A collection of classes that represent archaeological data. This package provides a set of S4 classes that represent different special types of matrix (absolute/relative frequency, presence/absence data, co-occurrence matrix, etc.) upon which package developers can build subclasses. It also provides a set of generic methods (mutators and coercion mechanisms) and functions (e.g. predicates). In addition, a few classes of general interest (e.g. that represent stratigraphic relationships) are implemented.
You can install the released version of arkhe from CRAN with:
install.packages("arkhe")And the development version from GitHub with:
# install.packages("remotes")
remotes::install_github("tesselle/arkhe")## Load the package
library(arkhe)arkhe provides a set of S4 classes that represent different special types of matrix.
CountMatrix represents absolute frequency data,OccurrenceMatrix represents a co-occurrence
matrix,CompositionMatrix represents relative frequency
(compositional) data,IncidenceMatrix represents presence/absence data,StratigraphicMatrix represents stratigraphic
relationships.It assumes that you keep your data tidy: each variable (type/taxa) must be saved in its own column and each observation (assemblage/sample) must be saved in its own row.
These new classes are of simple use as they inherit from the base
matrix:
## Define a count data matrix
## (data will be rounded to zero decimal places, then coerced with as.integer)
quanti <- CountMatrix(data = sample(0:10, 100, TRUE), nrow = 10, ncol = 10)
## Define a logical matrix
## (data will be coerced with as.logical)
quali <- IncidenceMatrix(data = sample(0:1, 100, TRUE), nrow = 10, ncol = 10)arkhe uses coercing mechanisms (with validation methods) for data type conversions:
## Create a count matrix
X <- matrix(data = sample(0:10, 75, TRUE), nrow = 15, ncol = 5)
## Coerce to absolute frequencies
A1 <- as_count(X)
## Coerce to relative frequencies
B <- as_composition(A1)
## Row sums are internally stored before coercing to a frequency matrix
## (use get_totals() to get these values)
## This allows to restore the source data
A2 <- as_count(B)
all(A1 == A2)
#> [1] TRUE
## Coerce to presence/absence
D <- as_incidence(A1)
## Coerce to a co-occurrence matrix
E <- as_occurrence(A1)The CountMatrix, CompositionMatrix and
IncidenceMatrix classes have special slots:
samples for replicated measurements/observation,groups to group data by site/area,dates to specify the date point estimate of an
assemblage,tqp and taq to specify the chronology of
an assemblage.The way chronological information is handled is somewhat opinionated.
Sub-annual precision is overkill/meaningless in most situations: dates
are assumed to be expressed in years CE and are stored as integers
(values are coerced with as.integer() and hence truncated
towards zero).
When coercing a data.frame to a *Matrix
object, an attempt is made to automatically assign values to these slots
by mapping column names. This behavior can be disabled by setting
options(arkhe.autodetect = FALSE).
Y <- as.data.frame(X)
Y$samples <- sample(c("a", "b", "c", "d", "e"), 15, TRUE)
Y$groups <- sample(c("A", "B", "C", "D", "E"), 15, TRUE)
Y$dates <- sample(1400:1451, 15, TRUE)
Y$tpq <- sample(1301:1400, 15, TRUE) # TPQ
Y$taq <- sample(1451:1500, 15, TRUE) # TAQ
## Coerce to a count matrix
Z <- as_count(Y)
## Get groups
get_samples(Z)
#> [1] "d" "a" "b" "e" "b" "e" "b" "d" "e" "d" "d" "e" "e" "e" "a"
## Get groups
get_groups(Z)
#> [1] "A" "E" "A" "B" "A" "D" "A" "E" "D" "B" "E" "D" "A" "A" "C"
## Get dates
get_dates(Z)
#> [1] 1442 1449 1431 1439 1429 1411 1400 1439 1437 1440 1444 1418 1450 1436 1427
## Get chronology
get_terminus(Z)
#> tpq taq
#> row1 1302 1486
#> row2 1346 1496
#> row3 1349 1456
#> row4 1372 1485
#> row5 1370 1495
#> row6 1318 1455
#> row7 1389 1467
#> row8 1377 1488
#> row9 1346 1462
#> row10 1308 1487
#> row11 1362 1464
#> row12 1400 1451
#> row13 1312 1464
#> row14 1316 1483
#> row15 1332 1468
## Summarize
summary(Z)
#> <AbundanceSummary: 15 x 5>
#> A ------------------------------------------------------------------------------
#> * Observations: 6
#> * Variables: 5
#> * Replicated measurements: TRUE
#> * Chronology: 1302 - 1495 (year CE)
#> B ------------------------------------------------------------------------------
#> * Observations: 2
#> * Variables: 5
#> * Replicated measurements: FALSE
#> * Chronology: 1308 - 1487 (year CE)
#> C ------------------------------------------------------------------------------
#> * Observation: 1
#> * Variables: 5
#> * Replicated measurements: FALSE
#> * Chronology: 1332 - 1468 (year CE)
#> D ------------------------------------------------------------------------------
#> * Observations: 3
#> * Variables: 5
#> * Replicated measurements: TRUE
#> * Chronology: 1318 - 1462 (year CE)
#> E ------------------------------------------------------------------------------
#> * Observations: 3
#> * Variables: 5
#> * Replicated measurements: TRUE
#> * Chronology: 1346 - 1496 (year CE)
#> --------------------------------------------------------------------------------Please note that the arkhe project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.