Diffusion neural network
cd
to the directory, and
conda env create -f environment.yml
on a local machine andconda env create -f environment_cbica.yml
on the CBICA cluster.conda
, visit anaconda.com.conda activate dnn
for a local machine and conda activate dnn-cbica
on the cluster.dnn
directory as a project.dataset/hcp/res/hcp_covariates.csv
. ~/.aws/credentials
in you home folder with conents
[default]
aws_access_key_id = (your HCP access key here)
aws_secret_access_key = (your HCP secret access key here)
aws configure
.dataset/hcp/dti/scripts/conf/subjects.txt
.python schedule (local/debug/cbica_cpu) dataset/hcp/dti/scripts/conf/args.ini
.
~/.dnn/datasets/hcp
, accessible from your home folder./cbica/home/beckerc/.dnn/datasets/hcp/processing
. Set local_processing_directory
in your .ini
experiment configuration file in experiments/hcp/conf
.arg.ini
file describing your experiment.python schedule (local/debug/cbica_cpu/cbica_gpu) experiments/hcp/conf/args.ini
.
experiments/hcp/conf/(test|train)_subjects.txt
.
See README.md on dataset/synth.