tests/testthat/test_read_data.R

In shug0131/cctu: In-house Functions for Report Writing at Cambridge Clinical Trials Unit

context("read_data")

 data_table <- data.frame(name=c("dirtydata","meta"),
                          file=c("dirtydata.csv",
                                 "meta_table.xlsx"),
                          folder=system.file("extdata", package="cctu"),
                          stringsAsFactors = FALSE
                          )




 test_that("basic case",{expect_is(data_table_summary(data_table), "data.frame")
 options("verbose"=TRUE)

 expect_false(exists("dirtydata"))
 expect_false(exists("meta"))
 read_data(data_table)
 expect_true(exists("dirtydata"))
 expect_true(exists("meta"))
 rm(dirtydata, meta)
 data2 <- data_table
 names(data2) <- c("link","path","folder")
 read_data(data2, name_variable="link", file_variable="path")
 expect_true(exists("dirtydata"))
 expect_true(exists("meta"))
 rm(dirtydata, meta)

 }
)

 test_that("non standard case",{
 X <- read_data(data_table[1,], frame=NULL, stringsAsFactors=FALSE)
 expect_false(is.factor(X$gender))
 expect_error(read_data("dirtydata",data_table, fun=readxl::read_excel, frame=NULL))
 expect_warning(read_data("dirtydata",data_table, fun=print, remove_blank_rows_cols_option=FALSE,frame=NULL),
                "this function is designed to be used for reading in data. You are calling: print"
 )


 old_fn <- base::requireNamespace
 myrequireNamespace <- function(...) FALSE
 unlockBinding("requireNamespace", as.environment("package:base"))
 assign("requireNamespace",myrequireNamespace, "package:base")
 expect_error(read_data("meta",data_table,  frame=NULL),"Package \"readxl\" needed for this function to load excel files")
 assign("requireNamespace",old_fn, "package:base")
 lockBinding("requireNamespace", as.environment("package:base"))
 rm(old_fn, myrequireNamespace)

}
)


test_that( "interaction with apply_macro_dict",{
        my_data <- data.frame(
         name=c("dt","dlu","clu"),
         file=c("pilotdata.csv","pilotdata_dlu.csv", "pilotdata_clu.csv"),
         folder=system.file("extdata",  package="cctu")

        )

        read_data(my_data, colClasses = "character")
        dt$subjid <- substr(dt$USUBJID, 8, 11)
        # Apply CLU and DLU files

        expect_s3_class(apply_macro_dict(dt, dlu = dlu, clu = clu),"data.table")
        dt <- apply_macro_dict(dt, dlu = dlu, clu = clu)
        expect_true( "arm" %in% names(dt))
        expect_false("arm" %in% dlu$shortcode)
        # this assume the dlu & clu have teh column names cleaned, as well
        # as cleaning the content of "shortcode". shortcode -> shortcode
        # expect_flase("arm" %in% clu$shortcode)
        clean_dlu <- tidy_dlu(dlu)
        expect_true("arm" %in% clean_dlu$shortcode)

        expect_type( dt$arm, "double")
        expect_true(has.labels(dt$arm))
        # there's no columns that are dates, to check their conversion,
        #but I'm not so bothered about these.
        read_data(my_data, colClasses = "character", clean_names=TRUE)
        # The remove_blank_rows_cols, woudl be applicable when a
        # trial is early in its life. No patients have doen the later visits
        # So MACRO does not export them , and or they might be deleted
        # does apply_macro_dict look to see what is in the data, and then
        # look up the clu/dlu to convert, and do it in that order?
        dt$subjid <- substr(dt$usubjid, 8, 11)
        # expect_error( apply_macro_dict(dt, dlu = dlu, clu = clu))
}
)