#' Interactive Stacked Plots of Multichannel Sequences and/or Most Probable
#' Paths for Mixture Hidden Markov Models
#'
#' Function \code{mssplot} plots stacked sequence plots of observation sequences
#' and/or most probable hidden state paths for each model of the \code{mhmm}
#' object (model chosen according to the most probable path).
#'
#' @export
#'
#' @param x Mixture hidden Markov model object of class \code{mhmm}.
#'
#' @param ask If \code{TRUE} and \code{which.plots} is NULL, \code{plot.mhmm} operates in interactive mode, via \code{\link{menu}}. Defaults to \code{FALSE}.
#'
#' @param which.plots The number(s) of the requested model(s) as an integer vector. The default \code{NULL} produces all plots.
#'
#' @param hidden.paths Output from the \code{\link{hidden_paths}} function. The
#' default value \code{NULL} computes hidden paths automatically, if needed.
#'
#' @param plots What to plot. One of \code{"obs"} for observations (the default),
#' \code{"hidden.paths"} for most probable paths of hidden states,
#' or \code{"both"} for observations and hidden paths together.
#'
#' @param type The type of the plot. Available types are \code{"I"} for index
#' plots and \code{"d"} for state distribution plots (the default). See
#' \code{\link{seqplot}} for details.
#'
#' @param tlim Indexes of the subjects to be plotted (the default is 0,
#' i.e. all subjects are plotted). For example, \code{tlim = 1:10} plots
#' the first ten subjects in data.
#'
#' @param sortv A sorting variable or a sort method (one of \code{"from.start"},
#' \code{"from.end"}, \code{"mds.obs"}, or \code{"mds.hidden"}) for
#' \code{type = "I"}. The value \code{"mds.hidden"} is only available when
#' \code{which = "both"} and \code{which = "hidden.paths"}. Options \code{"mds.obs"} and
#' \code{"mds.hidden"} automatically arrange the sequences according to the
#' scores of multidimensional scaling (using \code{\link{cmdscale}}) for the
#' observed data or hidden states paths.
#' MDS scores are computed from distances/dissimilarities using a metric
#' defined in argument \code{dist.method}. See \code{\link{plot.stslist}} for
#' more details on \code{"from.start"} and \code{"from.end"}.
#'
#' @param sort.channel The number of the channel according to which the
#' \code{"from.start"} or \code{"from.end"} sorting is done. Sorting according
#' to hidden states is called with value 0. The default value is 1 (the first
#' channel).
#'
#' @param dist.method The metric to be used for computing the distances of the
#' sequences if multidimensional scaling is used for sorting. One of "OM"
#' (optimal matching, the default), "LCP" (longest common prefix), "RLCP"
#' (reversed LCP, i.e. longest common suffix), "LCS" (longest common
#' subsequence), "HAM" (Hamming distance), and "DHD" (dynamic Hamming distance).
#' Transition rates are used for defining substitution costs if needed. See
#' \code{\link[TraMineR]{seqdef}} for more information on the metrics.
#'
#' @param with.missing Controls whether missing states are included in state
#' distribution plots (\code{type = "d"}). The default is \code{FALSE}.
#'
#' @param missing.color Alternative color for representing missing values
#' in the sequences. By default, this color is taken from the \code{missing.color}
#' attribute of the sequence object.
#'
#' @param title A vector of main titles for the graphics. The default is \code{NA}: if
#' \code{title.n = TRUE}, the name of the cluster and the number of subjects is plotted.
#' \code{FALSE} prints no titles, even when \code{title.n = TRUE}.
#'
#' @param title.n Controls whether the number of subjects is printed in the main
#' titles of the plots. The default is \code{TRUE}: n is plotted if \code{title}
#' is anything but \code{FALSE}.
#'
#' @param cex.title Expansion factor for setting the size of the font for the main
#' titles. The default value is 1. Values lesser than 1 will reduce the size of
#' the font, values greater than 1 will increase the size.
#'
#' @param title.pos Controls the position of the main titles of the plots. The
#' default value is 1. Values greater than 1 will place the title higher.
#'
#' @param with.legend Defines if and where the legend for the states is plotted.
#' The default value \code{"auto"} (equivalent to \code{TRUE} and
#' \code{"right"}) creates separate legends for each requested plot and
#' positiones them on the right-hand side of the plot. Other possible values
#' are \code{"bottom"},
#' \code{"right.combined"}, and \code{"bottom.combined"}, of which the last
#' two create a combined legend in the selected position. \code{FALSE} prints no legend.
#'
#' @param ncol.legend (A vector of) the number of columns for the legend(s). The
#' default \code{"auto"} creates one column for each legend.
#'
#' @param with.missing.legend If set to \code{"auto"} (the default), a legend
#' for the missing state is added automatically if one or more of the
#' sequences in the data/channel contains missing states and \code{type = "I"}.
#' If \code{type = "d"} missing states are omitted from the legends unless
#' \code{with.missing = TRUE}. With the value \code{TRUE} a
#' legend for the missing state is added in any case; equivalently
#' \code{FALSE} omits the legend for the missing state.
#'
#' @param legend.prop Sets the proportion of the graphic area used for plotting
#' the legend when \code{with.legend} is not \code{FALSE}. The default value is
#' 0.3. Takes values from 0 to 1.
#'
#' @param cex.legend Expansion factor for setting the size of the font for the
#' labels in the legend. The default value is 1. Values lesser than 1 will
#' reduce the size of the font, values greater than 1 will increase the size.
#'
#' @param hidden.states.colors A vector of colors assigned to hidden states. The default
#' value \code{"auto"} uses the colors assigned to the \code{stslist} object (created
#' with \code{\link[TraMineR]{seqdef}}) if \code{hidden.paths} is given; otherwise colors from
#' \code{\link{colorpalette}} are automatically used.
#'
#' @param hidden.states.labels Labels for the hidden states. The default value
#' \code{"auto"} uses the names provided in \code{x$state_names} if \code{x} is
#' an \code{hmm} object; otherwise the number of the hidden state.
#'
#' @param xaxis Controls whether an x-axis is plotted below the plot at the
#' bottom. The default value is \code{TRUE}.
#'
#' @param xlab An optional label for the x-axis. If set to \code{NA}, no label
#' is drawn.
#'
#' @param xtlab Optional labels for the x-axis tick labels. If unspecified, the
#' column names of the \code{seqdata} sequence object are used (see
#' \code{\link[TraMineR]{seqdef}}).
#'
#' @param xlab.pos Controls the position of the x-axis label. The default value
#' is 1. Values greater than 1 will place the label further away from the plot.
#'
#' @param yaxis Controls whether or not to plot the y-axis. The default is \code{FALSE}.
#'
#' @param ylab Labels for the channels shown as labels for y-axes.
#' A vector of names for each channel
#' (observations). The default value \code{"auto"} uses the names provided in
#' \code{x$channel_names} if \code{x} is an \code{hmm} object; otherwise the
#' names of the list in \code{x} if given, or the
#' number of the channel if names are not given. \code{FALSE} prints no labels.
#'
#' @param hidden.states.title Optional label for the hidden state plot (in the
#' y-axis). The default is \code{"Hidden states"}.
#'
#' @param ylab.pos Controls the position of the y axis labels (labels for
#' channels and/or hidden states). Either \code{"auto"} or a numerical vector
#' indicating how far away from the plots the titles are positioned. The
#' default value \code{"auto"} positions all titles on line 1.
#' Shorter vectors are recycled.
#'
#' @param cex.lab Expansion factor for setting the size of the font for the axis
#' labels. The default value is 1. Values lesser than 1 will reduce the size
#' of the font, values greater than 1 will increase the size.
#'
#' @param cex.axis Expansion factor for setting the size of the font for the x-axis
#' tick labels. The default value is 1. Values lesser than 1 will reduce the size of
#' the font, values greater than 1 will increase the size.
#' @param respect_void If \code{TRUE} (default), states at the time points
#' corresponding to TraMineR's void in the observed sequences are set to void
#' in the hidden state sequences as well.
#'
#' @param ... Other arguments to be passed on to
#' \code{\link[TraMineR]{seqplot}}.
#'
#' @examples
#' # Loading mixture hidden Markov model (mhmm object)
#' # of the biofam data
#' data("mhmm_biofam")
#'
#' # Plotting the first cluster only
#' mssplot(mhmm_biofam, which.plots = 1)
#'
#' if (interactive()) {
#' # Interactive plot
#' mssplot(mhmm_biofam)
#' }
#'
#' @seealso \code{\link{build_mhmm}} and \code{\link{fit_model}} for building and
#' fitting mixture hidden Markov models, \code{\link{hidden_paths}} for
#' computing the most probable paths (Viterbi paths) of hidden states,
#' \code{\link{plot.mhmm}} for plotting \code{mhmm} objects as directed graphs, and
#' \code{\link{colorpalette}} for default colors.
#'
mssplot <- function(
x, ask = FALSE, which.plots = NULL, hidden.paths = NULL,
plots = "obs", type = "d", tlim = 0,
sortv = NULL, sort.channel = 1, dist.method = "OM",
with.missing = FALSE, missing.color = NULL,
title = NA, title.n = TRUE, cex.title = 1, title.pos = 1,
with.legend = "auto", ncol.legend = "auto",
with.missing.legend = "auto",
legend.prop = 0.3, cex.legend = 1,
hidden.states.colors = "auto", hidden.states.labels = "auto",
xaxis = TRUE, xlab = NA, xtlab = NULL, xlab.pos = 1,
ylab = "auto", hidden.states.title = "Hidden states",
yaxis = FALSE, ylab.pos = "auto",
cex.lab = 1, cex.axis = 1, respect_void = TRUE, ...) {
check_deprecated_args(match.call())
# Checking for class of x
if (!inherits(x, "mhmm")) {
stop("Your object x is not a mhmm object. Use build_mhmm to create one.")
}
oldPar <- par(no.readonly = TRUE)
on.exit(par(oldPar), add = TRUE)
oldWarn <- options("warn")
options(warn = 1)
on.exit(options(oldWarn), add = TRUE)
# ssp arguments (besides mhmm object and hidden.paths)
args <- as.list(match.call())[-(1:2)]
if ("ask" %in% names(args)) {
args <- args[-which(names(args) == "ask")]
}
if ("which.plots" %in% names(args)) {
args <- args[-which(names(args) == "which.plots")]
}
if ("hidden.paths" %in% names(args)) {
args <- args[-which(names(args) == "hidden.paths")]
}
if (!("title" %in% names(args))) {
titles <- x$cluster_names
} else {
if (length(title) == 1 && (is.na(title) || !title)) {
titles <- rep(title, x$n_clusters)
} else if (length(title) != x$n_clusters) {
warning("The length of the vector provided for the title argument does not match the number of clusters. Automatic titles were used instead.")
titles <- x$cluster_names
} else {
titles <- eval(args$title)
}
args <- args[-which(names(args) == "title")]
}
if (length(ylab) == 1 && ylab == "auto") {
args$ylab <- x$channel_names
}
if (is.null(hidden.paths)) {
hidden.paths <- suppressWarnings(suppressMessages((x, respect_void = respect_void)))
}
if (!("hidden.states.labels" %in% names(args))) {
hidden.states.labels <- unlist(x$state_names)
}
hidden.pathslabs <- list()
k <- 0
for (i in 1:x$n_clusters) {
hidden.pathslabs[[i]] <- hidden.states.labels[(k + 1):(k + x$n_states[i])]
k <- k + x$n_states[i]
}
n_alphabet <- length(alphabet(hidden.paths))
if (!("hidden.states.colors" %in% names(args))) {
if (n_alphabet <= 200) {
hidden.states.colors <- seqHMM::colorpalette[[n_alphabet]]
} else {
stop(
"Model contains ", n_alphabet, " hidden states, which ",
" is more than supported by the default color palette. Specify your ",
" own color palette with the argument 'hidden.states.colors'."
)
}
}
if (n_alphabet != length(hidden.states.colors)) {
stop(
"The number of hidden states is ", n_alphabet,
" but the supplied color palette contains only ",
length(hidden.states.colors), "colours."
)
}
hidden.pathscols <- list()
k <- 0
for (i in 1:x$n_clusters) {
hidden.pathscols[[i]] <- hidden.states.colors[(k + 1):(k + x$n_states[i])]
k <- k + unname(x$n_states[i])
}
# Clusters determined by hidden_paths
hp_by_cluster_logic <- rep(list(NULL), x$n_clusters)
hp_by_cluster <- rep(list(NULL), x$n_clusters)
mm <- NULL
for (i in 1:x$n_clusters) {
# Find matching cluster names from the first hidden state of each individual
if (length(unique(unlist(x$state_names))) == length(unlist(x$state_names))) {
hp_by_cluster_logic[[i]] <- hidden.paths[, 1] %in% x$state_names[[i]]
} else {
hp_by_cluster_logic[[i]] <- grepl(paste0(x$cluster_names[i], ":"), hidden.paths[, 1])
}
hp_by_cluster[[i]] <- hidden.paths[hp_by_cluster_logic[[i]], ]
# Give a warning, if no subjects assigned to cluster
if (sum(hp_by_cluster_logic[[i]]) == 0) {
mm <- c(mm, i)
}
}
if (length(mm) > 0) {
warning(paste("When computing the most probable paths, no subjects were assigned to following clusters:", paste(x$cluster_names[mm], collapse = ", ")))
}
if (!is.null(which.plots)) {
if (any(!is.numeric(which.plots)) || any(!(which.plots %in% 1:x$n_clusters))) {
stop(paste0("The which.plot argument only accepts numerical values between 1 and ", x$n_clusters, "."))
} else if (any(which.plots %in% mm)) {
warning("You requested cluster(s) with no subjects. Plotting only relevant clusters.")
which.plots <- setdiff(which.plots, mm)
}
} else if (!ask && is.null(which.plots)) {
which.plots <- 1:x$n_clusters
# removing clusters with no subjects (according to hidden.paths)
which.plots <- setdiff(which.plots, mm)
}
if (x$n_channels == 1) {
x$observations <- list(x$observations)
}
if (ask && is.null(which.plots)) {
tmenu <- 1:x$n_clusters
tmenu <- setdiff(tmenu, mm)
tmenunames <- x$cluster_names[tmenu]
plot.new()
repeat {
pick <- menu(tmenunames, title = "\n Select cluster (or 0 to exit):\n")
if (pick == 0) {
return(invisible())
} else {
args$x <- lapply(x$observations, function(y) y[hp_by_cluster_logic[[pick]], ])
if (plots != "obs") {
args$hidden.states.labels <- hidden.pathslabs[[pick]]
args$hidden.paths <- hp_by_cluster[[pick]]
states <- paste(
x$cluster_names[pick],
x$state_names[[pick]],
sep = ":"
)
attr(args$hidden.paths, "alphabet") <- states
if (attr(args$hidden.paths, "nr") %in% levels(args$hidden.paths[[1]])) {
states <- c(states, attr(args$hidden.paths, "nr"))
}
if (attr(args$hidden.paths, "void") %in% levels(args$hidden.paths[[1]])) {
states <- c(states, attr(args$hidden.paths, "void"))
}
args$hidden.paths[] <- lapply(
args$hidden.paths, factor, levels = states
)
attr(args$hidden.paths, "labels") <- args$hidden.states.labels
attr(args$hidden.paths, "cpal") <- hidden.pathscols[[pick]]
args$hidden.states.colors <- hidden.pathscols[[pick]]
if (!is.null(sortv) && sortv == "mds.hidden") {
if (length(args$hidden.states.labels) == 1) {
args$sortv <- "mds.obs"
} else {
args$sortv <- "mds.hidden"
}
}
}
args$title <- titles[tmenu[pick]]
do.call(ssplotM, args = args)
}
}
} else if (ask && !is.null(which.plots)) {
tmenu <- which.plots
tmenunames <- x$cluster_names[which.plots]
plot.new()
repeat {
pick <- menu(tmenunames, title = "\n Select cluster (or 0 to exit):\n")
if (pick == 0) {
return(invisible())
} else {
args$x <- lapply(x$observations, function(y) y[hp_by_cluster_logic[[pick]], ])
if (plots != "obs") {
args$hidden.states.labels <- hidden.pathslabs[[pick]]
args$hidden.paths <- hp_by_cluster[[pick]]
states <- paste(
x$cluster_names[pick],
x$state_names[[pick]],
sep = ":"
)
attr(args$hidden.paths, "alphabet") <- states
if (attr(args$hidden.paths, "nr") %in% levels(args$hidden.paths[[1]])) {
states <- c(states, attr(args$hidden.paths, "nr"))
}
if (attr(args$hidden.paths, "void") %in% levels(args$hidden.paths[[1]])) {
states <- c(states, attr(args$hidden.paths, "void"))
}
args$hidden.paths[] <- lapply(
args$hidden.paths, factor, levels = states
)
attr(args$hidden.paths, "labels") <- args$hidden.states.labels
attr(args$hidden.paths, "cpal") <- hidden.pathscols[[pick]]
args$hidden.states.colors <- hidden.pathscols[[pick]]
if (!is.null(sortv) && sortv == "mds.hidden") {
if (length(args$hidden.states.labels) == 1) {
args$sortv <- "mds.obs"
} else {
args$sortv <- "mds.hidden"
}
}
}
args$title <- titles[tmenu[pick]]
do.call(ssplotM, args = args)
}
}
} else {
ask <- length(which.plots) > 1
plot.new()
for (i in which.plots) {
args$x <- lapply(x$observations, function(y) y[hp_by_cluster_logic[[i]], ])
if (plots != "obs") {
args$hidden.paths <- hp_by_cluster[[i]]
states <- paste(
x$cluster_names[i],
x$state_names[[i]],
sep = ":"
)
attr(args$hidden.paths, "alphabet") <- states
if (attr(args$hidden.paths, "nr") %in% levels(args$hidden.paths[[1]])) {
states <- c(states, attr(args$hidden.paths, "nr"))
}
if (attr(args$hidden.paths, "void") %in% levels(args$hidden.paths[[1]])) {
states <- c(states, attr(args$hidden.paths, "void"))
}
args$hidden.paths[] <- lapply(
args$hidden.paths, factor, levels = states
)
args$hidden.states.labels <- hidden.pathslabs[[i]]
attr(args$hidden.paths, "labels") <- args$hidden.states.labels
attr(args$hidden.paths, "cpal") <- hidden.pathscols[[i]]
args$hidden.states.colors <- hidden.pathscols[[i]]
if (!is.null(sortv) && sortv == "mds.hidden") {
if (length(args$hidden.states.labels) == 1) {
args$sortv <- "mds.obs"
} else {
args$sortv <- "mds.hidden"
}
}
}
args$title <- titles[i]
do.call(ssplotM, args = args)
if (ask) {
op <- par(ask = TRUE)
}
}
# par(ask = FALSE)
}
invisible()
}
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