Installation
Install from github:
pip install -e git+https://github.com/akhanf/snakedwi#egg=snakedwi
Note: you can re-run this command to re-install with the latest version
Running the app
Do a dry-run first (-n
) and simply print (-p
) what would be run:
snakedwi /path/to/bids/dir /path/to/output/dir participant -np
Run the app, using all cores:
snakedwi /path/to/bids/dir /path/to/output/dir participant --cores all
If any workflow rules require containers, then run with the --use-singularity
option.
Generating a report
After your processing is complete, you can use snakemake’s --report
feature to generate
an HTML report. This report will include a graph of all the jobs run, with clickable nodes
to inspect the shell command or python code used in each job, along with the config files and
run times for each job. Workflows may also contain append images for quality assurance or to
summarize outputs, by using the report(...)
function on any snakemake output.
To generate a report, run:
snakedwi /path/to/bids/dir /path/to/output/dir participant --report
Compute Canada Instructions
Setting up a dev environment
Here are some instructions to get your python environment set-up on graham to run snakedwi:
Create a virtualenv and activate it:
cd $SCRATCH module load python/3 virtualenv venv_snakedwi source venv_snakedwi/bin/activate
Follow the steps above to install from github repository
Install job submission helpers
Snakemake can submit jobs with SLURM, but you need to set-up a Snakemake profile to enable this. The Khan lab has a snakemake profile that is configured for graham but is customizable upon install, please see cc-slurm for more info.
If you don’t need Snakemake to parallelize jobs across different nodes, you can make use of the simple job submission wrappers in neuroglia-helpers, e.g. regularSubmit
or regularInteractive
wrappers.
These are used in the instructions below.
Running jobs on Compute Canada
In an interactive job (for testing):
regularInteractive -n 8
snakedwi bids_dir out_dir participant --participant_label 001 -j 8
Submitting a job (for larger cores, more subjects), still single job, but snakemake will parallelize over the 32 cores:
regularSubmit -j Fat snakedwi bids_dir out_dir participant -j 32
Scaling up to ~hundred subjects (needs cc-slurm snakemake profile installed), submits 1 16core job per subject:
snakedwi bids_dir out_dir participant --profile cc-slurm
Scaling up to even more subjects (uses group-components to bundle multiple subjects in each job), 1 32core job for N subjects (e.g. 10):
snakedwi bids_dir out_dir participant --profile cc-slurm --group-components subj=10