From aaa4b9302c70abc094331a7b2a0d93786c3b9542 Mon Sep 17 00:00:00 2001
From: Waldir Leoncio <waldir.leoncio@gmail.com>
Date: Wed, 15 Jan 2020 10:55:50 +0100
Subject: [PATCH] Fixed repmat

---
 R/repmat.R    | 16 +++++++++++++---
 man/repmat.Rd |  2 ++
 2 files changed, 15 insertions(+), 3 deletions(-)

diff --git a/R/repmat.R b/R/repmat.R
index fcc041f..be72325 100644
--- a/R/repmat.R
+++ b/R/repmat.R
@@ -6,13 +6,23 @@
 #' @param n either a scalar with the number of replications in both rows and columns or a 2-length vector with individual repetitions.
 #' @return matrix replicated over `ncol(mx) * n` columns and `nrow(mx) * n` rows
 #' @note The Matlab implementation of this function accepts `n` with length > 2.
+#' 
+#' It should also be noted that a concatenated vector in R, e.g. `c(5, 2)`, becomes a column vector when coerced to matrix, even though it may look like a row vector at first glance. This is important to keep in mind when considering the expected output of this function. Vectors in R make sense to be seen as column vectors, given R's Statistics-oriented paradigm where variables are usually disposed as columns in a dataset.
 #' @export
 repmat <- function (mx, n) {
+    # Validation
     if (length(n) > 2) warning("Extra dimensions of n ignored")
     if (length(n) == 1) n <- rep(n, 2)
-    out <- mx_cols <- rep(mx, n[1])
-    if (n[2] > 1) {
-        for (i in seq(n[2] - 1)) out <- rbind(out, mx_cols)
+    if (class(mx) != "matrix") mx <- as.matrix(mx)
+
+    # Replicating cols
+    out <- mx_col <- matrix(rep(mx, n[2]), nrow(mx))
+
+    # Replicating rows
+    if (n[1] > 1) {
+        for (i in seq(n[1] - 1)) out <- rbind(out, mx_col)
     }
+
+    # Output
     return(unname(as.matrix(out)))
 }
\ No newline at end of file
diff --git a/man/repmat.Rd b/man/repmat.Rd
index f05885b..3ec7750 100644
--- a/man/repmat.Rd
+++ b/man/repmat.Rd
@@ -23,4 +23,6 @@ function on Matlab
 }
 \note{
 The Matlab implementation of this function accepts `n` with length > 2.
+
+It should also be noted that a concatenated vector in R, e.g. `c(5, 2)`, becomes a column vector when coerced to matrix, even though it may look like a row vector at first glance. This is important to keep in mind when considering the expected output of this function. Vectors in R make sense to be seen as column vectors, given R's Statistics-oriented paradigm where variables are usually disposed as columns in a dataset.
 }