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https://github.com/agdamsbo/REDCapCAST.git
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Completed working test suite and added CI
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parent
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commit
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^.*\.Rproj$
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^\.Rproj\.user$
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^\.travis\.yml$
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^appveyor\.yml$
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5
R/.travis.yml
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5
R/.travis.yml
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# R for travis: see documentation at https://docs.travis-ci.com/user/languages/r
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language: R
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sudo: false
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cache: packages
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45
R/appveyor.yml
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45
R/appveyor.yml
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# DO NOT CHANGE the "init" and "install" sections below
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# Download script file from GitHub
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init:
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ps: |
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$ErrorActionPreference = "Stop"
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Invoke-WebRequest http://raw.github.com/krlmlr/r-appveyor/master/scripts/appveyor-tool.ps1 -OutFile "..\appveyor-tool.ps1"
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Import-Module '..\appveyor-tool.ps1'
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install:
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ps: Bootstrap
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cache:
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- C:\RLibrary
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# Adapt as necessary starting from here
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build_script:
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- travis-tool.sh install_deps
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test_script:
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- travis-tool.sh run_tests
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on_failure:
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- 7z a failure.zip *.Rcheck\*
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- appveyor PushArtifact failure.zip
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artifacts:
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- path: '*.Rcheck\**\*.log'
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name: Logs
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- path: '*.Rcheck\**\*.out'
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name: Logs
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- path: '*.Rcheck\**\*.fail'
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name: Logs
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- path: '*.Rcheck\**\*.Rout'
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name: Logs
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- path: '\*_*.tar.gz'
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name: Bits
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- path: '\*_*.zip'
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name: Bits
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@ -1,3 +1,49 @@
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# Setup -------------------------------------------------------------------
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devtools::load_all()
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library(digest)
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library(magrittr)
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library(jsonlite)
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ref_data_location <- function(x) file.path("tests","testthat","data", x)
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# RCurl -------------------------------------------------------------------
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REDCap_split(
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ref_data_location("ExampleProject_records.json") %>% fromJSON,
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ref_data_location("ExampleProject_metadata.json") %>% fromJSON
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) %>% digest
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# Basic CSV ---------------------------------------------------------------
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REDCap_split(
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ref_data_location("ExampleProject_DATA_2018-06-07_1129.csv") %>% read.csv,
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ref_data_location("ExampleProject_DataDictionary_2018-06-07.csv") %>% read.csv
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) %>% digest
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# REDCap R Export ---------------------------------------------------------
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source("tests/testthat/helper-ExampleProject_R_2018-06-07_1129.r")
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REDCap_split(
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ref_data_location("ExampleProject_DATA_2018-06-07_1129.csv") %>%
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read.csv %>%
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REDCap_process_csv,
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ref_data_location("ExampleProject_DataDictionary_2018-06-07.csv") %>% read.csv
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) %>% digest
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# Longitudinal data from @pbchase; Issue #7 -------------------------------
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# Something will go here.
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file_paths <- sapply(
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c(
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records = "WARRIORtestForSoftwa_DATA_2018-06-21_1431.csv",
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metadata = "WARRIORtestForSoftwareUpgrades_DataDictionary_2018-06-21.csv"
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), ref_data_location
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)
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redcap <- lapply(file_paths, read.csv, stringsAsFactors = FALSE)
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redcap[["metadata"]] <- with(redcap, metadata[metadata[,1] > "",])
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with(redcap, REDCap_split(records, metadata)) %>% digest
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REDCap_process_csv <- function(data) {
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#Load Hmisc library
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if (!require(Hmisc))
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if (!requireNamespace("Hmisc", quietly = TRUE)) {
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stop("This test requires the 'Hmisc' package")
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}
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label(data$row)="Name"
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label(data$redcap_repeat_instrument)="Repeat Instrument"
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label(data$redcap_repeat_instance)="Repeat Instance"
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label(data$mpg)="Miles/(US) gallon"
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label(data$cyl)="Number of cylinders"
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label(data$disp)="Displacement"
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label(data$hp)="Gross horsepower"
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label(data$drat)="Rear axle ratio"
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label(data$wt)="Weight"
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label(data$qsec)="1/4 mile time"
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label(data$vs)="V engine?"
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label(data$am)="Transmission"
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label(data$gear)="Number of forward gears"
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label(data$carb)="Number of carburetors"
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label(data$color_available___red)="Colors Available (choice=Red)"
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label(data$color_available___green)="Colors Available (choice=Green)"
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label(data$color_available___blue)="Colors Available (choice=Blue)"
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label(data$color_available___black)="Colors Available (choice=Black)"
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label(data$motor_trend_cars_complete)="Complete?"
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label(data$letter_group___a)="Which group? (choice=A)"
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label(data$letter_group___b)="Which group? (choice=B)"
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label(data$letter_group___c)="Which group? (choice=C)"
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label(data$choice)="Choose one"
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label(data$grouping_complete)="Complete?"
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label(data$price)="Sale price"
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label(data$color)="Color"
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label(data$customer)="Customer Name"
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label(data$sale_complete)="Complete?"
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Hmisc::label(data$row)="Name"
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Hmisc::label(data$redcap_repeat_instrument)="Repeat Instrument"
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Hmisc::label(data$redcap_repeat_instance)="Repeat Instance"
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Hmisc::label(data$mpg)="Miles/(US) gallon"
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Hmisc::label(data$cyl)="Number of cylinders"
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Hmisc::label(data$disp)="Displacement"
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Hmisc::label(data$hp)="Gross horsepower"
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Hmisc::label(data$drat)="Rear axle ratio"
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Hmisc::label(data$wt)="Weight"
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Hmisc::label(data$qsec)="1/4 mile time"
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Hmisc::label(data$vs)="V engine?"
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Hmisc::label(data$am)="Transmission"
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Hmisc::label(data$gear)="Number of forward gears"
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Hmisc::label(data$carb)="Number of carburetors"
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Hmisc::label(data$color_available___red)="Colors Available (choice=Red)"
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Hmisc::label(data$color_available___green)="Colors Available (choice=Green)"
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Hmisc::label(data$color_available___blue)="Colors Available (choice=Blue)"
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Hmisc::label(data$color_available___black)="Colors Available (choice=Black)"
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Hmisc::label(data$motor_trend_cars_complete)="Complete?"
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Hmisc::label(data$letter_group___a)="Which group? (choice=A)"
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Hmisc::label(data$letter_group___b)="Which group? (choice=B)"
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Hmisc::label(data$letter_group___c)="Which group? (choice=C)"
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Hmisc::label(data$choice)="Choose one"
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Hmisc::label(data$grouping_complete)="Complete?"
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Hmisc::label(data$price)="Sale price"
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Hmisc::label(data$color)="Color"
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Hmisc::label(data$customer)="Customer Name"
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Hmisc::label(data$sale_complete)="Complete?"
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#Setting Units
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R/tests/testthat/helper-paths.R
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9
R/tests/testthat/helper-paths.R
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# get_data_location <- function(x) {
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# system.file(
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# "testdata",
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# x,
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# package = "REDCapRITS"
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# )
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# }
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get_data_location <- function(x) file.path("data", x)
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context("Reading in JSON")
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# Set up the path ----------------------------------------------------------
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data_dir <- system.file("tests", "testthat", "data", package = "REDCapRITS")
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# Check the RCurl export ---------------------------------------------------
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test_that("JSON character vector from RCurl matches reference", {
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metadata <- jsonlite::fromJSON(
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file.path(
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data_dir,
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get_data_location(
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"ExampleProject_metadata.json"
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)
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)
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records <- jsonlite::fromJSON(
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file.path(
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data_dir,
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get_data_location(
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"ExampleProject_records.json"
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)
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)
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context("CSV Exports")
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# Set up the path and data -------------------------------------------------
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data_dir <- system.file("tests", "testthat", "data", package = "REDCapRITS")
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metadata <- read.csv(
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file.path(
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data_dir,
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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 <- read.csv(
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file.path(
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data_dir,
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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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})
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# Test that R code enhanced CSV export matches reference --------------------
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test_that("R code enhanced export matches reference", {
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source(file.path(data_dir, "ExampleProject_R_2018-06-07_1129.r"))
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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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redcap_output_csv2 <- REDCap_split(REDCap_process_csv(records), metadata)
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expect_known_hash(redcap_output_csv2, "34f82cab35bf8aae47d08cd96f743e6b")
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})
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}
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expect_known_hash(redcap_output_csv2, "34f82cab35bf8aae47d08cd96f743e6b")
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})
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context("Longitudinal data")
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test_that("CSV export matches reference", {
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# Reading in the files
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file_paths <- file.path(
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system.file("tests", "testthat", "data", package = "REDCapRITS"),
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file_paths <- sapply(
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c(
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records = "WARRIORtestForSoftwa_DATA_2018-06-21_1431.csv",
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metadata = "WARRIORtestForSoftwareUpgrades_DataDictionary_2018-06-21.csv"
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)
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), get_data_location
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)
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redcap <- lapply(file_paths, read.csv, stringsAsFactors = FALSE)
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names(redcap) <- c("records", "metadata")
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redcap[["metadata"]] <- with(redcap, metadata[metadata[,1] > "",])
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redcap_output <- with(redcap, REDCap_split(records, metadata))
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@ -157,6 +157,9 @@ welcome your contributions!
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## Instructions
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### R
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[![Travis-CI Build Status](https://travis-ci.org/SpectrumHealthResearch/REDCapRITS.svg?branch=master)](https://travis-ci.org/SpectrumHealthResearch/REDCapRITS)
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[![AppVeyor Build Status](https://ci.appveyor.com/api/projects/status/github/SpectrumHealthResearch/REDCapRITS?branch=master&svg=true)](https://ci.appveyor.com/project/SpectrumHealthResearch/REDCapRITS)
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#### Installation
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First you must install the package. To do so, execute the following in your R console:
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