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virtual-twin/tvbo

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(local_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(local_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.

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