Float32 RawArray?
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 35/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- python
- Domain
- data, performance
Research direction
Start by tracing the RawArray creation path and inspect how the underlying _data dtype is enforced across processing functions. Review the existing six-comment discussion before defining scope; done would require an agreed approach for float32 support and clear compatibility and memory or storage criteria.
Written by the indexing model from the issue text.
Description
Describe the new feature or enhancement
float32 rawarray
Describe your proposed implementation
dtype argument on creating rawarray
Additional comments
At the moment we are looking into potential memory savings when using mne for braindecode. We noticed the underlying _data of a RawArray is forced to be float32, and were wondering if it is realistic that mne also offers float32. Or is float64 too fundamental for mne/too many interactions with processing functions? Concretely, we would prefer float32 for two scenarios:
- Data is in main memory, float32 for saving main memory
- Data is stored on disk and loaded on the fly, float32 for faster storing and loading as well as saving hard disk space and main memory after load
Also other ideas what to do in those scenarios are appreciated.
- Dominant language
- Python
- Stars
- 3.5k
- Forks
- 1.6k
- Avg merge
- 1d 6h
- Merged PRs (30d)
- 100
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.
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