🩹 Fix pretty_format_numerical for negative values

[s-weigand]

While working on the extras I discovered that I implemented pretty_format_numerical with a stupid bug that breaks it's functionality when confronted with negative values (not to myself use abs when comparing absolute values 🤦‍♀️).
We didn't encounter it because:
a) It is only used for t-values
b) The unit tests for it only used positive numbers (100% line coverage != bug free)🤦‍♀️

Change summary

• 🩹 Fix pretty_format_numerical for negative values
• 👌 Special treat int and values that are a machine epsilon close to int
• 🩹 Fix handeling inf nan and inf values

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)

[sourcery-ai]

Sourcery Code Quality Report

❌  Merging this PR will decrease code quality in the affected files by 0.98%.

Quality metrics	Before	After	Change
Complexity	7.05 ⭐	7.12 ⭐	0.07 👎
Method Length	49.44 ⭐	54.94 ⭐	5.50 👎
Working memory	6.65 🙂	6.66 🙂	0.01 👎
Quality	75.62% ⭐	74.64% 🙂	-0.98% 👎

Other metrics	Before	After	Change
Lines	295	314	19

Changed files	Quality Before	Quality After	Quality Change
glotaran/utils/sanitize.py	72.42% 🙂	71.71% 🙂	-0.71% 👎
glotaran/utils/test/test_sanitize.py	87.86% ⭐	86.52% ⭐	-1.34% 👎

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

File	Function	Complexity	Length	Working Memory	Quality	Recommendation
glotaran/utils/sanitize.py	sanitize_dict_values	20 😞	95 🙂	9 🙂	53.85% 🙂	Refactor to reduce nesting
glotaran/utils/sanitize.py	sanitize_dict_keys	12 🙂	93 🙂	10 😞	58.47% 🙂	Extract out complex expressions

Legend and Explanation

The emojis denote the absolute quality of the code:

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• 🙂 good
• 😞 poor
• ⛔ very poor

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

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

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[github-actions]

👈 Launch a binder notebook on branch s-weigand/pyglotaran/fix-pretty_format_numerical

[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]       [14afaff3]
     <v0.6.0>                   
!      45.8±0.2ms           failed      n/a  BenchmarkOptimize.time_optimize(False, False, False)
!      48.0±0.4ms           failed      n/a  BenchmarkOptimize.time_optimize(False, False, True)
!      45.6±0.4ms           failed      n/a  BenchmarkOptimize.time_optimize(False, True, False)
!      47.9±0.3ms           failed      n/a  BenchmarkOptimize.time_optimize(False, True, True)
!      55.7±0.4ms           failed      n/a  BenchmarkOptimize.time_optimize(True, False, False)
!        67.4±5ms           failed      n/a  BenchmarkOptimize.time_optimize(True, False, True)
!      55.3±0.4ms           failed      n/a  BenchmarkOptimize.time_optimize(True, True, False)
!        63.4±3ms           failed      n/a  BenchmarkOptimize.time_optimize(True, True, True)
             205M             207M     1.01  IntegrationTwoDatasets.peakmem_optimize
-      1.91±0.05s       1.01±0.02s     0.53  IntegrationTwoDatasets.time_optimize

Benchmark diff main vs. PR

Parametrized benchmark signatures:

BenchmarkOptimize.time_optimize(index_dependent, grouped, weight)

All benchmarks:

       before           after         ratio
     [14afaff3]       [ba7ab9fc]
           failed           failed      n/a  BenchmarkOptimize.time_optimize(False, False, False)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(False, False, True)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(False, True, False)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(False, True, True)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(True, False, False)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(True, False, True)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(True, True, False)
           failed           failed      n/a  BenchmarkOptimize.time_optimize(True, True, True)
             207M             207M     1.00  IntegrationTwoDatasets.peakmem_optimize
       1.01±0.02s       1.01±0.03s     1.00  IntegrationTwoDatasets.time_optimize

[codecov]

Codecov Report

Base: 87.6% // Head: 87.6% // Increases project coverage by +0.0% 🎉

Coverage data is based on head (ba7ab9f) compared to base (14afaff).
Patch coverage: 100.0% of modified lines in pull request are covered.

Additional details and impacted files

@@          Coverage Diff          @@
##            main   #1192   +/-   ##
=====================================
  Coverage   87.6%   87.6%           
=====================================
  Files        104     104           
  Lines       4954    4959    +5     
  Branches     821     823    +2     
=====================================
+ Hits        4344    4349    +5     
  Misses       493     493           
  Partials     117     117           

Impacted Files	Coverage Δ
glotaran/utils/sanitize.py	64.9% <100.0%> (+2.4%)	⬆️

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[sonarqubecloud]

Kudos, SonarCloud Quality Gate passed!   

0 Bugs
0 Vulnerabilities
0 Security Hotspots
0 Code Smells

No Coverage information
0.0% Duplication