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Tutorials and introductory examples
===================================



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    <div class="sphx-glr-thumbcontainer" tooltip="   In this tutorial, we briefly introduce the vocabulary used in    spatial harmonic analysis (SPHARA) and we give a simple learning    example to SpharaPy. In addition, we show how to design a simple    spatial low-pass filter in the SPHARA domain.">

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  .. image:: /auto_examples/images/thumb/sphx_glr_plot_01_quick_start_thumb.png
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  :doc:`/auto_examples/plot_01_quick_start`

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      <div class="sphx-glr-thumbnail-title">Quick start with SpharaPy</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="   This tutorial introduces the steps necessary to determine a    generalized spatial Fourier basis for an EEG sensor setup    using SpharaPy. The special properties of the different    discretization approaches of the Laplace–Beltrami operator will be    discussed.">

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  .. image:: /auto_examples/images/thumb/sphx_glr_plot_02_sphara_basis_eeg_thumb.png
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  :doc:`/auto_examples/plot_02_sphara_basis_eeg`

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      <div class="sphx-glr-thumbnail-title">Determination of the SPHARA basis functions for an EEG sensor setup</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="   This tutorial shows exemplarily the spatial SPHARA analysis of    256-channel EEG data. The FEM discretization of the    Laplace–Beltrami operator is employed to calculate the SPHARA basic    functions that are used for the SPHARA decomposition.">

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  .. image:: /auto_examples/images/thumb/sphx_glr_plot_03_sphara_analysis_eeg_thumb.png
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  :doc:`/auto_examples/plot_03_sphara_analysis_eeg`

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      <div class="sphx-glr-thumbnail-title">Spatial SPHARA analysis of EEG data</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="   In this tutorial we show how to use the SPHARA basis functions to    design spatial low-pass filters for application to EEG data. The    FEM discretization of the Laplace-Beltrami operator is used to    calculate the SPHARA basis functions. We then construct different    low-pass designs (ideal, Gaussian, Butterworth) using the helper    functions provided by spharapy.spectral_filters.">

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  .. image:: /auto_examples/images/thumb/sphx_glr_plot_04_sphara_filter_eeg_thumb.png
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  :doc:`/auto_examples/plot_04_sphara_filter_eeg`

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      <div class="sphx-glr-thumbnail-title">Spatial SPHARA filtering of EEG data</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Based on the course materials from Training Course 4, held at the International Conference on Basic and Clinical Multimodal Imaging (BaCI) in Chengdu, China, in September 2019.">

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  .. image:: /auto_examples/images/thumb/sphx_glr_plot_05_BaCI2019_TrainingCourse4_SpharaPy_01_thumb.png
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  :doc:`/auto_examples/plot_05_BaCI2019_TrainingCourse4_SpharaPy_01`

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      <div class="sphx-glr-thumbnail-title">SPHARA basis and transform on EEG data (BaCI 2019)</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Based on the course materials from Training Course 4, held at the International Conference on Basic and Clinical Multimodal Imaging (BaCI) in Chengdu, China, in September 2019.">

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  .. image:: /auto_examples/images/thumb/sphx_glr_plot_05_BaCI2019_TrainingCourse4_SpharaPy_02_thumb.png
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  :doc:`/auto_examples/plot_05_BaCI2019_TrainingCourse4_SpharaPy_02`

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      <div class="sphx-glr-thumbnail-title">SPHARA spatial filtering of EEG data (BaCI 2019)</div>
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    </div>


.. toctree::
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   /auto_examples/plot_01_quick_start
   /auto_examples/plot_02_sphara_basis_eeg
   /auto_examples/plot_03_sphara_analysis_eeg
   /auto_examples/plot_04_sphara_filter_eeg
   /auto_examples/plot_05_BaCI2019_TrainingCourse4_SpharaPy_01
   /auto_examples/plot_05_BaCI2019_TrainingCourse4_SpharaPy_02



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