har_stream_experiment: Streaming experiment runner

In harbinger: A Unified Time Series Event Detection Framework

Streaming experiment runner

Description

Runs a reproducible grid of online streaming experiments by combining detectors, source factories, batch settings, memory policies, and optional labeled references.

The experiment runner is intentionally lightweight. It reuses the online session layer and returns both the raw runs and a compact summary table.

Usage

har_stream_experiment(
  detectors,
  source_factory,
  warmup_grid,
  batch_grid,
  memory_grid,
  executor = har_online_refit_full(),
  reference = NULL,
  mode = c("auto", "pull", "push"),
  ...
)

Arguments

detectors	Named list of detector objects. An unnamed list is also accepted and will be labeled by class.
source_factory	Function that creates a fresh source object for each run. This keeps each execution independent and reproducible.
warmup_grid	Integer vector of warm-up sizes.
batch_grid	Integer vector of batch sizes.
memory_grid	List of memory policy objects.
executor	Execution strategy. Defaults to har_online_refit_full().
reference	Optional event reference vector.
mode	Session mode: "auto", "pull", or "push".
...	Additional arguments forwarded to run_online().

Value

A har_stream_experiment object with:

• runs: a list of raw run objects containing session, trace, and evaluation;

• summary: a compact data frame for cross-configuration comparison.

Examples

factory <- function() har_source_simulated(c(1, 1, 1, 10, 1, 1))
experiment <- har_stream_experiment(
  detectors = list(page = hcp_page_hinkley(min_instances = 3, threshold = 1)),
  source_factory = factory,
  warmup_grid = 3,
  batch_grid = c(1, 2),
  memory_grid = list(har_memory_full())
)
experiment$summary

harbinger documentation built on July 10, 2026, 5:07 p.m.