A quick example to load a data file from Neotoma and then run Bacon.

neotoma_and_bacon

#  This needs to run in the directory in which you have Bacon installed.
#  If you do not currently have the `neotoma` package installed then uncomment
#  and run the following code. Right now you will need to install the package from GitHub
#  because our latest bug fixes haven't been pushed up into CRAN.
#
#  install.packages('devtools')
#  library(devtools)
#  install_github('ropensci/neotoma')
#
#  The Neotoma package is described more fully here:
#
#  Goring, S., Dawson, A., Simpson, G. L., Ram, K., Graham, R. W., Grimm, E. C., &
#    Williams, J. W.. (2015). neotoma: A Programmatic Interface to the Neotoma
#    Paleoecological Database, 1(1), Art. 2. DOI: http://doi.org/10.5334/oq.ab
#
#  

library(neotoma)
library(maps)  # you may also want to install this.

#  There are (surprisingly?) no data records from Nevada currently.  Instead we will
#  pull records from California. In this call I want to find high elevation sites
#  because they're kind of interesting.

ca_pollen <- get_dataset(gpid = 'California', datasettype = 'pollen', 
                         ageold = 10000,  altmin=1000)

plot(get_site(ca_pollen)[,c('long', 'lat')], 
     xlim = c(-125, -115), ylim=c(30, 45), 
     pch=19, col=2)
map('world', add=TRUE)
map("state", add=TRUE)

#  Now we can download the records.
#  You should see the site names running by.  As you do this, reflect on all the work
#  that's gone into these records and give thanks to the named and unnamed workers who
#  toiled behind a microscope for months at a time so that you could download their data
#  in mere seconds.
ca_download <- get_download(ca_pollen)

#  For this example we should find the one that gives us the most dated material.
dated_samples <- get_chroncontrol(ca_download)

#  This next line is just FYI - we're getting a vector of the number of dates in each core.
#  Some will return a NULL if there is no associated control table.  This happens for single
#  stratigraphic pollen sections for example.
sapply(dated_samples, function(x)nrow(x$chron.control))

#  The last core (Taquitz Meadow) has 6, controls:
#  The number is quotes is the dataset number.  To choose a different dataset look at the
#  available datasets and enter in a different number.

plot(dated_samples[['15594']]$chron.control[,c('depth', 'age')])
#  You can try a few different ones to see how things look.

#  So Taquitz Meadow looks good.  We can look at it in the Neotoma Explorer like this:
#  http://apps.neotomadb.org/explorer/?datasetid=15594

# The original model was generated in Bacon, let's see how well we do:
write_agefile(ca_download[['15594']], chronology = 1, 
              path = '.', corename = 'TAQUITZ', cal.prog = 'Bacon')

#  Source Bacon . . . 
source('Bacon.R')

#  Please note that this will actually take a very very long time.  It might be worth picking a different site.  
Bacon('TAQUITZ')

I didn't get a notification of this very old comment. Bacon.R is part of the Bacon package, which can be downloaded from: http://www.chrono.qub.ac.uk/blaauw/bacon.html