% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/biometric-plots.R
\name{plot_gazepoint_biometric_signals}
\alias{plot_gazepoint_biometric_signals}
\title{Plot Gazepoint biometric signal time series}
\usage{
plot_gazepoint_biometric_signals(
  data,
  signal_cols = NULL,
  time_col = NULL,
  group_col = NULL,
  max_points = 5000L,
  standardize = FALSE,
  type = c("line", "points", "both"),
  main = NULL,
  xlab = NULL,
  ylab = NULL,
  legend = TRUE,
  plot = TRUE,
  ...
)
}
\arguments{
\item{data}{A data frame.}

\item{signal_cols}{Optional character vector of signal columns. If \code{NULL},
common Gazepoint biometric signal columns are detected.}

\item{time_col}{Optional time/order column for the x-axis. If \code{NULL}, row
number is used.}

\item{group_col}{Optional grouping column recorded in the returned overview.
The current plotting implementation overlays the selected rows rather than
faceting by group.}

\item{max_points}{Maximum number of rows to plot. Large data are evenly
downsampled for display only; returned summaries still describe the input
signal columns.}

\item{standardize}{Logical. Should each signal be z-standardised before
plotting? This is useful when signals are on different scales.}

\item{type}{Plot type: \code{"line"}, \code{"points"}, or \code{"both"}.}

\item{main}{Optional plot title.}

\item{xlab}{Optional x-axis label.}

\item{ylab}{Optional y-axis label.}

\item{legend}{Logical. Should a legend be drawn when more than one signal is
plotted?}

\item{plot}{Logical. If \code{FALSE}, no plot is drawn and only the plot object is
returned.}

\item{...}{Additional arguments passed to \code{\link[=matplot]{matplot()}}.}
}
\value{
A list with \code{overview}, \code{plot_data}, \code{signal_summary}, and \code{settings}.
}
\description{
Plots one or more Gazepoint biometric signals using base R graphics and
returns the plotted data and signal summary. The helper is intentionally
descriptive and does not infer emotional valence, cognition, or HRV from raw
biometric columns.
}
\examples{
df <- data.frame(
  CNT = 1:5,
  GSR = c(1, 1.1, 1.2, 1.1, 1),
  HR = c(70, 71, 72, 71, 70)
)
plot_gazepoint_biometric_signals(df, time_col = "CNT", plot = FALSE)

}
