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Fix dataSetToDataFrame #606

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merged 2 commits into from
Sep 8, 2021
Merged

Fix dataSetToDataFrame #606

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a792506
-Add the line "name" to print of data set
PavelBal Sep 8, 2021
851231e
Avoid code repetition
PavelBal Sep 8, 2021
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1 change: 1 addition & 0 deletions R/data-set.R
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Original file line number Diff line number Diff line change
Expand Up @@ -223,6 +223,7 @@ DataSet <- R6::R6Class(
#' @param ... Rest arguments.
print = function(...) {
private$printClass()
private$printLine("Name", self$name)
private$printLine("X dimension", self$xDimension)
private$printLine("X unit", self$xUnit)
private$printLine("Y dimension", self$yDimension)
Expand Down
57 changes: 32 additions & 25 deletions R/utilities-data-set.R
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Original file line number Diff line number Diff line change
@@ -1,4 +1,5 @@
.makeDataFrameColumn <- function(dataSet, property, metaDataName = NULL) {
.makeDataFrameColumn <- function(dataSets, property, metaDataName = NULL) {
columForDataSet <- function(dataSet){
# check length of entry for a certain property of this data set, i.e. if it exists
if (is.null(metaDataName)) {
len <- length(dataSet[[property]])
Expand All @@ -17,6 +18,11 @@
} else {
dataSet[[property]]
}
}

unlist(lapply(dataSets, function(x) {
columForDataSet(x)
}), use.names = FALSE)
}

#' Loads data (typically observed data) from a PKML file and creates a \code{DataSet} from it.
Expand Down Expand Up @@ -55,41 +61,42 @@ saveDataSetToPKML <- function(dataSet, filePath) {
rClr::clrCall(dataRepositoryTask, "SaveDataRepository", dataSet$dataRepository$ref, filePath)
}

#' Converts a list of DataSet objects to a data.frame
#' Converts a list of `DataSet` objects to a data.frame
#'
#' @param dataSets A list of DataSet objects or a single DataSet
#' @param dataSets A list of `DataSet` objects or a single `DataSet`
#'
#' @return DataSet objects as data.frame with columns name, xValue, yValue, yErrorValues,
#' xDimension, xUnit, yDimension, yUnit, yErrorType, yErrorUnit, yMolWeight
#' @return DataSet objects as data.frame with columns name, xValues, yValues, yErrorValues,
#' xDimension, xUnit, yDimension, yUnit, yErrorType, yErrorUnit, molWeight, lloq,
#' and a column for each meta data that is present in any `DataSet`
#' @export
dataSetToDataFrame <- function(dataSets) {
dataSets <- c(dataSets)
validateIsOfType(dataSets, DataSet)

name <- unlist(mapply(.makeDataFrameColumn, dataSets, "name"))
xUnit <- unlist(mapply(.makeDataFrameColumn, dataSets, "xUnit"))
yUnit <- unlist(mapply(.makeDataFrameColumn, dataSets, "yUnit"))
yErrorUnit <- as.character(unlist(mapply(.makeDataFrameColumn, dataSets, "yErrorUnit")))
xDimension <- unlist(mapply(.makeDataFrameColumn, dataSets, "xDimension"))
yDimension <- unlist(mapply(.makeDataFrameColumn, dataSets, "yDimension"))
yErrorType <- as.character(unlist(mapply(.makeDataFrameColumn, dataSets, "yErrorType")))
yMolWeight <- unlist(mapply(.makeDataFrameColumn, dataSets, "molWeight"))
xValue <- unlist(mapply(.makeDataFrameColumn, dataSets, "xValues"))
yValue <- unlist(mapply(.makeDataFrameColumn, dataSets, "yValues"))
yErrorValues <- unlist(mapply(.makeDataFrameColumn, dataSets, "yErrorValues"))

name <- .makeDataFrameColumn(dataSets, "name")
xUnit <- .makeDataFrameColumn(dataSets, "xUnit")
yUnit <- .makeDataFrameColumn(dataSets, "yUnit")
yErrorUnit <- .makeDataFrameColumn(dataSets, "yErrorUnit")
xDimension <- .makeDataFrameColumn(dataSets, "xDimension")
yDimension <- .makeDataFrameColumn(dataSets, "yDimension")
yErrorType <- .makeDataFrameColumn(dataSets, "yErrorType")
molWeight <- .makeDataFrameColumn(dataSets, "molWeight")
xValues <- .makeDataFrameColumn(dataSets, "xValues")
yValues <- .makeDataFrameColumn(dataSets, "yValues")
yErrorValues <- .makeDataFrameColumn(dataSets, "yErrorValues")
lloq <- .makeDataFrameColumn(dataSets, "LLOQ")
df <- data.frame(
name, xValue, yValue, yErrorValues, xDimension, xUnit, yDimension,
yUnit, yErrorType, yErrorUnit, yMolWeight
name, xValues, yValues, yErrorValues, xDimension, xUnit, yDimension,
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Renamed column names (using plural) and added a LLOQ column.

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if feels like you could write a method

makeColums <- function(dataSets, columnName) {
  unlist(lapply(dataSet, function(x){
.makeDatqaFrameColumn(x, columnsName)
}
}

or sthg like this

yUnit, yErrorType, yErrorUnit, molWeight, lloq
)

# get all names of meta data entries from all data sets
metaDataNames <- unique(unlist(sapply(dataSets, function(dataSets) {
return(names(dataSets[["metaData"]]))
})))
metaDataNames <- unique(unlist(lapply(dataSets, function(dataSets) {
names(dataSets[["metaData"]])
}), use.names = FALSE))
# add one column for each one
for (name in metaDataNames) {
col <- unlist(lapply(dataSets, .makeDataFrameColumn, "metaData", metaDataName = name))
col <- .makeDataFrameColumn(dataSets, "metaData", metaDataName = name)
df[[name]] <- col
}

Expand Down Expand Up @@ -127,11 +134,11 @@ loadDataSetsFromExcel <- function(xlsFilePath, importerConfiguration, importAllS
dataImporterTask <- getNetTask("DataImporterTask")
rClr::clrSet(dataImporterTask, "IgnoreSheetNamesAtImport", importAllSheets)
dataRepositories <- rClr::clrCall(dataImporterTask, "ImportExcelFromConfiguration", importerConfiguration$ref, xlsFilePath)
dataSets <- lapply(dataRepositories, function(x){
dataSets <- lapply(dataRepositories, function(x) {
repository <- DataRepository$new(x)
DataSet$new(repository)
})
names(dataSets) <- lapply(dataSets, function(x){
names(dataSets) <- lapply(dataSets, function(x) {
x$name
})

Expand Down
11 changes: 6 additions & 5 deletions man/dataSetToDataFrame.Rd
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108 changes: 54 additions & 54 deletions tests/testthat/test-utilities-data-set.R
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Original file line number Diff line number Diff line change
Expand Up @@ -15,9 +15,10 @@ test_that("It can convert an empty data set", {
expect_equal(
dataSetToDataFrame(dataSet),
data.frame(
name = character(0), xValue = logical(0), yValue = logical(0), yErrorValues = logical(0),
name = character(0), xValues = logical(0), yValues = logical(0), yErrorValues = logical(0),
xDimension = character(0), xUnit = character(0), yDimension = character(0),
yUnit = character(0), yErrorType = character(0), yErrorUnit = character(0), yMolWeight = logical(0)
yUnit = character(0), yErrorType = logical(0), yErrorUnit = logical(0), molWeight = logical(0),
lloq = logical(0)
)
)
})
Expand All @@ -27,10 +28,10 @@ test_that("It can convert a data set with xValues and yValues set by setValues,
expect_equal(
dataSetToDataFrame(dataSet),
data.frame(
name = rep("", 5), xValue = dataSet$xValues, yValue = dataSet$yValues, yErrorValues = rep(NA, 5),
name = rep("", 5), xValues = dataSet$xValues, yValues = dataSet$yValues, yErrorValues = rep(NA, 5),
xDimension = rep(dataSet$xDimension, 5), xUnit = rep(dataSet$xUnit, 5),
yDimension = rep(dataSet$yDimension, 5), yUnit = rep(dataSet$yUnit, 5),
yErrorType = rep(NA_character_, 5), yErrorUnit = rep(NA_character_, 5), yMolWeight = rep(NA, 5)
yErrorType = rep(NA, 5), yErrorUnit = rep(NA, 5), molWeight = rep(NA, 5), lloq = rep(NA, 5)
)
)
})
Expand All @@ -39,88 +40,56 @@ test_that("It can convert a data set with only non-empty fields, except for meta
dataSet$setValues(xValues = c(1, 2, 3, 4, 5), yValues = c(10, 20, 30, 40, 50), yErrorValues = c(0, 1, 2, 3, 0))
dataSet$name <- "Data1"
dataSet$molWeight <- 123
dataSet$LLOQ <- 0.2
expect_equal(
dataSetToDataFrame(dataSet),
data.frame(
name = rep(dataSet$name, 5), xValue = dataSet$xValues,
yValue = dataSet$yValues, yErrorValues = dataSet$yErrorValues,
name = rep(dataSet$name, 5), xValues = dataSet$xValues,
yValues = dataSet$yValues, yErrorValues = dataSet$yErrorValues,
xDimension = rep(dataSet$xDimension, 5), xUnit = rep(dataSet$xUnit, 5),
yDimension = rep(dataSet$yDimension, 5), yUnit = rep(dataSet$yUnit, 5),
yErrorType = rep(dataSet$yErrorType, 5), yErrorUnit = rep(dataSet$yErrorUnit, 5),
yMolWeight = rep(dataSet$molWeight, 5)
molWeight = rep(dataSet$molWeight, 5), lloq = rep(dataSet$LLOQ, 5)
)
)
})

test_that("It can convert a list of data sets", {
dataSet$setValues(xValues = c(1, 2, 3, 4, 5), yValues = c(10, 20, 30, 40, 50), yErrorValues = c(0, 1, 2, 3, 0))
dataSet$name <- "Data1"
dataSet$molWeight <- 123
dataSet2 <- DataSet$new()
dataSet2$setValues(xValues = c(6, 7, 8), yValues = c(11, 21, 31))
dataSet2$molWeight <- 456

expect_equal(
dataSetToDataFrame(list(dataSet, dataSet2)),
data.frame(
name = c(rep(dataSet$name, 5), rep("", 3)), xValue = c(dataSet$xValues, dataSet2$xValues),
yValue = c(dataSet$yValues, dataSet2$yValues), yErrorValues = c(dataSet$yErrorValues, rep(NA, 3)),
xDimension = c(rep(dataSet$xDimension, 5), rep(dataSet2$xDimension, 3)),
xUnit = c(rep(dataSet$xUnit, 5), rep(dataSet2$xUnit, 3)),
yDimension = c(rep(dataSet$yDimension, 5), rep(dataSet2$yDimension, 3)),
yUnit = c(rep(dataSet$yUnit, 5), rep(dataSet2$yUnit, 3)),
yErrorType = c(rep(dataSet$yErrorType, 5), rep(NA_character_, 3)),
yErrorUnit = c(rep(dataSet$yErrorUnit, 5), rep(NA_character_, 3)),
yMolWeight = c(rep(dataSet$molWeight, 5), rep(dataSet2$molWeight, 3))
)
)
})

test_that("It can convert a single data set with meta data", {
dataSet$setValues(xValues = c(1, 2, 3, 4, 5), yValues = c(10, 20, 30, 40, 50))
dataSet$name <- "Data1"
dataSet$molWeight <- 123
dataSet$addMetaData("City", "Rome")

test_that("It can convert a data set with metaData", {
dataSet$addMetaData("Organ", "Blood")
expect_equal(
dataSetToDataFrame(dataSet),
data.frame(
name = rep(dataSet$name, 5), xValue = dataSet$xValues, yValue = dataSet$yValues, yErrorValues = rep(NA, 5),
name = rep(dataSet$name, 5), xValues = dataSet$xValues,
yValues = dataSet$yValues, yErrorValues = dataSet$yErrorValues,
xDimension = rep(dataSet$xDimension, 5), xUnit = rep(dataSet$xUnit, 5),
yDimension = rep(dataSet$yDimension, 5), yUnit = rep(dataSet$yUnit, 5),
yErrorType = rep(NA_character_, 5), yErrorUnit = rep(NA_character_, 5), yMolWeight = rep(123, 5),
City = rep("Rome", 5)
yErrorType = rep(dataSet$yErrorType, 5), yErrorUnit = rep(dataSet$yErrorUnit, 5),
molWeight = rep(dataSet$molWeight, 5), lloq = rep(dataSet$LLOQ, 5),
Organ = rep("Blood", 5)
)
)
})

test_that("It can convert a list of data sets with meta data", {
dataSet$setValues(xValues = c(1, 2, 3, 4, 5), yValues = c(10, 20, 30, 40, 50), yErrorValues = c(0, 1, 2, 3, 0))
dataSet$name <- "Data1"
dataSet$molWeight <- 123
dataSet$addMetaData("City", "Rome")
test_that("It can convert a list of data sets", {
dataSet2 <- DataSet$new()
dataSet2$setValues(xValues = c(6, 7, 8), yValues = c(11, 21, 31))
dataSet2$molWeight <- 456
dataSet2$addMetaData("City", "Berlin")
dataSet2$addMetaData("ZIP", "10245")
dataSet2$addMetaData("Country", "Germany")
dataSet2$addMetaData("Compartment", "Plasma")

expect_equal(
dataSetToDataFrame(list(dataSet, dataSet2)),
data.frame(
name = c(rep(dataSet$name, 5), rep("", 3)), xValue = c(dataSet$xValues, dataSet2$xValues),
yValue = c(dataSet$yValues, dataSet2$yValues), yErrorValues = c(dataSet$yErrorValues, rep(NA, 3)),
name = c(rep(dataSet$name, 5), rep("", 3)), xValues = c(dataSet$xValues, dataSet2$xValues),
yValues = c(dataSet$yValues, dataSet2$yValues), yErrorValues = c(dataSet$yErrorValues, rep(NA, 3)),
xDimension = c(rep(dataSet$xDimension, 5), rep(dataSet2$xDimension, 3)),
xUnit = c(rep(dataSet$xUnit, 5), rep(dataSet2$xUnit, 3)),
yDimension = c(rep(dataSet$yDimension, 5), rep(dataSet2$yDimension, 3)),
yUnit = c(rep(dataSet$yUnit, 5), rep(dataSet2$yUnit, 3)),
yErrorType = c(rep(dataSet$yErrorType, 5), rep(NA_character_, 3)),
yErrorUnit = c(rep(dataSet$yErrorUnit, 5), rep(NA_character_, 3)),
yMolWeight = c(rep(dataSet$molWeight, 5), rep(dataSet2$molWeight, 3)),
City = c(rep("Rome", 5), rep("Berlin", 3)),
ZIP = c(rep(NA_character_, 5), rep("10245", 3)),
Country = c(rep(NA_character_, 5), rep("Germany", 3))
molWeight = c(rep(dataSet$molWeight, 5), rep(dataSet2$molWeight, 3)),
lloq = c(rep(dataSet$LLOQ, 5), rep(NA, 3)),
Organ = c(rep("Blood", 5), rep(NA, 3)), Compartment = c(rep(NA, 5), rep("Plasma", 3))
)
)
})
Expand Down Expand Up @@ -191,3 +160,34 @@ test_that("it can load when loading from file with one sheet without
expect_true(isOfType(dataSets, DataSet))
expect_equal(length(dataSets), 4)
})

test_that("it can convert DataSets loaded from excel to data.frame", {
dataSets <- loadDataSetsFromExcel(xlsFilePath = xlsFilePath, importerConfiguration = importerConfiguration, importAllSheets = TRUE)
dataSetsFrame <- dataSetToDataFrame(dataSets)
expect_equal(names(dataSetsFrame), c(
"name",
"xValues",
"yValues",
"yErrorValues",
"xDimension",
"xUnit",
"yDimension",
"yUnit",
"yErrorType",
"yErrorUnit",
"molWeight",
"lloq",
"Source",
"Sheet",
"Study Id",
"Organ",
"Compartment",
"Species",
"Gender",
"Molecule",
"Route",
"Subject Id",
"Dose",
"Group Id"
))
})