troubleshooting bioc build check

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: immApex
 Title: Tools for Adaptive Immune Receptor Sequence-Based Keras3 Modeling
-Version: 1.0.3
-Date: 2024-11-4
+Version: 1.0.4
+Date: 2024-11-5
 Authors@R: c(
     person(given = "Nick", family = "Borcherding", role = c("aut", "cre"), email = "[email protected]"))
 Description: A set of tools to build tensorflow/keras3-based models in R from amino acid and nucleotide sequences focusing on adaptive immune receptors. The package includes pre-processing of sequences, unifying gene nomenclature usage, encoding sequences, and combining models. This package will serve as the basis of future immune receptor sequence functions/packages/models compatible with the scRepertoire ecosystem.

NEWS.md

@@ -1,3 +1,9 @@
+# immApex VERSION 1.0.4
+
+## UNDERLYING CHANGES
+* Optional testthat variationalSequences() evaulate presence of Keras
+
+
 # immApex VERSION 1.0.3
 
 ## UNDERLYING CHANGES

tests/testthat/test-variationalSequences.R

@@ -1,42 +1,40 @@
 # test script for variationalSequences.R - testcases are NOT comprehensive!
 
 test_that("variationalSequences works", {
-
-  set.seed(42)
-  test_that("Test for valid input sequence length", {
-    expect_error(variationalSequences(input.sequences = character(0)),
-                 "input.sequences must have at least one sequence.")
-  })
-
-  test_that("Test for valid encoder function", {
-    sequences <- c("CASGY", "CASDY", "CASTY")
-    expect_error(variationalSequences(input.sequences = sequences,
-                                      encoder.function = "invalidEncoder"),
-                 "Invalid encoder provided.")
-  })
-
-  test_that("Test for valid optimizer", {
-    sequences <- c("CASGY", "CASDY", "CASTY")
-    expect_error(variationalSequences(input.sequences = sequences,
-                                      optimizer = "invalidOptimizer"),
-                 "Please select a compatible optimizer function in the Keras R implementation.")
-  })
-
-  test_that("Test for correct output type", {
-    sequences <- getdata("generateSequences", "generateSequences_T1")[1:100]
-    result <- variationalSequences(input.sequences = sequences, 
-                                   sequence.dictionary = amino.acids[1:20])
-    expect_true(is.vector(result))
-  })
-
-  test_that("Test for correct sequence generation", {
-    sequences <- getdata("generateSequences", "generateSequences_T1")[1:100]
-    number_of_sequences <- 5
-    result <- variationalSequences(input.sequences = sequences, 
-                                   number.of.sequences = number_of_sequences)
-    expect_equal(length(result), number_of_sequences)
-  })
-
-  #TODO Test for Reproducibility
-
+  if(reticulate::py_module_available("keras")) {
+    set.seed(42)
+    test_that("Test for valid input sequence length", {
+      expect_error(variationalSequences(input.sequences = character(0)),
+                   "input.sequences must have at least one sequence.")
+    })
+
+    test_that("Test for valid encoder function", {
+      sequences <- c("CASGY", "CASDY", "CASTY")
+      expect_error(variationalSequences(input.sequences = sequences,
+                                        encoder.function = "invalidEncoder"),
+                   "Invalid encoder provided.")
+    })
+
+    test_that("Test for valid optimizer", {
+      sequences <- c("CASGY", "CASDY", "CASTY")
+      expect_error(variationalSequences(input.sequences = sequences,
+                                        optimizer = "invalidOptimizer"),
+                   "Please select a compatible optimizer function in the Keras R implementation.")
+    })
+
+    test_that("Test for correct output type", {
+      sequences <- getdata("generateSequences", "generateSequences_T1")[1:100]
+      result <- variationalSequences(input.sequences = sequences, 
+                                     sequence.dictionary = amino.acids[1:20])
+      expect_true(is.vector(result))
+    })
+
+    test_that("Test for correct sequence generation", {
+      sequences <- getdata("generateSequences", "generateSequences_T1")[1:100]
+      number_of_sequences <- 5
+      result <- variationalSequences(input.sequences = sequences, 
+                                     number.of.sequences = number_of_sequences)
+      expect_equal(length(result), number_of_sequences)
+    })
+  }
 })