Installation

1. Clone the repository and enter it:

   $ git clone [email protected]:BrainProjectTau/Brain.git
   ...
   $ cd Brain/

2. Run the installation script and activate the virtual environment:

   $ ./scripts/install.sh
   ...
   $ source .env/bin/activate
   [Brain] $ # you're good to go!

3. To check that everything is working as expected, run the tests:

   $ pytest tests/
   ...

Usage

The Brain packages provides the following classes:

• Area

  This class represents an Area in the brain.

  >>> from Brain import Area
  >>> area = Area(beta = 0.1, n = 10 ** 7, k = 10 ** 4)

• Assembly

  This class represents an Assembly in the brain.

• Connectome

  Sub-package which holds the structre of the brain. The sub-package defines the following classes:

  • Connectome Abstract class which defines the API which a general connectome should have. This class should be inhereted and implemented.

    >>> from Connectome import Connectome
    >>> class LazyConnectome(Connectome):
    >>>     #implementation of a specific connectome
    >>>> connectome = LazyConnectome()
    >>> area = Area(beta = 0.1, n = 10 ** 7, k = 10 ** 4)
    >>> connectome.add_area(area)

  • NonLazyRandomConnectome Already implemented Connectome which by decides it's edge by chance. This Connectome doesn't use any kind of laziness.

     >>> from Connectome import NonLazyRandomConnectome
     >>>> connectome = NonLazyRandomConnectome()
     >>> area = Area(beta = 0.1, n = 10 ** 7, k = 10 ** 4)
     >>> connectome.add_area(area)

  • To be continued More ways to implement a connectome can be applied simply by inhereting from Connectome and implementing it's API.

• Brain

  This class represents a simulated brain, with it's connectome which holds the areas, stimuli, and all the synapse weights.

  >>> from Brain import Brain, NonLazyRandomConnectome, Area
  >>> connectome = NonLazyRandomConnectome()
  >>> area = Area(beta = 0.1, n = 10 ** 7, k = 10 ** 4)
  >>> connectome.add_area(area)
  >>> brain = Brain(connectome)