Mobgap

Added
- Added a simple way to add performance (as in "time algo needs to run") tracking to algorithms
- Performance values are now reported by the GSD algorithms and the full pipelines via the `perf_` attribute.
- The TVS datasets now have two new columns `{test/recording}_name` and `{test/recording}_name_pretty` that have easier
to read names for the tests and recordings.

Changed
- Swapped out the peak detection per window in GSD Iluz to a custom vectorized one that can be jit compiled.
This provides a 2-3x speedup for large inputs.
- Critical path in GSD-Ionesco is now jit compiled.

For Developers

- We now support adding a `.env` file to the root of the project to set environment variables and have them loaded
automatically when running the tests or examples for the TVS dataset.
When test depend on env vars, use the `mobgap.misc.get_env_var` function to access them.

Changed
- The `calculate_matched_gsd_performance_metrics` function now always return the error metrics that depend on TN
samples, not just when TN samples exist.
This way the output structure is consistent, and we can avoid bugs in scorer functions, where some datapoints might
unexpectedly return a different set of error metrics.
- The official script to aggregate DMOs, now correctly converts stride length values to cm and variance values to cm^2.
Note, that the internal function within mobgap, does not do this conversion automatically, as we use different units
in mobgap internally. If you need to match the official script, you have to do this conversion manually.
see `examples/aggregation/_99_cvs_agg_pipeline_no_exc.py`.

Fixed
- The zero division hint for error functions did not properly replace the value with NaN, when the result of the
operation was -inf instead of inf.

Scientific Changes

- **BREAKING**: Using "high precision" standard value of gravity everywhere (9.80665 m/s^2).
Before we were using 9.81 m/s^2 during the loading of MobiliseD matlab files and when calculating the stride length
validity threshold.
This should have a small impact on the results of most algorithms, hence, we marked it as a breaking change.

Added

- The `apply_aggregations` and `apply_transformation` functions now have an option (on by default) to ignore
transformations that expect columns that don't exist.
This should allow the use of the default aggregations and transformations in more situations.

Changed

- The matlab loader now accepts infoForAlgo files that are missing some of the optional fields.

Scientific Changes

- **CRITICAL**: The default thresholds for both variants of the GSDIonescu algorithms were not correctly adapted to the
input data being in m/s2 instead of g.
With the old threshold far to many gait sequences were detected.
This fix should have a substantial positive impact on the performance of the Impaired pipeline.

Fixed
- `as_samples` now correctly preserves the index of a dataframe.

Added

- Evaluation Examples for CAD and Stride Length (https://github.com/mobilise-d/mobgap/pull/174)

Changed

- The reference data parser now allows missing information. In case either no turns, no ICs or no strides are available,
the respective attribute of the reference data is set to None. Before this threw an error.

- Correctly specified minimal pandas version as >=2.2.0