Function to return chronological control tables used to build age models.
Source:R/get_chroncontrol.R
get_chroncontrol.Rd
Using the dataset ID, return all records associated with the data. At present, only returns the dataset in an unparsed format, not as a data table. This function will only download one dataset at a time.
Arguments
- x
A single numeric chronology ID, a vector of numeric dataset IDs as returned by
get_dataset
or adownload
ordownload_list
object.- chronology
When
download
objects have more than associated chronology, which chronology do you want? Default is1
.- verbose
logical, should messages on API call be printed?
- add
logical, should this chron control be added to the download object?
Value
This command returns either an object of class "try-error"
containing the error returned
from the Neotoma API call, or a full data object containing all the relevant information required to build either the default or prior chronology for a core.
When download
or download_list
objects are passes, the user can add
the chroncontrol to the
download
object explicitly, in which case the function will return a download with chroncontrol
embedded.
This is a list comprising the following items:
-
chron.control
A table describing the collection, including dataset information, PI data compatable with
get_contact
and site data compatable withget_site
.-
meta
Dataset information for the core, primarily the age-depth model and chronology. In cases where multiple age models exist for a single record the most recent chronology is provided here.
If Neotoma returns empty content, either the control table or the associated metadata (which happens in approximately 25
References
+ Neotoma Project Website: http://www.neotomadb.org + API Reference: http://wnapi.neotomadb.org/doc/resources/contacts
Author
Simon J. Goring simon.j.goring@gmail.com
Examples
if (FALSE) { # \dontrun{
# The point of pulling chronology tables is to re-build or examine the
# chronological information that was used to build the age-depth model for
# the core. You can do this by hand, but the `write_agefile` function works
# with `download` objects directly.
three_pines <- get_download(get_dataset(get_site("Three Pines Bog"),
datasettype = "pollen"))
pines_chron <- get_chroncontrol(three_pines)
# Spline interpolation:
model <- smooth.spline(x = pines_chron[[1]]$chron.control$depth,
y = pines_chron[[1]]$chron.control$age)
new_ages <- predict(model, x = three_pines[[1]]$sample.meta$depth)
} # }