✨ Add clp guidance megacomplex (Sourcery refactored)

[sourcery-ai]

Pull Request #1029 refactored by Sourcery.

Since the original Pull Request was opened as a fork in a contributor's
repository, we are unable to create a Pull Request branching from it.

To incorporate these changes, you can either:

1. Merge this Pull Request instead of the original, or

2. Ask your contributor to locally incorporate these commits and push them to
   the original Pull Request

   Incorporate changes via command line

   git fetch https://github.com/glotaran/pyglotaran pull/1029/head
   git merge --ff-only FETCH_HEAD
   git push

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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[github-actions]

👈 Launch a binder notebook on branch glotaran/pyglotaran/sourcery/pull-1029

[sourcery-ai]

Sourcery Code Quality Report

❌  Merging this PR will decrease code quality in the affected files by 0.78%.

Quality metrics	Before	After	Change
Complexity	3.80 ⭐	4.01 ⭐	0.21 👎
Method Length	50.68 ⭐	51.19 ⭐	0.51 👎
Working memory	6.85 🙂	7.16 🙂	0.31 👎
Quality	73.12% 🙂	72.34% 🙂	-0.78% 👎

Other metrics	Before	After	Change
Lines	2008	2147	139

Changed files	Quality Before	Quality After	Quality Change
glotaran/analysis/optimization_group.py	73.02% 🙂	72.70% 🙂	-0.32% 👎
glotaran/builtin/megacomplexes/decay/test/test_decay_megacomplex.py	54.89% 🙂	54.89% 🙂	0.00%
glotaran/model/dataset_model.py	80.93% ⭐	73.28% 🙂	-7.65% 👎
glotaran/model/megacomplex.py	74.48% 🙂	73.97% 🙂	-0.51% 👎
glotaran/model/model.py	70.83% 🙂	70.74% 🙂	-0.09% 👎
glotaran/model/test/test_model.py	72.68% 🙂	72.44% 🙂	-0.24% 👎
glotaran/project/result.py	76.82% ⭐	76.91% ⭐	0.09% 👍
glotaran/project/test/test_result.py	82.73% ⭐	83.23% ⭐	0.50% 👍

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

File	Function	Complexity	Length	Working Memory	Quality	Recommendation
glotaran/model/dataset_model.py	DatasetModel.ensure_unique_megacomplexes	14 🙂	104 🙂	15 😞	47.35% 😞	Extract out complex expressions
glotaran/project/result.py	Result.markdown	7 ⭐	186 😞	13 😞	47.42% 😞	Try splitting into smaller methods. Extract out complex expressions
glotaran/analysis/optimization_group.py	OptimizationGroup._add_weight	15 🙂	134 😞	11 😞	48.74% 😞	Try splitting into smaller methods. Extract out complex expressions
glotaran/model/model.py	Model.markdown	13 🙂	168 😞	10 😞	48.74% 😞	Try splitting into smaller methods. Extract out complex expressions
glotaran/model/model.py	Model.from_dict	12 🙂	162 😞	10 😞	50.19% 🙂	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!

[sonarqubecloud]

Kudos, SonarCloud Quality Gate passed!   

0 Bugs
0 Vulnerabilities
0 Security Hotspots
3 Code Smells

No Coverage information
0.0% Duplication

[github-actions]

Benchmark is done. Checkout the benchmark result page.
Benchmark differences below 5% might be due to CI noise.

Benchmark diff v0.5.1 vs. main

Parametrized benchmark signatures:

BenchmarkOptimize.time_optimize(index_dependent, grouped, weight)

All benchmarks:

       before           after         ratio
     [96b42630]       [628d8b20]
     <v0.5.1>                   
       53.7±0.3ms       52.7±0.4ms     0.98  BenchmarkOptimize.time_optimize(False, False, False)
        58.7±30ms       57.0±0.3ms     0.97  BenchmarkOptimize.time_optimize(False, False, True)
       53.5±0.1ms       53.1±0.2ms     0.99  BenchmarkOptimize.time_optimize(False, True, False)
       57.8±0.5ms         57.3±1ms     0.99  BenchmarkOptimize.time_optimize(False, True, True)
       65.4±0.2ms       64.6±0.5ms     0.99  BenchmarkOptimize.time_optimize(True, False, False)
         101±40ms        69.2±30ms    ~0.68  BenchmarkOptimize.time_optimize(True, False, True)
       65.3±0.4ms       65.0±0.4ms     1.00  BenchmarkOptimize.time_optimize(True, True, False)
        71.8±30ms        68.5±30ms     0.95  BenchmarkOptimize.time_optimize(True, True, True)
             203M             205M     1.01  IntegrationTwoDatasets.peakmem_optimize
       1.82±0.03s       1.67±0.03s     0.92  IntegrationTwoDatasets.time_optimize

Benchmark diff main vs. PR

Parametrized benchmark signatures:

BenchmarkOptimize.time_optimize(index_dependent, grouped, weight)

All benchmarks:

       before           after         ratio
     [d15d9bd3]       [628d8b20]
       53.1±0.3ms       52.7±0.4ms     0.99  BenchmarkOptimize.time_optimize(False, False, False)
        65.4±30ms       57.0±0.3ms    ~0.87  BenchmarkOptimize.time_optimize(False, False, True)
       53.0±0.3ms       53.1±0.2ms     1.00  BenchmarkOptimize.time_optimize(False, True, False)
      56.8±0.08ms         57.3±1ms     1.01  BenchmarkOptimize.time_optimize(False, True, True)
       65.1±0.7ms       64.6±0.5ms     0.99  BenchmarkOptimize.time_optimize(True, False, False)
       68.5±0.5ms        69.2±30ms     1.01  BenchmarkOptimize.time_optimize(True, False, True)
       64.9±0.4ms       65.0±0.4ms     1.00  BenchmarkOptimize.time_optimize(True, True, False)
         110±30ms        68.5±30ms    ~0.62  BenchmarkOptimize.time_optimize(True, True, True)
             204M             205M     1.00  IntegrationTwoDatasets.peakmem_optimize
       1.67±0.03s       1.67±0.03s     1.00  IntegrationTwoDatasets.time_optimize

[codecov]

Codecov Report

Attention: Patch coverage is 89.39394% with 7 lines in your changes missing coverage. Please review.

Project coverage is 85.9%. Comparing base (d15d9bd) to head (628d8b2).
Report is 245 commits behind head on main.

Files	Patch %	Lines
glotaran/project/result.py	42.8%	2 Missing and 2 partials ⚠️
glotaran/model/dataset_model.py	93.7%	0 Missing and 2 partials ⚠️
glotaran/model/model.py	75.0%	0 Missing and 1 partial ⚠️

Additional details and impacted files

@@          Coverage Diff          @@
##            main   #1031   +/-   ##
=====================================
  Coverage   85.9%   85.9%           
=====================================
  Files         92      94    +2     
  Lines       4972    5023   +51     
  Branches     937     946    +9     
=====================================
+ Hits        4272    4318   +46     
- Misses       552     554    +2     
- Partials     148     151    +3     

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[s-weigand]

Hmmm, guess changing the title of the original PR dislinked this PR from it.