Fivox (Field Voxelization) is a library to generate volumetric images of 3d scalar fields (Local Field Potential, spike densities, voltage sensitive dye), with loaders for the compartment, soma and spike reports generated by the Neuron and NEST simulators used in the Blue Brain Project. Fivox supports time animation. For more information see @ref applications.

Fivox can be retrieved by cloning the source code.

The voxelize command line tool can be used to generate volumes for ParaView or other volume rendering applications. When compiled with Livre, launch Livre with one of the URIs used by the voxelize command line tool as the volume parameter. The fivox data source will be loaded automatically and selected through one of the volume URI schemes.

The sample-point command line tool can be used to extract the time series at a specific 3D point. The output file can be then used as the input for the plot2D.py python tool to generate a 2D graph showing the evolution of the data over time.

To use the ImageSource programmatically, please refer to the @ref fivox namespace documentation and voxelize command line tool.

Fivox provides the following major features:

• Converting compartment reports to volumetric LFP-like data
• Converting spike reports densities to volumetric data
• Converting compartment and surface area reports to volumetric data
• Time and animation support
• Extract the time series at a specific point

Build Fivox from source:

git clone --recursive https://github.com/BlueBrain/Fivox
mkdir Fivox/Build
cd Fivox/Build
cmake -GNinja -DCLONE_SUBPROJECTS=ON ..
ninja

All command line applications support the following parameters:

@snippet apps/commandLineApplication.h AppParameters @snippet fivox/uriHandler.cpp VolumeParameters

The voxelize command line tool also supports:

@snippet apps/voxelize/voxelize.cpp VoxelizeParameters

The sample-point command line tool also supports:

@snippet apps/samplePoint/sample-point.cpp SamplePointParameters

Fivox uses CMake to create a platform-specific build environment. The following platforms and build environments are tested:

• Linux: Ubuntu 14.04, RHEL 6.6 (Makefile, x64)
• Mac OS X 10.9

The API documentation can be found on bluebrain.github.io.

The development of this software was 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.

This project has received funding from the European Union’s FP7-ICT programme under Grant Agreement No. 604102 (Human Brain Project RUP).

This project has received funding from the European Union's Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 720270 (Human Brain Project SGA1).

This project is based upon work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. OSR-2017-CRG6-3438.

Copyright (c) 2013-2022 Blue Brain Project/EPFL