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========
Examples
========



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    <div class="sphx-glr-thumbcontainer" tooltip="Example to plot EEG graph using EEGrasp package. The EEG graph is constructed using the electrode positions from the Biosemi 64 channel montage. The graph is plotted in 3D and topoplot formats.">

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  .. image:: /examples/images/thumb/sphx_glr_plot_eeg_graph_thumb.png
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  :ref:`sphx_glr_examples_plot_eeg_graph.py`

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      <div class="sphx-glr-thumbnail-title">Plot EEG Graph.</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="creation date: 21/03/2024 author: jrodino14@gmail.com description: Example script to calculate distance from an electrode montage from MNE. Requirements: None">

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  .. image:: /examples/images/thumb/sphx_glr_electrode_distance_thumb.png
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  :ref:`sphx_glr_examples_electrode_distance.py`

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      <div class="sphx-glr-thumbnail-title">Electrode Distance.</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="This example demonstrates how to create a graph from EEG electrode positions using a gaussian kernel. The example uses the Biosemi 64 channel montage. The graph is created with two different values of sigma (0.1 and 0.3) and epsilon=0.5.">

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  .. image:: /examples/images/thumb/sphx_glr_make_graph_gaussian_thumb.png
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  :ref:`sphx_glr_examples_make_graph_gaussian.py`

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      <div class="sphx-glr-thumbnail-title">Make Gaussian Graph.</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Channel interpolation example.">

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  .. image:: /examples/images/thumb/sphx_glr_interpolate_channel_thumb.png
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  :ref:`sphx_glr_examples_interpolate_channel.py`

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      <div class="sphx-glr-thumbnail-title">Interpolate Channel.</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Example on how to interpolate missing channels.">

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  .. image:: /examples/images/thumb/sphx_glr_ERP_reconstruction_thumb.png
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  :ref:`sphx_glr_examples_ERP_reconstruction.py`

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      <div class="sphx-glr-thumbnail-title">ERP Construction.</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Learn the graph from EEG signals using the algorithm proposed by Kalofolias et al. (2019) and implemented in pygsp2. This example follows the methods described in Miri et al. (2024). To run this example download the following data file data_set_IVa_aa.mat from the BCI Competition III:">

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  .. image:: /examples/images/thumb/sphx_glr_graph_learning_thumb.png
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  :ref:`sphx_glr_examples_graph_learning.py`

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      <div class="sphx-glr-thumbnail-title">Graph Learning.</div>
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    </div>


.. toctree::
   :hidden:

   /examples/plot_eeg_graph
   /examples/electrode_distance
   /examples/make_graph_gaussian
   /examples/interpolate_channel
   /examples/ERP_reconstruction
   /examples/graph_learning


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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: examples_python.zip </examples/examples_python.zip>`

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

      :download:`Download all examples in Jupyter notebooks: examples_jupyter.zip </examples/examples_jupyter.zip>`


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

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