Distributed Convolution via FFT

[LScheib]

Due Diligence

• General:
  • [ ] base branch must be main for new features, latest release branch (e.g. release/1.3.x) for bug fixes
  • [ ] title of the PR is suitable to appear in the Release Notes
• Implementation:
  • [ ] unit tests: all split configurations tested
  • [ ] unit tests: multiple dtypes tested
  • [ ] documentation updated where needed

Description

Issue/s resolved: #1248

Changes proposed:

Type of change

Memory requirements

Performance

Does this change modify the behaviour of other functions? If so, which?

yes / no

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[github-actions[bot]]

Thank you for the PR!

[codecov[bot]]

Codecov Report

Attention: 87 lines in your changes are missing coverage. Please review.

Comparison is base (02028b9) 91.81% compared to head (38d9fc7) 87.34%. Report is 3 commits behind head on main.

:exclamation: Current head 38d9fc7 differs from pull request most recent head be025ad. Consider uploading reports for the commit be025ad to get more accurate results

Files	Patch %	Lines
heat/core/signal.py	13.00%	87 Missing :warning:

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1291      +/-   ##
==========================================
- Coverage   91.81%   87.34%   -4.48%     
==========================================
  Files          79       79              
  Lines       11463    11559      +96     
==========================================
- Hits        10525    10096     -429     
- Misses        938     1463     +525     

Flag	Coverage Δ
unit	87.34% <13.00%> (-4.48%)	:arrow_down:

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[github-actions[bot]]

Thank you for the PR!

[mrfh92]

After a first quick look, this looks very good :+1: Depending on how close your implementation follows the one in SciPy, we should probably add a citation (sth like "Our implementation closely follows the one of fftconvolve in SciPy; see [link]...")

[github-actions[bot]]

Thank you for the PR!

[github-actions[bot]]

Thank you for the PR!