Installation

There are two ways of getting sMRIPrep installed:

within a Manually Prepared Environment (Python 3.5+), also known as bare-metal installation; or
using container technologies (RECOMMENDED), such as Docker or Singularity.

Once you have your bare-metal environment set-up (first option above), the next step is executing the smriprep command-line. The smriprep command-line options are documented in the Usage section. The smriprep command-line adheres to the BIDS-Apps recommendations for the user interface. Therefore, the command-line has the following structure:

$ smriprep <input_bids_path> <derivatives_path> <analysis_level> <named_options>

On the other hand, if you chose a container infrastructure, then the command-line will be composed of a preamble to configure the container execution followed by the smriprep command-line options as if you were running it on a bare-metal installation. The command-line structure above is then modified as follows:

$ <container_command_and_options> <container_image> \
     <input_bids_path> <derivatives_path> <analysis_level> <smriprep_named_options>

Therefore, once specified, the container options and the image to be run the command line is the same as for the bare-metal installation but dropping the smriprep executable name.

Container technologies: Docker and Singularity

Container technologies are operating-system-level virtualization methods to run Linux systems using the host’s Linux kernel. This is a lightweight approach to virtualization, as compares to virtual machines.

Docker (recommended for PC/laptop and commercial Cloud)

Probably, the most popular framework to execute containers is Docker. If you are to run sMRIPrep on your PC/laptop, this is the RECOMMENDED way of execution. Please make sure you follow the Docker installation instructions. You can check your Docker Engine installation running their hello-world image:

$ docker run --rm hello-world

If you have a functional installation, then you should obtain the following output.

Hello from Docker!
This message shows that your installation appears to be working correctly.

To generate this message, Docker took the following steps:
 1. The Docker client contacted the Docker daemon.
 1. The Docker daemon pulled the "hello-world" image from the Docker Hub.
    (amd64)
 1. The Docker daemon created a new container from that image which runs the
    executable that produces the output you are currently reading.
 1. The Docker daemon streamed that output to the Docker client, which sent it
    to your terminal.

To try something more ambitious, you can run an Ubuntu container with:
 $ docker run -it ubuntu bash

Share images, automate workflows, and more with a free Docker ID:
 https://hub.docker.com/

For more examples and ideas, visit:
 https://docs.docker.com/get-started/

After checking your Docker Engine is capable of running Docker images, then go ahead and check out our documentation to run the sMRIPrep image. The list of Docker images ready to use is found at the Docker Hub, under the nipreps/smriprep identifier.

The `smriprep-docker` wrapper

This is the easiest way to run sMRIPrep using Docker. The Docker wrapper is a Python script that operates the Docker Engine seamlessly as if you were running smriprep directly. To that end, smriprep-docker reinterprets the command-line you are passing and converts it into a docker run command. The wrapper just requires Python and an Internet connection. Install the wrapper using a Python distribution system, e.g.:

$ python -m pip install --user --upgrade smriprep-docker

Singularity (recommended for HPC)

For security reasons, many HPCs (e.g., TACC) do not allow Docker containers, but do allow Singularity containers. The improved security for multi-tenant systems comes at the price of some limitations and extra steps necessary for execution. Please make sure you follow our tips and tricks to run sMRIPrep’s Singularity images.

Manually Prepared Environment (Python 3.5+)

Warning

This method is not recommended! Please checkout container alternatives such as Docker, or Singularity.

Make sure all of sMRIPrep’s External Dependencies are installed. These tools must be installed and their binaries available in the system’s $PATH. A relatively interpretable description of how your environment can be set-up is found in the Dockerfile. As an additional installation setting, FreeSurfer requires a license file (see The FreeSurfer license).

On a functional Python 3.5 (or above) environment with pip installed, sMRIPrep can be installed using the habitual command

$ python -m pip install smriprep

Check your installation with the --version argument

$ smriprep --version

External Dependencies

sMRIPrep is written using Python 3.5 (or above), and is based on nipype.

sMRIPrep requires some other neuroimaging software tools that are not handled by the Python’s packaging system (Pypi) used to deploy the smriprep package:

FSL (version 5.0.9)
ANTs (version 2.2.0 - NeuroDocker build)
AFNI (version Debian-16.2.07)
C3D (version 1.0.0)
FreeSurfer (version 6.0.1)
bids-validator (version 1.1.0)