% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ggInterval_radarplot.R
\name{ggInterval_radarplot}
\alias{ggInterval_radarplot}
\title{Radar plot for symbolic data}
\usage{
ggInterval_radarplot(data=NULL,layerNumber=3,
inOneFig=TRUE,showLegend=TRUE,showXYLabs=FALSE,
plotPartial=NULL,
alpha=0.5,
base_circle=TRUE,
base_lty=2,
addText=TRUE,
type="default",
quantileNum=4,
Drift=0.5,
addText_modal=TRUE,
addText_modal.p=FALSE)
}
\arguments{
\item{data}{A ggInterval object. It can also be either RSDA object or
classical data frame(not recommended),which will be automatically convert to ggInterval
data.}

\item{layerNumber}{Number of concentric guide layers in the radar display.}

\item{inOneFig}{Logical. If \code{TRUE}, draw all selected observations in
one figure. Otherwise, generate separate figures for the selected
observations.}

\item{showLegend}{Logical. Whether to show the legend.}

\item{showXYLabs}{Logical. Whether to show the x- and y-axis labels.}

\item{plotPartial}{Numeric vector giving the row indices to plot. If
\code{NULL}, all observations are used. This argument is ignored when
\code{type = "quantile"} because the quantile plot summarizes all
observations.}

\item{alpha}{Alpha transparency for filled elements.}

\item{base_circle}{Logical. If \code{TRUE}, add inner guide circles.}

\item{base_lty}{Line type used in the base figure.}

\item{addText}{Logical. Whether to add interval-valued labels to the plot.}

\item{type}{Radar representation. Use \code{"default"} for polygon
intervals, \code{"rect"} for rectangle intervals, or \code{"quantile"}
for the quantile-radar display.}

\item{quantileNum}{Number of quantile layers when
\code{type = "quantile"}.}

\item{Drift}{Drift term controlling where the radar values begin.}

\item{addText_modal}{Logical. Whether to add labels for modal
multivalued variables.}

\item{addText_modal.p}{Logical. Whether to add modal percentages.}
}
\description{
Visualize interval-valued and mixed symbolic data with a
radar-style display. Interval-valued variables are represented through
their lower and upper bounds, while modal multivalued variables can be
shown with stacked bars. When \code{type = "quantile"}, the function
summarizes all observations of each interval-valued variable through
nested empirical quantile bands.
}
\examples{
\donttest{
# must specify plotPartial to the rows you want to plot
Environment.n <- Environment[, 5:17]
ggInterval_radarplot(Environment.n,
  plotPartial = 2,
  showLegend = FALSE,
  base_circle = TRUE,
  base_lty = 2,
  addText = FALSE
) +
  labs(title = "") +
  scale_fill_manual(values = c("gray50")) +
  scale_color_manual(values = c("red"))

ggInterval_radarplot(Environment,
  plotPartial = 2,
  showLegend = FALSE,
  base_circle = FALSE,
  base_lty = 1,
  addText = TRUE,
  type = "rect"
) +
  labs(title = "") +
  scale_fill_manual(values = c("gray50")) +
  scale_color_manual(values = c("gray50"))

ggInterval_radarplot(
  facedata,
  base_circle = FALSE,
  base_lty = 1,
  type = "quantile",
  quantileNum = 5,
  showLegend = TRUE,
  Drift = 0
) +
  scale_fill_brewer(palette = "Greys") +
  labs(title = "", fill = "Quantiles")
}

}
