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

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_auto_examples_run_microcircuit.py>`
        to download the full example code.

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

.. _sphx_glr_auto_examples_run_microcircuit.py:


Microcircuit example (Potjans & Diesmann 2014)
----------------------------------------------

Example illustrating usage of the `microcircuit` python package.

.. GENERATED FROM PYTHON SOURCE LINES 32-44

.. code-block:: Python

    import time
    import nest
    import numpy as np

    ## import model implementation
    from microcircuit import network

    ## import (default) parameters (network, simulation, stimulus)
    from microcircuit.network_params import default_net_dict as net_dict
    from microcircuit.sim_params import default_sim_dict as sim_dict
    from microcircuit.stimulus_params import default_stim_dict as stim_dict


.. GENERATED FROM PYTHON SOURCE LINES 45-118

.. code-block:: Python


    ## set network scale
    scaling_factor = 0.2
    net_dict["N_scaling"] = scaling_factor
    net_dict["K_scaling"] = scaling_factor

    ## set path for storing spike data and figures
    sim_dict['data_path'] = 'data_scale_%.2f/' % scaling_factor
    
    def main():

        ## start timer 
        time_start = time.time()

        ## create instance of the network
        net = network.Network(sim_dict, net_dict, stim_dict)
        time_network = time.time()

        ## create all nodes (neurons, devices)
        net.create()
        time_create = time.time()

        ## connect nework
        net.connect()
        time_connect = time.time()

        ## pre-simulation (warm-up phase)
        net.simulate(sim_dict["t_presim"])
        time_presimulate = time.time()

        ## simulation
        net.simulate(sim_dict["t_sim"])
        time_simulate = time.time()

        ## store metadata
        net.store_metadata()

        ## current memory consumption of the python process (in MB)
        import psutil
        mem = psutil.Process().memory_info().rss / (1024 * 1024)
    
        #####################
        ## plot spikes and firing rate distribution
        print()
        print('##########################################')
        print()
        observation_interval = np.array([sim_dict["t_presim"], sim_dict["t_presim"] + sim_dict["t_sim"]])
        net.evaluate(observation_interval , observation_interval )
        print()
        print('Raster plot                  : see %s ' % (sim_dict['data_path'] + 'raster_plot.png') )
        print('Distributions of firing rates: see %s ' % (sim_dict['data_path'] + 'box_plot.png'   ) )
        time_evaluate = time.time()

        #####################
        ## print timers and memory consumption

        print()
        print('##########################################')
        print()
        print('Times of Rank %d:' % nest.Rank())
        print('    Total time:')
        print('    Time to initialize  : %.3fs' % (time_network - time_start))
        print('    Time to create      : %.3fs' % (time_create - time_network))
        print('    Time to connect     : %.3fs' % (time_connect - time_create))
        print('    Time to presimulate : %.3fs' % (time_presimulate - time_connect))
        print('    Time to simulate    : %.3fs' % (time_simulate - time_presimulate))
        print('    Time to evaluate    : %.3fs' % (time_evaluate - time_simulate))
        print()
        print("Memory consumption: %dMB" % mem)
        print()
        print('##########################################')
        print()
    

.. GENERATED FROM PYTHON SOURCE LINES 119-122

.. code-block:: Python


    if __name__== '__main__':
        main()


.. _sphx_glr_download_auto_examples_run_microcircuit.py:

.. only:: html

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

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

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

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

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

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: run_microcircuit.zip <run_microcircuit.zip>`


.. only:: html

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

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