Add tidy function for adonis2 result

NAMESPACE

@@ -2,6 +2,7 @@
 
 S3method(plot,pcoaplus)
 S3method(tidy,adonis)
+S3method(tidy,anova.cca)
 export("%>%")
 export(adonisplus)
 export(adonispost)

R/tidy.R

@@ -26,3 +26,28 @@ tidy.adonis <- function (x, ...) {
   attr(ret, "heading") <- NULL
   ret
 }
+
+#' Tidy an \code{anova.cca} object
+#'
+#' @param x an object returned from \code{vegan::adonis2()}.
+#' @param ... Additional arguments are not used.
+#' @return A \code{tibble} with the following columns:
+#'   \item{term}{The name of the regression term.}
+#'   \item{df}{Degrees of freedom used by the model.}
+#'   \item{sumsq}{Sum of squares explained by this term.}
+#'   \item{r.squared}{
+#'     R-squared statistic, or the percent of variation explained by the model.}
+#'   \item{statistic}{
+#'     The value of a pseudo-F-statistic to use in the permutation test.}
+#'   \item{p.value}{P-value from the permutation test.}
+#' @export
+tidy.anova.cca <- function (x, ...) {
+  ret <- tibble::as_tibble(x, rownames = "term")
+  colnames(ret) <- c(
+    "term", "df", "sumsq", "r.squared", "statistic", "p.value")
+  attr(ret, "Random.seed") <- NULL
+  attr(ret, "F.perm") <- NULL
+  attr(ret, "control") <- NULL
+  attr(ret, "heading") <- NULL
+  ret
+}

tests/testthat/test-tidy.R

@@ -20,3 +20,23 @@ test_that("tidy.adonis produces expected result", {
     p.value = c(0.635, NA, NA))
   expect_equal(tidy(adonis_res), expected)
 })
+
+adonis2_res <- data.frame(
+  Df = c(1, 9, 10),
+  SumOfSqs = c(0.141236772727273, 1.4724405, 1.61367727272727),
+  R2 = c(0.0875247951460386, 0.912475204853961, 1),
+  F = c(0.863281711244329, NA, NA),
+  `Pr(>F)` = c(0.643, NA, NA),
+  row.names = c("study_group", "Residual", "Total"))
+class(adonis2_res) <- c("anova.cca", "anova", "data.frame")
+
+test_that("tidy.anova.cca produces expected result", {
+  expected <- tibble::tibble(
+    term = c("study_group", "Residual", "Total"),
+    df = c(1, 9, 10),
+    sumsq = c(0.141236772727273, 1.4724405, 1.61367727272727),
+    r.squared = c(0.0875247951460386, 0.912475204853961, 1),
+    statistic = c(0.863281711244329, NA, NA),
+    p.value = c(0.643, NA, NA))
+  expect_equal(tidy(adonis2_res), expected)
+})