Reproducing ArchaeoPhases Objects

In ArchaeoPhases: Post-Processing of the Markov Chain Simulated by 'ChronoModel', 'Oxcal' or 'BCal'

4. ArchaeoPhases : Reproducibility

knitr::opts_chunk$set(comment = "")
options(width = 120, max.print = 20)
library(ArchaeoPhases)

Introduction

Version ArchaeoPhases 1.5 adds new read, plot, and statistical functions designed to encourage reproducibility. This vignette describes some of these functions and illustrates how to use them to reproduce an analysis.

New read functions read_bcal(), read_oxcal(), and read_chronomodel() are intended to replace the general purpose function, ImportCSV(). The new functions are built on the function read_csv(), which is fast and able to read remote files, as well as local files. The new functions return S3 objects that can identify the file that produced them. This facility might be useful in situations where an analysis is based on a remote file that isn't under the analyst's control, or when files are shared electronically and potentially subject to corruption.

Test for Original Data File

The following code block illustrates this capability. After the ArchaeoPhases package has been loaded, the read_oxcal function is used to read a remote OxCal file and assign an S3 object to the variable oxc. The original_file method of the oxc object checks if the original file used to create it has changed since the object was created. If the original file still exists and is unchanged, then the function returns TRUE. If the original file cannot be found, or has changed, then the function returns FALSE.

## load ArchaeoPhases
library(ArchaeoPhases)
## read remote file
data(oxc)
## returns TRUE, if ox.csv has not changed on the server
original_file(oxc)

New Plot Functions

The new plot functions, multi_dates_plot(), tempo_activity_plot(), tempo_plot(), marginal_plot(), multi_marginal_plot(), and occurrence_plot() are functional replacements for the originals with camelCase names, e.g., TempoPlot() -> tempo_plot(). They return S3 objects with plot() and reproduce() methods that inherit from data frame and can be passed to statistical functions.

The following code block illustrates the plot() and reproduce() methods. The call to the marginal_plot function draws a plot of the first marginal posterior in the oxc object and returns an S3 object, which is assigned to the variable oxc.mar. The call to the plot method of the oxc.mar object draws the same plot and also returns an S3 object. Note that the S3 objects returned by marginal_plot() and plot() differ because the calls that created them differ. Nevertheless, the data returned by the two calls are identical, as expected. The call, reproduce(oxc.mar) checks that the original file is accessible and has not changed, then recreates the plot. If successful, the object it returns is identical with the object it reproduces.

## create mariginal plot object
oxc.mar <- marginal_plot(oxc)
## use plot method to reproduce marginal plot
oxc.mar.plot <- plot(oxc.mar)
## check for identity returns FALSE because calls differ
identical(oxc.mar, oxc.mar.plot)
## check for data identity returns TRUE
identical(oxc.mar$x, oxc.mar.plot$x)
## reproduce the marginal plot object
oxc.mar.rep <- reproduce(oxc.mar)
## check for object identity returns TRUE
identical(oxc.mar.rep, oxc.mar)

Objects Are Data Frames

The objects returned by the read_*() functions behave like data frames. The new function, multi_marginal_statistics, expects a data frame as its first argument. When passed the oxc object, it returns an object with various summary statistics of the marginals, as if it had been passed a standard data frame.

oxc.stats <- multi_marginal_statistics(oxc)
oxc.stats$statistics

Use Cases

The ability to reproduce an ArchaeoPhases analysis might find several uses.

One use case is when work on a project is interrupted. In this use case, objects produced during an earlier session and saved to disk can be read into the new R session. The reproduce methods of the objects will indicate whether or not the Bayesian calibration output is still available, and if so, whether or not it has changed.

Another use case is a collaboration where one might wish to distribute an MCMC file and the R code required to make an informative plot. An email message with the MCMC file and the saved ArchaeoPhases object attached is a reasonable way this might be accomplished. In this situation, the recipient can point the reproduce() function to the local MCMC file and verify that the analysis carried out by the sender can actually be reproduced.

A third use case is one you should know how to avoid. The S3 objects produced by ArchaeoPhases can be manipulated to include malicious code and an unscrupulous scoundrel might intend to harm you in this way. The best defense is, as usual, to choose trustworthy collaborators and not try to reproduce objects from unknown sources. In any event, a simple way to check for malicious code is to inspect the call attribute of the object, as shown in the following source code block. If the call looks good, then all should be well.

attr(oxc.mar, "call")

ArchaeoPhases documentation built on June 22, 2022, 1:05 a.m.