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

.. only:: html

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

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

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

.. _sphx_glr_auto_examples_one_neuron_with_noise.py:


One neuron with noise
---------------------

This script simulates a neuron with input from the ``poisson_generator``, and
records the neuron's membrane potential.

.. GENERATED FROM PYTHON SOURCE LINES 32-39

First, we import all necessary modules needed to simulate, analyze and
plot our example. Additionally, we set the verbosity to only show warnings
and reset the kernel.
Resetting the kernel removes any nodes we may have created previously and
resets the internal clock to zero. This allows us to execute the script
several times in a Python shell without interference from previous NEST
simulations.

.. GENERATED FROM PYTHON SOURCE LINES 39-47

.. code-block:: default


    import nest
    import nest.voltage_trace
    import matplotlib.pyplot as plt

    nest.set_verbosity("M_WARNING")
    nest.ResetKernel()


.. GENERATED FROM PYTHON SOURCE LINES 48-51

Second, the nodes (the neuron, poisson generator (two of them), and the
voltmeter) are created using  the ``Create`` function.
We store the returned handles in variables for later reference.

.. GENERATED FROM PYTHON SOURCE LINES 51-56

.. code-block:: default


    neuron = nest.Create("iaf_psc_alpha")
    noise = nest.Create("poisson_generator", 2)
    voltmeter = nest.Create("voltmeter")


.. GENERATED FROM PYTHON SOURCE LINES 57-62

Third, the Poisson generator is configured using ``SetStatus``, which expects
a list of node handles and a list of parameter dictionaries. We set the
Poisson generators to 8,000 Hz and 15,000 Hz, respectively. Note that we do
not need to set parameters for the neuron and the voltmeter, since they have
satisfactory defaults.

.. GENERATED FROM PYTHON SOURCE LINES 62-66

.. code-block:: default


    noise[0].rate = 80000.0
    noise[1].rate = 15000.0


.. GENERATED FROM PYTHON SOURCE LINES 67-69

Fourth, the neuron is connected to the ``poisson_generator`` and to the
``voltmeter``. We also specify the synaptic weight and delay in this step.

.. GENERATED FROM PYTHON SOURCE LINES 69-73

.. code-block:: default


    nest.Connect(noise, neuron, syn_spec={'weight': [[1.2, -1.0]], 'delay': 1.0})
    nest.Connect(voltmeter, neuron)


.. GENERATED FROM PYTHON SOURCE LINES 74-76

Now we simulate the network using ``Simulate``, which takes the
desired simulation time in milliseconds.

.. GENERATED FROM PYTHON SOURCE LINES 76-79

.. code-block:: default


    nest.Simulate(1000.0)


.. GENERATED FROM PYTHON SOURCE LINES 80-82

Finally, we plot the neuron's membrane potential as a function of
time.

.. GENERATED FROM PYTHON SOURCE LINES 82-85

.. code-block:: default


    nest.voltage_trace.from_device(voltmeter)
    plt.show()


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

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


.. _sphx_glr_download_auto_examples_one_neuron_with_noise.py:

.. only:: html

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


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

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

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

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


.. only:: html

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

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