Waveforms Widgets Gallery

Here is a gallery of all the available widgets using a pair of RecordingExtractor-SortingExtractor objects.

import matplotlib.pyplot as plt

import spikeinterface as si
import spikeinterface.extractors as se
import spikeinterface.postprocessing as spost
import spikeinterface.widgets as sw

First, let’s download a simulated dataset

from the repo ‘https://gin.g-node.org/NeuralEnsemble/ephy_testing_data’

local_path = si.download_dataset(remote_path='mearec/mearec_test_10s.h5')
recording = se.MEArecRecordingExtractor(local_path)
sorting = se.MEArecSortingExtractor(local_path)
print(recording)
print(sorting)

MEArecRecordingExtractor: 32 channels - 1 segments - 32.0kHz - 10.000s
  file_path: /home/docs/spikeinterface_datasets/ephy_testing_data/mearec/mearec_test_10s.h5
MEArecSortingExtractor: 10 units - 1 segments - 32.0kHz
  file_path: /home/docs/spikeinterface_datasets/ephy_testing_data/mearec/mearec_test_10s.h5

Extract spike waveforms

For convenience, metrics are computed on the WaveformExtractor object that gather recording/sorting and extracted waveforms in a single object

folder = 'waveforms_mearec'
we = si.extract_waveforms(recording, sorting, folder,
    load_if_exists=True,
    ms_before=1, ms_after=2., max_spikes_per_unit=500,
    n_jobs=1, chunk_size=30000)

# pre-compute postprocessing data
_ = spost.compute_spike_amplitudes(we)
_ = spost.compute_unit_locations(we)
_ = spost.compute_spike_locations(we)
_ = spost.compute_template_metrics(we)

plot_unit_waveforms()

unit_ids = sorting.unit_ids[:4]

sw.plot_unit_waveforms(we, unit_ids=unit_ids)

<spikeinterface.widgets.matplotlib.unit_waveforms.UnitWaveformPlotter object at 0x7f29879eca00>

plot_unit_templates()

unit_ids = sorting.unit_ids

sw.plot_unit_templates(we, unit_ids=unit_ids, ncols=5)

<spikeinterface.widgets.matplotlib.unit_templates.UnitTemplatesPlotter object at 0x7f29879ecf10>

plot_amplitudes()

sw.plot_amplitudes(we, plot_histograms=True)

<spikeinterface.widgets.matplotlib.amplitudes.AmplitudesPlotter object at 0x7f2994db87f0>

plot_unit_locations()

sw.plot_unit_locations(we)

<spikeinterface.widgets.matplotlib.unit_locations.UnitLocationsPlotter object at 0x7f29951ed700>

plot_unit_waveform_density_map()

This is your best friend to check over merge

unit_ids = sorting.unit_ids[:4]
sw.plot_unit_waveforms_density_map(we, unit_ids=unit_ids, max_channels=5)

<spikeinterface.widgets.matplotlib.unit_waveforms_density_map.UnitWaveformDensityMapPlotter object at 0x7f297815fc10>

plot_amplitudes_distribution()

sw.plot_amplitudes_distribution(we)

<spikeinterface.widgets._legacy_mpl_widgets.amplitudes.AmplitudeDistributionWidget object at 0x7f298ee47a00>

plot_units_depth_vs_amplitude()

sw.plot_units_depth_vs_amplitude(we)

<spikeinterface.widgets._legacy_mpl_widgets.depthamplitude.UnitsDepthAmplitudeWidget object at 0x7f298ed880a0>

plot_unit_probe_map()

unit_ids = sorting.unit_ids[:4]
sw.plot_unit_probe_map(we, unit_ids=unit_ids)



plt.show()