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REDCapCAST/tests/testthat/test-csv-exports.R

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# Set up the path and data -------------------------------------------------
metadata <- read.csv(
get_data_location("ExampleProject_DataDictionary_2018-06-07.csv"),
stringsAsFactors = TRUE
)
records <-
read.csv(get_data_location("ExampleProject_DATA_2018-06-07_1129.csv"),
stringsAsFactors = TRUE
)
redcap_output_csv1 <- REDCap_split(records, metadata)
# Test that basic CSV export matches reference ------------------------------
test_that("CSV export matches reference", {
# expect_known_hash(redcap_output_csv1, "cb5074a06e1abcf659d60be1016965d2")
# dput(redcap_output_csv1)
expect_identical(
redcap_output_csv1,
list(
structure(list(
row = structure(1:32, levels = c(
"AMC Javelin",
"Cadillac Fleetwood", "Camaro Z28", "Chrysler Imperial", "Datsun 710",
"Dodge Challenger", "Duster 360", "Ferrari Dino", "Fiat 128",
"Fiat X1-9", "Ford Pantera L", "Honda Civic", "Hornet 4 Drive",
"Hornet Sportabout", "Lincoln Continental", "Lotus Europa", "Maserati Bora",
"Mazda RX4", "Mazda RX4 Wag", "Merc 230", "Merc 240D", "Merc 280",
"Merc 280C", "Merc 450SE", "Merc 450SL", "Merc 450SLC", "Pontiac Firebird",
"Porsche 914-2", "Toyota Corolla", "Toyota Corona", "Valiant",
"Volvo 142E"
), class = "factor"), mpg = c(
15.2, 10.4, 13.3, 14.7,
22.8, 15.5, 14.3, 19.7, 32.4, 27.3, 15.8, 30.4, 21.4, 18.7, 10.4,
30.4, 15, 21, 21, 22.8, 24.4, 19.2, 17.8, 16.4, 17.3, 15.2, 19.2,
26, 33.9, 21.5, 18.1, 21.4
), cyl = c(
8L, 8L, 8L, 8L, 4L, 8L,
8L, 6L, 4L, 4L, 8L, 4L, 6L, 8L, 8L, 4L, 8L, 6L, 6L, 4L, 4L, 6L,
6L, 8L, 8L, 8L, 8L, 4L, 4L, 4L, 6L, 4L
), disp = c(
304, 472, 350,
440, 108, 318, 360, 145, 78.7, 79, 351, 75.7, 258, 360, 460,
95.1, 301, 160, 160, 140.8, 146.7, 167.6, 167.6, 275.8, 275.8,
275.8, 400, 120.3, 71.1, 120.1, 225, 121
), hp = c(
150L, 205L,
245L, 230L, 93L, 150L, 245L, 175L, 66L, 66L, 264L, 52L, 110L,
175L, 215L, 113L, 335L, 110L, 110L, 95L, 62L, 123L, 123L, 180L,
180L, 180L, 175L, 91L, 65L, 97L, 105L, 109L
), drat = c(
3.15,
2.93, 3.73, 3.23, 3.85, 2.76, 3.21, 3.62, 4.08, 4.08, 4.22, 4.93,
3.08, 3.15, 3, 3.77, 3.54, 3.9, 3.9, 3.92, 3.69, 3.92, 3.92,
3.07, 3.07, 3.07, 3.08, 4.43, 4.22, 3.7, 2.76, 4.11
), wt = c(
3.435,
5.25, 3.84, 5.345, 2.32, 3.52, 3.57, 2.77, 2.2, 1.935, 3.17,
1.615, 3.215, 3.44, 5.424, 1.513, 3.57, 2.62, 2.875, 3.15, 3.19,
3.44, 3.44, 4.07, 3.73, 3.78, 3.845, 2.14, 1.835, 2.465, 3.46,
2.78
), qsec = c(
17.3, 17.98, 15.41, 17.42, 18.61, 16.87, 15.84,
15.5, 19.47, 18.9, 14.5, 18.52, 19.44, 17.02, 17.82, 16.9, 14.6,
16.46, 17.02, 22.9, 20, 18.3, 18.9, 17.4, 17.6, 18, 17.05, 16.7,
19.9, 20.01, 20.22, 18.6
), vs = c(
0L, 0L, 0L, 0L, 1L, 0L, 0L,
0L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 1L, 1L,
0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L
), am = c(
0L, 0L, 0L, 0L, 1L,
0L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L
), gear = c(
3L, 3L,
3L, 3L, 4L, 3L, 3L, 5L, 4L, 4L, 5L, 4L, 3L, 3L, 3L, 5L, 5L, 4L,
4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 5L, 4L, 3L, 3L, 4L
), carb = c(
2L,
4L, 4L, 4L, 1L, 2L, 4L, 6L, 1L, 1L, 4L, 2L, 1L, 2L, 4L, 2L, 8L,
4L, 4L, 2L, 2L, 4L, 4L, 3L, 3L, 3L, 2L, 2L, 1L, 1L, 1L, 2L
),
color_available___red = c(
1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
), color_available___green = c(
1L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L
), color_available___blue = c(
1L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
), color_available___black = c(
0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L
), motor_trend_cars_complete = c(
1L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
), letter_group___a = c(
1L,
0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L
), letter_group___b = c(
1L, 0L, 0L, 1L, 1L, 0L, 1L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
), letter_group___c = c(
0L,
0L, 1L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L
), choice = structure(c(
3L, 1L, 2L, 2L, 1L, 1L, 2L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
), levels = c(
"", "choice1",
"choice2"
), class = "factor"), grouping_complete = c(
2L,
0L, 2L, 2L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L
)
), row.names = c(
1L, 5L, 6L, 9L, 11L, 12L, 13L, 18L, 19L,
20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 34L, 35L,
36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L
), class = "data.frame"),
sale = structure(list(
row = structure(c(
1L, 1L, 1L, 3L, 3L,
4L, 7L, 7L, 7L, 7L, 20L, 20L, 20L
), levels = c(
"AMC Javelin",
"Cadillac Fleetwood", "Camaro Z28", "Chrysler Imperial",
"Datsun 710", "Dodge Challenger", "Duster 360", "Ferrari Dino",
"Fiat 128", "Fiat X1-9", "Ford Pantera L", "Honda Civic",
"Hornet 4 Drive", "Hornet Sportabout", "Lincoln Continental",
"Lotus Europa", "Maserati Bora", "Mazda RX4", "Mazda RX4 Wag",
"Merc 230", "Merc 240D", "Merc 280", "Merc 280C", "Merc 450SE",
"Merc 450SL", "Merc 450SLC", "Pontiac Firebird", "Porsche 914-2",
"Toyota Corolla", "Toyota Corona", "Valiant", "Volvo 142E"
), class = "factor"), redcap_repeat_instrument = c(
"sale",
"sale", "sale", "sale", "sale", "sale", "sale", "sale", "sale",
"sale", "sale", "sale", "sale"
), redcap_repeat_instance = c(
1L,
2L, 3L, 1L, 2L, 1L, 1L, 2L, 3L, 4L, 1L, 2L, 3L
), price = c(
12000.5,
13750.77, 15004.57, 7800, 8000, 7500, 8756.4, 6800.88, 8888.88,
970, 7800.98, 7954, 6800.55
), color = c(
1L, 3L, 2L, 2L, 3L,
1L, 4L, 2L, 1L, 4L, 2L, 1L, 3L
), customer = structure(c(
2L,
12L, 7L, 4L, 14L, 5L, 10L, 8L, 3L, 6L, 13L, 9L, 11L
), levels = c(
"",
"Bob", "Erica", "Janice", "Jim", "Juan", "Kim", "Pablo",
"Quentin", "Sarah", "Sharon", "Sue", "Ted", "Tim"
), class = "factor"),
sale_complete = c(
0L, 2L, 0L, 2L, 0L, 2L, 1L, 0L, 0L,
0L, 0L, 0L, 2L
)
), row.names = c(
2L, 3L, 4L, 7L, 8L, 10L,
14L, 15L, 16L, 17L, 31L, 32L, 33L
), class = "data.frame")
)
)
})
# Test that REDCap_split can handle a focused dataset
records_red <- records[
!records$redcap_repeat_instrument == "sale",
!names(records) %in%
metadata$field_name[metadata$form_name == "sale"] &
!names(records) == "sale_complete"
]
records_red$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 R code enhanced CSV export matches reference --------------------
if (requireNamespace("Hmisc", quietly = TRUE)) {
test_that("R code enhanced export matches reference", {
redcap_output_csv2 <-
REDCap_split(REDCap_process_csv(records), metadata)
# expect_known_hash(redcap_output_csv2, "578dc054e59ec92a21e950042e08ee37")
# dput(redcap_output_csv2)
expect_identical(
redcap_output_csv2,
list(structure(list(
row = structure(1:32, levels = c(
"AMC Javelin",
"Cadillac Fleetwood", "Camaro Z28", "Chrysler Imperial", "Datsun 710",
"Dodge Challenger", "Duster 360", "Ferrari Dino", "Fiat 128",
"Fiat X1-9", "Ford Pantera L", "Honda Civic", "Hornet 4 Drive",
"Hornet Sportabout", "Lincoln Continental", "Lotus Europa", "Maserati Bora",
"Mazda RX4", "Mazda RX4 Wag", "Merc 230", "Merc 240D", "Merc 280",
"Merc 280C", "Merc 450SE", "Merc 450SL", "Merc 450SLC", "Pontiac Firebird",
"Porsche 914-2", "Toyota Corolla", "Toyota Corona", "Valiant",
"Volvo 142E"
), class = c("labelled", "factor"), label = "Name"),
mpg = structure(c(
15.2, 10.4, 13.3, 14.7, 22.8, 15.5, 14.3,
19.7, 32.4, 27.3, 15.8, 30.4, 21.4, 18.7, 10.4, 30.4, 15,
21, 21, 22.8, 24.4, 19.2, 17.8, 16.4, 17.3, 15.2, 19.2, 26,
33.9, 21.5, 18.1, 21.4
), label = "Miles/(US) gallon", class = c(
"labelled",
"numeric"
)), cyl = structure(c(
8L, 8L, 8L, 8L, 4L, 8L, 8L,
6L, 4L, 4L, 8L, 4L, 6L, 8L, 8L, 4L, 8L, 6L, 6L, 4L, 4L, 6L,
6L, 8L, 8L, 8L, 8L, 4L, 4L, 4L, 6L, 4L
), label = "Number of cylinders", class = c(
"labelled",
"integer"
)), disp = structure(c(
304, 472, 350, 440, 108,
318, 360, 145, 78.7, 79, 351, 75.7, 258, 360, 460, 95.1,
301, 160, 160, 140.8, 146.7, 167.6, 167.6, 275.8, 275.8,
275.8, 400, 120.3, 71.1, 120.1, 225, 121
), label = "Displacement", class = c(
"labelled",
"numeric"
)), hp = structure(c(
150L, 205L, 245L, 230L, 93L,
150L, 245L, 175L, 66L, 66L, 264L, 52L, 110L, 175L, 215L,
113L, 335L, 110L, 110L, 95L, 62L, 123L, 123L, 180L, 180L,
180L, 175L, 91L, 65L, 97L, 105L, 109L
), label = "Gross horsepower", class = c(
"labelled",
"integer"
)), drat = structure(c(
3.15, 2.93, 3.73, 3.23, 3.85,
2.76, 3.21, 3.62, 4.08, 4.08, 4.22, 4.93, 3.08, 3.15, 3,
3.77, 3.54, 3.9, 3.9, 3.92, 3.69, 3.92, 3.92, 3.07, 3.07,
3.07, 3.08, 4.43, 4.22, 3.7, 2.76, 4.11
), label = "Rear axle ratio", class = c(
"labelled",
"numeric"
)), wt = structure(c(
3.435, 5.25, 3.84, 5.345, 2.32,
3.52, 3.57, 2.77, 2.2, 1.935, 3.17, 1.615, 3.215, 3.44, 5.424,
1.513, 3.57, 2.62, 2.875, 3.15, 3.19, 3.44, 3.44, 4.07, 3.73,
3.78, 3.845, 2.14, 1.835, 2.465, 3.46, 2.78
), label = "Weight", class = c(
"labelled",
"numeric"
)), qsec = structure(c(
17.3, 17.98, 15.41, 17.42,
18.61, 16.87, 15.84, 15.5, 19.47, 18.9, 14.5, 18.52, 19.44,
17.02, 17.82, 16.9, 14.6, 16.46, 17.02, 22.9, 20, 18.3, 18.9,
17.4, 17.6, 18, 17.05, 16.7, 19.9, 20.01, 20.22, 18.6
), label = "1/4 mile time", class = c(
"labelled",
"numeric"
)), vs = structure(c(
0L, 0L, 0L, 0L, 1L, 0L, 0L,
0L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 1L,
1L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L
), label = "V engine?", class = c(
"labelled",
"integer"
)), am = structure(c(
0L, 0L, 0L, 0L, 1L, 0L, 0L,
1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L
), label = "Transmission", class = c(
"labelled",
"integer"
)), gear = structure(c(
3L, 3L, 3L, 3L, 4L, 3L, 3L,
5L, 4L, 4L, 5L, 4L, 3L, 3L, 3L, 5L, 5L, 4L, 4L, 4L, 4L, 4L,
4L, 3L, 3L, 3L, 3L, 5L, 4L, 3L, 3L, 4L
), label = "Number of forward gears", class = c(
"labelled",
"integer"
)), carb = structure(c(
2L, 4L, 4L, 4L, 1L, 2L, 4L,
6L, 1L, 1L, 4L, 2L, 1L, 2L, 4L, 2L, 8L, 4L, 4L, 2L, 2L, 4L,
4L, 3L, 3L, 3L, 2L, 2L, 1L, 1L, 1L, 2L
), label = "Number of carburetors", class = c(
"labelled",
"integer"
)), color_available___red = structure(c(
1L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
), label = "Colors Available (choice<-Red)", class = c(
"labelled",
"integer"
)), color_available___green = structure(c(
1L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
), label = "Colors Available (choice<-Green)", class = c(
"labelled",
"integer"
)), color_available___blue = structure(c(
1L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
), label = "Colors Available (choice<-Blue)", class = c(
"labelled",
"integer"
)), color_available___black = structure(c(
0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
), label = "Colors Available (choice<-Black)", class = c(
"labelled",
"integer"
)), motor_trend_cars_complete = structure(c(
1L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L
), label = "Complete?", class = c("labelled", "integer")), letter_group___a = structure(c(
1L, 0L, 1L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
), label = "Which group? (choice<-A)", class = c(
"labelled",
"integer"
)), letter_group___b = structure(c(
1L, 0L, 0L, 1L,
1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L,
1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
), label = "Which group? (choice<-B)", class = c(
"labelled",
"integer"
)), letter_group___c = structure(c(
0L, 0L, 1L, 1L,
1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
), label = "Which group? (choice<-C)", class = c(
"labelled",
"integer"
)), choice = structure(c(
3L, 1L, 2L, 2L, 1L, 1L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
), levels = c(
"",
"choice1", "choice2"
), class = c("labelled", "factor"), label = "Choose one"),
grouping_complete = structure(c(
2L, 0L, 2L, 2L, 0L, 0L, 1L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
), label = "Complete?", class = c(
"labelled",
"integer"
)), cyl.factor = structure(c(
6L, 6L, 6L, 6L, 2L,
6L, 6L, 4L, 2L, 2L, 6L, 2L, 4L, 6L, 6L, 2L, 6L, 4L, 4L, 2L,
2L, 4L, 4L, 6L, 6L, 6L, 6L, 2L, 2L, 2L, 4L, 2L
), levels = c(
"3",
"4", "5", "6", "7", "8"
), class = "factor"), vs.factor = structure(c(
2L,
2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L,
2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L,
1L
), levels = c("Yes", "No"), class = "factor"), am.factor = structure(c(
1L,
1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L,
2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L,
2L
), levels = c("Automatic", "Manual"), class = "factor"),
gear.factor = structure(c(
1L, 1L, 1L, 1L, 2L, 1L, 1L, 3L,
2L, 2L, 3L, 2L, 1L, 1L, 1L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L,
1L, 1L, 1L, 1L, 3L, 2L, 1L, 1L, 2L
), levels = c(
"3", "4",
"5"
), class = "factor"), carb.factor = structure(c(
2L, 4L,
4L, 4L, 1L, 2L, 4L, 6L, 1L, 1L, 4L, 2L, 1L, 2L, 4L, 2L, 8L,
4L, 4L, 2L, 2L, 4L, 4L, 3L, 3L, 3L, 2L, 2L, 1L, 1L, 1L, 2L
), levels = c("1", "2", "3", "4", "5", "6", "7", "8"), class = "factor"),
color_available___red.factor = structure(c(
2L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
), levels = c(
"Unchecked",
"Checked"
), class = "factor"), color_available___green.factor = structure(c(
2L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L
), levels = c("Unchecked", "Checked"), class = "factor"),
color_available___blue.factor = structure(c(
2L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
), levels = c(
"Unchecked",
"Checked"
), class = "factor"), color_available___black.factor = structure(c(
1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L
), levels = c("Unchecked", "Checked"), class = "factor"),
motor_trend_cars_complete.factor = structure(c(
2L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
), levels = c(
"Incomplete",
"Unverified", "Complete"
), class = "factor"), letter_group___a.factor = structure(c(
2L,
1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L
), levels = c("Unchecked", "Checked"), class = "factor"),
letter_group___b.factor = structure(c(
2L, 1L, 1L, 2L, 2L,
1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
), levels = c(
"Unchecked",
"Checked"
), class = "factor"), letter_group___c.factor = structure(c(
1L,
1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L
), levels = c("Unchecked", "Checked"), class = "factor"),
choice.factor = structure(c(
2L, NA, 1L, 1L, NA, NA, 1L, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2L, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA
), levels = c(
"Choice 1",
"Choice 2"
), class = "factor"), grouping_complete.factor = structure(c(
3L,
1L, 3L, 3L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L
), levels = c("Incomplete", "Unverified", "Complete"), class = "factor")
), row.names = c(
1L,
5L, 6L, 9L, 11L, 12L, 13L, 18L, 19L, 20L, 21L, 22L, 23L, 24L,
25L, 26L, 27L, 28L, 29L, 30L, 34L, 35L, 36L, 37L, 38L, 39L, 40L,
41L, 42L, 43L, 44L, 45L
), class = "data.frame"), sale = structure(list(
row = structure(c(
1L, 1L, 1L, 3L, 3L, 4L, 7L, 7L, 7L, 7L,
20L, 20L, 20L
), levels = c(
"AMC Javelin", "Cadillac Fleetwood",
"Camaro Z28", "Chrysler Imperial", "Datsun 710", "Dodge Challenger",
"Duster 360", "Ferrari Dino", "Fiat 128", "Fiat X1-9", "Ford Pantera L",
"Honda Civic", "Hornet 4 Drive", "Hornet Sportabout", "Lincoln Continental",
"Lotus Europa", "Maserati Bora", "Mazda RX4", "Mazda RX4 Wag",
"Merc 230", "Merc 240D", "Merc 280", "Merc 280C", "Merc 450SE",
"Merc 450SL", "Merc 450SLC", "Pontiac Firebird", "Porsche 914-2",
"Toyota Corolla", "Toyota Corona", "Valiant", "Volvo 142E"
), class = c("labelled", "factor"), label = "Name"), redcap_repeat_instrument = c(
"sale",
"sale", "sale", "sale", "sale", "sale", "sale", "sale", "sale",
"sale", "sale", "sale", "sale"
), redcap_repeat_instance = structure(c(
1L,
2L, 3L, 1L, 2L, 1L, 1L, 2L, 3L, 4L, 1L, 2L, 3L
), label = "Repeat Instance", class = c(
"labelled",
"integer"
)), price = structure(c(
12000.5, 13750.77, 15004.57,
7800, 8000, 7500, 8756.4, 6800.88, 8888.88, 970, 7800.98,
7954, 6800.55
), label = "Sale price", class = c(
"labelled",
"numeric"
)), color = structure(c(
1L, 3L, 2L, 2L, 3L, 1L,
4L, 2L, 1L, 4L, 2L, 1L, 3L
), label = "Color", class = c(
"labelled",
"integer"
)), customer = structure(c(
2L, 12L, 7L, 4L, 14L,
5L, 10L, 8L, 3L, 6L, 13L, 9L, 11L
), levels = c(
"", "Bob",
"Erica", "Janice", "Jim", "Juan", "Kim", "Pablo", "Quentin",
"Sarah", "Sharon", "Sue", "Ted", "Tim"
), class = c(
"labelled",
"factor"
), label = "Customer Name"), sale_complete = structure(c(
0L,
2L, 0L, 2L, 0L, 2L, 1L, 0L, 0L, 0L, 0L, 0L, 2L
), label = "Complete?", class = c(
"labelled",
"integer"
)), redcap_repeat_instrument.factor = structure(c(
1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
), levels = "Sale", class = "factor"),
color.factor = structure(c(
1L, 3L, 2L, 2L, 3L, 1L, 4L, 2L,
1L, 4L, 2L, 1L, 3L
), levels = c("red", "green", "blue", "black"), class = "factor"), sale_complete.factor = structure(c(
1L,
3L, 1L, 3L, 1L, 3L, 2L, 1L, 1L, 1L, 1L, 1L, 3L
), levels = c(
"Incomplete",
"Unverified", "Complete"
), class = "factor")
), row.names = c(
2L,
3L, 4L, 7L, 8L, 10L, 14L, 15L, 16L, 17L, 31L, 32L, 33L
), class = "data.frame"))
)
})
}
if (requireNamespace("readr", quietly = TRUE)) {
metadata <-
readr::read_csv(get_data_location(
"ExampleProject_DataDictionary_2018-06-07.csv"
))
records <-
readr::read_csv(get_data_location(
"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)
)
}
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)
})
}
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