Merge pull request #113 from ACCLAB/revert-112-d2

Revert "delta delta function"

tests/testthat/helper-generate-dummy-data.R

@@ -1,107 +1,45 @@
-generate.two.groups <- function(sampleN = 40, populationN = 10000,
-                                control_mean = 100, sd = 50,
-                                difference = 25, seed = 54321) {
-  set.seed(seed)
-
-  pop1 <- rnorm(populationN, mean = control_mean, sd = sd)
-
-  pop2 <- rnorm(populationN, mean = control_mean + difference, sd = sd)
-
-  sample1 <- sample(pop1, sampleN)
-
-  sample2 <- sample(pop2, sampleN)
-
-  id      <- seq(1: sampleN)
-
-  my.data <-
-    tibble::tibble(Control = sample1, Test = sample2, ID = id) %>%
-    tidyr::gather(key = Group, value = Value, -ID)
-
-  return(my.data)
-}
-
-
-
-generate.canned.data <- function() {
-  set.seed(54321)
-
-  N = 40
-  c1 <- rnorm(N, mean = 100, sd = 25)
-  c2 <- rnorm(N, mean = 100, sd = 50)
-  g1 <- rnorm(N, mean = 120, sd = 25)
-  g2 <- rnorm(N, mean = 80, sd = 50)
-  g3 <- rnorm(N, mean = 100, sd = 12)
-  g4 <- rnorm(N, mean = 100, sd = 50)
-  gender <- c(rep('Male', N/2), rep('Female', N/2))
-  id <- 1: N
-
-  wide.data <- tibble::tibble(
-    Control1 = c1, Control2 = c2,
-    Group1 = g1, Group2 = g2, Group3 = g3, Group4 = g4,
-    Gender = gender, ID = id)
-
-  my.data <- wide.data %>%
-    tidyr::gather(key = Group, value = Measurement, -ID, -Gender)
-}
-
-generate.time.groups <- function(sampleN = 40, populationN = 10000,
-                                 control_mean = 100, sd = 50,
-                                 difference = 25, seed = 54321) {
-  set.seed(seed)
-
-  # 3 time points
-  time1 <- rnorm(populationN, mean = control_mean, sd = sd)
-
-  time2 <- rnorm(populationN, mean = control_mean + difference, sd = sd)
-
-  time3 <- rnorm(populationN, mean = control_mean + difference + difference, sd = sd)
-
-  sample1 <- sample(time1, sampleN)
-
-  sample2 <- sample(time2, sampleN)
-
-  sample3 <- sample(time3, sampleN)
-
-  id      <- seq(1: sampleN)
-
-  my.data <-
-    tibble::tibble(Timepoint1 = sample1, Timepoint2 = sample2, 
-                   Timepoint3 = sample3, ID = id) %>%
-    tidyr::gather(key = Group, value = Value, -ID)
-
-  return(my.data)
-}
-
-generate.dd.data <- function() {
-  ax23.t1 <- c(72, 78, 71, 72, 66, 74, 62, 69)
-  ax23.t2 <- c(86, 83, 82, 83, 79, 83, 73, 75)
-  ax23.t3 <- c(81, 88, 81, 83, 77, 84, 78, 76)
-  ax23.t4 <- c(77, 81, 75, 69, 66, 77, 70, 70)
-  ax23 <- c(ax23.t1, ax23.t2, ax23.t3, ax23.t4)
-
-  bww9.t1 <- c(85, 82, 71, 83, 86, 85, 79, 83)
-  bww9.t2 <- c(86, 86, 78, 88, 85, 82, 83, 84)
-  bww9.t3 <- c(83, 80, 70, 79, 76, 83, 80, 78)
-  bww9.t4 <- c(80, 84, 75, 81, 76, 80, 81, 81)
-  bww9 <- c(bww9.t1, bww9.t2, bww9.t3, bww9.t4)
-
-  ctrl.t1 <- c(69, 66, 84, 80, 72, 65, 75, 71)
-  ctrl.t2 <- c(73, 62, 90, 81, 72, 62, 69, 70)
-  ctrl.t3 <- c(72, 67, 88, 77, 69, 65, 69, 65)
-  ctrl.t4 <- c(74, 73, 87, 72, 70, 61, 68, 65)
-  ctrl <- c(ctrl.t1, ctrl.t2, ctrl.t3, ctrl.t4)
-
-  id <- c(1:8, 1:8, 1:8, 1:8)
-  treatment <- c(rep("T1", 8), rep("T2", 8),
-                 rep("T3", 8), rep("T4", 8))
-
-  Value <- c(ctrl, ax23, bww9)
-  ids <- c(id, id, id)
-  Group <- c(paste(treatment, "Control"),
-             paste(treatment, "AX23"),
-             paste(treatment, "BWW9"))
-
-  data.test3 <- tibble::tibble(ids, Value, Group)
-
-  return(data.test3)
-}
+generate.two.groups <- function(sampleN = 40, populationN = 10000,
+                                control_mean = 100, sd = 50,
+                                difference = 25, seed = 54321) {
+  set.seed(seed)
+
+  pop1 <- rnorm(populationN, mean = control_mean, sd = sd)
+
+  pop2 <- rnorm(populationN, mean = control_mean + difference, sd = sd)
+
+  sample1 <- sample(pop1, sampleN)
+
+  sample2 <- sample(pop2, sampleN)
+
+  id      <- seq(1: sampleN)
+
+  my.data <-
+    tibble::tibble(Control = sample1, Test = sample2, ID = id) %>%
+    tidyr::gather(key = Group, value = Value, -ID)
+
+  return(my.data)
+}
+
+
+
+generate.canned.data <- function() {
+  set.seed(54321)
+
+  N = 40
+  c1 <- rnorm(N, mean = 100, sd = 25)
+  c2 <- rnorm(N, mean = 100, sd = 50)
+  g1 <- rnorm(N, mean = 120, sd = 25)
+  g2 <- rnorm(N, mean = 80, sd = 50)
+  g3 <- rnorm(N, mean = 100, sd = 12)
+  g4 <- rnorm(N, mean = 100, sd = 50)
+  gender <- c(rep('Male', N/2), rep('Female', N/2))
+  id <- 1: N
+
+  wide.data <- tibble::tibble(
+    Control1 = c1, Control2 = c2,
+    Group1 = g1, Group2 = g2, Group3 = g3, Group4 = g4,
+    Gender = gender, ID = id)
+
+  my.data <- wide.data %>%
+    tidyr::gather(key = Group, value = Measurement, -ID, -Gender)
+}