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

.. only:: html

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

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

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

.. _sphx_glr_auto_examples_spatial_conncon_targets.py:


Convergent projection and rectangular mask, from source perspective
--------------------------------------------------------------------

Create two populations of iaf_psc_alpha neurons on a 30x30 grid
Connect the two populations with convergent projection and rectangular mask, and
visualize connections from source perspective

BCCN Tutorial @ CNS*09
Hans Ekkehard Plesser, UMB

.. GENERATED FROM PYTHON SOURCE LINES 33-42

.. code-block:: default


    import nest
    import matplotlib.pyplot as plt
    import numpy as np

    nest.ResetKernel()

    pos = nest.spatial.grid(shape=[30, 30], extent=[3., 3.], edge_wrap=True)


.. GENERATED FROM PYTHON SOURCE LINES 43-44

create and connect two populations

.. GENERATED FROM PYTHON SOURCE LINES 44-57

.. code-block:: default

    a = nest.Create('iaf_psc_alpha', positions=pos)
    b = nest.Create('iaf_psc_alpha', positions=pos)

    cdict = {'rule': 'pairwise_bernoulli',
             'p': 0.5,
             'use_on_source': True,
             'mask': {'rectangular': {'lower_left': [-0.2, -0.5],
                                      'upper_right': [0.2, 0.5]}}}

    nest.Connect(a, b,
                 conn_spec=cdict,
                 syn_spec={'weight': nest.random.uniform(0.5, 2.)})


.. GENERATED FROM PYTHON SOURCE LINES 58-59

first, clear existing figure, get current figure

.. GENERATED FROM PYTHON SOURCE LINES 59-79

.. code-block:: default

    plt.clf()
    fig = plt.gcf()

    # plot targets of two source neurons into same figure, with mask
    for src_index in [30 * 15 + 15, 0]:
        # obtain node id for center
        src = a[src_index:src_index + 1]
        nest.PlotTargets(src, b, mask=cdict['mask'], fig=fig)

    # beautify
    plt.axes().set_xticks(np.arange(-1.5, 1.55, 0.5))
    plt.axes().set_yticks(np.arange(-1.5, 1.55, 0.5))
    plt.grid(True)
    plt.axis([-2.0, 2.0, -2.0, 2.0])
    plt.axes().set_aspect('equal', 'box')
    plt.title('Connection targets')

    plt.show()

    # plt.savefig('conncon_targets.pdf')


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

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


.. _sphx_glr_download_auto_examples_spatial_conncon_targets.py:

.. only:: html

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


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

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

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

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


.. only:: html

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

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