🩹 Fix save_result crashes on Windows if input data are on a different drive than result

[s-weigand]

This fixes the crash of save_result when the original data and the result path are on different drives on windows.

The commit e431760 is optional.

Change summary

• 🩹 Made 'relative_posix_path' more stable on windows
  - ♻️ Changed save_result folder to use the result.data for scheme.data

Checklist

• ✔️ Passing the tests (mandatory for all PR's)
• 👌 Closes issue (mandatory for ✨ feature and 🩹 bug fix PR's)

Closes issues

closes #924

[github-actions]

👈 Launch a binder notebook on branch s-weigand/pyglotaran/fix-save_result-win-driff-drives

[github-actions]

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

Benchmark diff v0.5.0 vs. main

Parametrized benchmark signatures:

BenchmarkOptimize.time_optimize(index_dependent, grouped, weight)

All benchmarks:

       before           after         ratio
     [89046e0a]       [46859f47]
     <v0.5.0>                   
       48.2±0.9ms         50.3±3ms     1.04  BenchmarkOptimize.time_optimize(False, False, False)
         50.8±1ms         54.6±4ms     1.08  BenchmarkOptimize.time_optimize(False, False, True)
       47.7±0.2ms         53.2±4ms    ~1.12  BenchmarkOptimize.time_optimize(False, True, False)
         51.9±1ms         55.9±5ms     1.08  BenchmarkOptimize.time_optimize(False, True, True)
         56.9±1ms         65.0±7ms    ~1.14  BenchmarkOptimize.time_optimize(True, False, False)
        65.1±40ms        79.5±30ms    ~1.22  BenchmarkOptimize.time_optimize(True, False, True)
         56.7±1ms         66.9±5ms    ~1.18  BenchmarkOptimize.time_optimize(True, True, False)
        63.1±40ms        71.8±50ms    ~1.14  BenchmarkOptimize.time_optimize(True, True, True)
             188M             190M     1.01  IntegrationTwoDatasets.peakmem_optimize
       1.77±0.02s       1.73±0.06s     0.98  IntegrationTwoDatasets.time_optimize

Benchmark diff main vs. PR

Parametrized benchmark signatures:

BenchmarkOptimize.time_optimize(index_dependent, grouped, weight)

All benchmarks:

       before           after         ratio
     [89046e0a]       [46859f47]
     <v0.5.0>                   
       48.2±0.9ms         50.3±3ms     1.04  BenchmarkOptimize.time_optimize(False, False, False)
         50.8±1ms         54.6±4ms     1.08  BenchmarkOptimize.time_optimize(False, False, True)
       47.7±0.2ms         53.2±4ms    ~1.12  BenchmarkOptimize.time_optimize(False, True, False)
         51.9±1ms         55.9±5ms     1.08  BenchmarkOptimize.time_optimize(False, True, True)
         56.9±1ms         65.0±7ms    ~1.14  BenchmarkOptimize.time_optimize(True, False, False)
        65.1±40ms        79.5±30ms    ~1.22  BenchmarkOptimize.time_optimize(True, False, True)
         56.7±1ms         66.9±5ms    ~1.18  BenchmarkOptimize.time_optimize(True, True, False)
        63.1±40ms        71.8±50ms    ~1.14  BenchmarkOptimize.time_optimize(True, True, True)
             188M             190M     1.01  IntegrationTwoDatasets.peakmem_optimize
       1.77±0.02s       1.73±0.06s     0.98  IntegrationTwoDatasets.time_optimize

[codecov]

Codecov Report

Merging #931 (46859f4) into main (89046e0) will increase coverage by 0.0%.
The diff coverage is 100.0%.

@@          Coverage Diff          @@
##            main    #931   +/-   ##
=====================================
  Coverage   85.1%   85.1%           
=====================================
  Files         85      85           
  Lines       4796    4799    +3     
  Branches     921     921           
=====================================
+ Hits        4082    4085    +3     
  Misses       562     562           
  Partials     152     152           

Impacted Files	Coverage Δ
glotaran/utils/io.py	100.0% <100.0%> (ø)

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[joernweissenborn]

Using result.data will crash in future.

[s-weigand]

I dropped e431760 since it causes the examples to fail when reoptimizing a result for some reason.
Since the result contains the original data, this needs some more investigation!

[jsnel]

Some typos to correct and suggest to do some sanity investigation on the other platforms we target.

[sourcery-ai]

Sourcery Code Quality Report

✅  Merging this PR will increase code quality in the affected files by 0.56%.

Quality metrics	Before	After	Change
Complexity	2.30 ⭐	2.33 ⭐	0.03 👎
Method Length	51.70 ⭐	51.14 ⭐	-0.56 👍
Working memory	6.79 🙂	6.69 🙂	-0.10 👍
Quality	74.71% 🙂	75.27% ⭐	0.56% 👍

Other metrics	Before	After	Change
Lines	309	324	15

Changed files	Quality Before	Quality After	Quality Change
glotaran/utils/io.py	75.08% ⭐	75.10% ⭐	0.02% 👍
glotaran/utils/test/test_io.py	74.50% 🙂	75.36% ⭐	0.86% 👍

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

File	Function	Complexity	Length	Working Memory	Quality	Recommendation
glotaran/utils/io.py	_load_datasets	15 🙂	156 😞	12 😞	44.60% 😞	Try splitting into smaller methods. Extract out complex expressions
glotaran/utils/test/test_io.py	test_load_datasets_single_dataset	0 ⭐	208 ⛔	7 🙂	64.44% 🙂	Try splitting into smaller methods

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
0 Code Smells

No Coverage information
1.5% Duplication