.. raw:: html

   <link rel="stylesheet" type="text/css" href="_static/custom.css">


Virtual Brain Inference (VBI)
##############################


.. image:: _static/vbi_log.png
   :alt: VBI Logo
   :width: 200px
   :align: center


The **Virtual Brain Inference (VBI)** toolkit is an open-source, flexible solution tailored for probabilistic inference on virtual brain models. It integrates computational models with personalized anatomical data to deepen the understanding of brain dynamics and neurological processes. VBI supports **fast simulations**, comprehensive **feature extraction**, and employs **deep neural density estimators** to handle various neuroimaging data types. Its goal is to bridge the gap in solving the inverse problem of identifying control parameters that best explain observed data, thereby making these models applicable for clinical settings. VBI leverages high-performance computing through GPU acceleration and C++ code to ensure efficiency in processing.


Workflow
========

.. image:: _static/Fig1.png
   :alt: VBI Logo
   :width: 800px

Installation
============


.. code-block:: bash


    conda env create --name vbi python=3.10
    conda activate vbi
    git clone https://github.com/ins-amu/vbi.git
    cd vbi
    pip install .
    # pip install -e .[all,dev,docs]

Using Docker
============

To use the Docker image, you can pull it from the GitHub Container Registry and run it as follows:

.. code-block:: bash

   
    # Get it without building anything locally
    # without GPU
    docker run --rm -it -p 8888:8888 ghcr.io/ins-amu/vbi:main

    # with GPU
    docker run --gpus all --rm -it -p 8888:8888 ghcr.io/ins-amu/vbi:main


    # or build it locally:
    docker build -t vbi-project .                      # build
    docker run --gpus all -it -p 8888:8888 vbi-project # use with gpu

    # Open the browser and go to
    http://127.0.0.1:8888
    
    #Adding Your Notebooks
    #If your notebooks are in /path/examples. To access them in Jupyter, add the volume mapping:
    docker run --gpus all -it -p 8888:8888 -v /path/examples:/app/notebooks vbi-project
    #In the Jupyter interface, you’ll see a notebooks directory containing your .ipynb files.

   

.. code-block:: python 

   import vbi 
   vbi.tests()
   vbi.test_imports()  

   #             Dependency Check              
                                           
   # Package      Version       Status        
   # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 
   # vbi          v0.1.3        ✅ Available  
   # numpy        1.24.4        ✅ Available  
   # scipy        1.10.1        ✅ Available  
   # matplotlib   3.7.5         ✅ Available  
   # sbi          0.22.0        ✅ Available  
   # torch        2.4.1+cu121   ✅ Available  
   # cupy         12.3.0        ✅ Available  
                                            
   # Torch GPU available: True
   # Torch device count: 1
   # Torch CUDA version: 12.1
   # CuPy GPU available: True
   # CuPy device count: 1
   # CUDA Version: 11.8
   # Device Name: NVIDIA RTX A5000
   # Total Memory: 23.68 GB
   # Compute Capability: 8.6



.. toctree::
   :maxdepth: 2
   :caption: Contents:

   models


Examples
=========

.. toctree::
   :maxdepth: 2
   :caption: Contents:

   examples/intro
   examples/intro_feature
   examples/do_cpp
   examples/do_nb
   examples/vep_sde
   examples/mpr_sde_cupy
   examples/mpr_sde_numba
   examples/jansen_rit_sde_cpp
   examples/jansen_rit_sde_cupy
   examples/ww_sde_torch_kong
   examples/ghb_sde_cupy



.. toctree::
    :maxdepth: 2
    :caption: API Reference

    API


Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`