Add StateVectorActionGenerator and make OptunaSensorManager compatible

[nperree-dstl]

IntroducesStateVectorActionGenerator as a base class for generating actions which change the state (e.g. platform location), and MovePositionActionGenerator for generating MovePositionActions.

Updates OptunaSensorManager so it is compatible with StateVectorActionGenerators.

Addresses #1190.

[codecov]

Codecov Report

❌ Patch coverage is 87.67123% with 9 lines in your changes missing coverage. Please review.
✅ Project coverage is 94.60%. Comparing base (b30d402) to head (4407286).
⚠️ Report is 21 commits behind head on main.

Files with missing lines	Patch %	Lines
stonesoup/sensormanager/optuna.py	77.77%	2 Missing and 4 partials ⚠️
stonesoup/movable/action/move_position_action.py	90.62%	1 Missing and 2 partials ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1251      +/-   ##
==========================================
+ Coverage   94.58%   94.60%   +0.01%     
==========================================
  Files         233      233              
  Lines       16743    16761      +18     
  Branches     2356     2363       +7     
==========================================
+ Hits        15837    15856      +19     
+ Misses        607      604       -3     
- Partials      299      301       +2     

Flag	Coverage Δ
integration	66.68% <38.35%> (-0.11%)	⬇️
unittests	91.97% <87.67%> (+0.02%)	⬆️

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[sdhiscocks]

I wonder if max change could be something that is part of the action generator, as different StateVectorActionGenerators may have different ways to define constraints. Possibly min and max?

[hpritchett-dstl]

I think having a min / max StateVector with the same length as action mapping that defines the min / max of each dimension would be useful. This specific constraint seems to be an inequality rather than a min / max, i.e. bounding a 2d position by a circle, rather than a square (which min / max would do).

To do this generally, we would need to add lower (or upper) inequalities to generators. This could be a list of callables that act on this generator's action space?

e.g for CircleSamplePositionActionGenerator and MaxSpeedPositionActionGenerator we would have a less than or equal inequality looking something like:

lambda x: np.sum( [ (x[index] - self.current_value[index]) ** 2 for index in self.action_mapping ] ) - self.maximum_travel**2

These could then be integrated into constraints for Optuna objectives / other optimisation packages more easily without having to have custom logic per generator in each sensor manager.

[hpritchett-dstl]

The resolution for the NStepDirectionalGridActionGenerator is resolution * step_size. So in most cases a platform with that generator will be given an action value it doesn't contain and it will fail silently.