How to use the nwbwidgets.timeseries.show_indexed_timeseries_mpl function in nwbwidgets

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github NeurodataWithoutBorders / nwb-jupyter-widgets / nwbwidgets / icephys.py View on Github external
matplotlib.pyplot.Figure

    """

    nsweeps = len(sweep_sequence)
    if axs is None:
        fig, axs = plt.subplots(2, 1, sharex=True)
    else:
        fig = axs[0].get_figure()
    for i in range(nsweeps):
        start, stop, ts = sweep_sequence['recordings'].iloc[i]['response'].iloc[0]
        show_indexed_timeseries_mpl(ts, istart=start, istop=stop, ax=axs[0], zero_start=True, xlabel='', title=title, **kwargs)

        start, stop, ts = sweep_sequence['recordings'].iloc[i]['stimulus'].iloc[0]
        show_indexed_timeseries_mpl(ts, istart=start, istop=stop, ax=axs[1], zero_start=True, **kwargs)
    return fig
github NeurodataWithoutBorders / nwb-jupyter-widgets / nwbwidgets / icephys.py View on Github external
Returns
    -------

    matplotlib.pyplot.Figure

    """

    nsweeps = len(sweep_sequence)
    if axs is None:
        fig, axs = plt.subplots(2, 1, sharex=True)
    else:
        fig = axs[0].get_figure()
    for i in range(nsweeps):
        start, stop, ts = sweep_sequence['recordings'].iloc[i]['response'].iloc[0]
        show_indexed_timeseries_mpl(ts, istart=start, istop=stop, ax=axs[0], zero_start=True, xlabel='', title=title, **kwargs)

        start, stop, ts = sweep_sequence['recordings'].iloc[i]['stimulus'].iloc[0]
        show_indexed_timeseries_mpl(ts, istart=start, istop=stop, ax=axs[1], zero_start=True, **kwargs)
    return fig