A wrapper for rcarbon::spd()
that takes a list of calibrated dates rather
than a CalDates
object. This allows you to use the output of c14_calibrate()
and
take advantage of tidy summary syntax (dplyr::group_by()
, etc.)
c14_sum(cal, time_range = NA, ...)
cal | A list of |
---|---|
time_range | Vector of length 2 indicating the range of calendar dates
over which to sum. If left |
... | Optional arguments to be passed to |
A calGrid
object containing the summed probability distribution.
Unlike rcarbon::spd()
, this function will attempt to guess an appropriate
time range if it isn't explicitly specified with time_range
. It's probably
a good idea to specify it.
Other tidy radiocarbon functions:
c14_calibrate()
,
cal()
data("shub1_radiocarbon") shub1_radiocarbon %>% dplyr::mutate(cal = c14_calibrate(cra, error, normalise = FALSE, verbose = FALSE)) %>% dplyr::group_by(phase) %>% dplyr::summarise(SPD = c14_sum(cal, spdnormalised = TRUE, verbose = FALSE), .groups = "drop_last")#> # A tibble: 7 x 2 #> phase SPD #> * <chr> <list> #> 1 Phase 1 <CalGrid[,2] [11,659 × 2]> #> 2 Phase 2 <CalGrid[,2] [560 × 2]> #> 3 Phase 3 <CalGrid[,2] [473 × 2]> #> 4 Phase 4 <CalGrid[,2] [1,273 × 2]> #> 5 Phase 5 <CalGrid[,2] [1,377 × 2]> #> 6 Phase 6 <CalGrid[,2] [1,155 × 2]> #> 7 Phase 7 <CalGrid[,2] [1,327 × 2]>