temp (Sourcery refactored)

[sourcery-ai[bot]]

Pull Request #4 refactored by Sourcery.

If you're happy with these changes, merge this Pull Request using the Squash and merge strategy.

NOTE: As code is pushed to the original Pull Request, Sourcery will re-run and update (force-push) this Pull Request with new refactorings as necessary. If Sourcery finds no refactorings at any point, this Pull Request will be closed automatically.

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[ghost]

Review on Crocodile

[github-actions[bot]]

👋 @sourcery-ai[bot] Thanks for creating a PR!

Until this PR is ready for review, you can include the [WIP] tag in its title, or leave it as a github draft.

Please make sure it is compliant with our contributing guidelines. In particular, be sure it checks the boxes listed below.

• [ ] PR has an interpretable title.
• [ ] PR links to Github issue with mention "Closes #XXXX"
• [ ] Code is PEP8-compliant.
• [ ] Changelog or what's new entry in "doc/changes/latest.rst"
• [ ] (Bug fixes) There is at least one test that would fail under the original bug conditions.
• [ ] (New features) There is at least one unit test per new function / class.
• [ ] (New features) The new feature is demoed in at least one relevant example.

We will review it as quick as possible, feel free to ping us with questions if needed.

[sourcery-ai[bot]]

Sourcery Code Quality Report

✅  Merging this PR will increase code quality in the affected files by 0.45%.

Quality metrics	Before	After	Change
Complexity	14.95 🙂	14.27 🙂	-0.68 👍
Method Length	145.04 😞	144.66 😞	-0.38 👍
Working memory	14.13 😞	14.09 😞	-0.04 👍
Quality	47.72% 😞	48.17% 😞	0.45% 👍

Other metrics	Before	After	Change
Lines	7466	7419	-47

Changed files	Quality Before	Quality After	Quality Change
nilearn/decoding/decoder.py	41.38% 😞	42.33% 😞	0.95% 👍
nilearn/decoding/fista.py	14.04% ⛔	14.61% ⛔	0.57% 👍
nilearn/decoding/objective_functions.py	77.37% ⭐	77.43% ⭐	0.06% 👍
nilearn/decoding/proximal_operators.py	29.18% 😞	30.36% 😞	1.18% 👍
nilearn/decoding/searchlight.py	60.42% 🙂	62.10% 🙂	1.68% 👍
nilearn/decoding/space_net.py	35.48% 😞	36.57% 😞	1.09% 👍
nilearn/decoding/space_net_solvers.py	60.45% 🙂	61.11% 🙂	0.66% 👍
nilearn/decoding/tests/simulate_graph_net_data.py	41.96% 😞	42.00% 😞	0.04% 👍
nilearn/decoding/tests/test_decoder.py	57.24% 🙂	57.28% 🙂	0.04% 👍
nilearn/decoding/tests/test_same_api.py	65.32% 🙂	65.46% 🙂	0.14% 👍
nilearn/glm/second_level/second_level.py	49.07% 😞	49.56% 😞	0.49% 👍
nilearn/glm/tests/test_second_level.py	60.96% 🙂	60.94% 🙂	-0.02% 👎
nilearn/glm/tests/test_utils.py	71.24% 🙂	71.77% 🙂	0.53% 👍
nilearn/mass_univariate/permuted_least_squares.py	3.57% ⛔	3.61% ⛔	0.04% 👍

Here are some functions in these files that still need a tune-up:

File	Function	Complexity	Length	Working Memory	Quality	Recommendation
nilearn/mass_univariate/permuted_least_squares.py	permuted_ols	84 ⛔	1371 ⛔	30 ⛔	1.30% ⛔	Refactor to reduce nesting. Try splitting into smaller methods. Extract out complex expressions
nilearn/decoding/proximal_operators.py	_prox_tvl1	45 ⛔	473 ⛔	28 ⛔	6.04% ⛔	Refactor to reduce nesting. Try splitting into smaller methods. Extract out complex expressions
nilearn/decoding/space_net.py	path_scores	36 ⛔	549 ⛔	37 ⛔	7.48% ⛔	Refactor to reduce nesting. Try splitting into smaller methods. Extract out complex expressions
nilearn/decoding/fista.py	mfista	38 ⛔	423 ⛔	29 ⛔	8.27% ⛔	Refactor to reduce nesting. Try splitting into smaller methods. Extract out complex expressions
nilearn/decoding/space_net.py	BaseSpaceNet.fit	35 ⛔	834 ⛔	28 ⛔	8.49% ⛔	Refactor to reduce nesting. Try splitting into smaller methods. Extract out complex expressions

Legend and Explanation

The emojis denote the absolute quality of the code:

• ⭐ excellent
• 🙂 good
• 😞 poor
• ⛔ very poor

The 👍 and 👎 indicate whether the quality has improved or gotten worse with this pull request.

---

Please see our documentation here for details on how these metrics are calculated.

We are actively working on this report - lots more documentation and extra metrics to come!

Help us improve this quality report!

[codecov-commenter]

Codecov Report

Merging #5 (5d62018) into formatting (2ee9bc1) will increase coverage by 0.05%. The diff coverage is 83.05%.

@@              Coverage Diff               @@
##           formatting       #5      +/-   ##
==============================================
+ Coverage       91.00%   91.05%   +0.05%     
==============================================
  Files             133      133              
  Lines           15356    15322      -34     
  Branches         3033     3015      -18     
==============================================
- Hits            13975    13952      -23     
+ Misses            817      813       -4     
+ Partials          564      557       -7     

Impacted Files	Coverage Δ
nilearn/decoding/fista.py	87.65% <20.00%> (ø)
nilearn/decoding/objective_functions.py	88.60% <66.66%> (+2.02%)	:arrow_up:
nilearn/decoding/proximal_operators.py	71.96% <66.66%> (+0.14%)	:arrow_up:
nilearn/decoding/space_net.py	88.23% <82.35%> (+0.01%)	:arrow_up:
nilearn/glm/second_level/second_level.py	97.52% <95.00%> (+0.29%)	:arrow_up:
nilearn/decoding/decoder.py	96.65% <100.00%> (+0.68%)	:arrow_up:
nilearn/decoding/searchlight.py	96.00% <100.00%> (+2.25%)	:arrow_up:
nilearn/decoding/space_net_solvers.py	98.02% <100.00%> (-0.04%)	:arrow_down:
nilearn/mass_univariate/permuted_least_squares.py	91.28% <100.00%> (+0.82%)	:arrow_up:

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