RaymarchTrafficScenario
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.
One depth stream ray-marched into a map on site.machine’s host SoC.
Notes
Equation: result evaluates the configured solver; its contract owns the governing equations.
Assumptions: Every depth pixel follows the same ray length and step pitch at a fixed frame rate.
Excludes: Early termination, sparsity, cache reuse, and competing host traffic.
References
Derivation: The scenario binds declared inputs to RaymarchTrafficModel. Those implementations document their derivations and sources.
Examples
Execute the registered worked inputs; this is a modeled calculation.
>>> from mlsysim import Scenarios
>>> case = Scenarios.WarehouseDepthRaymarchTraffic
>>> value = case.result
>>> print(f"{value.traffic:.3f~P}")
7.373 GB/sAttributes
| Name | Description |
|---|---|
| bytes_per_step | |
| frame_rate | |
| height_px | |
| pitch | |
| ray_length | |
| result | Evaluate the configured inputs with mlsysim.solvers.RaymarchTrafficModel.solve. |
| site | |
| width_px |
site
Type: Any.
Declared default: required.
width_px
Type: int.
Declared default: required.
height_px
Type: int.
Declared default: required.
frame_rate
Type: Quantity.
Declared default: required.
ray_length
Type: Quantity.
Declared default: required.
pitch
Type: Quantity.
Declared default: required.
bytes_per_step
Type: Quantity.
Declared default: required.
result
engine.scenario_types.RaymarchTrafficScenario.result
Evaluate the configured inputs with mlsysim.solvers.RaymarchTrafficModel.solve.
The returned typed result retains the solver’s documented units, assumptions, and feasibility semantics; this property adds no measurement or safety claim. Equation: result = RaymarchTrafficModel().solve(...) using the fields shown below.