QuantEcon / QuantEcon/QuantEcon.py

[Update] ``Cartesian`` Module

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enhancement performance
Dominant language
Python
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Forks
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Avg merge
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Merged PRs (30d)
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Description

Review cartesian module and update as required:

  • line_profile to see if further numbafication is useful or not

Current discussion from @albop:
@oyamad , @mmcky : On the cartesian function, the reasoning was that the loops and list comprehensions are made over the number of dimensions, so that they are probably only a few iterations. Appart from the loop over _repeat_1d, it seems likely that everything else is going to stay in python mode, with little performance gain if any. This was just my feeling though, I didn't test it.

  • update so that numba isn't an explicit requirement (numpy version?)
  • Incorporate Issue #98

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reading the cartesian module, especially line_profile, and review the discussion about loop performance and numba. Check Issue #98 and identify the current numba requirement. Done means resolving the checklist items: deciding whether numba helps, removing its explicit requirement if appropriate, and incorporating Issue #98.

Written by the indexing model from the issue text.

Assessment

Tech stack
numpy, python
Domain
backend
Issue type
Refactor
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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