1. Installing junifer#

1.1. Requirements#

junifer is compatible with Python >= 3.8 and requires the following packages:

  • click>=8.1.3,<8.2

  • numpy>=1.22,<1.24

  • datalad>=0.15.4,<0.18

  • pandas>=1.4.0,<1.6

  • nibabel>=3.2.0,<4.1

  • nilearn>=0.9.0,<1.0

  • sqlalchemy>=1.4.27,<= 1.5.0

  • pyyaml>=5.1.2,<7.0

Depending on the installation method, these packages might be installed automatically.

1.2. Installation#

Depending on your use-case, junifer can be installed differently:

Either way, we strongly recommend using virtual environments.

1.2.1. Stable release#

Use pip to install julearn from PyPI, like so:

pip install junifer

1.2.2. Local Git repository#

Follow the detailed contribution guidelines.

2. Installing external dependencies#

Some markers will require optional external dependencies to be installed. In this section you will find a list of all external dependencies that are required for specific markers.

2.1. AFNI#

To install AFNI, you can always follow the AFNI official instructions. Additionally, you can also follow the following steps to install and configure the AFNI Docker container in your local system.

Important

The AFNI Docker container wrappers add the commands required by junifer. Using these commands have some limitations, mostly related to handling files and paths. Junifer knows about this and uses these commands in the proper way. Keep this in mind if you try to use the AFNI Docker wrappers outside of junifer. These caveats and limitations are not documented.

  1. Install Docker. You can follow the Docker official instructions.

  2. Pull the AFNI Docker image from Docker Hub:

docker pull afni/afni_make_build

  1. Add the Junifer AFNI scripts to your PATH environmental variable. Run the following command:

junifer setup afni-docker

Take the last line and copy it to your .bashrc or .zshrc file.

Or, alternatively, you can exceute this command which will update the ~/.bashrc for you:

junifer setup afni-docker | grep "PATH=" | xargs | >> ~/.bashrc