fix: error if ca data only has two rows or columns (#45)

Author: juba

NEWS.md

@@ -1,3 +1,7 @@
+# explor (development version)
+
+- Add more explicit error messages when data from a correspondance analysis had only two rows or two columns (#45)
+
 # explor 0.3.10
 
 - Fix varsup and indsup functions renamed to supvar and supind in GDAtools

R/prepare_results_CA.R

@@ -10,6 +10,7 @@
 prepare_results.CA <- function(obj) {
 
     if (!inherits(obj, "CA")) stop("obj must be of class CA")
+    if (!is.array(obj$row$coord) || !is.array(obj$col$coord)) stop("obj must have at least two dimensions on rows or columns")
 
     ## Axes names and inertia
     axes <- seq_len(ncol(obj$col$coord))

R/prepare_results_dudi_coa.R

@@ -10,6 +10,7 @@
 prepare_results.coa <- function(obj) {
 
     if (!inherits(obj, "coa")) stop("obj must be of class coa")
+    if ((ncol(obj$li) < 2) || (ncol(obj$co) < 2)) stop("obj must have at least two dimensions on rows or columns")
 
     if (!requireNamespace("ade4", quietly = TRUE)) {
         stop("the ade4 package is needed for this function to work.")

tests/testthat/test_prepare_results_CA.R

@@ -8,6 +8,13 @@ ca <- FactoMineR::CA(children[, 1:5],
 )
 res <- prepare_results(ca)
 
+test_that("error if not at least three rows or cols", {
+  tmp <- FactoMineR::CA(children[, 1:2])
+  expect_error(prepare_results(tmp))
+  tmp <- FactoMineR::CA(children[1:2, ])
+  expect_error(prepare_results(tmp))
+})
+
 test_that("Eigenvalues are equals", {
   expect_equal(unname(ca$eig[, "percentage of variance"]), res$eig$percent)
 })

tests/testthat/test_prepare_results_dudi.coa.R

@@ -11,6 +11,13 @@ coa$supc <- ade4::supcol(coa, col_sup)
 iner <- ade4::inertia.dudi(coa, row.inertia = TRUE, col.inertia = TRUE)
 res <- prepare_results(coa)
 
+test_that("error if not at least three rows or cols", {
+  tmp <- dudi.coa(tab[, 1:2], nf = 5, scannf = FALSE)
+  expect_error(prepare_results(tmp))
+  tmp <- dudi.coa(tab[1:2, ], nf = 5, scannf = FALSE)
+  expect_error(prepare_results(tmp))
+})
+
 test_that("Eigenvalues are equals", {
   expect_equal(coa$eig / sum(coa$eig) * 100, res$eig$percent)
 })