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AG Damsbo
parent
992091f94c
commit
be3969d007
11 changed files with 200 additions and 265 deletions
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@ -4,75 +4,85 @@ REDCap_process_csv <- function(data) {
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stop("This test requires the 'Hmisc' package")
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}
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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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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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#Setting Factors(will create new variable for factors)
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data$redcap_repeat_instrument.factor = factor(data$redcap_repeat_instrument,levels=c("sale"))
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data$cyl.factor = factor(data$cyl,levels=c("3","4","5","6","7","8"))
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data$vs.factor = factor(data$vs,levels=c("1","0"))
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data$am.factor = factor(data$am,levels=c("0","1"))
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data$gear.factor = factor(data$gear,levels=c("3","4","5"))
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data$carb.factor = factor(data$carb,levels=c("1","2","3","4","5","6","7","8"))
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data$color_available___red.factor = factor(data$color_available___red,levels=c("0","1"))
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data$color_available___green.factor = factor(data$color_available___green,levels=c("0","1"))
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data$color_available___blue.factor = factor(data$color_available___blue,levels=c("0","1"))
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data$color_available___black.factor = factor(data$color_available___black,levels=c("0","1"))
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data$motor_trend_cars_complete.factor = factor(data$motor_trend_cars_complete,levels=c("0","1","2"))
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data$letter_group___a.factor = factor(data$letter_group___a,levels=c("0","1"))
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data$letter_group___b.factor = factor(data$letter_group___b,levels=c("0","1"))
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data$letter_group___c.factor = factor(data$letter_group___c,levels=c("0","1"))
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data$choice.factor = factor(data$choice,levels=c("choice1","choice2"))
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data$grouping_complete.factor = factor(data$grouping_complete,levels=c("0","1","2"))
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data$color.factor = factor(data$color,levels=c("1","2","3","4"))
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data$sale_complete.factor = factor(data$sale_complete,levels=c("0","1","2"))
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data$redcap_repeat_instrument.factor = factor(data$redcap_repeat_instrument, levels =
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c("sale"))
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data$cyl.factor = factor(data$cyl, levels = c("3", "4", "5", "6", "7", "8"))
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data$vs.factor = factor(data$vs, levels = c("1", "0"))
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data$am.factor = factor(data$am, levels = c("0", "1"))
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data$gear.factor = factor(data$gear, levels = c("3", "4", "5"))
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data$carb.factor = factor(data$carb, levels = c("1", "2", "3", "4", "5", "6", "7", "8"))
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data$color_available___red.factor = factor(data$color_available___red, levels =
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c("0", "1"))
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data$color_available___green.factor = factor(data$color_available___green, levels =
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c("0", "1"))
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data$color_available___blue.factor = factor(data$color_available___blue, levels =
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c("0", "1"))
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data$color_available___black.factor = factor(data$color_available___black, levels =
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c("0", "1"))
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data$motor_trend_cars_complete.factor = factor(data$motor_trend_cars_complete, levels =
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c("0", "1", "2"))
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data$letter_group___a.factor = factor(data$letter_group___a, levels =
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c("0", "1"))
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data$letter_group___b.factor = factor(data$letter_group___b, levels =
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c("0", "1"))
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data$letter_group___c.factor = factor(data$letter_group___c, levels =
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c("0", "1"))
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data$choice.factor = factor(data$choice, levels = c("choice1", "choice2"))
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data$grouping_complete.factor = factor(data$grouping_complete, levels =
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c("0", "1", "2"))
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data$color.factor = factor(data$color, levels = c("1", "2", "3", "4"))
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data$sale_complete.factor = factor(data$sale_complete, levels = c("0", "1", "2"))
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levels(data$redcap_repeat_instrument.factor)=c("Sale")
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levels(data$cyl.factor)=c("3","4","5","6","7","8")
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levels(data$vs.factor)=c("Yes","No")
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levels(data$am.factor)=c("Automatic","Manual")
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levels(data$gear.factor)=c("3","4","5")
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levels(data$carb.factor)=c("1","2","3","4","5","6","7","8")
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levels(data$color_available___red.factor)=c("Unchecked","Checked")
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levels(data$color_available___green.factor)=c("Unchecked","Checked")
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levels(data$color_available___blue.factor)=c("Unchecked","Checked")
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levels(data$color_available___black.factor)=c("Unchecked","Checked")
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levels(data$motor_trend_cars_complete.factor)=c("Incomplete","Unverified","Complete")
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levels(data$letter_group___a.factor)=c("Unchecked","Checked")
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levels(data$letter_group___b.factor)=c("Unchecked","Checked")
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levels(data$letter_group___c.factor)=c("Unchecked","Checked")
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levels(data$choice.factor)=c("Choice 1","Choice 2")
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levels(data$grouping_complete.factor)=c("Incomplete","Unverified","Complete")
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levels(data$color.factor)=c("red","green","blue","black")
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levels(data$sale_complete.factor)=c("Incomplete","Unverified","Complete")
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levels(data$redcap_repeat_instrument.factor) = c("Sale")
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levels(data$cyl.factor) = c("3", "4", "5", "6", "7", "8")
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levels(data$vs.factor) = c("Yes", "No")
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levels(data$am.factor) = c("Automatic", "Manual")
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levels(data$gear.factor) = c("3", "4", "5")
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levels(data$carb.factor) = c("1", "2", "3", "4", "5", "6", "7", "8")
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levels(data$color_available___red.factor) = c("Unchecked", "Checked")
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levels(data$color_available___green.factor) = c("Unchecked", "Checked")
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levels(data$color_available___blue.factor) = c("Unchecked", "Checked")
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levels(data$color_available___black.factor) = c("Unchecked", "Checked")
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levels(data$motor_trend_cars_complete.factor) = c("Incomplete", "Unverified", "Complete")
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levels(data$letter_group___a.factor) = c("Unchecked", "Checked")
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levels(data$letter_group___b.factor) = c("Unchecked", "Checked")
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levels(data$letter_group___c.factor) = c("Unchecked", "Checked")
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levels(data$choice.factor) = c("Choice 1", "Choice 2")
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levels(data$grouping_complete.factor) = c("Incomplete", "Unverified", "Complete")
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levels(data$color.factor) = c("red", "green", "blue", "black")
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levels(data$sale_complete.factor) = c("Incomplete", "Unverified", "Complete")
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data
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}
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@ -6,4 +6,5 @@
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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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get_data_location <- function(x)
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file.path("data", x)
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@ -1,26 +1,12 @@
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context("Reading in JSON")
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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(get_data_location("ExampleProject_metadata.json"))
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metadata <- jsonlite::fromJSON(
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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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get_data_location(
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"ExampleProject_records.json"
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)
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)
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records <- jsonlite::fromJSON(get_data_location("ExampleProject_records.json"))
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redcap_output_json1 <- REDCap_split(records, metadata)
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expect_known_hash(redcap_output_json1, "2c8b6531597182af1248f92124161e0c")
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})
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# Check the httr export ---------------------------------------------------
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# Something will go here.
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@ -1,4 +1,3 @@
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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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@ -6,10 +5,8 @@ metadata <- read.csv(
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stringsAsFactors = TRUE
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)
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records <- read.csv(
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get_data_location("ExampleProject_DATA_2018-06-07_1129.csv"),
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stringsAsFactors = TRUE
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)
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records <- read.csv(get_data_location("ExampleProject_DATA_2018-06-07_1129.csv"),
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stringsAsFactors = TRUE)
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redcap_output_csv1 <- REDCap_split(records, metadata)
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@ -21,48 +18,38 @@ test_that("CSV export matches reference", {
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# Test that R code enhanced CSV export matches reference --------------------
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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 <-
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REDCap_split(REDCap_process_csv(records), metadata)
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expect_known_hash(redcap_output_csv2, "34f82cab35bf8aae47d08cd96f743e6b")
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expect_known_hash(redcap_output_csv2, "34f82cab35bf8aae47d08cd96f743e6b")
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})
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}
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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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metadata <- readr::read_csv(get_data_location("ExampleProject_DataDictionary_2018-06-07.csv"))
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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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records <- readr::read_csv(get_data_location("ExampleProject_DATA_2018-06-07_1129.csv"))
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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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expect_identical(lapply(redcap_output_readr, FUN),
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lapply(redcap_output_csv1, FUN))
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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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test_that("Result of data read in with `readr` will match result with `read.csv`",
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{
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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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# 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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# 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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@ -1,63 +1,57 @@
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context("Using the `forms = 'all'` argument")
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# Global variables --------------------------------------------------------
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# Cars
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metadata <- jsonlite::fromJSON(
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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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metadata <-
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jsonlite::fromJSON(get_data_location("ExampleProject_metadata.json"))
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records <- jsonlite::fromJSON(
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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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records <-
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jsonlite::fromJSON(get_data_location("ExampleProject_records.json"))
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redcap_output_json <- REDCap_split(records, metadata, forms = "all")
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# Longitudinal
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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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), get_data_location
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c(records = "WARRIORtestForSoftwa_DATA_2018-06-21_1431.csv",
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metadata = "WARRIORtestForSoftwareUpgrades_DataDictionary_2018-06-21.csv"),
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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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redcap[["metadata"]] <- with(redcap, metadata[metadata[,1] > "",])
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redcap_output_long <- with(redcap, REDCap_split(records, metadata, forms = "all"))
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redcap[["metadata"]] <- with(redcap, metadata[metadata[, 1] > "",])
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redcap_output_long <-
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with(redcap, REDCap_split(records, metadata, forms = "all"))
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redcap_long_names <- names(redcap[[1]])
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# Tests -------------------------------------------------------------------
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test_that("Each form is an element in the list", {
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expect_length(redcap_output_json, 3L)
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expect_identical(names(redcap_output_json), c("motor_trend_cars", "grouping", "sale"))
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expect_identical(names(redcap_output_json),
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c("motor_trend_cars", "grouping", "sale"))
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})
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test_that("All variables land somewhere", {
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expect_true(setequal(names(records), Reduce("union", sapply(redcap_output_json, names))))
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expect_true(setequal(names(records), Reduce(
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"union", sapply(redcap_output_json, names)
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)))
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})
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test_that("Primary table name is ignored", {
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expect_identical(
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REDCap_split(records, metadata, "HELLO", "all"),
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redcap_output_json
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)
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expect_identical(REDCap_split(records, metadata, "HELLO", "all"),
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redcap_output_json)
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})
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test_that("Supports longitudinal data", {
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# setdiff(redcap_long_names, Reduce("union", sapply(redcap_output_long, names)))
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## [1] "informed_consent_and_addendum_timestamp"
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expect_true(setequal(redcap_long_names, Reduce("union", sapply(redcap_output_long, names))))
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expect_true(setequal(redcap_long_names, Reduce(
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"union", sapply(redcap_output_long, names)
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)))
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})
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|
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@ -1,4 +1,4 @@
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context("Longitudinal data")
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## "Longitudinal data"
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test_that("CSV export matches reference", {
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file_paths <- sapply(
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|
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@ -1,28 +1,17 @@
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context("Primary table name processing")
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## "Primary table name processing"
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# Global variables -------------------------------------------------------
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metadata <- jsonlite::fromJSON(
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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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metadata <- jsonlite::fromJSON(get_data_location("ExampleProject_metadata.json"))
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records <- jsonlite::fromJSON(
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get_data_location(
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"ExampleProject_records.json"
|
||||
)
|
||||
)
|
||||
records <- jsonlite::fromJSON(get_data_location("ExampleProject_records.json"))
|
||||
|
||||
ref_hash <- "2c8b6531597182af1248f92124161e0c"
|
||||
|
||||
# Tests -------------------------------------------------------------------
|
||||
test_that("Will not use a repeating instrument name for primary table", {
|
||||
|
||||
redcap_output_json1 <- expect_warning(
|
||||
REDCap_split(records, metadata, "sale"),
|
||||
"primary table"
|
||||
)
|
||||
redcap_output_json1 <- expect_warning(REDCap_split(records, metadata, "sale"),
|
||||
"primary table")
|
||||
|
||||
expect_known_hash(redcap_output_json1, ref_hash)
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue