Float32 RawArray?

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#10,274 6 comments 0 reactions 0 assignees View on GitHub

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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

ENH
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:

  1. Data is in main memory, float32 for saving main memory
  2. 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
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Forks
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Avg merge
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Merged PRs (30d)
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