Merge pull request #1 from tdaverse/coverage

Bring code coverage to 100%.

Author: astamm

R/two-sample-test.R

@@ -6,7 +6,8 @@
 #' - A persistence set, which is a collection of persistence diagrams.
 #' - A distance matrix, which is a pairwise distance matrix between persistence
 #' diagrams.
-#' - One of the PH vectorizations available in the [{tdarec}]() package.
+#' - One of the PH vectorizations available in the
+#' [{TDAvec}](https://cran.r-project.org/package=TDAvec) package.
 #'
 #' @param x An object of class `persistence_set` typically produced by
 #'   [`phutil::as_persistence_set()`] or of class `dist` typically produced by

R/utils.R

@@ -3,6 +3,12 @@ null_spec <- function(y, parameters) {
 }
 
 compute_distance_matrix <- function(x, dimension = 0L, p = 2L, ncores = 1L) {
+  if (p == 0L) {
+    cli::cli_abort(
+      "The p-norm {.val p} must be greater than zero. Use {.val p = Inf} for the Bottleneck distance."
+    )
+  }
+
   if (is.infinite(p)) {
     D <- phutil::bottleneck_pairwise_distances(
       x = x,

inst/tinytest/test-two-sample-test.R

@@ -14,16 +14,16 @@ test_two_sample_test_inputs <- function() {
   result <- two_sample_test(ps1, ps2, B = 10L)
   expect_true(is.numeric(result))
 
-  ps1 <- phutil::wasserstein_pairwise_distances(
+  D <- phutil::wasserstein_pairwise_distances(
     ps1,
     dimension = 0L,
     p = 2L,
     ncores = 1L
   )
   ps2 <- 0
-  expect_error(two_sample_test(ps1, ps2))
+  expect_error(two_sample_test(D, ps2))
   ps2 <- c(5L, 5L) # Sample sizes
-  result <- two_sample_test(ps1, ps2, B = 10L)
+  result <- two_sample_test(D, ps2, B = 10L)
   expect_true(is.numeric(result))
 }
 
@@ -69,6 +69,18 @@ test_two_sample_test_verbose <- function() {
   ps2 <- trefoils2[1:5]
 
   expect_silent(two_sample_test(ps1, ps2, B = 10L, verbose = FALSE))
+  expect_message(
+    two_sample_test(ps1, ps2, B = 10L, verbose = TRUE),
+    "Parsing inputs..."
+  )
+  expect_message(
+    two_sample_test(ps1, ps2, B = 10L, verbose = TRUE),
+    "Setting up the plausibility function..."
+  )
+  expect_message(
+    two_sample_test(ps1, ps2, B = 10L, verbose = TRUE),
+    "Calculating the p-value..."
+  )
 }
 
 # Test different npc methods
@@ -83,6 +95,15 @@ test_two_sample_test_npc <- function() {
   expect_true(is.numeric(result_fisher))
 }
 
+test_two_sample_test_bottleneck <- function() {
+  ps1 <- trefoils1[1:5]
+  ps2 <- trefoils2[1:5]
+
+  result <- two_sample_test(ps1, ps2, p = Inf, B = 10L)
+  expect_true(is.numeric(result))
+  expect_true(result >= 0 && result <= 1)
+}
+
 # Run all tests
 test_two_sample_test <- function() {
   test_two_sample_test_inputs()
@@ -91,6 +112,7 @@ test_two_sample_test <- function() {
   test_two_sample_test_dist()
   test_two_sample_test_verbose()
   test_two_sample_test_npc()
+  test_two_sample_test_bottleneck()
 }
 
 test_two_sample_test()