.. currentmodule:: brian2

.. 01_using_cython:

Example: 01_using_cython
========================


        .. only:: html

            .. |launchbinder| image:: http://mybinder.org/badge.svg
            .. _launchbinder: https://mybinder.org/v2/gh/brian-team/brian2-binder/master?filepath=examples/multiprocessing/01_using_cython.ipynb

            .. note::
               You can launch an interactive, editable version of this
               example without installing any local files
               using the Binder service (although note that at some times this
               may be slow or fail to open): |launchbinder|_

        

Parallel processes using Cython

This example use multiprocessing to run several simulations in parallel.
The code is using the default runtime mode (and Cython compilation, if
possible).

The ``numb_proc`` variable set the number of processes. ``run_sim`` is just a
toy example that creates a single neuron and connects a `StateMonitor` to
record the voltage.

For more details see the `github issue 1154 <https://github.com/brian-team/brian2/issues/1154#issuecomment-582994117>`_:

Note that Python's `multiprocessing` module cannot deal with user-defined functions (including `TimedArray`) and other
complex code structures. If you run into `PicklingError` or `AttributeError` exceptions, you might
have to use the `pathos` (https://pypi.org/project/pathos) package instead, which can handle more complex
code structures.

::

    import os
    import multiprocessing
    
    from brian2 import *
    
    
    def run_sim(tau):
        pid = os.getpid()
        print(f'RUNNING {pid}')
        G = NeuronGroup(1, 'dv/dt = -v/tau : 1', method='exact')
        G.v = 1
        mon = StateMonitor(G, 'v', record=0)
        run(100*ms)
        print(f'FINISHED {pid}')
        return mon.t/ms, mon.v[0]
    
    
    if __name__ == "__main__":
        num_proc = 4
    
        tau_values = np.arange(10)*ms + 5*ms
        with multiprocessing.Pool(num_proc) as p:
            results = p.map(run_sim, tau_values)
    
        for tau_value, (t, v) in zip(tau_values, results):
            plt.plot(t, v, label=str(tau_value))
        plt.legend()
        plt.show()
    

.. image:: ../resources/examples_images/multiprocessing.01_using_cython.1.png