Skip to main content

Biologically detailed neural network simulations and analysis.

Project description

banner

BlueCelluLab

Latest Release

latest release

Documentation

latest documentation

License

license

Build Status

CI

Coverage

coverage

Gitter

Join the chat at https://gitter.im/BlueBrain/BlueCelluLab

Citation

zenodo

The Blue Brain Cellular Laboratory is designed for simulations and experiments on individual cells or groups of cells. Suitable use cases for BlueCelluLab include:

  • Scripting and statistical analysis for single cells or cell pairs.

  • Lightweight, detailed reporting on specific state variables after simulation.

  • Developing synaptic plasticity rules.

  • Validating dynamics of synaptic properties.

  • Automating in-silico whole-cell patching experiments.

  • Debugging, both scientifically and computationally.

Citation

When you use this BlueCelluLab software for your research, we ask you to cite the following reference(this includes poster presentations):

@software{bluecellulab_zenodo,
  author       = {Tuncel, Anil and Van Geit, Werner and Gevaert, Mike and Torben-Nielsen, Benjamin and Mandge, Darshan and Kilic, Ilkan and Jaquier, Aurélien and Muller, Eilif and Kanari, Lida and Markram, Henry},
  title        = {BlueCelluLab},
  month        = jul,
  year         = 2023,
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.8113483},
  url          = {https://doi.org/10.5281/zenodo.8113483}
}

Support

We are providing support on Gitter. We suggest you create tickets on the Github issue tracker in case you encounter problems while using the software or if you have some suggestions.

Main dependencies

Installation

BlueCelluLab can be pip installed with the following command:

pip install bluecellulab

Quick Start

The following example shows how to create a cell, add a stimulus and run a simulation:

from bluecellulab.cell import create_ball_stick
from bluecellulab import Simulation

cell = create_ball_stick()
sim = Simulation()
sim.add_cell(cell)
stimulus = cell.add_step(start_time=5.0, stop_time=20.0, level=0.5)

sim.run(25, cvode=False)
time, voltage = cell.get_time(), cell.get_soma_voltage()
# plotting time and voltage ...
Voltage plot

Tutorial

A more detailed explanation on how to use BlueCelluLab, as well as other examples can be found on the examples page.

API Documentation

The API documentation can be found on ReadTheDocs.

Running the tests

Testing is set up using tox:

pip install tox

tox -e py3  # runs the tests
tox -e lint  # runs the format checks

Contributing

We welcome contributions to BlueCelluLab! Please see the CONTRIBUTING.rst for guidelines on how to contribute.

Funding & Acknowledgements

The development and maintenance of this code is supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

bluecellulab-2.6.32.tar.gz (505.6 kB view details)

Uploaded Source

Built Distribution

bluecellulab-2.6.32-py3-none-any.whl (120.3 kB view details)

Uploaded Python 3

File details

Details for the file bluecellulab-2.6.32.tar.gz.

File metadata

  • Download URL: bluecellulab-2.6.32.tar.gz
  • Upload date:
  • Size: 505.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.12.5

File hashes

Hashes for bluecellulab-2.6.32.tar.gz
Algorithm Hash digest
SHA256 0e29b8ad3ec957e08d95c458acec8b65fc0785a6770f28ab2b55f3c0de4744e7
MD5 4e7e1a48f6755624d1f01c5cd3a1be3d
BLAKE2b-256 badf2eae20e31574ccb274ce0da27dd9fc46b003a9e78910e8789b5c250604b4

See more details on using hashes here.

File details

Details for the file bluecellulab-2.6.32-py3-none-any.whl.

File metadata

File hashes

Hashes for bluecellulab-2.6.32-py3-none-any.whl
Algorithm Hash digest
SHA256 98beabc44cb203cafa71b0cb2ed2a5204f9142adab7a35a352a8895f11192864
MD5 fb9f580114d95a87a84151ad535fd030
BLAKE2b-256 83daa58b6f5745e70709a5303ff29a0e9f780e3d45406d079382062799c10ef4

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page