har_online_session: Harbinger online session

In harbinger: A Unified Time Series Event Detection Framework

Harbinger online session

Description

Creates and runs a streaming session that reuses existing Harbinger detectors without changing their offline APIs. The session layer is intentionally additive: it orchestrates ingestion, batching, memory management, tracing, and evaluation support around the detector already provided by the package.

The session supports:

• pull sources through next_observation()

• push ingestion through ingest()

• full or bounded memory policies

• explicit execution strategies

• structured tracing for Detection Probability (DP) and Detection Lag (DL)

Usage

har_online_session(
  source,
  detector,
  executor = har_online_refit_full(),
  warmup_size = 30,
  batch_size = 30,
  memory = har_memory_full(),
  mode = c("auto", "pull", "push")
)

Arguments

source	Streaming source object. May be NULL for push-only sessions.
detector	Any existing Harbinger detector.
executor	Execution strategy. Defaults to har_online_refit_full().
warmup_size	Number of initial observations consumed before regular streaming detection starts.
batch_size	Number of new observations required to trigger one online detection cycle.
memory	Memory policy. Defaults to har_memory_full().
mode	Session mode: "auto": behaves like pull mode when a source is available and like push mode when source = NULL; "pull": observations are requested through next_observation(source); "push": observations must be provided explicitly through ingest().

Value

A har_online_session object.

Examples

source <- har_source_simulated(c(10, 11, 12, 20, 12, 11, 10))
session <- har_online_session(
  source = source,
  detector = hcp_page_hinkley(min_instances = 3, threshold = 1),
  warmup_size = 3,
  batch_size = 2
)
session <- daltoolbox::fit(session)
session <- run_online(session)
head(collect_detection(session))

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