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

.. only:: html

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

        Click :ref:`here <sphx_glr_download_auto_examples_testiaf.py>`
        to download the full example code

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

.. _sphx_glr_auto_examples_testiaf.py:


IAF neuron example with current generator
-----------------------------------------

A DC current is injected into the neuron using a current generator
device. The membrane potential as well as the spiking activity are
recorded by corresponding devices.

It can be observed how the current charges the membrane, a spike
is emitted, the neuron becomes absolute refractory, and finally
starts to recover.

.. GENERATED FROM PYTHON SOURCE LINES 37-38

First, we import all necessary modules for simulation and plotting

.. GENERATED FROM PYTHON SOURCE LINES 38-42

.. code-block:: default


    import nest
    import matplotlib.pyplot as plt


.. GENERATED FROM PYTHON SOURCE LINES 43-58

Second the function ``build_network`` is defined to build the network and
return the handles of the ``spike_recorder`` and the ``voltmeter``. The
function takes the simulation resolution as argument

The function first resets the simulation kernel and sets the number of
threads and the simulation resolution.  The ``iaf_psc_alpha`` neuron is
created and the handle is stored in the variable `neuron`. The status of
the neuron is changed so it receives an external current. Next a
``voltmeter`` and a ``spike_recorder`` are created and their handles stored
in the variables `vm` and `sr` respectively.

The voltmeter and spike recorder are then connected to the neuron. ``Connect``
takes the device and neuron handles as input. The voltmeter is connected to the
neuron and the neuron to the spike recorder because the neuron sends spikes
to the recorder and the voltmeter 'observes' the neuron.

.. GENERATED FROM PYTHON SOURCE LINES 58-78

.. code-block:: default



    def build_network(dt):

        nest.ResetKernel()
        nest.local_num_threads = 1
        nest.resolution = dt

        neuron = nest.Create('iaf_psc_alpha')
        neuron.I_e = 376.0

        vm = nest.Create('voltmeter')
        sr = nest.Create('spike_recorder')

        nest.Connect(vm, neuron)
        nest.Connect(neuron, sr)

        return vm, sr



.. GENERATED FROM PYTHON SOURCE LINES 79-81

The neuron is simulated for three different resolutions and then the
voltage trace is plotted

.. GENERATED FROM PYTHON SOURCE LINES 81-88

.. code-block:: default


    for dt in [0.1, 0.5, 1.0]:
        print(f"Running simulation with dt={dt:.2f}")
        vm, sr = build_network(dt)

        nest.Simulate(1000.0)


.. GENERATED FROM PYTHON SOURCE LINES 89-98

The network is simulated using ``Simulate``, which takes the desired
simulation time in milliseconds and advances the network state by this
amount of time. During simulation, the ``spike_recorder`` counts the
spikes of the target neuron and the total number is read out at the
end of the simulation period.

The values of the voltage recorded by the voltmeter are read out and
the values for the membrane potential are stored in potential and the
corresponding times in the times array

.. GENERATED FROM PYTHON SOURCE LINES 98-102

.. code-block:: default


        potentials = vm.get('events', 'V_m')
        times = vm.get('events', 'times')


.. GENERATED FROM PYTHON SOURCE LINES 103-104

Using the matplotlib library the voltage trace is plotted over time

.. GENERATED FROM PYTHON SOURCE LINES 104-108

.. code-block:: default


        plt.plot(times, potentials, label=f"dt={dt:.2f}")
        print(f"  Number of spikes: {sr.n_events}")


.. GENERATED FROM PYTHON SOURCE LINES 109-110

Finally the axis are labelled and a legend is generated

.. GENERATED FROM PYTHON SOURCE LINES 110-116

.. code-block:: default


        plt.legend(loc=3)
        plt.xlabel("time (ms)")
        plt.ylabel("V_m (mV)")

    plt.show()


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

   **Total running time of the script:** ( 0 minutes  0.000 seconds)


.. _sphx_glr_download_auto_examples_testiaf.py:

.. only:: html

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


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

      :download:`Download Python source code: testiaf.py <testiaf.py>`

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

      :download:`Download Jupyter notebook: testiaf.ipynb <testiaf.ipynb>`


.. only:: html

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

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