Paradigm for "cropped" epoching
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- Dominant language
- Python
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Description
Implementing a paradigm that allows doing a "cropped" epoching (in the sense of braindecode: https://braindecode.org/stable/auto_examples/plot_bcic_iv_2a_moabb_cropped.html) would be relatively simple with the new modular paradigms. We would just need to implement a new processing step that computes events from raw objects (i.e. similar to RawToEvents and RawToFixedIntervalEvents).
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the existing RawToEvents and RawToFixedIntervalEvents processing steps and how modular paradigms invoke them. Add a processing step that computes cropped-epoch events from raw objects, with completion indicated by the new paradigm supporting the braindecode-style cropped epoching behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100