neuro-forge: reproducible provisioning of neuroimaging workspaces for image processing and data analysis
This project contains everything needed to build and update the neuro-forge packages. neuro-forge is a set of packages for the Conda ecosystem dedicated to image analysis and data analysis in neuroimaging. The URL for neuro-forge channel is https://brainvisa.info/neuro-forge.
neuro-forge is still in early alpha stage and should only be used for testing.
Most action with neuro-forge requires to install Pixi. Pixi is a package manager fully compatible with Conda packages ecosystem but, at the time of this writing, much more efficient than Conda.
neuro-forge packages are contained in a Conda channel located in https://brainvisa.info/neuro-forge. They can be installed using Pixi, Mamba or Conda. We recommend the use of pixi. For instance, once pixi is installed, one can use the following script to setup a workspace containing anatomist:
# Create a workspace directory
mkdir ~/workspace
# Setup workspace
cd ~/workspace
pixi init -c https://brainvisa.info/neuro-forge -c conda-forge
# Enter workspace
pixi shell
# Install anatomist
pixi add anatomist
# Run anatomist
anatomist
Neuro-forge is currently maintained by Neurospin GAIA team. The only way to add/modify/remove a package from neuro-forge channel is to modify the neuro-forge channel directory which is a clone of the published channel located in Neurospin. Modification to this directory is allowed to packages maintainer. The neuro-forge channel directory is synchronized to neuro-forge channel when modified.
If you wish to participate to neuro-forge, you can contact the BrainVISA team.
The creation of packages for neuro-forge is based on the use of rattler-build. Each package is created by writing a recipe that is used by rattler-build to create the final package file. The neuro-forge channel is composed of three kinds of recipes:
- Standard recipes that are standard rattler-build recipes that are git compatible (i.e. composed of, at most, a few text file) and can be built independently using only dependencies from standard channels such as conda-forge and bioconda.
- Internal recipes that are located in the neuro-forge directory in Neurospin. Packages are put here either because they are too big (some packages requires several giga bytes of data) or because the recipe is not public.
- soma-forge recipes that are used to create packages for the BrainVISA project. Most of these packages are compiled ; that adds a binary dependency between them. Therefore their compilation and packaging requires a soma-forge development environment.
In order to build packages from standard recipes, the neuro-forge build command can be used. To setup an environment for this command, one can use git and pixi with the following script:
git clone https://github.com/neurospin/neuro-forge
cd neuro-forge
pixi shell
Then, one or more packages can be built by using the following command.
neuro-forge build {output directory} {package} [{package}...]
For instance, to build a package for the latest ldscore release:
neuro-forge build /tmp/channel ldscore
First install soma-forge command that is located in neuro-forge project.
git clone https://github.com/neurospin/neuro-forge
cd neuro-forge
Then create the BrainVISA development directory by giving its location and the environment version, plus optionally a list of target packages. Environment version is 0.0 for standard development using default git branches, 0.1 for development with Capsul 3 or 6.0 for the compilation of brainvisa-6.0 branches. Target packages are the name of soma-forge packages. It will select all corresponding brainvisa-cmake components (taking into account packages dependencies) and put them in bv_maker.cfg file. By default, a selection of packages defined specifically for the environment will be included.
pixi run soma-forge init /somewhere/soma-forge-0.0 0.0
Finally, the development directory can be used independently of neuroforge:
cd /somewhere/soma-forge-0.0
pixi shell
bv_maker
The packages currently built have the following dependencies:
- blue: empty package with only dependencies ;
- dark green: package containing compiled brainvisa-cmake components ;
- light green: package containing interpreted brainvisa-cmake components ;
- bisque: neuro-forge package ;
- light grey: package from public channel such as conda-forge or bioconda.
