return int(value)
if __name__ == '__main__':
CLI = argparse.ArgumentParser()
CLI.add_argument("--data", nargs='?', type=str)
CLI.add_argument("--output", nargs='?', type=str)
CLI.add_argument("--tstart", nargs='?', type=float)
CLI.add_argument("--tstop", nargs='?', type=float)
CLI.add_argument("--channel", nargs='+', type=none_or_int)
args = CLI.parse_args()
with neo.NixIO(args.data) as io:
asig = io.read_block().segments[0].analogsignals
check_analogsignal_shape(asig)
asig = asig[0]
dim_t, channel_num = asig.shape
for i, channel in enumerate(args.channel):
if channel is None:
args.channel[i] = random.randint(0, channel_num)
asig = asig.time_slice(args.tstart * pq.s, args.tstop * pq.s)
sns.set(style='ticks', palette="deep", context="notebook")
fig, ax = plt.subplots()
offset = np.max(np.abs(asig.as_array()[:, args.channel]))
return X * signal.units
elif isinstance(signal, np.ndarray):
return X
if __name__ == '__main__':
CLI = argparse.ArgumentParser()
CLI.add_argument("--data", nargs='?', type=str)
CLI.add_argument("--output", nargs='?', type=str)
CLI.add_argument("--order", nargs='?', type=int)
args = CLI.parse_args()
# load images
with neo.NixIO(args.data) as io:
block = io.read_block()
check_analogsignal_shape(block.segments[0].analogsignals)
remove_annotations([block] + block.segments +
block.segments[0].analogsignals)
asig = detrending(block.segments[0].analogsignals[0], args.order)
# save processed data
asig.name += ""
asig.description += "Detrended by order {} ({}). "\
.format(args.order, os.path.basename(__file__))
block.segments[0].analogsignals[0] = asig
with neo.NixIO(args.output) as io:
io.write(block)