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Harbinger online session

Source: R/har_online_session.R
har_online_session.Rd

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))
#>   idx event        type detection_probability detection_lag_batches
#> 1   1 FALSE                                 0                    NA
#> 2   2 FALSE                                 0                    NA
#> 3   3  TRUE changepoint                     1                     0
#> 4   4 FALSE                                 0                    NA
#> 5   5 FALSE                                 0                    NA
#> 6   6 FALSE                                 0                    NA
#>   detection_lag_observations
#> 1                         NA
#> 2                         NA
#> 3                          2
#> 4                         NA
#> 5                         NA
#> 6                         NA