tektronix / tektronix/tm_data_types
[FEAT]: Investigate using np.shift_left/np.shift_right and np.view instead of using multiplication and offset
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- Dominant language
- Python
- Stars
- 8
- Forks
- 14
- Avg merge
- 3d 10h
- Merged PRs (30d)
- 4
Description
Description
currently converting between types using the RawSample type uses multiplication and addition to convert between uint and int and float. This could probably be done faster using shift_left/shift_right and view
Additional Information
This would only be applicable from integer to integer conversion, as integer to float does not work by using bit shift
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 locating the RawSample type conversions and examining how integer-to-integer, integer-to-float, and float conversions currently use multiplication and addition. Investigate NumPy shift_left, shift_right, and view for the integer-only case; done means the applicable conversions use the proposed operations without changing integer-to-float behavior, with performance checked.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- numpy, python
- Domain
- data, performance
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100