SyntheticFootprintScenario
Data scenarios · Implementation: mlsysim/engine/scenario_definitions/data.py.
Construct this scenario with keyword inputs. The fields below show the types and defaults declared by this class.
Generated samples with provenance metadata, read once per verification pass.
Notes
Equation: Compose mlsysim.solvers.SyntheticFootprintModel.
Assumptions: The stated fields are inputs to mlsysim.solvers.SyntheticFootprintModel; its documented validity regime, units, and modeling choices apply unchanged.
Excludes: This scenario adds no measurement, empirical calibration, or mechanisms beyond mlsysim.solvers.SyntheticFootprintModel.
References
Derivation: this scenario binds its input fields to the referenced implementation contracts: mlsysim.solvers.SyntheticFootprintModel. The methods below identify any additional arithmetic.
Examples
>>> from mlsysim import Scenarios
>>> case = Scenarios.SyntheticDataProvenance
>>> type(case.result).__name__
'SyntheticFootprintResult'Attributes
| Name | Description |
|---|---|
| payload_bytes | |
| provenance_overhead | |
| result | Evaluate this scenario through mlsysim.solvers.SyntheticFootprintModel.solve. |
| verification_passes |
payload_bytes
Type: Quantity.
Declared default: required.
provenance_overhead
Type: float.
Declared default: required.
verification_passes
Type: int.
Declared default: required.
result
engine.scenario_types.SyntheticFootprintScenario.result
Evaluate this scenario through mlsysim.solvers.SyntheticFootprintModel.solve. Equation: pass the stated fields to that implementation; its contract defines the calculation and feasibility tests. Units: each returned field follows the referenced result schema; no independent equation is evaluated by this wrapper.