Coerce a time series object to values plus a time index

Detection itself runs on positions — every wrapped engine assumes an equally spaced sequence — but real series carry dates, and reporting a changepoint as "index 147" when the data are monthly rainfall is an unnecessary translation step for the user. as_cpt_series() is the one place that separates the two: it pulls the numeric values out of a ts, xts, zoo, tsibble or data frame and returns the time index alongside them, so cpt_detect() can detect on positions and report on dates.

Usage

as_cpt_series(x, index = NULL, check_regular = TRUE)

Arguments

x

A numeric vector or matrix, or a ts/mts, xts, zoo or tsibble object. The xts, zoo and tsibble paths need those packages installed (they are Suggests).

index

Optional explicit index, one value per observation. Overrides any index carried by x, and is the way to attach dates to a plain numeric vector.

check_regular

Warn when the index is not equally spaced? Defaults to TRUE. Every engine in the package assumes equal spacing, so an irregular index means the positions the engine sees are not the times the user means.

Value

A list with components values (a numeric vector, or a matrix for multivariate input), index (the time index, or NULL when there is none) and index_label (a name for the x axis).

See also

Other result class: annotate_segments(), as_ggcpt(), cpt_annotations(), is_ggcpt(), new_ggcpt()

Examples

as_cpt_series(1:10)$index
#> NULL
s <- as_cpt_series(1:10, index = as.Date("2020-01-01") + 0:9)
s$index
#>  [1] "2020-01-01" "2020-01-02" "2020-01-03" "2020-01-04" "2020-01-05"
#>  [6] "2020-01-06" "2020-01-07" "2020-01-08" "2020-01-09" "2020-01-10"