linting

tests/testthat/data/create-ref-data.R

@@ -7,22 +7,23 @@ library(magrittr)
 library(jsonlite)
 
 
-ref_data_location <- function(x) file.path("tests","testthat","data", x)
+ref_data_location <- function(x) file.path("tests", "testthat", "data", x)
 
 # RCurl -------------------------------------------------------------------
 
 REDCap_split(
-  ref_data_location("ExampleProject_records.json") %>% fromJSON,
-  ref_data_location("ExampleProject_metadata.json") %>% fromJSON
-  ) %>% digest
+  ref_data_location("ExampleProject_records.json") %>% fromJSON(),
+  ref_data_location("ExampleProject_metadata.json") %>% fromJSON()
+) %>% digest()
 
 
 # Basic CSV ---------------------------------------------------------------
 
 REDCap_split(
-  ref_data_location("ExampleProject_DATA_2018-06-07_1129.csv") %>% read.csv,
-  ref_data_location("ExampleProject_DataDictionary_2018-06-07.csv") %>% read.csv
-  ) %>% digest
+  ref_data_location("ExampleProject_DATA_2018-06-07_1129.csv") %>% read.csv(),
+  ref_data_location("ExampleProject_DataDictionary_2018-06-07.csv") %>%
+    read.csv()
+) %>% digest()
 
 # REDCap R Export ---------------------------------------------------------
 
@@ -30,10 +31,11 @@ source("tests/testthat/helper-ExampleProject_R_2018-06-07_1129.r")
 
 REDCap_split(
   ref_data_location("ExampleProject_DATA_2018-06-07_1129.csv") %>%
-    read.csv %>%
-    REDCap_process_csv,
-  ref_data_location("ExampleProject_DataDictionary_2018-06-07.csv") %>% read.csv
-  ) %>% digest
+    read.csv() %>%
+    REDCap_process_csv(),
+  ref_data_location("ExampleProject_DataDictionary_2018-06-07.csv") %>%
+    read.csv()
+) %>% digest()
 
 # Longitudinal data from @pbchase; Issue #7 -------------------------------
 
@@ -41,9 +43,10 @@ file_paths <- vapply(
   c(
     records = "WARRIORtestForSoftwa_DATA_2018-06-21_1431.csv",
     metadata = "WARRIORtestForSoftwareUpgrades_DataDictionary_2018-06-21.csv"
-  ), FUN.VALUE = "character", ref_data_location
+  ),
+  FUN.VALUE = "character", ref_data_location
 )
 
 redcap <- lapply(file_paths, read.csv, stringsAsFactors = FALSE)
-redcap[["metadata"]] <- with(redcap, metadata[metadata[,1] > "",])
-with(redcap, REDCap_split(records, metadata)) %>% digest
+redcap[["metadata"]] <- with(redcap, metadata[metadata[, 1] > "", ])
+with(redcap, REDCap_split(records, metadata)) %>% digest()

tests/testthat/helper-ExampleProject_R_2018-06-07_1129.r

@@ -1,5 +1,5 @@
 REDCap_process_csv <- function(data) {
-  #Load Hmisc library
+  # Load Hmisc library
   if (!requireNamespace("Hmisc", quietly = TRUE)) {
     stop("This test requires the 'Hmisc' package")
   }
@@ -36,13 +36,13 @@ REDCap_process_csv <- function(data) {
   Hmisc::label(data$color) <- "Color"
   Hmisc::label(data$customer) <- "Customer Name"
   Hmisc::label(data$sale_complete) <- "Complete?"
-  #Setting Units
+  # Setting Units
 
 
-  #Setting Factors(will create new variable for factors)
+  # Setting Factors(will create new variable for factors)
   data$redcap_repeat_instrument.factor <-
     factor(data$redcap_repeat_instrument, levels <-
-             c("sale"))
+      c("sale"))
   data$cyl.factor <-
     factor(data$cyl, levels <- c("3", "4", "5", "6", "7", "8"))
   data$vs.factor <- factor(data$vs, levels <- c("1", "0"))
@@ -50,36 +50,36 @@ REDCap_process_csv <- function(data) {
   data$gear.factor <- factor(data$gear, levels <- c("3", "4", "5"))
   data$carb.factor <-
     factor(data$carb, levels <-
-             c("1", "2", "3", "4", "5", "6", "7", "8"))
+      c("1", "2", "3", "4", "5", "6", "7", "8"))
   data$color_available___red.factor <-
     factor(data$color_available___red, levels <-
-             c("0", "1"))
+      c("0", "1"))
   data$color_available___green.factor <-
     factor(data$color_available___green, levels <-
-             c("0", "1"))
+      c("0", "1"))
   data$color_available___blue.factor <-
     factor(data$color_available___blue, levels <-
-             c("0", "1"))
+      c("0", "1"))
   data$color_available___black.factor <-
     factor(data$color_available___black, levels <-
-             c("0", "1"))
+      c("0", "1"))
   data$motor_trend_cars_complete.factor <-
     factor(data$motor_trend_cars_complete, levels <-
-             c("0", "1", "2"))
+      c("0", "1", "2"))
   data$letter_group___a.factor <-
     factor(data$letter_group___a, levels <-
-             c("0", "1"))
+      c("0", "1"))
   data$letter_group___b.factor <-
     factor(data$letter_group___b, levels <-
-             c("0", "1"))
+      c("0", "1"))
   data$letter_group___c.factor <-
     factor(data$letter_group___c, levels <-
-             c("0", "1"))
+      c("0", "1"))
   data$choice.factor <-
     factor(data$choice, levels <- c("choice1", "choice2"))
   data$grouping_complete.factor <-
     factor(data$grouping_complete, levels <-
-             c("0", "1", "2"))
+      c("0", "1", "2"))
   data$color.factor <-
     factor(data$color, levels <- c("1", "2", "3", "4"))
   data$sale_complete.factor <-

tests/testthat/test-csv-exports.R

@@ -1,5 +1,3 @@
-
-
 # Set up the path and data -------------------------------------------------
 metadata <- read.csv(
   get_data_location("ExampleProject_DataDictionary_2018-06-07.csv"),
@@ -8,7 +6,8 @@ metadata <- read.csv(
 
 records <-
   read.csv(get_data_location("ExampleProject_DATA_2018-06-07_1129.csv"),
-           stringsAsFactors = TRUE)
+    stringsAsFactors = TRUE
+  )
 
 redcap_output_csv1 <- REDCap_split(records, metadata)
 
@@ -19,20 +18,21 @@ test_that("CSV export matches reference", {
 
 # Test that REDCap_split can handle a focused dataset
 
-records_red <- records[!records$redcap_repeat_instrument == "sale",
-                       !names(records) %in%
-                         metadata$field_name[metadata$form_name == "sale"] &
-                         !names(records) == "sale_complete"]
+records_red <- records[
+  !records$redcap_repeat_instrument == "sale",
+  !names(records) %in%
+    metadata$field_name[metadata$form_name == "sale"] &
+    !names(records) == "sale_complete"
+]
 records_red$redcap_repeat_instrument <-
   as.character(records_red$redcap_repeat_instrument)
 
 redcap_output_red <- REDCap_split(records_red, metadata)
 
 
-test_that("REDCap_split handles subset dataset",
-          {
-            testthat::expect_length(redcap_output_red, 1)
-          })
+test_that("REDCap_split handles subset dataset", {
+  testthat::expect_length(redcap_output_red, 1)
+})
 
 
 # Test that R code enhanced CSV export matches reference --------------------
@@ -47,35 +47,40 @@ if (requireNamespace("Hmisc", quietly = TRUE)) {
 
 
 if (requireNamespace("readr", quietly = TRUE)) {
-
   metadata <-
     readr::read_csv(get_data_location(
-      "ExampleProject_DataDictionary_2018-06-07.csv"))
+      "ExampleProject_DataDictionary_2018-06-07.csv"
+    ))
 
   records <-
     readr::read_csv(get_data_location(
-      "ExampleProject_DATA_2018-06-07_1129.csv"))
+      "ExampleProject_DATA_2018-06-07_1129.csv"
+    ))
 
   redcap_output_readr <- REDCap_split(records, metadata)
 
   expect_matching_elements <- function(FUN) {
     FUN <- match.fun(FUN)
-    expect_identical(lapply(redcap_output_readr, FUN),
-                     lapply(redcap_output_csv1, FUN))
+    expect_identical(
+      lapply(redcap_output_readr, FUN),
+      lapply(redcap_output_csv1, FUN)
+    )
   }
 
   test_that("Result of data read in with `readr` will
-            match result with `read.csv`",
-            {
-              # The list itself
-              expect_identical(length(redcap_output_readr),
-                               length(redcap_output_csv1))
-              expect_identical(names(redcap_output_readr),
-                               names(redcap_output_csv1))
-
-              # Each element of the list
-              expect_matching_elements(names)
-              expect_matching_elements(dim)
-            })
+            match result with `read.csv`", {
+    # The list itself
+    expect_identical(
+      length(redcap_output_readr),
+      length(redcap_output_csv1)
+    )
+    expect_identical(
+      names(redcap_output_readr),
+      names(redcap_output_csv1)
+    )
 
+    # Each element of the list
+    expect_matching_elements(names)
+    expect_matching_elements(dim)
+  })
 }

tests/testthat/test-utils.R

@@ -1,20 +1,22 @@
 test_that("strsplitx works", {
   expect_equal(2 * 2, 4)
-  test <- c("12 months follow-up", "3 steps", "mRS 6 weeks", "Counting to 231 now")
-  expect_length(strsplitx(test,"[0-9]",type="around")[[1]],3)
+  test <- c("12 months follow-up", "3 steps", "mRS 6 weeks",
+            "Counting to 231 now")
+  expect_length(strsplitx(test, "[0-9]", type = "around")[[1]], 3)
 
-  expect_equal(strsplitx(test,"[0-9]",type="classic")[[2]][1],"")
-  expect_length(strsplitx(test,"[0-9]",type="classic")[[4]],4)
+  expect_equal(strsplitx(test, "[0-9]", type = "classic")[[2]][1], "")
+  expect_length(strsplitx(test, "[0-9]", type = "classic")[[4]], 4)
 
-  expect_length(strsplitx(test,"[0-9]",type="classic")[[4]],4)
+  expect_length(strsplitx(test, "[0-9]", type = "classic")[[4]], 4)
 })
 
 test_that("d2w works", {
+  expect_length(d2w(c(2:8, 21)), 8)
 
-  expect_length(d2w(c(2:8,21)),8)
+  expect_equal(d2w(data.frame(2:7, 3:8, 1),
+    lang = "da",
+    neutrum = TRUE
+  )[1, 3], "et")
 
-  expect_equal(d2w(data.frame(2:7,3:8,1),lang="da",
-                              neutrum=TRUE)[1,3],"et")
-
-  expect_equal(d2w(list(2:8,c(2,6,4,23),2), everything=T)[[2]][4],"two three")
+  expect_equal(d2w(list(2:8, c(2, 6, 4, 23), 2), everything = T)[[2]][4], "two three")
 })