return ax
if __name__ == '__main__':
CLI = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
CLI.add_argument("--data", nargs='?', type=str, required=True,
help="path to input data in neo format")
CLI.add_argument("--output", nargs='?', type=str, required=True,
help="path of output file")
CLI.add_argument("--output_img", nargs='?', type=none_or_str,
help="path of output image", default=None)
CLI.add_argument("--output_array", nargs='?', type=none_or_str,
help="path of output numpy array", default=None)
args = CLI.parse_args()
block = load_neo(args.data)
asig = block.segments[0].analogsignals[0]
signal = asig.as_array()
background = np.nanmean(signal, axis=0)
signal -= background
if args.output_img or args.output_array is not None:
coords = np.array([(x,y) for x,y in
zip(asig.array_annotations['x_coords'],
asig.array_annotations['y_coords'])],
dtype=int)
frame = shape_frame(background, coords)
if args.output_array is not None:
np.save(args.output_array, frame)
if args.output_img is not None:
plot_frame(frame)
type=float,
default=0,
help="start time in seconds")
CLI.add_argument("--t_stop",
nargs='?',
type=float,
default=10,
help="stop time in seconds")
CLI.add_argument("--channel",
nargs='?',
type=int,
default=0,
help="channel to plot")
args = CLI.parse_args()
orig_asig = load_neo(args.original_data, 'analogsignal', lazy=True)
orig_asig = time_slice(orig_asig,
t_start=args.t_start,
t_stop=args.t_stop,
lazy=True,
channel_indexes=args.channel)
proc_asig = load_neo(args.processed_data, 'analogsignal', lazy=True)
proc_asig = time_slice(proc_asig,
t_start=args.t_start,
t_stop=args.t_stop,
lazy=True,
channel_indexes=args.channel)
plot_traces(orig_asig, proc_asig, args.channel)
default=None,
help="metadata of the dataset")
CLI.add_argument("--array_annotations",
nargs='+',
type=none_or_str,
default=None,
help="channel-wise metadata")
CLI.add_argument("--kwargs",
nargs='+',
type=none_or_str,
default=None,
help="additional optional arguments")
args = CLI.parse_args()
try:
block = load_neo(args.data, try_signal_grouping=True)
except Exception as e:
print(e)
block = load_neo(args.data, try_signal_grouping=True)
asigs = block.segments[0].analogsignals
if len(asigs) > 1:
print(f'Merging {len(asigs)} AnalogSignals into one.')
asig = merge_analogsingals(asigs)
else:
asig = asigs[0]
asig = time_slice(asig, args.t_start, args.t_stop)
# add metadata
if __name__ == '__main__':
CLI = argparse.ArgumentParser()
CLI.add_argument("--data", nargs='?', type=str)
CLI.add_argument("--frame_folder", nargs='?', type=str)
CLI.add_argument("--frame_name", nargs='?', type=str)
CLI.add_argument("--frame_format", nargs='?', type=str)
CLI.add_argument("--frame_rate", nargs='?', type=none_or_float)
CLI.add_argument("--colormap", nargs='?', type=str)
CLI.add_argument("--event", nargs='?', type=none_or_str, default=None)
CLI.add_argument("--markercolor", nargs='?', type=str, default='k')
args = CLI.parse_args()
blk = load_neo(args.data)
blk = AnalogSignal2ImageSequence(blk)
# get data
imgseq = blk.segments[0].imagesequences[0]
times = blk.segments[0].analogsignals[0].times # to be replaced
t_start = blk.segments[0].analogsignals[0].t_start # to be replaced
t_stop = blk.segments[0].analogsignals[0].t_stop # to be replaced
dim_t, dim_x, dim_y = imgseq.shape
optical_flow = get_opticalflow(blk.segments[0].imagesequences)
if args.event is not None:
up_coords = get_events(blk.segments[0].events,
frame_times=times,
event_name=args.event)
help="lower bound of frequency band in Hz")
CLI.add_argument("--lowpass_freq",
nargs='?',
type=none_or_float,
default='None',
help="upper bound of frequency band in Hz")
CLI.add_argument("--psd_freq_res",
nargs='?',
type=float,
default=5,
help="frequency resolution of the power spectrum in Hz")
CLI.add_argument("--psd_overlap",
nargs='?',
type=float,
default=0.5,
help="overlap parameter for Welch's algorithm [0-1]")
args = CLI.parse_args()
asig = load_neo(args.data, 'analogsignal')
freqs, psd = welch_psd(asig,
freq_res=args.psd_freq_res * pq.Hz,
overlap=args.psd_overlap)
plot_psd(freqs=freqs,
psd=psd,
highpass_freq=args.highpass_freq,
lowpass_freq=args.lowpass_freq)
save_plot(args.output)
import neo
from utils import load_neo, write_neo, AnalogSignal2ImageSequence
if __name__ == '__main__':
CLI = argparse.ArgumentParser(description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
CLI.add_argument("--waves", nargs='?', type=str, required=True,
help="path to input data in neo format")
CLI.add_argument("--properties", nargs='?', type=lambda v: v.split(','), default=None,
help="paths to input data in neo format")
CLI.add_argument("--output", nargs='?', type=str, required=True,
help="path of output file")
args = CLI.parse_args()
waves_block = load_neo(args.waves)
asig_names = [asig.name for asig in waves_block.segments[0].analogsignals]
event_names = [event.name for event in waves_block.segments[0].events]
if args.properties is None:
args.properties = []
for property in args.properties:
block = load_neo(property)
for asig in block.segments[0].analogsignals:
if asig.name not in asig_names:
waves_block.segments[0].analogsignals.append(asig)
for event in block.segments[0].events:
type=str,
required=True,
help="path to input data in neo format")
CLI.add_argument("--node_data",
nargs='?',
type=str,
required=True,
help="path to input data in neo format")
CLI.add_argument("--output",
nargs='?',
type=str,
required=True,
help="path of output file")
args = CLI.parse_args()
trigger_block = load_neo(args.trigger_data)
node_block = load_neo(args.node_data)
block = AnalogSignal2ImageSequence(node_block)
wavefront_evt = [
evt for evt in trigger_block.segments[0].events
if evt.name == "Wavefronts"
]
if wavefront_evt:
wavefront_evt = wavefront_evt[0]
else:
raise ValueError("Input does not contain an event with name " \
+ "'Wavefronts'!")
block.segments[0].events.append(wavefront_evt)
CLI.add_argument("--t_start",
nargs='?',
type=float,
default=0,
help="start time in seconds")
CLI.add_argument("--t_stop",
nargs='?',
type=float,
default=10,
help="stop time in seconds")
CLI.add_argument("--channels",
nargs='+',
type=none_or_int,
default=0,
help="list of channels to plot")
args = CLI.parse_args()
asig = load_neo(args.data, 'analogsignal', lazy=True)
channels = parse_plot_channels(args.channels, args.data)
asig = time_slice(asig,
t_start=args.t_start,
t_stop=args.t_stop,
lazy=True,
channel_indexes=channels)
fig = plot_traces(asig, channels)
save_plot(args.output)
