Introduction

The Blue Brain Python Optimisation Library (BluePyOpt) is an extensible framework for data-driven model parameter optimisation that wraps and standardises several existing open-source tools. It simplifies the task of creating and sharing these optimisations, and the associated techniques and knowledge. This is achieved by abstracting the optimisation and evaluation tasks into various reusable and flexible discrete elements according to established best-practices. Further, BluePyOpt provides methods for setting up both small- and large-scale optimisations on a variety of platforms, ranging from laptops to Linux clusters and cloud-based compute infrastructures.

Citation

When you use the BluePyOpt software or method for your research, we ask you to cite the following Arxiv preprint in your publications:

Van Geit, W., M. Gevaert, G. Chindemi, C. Rössert, J.-D. Courcol, E. Muller, F. Schürmann, I. Segev, and H. Markram (2016, March). BluePyOpt: Leveraging open source software and cloud infrastructure to optimise model parameters in neuroscience. ArXiv e-prints.

@ARTICLE{bluepyopt,
   author = {{Van Geit}, W. and {Gevaert}, M. and {Chindemi}, G. and {R{\"o}ssert}, C. and 
	{Courcol}, J.-D. and {Muller}, E. and {Sch{\"u}rmann}, F. and 
	{Segev}, I. and {Markram}, H.},
    title = "{BluePyOpt: Leveraging open source software and cloud infrastructure to optimise model parameters in neuroscience}",
  journal = {ArXiv e-prints},
archivePrefix = "arXiv",
   eprint = {1603.00500},
 primaryClass = "q-bio.NC",
 keywords = {Quantitative Biology - Neurons and Cognition},
     year = 2016,
    month = mar
}

News

• 2016/03/24: Released version 1.0

Requirements

• Python 2.7+
• Pip (installed by default in newer versions of Python)
• BlueBrain version of DEAP
• Neuron 7.4 (compiled with Python support)
• eFEL eFeature Extraction Library (automatically installed by pip)
• Numpy (automatically installed by pip)
• Pandas (automatically installed by pip)
• The instruction below are written assuming you have access to a command shell on Linux / UNIX / MacOSX / Cygwin

Installation

If you want to use the ephys module of BluePyOpt, you first need to install Neuron with Python support on your machine.

All users need to install the BlueBrain version of DEAP:

pip install git+http://github.com/BlueBrain/deap/

And then bluepyopt itself:

pip install bluepyopt

Cloud infrastructure

We provide instruction on how to set up an optimisation environment on cloud infrastructure or cluster computers here

Quick Start

Single compartmentel model

An iPython notebook with an introductory optimisation of a one compartmental model with 2 HH channels can be found at

https://github.com/BlueBrain/BluePyOpt/blob/master/examples/simplecell/simplecell.ipynb

There is a Binder Virtual Machine available that allows you to run this notebook in your browser:

http://mybinder.org/repo/BlueBrain/BluePyOpt/examples/simplecell/simplecell.ipynb

Neocortical Layer 5 Pyramidal Cell

Scripts for a more complex neocortical L5PC are in this directory

With a notebook:

https://github.com/BlueBrain/BluePyOpt/blob/master/examples/l5pc/L5PC.ipynb

And you can run this in a VM:

http://mybinder.org/repo/BlueBrain/BluePyOpt/examples/l5pc/L5PC.ipynb

API documentation

The API documentation can be found here