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 https://github.com/BlueBrain/Fivox
mkdir Fivox/build
cd Fivox/build
cmake ..
make
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.