How-To Guides#
Task-focused recipes for specific EEGDash workflows. Each guide assumes you already know the basics and want a direct answer to a single question – “how do I work offline?”, “how do I parallelise feature extraction?”, “how do I run preprocessing on SLURM?”. Difficulty 1-2; assumes the Start Here trio.
How-to guides sit in the recipe quadrant of the Diataxis framework: not
a curated learning path (those are the tutorials), not a deep
explanation (that is Concepts), not a complete API reference. They
are the answers to the operational questions that come up once you are
running EEGDash for real work. Sourced from
docs/tutorial_restructure_plan.md Category I (lines 615-621 and
1021-1037). Cross-link with the HPC track when relevant.
What you will learn:
How to download a dataset locally and pin it in the cache so reruns do not refetch.
How to parallelise feature extraction across CPU cores using
jobliband EEGDash’s batch helpers.How to run preprocessing as a SLURM array job on a shared cluster (paired with the HPC tutorials).
How to use the HPC cache layout so two jobs on the same cluster share preprocessed data.
How to work fully offline: cache management, manifest export, and reloading without network access.
Each how-to is a single self-contained script or markdown file.
Download an EEGDash dataset in advance and validate the local cache
Place the EEGDash cache on shared or local cluster storage
How-to: work offline against a populated EEGDash cache