Resolve deprecations

[SebastianSchmidl]

We use some outdated features of scipy and jsonschema. We should fix the deprecation warnings to stay up-to-date with the libraries in future versions:

=============================== warnings summary ===============================
gutenTAG/config/validator.py:4
gutenTAG/config/validator.py:4
  /home/runner/work/GutenTAG/GutenTAG/gutenTAG/config/validator.py:4: DeprecationWarning: jsonschema.RefResolver is deprecated as of v4.18.0, in favor of the https://github.com/python-jsonschema/referencing library, which provides more compliant referencing behavior as well as more flexible APIs for customization. A future release will remove RefResolver. Please file a feature request (on referencing) if you are missing an API for the kind of customization you need.
    from jsonschema import RefResolver

tests/test_addons.py: 1 warning
tests/test_integration/test_anomaly_types.py: 1 warning
tests/test_integration/test_base_oscillations.py: 2 warnings
tests/test_integration/test_benchmark_generation.py: 317 warnings
tests/test_seeding.py: 6 warnings
  /usr/share/miniconda/envs/test/lib/python3.13/site-packages/neurokit2/ecg/ecg_simulate.py:1[30](https://github.com/TimeEval/GutenTAG/actions/runs/14909896278/job/41881384447#step:5:31): DeprecationWarning: Please import `daub` from the `scipy.signal` namespace; the `scipy.signal.wavelets` namespace is deprecated and will be removed in SciPy 2.0.0.
    cardiac = scipy.signal.wavelets.daub(10)

tests/test_addons.py: 1 warning
tests/test_integration/test_anomaly_types.py: 1 warning
tests/test_integration/test_base_oscillations.py: 2 warnings
tests/test_integration/test_benchmark_generation.py: [31](https://github.com/TimeEval/GutenTAG/actions/runs/14909896278/job/41881384447#step:5:32)7 warnings
tests/test_seeding.py: 6 warnings
  /usr/share/miniconda/envs/test/lib/python3.13/site-packages/neurokit2/ecg/ecg_simulate.py:130: DeprecationWarning: scipy.signal.daub is deprecated in SciPy 1.12 and will be removed
  in SciPy 1.15. We recommend using PyWavelets instead.
  
    cardiac = scipy.signal.wavelets.daub(10)