.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "generated/tutorials/00_introduction.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_generated_tutorials_00_introduction.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_generated_tutorials_00_introduction.py:


Introduction to real-time LSL streams
=====================================

.. include:: ./../../links.inc

.. _SSP projectors: https://mne.tools/dev/documentation/implementation.html#signal-space-projection-ssp

LSL is an open-source networked middleware ecosystem to stream, receive, synchronize,
and record neural, physiological, and behavioral data streams acquired from diverse
sensor hardware. It reduces complexity and barriers to entry for researchers, sensor
manufacturers, and users through a simple, interoperable, standardized API to connect
data consumers to data producers while abstracting obstacles such as platform
differences, stream discovery, synchronization and fault-tolerance.
Source: `LabStreamingLayer website <lsl_>`_.

In real-time applications, a server emits a data stream, and one or more clients connect
to the server to receive this data. In LSL terminology, the server is referred to as a
:class:`~mne_lsl.lsl.StreamOutlet`, while the client is referred to as a
:class:`~mne_lsl.lsl.StreamInlet`. The power of LSL resides in its ability to facilitate
interoperability and synchronization among streams. Clients have the capability to
connect to multiple servers, which may be running on the same or different computers
(and therefore different platforms/operating systems), and synchronize the streams
originating from these various servers.

MNE-LSL enhances the LSL API by offering a high-level interface akin to the
`MNE-Python <mne stable_>`_ API. While this tutorial concentrates on the high-level API,
detailed coverage of the low-level LSL API is provided in
:ref:`this separate tutorial <tut-low-level-api>`.

Concepts
--------

In essence, a real-time LSL stream can be envisioned as a perpetual recording, akin to
a :class:`mne.io.Raw` instance, characterized by an indeterminate length and providing
access solely to current and preceding samples. In memory, it can be depicted as a ring
buffer, also known as a circular buffer, a data structure employing a single, unchanging
buffer size, seemingly interconnected end-to-end.

.. image:: ../../_static/tutorials/circular-buffer-light.png
    :align: center
    :class: only-light

.. image:: ../../_static/tutorials/circular-buffer-dark.png
    :align: center
    :class: only-dark

Within a ring buffer, there are two pivotal pointers:

* The "head" pointer, also referred to as "start" or "read," indicates the subsequent
  data block available for reading.
* The "tail" pointer, known as "end" or "write," designates the forthcoming data block
  to be replaced with fresh data.

In a ring buffer configuration, when the "tail" pointer aligns with the "head" pointer,
data is overwritten before it can be accessed. Conversely, the "head" pointer cannot
surpass the "tail" pointer; it will always lag at least one sample behind. In all cases,
it falls upon the user to routinely inspect and fetch samples from the ring buffer,
thereby advancing the "head" pointer.

Within MNE-LSL, the :class:`~mne_lsl.stream.StreamLSL` object manages a ring buffer
internally, which is continuously refreshed with new samples. Notably, the two pointers
are concealed, with the head pointer being automatically adjusted to the latest received
sample. Given the preference for accessing the most recent information in neural,
physiological, and behavioral real-time applications, this operational approach
streamlines interaction with LSL streams and mitigates the risk of users accessing
outdated data.

Mocking an LSL stream
---------------------

To build real-time applications or showcase their functionalities, such as in this
tutorial, it's essential to generate simulated LSL streams. This involves creating a
:class:~mne_lsl.lsl.StreamOutlet and regularly sending data through it.

Within MNE-LSL, the :class:`~mne_lsl.player.PlayerLSL` generates a simulated LSL stream
utilizing data from a :class:`mne.io.Raw` file or object. This stream inherits its
description and channel specifications from the associated :class:`~mne.Info`. This
information encompasses channel properties, channel locations, filters, digitization,
and `SSP projectors`_. The :class:~mne_lsl.player.PlayerLSL subsequently publishes data
at regular intervals and seamlessly loops back to the starting point once the end of the
file is reached.

.. GENERATED FROM PYTHON SOURCE LINES 84-97

.. code-block:: Python


    import time
    import uuid

    from matplotlib import pyplot as plt
    from mne import set_log_level

    from mne_lsl.datasets import sample
    from mne_lsl.player import PlayerLSL as Player
    from mne_lsl.stream import StreamLSL as Stream

    set_log_level("WARNING")








.. GENERATED FROM PYTHON SOURCE LINES 98-103

.. note::

    The argument ``source_id`` can be omitted most of the time. But for reliability in
    our documentation build on CIs, we assign a random unique identifier to each
    mock stream created.

.. GENERATED FROM PYTHON SOURCE LINES 103-109

.. code-block:: Python


    source_id = uuid.uuid4().hex
    fname = sample.data_path() / "sample-ant-raw.fif"
    player = Player(fname, chunk_size=200, source_id=source_id).start()
    player.info






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    <tr class="repr-element general-5478f873-7b8e-4a08-86bf-2382e1ce3406 ">
        <td class="repr-section-toggle-col"></td>
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        <td>mne_anonymize</td>
    
    </tr>
    







    <tr class="repr-section-header acquisition-59627769-9eb1-4625-b0e1-94c586df19fa" 
        title="Hide section"  onclick="toggleVisibility('acquisition-59627769-9eb1-4625-b0e1-94c586df19fa')">
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    <tr class="repr-element acquisition-59627769-9eb1-4625-b0e1-94c586df19fa ">
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                63
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    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 110-121

Once the :meth:`~mne_lsl.player.PlayerLSL.start` is called, data is published at
regular intervals. The interval duration depends on the sampling rate and on the
number of samples pushed at once, defined by the ``chunk_size`` argument of the
:class:`~mne_lsl.player.PlayerLSL` object.

.. note::

    The default setting for chunk_size is ``10``. In real-time applications, there may
    be advantages to employing smaller chunk sizes for data publication, but to build
    the documentation website or to run test successfully on CIs, a larger chunk size
    is used to reduce the number of push operations and improve stability.

.. GENERATED FROM PYTHON SOURCE LINES 121-127

.. code-block:: Python


    sfreq = player.info["sfreq"]
    chunk_size = player.chunk_size
    interval = chunk_size / sfreq  # in seconds
    print(f"Interval between 2 push operations: {interval} seconds.")





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Interval between 2 push operations: 0.1953125 seconds.




.. GENERATED FROM PYTHON SOURCE LINES 128-151

A :class:`~mne_lsl.player.PlayerLSL` can also stream annotations attached to the
:class:`mne.io.Raw` object. Annotations are streamed on a second irregularly sampled
:class:`~mne_lsl.lsl.StreamOutlet`. See
:ref:`this separate tutorial <tut-player-annotations>` for additional information.

Subscribing to an LSL stream
----------------------------

With the mock LSL stream operational in the background, we can proceed to subscribe to
this stream and access both its description and the data stored within its buffer. The
:class:`~mne_lsl.stream.StreamLSL` object operates both the underlying
:class:`~mne_lsl.lsl.StreamInlet` and the ring buffer, which size must be
explicitly set upon creation.

.. note::

    A :class:`~mne_lsl.stream.StreamLSL` can connect to a single LSL stream. Thus, if
    multiple LSL stream are present on the network, it's crucial to uniquely identify
    a specific LSL stream using the ``name``, ``stype``, and ``source_id`` arguments
    of the :class:`~mne_lsl.stream.StreamLSL` object.

The stream description is automatically parsed into an :class:`mne.Info` upon
connection with the method :meth:`mne_lsl.stream.StreamLSL.connect`.

.. GENERATED FROM PYTHON SOURCE LINES 151-155

.. code-block:: Python


    stream = Stream(bufsize=2, source_id=source_id).connect()
    stream.info






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    <table class="repr table table-hover table-striped table-sm table-responsive small">
    







    <tr class="repr-section-header general-bda6833e-5758-4375-b0b1-d70404bf8893"  title="Hide section" 
        onclick="toggleVisibility('general-bda6833e-5758-4375-b0b1-d70404bf8893')">
        <th class="repr-section-toggle-col">
            <button>
            
                <span class="collapse-uncollapse-caret"></span>
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        </th>
        <th colspan="2">
            <strong>General</strong>
        </th>
    </tr>

    <tr class="repr-element general-bda6833e-5758-4375-b0b1-d70404bf8893 ">
        <td class="repr-section-toggle-col"></td>
        <td>MNE object type</td>
        <td>Info</td>
    </tr>
    <tr class="repr-element general-bda6833e-5758-4375-b0b1-d70404bf8893 ">
        <td class="repr-section-toggle-col"></td>
        <td>Measurement date</td>
    
        <td>Unknown</td>
    
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    <tr class="repr-element general-bda6833e-5758-4375-b0b1-d70404bf8893 ">
        <td class="repr-section-toggle-col"></td>
        <td>Participant</td>
    
        <td>Unknown</td>
    
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    <tr class="repr-element general-bda6833e-5758-4375-b0b1-d70404bf8893 ">
        <td class="repr-section-toggle-col"></td>
        <td>Experimenter</td>
    
        <td>Unknown</td>
    
    </tr>
    







    <tr class="repr-section-header acquisition-9ca8b3ec-dccf-4c30-80e6-f91118fd62ab" 
        title="Hide section"  onclick="toggleVisibility('acquisition-9ca8b3ec-dccf-4c30-80e6-f91118fd62ab')">
        <th class="repr-section-toggle-col">
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    <tr class="repr-element acquisition-9ca8b3ec-dccf-4c30-80e6-f91118fd62ab ">
        <td class="repr-section-toggle-col"></td>
        <td>Sampling frequency</td>
        <td>1024.00 Hz</td>
    </tr>



    







    <tr class="repr-section-header channels-e4f2e4a4-01cf-44e6-9b61-fcf10234e3ae"  title="Hide section" 
        onclick="toggleVisibility('channels-e4f2e4a4-01cf-44e6-9b61-fcf10234e3ae')">
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    <tr class="repr-element channels-e4f2e4a4-01cf-44e6-9b61-fcf10234e3ae ">
        <td class="repr-section-toggle-col"></td>
        <td>EEG</td>
        <td>
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                63
            </button>

        
        </td>
    </tr>


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        <td class="repr-section-toggle-col"></td>
        <td>EOG</td>
        <td>
            <button class="channel-names-btn" onclick="alert('Good EOG:\n\nvEOG, hEOG')" title="(Click to open in popup)&#13;&#13;vEOG, hEOG">
                2
            </button>

        
        </td>
    </tr>


    <tr class="repr-element channels-e4f2e4a4-01cf-44e6-9b61-fcf10234e3ae ">
        <td class="repr-section-toggle-col"></td>
        <td>ECG</td>
        <td>
            <button class="channel-names-btn" onclick="alert('Good ECG:\n\nECG')" title="(Click to open in popup)&#13;&#13;ECG">
                1
            </button>

        
        </td>
    </tr>


    <tr class="repr-element channels-e4f2e4a4-01cf-44e6-9b61-fcf10234e3ae ">
        <td class="repr-section-toggle-col"></td>
        <td>Stimulus</td>
        <td>
            <button class="channel-names-btn" onclick="alert('Good Stimulus:\n\nTRIGGER')" title="(Click to open in popup)&#13;&#13;TRIGGER">
                1
            </button>

        
        </td>
    </tr>


    <tr class="repr-element channels-e4f2e4a4-01cf-44e6-9b61-fcf10234e3ae ">
        <td class="repr-section-toggle-col"></td>
        <td>Galvanic skin response</td>
        <td>
            <button class="channel-names-btn" onclick="alert('Good Galvanic skin response:\n\nEDA')" title="(Click to open in popup)&#13;&#13;EDA">
                1
            </button>

        
        </td>
    </tr>


    <tr class="repr-element channels-e4f2e4a4-01cf-44e6-9b61-fcf10234e3ae ">
        <td class="repr-section-toggle-col"></td>
        <td>Head & sensor digitization</td>
    
        <td>Not available</td>
    
    </tr>
    







    <tr class="repr-section-header filters-11e0f24e-ae9f-4a22-8a8b-d3d9d101cc1e"  title="Hide section" 
        onclick="toggleVisibility('filters-11e0f24e-ae9f-4a22-8a8b-d3d9d101cc1e')">
        <th class="repr-section-toggle-col">
            <button>
            
                <span class="collapse-uncollapse-caret"></span>
            </button>
        </th>
        <th colspan="2">
            <strong>Filters</strong>
        </th>
    </tr>

    <tr class="repr-element filters-11e0f24e-ae9f-4a22-8a8b-d3d9d101cc1e ">
        <td class="repr-section-toggle-col"></td>
        <td>Highpass</td>
        <td>0.00 Hz</td>
    </tr>


    <tr class="repr-element filters-11e0f24e-ae9f-4a22-8a8b-d3d9d101cc1e ">
        <td class="repr-section-toggle-col"></td>
        <td>Lowpass</td>
        <td>512.00 Hz</td>
    </tr>


    </table>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 156-160

Interaction with a :class:`~mne_lsl.stream.StreamLSL` is similar to the interaction
with a :class:`mne.io.Raw`. In this example, the stream is mocked from a 64 channels
EEG recording with an ANT Neuro amplifier. It includes 63 EEG, 2 EOG, 1 ECG, 1 EDA, 1
STIM channel, and uses CPz as reference.

.. GENERATED FROM PYTHON SOURCE LINES 160-164

.. code-block:: Python


    ch_types = stream.get_channel_types(unique=True)
    print(f"Channel types included: {', '.join(ch_types)}")





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Channel types included: eeg, eog, gsr, ecg, stim




.. GENERATED FROM PYTHON SOURCE LINES 165-178

Operations such as channel selection, re-referencing, and filtering are performed
directly on the ring buffer. For instance, we can select the EEG channels, add the
missing reference channel and re-reference using a common average referencing scheme
which will reduce the ring buffer to 64 channels.

.. note::

    By design, once a re-referencing operation is performed or if at least one filter
    is applied, it is not possible anymore to select a subset of channels with the
    methods :meth:`~mne_lsl.stream.StreamLSL.pick` or
    :meth:`~mne_lsl.stream.StreamLSL.drop_channels`. Note that the re-referencing is
    not reversible while filters can be removed with the method
    :meth:`~mne_lsl.stream.StreamLSL.del_filter`.

.. GENERATED FROM PYTHON SOURCE LINES 178-185

.. code-block:: Python


    stream.pick("eeg")  # channel selection
    assert "CPz" not in stream.ch_names  # reference absent from the data stream
    stream.add_reference_channels("CPz")
    stream.set_eeg_reference("average")
    stream.info






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        <th class="repr-section-toggle-col">
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    <tr class="repr-section-header channels-65b8cca3-0722-4e86-b0bd-433b9e5e2bbc"  title="Hide section" 
        onclick="toggleVisibility('channels-65b8cca3-0722-4e86-b0bd-433b9e5e2bbc')">
        <th class="repr-section-toggle-col">
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    <tr class="repr-element channels-65b8cca3-0722-4e86-b0bd-433b9e5e2bbc ">
        <td class="repr-section-toggle-col"></td>
        <td>EEG</td>
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                64
            </button>

        
        </td>
    </tr>


    <tr class="repr-element channels-65b8cca3-0722-4e86-b0bd-433b9e5e2bbc ">
        <td class="repr-section-toggle-col"></td>
        <td>Head & sensor digitization</td>
    
        <td>Not available</td>
    
    </tr>
    







    <tr class="repr-section-header filters-9b0b71bf-fe85-4926-a507-a1d273f2b740"  title="Hide section" 
        onclick="toggleVisibility('filters-9b0b71bf-fe85-4926-a507-a1d273f2b740')">
        <th class="repr-section-toggle-col">
            <button>
            
                <span class="collapse-uncollapse-caret"></span>
            </button>
        </th>
        <th colspan="2">
            <strong>Filters</strong>
        </th>
    </tr>

    <tr class="repr-element filters-9b0b71bf-fe85-4926-a507-a1d273f2b740 ">
        <td class="repr-section-toggle-col"></td>
        <td>Highpass</td>
        <td>0.00 Hz</td>
    </tr>


    <tr class="repr-element filters-9b0b71bf-fe85-4926-a507-a1d273f2b740 ">
        <td class="repr-section-toggle-col"></td>
        <td>Lowpass</td>
        <td>512.00 Hz</td>
    </tr>


    </table>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 186-197

.. note::

    As for MNE-Python, methods can be chained, e.g.

    .. code-block:: python

        stream.pick("eeg").add_reference_channels("CPz")

The ring buffer is accessed with the method :meth:`~mne_lsl.stream.StreamLSL.get_data`
which returns both the samples and their associated timestamps. In LSL terminology, a
sample is an array of shape (n_channels,).

.. GENERATED FROM PYTHON SOURCE LINES 197-213

.. code-block:: Python


    picks = ("Fz", "Cz", "Oz")  # channel selection
    f, ax = plt.subplots(3, 1, sharex=True, constrained_layout=True)
    for _ in range(3):  # acquire 3 separate window
        # figure how many new samples are available, in seconds
        winsize = stream.n_new_samples / stream.info["sfreq"]
        # retrieve and plot data
        data, ts = stream.get_data(winsize, picks=picks)
        for k, data_channel in enumerate(data):
            ax[k].plot(ts, data_channel)
        time.sleep(0.5)
    for k, ch in enumerate(picks):
        ax[k].set_title(f"EEG {ch}")
    ax[-1].set_xlabel("Timestamp (LSL time)")
    plt.show()




.. image-sg:: /generated/tutorials/images/sphx_glr_00_introduction_001.png
   :alt: EEG Fz, EEG Cz, EEG Oz
   :srcset: /generated/tutorials/images/sphx_glr_00_introduction_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 214-232

.. warning::

    Note that the first of the 3 chunks plotted is longer. This is because
    execution of the channel selection and re-referencing operations took a finite
    amount of time to complete while in the background, the
    :class:`~mne_lsl.stream.StreamLSL` was still acquiring new samples. Note also that
    :py:attr:`~mne_lsl.stream.StreamLSL.n_new_samples` is reset to 0 after each call
    to :meth:`~mne_lsl.stream.StreamLSL.get_data`, but it is not reset if the "tail"
    pointer overtakes the "head" pointer, in other words, it is not reset if the
    number of new samples since the last :meth:`~mne_lsl.stream.StreamLSL.get_data`
    call exceeds the buffer size.

Free resources
--------------

When you are done with a :class:`~mne_lsl.player.PlayerLSL` or
:class:`~mne_lsl.stream.StreamLSL`, don't forget to free the resources they both use
to continuously mock an LSL stream or receive new data from an LSL stream.

.. GENERATED FROM PYTHON SOURCE LINES 232-235

.. code-block:: Python


    stream.disconnect()





.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    <Stream: OFF | MNE-LSL-Player (source: 5e2ebcdf035d401fb6a3584bd03263c1)>



.. GENERATED FROM PYTHON SOURCE LINES 236-238

.. code-block:: Python


    player.stop()




.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    <Player: MNE-LSL-Player | OFF | /home/runner/mne_data/MNE-LSL-data/sample/sample-ant-raw.fif>




.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 5.536 seconds)

**Estimated memory usage:**  297 MB


.. _sphx_glr_download_generated_tutorials_00_introduction.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: 00_introduction.ipynb <00_introduction.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: 00_introduction.py <00_introduction.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: 00_introduction.zip <00_introduction.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_