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plot.R
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plot.R
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#' @export
Plot <- R6::R6Class(
"Plot",
public = list(
history = NULL,
cumulative = function(history,
regret = TRUE,
disp = NULL,
plot_only_disp = FALSE,
rate = FALSE,
interval = 1,
traces = FALSE,
traces_max = 100,
traces_alpha = 0.3,
smooth = FALSE,
no_par = FALSE,
xlim = NULL,
ylim = NULL,
xlab = NULL,
ylab = NULL,
legend = TRUE,
log = "",
use_colors = TRUE,
color_step = 1,
lty_step = 1,
lwd = 2,
legend_labels = NULL,
legend_border = NULL,
legend_position = "topleft",
legend_title = NULL,
limit_agents = NULL,
limit_context = NULL,
trunc_over_agents = TRUE,
trunc_per_agent = TRUE) {
self$history <- history
if (regret) {
if (rate) {
ylab_title <- "Cumulative regret rate"
line_data_name <- "cum_regret_rate"
disp_data_name <- "cum_regret_rate_none"
} else {
ylab_title <- "Cumulative regret"
line_data_name <- "cum_regret"
disp_data_name <- "cum_regret_none"
}
} else {
if (rate) {
ylab_title <- "Cumulative reward rate"
line_data_name <- "cum_reward_rate"
disp_data_name <- "cum_reward_rate_none"
} else {
ylab_title <- "Cumulative reward"
line_data_name <- "cum_reward"
disp_data_name <- "cum_reward_none"
}
}
private$do_plot(
line_data_name = line_data_name,
disp_data_name = disp_data_name,
ylab_title = ylab_title,
use_colors = use_colors,
log = log,
legend = legend,
disp = disp,
plot_only_disp = plot_only_disp,
no_par = no_par,
interval = interval,
color_step = color_step,
lty_step = lty_step,
lwd = lwd,
xlim = xlim,
ylim = ylim,
xlab = xlab,
ylab = ylab,
legend_labels = legend_labels,
legend_border = legend_border,
legend_position = legend_position,
legend_title = legend_title,
limit_agents = limit_agents,
limit_context = limit_context,
traces = traces,
traces_max = traces_max,
traces_alpha = traces_alpha,
smooth = smooth,
rate = rate,
trunc_over_agents = trunc_over_agents,
trunc_per_agent = trunc_per_agent
)
invisible(recordPlot())
},
optimal = function(history,
disp = NULL,
plot_only_disp = FALSE,
rate = FALSE,
interval = 1,
traces = FALSE,
traces_max = 100,
traces_alpha = 0.3,
smooth = FALSE,
no_par = FALSE,
xlim = NULL,
ylim = NULL,
xlab = NULL,
ylab = NULL,
legend = TRUE,
use_colors = TRUE,
log = "",
color_step = 1,
lty_step = 1,
lwd = 2,
legend_labels = NULL,
legend_border = NULL,
legend_position = "topleft",
legend_title = NULL,
limit_agents = NULL,
limit_context = NULL,
trunc_over_agents = TRUE,
trunc_per_agent = TRUE) {
self$history <- history
ylab_title <- "Optimal action"
line_data_name <- "optimal"
disp_data_name <- "optimal_none"
private$do_plot(
line_data_name = line_data_name,
disp_data_name = disp_data_name,
ylab_title = ylab_title,
use_colors = use_colors,
log = log,
legend = legend,
disp = disp,
plot_only_disp = plot_only_disp,
no_par = no_par,
interval = interval,
color_step = color_step,
lty_step = lty_step,
lwd = lwd,
xlim = xlim,
ylim = ylim,
legend_labels = legend_labels,
legend_border = legend_border,
legend_position = legend_position,
legend_title = legend_title,
limit_agents = limit_agents,
limit_context = limit_context,
traces = traces,
traces_max = traces_max,
traces_alpha = traces_alpha,
smooth = smooth,
trunc_over_agents = trunc_over_agents,
trunc_per_agent = trunc_per_agent
)
invisible(recordPlot())
},
average = function(history,
regret = TRUE,
disp = NULL,
plot_only_disp = FALSE,
rate = FALSE,
interval = 1,
traces = FALSE,
traces_max = 100,
traces_alpha = 0.3,
smooth = FALSE,
no_par = FALSE,
xlim = NULL,
ylim = NULL,
xlab = NULL,
ylab = NULL,
legend = TRUE,
use_colors = TRUE,
log = "",
color_step = 1,
lty_step = 1,
lwd = 2,
cum_average = FALSE,
legend_labels = NULL,
legend_border = NULL,
legend_position = "topleft",
legend_title = NULL,
limit_agents = NULL,
limit_context = NULL,
trunc_over_agents = TRUE,
trunc_per_agent = TRUE) {
self$history <- history
if (regret) {
ylab_title <- "Average regret"
line_data_name <- "regret"
disp_data_name <- "regret_none"
} else {
ylab_title <- "Average reward"
line_data_name <- "reward"
disp_data_name <- "reward_none"
}
private$do_plot(
line_data_name = line_data_name,
disp_data_name = disp_data_name,
ylab_title = ylab_title,
use_colors = use_colors,
log = log,
legend = legend,
disp = disp,
plot_only_disp = plot_only_disp,
no_par = no_par,
interval = interval,
color_step = color_step,
lty_step = lty_step,
lwd = lwd,
xlim = xlim,
ylim = ylim,
xlab = xlab,
ylab = ylab,
legend_labels = legend_labels,
legend_border = legend_border,
legend_position = legend_position,
legend_title = legend_title,
cum_average = cum_average,
limit_agents = limit_agents,
limit_context = limit_context,
traces = traces,
traces_max = traces_max,
traces_alpha = traces_alpha,
smooth = smooth,
rate = rate,
trunc_over_agents = trunc_over_agents,
trunc_per_agent = trunc_per_agent
)
invisible(recordPlot())
},
arms = function(history,
no_par = FALSE,
legend = TRUE,
use_colors = TRUE,
log = "",
interval = 1,
xlim = NULL,
ylim = NULL,
xlab = NULL,
ylab = NULL,
legend_labels = NULL,
legend_border = NULL,
legend_position = "bottomright",
legend_title = NULL,
limit_context = NULL,
smooth = FALSE,
trunc_over_agents = TRUE,
limit_agents = NULL) {
self$history <- history
if (!isTRUE(no_par)) {
dev.hold()
old.par <- par(no.readonly = TRUE)
par(mar = c(5, 5, 1, 1))
}
if(!is.null(limit_context)) {
dt <- self$history$get_data_table(
limit_cols = c("agent", "t", "choice", "sim", limit_context),
limit_agents = limit_agents,
interval = interval
)
dt <- dt[dt[, Reduce(`|`, lapply(.SD, `==`, 1)),.SDcols = limit_context],]
} else {
dt <- self$history$get_data_table(
limit_cols = c("agent", "t", "choice", "sim"),
limit_agents = limit_agents,
interval = interval
)
}
if(isTRUE(trunc_over_agents)) {
min_t_sim <- min(dt[,max(t), by = c("agent","sim")]$V1)
dt <- dt[t<=min_t_sim]
}
ylab_title <- "Arm choice %"
agent_levels <- levels(droplevels(dt$agent))
if (length(agent_levels) > 1) {
warning(strwrap(
prefix = " ", initial = "",
"## Arm percentage plot always plots the results of one agent, either at
index position one, or the first agent specified in limit_agents."
),
call. = FALSE
)
}
dt <- dt[agent == agent_levels[1]]
dt$agent <- NULL
data.table::setkey(dt, t, choice)
data <- dt[data.table::CJ(t, choice, unique = TRUE), list(arm_count = .N), by = .EACHI]
#data <- dt[, list(arm_count = .N), by = list(t, choice)]
max_sim <- dt[, max(sim)]
max_t <- dt[, max(t)]
arm_levels <- levels(as.factor(data$choice))
max_arm <- length(arm_levels)
N <- dt[,.N,by=c("t")]$N
N <- rep(N,each=max_arm)
data$arm_count <- as.double((unlist(data$arm_count, FALSE, FALSE) / N) * 100L)
eg <- expand.grid(t = dt[sim == 1]$t, choice = seq(1.0, max_arm, 1))
data <- merge(data, eg, all = TRUE)
# turn NA into 0
for (j in seq_len(ncol(data)))
set(data,which(is.na(data[[j]])),j,0)
data$dataum <- ave(data$arm_count, data$t, FUN = cumsum)
data$zero <- 0.0
min_ylim <- 0
max_ylim <- 100
if (isTRUE(smooth)) {
for (arm in arm_levels) {
data[data$choice == arm, c("t", "dataum") :=
supsmu(data[data$choice == arm]$t, data[data$choice == arm]$dataum, bass = 9)]
}
}
data.table::setorder(data, choice, t)
plot.new()
if (!is.null(xlim)) {
min_xlim <- xlim[1]
max_xlim <- xlim[2]
} else {
min_xlim <- 1
max_xlim <- data[, max(t)]
}
if (!is.null(ylim)) {
min_ylim <- ylim[1]
max_ylim <- ylim[2]
}
plot.window(
xlim = c(min_xlim, max_xlim),
ylim = c(min_ylim, max_ylim)
)
if (isTRUE(use_colors)) {
cl <- private$gg_color_hue(length(arm_levels))
} else {
cl <- gray.colors(length(arm_levels))
}
color <- 1
polygon(
c(data[data$choice == 1]$t, rev(data[data$choice == 1]$t)),
c(data[data$choice == 1]$dataum, rev(data[data$choice == 1]$zero)),
col = adjustcolor(cl[color], alpha.f = 0.6),
border = NA
)
color <- 2
for (arm_nr in c(2:length(arm_levels))) {
polygon(
c(data[data$choice == arm_nr]$t, rev(data[data$choice == arm_nr]$t)),
c(data[data$choice == arm_nr - 1]$dataum, rev(data[data$choice == arm_nr]$dataum)),
col = adjustcolor(cl[color], alpha.f = 0.6),
border = NA
)
color <- color + 1
}
if (is.null(legend_title)) {
legend_title <- agent_levels[1]
if(!is.null(limit_context))
legend_title <- paste(legend_title,limit_context)
}
if (is.null(legend_position)) {
legend_position <- "bottomright"
}
if (!is.null(legend_labels)) {
legend_labels <- legend_labels
} else {
legend_labels <- paste("arm", arm_levels, sep = " ")
}
axis(1)
axis(2)
title(xlab = "Time Step")
title(ylab = ylab_title)
box()
if (legend) {
legend(
legend_position,
NULL,
legend_labels,
col = adjustcolor(cl, alpha.f = 0.6),
title = legend_title,
pch = 15,
pt.cex = 1.2,
bg = "white",
inset = c(0.08, 0.1)
)
}
if (!isTRUE(no_par)) {
dev.flush()
par(old.par)
}
invisible(recordPlot())
}
),
private = list(
cum_average = function(cx) {
cx <- c(0,cx)
cx[(2):length(cx)] - cx[1:(length(cx) - 1)]
},
do_plot = function(line_data_name = line_data_name,
disp_data_name = disp_data_name,
disp = NULL,
plot_only_disp = FALSE,
ylab_title = NULL,
use_colors = FALSE,
log = "",
legend = TRUE,
no_par = FALSE,
xlim = NULL,
ylim = NULL,
xlab = NULL,
ylab = NULL,
interval = 1,
color_step = 1,
lty_step = 1,
lwd = 2,
legend_labels = NULL,
legend_border = NULL,
legend_position = "topleft",
legend_title = NULL,
limit_agents = NULL,
limit_context = NULL,
traces = NULL,
traces_max = 100,
traces_alpha = 0.3,
cum_average = FALSE,
smooth = FALSE,
rate = FALSE,
trunc_over_agents = TRUE,
trunc_per_agent = TRUE) {
cum_flip <- FALSE
if((line_data_name=="reward" || line_data_name=="regret") && isTRUE(cum_average)) {
line_data_name <- paste0("cum_",line_data_name)
cum_flip = TRUE
}
if (interval==1 && as.integer(self$history$meta$sim$max_t) > 1850) {
interval <- ceiling(as.integer(self$history$meta$sim$max_t)/1850) # nocov
if(isTRUE(cum_average) && isTRUE(cum_flip)) {
warning(strwrap(
prefix = " ", initial = "",
paste0("## As cum_reward was set to TRUE while plotting more than 1850 time steps,
the reward plot has been smoothed automatically using a window length of ",interval,
" timesteps.")
),
call. = FALSE
)
}
}
if (!is.null(disp) && disp %in% c("sd", "var", "ci")) {
disp_data_name <- gsub("none", disp, disp_data_name)
data <-
self$history$get_cumulative_data(
limit_cols = c("agent", "t", "sims", line_data_name, disp_data_name),
limit_agents = limit_agents,
interval = interval
)
} else {
disp <- NULL
data <-
self$history$get_cumulative_data(
limit_cols = c("agent", "t", "sims", line_data_name),
limit_agents = limit_agents,
interval = interval
)
}
agent_levels <- levels(droplevels(data$agent))
n_agents <- length(agent_levels)
# turn NA into 0
for (j in seq_len(ncol(data)))
data.table::set(data,which(is.na(data[[j]])),j,0)
if(isTRUE(trunc_per_agent)) {
data <- data[data$sims == max(data$sims)]
}
if(isTRUE(trunc_over_agents)) {
min_t_sim <- min(data[,max(t), by = c("agent")]$V1)
data <- data[t<=min_t_sim]
}
if (!is.null(xlim)) {
min_xlim <- xlim[1]
max_xlim <- xlim[2]
} else {
min_xlim <- 1
max_xlim <- data[, max(t)]
}
data.table::setorder(data, agent, t)
if(cum_flip==TRUE) {
if (line_data_name == "cum_reward") {
line_data_name <- "reward"
for (agent_name in agent_levels) {
data[data$agent == agent_name,
reward := private$cum_average(data[data$agent == agent_name]$cum_reward)/interval]
}
} else {
line_data_name <- "cum_regret"
for (agent_name in agent_levels) {
data[data$agent == agent_name,
regret := private$cum_average(data[data$agent == agent_name]$cum_regret)/interval]
}
}
}
if(!is.null(xlim)) data <- data[t>=xlim[1] & t<=xlim[2]]
if(!is.null(limit_context)) {
data <- data[data[, Reduce(`|`, lapply(.SD, `==`, 1)),.SDcols = sel],]
}
data.table::setorder(data, agent, t)
if (isTRUE(smooth)) {
for (agent_name in agent_levels) {
data[data$agent == agent_name, c("t", line_data_name) :=
supsmu(data[data$agent == agent_name]$t, data[data$agent == agent_name][[line_data_name]])]
if (!is.null(disp)) {
data[data$agent == agent_name, c("t", disp_data_name) :=
supsmu(data[data$agent == agent_name]$t, data[data$agent == agent_name][[disp_data_name]])]
}
}
}
if (!isTRUE(no_par)) {
dev.hold()
old.par <- par(no.readonly = TRUE)
par(mar = c(5, 5, 1, 1))
}
if (!is.null(disp) && !isTRUE(plot_only_disp)) {
disp_range <- data[[line_data_name]] + outer(data[[disp_data_name]], c(1, -1))
data <- cbind(data, disp_range)
colnames(data)[colnames(data) == "V2"] <- "disp_lower"
colnames(data)[colnames(data) == "V1"] <- "disp_upper"
}
if (isTRUE(plot_only_disp)) {
if(is.null(disp)) stop("Need to set disp to 'var','sd' or 'ci' when plot_only_disp is TRUE",
call. = FALSE)
line_data_name = disp_data_name
}
plot.new()
cl <- private$gg_color_hue(round(n_agents / color_step))
cl <- rep(cl, round(color_step))
if (lty_step > 1) {
lt <- rep(1:round(lty_step), each = round(n_agents / lty_step))
} else {
lt <- rep(1, n_agents)
}
if (!isTRUE(use_colors) && lty_step == 1) {
lty_step <- n_agents
lt <- rep(1:round(lty_step), each = round(n_agents / lty_step))
}
if (!is.null(disp) && !isTRUE(plot_only_disp) &&
!is.na(data[, min(disp_lower)]) && !is.na(data[, min(disp_upper)])) {
min_ylim <- data[, min(disp_lower)]
max_ylim <- data[, max(disp_upper)]
} else {
min_ylim <- data[, min(data[[line_data_name]])]
max_ylim <- data[, max(data[[line_data_name]])]
}
if (!is.null(ylim)) {
min_ylim <- ylim[1]
max_ylim <- ylim[2]
}
plot.window(
xlim = c(min_xlim, max_xlim),
ylim = c(min_ylim, max_ylim),
log = log
)
if (isTRUE(traces) && !isTRUE(plot_only_disp)) {
dt <- self$history$get_data_table(limit_agents = limit_agents, interval = interval)
data.table::setorder(dt, agent, sim, t)
for (agent_name in agent_levels) {
agent_sims <- unique(dt[dt$agent == agent_name]$sim)
for (as in head(agent_sims, traces_max)) {
Sys.sleep(0)
if (isTRUE(smooth)) {
lines(supsmu(
dt[dt$agent == agent_name & dt$sim == as]$t,
dt[dt$agent == agent_name & dt$sim == as][[line_data_name]]
),
lwd = lwd,
col = rgb(0.8, 0.8, 0.8, traces_alpha)
)
} else {
lines(dt[dt$agent == agent_name & dt$sim == as]$t,
dt[dt$agent == agent_name &
dt$sim == as][[line_data_name]],
lwd = lwd,
col = rgb(0.8, 0.8, 0.8, traces_alpha)
)
}
}
}
}
if (isTRUE(use_colors)) {
if (!is.null(disp) && !isTRUE(plot_only_disp)) {
color <- 1
for (agent_name in agent_levels) {
polygon(
c(data[data$agent == agent_name]$t, rev(data[data$agent == agent_name]$t)),
c(data[data$agent == agent_name]$disp_lower, rev(data[data$agent == agent_name]$disp_upper)),
col = adjustcolor(cl[color], alpha.f = 0.3),
border = NA
)
color <- color + 1
}
}
line_counter <- 1
for (agent_name in agent_levels) {
lines(
data[data$agent == agent_name]$t,
data[data$agent == agent_name][[line_data_name]],
lwd = lwd,
lty = lt[line_counter],
col = adjustcolor(cl[line_counter], alpha.f = 0.9),
type = "l"
)
line_counter <- line_counter + 1
}
} else {
line_counter <- 1
for (agent_name in agent_levels) {
if (!is.null(disp) && !isTRUE(plot_only_disp)) {
polygon(
c(data[data$agent == agent_name]$t, rev(data[data$agent == agent_name]$t)),
c(data[data$agent == agent_name]$disp_lower, rev(data[data$agent == agent_name]$disp_upper)),
col = rgb(0.8, 0.8, 0.8, 0.4),
border = NA
)
}
lines(
data[data$agent == agent_name]$t,
data[data$agent == agent_name][[line_data_name]],
lwd = lwd,
lty = lt[line_counter],
col = rgb(0.2, 0.2, 0.2, 0.8),
type = "l"
)
line_counter <- line_counter + 1
}
}
axis(1)
axis(2)
if (is.null(xlab)) xlab = "Time step"
title(xlab = xlab)
if(isTRUE(plot_only_disp)) ylab_title <- paste0(ylab_title,": ",disp)
if (is.null(ylab)) ylab = ylab_title
title(ylab = ylab)
box()
if (legend) {
if (!is.null(legend_labels)) {
agent_levels <- legend_labels
}
if (!is.null(legend_border)) {
bty <- "n"
} else {
bty <- "o"
}
if (!isTRUE(use_colors)) {
cl <- rgb(0.2, 0.2, 0.2, 0.8)
}
legend(
legend_position,
NULL,
agent_levels,
col = cl,
title = legend_title,
lwd = lwd,
lty = lt,
bty = bty,
bg = "white"
)
}
if (!isTRUE(no_par)) {
dev.flush()
par(old.par)
}
},
gg_color_hue = function(n) {
hues <- seq(15, 375, length = n + 1)
hcl(h = hues, l = 65, c = 100)[1:n]
}
)
)
#' Plot
#'
#' Generates plots from \code{\link{History}} data.
#'
#' Usually not instantiated directly but invoked by calling the generic \code{plot(h)}, where \code{h}
#' is an \code{\link{History}} class instance.
#'
#' @name Plot
#' @aliases average optimal arms do_plot gg_color_hue check_history_data
#'
#' @section Usage:
#' \preformatted{
#' Plot <- Plot$new()
#' }
#'
#' @section Methods:
#'
#' \describe{
#'
#' \item{\code{cumulative(history,...)}}{
#' Plots cumulative regret or reward (depending on parameter regret=TRUE/FALSE) over time.
#' }
#' \item{\code{average(history,...)}}{
#' Plots average regret or reward (depending on parameter regret=TRUE/FALSE) over time.
#' }
#' \item{\code{arms(history),...}}{
#' Plot the percentage of simulations per time step each arm was chosen over time.
#' If multiple agents have been run, plots only the first agent.
#' }
#' }
#'
#' @section Plot method arguments:
#'
#' \describe{
#' \item{\code{type}}{
#' \code{(character, "cumulative")} Can be either "cumulative" (default), "average", or "arms".
#' Sets the plot method when Plot() is called through R's generic plot() function.
#' Methods are descrived in the Methods section above.
#' }
#' \item{\code{regret}}{
#' \code{(logical, TRUE)} Plot policy regret (default, TRUE) or reward (FALSE)?
#' }
#' \item{\code{rate}}{
#' (\code{logical, TRUE)} If rate is TRUE, the rate of regret or reward is plotted.
#' }
#' \item{\code{limit_agents}}{
#' \code{(list , NULL)} Limit plotted agents to the agents in the list.
#' }
#' \item{\code{limit_context}}{
#' \code{(character vector , NULL)} Only plots data where context feature name(s) in vector equal to one.
#' }
#' \item{\code{no_par}}{
#' \code{(logical, FALSE)} If no_par is TRUE, Plot() does not set or adjust plotting parameters itself.
#' This makes it possible to set custom plotting parameters through R's par() function.
#' }
#' \item{\code{legend}}{
#' \code{(logical, TRUE)} Shows the legend when TRUE (default).
#' }
#' \item{\code{legend_title}}{
#' \code{(character , NULL)} Sets a custom legend title.
#' }
#' \item{\code{legend_labels}}{
#' \code{(character list , NULL)} Sets legend labels to custom values as specified in list.
#' }
#' \item{\code{legend_border}}{
#' \code{(logical , NULL)} When TRUE, the legend is borderless.
#' }
#' \item{\code{legend_position}}{
#' \code{(character , "topleft")} a single keyword from the list "bottomright", "bottom", "bottomleft",
#' "left", "topleft", "top", "topright", "right" and "center". This places the legend on the inside of
#' the plot frame at the given location.
#' }
#' \item{\code{xlim}}{
#' \code{(c(integer,integer), NULL)} Sets x-axis limits.
#' }
#' \item{\code{ylim}}{
#' \code{(c(integer,integer), NULL)} Sets y-axis limits.
#' }
#' \item{\code{log}}{
#' \code{(character , "")} A character string which contains "x" if the x axis is to be logarithmic,
#' "y" if the y axis is to be logarithmic and "xy" or "yx" if both axes are to be logarithmic.
#' }
#' \item{\code{use_colors}}{
#' \code{(logical, TRUE)} If use_colors is FALSE, plots will be in grayscale.
#' Otherwise, plots will make use of a color palette (default).
#' }
#' \item{\code{disp}}{
#' \code{(character, NULL)} When disp (for "dispersion measure") is set to either 'var','sd' or 'ci',
#' the variance, standard deviation, or 95% confidence interval will be added to the plot(s).
#' }
#' \item{\code{plot_only_disp}}{
#' \code{(logical, FALSE)} When TRUE and disp is either 'var','sd' or 'ci', plot only dispersion measure.
#' }
#' \item{\code{traces}}{
#' \code{(logical , FALSE)} Plot traces of independent simulations (default is FALSE).
#' }
#' \item{\code{traces_max}}{
#' \code{(integer , 100)} The number of trace lines.
#' }
#' \item{\code{traces_alpha}}{
#' \code{(numeric , 0.3)} Opacity of the trace lines. Default is 0.3 - that is, an opacity of 30%.
#' }
#' \item{\code{smooth}}{
#' \code{(logical , FALSE)} Smooth the plot (default is FALSE)
#' }
#' \item{\code{interval}}{
#' \code{(integer, NULL)} Plot only every t%%interval==0 data point.
#' }
#' \item{\code{cum_average}}{
#' \code{(logical , FALSE)} Calculates moving average from cum_reward or cum_regret with step
#' size \code{interval}.
#' }
#' \item{\code{color_step}}{
#' \code{(integer, 1)} When > 1, the plot cycles through \code{nr_agents/color_step} colors.
#' }
#' \item{\code{lty_step}}{
#' \code{(integer, 1)} When > 1, the plot cycles through \code{nr_agents/lty_step} line types.
#' }
#' \item{\code{lwd}}{
#' \code{(integer, 1)} Line width.
#' }
#' \item{\code{xlab}}{
#' \code{(character, NULL)} a title for the x axis
#' }
#' \item{\code{ylab}}{
#' \code{(character, NULL)} a title for the y axis
#' }
#' \item{\code{trunc_over_agents}}{
#' \code{(logical , TRUE)} Truncate the chart to the agent with the fewest time steps t.
#' }
#' \item{\code{trunc_per_agent}}{
#' \code{(logical , TRUE)} Truncate every agent's plot to the number of time steps that have been fully
#' simulated. That is, time steps for which the number of simulations equals the number defined in
#' \code{\link{Simulator}}'s \code{simulations} parameter.
#' }
#' }
#'
#'
#' @seealso
#'
#' Core contextual classes: \code{\link{Bandit}}, \code{\link{Policy}}, \code{\link{Simulator}},
#' \code{\link{Agent}}, \code{\link{History}}, \code{\link{Plot}}
#'
#' Bandit subclass examples: \code{\link{BasicBernoulliBandit}}, \code{\link{ContextualLogitBandit}},
#' \code{\link{OfflineReplayEvaluatorBandit}}
#'
#' Policy subclass examples: \code{\link{EpsilonGreedyPolicy}}, \code{\link{ContextualLinTSPolicy}}
#'
#' @examples
#' \dontrun{
#'
#' bandit <- ContextualPrecachingBandit$new(weights = c(0.9, 0.1, 0.1))
#'
#' agents <- list(Agent$new(RandomPolicy$new(), bandit),
#' Agent$new(OraclePolicy$new(), bandit),
#' Agent$new(ThompsonSamplingPolicy$new(1.0, 1.0), bandit),
#' Agent$new(Exp3Policy$new(0.1), bandit),
#' Agent$new(GittinsBrezziLaiPolicy$new(), bandit),
#' Agent$new(UCB1Policy$new(), bandit))
#'
#' history <- Simulator$new(agents, horizon = 100, simulations = 1000)$run()
#'
#' par(mfrow = c(3, 2), mar = c(1, 4, 2, 1), cex=1.3)
#'
#' plot(history, type = "cumulative", use_colors = FALSE, no_par = TRUE, legend_border = FALSE,
#' limit_agents = c("GittinsBrezziLai", "UCB1","ThompsonSampling"))
#'
#' plot(history, type = "cumulative", regret = FALSE, legend = FALSE,
#' limit_agents = c("UCB1"), traces = TRUE, no_par = TRUE)
#'
#' plot(history, type = "cumulative", regret = FALSE, rate = TRUE, disp = "sd",
#' limit_agents = c("Exp3", "ThompsonSampling"),
#' legend_position = "bottomright", no_par = TRUE)
#'
#' plot(history, type = "cumulative", rate = TRUE, plot_only_disp = TRUE,
#' disp = "var", smooth = TRUE, limit_agents = c("UCB1", "GittinsBrezziLai"),
#' legend_position = "bottomleft", no_par = TRUE)
#'
#' plot(history, type = "average", disp = "ci", regret = FALSE, interval = 10,
#' smooth = TRUE, legend_position = "bottomright", no_par = TRUE, legend = FALSE)
#'
#' plot(history, limit_agents = c("ThompsonSampling"), type = "arms",
#' interval = 20, no_par = TRUE)
#'
#' }
#'
#'
NULL