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)