2018-06-26 05:48:55 +02:00
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context("CSV Exports")
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# Set up the path and data -------------------------------------------------
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metadata <- read.csv(
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2018-06-28 23:20:14 +02:00
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get_data_location(
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2018-06-26 05:48:55 +02:00
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"ExampleProject_DataDictionary_2018-06-07.csv"
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)
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)
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records <- read.csv(
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2018-06-28 23:20:14 +02:00
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get_data_location(
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2018-06-26 05:48:55 +02:00
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"ExampleProject_DATA_2018-06-07_1129.csv"
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)
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)
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2019-07-29 18:30:52 +02:00
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redcap_output_csv1 <- REDCap_split(records, metadata)
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2018-06-26 05:48:55 +02:00
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# Test that basic CSV export matches reference ------------------------------
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test_that("CSV export matches reference", {
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expect_known_hash(redcap_output_csv1, "f74558d1939c17d9ff0e08a19b956e26")
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})
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# Test that R code enhanced CSV export matches reference --------------------
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2018-06-28 23:20:14 +02:00
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if (requireNamespace("Hmisc", quietly = TRUE)) {
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test_that("R code enhanced export matches reference", {
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redcap_output_csv2 <- REDCap_split(REDCap_process_csv(records), metadata)
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2018-06-26 05:48:55 +02:00
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2018-06-28 23:20:14 +02:00
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expect_known_hash(redcap_output_csv2, "34f82cab35bf8aae47d08cd96f743e6b")
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})
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}
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2018-06-26 05:48:55 +02:00
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2019-07-29 18:30:52 +02:00
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if (requireNamespace("readr", quietly = TRUE)) {
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context("Compatibility with readr")
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metadata <- readr::read_csv(
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get_data_location(
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"ExampleProject_DataDictionary_2018-06-07.csv"
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)
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)
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records <- readr::read_csv(
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get_data_location(
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"ExampleProject_DATA_2018-06-07_1129.csv"
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)
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)
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redcap_output_readr <- REDCap_split(records, metadata)
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expect_matching_elements <- function(FUN) {
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FUN <- match.fun(FUN)
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expect_identical(
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lapply(redcap_output_readr, FUN),
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lapply(redcap_output_csv1, FUN)
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)
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}
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test_that("Result of data read in with `readr` will match result with `read.csv`", {
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# The list itself
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expect_identical(length(redcap_output_readr), length(redcap_output_csv1))
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expect_identical(names(redcap_output_readr), names(redcap_output_csv1))
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# Each element of the list
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expect_matching_elements(names)
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expect_matching_elements(dim)
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})
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}
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