housekeeping (#159)

* housekeeping - spell check - consistently use markdown syntax in roxygen docs - style - vignette chunk label fixes - minor rephrasing - update roxygen version - remove unnecessary pander from suggests - follow best practices for Rproject * edits to plot config vignette and sundry * edits to theme maker vignette * edits to the TLF workflow vignette * better chunk options * fix warnings from ggplot2 3.3.3 * revert ggplot2 version bump; spelling * edits to box plot vignette * edits to atom plots vignette * edits to PK ratio vignette
Open-Systems-Pharmacology · Sep 13, 2021 · dbaa7a6 · dbaa7a6 · IndrajeetPatil · Sep 13, 2021
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -30,14 +30,12 @@ Imports:
 Depends: 
     R (>= 3.5)
 Encoding: UTF-8
-RoxygenNote: 7.1.1
+RoxygenNote: 7.1.2
 Roxygen: list(markdown = TRUE)
-LazyData: true    
 Suggests: 
     knitr,
     rmarkdown,
     testthat (>= 2.1.0),
-    pander,
     gridExtra
 VignetteBuilder: knitr
 Collate: 

diff --git a/R/aaa-utilities.R b/R/aaa-utilities.R
@@ -87,7 +87,7 @@ parseUpdateAestheticProperty <- function(aestheticProperty, plotConfigurationPro
       ',aesthetic = "', aestheticProperty, '"))'
     )),
     # remove the legend of aesthetic if default unmapped aesthetic
-    parse(text = paste0("if(isIncluded(", aestheticProperty, 'Variable, "legendLabels")){plotObject <- plotObject + ggplot2::guides(', aestheticProperty, " = FALSE)}"))
+    parse(text = paste0("if(isIncluded(", aestheticProperty, 'Variable, "legendLabels")){plotObject <- plotObject + ggplot2::guides(', aestheticProperty, " = 'none')}"))
   )
 }
 

diff --git a/R/aggregation-input.R b/R/aggregation-input.R
@@ -14,17 +14,17 @@ AggregationInput <- R6::R6Class(
     #' @field aggregationDimension dimension of aggregation output
     aggregationDimension = NULL,
 
-    #' @description Create a new \code{AggregationInput} object
+    #' @description Create a new `AggregationInput` object
     #' @param aggregationFunction list of functions to use for aggregation
     #' @param aggregationFunctionName vector of function names
     #' that will be used as variable name of the aggregation
     #' @param aggregationUnit unit of aggregation output
     #' @param aggregationDimension dimension of aggregation output
-    #' @return A new \code{AggregationInput} object
+    #' @return A new `AggregationInput` object
     initialize = function(aggregationFunction = NULL,
-                              aggregationFunctionName = NULL,
-                              aggregationUnit = NULL,
-                              aggregationDimension = NULL) {
+                          aggregationFunctionName = NULL,
+                          aggregationUnit = NULL,
+                          aggregationDimension = NULL) {
       self$aggregationFunction <- aggregationFunction
       self$aggregationFunctionName <- aggregationFunctionName
       self$aggregationUnit <- aggregationUnit
@@ -36,7 +36,7 @@ AggregationInput <- R6::R6Class(
 predefinedPercentiles <- c(0, 1, 2.5, 5, 10, 15, 20, 25, 50, 75, 80, 85, 90, 95, 97.5, 99, 100)
 #' @title tlfStatFunctions
 #' @description
-#' Bank of predifined functions ready to use by Aggregation methods. Bank defined as Enum.
+#' Bank of predefined functions ready to use by Aggregation methods. Bank defined as Enum.
 #' To access the function from its name, use match.fun: e.g. testFun <- match.fun("mean-1.96sd")
 #' @include enum.R
 #' @export

diff --git a/R/aggregation-summary.R b/R/aggregation-summary.R
@@ -1,25 +1,25 @@
 #' @title AggregationSummary
 #' @description R6 class to split a data.frame data into subsets defined by unique combinations of elements
-#' in the columns \code{xColumnNames} and \code{groupingColumnNames}.
-#' Applies functions defined in \code{aggregationFunctionsVector} to column \code{yColumnNames.}
-#' Returns a list of data.frame, one data.frame for each function listed in \code{aggregationFunctionsVector}.
-#' Each data.frame in list element is named after the function's corresponding string in \code{aggregationFunctionNames}.
+#' in the columns `xColumnNames` and `groupingColumnNames`.
+#' Applies functions defined in `aggregationFunctionsVector` to column `yColumnNames.`
+#' Returns a list of data.frame, one data.frame for each function listed in `aggregationFunctionsVector`.
+#' Each data.frame in list element is named after the function's corresponding string in `aggregationFunctionNames`.
 #' The summary statistic column name in each data.frame is the same as the name of the data.frame in the returned list.
 #' @export
 AggregationSummary <- R6::R6Class(
   "AggregationSummary",
   public = list(
     #' @field data data.frame
     data = NULL,
-    #' @field metaData list of information on \code{data}
+    #' @field metaData list of information on `data`
     metaData = NULL,
     #' @field xColumnNames character names of grouping variables
     xColumnNames = NULL,
     #' @field groupingColumnNames character names of grouping variables
     groupingColumnNames = NULL,
     #' @field yColumnNames character names of dependent variables (that are grouped)
     yColumnNames = NULL,
-    #' @field aggregationInputsVector list of R6 class \code{AggregationInput} objects
+    #' @field aggregationInputsVector list of R6 class `AggregationInput` objects
     aggregationInputsVector = NULL,
     #' @field aggregationFunctionsVector list of functions to use for aggregation
     aggregationFunctionsVector = NULL,
@@ -31,31 +31,31 @@ AggregationSummary <- R6::R6Class(
     aggregationDimensionsVector = NULL,
     #' @field dfHelper data.frame of aggregated values
     dfHelper = NULL,
-    #' @field metaDataHelper list of information on \code{dfHelper}
+    #' @field metaDataHelper list of information on `dfHelper`
     metaDataHelper = NULL,
 
-    #' @description Create a new \code{AggregationSummary} object
+    #' @description Create a new `AggregationSummary` object
     #' @param data data.frame
-    #' @param metaData list of information on \code{data}
+    #' @param metaData list of information on `data`
     #' @param xColumnNames character names of grouping variables
     #' @param groupingColumnNames character names of grouping variables
     #' @param yColumnNames character names of dependent variables (that are grouped)
-    #' @param aggregationInputsVector list of R6 class \code{AggregationInput} objects
+    #' @param aggregationInputsVector list of R6 class `AggregationInput` objects
     #' @param aggregationFunctionsVector list of functions to use for aggregation
     #' @param aggregationFunctionNames vector of function names that will be used as variable name of the aggregation
     #' @param aggregationUnitsVector character vector of units of aggregation output
     #' @param aggregationDimensionsVector character vector of dimensions of aggregation output
-    #' @return A new \code{AggregationSummary} object
+    #' @return A new `AggregationSummary` object
     initialize = function(data,
-                              metaData = NULL,
-                              xColumnNames = NULL,
-                              groupingColumnNames = NULL,
-                              yColumnNames = NULL,
-                              aggregationInputsVector = NULL,
-                              aggregationFunctionsVector = NULL,
-                              aggregationFunctionNames = NULL,
-                              aggregationUnitsVector = NULL,
-                              aggregationDimensionsVector = NULL) {
+                          metaData = NULL,
+                          xColumnNames = NULL,
+                          groupingColumnNames = NULL,
+                          yColumnNames = NULL,
+                          aggregationInputsVector = NULL,
+                          aggregationFunctionsVector = NULL,
+                          aggregationFunctionNames = NULL,
+                          aggregationUnitsVector = NULL,
+                          aggregationDimensionsVector = NULL) {
       self$data <- data
       self$metaData <- metaData
       self$xColumnNames <- xColumnNames
@@ -71,8 +71,7 @@ AggregationSummary <- R6::R6Class(
           self$aggregationUnitsVector <- append(self$aggregationUnitsVector, aggregationInputValue$aggregationUnit)
           self$aggregationDimensionsVector <- append(self$aggregationDimensionsVector, aggregationInputValue$aggregationDimension)
         }
-      }
-      else {
+      } else {
         self$aggregationFunctionsVector <- c(aggregationFunctionsVector)
         self$aggregationFunctionNames <- aggregationFunctionNames
         self$aggregationUnitsVector <- aggregationUnitsVector
@@ -81,7 +80,7 @@ AggregationSummary <- R6::R6Class(
       self$generateAggregatedValues()
     },
 
-    #' @description Apply aggregation functions on \code{x}
+    #' @description Apply aggregation functions on `x`
     #' @param x numeric vector
     #' @return A list or vector of aggregated values
     applyAggregationFunctions = function(x) {
@@ -99,23 +98,23 @@ AggregationSummary <- R6::R6Class(
 
       xGroupingCols <- self$data[xGroupingColNames] # Extract grouping columns from dataframe and group them into a list called xGroupingCols
 
-      yValuesCol <- self$data[ self$yColumnNames ] # Extract column of values from dataframe
+      yValuesCol <- self$data[self$yColumnNames] # Extract column of values from dataframe
 
       aggSummaries <- aggregate(yValuesCol, xGroupingCols, function(x) {
         res <- self$applyAggregationFunctions(x)
         return(res)
       })
 
-      summaryMatrix <- matrix(aggSummaries[[ self$yColumnNames ]], ncol = length(self$aggregationFunctionsVector))
-      self$dfHelper <- aggSummaries[ xGroupingColNames ]
+      summaryMatrix <- matrix(aggSummaries[[self$yColumnNames]], ncol = length(self$aggregationFunctionsVector))
+      self$dfHelper <- aggSummaries[xGroupingColNames]
       self$metaDataHelper <- self$metaData[xGroupingColNames]
 
       for (n in seq(1, length(self$aggregationFunctionNames))) {
         dF <- data.frame(summaryMatrix[, n])
         colnames(dF)[1] <- self$aggregationFunctionNames[n]
         self$dfHelper <- cbind(self$dfHelper, dF)
 
-        self$metaDataHelper [[self$aggregationFunctionNames[n]]] <- list(unit = self$aggregationUnitsVector[n], dimension = self$aggregationDimensionsVector[n])
+        self$metaDataHelper[[self$aggregationFunctionNames[n]]] <- list(unit = self$aggregationUnitsVector[n], dimension = self$aggregationDimensionsVector[n])
       }
     }
   )