Drop unused function calcPlotPCAscores2

R/Plots.R

@@ -2408,103 +2408,6 @@ calcPlotPCAscores1 <- function(pcaObj, dataList, filterObj, pcaDimensionOne, pca
   }
 }
 
-#######################
-calcPlotPCAscores2 <- function(pcaObj, dataList, filterObj, pcaDimensionOne, pcaDimensionTwo, showScoresLabels, xInterval = NULL, yInterval = NULL){
-  #### changing this to 1
-  palette <- colorPaletteScores()
-  #dev.new(width=15,height=15)
-  if(filterObj$filterBySamples){
-    colorsForReplicates <- palette[unlist(lapply(X = filterObj$grouXXXps, FUN = function(x){ 
-      groupIdx <- dataList$groupIdxFromGroupName(x)
-      samples <- dataList$dataColumnsNameFunctionFromGroupName(x, sampleNamesToExclude = dataList$excludedSamples(dataList$groupSampleDataFrame))
-      samples <- intersect(samples, filterObj$sampleSet)
-      rep(x = groupIdx, times = length(samples))
-    }))]
-  } else {
-    colorsForReplicates <- palette[unlist(lapply(X = filterObj$grouXXXps, FUN = function(x){ 
-      groupIdx <- dataList$groupIdxFromGroupName(x)
-      rep(x = groupIdx, times = length(dataList$dataColumnsNameFunctionFromGroupName(x, sampleNamesToExclude = dataList$excludedSamples(dataList$groupSampleDataFrame))))
-    }))]
-  }
-
-  ## data
-  dataDimOne <- pcaObj$scores[, pcaDimensionOne]
-  dataDimTwo <- pcaObj$scores[, pcaDimensionTwo]
-
-  ## performance
-  resultObj <- getPcaPerformanceIndicator(pcaObj = pcaObj, isScores = TRUE)
-  xAxisLabel <- resultObj$xAxisLabel
-  yAxisLabel <- resultObj$yAxisLabel
-
-  ## xlim / ylim
-  xMin <- min(dataDimOne)
-  xMax <- max(dataDimOne)
-  yMin <- min(dataDimTwo)
-  yMax <- max(dataDimTwo)
-
-  if(any(is.na(c(xMin, xMax, yMin, yMax)))){
-    xMin <- -1
-    xMax <- 1
-    yMin <- -1
-    yMax <- 1
-    #### I am changing this 
-    # xMin <- -0.05
-    # xMax <- -0.05
-    # yMin <- -0.5
-    # yMax <-  -0.5
-    ##############
-
-  }
-
-  if(is.null(xInterval))
-    xInterval <- c(xMin, xMax)
-  if(is.null(yInterval))
-    yInterval <- c(yMin, yMax)
-  #### this is the original one 
-  #par(mar=c(3 + 0.35, 3, 2, 1), mgp = c(2, 1, 0))  ## c(bottom, left, top, right)
-  par(mar=c(3+0.0125, 3+0.125, 2, 1), mgp = c(2, 1, 0),par(xpd=FALSE))  ## c(bottom, left, top, right)
-  #par(mar=c(3,0,2,1), mgp = c(2, 1, 0))
-  plot(
-    x = dataDimOne, y = dataDimTwo, 
-    xlim = xInterval, ylim = yInterval, 
-    xlab = xAxisLabel, ylab = yAxisLabel, main = "Scores", 
-    #### this is my blind test changing from 19 to 19:22
-    #ntemp<-length(filterObj$grouXXXps),
-    #ntemp1<-sum(ntemp,1),
-    ### I am testing the filterObj$grouXXXps... This is fine .. will test the 
-    col = colorsForReplicates, pch=1:length(filterObj$grouXXXps),lty=1,lwd=2,cex=1.
-    ### checking the colorsForReplicates
-
-  )
-
-  ## axis
-  xInt <- xMax - xMin
-  yInt <- yMax - yMin
-  xl <- xMin - xInt
-  xr <- xMax + xInt
-  yl <- yMin - yInt
-  yr <- yMax + yInt
-  ###checking what happens if i comment this...this is original 
-  #segments(x0 = xl, x1 = xr, y0 = 0, y1 = 0, col = "black", lwd = 1)
-  #segments(x0 = 0, x1 = 0, y0 = yl, y1 = yr, col = "black", lwd = 1)
-  ##############
-
-  #############
-
-  if(showScoresLabels){
-
-    if(filterObj$filterBySamples){
-      labels <- dataList$dataColumnsNameFunctionFromGroupNames(filterObj$grouXXXps, sampleNamesToExclude = dataList$excludedSamples(dataList$groupSampleDataFrame))
-      labels <- intersect(labels, filterObj$sampleSet)
-    } else {
-      labels <- dataList$dataColumnsNameFunctionFromGroupNames(filterObj$grouXXXps, sampleNamesToExclude = dataList$excludedSamples(dataList$groupSampleDataFrame))
-    }
-    graphics::text(x = dataDimOne, y = dataDimTwo, labels = labels, pos = 4)
-  }
-}
-
-########################################### adding this new line 
-
 calcPlotPCAloadings <- function(
   pcaObj, dataList, filter, 
   pcaDimensionOne, pcaDimensionTwo,