neurotechdevkit 0.0.8

A research repo for the NDK (Neurotech Development Kit) project

Neurotech Development Kit (NDK) Research

Exploring the Repository

The NDK API was developed with easy-of-use in mind, and 3 lines of code is all you need to run a simulation:

import neurotechdevkit as ndk

scenario = ndk.make('scenario-2-2d-v0')
result = scenario.simulate_steady_state()

... and one line to see the results!

result.render_steady_state_amplitudes()

Setup

Install poetry if it is not already on your system:

$ curl -sSL https://install.python-poetry.org | python -

Install research dependencies for the project either to the current virtual environment or a new one:

$ poetry install

Install stride with

$ poetry run pip install git+https://github.com/trustimaging/stride

---

This will also install the neurotechdevkit package.

If you are not using a virtual environment, poetry will create one for you by default. If you are already using a virtual environment, then poetry will install dependencies to that environment.

Environment

If you let poetry manage your virtual environment, you can use the environment in one of two ways:

1. Activate the environment directly via:

   $ poetry shell
   

2. Prepend poetry run to any python command in order to run the command within the virtual environment. Example:

   $ poetry run foo
   

If you are already using your own virtual environment, you should not need to change anything.

Development

For development, the installation instructions are the same as listed above (poetry installs developer requirements by default).

See our contribution requirements for more information on how to contribute.

A Makefile is provided to assist with common commands such as linting and running unit tests.

$ make lint

$ make test

See the Makefile for other commands.

Acknowledgements

Thanks to Fred Ehrsam for supporting this project, Quintin Frerichs and Milan Cvitkovic for providing direction, and to Sumner Norman for his ultrasound and neuroscience expertise. Thanks to Stride for facilitating ultrasound simulations, Devito for providing the backend solver, Napari for great 3D visualization, and to Jean-Francois Aubry, et al. for the basis of the simulation scenarios.