R/Plots.R

In matloff/qeML: Quick and Easy Machine Learning Tools

# misc. plots, especially for dimension reduction

plotClassesUMAP <- function(data,classVar) 
{
   checkPkgLoaded('uwot')
   umap <- NULL  # fake; actual def happens here:
   checkPkgLoaded('umap')

   if (is.character(classVar)) {  # name of a column in 'data'
      whichClass <- which(names(data) == classVar)
      x <- data[,-whichClass]
      classVar <- data[,whichClass]
   } else {
      x <- data
   }
   if (!is.factor(classVar)) classVar <- as.factor(classVar)
   if (!allNumeric(x)) x <- regtools::factorsToDummies(x)
   # ump <- uwot::umap(x)
   ump <- umap(x)
   plot(ump[,1:2],col=classVar,xlab='UMAP1',ylab='UMAP2')
}

# plotting residuals against predictors, two at a time

# qeOut: return object from the various qeML ftns; call must have had
# holdout non-NULL

plotPairedResids <- function(data,qeOut) 
{
   # require(autoimage)
   autopoints <- NULL  # fake; actual def happens here:
   checkPkgLoaded('autoimage')

   qo <- qeOut
   if (qo$classif) stop('not for classification problems')
   yName <- qo$yName
   yCol <- which(names(data) == yName)  
   predErrs <- data[qo$holdIdxs,yCol] - qo$holdoutPreds
   x <- data[,-yCol,drop=FALSE]
   xF <- which(sapply(x,is.factor))
   if (length(xF) > 0) x <- x[,-xF,drop=FALSE]
   x <- x[qo$holdIdxs,]
   namesX <- names(x)
   nX <- ncol(x)
   while (1) {
      ij <- sample(1:nX,2)
      i <- ij[1]; j <- ij[2]
      autoimage::autopoints(x[,i],x[,j],predErrs,xlab=namesX[i],ylab=namesX[j])
      ans <- readline('hit Enter for next plot, "q" for quit ')
      if (ans == 'q') break
   }
}

# in Utils.R
### # run R call from string
### evalr <- function(toexec) {
###    eval(parse(text=toexec),parent.frame())
### }

# extract args from ...

getDotsArgs <- defmacro(argName, expr=
   {
      v <- c(as.list(environment()), list(...))
      if (is.null(v[[argName]])) {
         stop(sprintf('%s argument missing',argName))
      } else {
         cmd <- sprintf('%s <<- v$%s',argName,argName)
         evalr(cmd)
      }
   }
)