alleninstitute/bmtk repository overview

⁠bmtk docker

A container for running the bmtk with all the prerequisites already installed including

• python 2.9 and required packages
• NEURON 8.0
• NEST 3.3
• DiPDE 2.0

Note: You will not be able to utilize parallelization support (MPI) if running bmtk through Docker. Similarly you can expect memory issues and slowness for larger networks. For building and simulating large networks we recommend installing bmtk and the required tools natively on your machine.

⁠Running the BMTK

There are two ways to use this container; use as a command-line tool for building networks and running simulation of network on your local machine. Or as a Jupyter notebook server.

⁠Through the command-line

To run a network-build or simulation-run bmtk script using the docker container, go to the directory containing your python script and any necessary supporting files:

  $ docker run -v $(pwd):/home/shared/workspace alleninstitute/bmtk python <my_script>.py <opts>

NOTE: All files must be under the directory you are running the command; including network, components, and output directories. If your config.json files references anything outside the working directory branch things will not work as expected.

⁠NEURON Mechanisms

If you are running BioNet and have special mechanims/mod files that need to be compiled, you can do so by running:

$ cd path/to/mechanims  
$ docker run -v $(pwd):/home/shared/workspace/mechanisms alleninstitute/bmtk nrnivmodl modfiles/

⁠Through Jupyter Notebooks

To run a Jupyter Notebook server:

  $ docker run -v $(pwd):/home/shared/workspace -p 8888:8888 alleninstitute/bmtk jupyter

Then open a browser to 127.0.0.1:8888/. Any new files and/or notebooks that you want to save permanently should be created in the workspace folder, otherwise the work will be lost when the server is stopped.