Files for creating an nipype Singularity container based on the docker image nipype/nipype:latest .

nipype.swist

Bootstrap: docker
From: nipype/nipype:latest

# This is the adjusted (fixed) build recipe for the issue above.
# sudo singularity build swist Singularity.swist

%labels
    Maintainer GT
    Version v1.0

%environment
    . /opt/conda/bin/activate neuro

%post
    # Install nano
    apt-get update && apt-get install -y nano

    # conda installs to /opt/miniconda-latest, so link to the expected location
    ln -s /opt/miniconda-latest /opt/conda

    echo ". /opt/conda/etc/profile.d/conda.sh" >>$SINGULARITY_ENVIRONMENT
    echo "conda activate neuro" >>$SINGULARITY_ENVIRONMENT

    # Install into conda environment
    . /opt/conda/bin/activate neuro &&
    /opt/conda/bin/conda install --name neuro -y seaborn &&
    /opt/conda/bin/conda install --name neuro -y jupyter &&
    /opt/conda/envs/neuro/bin/pip install pybids
    

resize_partition.sh

# List of commands I used to resize the paritition within vagrant
#
# Caveat emptor.
#
# sudo vgdisplay
# sudo lvextend -L+78 /dev/vagrant-vg/root
# sudo resize2fs /dev/vagrant-vg/root

run_nipype_docker.sh

#!/bin/bash

docker run -it --rm \
       -v /Volumes/Data/Courses/Tutorials/nipype_tutorial/:/home/neuro/nipype_tutorial \
       -v /Volumes/Data/Courses/Tutorials/nipype_tutorial/data/:/data \
       -v /Volumes/Data/Courses/Tutorials/nipype_tutorial/output/:/output \
       -p 8989:8888 \
       miykael/nipype_tutorial \
       jupyter notebook

Vagrantfile

# -*- mode: ruby -*-
# vi: set ft=ruby :

# All Vagrant configuration is done below. The "2" in Vagrant.configure
# configures the configuration version (we support older styles for
# backwards compatibility). Please don't change it unless you know what
# you're doing.
Vagrant.configure("2") do |config|
  # The most common configuration options are documented and commented below.
  # For a complete reference, please see the online documentation at
  # https://docs.vagrantup.com.

  # Every Vagrant development environment requires a box. You can search for
  # boxes at https://vagrantcloud.com/search.
  config.vm.box = "sylabs/singularity-3.7-ubuntu-bionic64"

  # Disable automatic box update checking. If you disable this, then
  # boxes will only be checked for updates when the user runs
  # `vagrant box outdated`. This is not recommended.
  # config.vm.box_check_update = false

  # Create a forwarded port mapping which allows access to a specific port
  # within the machine from a port on the host machine. In the example below,
  # accessing "localhost:8080" will access port 80 on the guest machine.
  # NOTE: This will enable public access to the opened port
  # config.vm.network "forwarded_port", guest: 80, host: 8080

  # Create a forwarded port mapping which allows access to a specific port
  # within the machine from a port on the host machine and only allow access
  # via 127.0.0.1 to disable public access
  # config.vm.network "forwarded_port", guest: 80, host: 8080, host_ip: "127.0.0.1"

  # Create a private network, which allows host-only access to the machine
  # using a specific IP.
  # config.vm.network "private_network", ip: "192.168.33.10"

  # Create a public network, which generally matched to bridged network.
  # Bridged networks make the machine appear as another physical device on
  # your network.
  # config.vm.network "public_network"

  # Share an additional folder to the guest VM. The first argument is
  # the path on the host to the actual folder. The second argument is
  # the path on the guest to mount the folder. And the optional third
  # argument is a set of non-required options.
  config.vm.synced_folder "../data", "/vagrant_data"
  
  # n.b. the disk seems to be created with a 20GiB partition within the 50GiB space, and requires
  # LVM commands to resize the partition. JTJ 2022-04-12
  config.disksize.size = '50GB'

  # Provider-specific configuration so you can fine-tune various
  # backing providers for Vagrant. These expose provider-specific options.
  # Example for VirtualBox:
  #
  config.vm.provider "virtualbox" do |vb|
    # Display the VirtualBox GUI when booting the machine
    vb.gui = true
    # Customize the amount of memory on the VM:
    vb.memory = "8192"
  end
  #
  # View the documentation for the provider you are using for more
  # information on available options.

  # Enable provisioning with a shell script. Additional provisioners such as
  # Ansible, Chef, Docker, Puppet and Salt are also available. Please see the
  # documentation for more information about their specific syntax and use.
  # config.vm.provision "shell", inline: <<-SHELL
  #   apt-get update
  #   apt-get install -y apache2
  # SHELL
end

fMRI
Nipype is a Python system
that abstract away the command line and gui interfaces of the analysis
packages I listed in my previous email. Some of those packages are
Python- and compiled C-based, such as FSL. Others, such as AFNI is
written in C, Python, R, and shell scripts, while SPM is MATLAB-based.
Thus the need for Docker or Singularity, to ensure that everything is
installed, configured, and set up to work with nipype and/or fmriflows.
Nipype provides a consistent and sensible interface to all the
underlying packages, and allows creating workflows where the output of
one program can be sent to another. The underlying shell commands,
temporary files, etc. happen behind the scenes. Nipype is a 'glass box',
if you will.

I've been working to try to get either running on my computer, then
realized that the engineers are well suited for that. Here are a couple
of resources that should allow creation of Singularity containers from
the available Docker images.

This gist has a .swist file for nipype. It's a version of one I found
online here
https://gist.github.com/vsoch/dca1abe2baf373e5e2b451a0baf8591d#file-singularity-swist-L10.
https://gist.github.com/JohnAtl/515577dd365accc71e7c16f7e329b09e
Also included are the Docker command that I use to start the Docker
image when I'm running the Docker. It maps local folders to the Docker
folders so that I can work on the notebooks, data, and access the output
outside the container, and those changes will persist. I would need the
same functionality with a Singularity container, which I believe is
possible with Vagrant.