Patterns

AssetDatabase + SceneBounds -> PhysicalSimulationState

Programmatically spawn, orient, and position 3D assets within defined bounds subject to non-collision constraints to initialize a physical simulation.

Transaction -> ValidationResult

Verify a transaction's structural and business logic validity by running its input and output states through deterministic smart contract rules on the JVM.

ReserveUtilization -> VariableInterestRate

Compute dynamic borrowing costs using a multi-slope curve that accelerates sharply once asset utilization crosses a target kink.

(uint256, uint256) -> uint256

Multiply two numbers, validating that the product divided by the first factor recovers the second factor to prevent integer overflow.

AgentPositions, SpatialRaster -> CellIndices

Determine and update agent locations on a spatial grid using vectorized coordinate-to-index transformations instead of loops.

PriorityQueue<SimulationEvent> -> UpdatedSimulationState

Execute scheduled functions chronologically via a priority queue, appending new events dynamically spawned by running modules.

List<FHIR.Observation> -> FHIR.Observation<GMI>

Calculate the Glucose Management Indicator (GMI / estimated HbA1c) from the mean sensor glucose value over a multi-day window (typically 12+ days) using clinical formula coefficients.

List<FHIR.Observation> -> FHIR.Observation<TIRSummary>

Aggregate periodic glucose readings over a designated duration to calculate percentage of time spent within hyper-, hypo-, and target-glycemic ranges.

Stream<SensorReading> -> Stream<FHIR.Observation>

Map raw continuous glucose monitor readings (timestamp, value, trend) to standardized FHIR Observation resources with LOINC and SNOMED coding.

List<Action> -> JointAction

Combine individual simultaneous decisions from multiple players into a single joint action to advance the game state.

GameState -> Action

Sample an environmental action from the defined probability distribution of a game's chance node.

VisualGraphJSON -> ExecutableDAG

Convert a visual graph definition of nodes and directional edges into a structured, dependency-resolved execution DAG (Directed Acyclic Graph).

ExpressionString, ExecutionHistory -> EvaluatedValue

Resolve dynamic parameter expressions by querying a historical state dictionary containing outputs of all previously executed nodes.

AnnotatedPythonClass -> APIRouteMap

Inspect Python class methods decorated with API metadata and type hints to dynamically generate REST/gRPC endpoints and schema validations.

Tuple<ToolFunction, RuntimeDependencies> -> ExecutableTool

Resolve and inject dynamic runtime dependencies (like active database clients or state) into tool execution scopes.

PointCloud -> Tuple<GroundPointCloud, ObstaclePointCloud>

Separate 3D LiDAR points into ground and non-ground subsets by analyzing local radial gradient changes of consecutive points.

Tuple<StartPose, GoalPose, Lanelet2Map> -> LaneletRoute

Generate a topological route sequence of lanes from a starting pose to a goal pose on a high-definition Lanelet2 semantic map.

Tuple<Trajectory, CurrentPose, VehicleKinematics> -> ControlCommand

Calculate optimal steering and acceleration commands over a finite time horizon by solving a quadratic programming problem based on a kinematic vehicle model.

Tuple<PointCloud, MapPointCloud, PriorPose> -> EstimatedPose

Align a real-time LiDAR point cloud with a 3D reference map using the Normal Distributions Transform to output a high-precision vehicle pose estimate.

State -> string

Dynamically determine the next execution node by evaluating a user-defined routing function on the current state.

(State, StateUpdate) -> State

Merge step-level state updates into a global graph state using schema-defined key-wise reducer functions.

PoolRates -> P2PRate

Calculate peer-to-peer interest rates dynamically as the mid-rate between the underlying pool's supply rate and borrow rate.