lazy, bfile="read_file.bench"):
streamlines = TrkFile.load(f, lazy_load=lazy).streamlines
if lazy:
for stream in streamlines:
continue
return stream
return streamlines[-1]
def read_prefetch_nib(paths,
lazy,
block_size,
prefetch_storage,
bfile="read_file.bench"):
fs = S3PrefetchFileSystem()
fs.invalidate_cache()
with fs.open(paths, "rb", block_size=block_size, header_bytes=1000) as f:
streamlines = TrkFile.load(f, lazy_load=lazy).streamlines
def read_mem_nib(paths, lazy, bfile="read_file.bench"):
for path in paths:
with open(path, "rb") as f:
streamlines = TrkFile.load(f, lazy_load=lazy).streamlines