:orphan:

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

Tutorials
=========

This page contains detailed tutorials using ``MNE-LSL``, presenting the different
objects and their features.



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    <div class="sphx-glr-thumbnails">

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    <div class="sphx-glr-thumbcontainer" tooltip="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.">

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  .. image:: /generated/tutorials/images/thumb/sphx_glr_00_introduction_thumb.png
    :alt:

  :ref:`sphx_glr_generated_tutorials_00_introduction.py`

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      <div class="sphx-glr-thumbnail-title">Introduction to real-time LSL streams</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="LSL is a library designed for streaming time series data across different platforms and programming languages. The core library is primarily written in C++, and bindings are accessible for Python, C#, Java, MATLAB, and Unity, among others. You can find a comprehensive list here.">

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  .. image:: /generated/tutorials/images/thumb/sphx_glr_10_low_level_API_thumb.png
    :alt:

  :ref:`sphx_glr_generated_tutorials_10_low_level_API.py`

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      <div class="sphx-glr-thumbnail-title">Low-level LSL API</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Annotations from a Raw object can be streamed as an event stream by PlayerLSL. The stream will be irregularly sampled, numerical, and of type &#x27;annotations&#x27;.">

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  .. image:: /generated/tutorials/images/thumb/sphx_glr_20_player_annotations_thumb.png
    :alt:

  :ref:`sphx_glr_generated_tutorials_20_player_annotations.py`

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      <div class="sphx-glr-thumbnail-title">Player with annotations</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="The StreamLSL object offers 2 mode of acquisition: automatic or manual. In automatic mode, the stream object acquires new chunks of samples at a regular interval. In manual mode, the user has to call the acquire to acquire new chunks of samples from the network. The automatic or manual acquisition is selected via the acquisition_delay argument of connect:">

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  .. image:: /generated/tutorials/images/thumb/sphx_glr_30_stream_manual_thumb.png
    :alt:

  :ref:`sphx_glr_generated_tutorials_30_stream_manual.py`

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      <div class="sphx-glr-thumbnail-title">Automatic vs Manual acquisition</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="The EpochsStream object can be used similarly to mne.Epochs to create epochs from a continuous stream of samples around events of interest.">

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  .. image:: /generated/tutorials/images/thumb/sphx_glr_40_epochs_thumb.png
    :alt:

  :ref:`sphx_glr_generated_tutorials_40_epochs.py`

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      <div class="sphx-glr-thumbnail-title">Epoching a Stream in real-time</div>
    </div>


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    </div>


.. toctree::
   :hidden:

   /generated/tutorials/00_introduction
   /generated/tutorials/10_low_level_API
   /generated/tutorials/20_player_annotations
   /generated/tutorials/30_stream_manual
   /generated/tutorials/40_epochs


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  .. container:: sphx-glr-footer sphx-glr-footer-gallery

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

      :download:`Download all examples in Python source code: tutorials_python.zip </generated/tutorials/tutorials_python.zip>`

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

      :download:`Download all examples in Jupyter notebooks: tutorials_jupyter.zip </generated/tutorials/tutorials_jupyter.zip>`


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

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