🩹 Fix result data overwritten when using multiple dataset_groups

[s-weigand]

This fixes a bug when using multiple dataset_groups, where each OptimizationGroup (one per dataset_group) overwrites previous results from different dataset_group with the input data.

Change summary

• 🧪 Extended test reproducing overwriting existing result dataset
• 🩹 Filter datasets in create_result_data.create_result_data to used ones

Checklist

• ✔️ Passing the tests (mandatory for all PR's)
• 🚧 Added changes to changelog (mandatory for all PR's)
• 🧪 Adds new tests for the feature (mandatory for ✨ feature and 🩹 bug fix PR's)

[github-actions]

👈 Launch a binder notebook on branch s-weigand/pyglotaran/fix-result-data-overwrite-multiple-groups

[sourcery-ai]

Sourcery Code Quality Report

❌  Merging this PR will decrease code quality in the affected files by 0.77%.

Quality metrics	Before	After	Change
Complexity	6.36 ⭐	6.48 ⭐	0.12 👎
Method Length	95.80 🙂	98.80 🙂	3.00 👎
Working memory	9.25 🙂	9.27 🙂	0.02 👎
Quality	58.26% 🙂	57.49% 🙂	-0.77% 👎

Other metrics	Before	After	Change
Lines	256	264	8

Changed files	Quality Before	Quality After	Quality Change
glotaran/optimization/optimization_group.py	59.12% 🙂	58.95% 🙂	-0.17% 👎
glotaran/optimization/test/test_multiple_goups.py	54.83% 🙂	52.52% 🙂	-2.31% 👎

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

File	Function	Complexity	Length	Working Memory	Quality	Recommendation
glotaran/optimization/optimization_group.py	OptimizationGroup.create_result_data	12 🙂	277 ⛔	12 😞	38.91% 😞	Try splitting into smaller methods. Extract out complex expressions
glotaran/optimization/test/test_multiple_goups.py	test_multiple_groups	4 ⭐	228 ⛔	10 😞	52.52% 🙂	Try splitting into smaller methods. Extract out complex expressions
glotaran/optimization/optimization_group.py	OptimizationGroup.__init__	6 ⭐	152 😞	10 😞	56.78% 🙂	Try splitting into smaller methods. Extract out complex expressions

Legend and Explanation

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

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[sonarqubecloud]

Kudos, SonarCloud Quality Gate passed!   

0 Bugs
0 Vulnerabilities
0 Security Hotspots
0 Code Smells

No Coverage information
0.8% Duplication

[github-actions]

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

Benchmark diff v0.6.0 vs. main

Parametrized benchmark signatures:

BenchmarkOptimize.time_optimize(index_dependent, grouped, weight)

All benchmarks:

       before           after         ratio
     [6c3c390e]       [69bb7dc0]
     <v0.6.0>                   
+      62.8±0.3ms          107±1ms     1.71  BenchmarkOptimize.time_optimize(False, False, False)
        67.4±30ms          128±1ms    ~1.90  BenchmarkOptimize.time_optimize(False, False, True)
+        62.0±1ms        106±0.8ms     1.71  BenchmarkOptimize.time_optimize(False, True, False)
         65.6±2ms          127±1ms    ~1.94  BenchmarkOptimize.time_optimize(False, True, True)
+      74.1±0.5ms        183±0.7ms     2.48  BenchmarkOptimize.time_optimize(True, False, False)
+       78.7±30ms        204±0.9ms     2.59  BenchmarkOptimize.time_optimize(True, False, True)
+        74.0±3ms          185±1ms     2.50  BenchmarkOptimize.time_optimize(True, True, False)
+       78.8±40ms        204±0.7ms     2.59  BenchmarkOptimize.time_optimize(True, True, True)
             201M             209M     1.04  IntegrationTwoDatasets.peakmem_optimize
-      1.96±0.07s       1.62±0.06s     0.82  IntegrationTwoDatasets.time_optimize

Benchmark diff main vs. PR

Parametrized benchmark signatures:

BenchmarkOptimize.time_optimize(index_dependent, grouped, weight)

All benchmarks:

       before           after         ratio
     [69bb7dc0]       [3dbd9ddf]
          107±1ms        107±0.2ms     1.00  BenchmarkOptimize.time_optimize(False, False, False)
          128±1ms        127±0.8ms     0.99  BenchmarkOptimize.time_optimize(False, False, True)
        106±0.8ms          106±2ms     1.00  BenchmarkOptimize.time_optimize(False, True, False)
          127±1ms          128±1ms     1.00  BenchmarkOptimize.time_optimize(False, True, True)
        183±0.7ms          186±1ms     1.01  BenchmarkOptimize.time_optimize(True, False, False)
        204±0.9ms        205±0.7ms     1.00  BenchmarkOptimize.time_optimize(True, False, True)
          185±1ms        185±0.7ms     1.00  BenchmarkOptimize.time_optimize(True, True, False)
        204±0.7ms          205±2ms     1.01  BenchmarkOptimize.time_optimize(True, True, True)
             209M             209M     1.00  IntegrationTwoDatasets.peakmem_optimize
       1.62±0.06s       1.64±0.03s     1.01  IntegrationTwoDatasets.time_optimize

[joernweissenborn]

Lgtm

[codecov]

Codecov Report

Base: 87.2% // Head: 87.2% // No change to project coverage 👍

Coverage data is based on head (3dbd9dd) compared to base (69bb7dc).
Patch coverage: 100.0% of modified lines in pull request are covered.

Additional details and impacted files

@@          Coverage Diff          @@
##            main   #1147   +/-   ##
=====================================
  Coverage   87.2%   87.2%           
=====================================
  Files        103     103           
  Lines       5274    5274           
  Branches     916     916           
=====================================
  Hits        4599    4599           
  Misses       527     527           
  Partials     148     148           

Impacted Files	Coverage Δ
glotaran/optimization/optimization_group.py	95.2% <100.0%> (ø)

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