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# CLASSES DEFINITION AND INITIALIZATION
#' @include reexport.R
NULL
# MCMC =========================================================================
#' MCMC
#'
#' An S4 class to represent the output of a MCMC algorithm.
#' @slot labels A [`character`] vector specifying the name of the events.
#' @slot depth A [`numeric`] vector giving the sample depth.
#' @slot hash A [`character`] string giving the 32-byte MD5 hash of the
#' original data file.
#' @section Subset:
#' In the code snippets below, `x` is a `MCMC` object.
#' \describe{
#' \item{`x[[i]]`}{Extracts a single event (one chain) selected by subscript
#' `i`. `i` is a length-one [`numeric`] or [`character`] vector.}
#' }
#' @note
#' This class inherits from [`matrix`].
#' @author N. Frerebeau
#' @family classes
#' @docType class
#' @aliases MCMC-class
#' @keywords internal
.MCMC <- setClass(
Class = "MCMC",
slots = c(
labels = "character",
depth = "numeric",
iteration = "integer",
hash = "character"
),
contains = "matrix"
)
## Events ----------------------------------------------------------------------
#' MCMC Events
#'
#' S4 classes to represent a collection of events.
#' @note
#' This class inherits from [`MCMC-class`].
#' @author N. Frerebeau
#' @family classes
#' @docType class
#' @aliases EventsMCMC-class
#' @keywords internal
.EventsMCMC <- setClass(Class = "EventsMCMC", contains = "MCMC")
## Duration --------------------------------------------------------------------
#' MCMC Duration
#'
#' S4 classes to represent the output of a MCMC algorithm.
#' @note
#' This class inherits from [`MCMC-class`].
#' @author N. Frerebeau
#' @family classes
#' @docType class
#' @aliases DurationsMCMC-class
#' @keywords internal
.DurationsMCMC <- setClass(Class = "DurationsMCMC", contains = "MCMC")
## Phases ----------------------------------------------------------------------
#' MCMC Phases
#'
#' S4 classes to represent a collection of phases.
#' @slot labels A [`character`] vector specifying the name of the phases.
#' @slot hash A [`character`] string giving the 32-byte MD5 hash of the
#' original data file.
#' @details
#' A phase object is an\eqn{n x m x 2}{n \times m \times 2} array, with
#' \eqn{n} being the number of iterations, \eqn{m} being the number of phases
#' and with the 2 columns of the third dimension containing the boundaries of
#' the phases.
#' @section Subset:
#' In the code snippets below, `x` is a `PhasesMCMC` object.
#' \describe{
#' \item{`x[[i]]`}{Extracts a single phase (two chains) selected by subscript
#' `i`. `i` is a length-one [`numeric`] or [`character`] vector.}
#' }
#' @note
#' This class inherits from [`array`].
#' @author N. Frerebeau
#' @family classes
#' @docType class
#' @aliases PhasesMCMC-class
#' @keywords internal
.PhasesMCMC <- setClass(
Class = "PhasesMCMC",
slots = c(
labels = "character",
iteration = "integer",
hash = "character"
),
contains = "array"
)
# Time Range ===================================================================
#' Cumulative Events
#'
#' An S4 class to represent time ranges.
#' @slot start,end A `numeric` [`matrix`] giving the lower and upper
#' boundaries.
#' @slot labels A [`character`] vector specifying the name of the events/phases.
#' @slot hash A [`character`] string giving the 32-byte MD5 hash of the
#' original data file.
#' @section Coerce:
#' In the code snippets below, `x` is a `CumulativeEvents` object.
#' \describe{
#' \item{`as.data.frame(x)`}{Coerces to a [`data.frame`].}
#' }
#' @author N. Frerebeau
#' @family classes
#' @docType class
#' @aliases TimeRange-class
#' @keywords internal
.TimeRange <- setClass(
Class = "TimeRange",
slots = c(
start = "matrix",
end = "matrix",
labels = "matrix",
hash = "character"
)
)
# Tempo ========================================================================
#' Cumulative Events
#'
#' An S4 class to store the result of a [`tempo`] plot.
#' @slot lower A [`numeric`] vector giving the lower boundaries of the
#' credibility interval.
#' @slot upper A [`numeric`] vector giving the upper boundaries of the
#' credibility interval.
#' @slot level A length-one [`numeric`] vector giving the confidence level.
#' @slot gauss A [`logical`] scalar indicating if the Gaussian approximation of
#' the credible interval was used.
#' @slot counts A [`logical`] scalar.
#' @slot events An [`integer`] scalar giving the number of events included in
#' the tempo plot.
#' @slot hash A [`character`] string giving the 32-byte MD5 hash of the
#' original data file.
#' @section Coerce:
#' In the code snippets below, `x` is a `CumulativeEvents` object.
#' \describe{
#' \item{`as.data.frame(x)`}{Coerces to a [`data.frame`].}
#' }
#' @note
#' This class inherits from [`TimeSeries-class`].
#' @author N. Frerebeau
#' @family classes
#' @docType class
#' @aliases CumulativeEvents-class
#' @keywords internal
.CumulativeEvents <- setClass(
Class = "CumulativeEvents",
slots = c(
credible = "matrix",
gauss = "matrix",
level = "numeric",
counts = "logical",
events = "integer",
hash = "character"
),
contains = "TimeSeries"
)
# Activity =====================================================================
#' Activity
#'
#' An S4 class to store the result of an [`activity`] plot.
#' @slot hash A [`character`] string giving the 32-byte MD5 hash of the
#' original data file.
#' @section Coerce:
#' In the code snippets below, `x` is an `ActivityEvents` object.
#' \describe{
#' \item{`as.data.frame(x)`}{Coerces to a [`data.frame`].}
#' }
#' @note
#' This class inherits from [`TimeSeries-class`].
#' @author N. Frerebeau
#' @family classes
#' @docType class
#' @aliases ActivityEvents-class
#' @keywords internal
.ActivityEvents <- setClass(
Class = "ActivityEvents",
slots = c(
hash = "character"
),
contains = "TimeSeries"
)
# Occurrence ===================================================================
#' Occurrence
#'
#' An S4 class to store the result of an [`occurrence`] plot.
#' @slot events An [`integer`] vector giving the occurrence.
#' @slot start A [`numeric`] vector giving the lower boundaries of the
#' credibility interval.
#' @slot end A [`numeric`] vector giving the upper boundaries of the
#' credibility interval.
#' @slot level A length-one [`numeric`] vector giving the confidence level.
#' @slot hash A [`character`] string giving the 32-byte MD5 hash of the
#' original data file.
#' @section Coerce:
#' In the code snippets below, `x` is an `OccurrenceEvents` object.
#' \describe{
#' \item{`as.data.frame(x)`}{Coerces to a [`data.frame`].}
#' }
#' @author N. Frerebeau
#' @family classes
#' @docType class
#' @aliases OccurrenceEvents-class
#' @keywords internal
.OccurrenceEvents <- setClass(
Class = "OccurrenceEvents",
slots = c(
events = "integer",
start = "numeric",
end = "numeric",
level = "numeric",
hash = "character"
)
)
# Age-Depth Model ==============================================================
#' Age-Depth Model
#'
#' An S4 class to represents an age-depth model.
#' @slot depth A [`numeric`] vector giving the depth of the samples.
#' @slot model A [`list`] of local polynomial regressions
#' (see [stats::loess()]).
#' @slot hash A [`character`] string giving the 32-byte MD5 hash of the
#' original data file.
#' @author N. Frerebeau
#' @family classes
#' @docType class
#' @aliases AgeDepthModel-class
#' @keywords internal
.AgeDepthModel <- setClass(
Class = "AgeDepthModel",
slots = c(
depth = "numeric",
model = "list",
hash = "character"
)
)
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