A repository for pipeline scripts - including organizing files, prepossessing and analyses
To run some of the code in this repository certain packages requires installation. One way to do that is go one by one - This takes time and also makes the installation applies the whole system in which it is installed. A different approach, is to define dedicated environments (e.g. per project; e.g. for the project of running the pipeline). [Conda] (https://docs.conda.io/en/latest/) allows the definition of such independent environments, and the easy installation of packages in that environment. Conda can be installed on a local PC (your computer) and is already installed and ready to use on the HPC.
Simple script to run and operate python 3.7 in anaconda within the Farnam HPC.
HPC has a specific version of conda called miniconda. The following command "switches conda on" (runs the miniconda module):
module load miniconda &
Many conda environments may exist on a machine (the ones you define). To learn which environments exist on the current machine run:
conda info --env
Activating one of the the existing environments (those listed by conda info --env). With this command you "enter" the specified environment (e.g. you can run python commands that use packages installed in the environment.
source activate [py37_dev] (replace _py37dev with the name of the environment you wish to activate)
Say you have an environment ready with all kinds of packages and you want to share it (with a colleague, or with a publication to assist others with running your code). You can list all the requirements of the current environment by running the command:
conda list
And to save it into a file, e.g. one named requirements.txt, run the command:
conda list -e > requirements.txt
jupyter notebook &
into conda mode
fmriPrep is a builtin pipeline that allow high quality preprocessing (for more information please see here: https://fmriprep.org/en/latest/index.html#)
In the folder fmriPrep you'll find three files.