Skip to main content

Dynamical Systems Modeling Framework

Project description

PyRates

License CircleCI PyPI version Documentation Status Python

PyRates is a framework for dynamical systems modeling, developed by Richard Gast and Daniel Rose. It is an open-source project that everyone is welcome to contribute to.

Basic features

Basic features:

  • Frontend:
    • implement models via a frontend of your choice: YAML or Python
    • create basic mathematical building blocks (i.e. differential equations and algebraic equations) and use them to define a networks of nodes connected by edges
    • create hierarchical networks by connecting networks via edges
  • Backend:
    • choose from a number of different backends
    • NumPy backend for dynamical systems modeling on CPUs via Python
    • Tensorflow and PyTorch backends for parameter optimization via gradient descent and dynamical systems modeling on GPUs
    • Julia backend for dynamical system modeling in Julia, via tools such as DifferentialEquations.jl
    • Fortran backend for dynamical systems modeling via Fortran 90 and interfacing the parameter continuation software Auto-07p
  • Other features:
    • perform quick numerical simulations via a single function call
    • choose between different numerical solvers
    • perform parameter sweeps over multiple parameters at once
    • generate backend-specific run functions that evaluate the vector field of your dynamical system
    • Implement dynamic edge equations that include scalar dealys or delay distributions (delay distributions are automatically translated into gamma-kernel convolutions)
    • choose from various pre-implemented dynamical systems that can be directly used for simulations or integrated into custom models

Installation

Stable release (PyPI)

PyRates can be installed via the pip command. We recommend to use Anaconda to create a new python environment with Python >= 3.6 and then simply run the following line from a terminal with the environment being activated:

pip install pyrates

You can install optional (non-default) packages by specifying one or more options in brackets, e.g.:

pip install pyrates[backends]

Available options are backends, dev, and all at the moment. The latter includes all optional packages. Furthermore, the option tests includes all packages necessary to run tests found in the github repository.

Development version (github)

Alternatively, it is possible to clone this repository and run one of the following lines from the directory in which the repository was cloned:

python setup.py install

or

pip install '.[<options>]'

Singularity container

Finally, a singularity container of the most recent version of this software can be found here. This container provides a stand-alone version of PyRates including all necessary Python tools to be run, independent of local operating systems. To be able to use this container, you need to install Singularity on your local machine first. Follow these instructions to install singularity and run scripts inside the PyRates container.

Documentation

For a full API of PyRates, see https://pyrates.readthedocs.io/en/latest/. For examplary simulations and model configurations, please have a look at the jupyter notebooks provided in the documenation folder.

Reference

If you use this framework, please cite: Gast, R., Rose, D., Salomon, C., Möller, H. E., Weiskopf, N., & Knösche, T. R. (2019). PyRates-A Python framework for rate-based neural simulations. PloS one, 14(12), e0225900.

Contact

If you have questions, problems or suggestions regarding PyRates, please contact Richard Gast.

Project details


Download files

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

Source Distribution

pyrates-0.11.2.tar.gz (114.8 kB view details)

Uploaded Source

Built Distribution

pyrates-0.11.2-py3-none-any.whl (159.4 kB view details)

Uploaded Python 3

File details

Details for the file pyrates-0.11.2.tar.gz.

File metadata

  • Download URL: pyrates-0.11.2.tar.gz
  • Upload date:
  • Size: 114.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/33.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.8.12

File hashes

Hashes for pyrates-0.11.2.tar.gz
Algorithm Hash digest
SHA256 0b7136c80ea1ce312ea58931795be4438e88165c99882a6e38008961d3210bfc
MD5 aa40da81c2025a807f67c989f528b134
BLAKE2b-256 db525edbfb042cd5c6f5a067135cba010ab8981ab07ce390253ba2f4c0c144c6

See more details on using hashes here.

Provenance

File details

Details for the file pyrates-0.11.2-py3-none-any.whl.

File metadata

  • Download URL: pyrates-0.11.2-py3-none-any.whl
  • Upload date:
  • Size: 159.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/33.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.8.12

File hashes

Hashes for pyrates-0.11.2-py3-none-any.whl
Algorithm Hash digest
SHA256 46d4f83cbb77205efa0381eeeeb17fb58cfca7ad046c855a2f343cec4660fb43
MD5 3c646590caf2def41415ce5937d79a39
BLAKE2b-256 a316596eb47b165fb52983604bad2ababbade356a4cf812f13ad0ca1e3a34724

See more details on using hashes here.

Provenance

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