R/dcmp_checks.R

In feasts: Feature Extraction and Statistics for Time Series

check_gaps <- function(x){
  if (any(has_gaps(x)$.gaps)) {
    abort(sprintf("%s contains implicit gaps in time. You should check your data and convert implicit gaps into explicit missing values using `tsibble::fill_gaps()` if required.", deparse(substitute(x))))
  }
}

check_regular <- function(x){
  if (!is_regular(x)) {
    abort(sprintf("%s is an irregular time series, which this decomposition does not support. You should consider if your data can be made regular, and use `tsibble::update_tsibble(%s, regular = TRUE)` if appropriate.", deparse(substitute(x)), deparse(substitute(x))))
  }
}

check_ordered <- function(x){
  if (!is_ordered(x)) {
    abort(sprintf("%s is an unordered time series. To use this decomposition, you first must sort the data in time order using `dplyr::arrange(%s, %s)`",
                  deparse(substitute(x)), paste(c(deparse(substitute(x)), key_vars(x)), collapse = ", "), as_string(index(x))))
  }
}

all_tsbl_checks <- function(.data){
  check_gaps(.data)
  check_regular(.data)
  check_ordered(.data)
  if(NROW(.data) == 0){
    abort("There is no data to decompose. Please provide a dataset with at least one observation.")
  }
}