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A quick example to load a data file from Neotoma and then run 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')
@dlebauer

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dlebauer commented Oct 11, 2015

@SimonGoring ... where is Bacon.R?

@SimonGoring

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SimonGoring commented Aug 14, 2017

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

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