Multi-label RAP switch

[rafdhaene]

Quick description

This PR adds multi-label Region-Adaptive Propagation (RAP) “switch” policies and integrates them into scil_tracking_local_dev.py, allowing tracking parameters to change based on an integer label map.

Main changes
• Multi label RAP policies (JSON) (per label: algo, theta in degrees, step_size), while keeping backward compatibility with the legacy single-policy format.
• Dynamic parameter switching during tracking: when entering a RAP label region (switch between det/prob, update theta, update step_size).
• CLI integration (--rap_mask, --rap_method switch, --rap_params (JSON policy file)

The goal here is to allow the tracking behavior to be changed conditionally on external information (here: a labeled RAP mask)

Type of change

Check the relevant options.

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

Provide data, screenshots, command line to test (if relevant)

Data: we use the FiberCup dataset (Tractometer).
RAP mask: integer label map (0...N).

Example JSON:
{
"1": {"algo": "det", "theta": 35, "step_size": 0.5},
"2": {"algo": "prob", "theta": 35, "step_size": 0.5},
"3": {"algo": "prob", "theta": 10, "step_size": 0.25}
}

Command line (local dev)
python -m scilpy.cli.scil_tracking_local_dev
<fodf.nii.gz> <seed_mask.nii.gz> <tracking_mask.nii.gz> out_rap_switch.trk
--algo prob --theta 35 --step 0.5 --min_length 10 --max_length 200
--rap_mask <rap_label_mask.nii.gz>
--rap_method switch
--rap_params <rap_policies.json>
-v INFO -f

Notes:
In some cases streamlines can exit voxel bounds, saving may require disabling bbox validation or filtering invalid streamlines prior to writing.
Do not pay attention to the modification of scil_local_tracking_rafael, was changed for tests at beginning

Next step: Implementation of stopping propagation when the next point is outside valid voxel bounds to reduce invalid streamlines

Checklist

• My code follows the style guidelines of this project (run autopep8)
• I added relevant citations to scripts, modules and functions docstrings and descriptions
• I have performed a self-review of my code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• My changes generate no new warnings
• I moved all functions from the script file (except the argparser and main) to scilpy modules
• I have added tests that prove my fix is effective or that my feature works
• New and existing unit tests pass locally with my changes