% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/nmfae.R
\name{nmfae.heatmap}
\alias{nmfae.heatmap}
\title{Heatmap visualization of nmfae factor matrices}
\usage{
nmfae.heatmap(
  x,
  Y1.label = NULL,
  X1.label = NULL,
  X2.label = NULL,
  Y2.label = NULL,
  palette = NULL,
  ...
)
}
\arguments{
\item{x}{An object of class \code{"nmfae"} returned by \code{\link{nmfae}}.}

\item{Y1.label}{Character vector of output variable names (rows of \eqn{X_1}).}

\item{X1.label}{Character vector of decoder basis labels (columns of \eqn{X_1}).}

\item{X2.label}{Character vector of encoder basis labels (rows of \eqn{X_2}).}

\item{Y2.label}{Character vector of input variable names (columns of \eqn{X_2}).}

\item{palette}{Color palette vector. Default is white-orange-red (64 colors).}

\item{...}{Not used.}
}
\value{
Invisible \code{NULL}. Called for its side effect (plot).
}
\description{
\code{nmfae.heatmap} displays the three factor matrices \eqn{X_1}, \eqn{\Theta},
and \eqn{X_2} as side-by-side heatmaps. This provides an alternative to DOT graph
visualization, especially when \eqn{Y_2} has many variables (e.g., kernel matrix).
}
\section{Lifecycle}{

This function is \strong{experimental}. The interface may change in
future versions; details are to be described in an upcoming paper.
}

\examples{
\donttest{
set.seed(1)
Y <- matrix(runif(20), nrow = 4)
res <- nmfae(Y, rank = 2)
nmfae.heatmap(res)
}
}
\seealso{
\code{\link{nmfae}}, \code{\link{plot.nmfae}}, \code{\link{nmfae.DOT}}
}
