Merge 366c8aa into 8205fd7

NAMESPACE

@@ -9,6 +9,7 @@ export(SimulateGMMData)
 export(Uhat)
 export(as.theta)
 export(choose.theta)
+export(classify)
 export(dmvnormal)
 export(fit.full.GMCM)
 export(fit.general.GMCM)

R/classify.R

@@ -0,0 +1,36 @@
+#' Classify observations
+#'
+#' Classify observations according to the maximum a posterior probabilites.
+#'
+#' @param x Either a \code{matrix} of A) observations where rows corresponds to
+#'   obsercations and columns to dimensions or B) class probabilities where rows
+#'   correspond to obsevations and columns to components.
+#' @param theta A list of parameters for the full model as described in
+#'   \code{\link{rtheta}}. If \code{theta} is supplied, \code{x} are assumed to
+#'   be observations (A). If \code{theta} is missing, \code{x} are assumed to be
+#'   probabilites (B).
+#'
+#' @return A integer vector of class numbers with length equal to the number of
+#'   rows in \code{x}.
+#'
+#' @examples
+#' # Classify using probabilites (usually returned from get.prob)
+#' probs <- matrix(runif(75), 25, 3)
+#' classify(probs)
+#'
+#' # Classify using a matrix of observations and theta
+#' theta <- rtheta(d = 4, m = 3)
+#' u <- SimulateGMCMData(n = 20, theta = theta)$u
+#' classify(x = u, theta = theta)
+#' @seealso \code{\link{get.prob}}
+#' @export
+classify <- function(x, theta) {
+  if (missing(theta)) {
+    stopifnot(all(0 <= x & x <= 1))
+    kappa <- x
+  } else {
+    kappa <- get.prob(x, theta)
+  }
+  map_class <- apply(kappa, 1, which.max)
+  return(map_class)
+}

inst/NEWS.Rd

@@ -6,9 +6,10 @@
 \section{Changes in version 1.4}{
   \itemize{
     \item Added a shiny application for the package. Available at \href{https://gmcm.shinyapps.io/GMCM/}{online} or via \code{GMCM::runGMCM()} for a local instance.
+    \item Added \code{classify()} function to ease classification after fitting a general GMCM.
   }
 }
-                         
+
 \section{Changes in version 1.3.2 (2018-03-12)}{
   \itemize{
     \item Hotfix due to new default RNG after R version 3.5.3.

tests/testthat/test-classify.R

@@ -0,0 +1,43 @@
+context("Check classify")
+
+# Create some test data
+d <- 2
+m <- 3
+n <- 50
+
+test_that("classify returns expected types and ranges using theta", {
+  theta <- rtheta(m = m, d = d, method = "EqualEllipsoidal")
+  u <- SimulateGMCMData(n, theta = theta)$u
+  out <- classify(x = u, theta = theta)
+  expect_true(is.numeric(out))
+  expect_length(out, n)
+  expect_lte(max(out), m)
+  expect_gte(min(out), 1)
+})
+
+test_that("classify returns expected types and ranges using probabilities", {
+  prob <- matrix(runif(n*m), n, m)
+  out <- classify(x = prob)
+  expect_true(is.numeric(out))
+  expect_length(out, n)
+  expect_lte(max(out), m)
+  expect_gte(min(out), 1)
+})
+
+# Test edge cases
+
+# m = 1 class, d = 2
+d <- 2
+m <- 1
+n <- 25
+theta <- rtheta(m = m, d = d, method = "EqualEllipsoidal")
+u <- SimulateGMCMData(n, theta = theta)$u
+
+test_that("classify returns only one class", {
+  out <- classify(x = u, theta = theta)
+  expect_true(is.numeric(out))
+  expect_length(out, n)
+  expect_lte(max(out), m)
+  expect_gte(min(out), 1)
+})
+