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ginbergginberg
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add examples to all functions (#202)
* add examples to functions
1 parent bb1c9ff commit 1e46b67

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‎R/Aggregation.R

+8
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@@ -23,6 +23,14 @@
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#' @return
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#' An object of class \code{covariateData}.
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#'
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#' @examples
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#' \dontrun{
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#' covariateData <- FeatureExtraction:::createEmptyCovariateData(cohortId = 1,
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#' aggregated = FALSE,
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#' temporal = FALSE)
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#' aggregatedCovariateData <- aggregateCovariates(covariateData)
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#' }
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#'
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#' @export
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aggregateCovariates <- function(covariateData) {
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if (!isCovariateData(covariateData))

‎R/CompareCohorts.R

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@@ -31,6 +31,14 @@
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#' A data frame with means and standard deviations per cohort as well as the standardized difference
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#' of mean.
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#'
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#' @examples
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#' \dontrun{
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#' binaryCovDataFile <- system.file("testdata/binaryCovariateData.zip",
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#' package = "FeatureExtraction")
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#' covariateData1 <- loadCovariateData(binaryCovDataFile)
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#' covariateData2 <- loadCovariateData(binaryCovDataFile)
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#' covDataDiff <- computeStandardizedDifference(covariateData1, covariateData2, cohortId1 = 1, cohortId2 = 2)
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#' }
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#' @export
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computeStandardizedDifference <- function(covariateData1, covariateData2, cohortId1 = NULL, cohortId2 = NULL) {
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if (!isCovariateData(covariateData1))

‎R/CovariateData.R

+53-3
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@@ -53,7 +53,16 @@ setClass("CovariateData", contains = "Andromeda")
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#' The data will be written to a set of files in the folder specified by the user.
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#'
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#' @examples
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#' # todo
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#' \dontrun{
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#' covariateData <- FeatureExtraction:::createEmptyCovariateData(cohortId = 1,
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#' aggregated = FALSE,
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#' temporal = FALSE)
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#' # For this example we'll use a temporary file location:
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#' fileName <- tempfile()
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#' saveCovariateData(covariateData = covariateData, file = fileName)
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#' # Cleaning up the file used in this example:
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#' unlink(fileName)
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#' }
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#'
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#' @export
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saveCovariateData <- function(covariateData, file) {
@@ -82,7 +91,11 @@ saveCovariateData <- function(covariateData, file) {
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#' An object of class \code{CovariateData}.
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#'
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#' @examples
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#' # todo
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#' \dontrun{
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#' binaryCovDataFile <- system.file("testdata/binaryCovariateData.zip",
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#' package = "FeatureExtraction")
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#' covData <- loadCovariateData(binaryCovDataFile)
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#' }
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#'
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#' @export
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loadCovariateData <- function(file, readOnly) {
@@ -151,11 +164,19 @@ print.summary.CovariateData <- function(x, ...) {
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#' Check whether an object is a CovariateData object
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#'
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#' @param x The object to check.
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#' @param x The object to check.
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#'
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#' @return
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#' A logical value.
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#'
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#' @examples
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#' \dontrun{
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#' binaryCovDataFile <- system.file("testdata/binaryCovariateData.zip",
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#' package = "FeatureExtraction")
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#' covData <- loadCovariateData(binaryCovDataFile)
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#' isCovData <- isCovariateData(covData)
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#' }
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#'
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#' @export
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isCovariateData <- function(x) {
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return(inherits(x, "CovariateData"))
@@ -168,6 +189,14 @@ isCovariateData <- function(x) {
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#' @return
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#' A logical value.
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#'
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#' @examples
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#' \dontrun{
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#' covariateData <- FeatureExtraction:::createEmptyCovariateData(cohortId = 1,
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#' aggregated = FALSE,
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#' temporal = FALSE)
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#' isAggrCovData <- isAggregatedCovariateData(covariateData)
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#' }
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#'
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#' @export
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isAggregatedCovariateData <- function(x) {
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if (!isCovariateData(x))
@@ -184,6 +213,14 @@ isAggregatedCovariateData <- function(x) {
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#' @return
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#' A logical value.
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#'
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#' @examples
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#' \dontrun{
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#' covariateData <- FeatureExtraction:::createEmptyCovariateData(cohortId = 1,
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#' aggregated = FALSE,
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#' temporal = FALSE)
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#' isTempCovData <- isTemporalCovariateData(covariateData)
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#' }
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#'
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#' @export
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isTemporalCovariateData <- function(x) {
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if (!isCovariateData(x))
@@ -193,6 +230,19 @@ isTemporalCovariateData <- function(x) {
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return("timeId" %in% colnames(x$covariates))
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}
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#' Creates an empty covariate data object
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#'
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#' @param cohortId cohort number
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#' @param aggregated if the data should be aggregated
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#' @param temporal if the data is temporary
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#'
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#' @examples
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#' \dontrun{
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#' covariateData <- FeatureExtraction:::createEmptyCovariateData(cohortId = 1,
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#' aggregated = FALSE,
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#' temporal = FALSE)
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#' }
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#'
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createEmptyCovariateData <- function(cohortId, aggregated, temporal) {
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dummy <- tibble(covariateId = 1,
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covariateValue = 1)

‎R/DetailedCovariateSettings.R

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@@ -27,6 +27,21 @@
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#'
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#' @return
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#' An object of type \code{covariateSettings}, to be used in other functions.
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#'
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#' @examples
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#' \dontrun{
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#' analysisDetails <- createAnalysisDetails(analysisId = 1,
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#' sqlFileName = "DemographicsGender.sql",
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#' parameters = list(analysisId = 1,
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#' analysisName = "Gender",
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#' domainId = "Demographics"),
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#' includedCovariateConceptIds = c(),
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#' addDescendantsToInclude = FALSE,
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#' excludedCovariateConceptIds = c(),
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#' addDescendantsToExclude = FALSE,
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#' includedCovariateIds = c())
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#' covSettings <- createDetailedCovariateSettings(analyses = analysisDetails)
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#' }
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#'
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#' @export
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createDetailedCovariateSettings <- function(analyses = list()) {
@@ -57,6 +72,23 @@ createDetailedCovariateSettings <- function(analyses = list()) {
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#' @return
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#' An object of type \code{covariateSettings}, to be used in other functions.
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#'
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#' @examples
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#' \dontrun{
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#' analysisDetails <- createAnalysisDetails(analysisId = 1,
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#' sqlFileName = "DemographicsGender.sql",
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#' parameters = list(analysisId = 1,
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#' analysisName = "Gender",
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#' domainId = "Demographics"),
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#' includedCovariateConceptIds = c(),
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#' addDescendantsToInclude = FALSE,
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#' excludedCovariateConceptIds = c(),
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#' addDescendantsToExclude = FALSE,
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#' includedCovariateIds = c())
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#' covSettings <- createDetailedTemporalCovariateSettings(analyses = analysisDetails,
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#' temporalStartDays = -365:-1,
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#' temporalEndDays = -365:-1)
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#' }
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#'
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#' @export
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createDetailedTemporalCovariateSettings <- function(analyses = list(),
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temporalStartDays = -365:-1,
@@ -144,6 +176,12 @@ createAnalysisDetails <- function(analysisId,
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#' @return
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#' An object of type \code{covariateSettings}, to be used in other functions.
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#'
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#' @examples
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#' \dontrun{
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#' covSettings <- createDefaultCovariateSettings()
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#' detailedSettings <- convertPrespecSettingsToDetailedSettings(covariateSettings = covSettings)
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#' }
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#'
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#' @export
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convertPrespecSettingsToDetailedSettings <- function(covariateSettings) {
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json <- .toJson(covariateSettings)
@@ -170,6 +208,15 @@ convertPrespecSettingsToDetailedSettings <- function(covariateSettings) {
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#' @return
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#' An object of type \code{covariateSettings}, to be used in other functions.
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#'
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#' @examples
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#' \dontrun{
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#' covSettings <- createDefaultCovariateSettings(includedCovariateConceptIds = c(1),
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#' addDescendantsToInclude = FALSE,
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#' excludedCovariateConceptIds = c(2),
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#' addDescendantsToExclude = FALSE,
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#' includedCovariateIds = c(1))
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#' }
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#'
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#' @export
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createDefaultCovariateSettings <- function(includedCovariateConceptIds = c(),
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addDescendantsToInclude = FALSE,
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#' @return
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#' An object of type \code{covariateSettings}, to be used in other functions.
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#'
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#' @examples
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#' \dontrun{
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#' covSettings <- createDefaultTemporalCovariateSettings(includedCovariateConceptIds = c(1),
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#' addDescendantsToInclude = FALSE,
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#' excludedCovariateConceptIds = c(2),
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#' addDescendantsToExclude = FALSE,
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#' includedCovariateIds = c(1))
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#' }
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#'
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#' @export
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createDefaultTemporalCovariateSettings <- function(includedCovariateConceptIds = c(),
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addDescendantsToInclude = FALSE,

‎R/GetCovariates.R

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@@ -60,6 +60,27 @@
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#' @return
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#' Returns an object of type \code{covariateData}, containing information on the covariates.
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#'
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#' @examples
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#' \dontrun{
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#' eunomiaConnectionDetails <- Eunomia::getEunomiaConnectionDetails()
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#' covSettings <- createDefaultCovariateSettings()
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#' Eunomia::createCohorts(connectionDetails = eunomiaConnectionDetails,
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#' cdmDatabaseSchema = "main",
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#' cohortDatabaseSchema = "main",
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#' cohortTable = "cohort")
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#' covData <- getDbCovariateData(connectionDetails = eunomiaConnectionDetails,
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#' oracleTempSchema = NULL,
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#' cdmDatabaseSchema = "main",
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#' cdmVersion = "5",
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#' cohortTable = "cohort",
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#' cohortDatabaseSchema = "main",
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#' cohortTableIsTemp = FALSE,
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#' cohortId = -1,
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#' rowIdField = "subject_id",
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#' covariateSettings = covSettings,
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#' aggregated = FALSE)
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#' }
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#'
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#' @export
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getDbCovariateData <- function(connectionDetails = NULL,
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connection = NULL,

‎R/GetCovariatesFromCohortAttributes.R

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@@ -23,6 +23,38 @@
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#' \code{\link{createCohortAttrCovariateSettings}} function.
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#'
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#' @template GetCovarParams
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#'
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#' @examples
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#' \dontrun{
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#' connectionDetails <- Eunomia::getEunomiaConnectionDetails()
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#' Eunomia::createCohorts(connectionDetails = connectionDetails,
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#' cdmDatabaseSchema = "main",
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#' cohortDatabaseSchema = "main",
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#' cohortTable = "cohort")
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#' connection <- DatabaseConnector::connect(connectionDetails)
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#' sql <- "SELECT 1 AS attribute_definition_id, 'Length of observation in days' AS attribute_name
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#' INTO @cohort_database_schema.@attribute_definition_table;"
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#' sql <- SqlRender::render(sql, cohort_database_schema = "main", attribute_definition_table = "attribute_definition")
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#' sql <- SqlRender::translate(sql = sql,
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#' targetDialect = attr(connection, "dbms"))
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#' DatabaseConnector::executeSql(connection, sql)
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#' covariateSettings <- createCohortAttrCovariateSettings(attrDatabaseSchema = "main",
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#' cohortAttrTable = "cohort_attribute",
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#' attrDefinitionTable = "attribute_definition",
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#' includeAttrIds = c(1),
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#' isBinary = FALSE,
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#' missingMeansZero = FALSE)
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#'
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#' covData <- getDbCohortAttrCovariatesData(connection = connection,
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#' oracleTempSchema = NULL,
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#' cdmDatabaseSchema = "main",
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#' cdmVersion = "5",
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#' cohortTable = "cohort",
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#' cohortId = 1,
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#' rowIdField = "subject_id",
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#' covariateSettings = covariateSettings,
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#' aggregated = FALSE)
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#' }
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#'
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#' @export
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getDbCohortAttrCovariatesData <- function(connection,
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#' @return
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#' An object of type \code{covariateSettings}, to be used in other functions.
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#'
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#' @examples
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#' \dontrun{
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#' covariateSettings <- createCohortAttrCovariateSettings(analysisId = 1,
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#' attrDatabaseSchema = "main",
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#' attrDefinitionTable = "attribute_definition",
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#' cohortAttrTable = "cohort_attribute",
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#' includeAttrIds = c(1),
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#' isBinary = FALSE,
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#' missingMeansZero = FALSE)
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#' }
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#'
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#' @export
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createCohortAttrCovariateSettings <- function(analysisId = -1,
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attrDatabaseSchema,

‎R/GetDefaultCovariates.R

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@@ -33,6 +33,21 @@
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#' @param targetAnalysisRefTable (Optional) The name of the table where the analysis reference will be stored.
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#'
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#' @template GetCovarParams
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#'
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#' @examples
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#' \dontrun{
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#' connection <- DatabaseConnector::connect(connectionDetails)
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#' Eunomia::createCohorts(connectionDetails)
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#'
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#' results <- getDbDefaultCovariateData(connection = connection,
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#' cdmDatabaseSchema = "main",
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#' cohortTable = "cohort",
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#' covariateSettings = createDefaultCovariateSettings(),
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#' targetDatabaseSchema = "main",
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#' targetCovariateTable = "ut_cov",
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#' targetCovariateRefTable = "ut_cov_ref",
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#' targetAnalysisRefTable = "ut_cov_analysis_ref")
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#' }
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#'
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#' @export
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getDbDefaultCovariateData <- function(connection,

‎R/HelperFunctions.R

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#'
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#' @return
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#' An object of type \code{covariateData}.
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#'
25+
#' @examples
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#' \dontrun{
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#' covariateData <- FeatureExtraction:::createEmptyCovariateData(cohortId = 1,
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#' aggregated = FALSE,
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#' temporal = FALSE)
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#'
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#' covData <- filterByRowId(covariateData = covariateData,
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#' rowIds = 1)
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#' }
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#'
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#' @export
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filterByRowId <- function(covariateData, rowIds) {
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if (!isCovariateData(covariateData))
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#'
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#' @return
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#' An object of type \code{covariateData}.
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#'
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#' @examples
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#' \dontrun{
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#' covariateData <- FeatureExtraction:::createEmptyCovariateData(cohortId = 1,
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#' aggregated = FALSE,
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#' temporal = FALSE)
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#'
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#' covData <- filterByCohortDefinitionId(covariateData = covariateData,
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#' cohortId = 1)
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#' }
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#'
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#' @export
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filterByCohortDefinitionId <- function(covariateData, cohortId) {
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if (!isCovariateData(covariateData))

‎R/Normalization.R

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#' frequency.
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#' @param normalize Normalize the covariates? (dividing by the max).
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#' @param removeRedundancy Should redundant covariates be removed?
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#'
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#' @examples
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#' \dontrun{
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#' covariateData <- FeatureExtraction:::createEmptyCovariateData(cohortId = 1,
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#' aggregated = FALSE,
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#' temporal = FALSE)
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#'
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#' covData <- tidyCovariateData(covariateData = covariateData,
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#' minFraction = 0.001,
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#' normalize = TRUE,
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#' removeRedundancy = TRUE)
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#' }
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#'
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#' @export
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tidyCovariateData <- function(covariateData,

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