% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/shape-sensitivity.R
\name{janusplot_shape_sensitivity_plot}
\alias{janusplot_shape_sensitivity_plot}
\title{Visualise a shape-sensitivity sweep}
\usage{
janusplot_shape_sensitivity_plot(
  results,
  type = c("confusion_fine", "confusion_archetype", "accuracy_grid", "recovery_curves")
)
}
\arguments{
\item{results}{Data frame from \code{\link[=janusplot_shape_sensitivity]{janusplot_shape_sensitivity()}} or the
precomputed \link{shape_sensitivity_demo}.}

\item{type}{One of \code{"confusion_fine"}, \code{"confusion_archetype"},
\code{"accuracy_grid"}, or \code{"recovery_curves"}.}
}
\value{
A \link[ggplot2:ggplot]{ggplot2::ggplot} object.
}
\description{
\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#experimental}{\figure{lifecycle-experimental.svg}{options: alt='[Experimental]'}}}{\strong{[Experimental]}}

Produce one of four diagnostic plots from the raw data frame returned
by \code{\link[=janusplot_shape_sensitivity]{janusplot_shape_sensitivity()}}:
\describe{
\item{\code{"confusion_fine"}}{24 x (|shapes|) confusion matrix at the
fine category level — rows = ground truth, columns = predicted,
cells coloured by \code{P(pred | truth)}.}
\item{\code{"confusion_archetype"}}{7 x 7 confusion matrix at the
archetype level.}
\item{\code{"accuracy_grid"}}{per-shape heatmap of archetype-level
accuracy across the \verb{(n, sigma)} design.}
\item{\code{"recovery_curves"}}{accuracy as a function of sigma,
one line per sample size, faceted by shape.}
}
}
\examples{
data("shape_sensitivity_demo", package = "janusplot")
janusplot_shape_sensitivity_plot(shape_sensitivity_demo,
                                 "recovery_curves")
}
\seealso{
Other shape-sensitivity: 
\code{\link{janusplot_shape_sensitivity}()},
\code{\link{janusplot_shape_sensitivity_shapes}()},
\code{\link{janusplot_shape_sensitivity_summary}()}
}
\concept{shape-sensitivity}
