EstimatorConsistencyScenario
Robotics scenarios · Implementation: mlsysim/engine/scenario_definitions/robotics/estimation.py.
Construct this scenario with keyword inputs. The fields below show the types and defaults declared by this class.
A qualification campaign of runs scalar estimates, and single-update gates against fusion’s misdated update.
Notes
Equation: The result property composes mlsysim.solvers.EstimatorConsistencyModel.solve with the stored fields and any derived properties described below.
Assumptions: Inputs use the units and validity ranges of mlsysim.solvers.EstimatorConsistencyModel.solve. The named scenario supplies a fixed configuration rather than observations of a new run.
Excludes: Additional runtime effects or statistical guarantees beyond the cited solver contracts; no measurement is performed by this wrapper.
References
Derivation: The result property composes mlsysim.solvers.EstimatorConsistencyModel.solve with the stored fields and any derived properties described below. Individual property contracts identify the exact accounting expression or reusable calculation. Registry entries supply the scenario inputs; this class does not turn them into measured outcomes.
Examples
Evaluate a named scenario using its declared inputs.
>>> from mlsysim import Scenarios
>>> scenario = Scenarios.RackEndMisdatedUpdateConsistency
>>> round(float(scenario.result.band_low), 4)
0.6471Attributes
| Name | Description |
|---|---|
| confidence | |
| dimension | |
| fusion | |
| gate_confidences | |
| result | Return the modeled EstimatorConsistency result from |
| runs |
fusion
Type: Any.
Declared default: required.
runs
Type: int.
Declared default: required.
dimension
Type: int.
Declared default: 1.
confidence
Type: float.
Declared default: 0.95.
gate_confidences
Type: List[float].
Declared default: [0.95, 0.99].
result
engine.scenario_types.EstimatorConsistencyScenario.result
Return the modeled EstimatorConsistency result from mlsysim.solvers.EstimatorConsistencyModel.solve.
Equation: the scenario supplies its named fields to that solver. Returned quantity units, validity conditions, and omissions follow its calculation contract; this property adds no empirical calibration.