<jupyter_start><jupyter_text>Recording+Sorting Widgets Gallery===================================================Here is a gallery of all the available widgets using a pair of RecordingExtractor-SortingExtractor objects.<jupyter_code>import spikeinterface.extractors as se
import spikeinterface.widgets as sw<jupyter_output><empty_output><jupyter_text>First, let's create a toy example with the `extractors` module:<jupyter_code>recording, sorting = se.example_datasets.toy_example(duration=10, num_channels=4, seed=0)<jupyter_output><empty_output><jupyter_text>plot_unit_waveforms()~~~~~~~~~~~~~~~~~~~~~~~~<jupyter_code>w_wf = sw.plot_unit_waveforms(recording, sorting, max_spikes_per_unit=100)<jupyter_output><empty_output><jupyter_text>plot_amplitudes_distribution()~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~<jupyter_code>w_ampd = sw.plot_amplitudes_distribution(recording, sorting, max_spikes_per_unit=300)<jupyter_output><empty_output><jupyter_text>plot_amplitudes_timeseres()~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~<jupyter_code>w_ampt = sw.plot_amplitudes_timeseries(recording, sorting, max_spikes_per_unit=300)<jupyter_output><empty_output><jupyter_text>plot_pca_features()~~~~~~~~~~~~~~~~~~~~~~~~<jupyter_code>w_feat = sw.plot_pca_features(recording, sorting, colormap='rainbow', nproj=3, max_spikes_per_unit=100)<jupyter_output><empty_output>
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