A package for modelling morphologically detailed neuronal microcircuits.
Project description
Note: The scaffold framework is still under heavy development. Please check the Known Issues section at the bottom for important issues that fell victim to our deadlines and will be solved at a later date.
BSB: A scaffold modelling framework
This package is intended to facilitate spatially, topologically and morphologically detailed simulations of brain regions developed by the Department of Brain and Behavioral Sciences at the University of Pavia.
Installation
pip
This software can be installed as a Python package from PyPI through pip:
pip install bsb
Developers
Developers best use pip's editable install. This creates a live link between the installed package and the local git repository:
git clone git@github.com:dbbs-lab/bsb
cd bsb
pip install -e .[dev]
pre-commit install
Usage
The scaffold framework can be used through the command line interface or as a python package.
Command line interface (CLI)
Run the framework in the command line with subcommand compile
to compile a network
architecture.
bsb --config=mouse_cerebellum_cortex_noTouch.json compile -x=200 -z=200 -p
To run with different configurations, change the config argument to the relative path of a
.json config file. The -p
flag indicates that the compiled network should be plotted
afterwards and can be omitted.
Python package
The central object is the bsb.core.Scaffold
class. This object requires a
bsb.config.ScaffoldConfig
instance for its construction. To emulate the CLI
functionality you can use the JSONConfig
class and provide the relative path to the
configuration file.
from bsb import Scaffold
from bsb.config import JSONConfig
config = new JSONConfig(file='mouse_cerebellum_cortex_noTouch.json')
scaffoldInstance = new Scaffold(config)
This scaffold instance can then be used to perform the subcommands available in the CLI by calling their corresponding functions:
scaffoldInstance.compile_network()
Plotting network architecture
After calling compile_network
the scaffold instance can be plotted:
scaffoldInstance.plot_network_cache()
Known issues
No configuration serialization
When modifying the config object through scripts and then saving it to file, you'll store the original configuration file text, and you won't actually serialize the modified object
We will fix this by version 4.0
If MPI is installed but mpi4py is not undefined behavior may occur
The amount of NEST virtual processes is determined by using mpi4py to get the amount of
MPI processes. But if the package is not installed it is assumed no MPI simulations will
be ran and the amount of virtual processes might be lower than expected when used in
combination with OpenMP. Be sure to pip install
using the [MPI]
requirement tag.
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