new functions lesson

R_Programming/Functions/customTests.R

@@ -1,40 +1,10 @@
-#' TODO:
-#' - Use testthat for more robust unit testing of functions?
-#' - Test that functions error appropriately
-#' - Create our own little wrapper around testthat or other DSL that
-#'    simplifies unit testing functions for course authors?
-
 test_func1 <- function() {
   try({
-    func <- get('f', globalenv())
-    t1 <- identical(func(3), 9)
-    t2 <- identical(func(-2), 4)
+    func <- get('boring_function', globalenv())
+    t1 <- identical(func(9), 9)
+    t2 <- identical(func(4), 4)
     t3 <- identical(func(0), 0)
     ok <- all(t1, t2, t3)
   }, silent = TRUE)
   exists('ok') && isTRUE(ok)
 }
-
-test_func2 <- function() {
-  try({
-    func <- get('f', globalenv())
-    t1 <- identical(func(3, 3), 27)
-    t2 <- identical(func(-2, 4), 16)
-    t3 <- identical(func(0, 3), 0)
-    t4 <- identical(func(-3, 0), 1)
-    ok <- all(t1, t2, t3, t4)
-  }, silent = TRUE)
-  exists('ok') && isTRUE(ok)
-}
-
-test_func3 <- function() {
-  try({
-    func <- get('min_positive', globalenv())
-    t1 <- identical(func(c(-4, 4, 2, 10)), 2)
-    t2 <- identical(func(c(0, 9)), 0)
-    t3 <- identical(func(c(-11, 0, 39)), 0)
-    t4 <- identical(func(c(5, 6, 7, 7)), 5)
-    ok <- all(t1, t2, t3, t4)
-  }, silent = TRUE)
-  exists('ok') && isTRUE(ok)
-}

R_Programming/Functions/lesson.yaml

@@ -1,25 +1,28 @@
 - Class: meta
-  Course: R Programming
-  Lesson: Functions
-  Author: Sean Kross
+  Course: Test Course
+  Lesson: Lesson to test script
+  Author: Nick
   Type: Standard
   Organization: swirlstats
-  Version: 2.2.14
+  Version: 2.2.12
 
-- Class: text
-  Output: Functions are one of the fundamental building blocks of the R language. They are small 
-    pieces of reusable code that can be treated like any other R object.
+- Class: script
+  Output: Update the function f so that it accepts one argument, x, and returns the value of x squared.
+  AnswerTests: test_func1()
+  Hint: Make sure f accepts one argument called x and returns x^2.
+  Script: test-script1.R
 
-- Class: text
-  Output: Functions usually take arguments which are variables that the function operates on. For example,
-    the mean() function takes a vector as as argument, like in the case of mean(c(2,6,8)) . The mean()
-    function then adds up all of the numbers in the vector and divides that sum by the
-    length of the vector.
+- Class: script
+  Output: Now, have f accept a second argument, y, and return the value of x to the power of y.
+  AnswerTests: test_func2()
+  Hint: f should now accept two arguments, x and y, and return x^y.
+  Script: test-script2.R
 
 - Class: script
-  Output: The last R expression to be evaluated in a function is the return value of that function.
-    We want this function to take one argument, x, and return x without modifying it. Delete the pound
-    sign so that x is returned without any modification.
-  AnswerTests: test_func1()
-  Hint: Make sure to delete the pound sign so the last expression in the function is just x.
-  Script: boring_function.R
+  Output: A friend of yours is trying to write a function called min_positive that accepts a vector of numbers and returns the minimum value that is greater than or equal to zero. She keeps getting an error and can't figure out why. Be a good friend and fix min_positive, so that it does what she wants it to do.
+  AnswerTests: test_func3()
+  Hint: You need to fix the error and have the function return the appropriate value.
+  Script: test-script3.R
+
+- Class: text
+  Output: Now you know how functions work!

R_Programming/Functions/scripts/boring_function-correct.R

@@ -0,0 +1,3 @@
+boring_function <- function(x) {
+  x
+}

R_Programming/Functions/scripts/boring_function.R

@@ -0,0 +1,3 @@
+boring_function <- function(x) {
+  #x
+}