asig.name += ""
asig.description += "Deconvoluted activity using the given {} kernel"\
.format(args.kernel)
block.segments[0].analogsignals[0] = asig
"""
# New method, creating a new block
# create an ImageSequence with the deconvoluted matrix
imgseq_deconv = neo.ImageSequence(
activities,
units=block.segments[0].analogsignals[0].units,
sampling_rate=block.segments[0].analogsignals[0].sampling_rate,
spatial_scale=block.segments[0].imagesequences[0].spatial_scale,
name=block.segments[0].analogsignals[0].name,
description=block.segments[0].analogsignals[0].description)
# create a new Block & Segment and append the ImageSequence
segm_deconv = neo.Segment()
segm_deconv.annotations = block.segments[0].annotations
segm_deconv.annotate(kernel=args.kernel) #ToDo: parameters annotations
segm_deconv.imagesequences.append(imgseq_deconv)
block_deconv = neo.Block()
block_deconv.segments.append(segm_deconv)
block_deconv.name = block.name
block_deconv.description = block.description
block_deconv.annotations = block.annotations
# converting into analogsignal
block_deconv = ImageSequence2AnalogSignal(block_deconv)
write_neo(args.output, block_deconv)
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)
save_plot(args.output_img)
new_asig = asig.duplicate_with_new_data(signal)
new_asig.array_annotations = asig.array_annotations
new_asig.name += ""
new_asig.description += "The mean of each channel was subtracted ({})."\
.format(os.path.basename(__file__))
block.segments[0].analogsignals[0] = new_asig
write_neo(args.output, block)
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:
if event.name not in event_names:
waves_block.segments[0].events.append(event)
del block
write_neo(args.output, waves_block)
