Skip to main content

The Virtual Brain Ontology

Project description

TVBO logo

The Virtual Brain Ontology

Python package PyPI version PyPI - Downloads License

tvbo is a Python library to access the knowledge representation system (i.e., ontology) and data model for the neuroinformatics platform The Virtual Brain (TVB).

🚀 Installation

pip install tvbo

Platform Notes

Intel Mac Users (x86_64): Due to JAX dropping Intel Mac support in version 0.5.0+, you need Python 3.9-3.12. The package will automatically install JAX 0.4.28 which is the last version supporting Intel Macs.

Apple Silicon Mac Users: Python ≥3.10 is supported. You'll get the latest compatible JAX version automatically.

📖 Quick Start

Example: Lorenz Attractor Simulation

📝 Model Specification (YAML)
name: LorenzAttractor
parameters:
    sigma:
        value: 10
        label: Prandtl number
    rho:
        label: Rayleigh number
        value: 28
    beta:
        value: 2.6666666666666665
state_variables:
    X:
        equation:
            lhs: \dot{X}
            rhs: sigma * (Y - X)
    Y:
        equation:
            lhs: \dot{Y}
            rhs: X * (rho - Z) - Y
    Z:
        equation:
            lhs: \dot{Z}
            rhs: X * Y - beta * Z
🔧 Generate Code
from tvbo import Dynamics, SimulationExperiment

lorenz = Dynamics(
    parameters={
        "sigma": {"value": 10.0},
        "rho": {"value": 28.0},
        "beta": {"value": 8 / 3},
    },
    state_variables={
        "X": {"equation": {"rhs": "sigma * (Y - X)"}},
        "Y": {"equation": {"rhs": "X * (rho - Z) - Y"}},
        "Z": {"equation": {"rhs": "X * Y - beta * Z"}},
    },
)

code = SimulationExperiment(dynamics=lorenz).render_code('jax')
print(code)
▶️ Run Simulation
from tvbo import Dynamics, SimulationExperiment

lorenz = Dynamics(
    parameters={
        "sigma": {"value": 10.0},
        "rho": {"value": 28.0},
        "beta": {"value": 8 / 3},
    },
    state_variables={
        "X": {"equation": {"rhs": "sigma * (Y - X)"}},
        "Y": {"equation": {"rhs": "X * (rho - Z) - Y"}},
        "Z": {"equation": {"rhs": "X * Y - beta * Z"}},
    },
)

# Run simulation and plot results
SimulationExperiment(dynamics=lorenz).run(duration=1000).plot()

📚 Documentation

🔬 Features

  • 🧠 Access TVB ontology and knowledge base
  • 📊 Define and simulate dynamical systems
  • 🔄 Code generation for multiple backends (JAX, NumPy)
  • 📈 Built-in visualization tools
  • 🗃️ Structured metadata schema

📦 Installation Options

Standard Installation

pip install tvbo

With API Server Support

pip install tvbo[api]

With TVB Integration

pip install tvbo[tvb]

Full Installation (All Features)

pip install tvbo[all]

Note: The knowledge extra requires manual installation:

pip install git+https://github.com/neurommsig/neurommsig-knowledge.git

📄 License

Copyright © 2025 Charité Universitätsmedizin Berlin. This software is licensed under the terms of the European Union Public Licence (EUPL) version 1.2 or later.

Funding

P.R. acknowledges support by EU Horizon Europe program Horizon EBRAINS2.0 (101147319), VirtualBrainTwin(101137289), EBRAINS-PREP101079717, AISN101057655, EBRAIN-Health 101058516, EIC grant PHRASE 101058240, by the Digital Europe Programme TEF-Health (101100700), Shaiped (101195135), CoordinaTEF (101168074) German Research Foundation SFB 1436 (project ID 425899996); SFB 1315 (project ID 327654276); SFB 936 (project ID 178316478); SPP Computational Connectomics RI 2073/6-1, RI 2073/10-2, RI 2073/9-1; DFG Clinical Research Group BECAUSE-Y 504745852, Berlin University Alliance OpenMake, the Virtual Research Environment at the Charité Berlin and EBRAINS Health Data Cloud and the Berlin Institute of Health and Foundation Charité. P.R. and J.M. acknowledge additionally support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project-ID 424778381 - TRR 295.

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

tvbo-0.3.6.tar.gz (13.4 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

tvbo-0.3.6-py3-none-any.whl (13.7 MB view details)

Uploaded Python 3

File details

Details for the file tvbo-0.3.6.tar.gz.

File metadata

  • Download URL: tvbo-0.3.6.tar.gz
  • Upload date:
  • Size: 13.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for tvbo-0.3.6.tar.gz
Algorithm Hash digest
SHA256 0ae43ddcbb47f4eb2c702242f61a9c91fc2f831e01ef9839f28fba48b41db467
MD5 44edfa963f33f14ccd8e2903e1f23a8b
BLAKE2b-256 dc9967755961459a16c8d97f955b3b2642b5ccc8c8c24eddfcd852b21bcf9401

See more details on using hashes here.

Provenance

The following attestation bundles were made for tvbo-0.3.6.tar.gz:

Publisher: publish-pypi.yml on virtual-twin/tvbo

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file tvbo-0.3.6-py3-none-any.whl.

File metadata

  • Download URL: tvbo-0.3.6-py3-none-any.whl
  • Upload date:
  • Size: 13.7 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for tvbo-0.3.6-py3-none-any.whl
Algorithm Hash digest
SHA256 0e7dcfc7935b5c7d710d9f31e5c6174ede147c372a1e6d62d946e9add8ff3a6c
MD5 7c6413fbcab1debac4268560893cb0f9
BLAKE2b-256 da2f676f99d2efa2f82e98a12490ebae5b67e6acdc78a15f88ec62a7ab5ebc42

See more details on using hashes here.

Provenance

The following attestation bundles were made for tvbo-0.3.6-py3-none-any.whl:

Publisher: publish-pypi.yml on virtual-twin/tvbo

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

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