Widgets module¶

The spikeinterface.widgets module includes plotting function to visualize recordings, sortings, waveforms, and more.

Since version 0.95.0, the spikeinterface.widgets module supports multiple backends:

“matplotlib”: static rendering using the matplotlib package
“ipywidgets”: interactive rendering within a jupyter notebook using the ipywidgets package
“sortingview”: web-based and interactive rendering using the sortingview and FIGURL packages.

Installation¶

The backends are loaded at run-time and can be installed separately.

matplotlib¶

The “matplotlib” backend (default) uses matplotlib to generate static figures.

To install it, run:

pip install matplotlib

ipywidgets¶

The “ipywidgets” backend allows users to interact with the plot, for example, by selecting units or scrolling through a time series.

To install it, run:

pip install matplotlib ipympl ipywidgets

To enable interactive widgets in your notebook, add and run a cell with:

%matplotlib widget

sortingview¶

The “sortingview” backends generates web-based and shareable links that can be viewed in the browser.

To install it, run:

pip install sortingview

Internally, the processed data to be rendered are uploaded to a public bucket in the cloud, so that they can be visualized via the web. To set up the backend, you need to authenticate to kachery-cloud using your google account by running the following command (you will be prompted a link):

kachery-cloud-init

Finally, if you wish to set up another cloud provider, follow the instruction from the kachery-cloud package (“Using your own storage bucket”).

Examples¶

You can specify which backend to use with the backend argument. In addition, each backend comes with specific arguments that can be set when calling the plotting function.

import spikeinterface.extractors as se
import spikeinterface.widgets as sw

# recording is a BaseRecording object
recording = se.read_spikeglx("spikeglx-folder")

# matplotlib backend
sw.plot_timeseries(recording, backend="matplotlib")

# ipywidgets backend
sw.plot_timeseries(recording, backend="ipywidgets")

# sortingview backend
sw.plot_timeseries(recording, backend="sortingview")

To inspect which backends are available for each function and what are the additional backend-specific arguments you can use the following notation:

sw.plot_timeseries?

which prints:

Signature:
si.plot_timeseries(
    recording,
    segment_index=None,
    channel_ids=None,
    order_channel_by_depth=False,
    time_range=None,
    mode='auto',
    cmap='RdBu',
    show_channel_ids=False,
    color_groups=False,
    color=None,
    clim=None,
    tile_size=512,
    seconds_per_row=0.2,
    with_colorbar=True,
    backend=None,
    **backend_kwargs,
)
Docstring:
Plots recording timeseries.

Parameters
----------
recording: RecordingExtractor or dict or list
    The recording extractor object
    If dict (or list) then it is a multi layer display to compare some processing
    for instance
segment_index: None or int
    The segment index.
channel_ids: list
    The channel ids to display.
order_channel_by_depth: boolean
    Reorder channel by depth.
time_range: list
    List with start time and end time
mode: 'line' or 'map' or 'auto'
    2 possible mode:
        * 'line' : classical for low channel count
        * 'map' : for high channel count use color heat map
        * 'auto' : auto switch depending the channel count <32ch
cmap: str default 'RdBu'
    matplotlib colormap used in mode 'map'
show_channel_ids: bool
    Set yticks with channel ids
color_groups: bool
    If True groups are plotted with different colors
color:   str default: None
    The color used to draw the traces.
clim: None, tuple, or dict
    When mode='map' this control color lims.
    If dict, keys should be the same as recording keys
with_colorbar: bool default True
    When mode='map' add colorbar
tile_size: int
    For sortingview backend, the size of each tile in the rendered image
seconds_per_row: float
    For 'map' mode and sortingview backend, seconds to render in each row

Returns
-------
W: TimeseriesWidget
    The output widget

Backends
--------

backends: str
    ['matplotlib', 'sortingview', 'ipywidgets']
backend_kwargs: kwargs

    matplotlib:
    - figure: Matplotlib figure. When None, it is created. Default None
    - ax: Single matplotlib axis. When None, it is created. Default None
    - axes: Multiple matplotlib axes. When None, they is created. Default None
    - ncols: Number of columns to create in subplots.  Default 5
    - figsize: Size of matplotlib figure. Default None
    - figtitle: The figure title. Default None
    sortingview:
    - generate_url: If True, the figurl URL is generated and printed. Default is True
    - figlabel: The figurl figure label. Default None
    ipywidgets:
    - width_cm: Width of the figure in cm (default 10)
    - height_cm: Height of the figure in cm (default 6)

Checkout the _sphx_glr_modules_widgets tutorials for an overview of available widgets!