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Dynamical systems models can be defined via two different interfaces in PyRates: via YAML files or via the
Python frontend. In this gallery, we will walk you through the steps of defining a model and the different options you
have along the way.


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    <div class="sphx-glr-thumbcontainer" tooltip="In this tutorial, you will learn how to use YAML definition files to implement a neurodynamic model with multiple interconnected neural populations. In this process, the following questions will be answered:">

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  :doc:`/auto_implementations/yaml_definitions`

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      <div class="sphx-glr-thumbnail-title">YAML-Based Model Definitions</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="In this tutorial, you will learn how to implement a neurodynamic model with multiple interconnected neural populations using Python only (i.e. without YAML definition files).">

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  :doc:`/auto_implementations/python_definitions`

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      <div class="sphx-glr-thumbnail-title">Python-Based Model Definitions</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="In this tutorial, we will go through the different options you have to define delay-coupled dynamical systems in PyRates. As an example, we will use a model of N = 2 interconnected leaky integrator units, the evolution equations of which are given by">

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  :doc:`/auto_implementations/delay_coupling`

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      <div class="sphx-glr-thumbnail-title">Delay Coupling</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="In this tutorial, we will go through the different options you have to define edge templates, i.e. formulations of the dynamics of signal propagation along the edges in a network. As an example, we will use a model of N = 2 interconnected leaky integrator units, the evolution equations of which are given by">

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  :doc:`/auto_implementations/edge_definitions`

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      <div class="sphx-glr-thumbnail-title">Edge Definitions</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Building large networks of coupled neural populations is a core workflow in computational neuroscience. With the legacy PyRates API, a network of N all-to-all coupled nodes requires defining N^2 individual scalar edges, which becomes impractically slow for N \gtrsim 50 because each edge spawns its own operator subgraph during compilation.">

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  .. image:: /auto_implementations/images/thumb/sphx_glr_population_connectivity_thumb.png
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  :doc:`/auto_implementations/population_connectivity`

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      <div class="sphx-glr-thumbnail-title">Large-Scale Networks with PopulationTemplate and Connectivity</div>
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.. toctree::
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   /auto_implementations/yaml_definitions
   /auto_implementations/python_definitions
   /auto_implementations/delay_coupling
   /auto_implementations/edge_definitions
   /auto_implementations/population_connectivity


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

      :download:`Download all examples in Python source code: auto_implementations_python.zip </auto_implementations/auto_implementations_python.zip>`

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

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


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