% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/4_1_topicsPlot.R
\name{topicsPlotOverview}
\alias{topicsPlotOverview}
\title{Combine topics and distribution legend into an overview figure (experimental)}
\usage{
topicsPlotOverview(
  plot_list,
  overview_plot_type,
  overview_n_topics = 9,
  scatter_legend_n = NULL,
  title_font = "sans"
)
}
\arguments{
\item{plot_list}{(list) Output from the `topicsPlot()` function.}

\item{overview_plot_type}{(character) One of `"topics_grid"`, `"textTopics"`,
`"one_dimension_topics"`, or `"two_dimension_topics"`.}

\item{overview_n_topics}{(integer) For the `"topics_grid"` / `"textTopics"`
overview only: the number of topic plots to include. Plots are arranged
in 3 columns (the default of 9 produces a 3x3 grid). Ignored for the
test-based 1D and 2D overviews, which instead use `scatter_legend_n`.
Default: 9.}

\item{scatter_legend_n}{(numeric vector) For the test-based 1D and 2D
overviews: the per-category counts that determine how many topic plots
appear in the overview. Length 3 for 1D (negative, non-significant,
positive) and length 9 for 2D (one value per quadrant). A value of 0
omits that category. Ignored for the prevalent-topics overview.}

\item{title_font}{Font family used for all non-word text elements in the plots
(e.g., titles, axis labels, tick labels, legend text, annotations).
Default: `"sans"`.}
}
\value{
A patchwork composition that can be printed, saved with `ggsave()`,
  or further modified with patchwork operators.
}
\description{
Assembles a single composite figure from the individual topic word clouds
returned by `topicsPlot()`. The shape of the composition depends on
`overview_plot_type`:
\itemize{
  \item `"topics_grid"` / `"textTopics"`: a grid of the most prevalent topics
    (no test), controlled by `overview_n_topics`.
  \item `"one_dimension_topics"`: three columns (negative / non-significant /
    positive), controlled by `scatter_legend_n` (length 3).
  \item `"two_dimension_topics"`: a 3x3 quadrant layout with the distribution
    legend in the centre, controlled by `scatter_legend_n` (length 9).
}
}
\details{
This function is intended as a convenience for quickly inspecting results.
For publication figures, users typically save the individual topic plots
(returned separately by `topicsPlot()`) and assemble them in external
software such as PowerPoint, Google Drawings, or Illustrator.
}
