added logicals to custom.subsets

DESCRIPTION

@@ -7,8 +7,8 @@ Authors@R: c(person("Thomas", "Guillerme", role = c("aut", "cre", "cph"),
   			 person("Jack", "Hatfield",    role = c("aut", "cph"))
   			 )
 Maintainer: Thomas Guillerme <[email protected]>
-Version: 1.8.1
-Date: 2023-12-15
+Version: 1.8.2
+Date: 2024-01-15
 Description: A modular package for measuring disparity (multidimensional space occupancy). Disparity can be calculated from any matrix defining a multidimensional space. The package provides a set of implemented metrics to measure properties of the space and allows users to provide and test their own metrics. The package also provides functions for looking at disparity in a serial way (e.g. disparity through time) or per groups as well as visualising the results. Finally, this package provides several statistical tests for disparity analysis.
 Depends:
     R (>= 3.6.0),

NEWS.md

@@ -1,6 +1,10 @@
-dispRity v1.8.1 (2023-12-15) 
+dispRity v1.8.2 (2024-01-15) 
 =========================
 
+### MINOR IMPROVEMENTS
+
+ * `custom.subsets` can now take a logical vector for 
+
 ### BUG FIXES
 
  * `scale.dispRity` now correctly ignores `NA`s when scaling. 

R/custom.subsets.R

@@ -4,7 +4,7 @@
 #' @description Splits the data into a customized subsets list.
 #'
 #' @param data A \code{matrix} or a \code{list} of matrices.
-#' @param group Either a \code{list} of row numbers or names to be used as different groups, a \code{data.frame} with the same \eqn{k} elements as in \code{data} as rownames or a \code{factor} vector. If \code{group} is a \code{phylo} object matching \code{data}, groups are automatically generated as clades (and the tree is attached to the resulting \code{dispRity} object).
+#' @param group Either a \code{list} of row numbers or names to be used as different groups, a \code{data.frame} with the same \eqn{k} elements as in \code{data} as rownames, a \code{factor} or a \code{logical} vector. If \code{group} is a \code{phylo} object matching \code{data}, groups are automatically generated as clades (and the tree is attached to the resulting \code{dispRity} object).
 #' @param tree \code{NULL} (default) or an optional \code{phylo} or \code{multiPhylo} object to be attached to the data.
 #' 
 #' @details
@@ -93,7 +93,7 @@ custom.subsets <- function(data, group, tree = NULL) {
     }
 
     ## Sanitize the group variable
-    group_class <- check.class(group, c("matrix", "data.frame", "list", "phylo", "factor"))
+    group_class <- check.class(group, c("matrix", "data.frame", "list", "phylo", "factor", "logical"))
     if(group_class == "phylo") {
         ## Saving the tree for export
         tree <- group

R/custom.subsets_fun.R

@@ -45,6 +45,12 @@ set.group.list <- function(group, data, group_class) {
         group <- as.data.frame(group)
     }
 
+    ## Logical is set to factor
+    if(group_class[1] == "logical") {
+        group <- as.factor(group)
+        group_class[1] <- "factor"
+    }
+
     ## Switch methods
     return(switch(group_class,
             ## Group is already a list
@@ -56,9 +62,9 @@ set.group.list <- function(group, data, group_class) {
                            unlist(group_list, recursive = FALSE)},
             ## Group is a phylo
             "phylo"      = get.tree.clades(group, data),
+            ## Group is factor
             "factor"     = {group_list <- lapply(as.list(levels(group)), function(lvl, group) which(group == lvl), group = group) ; names(group_list) <- levels(group) ; group_list}
-            )
-        )
+        ))
 }
 
 

tests/testthat/test-as.covar.R

@@ -1,4 +1,5 @@
 ## Test
+nocov <- TRUE
 #package_coverage(type = "tests", quiet = FALSE, clean = FALSE)
 test_that("as.covar works in standalone", {
 

tests/testthat/test-custom.subsets.R

@@ -443,4 +443,16 @@ test_that("custom.subsets works with a factor", {
     expect_is(test, "dispRity")
     expect_equal(n.subsets(test), 3)
     expect_equal(size.subsets(test), c("gulls" = 159, "plovers" = 98, "sandpipers" = 102))
+})
+
+test_that("custom.subsets works with a logical", {
+    ## Random 3D dataset with 200 taxa
+    data <- dispRity::space.maker(elements = 200, dimensions = 3, distribution = rnorm)
+    set.seed(1)
+    group <- sample(c(TRUE, FALSE), 200, replace = TRUE)
+
+    ## Creating groups with a logical
+    expect_warning(test <- custom.subsets(data, group = group))
+    expect_equal(name.subsets(test), c("FALSE", "TRUE"))
+    expect_equal(size.subsets(test), c("FALSE" = 98, "TRUE" = 102))
 })