Coerce annotations to changepoint labels

Turns a plain ground-truth changepoint set — the kind cpt_metrics() takes — into labelled regions, so one annotation can drive both the metric and the supervised machinery. Each true changepoint becomes a "one_change" region of width 2 * margin + 1, and the stretches between them become "no_change" regions.

Usage

as_cpt_labels(truth, n, margin = 5, negatives = TRUE, series = NA_character_)

Arguments

truth

Integer vector of true changepoint positions.

n

Series length.

margin

Half-width of the positive regions. Defaults to 5, matching cpt_metrics()'s default tolerance.

negatives

Add the "no_change" regions between the positives? Defaults to TRUE; without them a detector is never penalised for a false positive.

series

Optional series identifier.

Value

A cpt_labels tibble.

Examples

as_cpt_labels(c(50, 120), n = 200)
#> # A tibble: 5 × 5
#>   label_id series start   end change    
#>      <int> <chr>  <int> <int> <chr>     
#> 1        3 NA         1    44 no_change 
#> 2        1 NA        45    55 one_change
#> 3        4 NA        56   114 no_change 
#> 4        2 NA       115   125 one_change
#> 5        5 NA       126   199 no_change