ExperimentRunDefaults

@Serializable
data class ExperimentRunDefaults(val numberOfReplications: Int, val numChunks: Int, val startingRepId: Int, val lengthOfReplication: Double, val lengthOfReplicationWarmUp: Double, val replicationInitializationOption: Boolean, val maximumAllowedExecutionTimePerReplication: Duration, val resetStartStreamOption: Boolean, val advanceNextSubStreamOption: Boolean, val antitheticOption: Boolean, val numberOfStreamAdvancesPriorToRunning: Int, val garbageCollectAfterReplicationFlag: Boolean)(source)

Model-intrinsic defaults for the run-parameter surface of an experiment.

Captures the twelve parameter values that describe how a model is intended to be run: replication count, replication length, warm-up length, stream options, antithetic option, and so on. Deliberately omits the runtime-identification fields — experimentName, experimentId, runName — because those identify a specific run rather than the model itself.

Used as the run-parameter component of ksl.simulation.ModelDescriptor, the machine-readable snapshot that bundle tooling and consumers read. Its shape is deliberately a subset of ExperimentRunParameters; the latter remains the input directive for actually running an experiment, where the runtime-identification fields are required.

Note: currentReplicationNumber is not stored here either — it is an in-flight runtime value, not a default.

Constructors

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constructor(numberOfReplications: Int, numChunks: Int, startingRepId: Int, lengthOfReplication: Double, lengthOfReplicationWarmUp: Double, replicationInitializationOption: Boolean, maximumAllowedExecutionTimePerReplication: Duration, resetStartStreamOption: Boolean, advanceNextSubStreamOption: Boolean, antitheticOption: Boolean, numberOfStreamAdvancesPriorToRunning: Int, garbageCollectAfterReplicationFlag: Boolean)

Properties

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whether to advance sub-streams between replications (supports CRN)

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whether antithetic replications are used

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whether System.gc() is invoked after each replication

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replication length in model time units

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warm-up duration within a replication

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the model's recommended replication count

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the number of stream advances applied before running the experiment

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the model's chunking convention; 1 means run all replications as a single chunk

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whether the system state is re-initialized at the start of each replication

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whether random streams are reset prior to the first replication

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the first replication identifier (almost always 1)