+++ /dev/null
-#' @include z_runAlgorithm.R
-
-#' @title Get best expert index
-#'
-#' @description Return the weights corresponding to the best expert (...0,1,0...)
-#'
-#' @param r Output of \code{\link{runAlgorithm}}
-#'
-#' @export
-getBestExpert = function(r)
-{
- X = as.matrix(r$data[,names(r$data) %in% r$experts])
- Y = r$data[,"Measure"]
-
- bestIndex = which.min(colMeans(abs(X - Y)^2, na.rm=TRUE))
- res = rep(0.0, length(r$experts))
- res[bestIndex] = 1.0
- return (res)
-}
-
-#' @title Get best convex combination
-#'
-#' @description Return the weights p minimizing the quadratic error ||X*p-Y||^2 under convexity contraint.
-#'
-#' @param r Output of \code{\link{runAlgorithm}}
-#'
-#' @export
-getBestConvexCombination = function(r)
-{
- X = r$data[,r$experts]
- Y = as.double(r$data[,"Measure"])
- indices = getNoNAindices(X) & !is.na(Y)
- X = as.matrix(X[indices,])
- Y = Y[indices]
-
- K = length(r$experts)
- return (constrOptim(theta=rep(1.0/K,K),
- method="Nelder-Mead", #TODO: others not better... why?
- f=function(p){return(sum((X%*%p-Y)^2))},
- grad=NULL, #function(p){return(2.*t(X)%*%(X%*%p-Y))},
- ui=rbind(rep(1.,K),rep(-1.,K),diag(K)), ci=c(0.99999,-1.00001, rep(0.,K)),
- control=list(ndeps=1e-3,maxit=10000))$par)
-}
-
-#' @title Get best linear combination
-#'
-#' @description Return the weights u minimizing the quadratic error ||r$X*u-r$Y||^2
-#'
-#' @param r Output of \code{\link{runAlgorithm}}
-#'
-#' @export
-getBestLinearCombination = function(r)
-{
- X = r$data[,r$experts]
- Y = r$data[,"Measure"]
- indices = getNoNAindices(X) & !is.na(Y)
- X = as.matrix(X[indices,])
- Y = Y[indices]
-
- return (mpPsInv(X) %*% Y)
-}
-
-#' @title Get statistical indicators
-#'
-#' @description Return respectively the TS, FA, MA, RMSE, EV indicators in a list.
-#'
-#' @param r Output of \code{\link{runAlgorithm}}
-#' @param thresh Threshold to compute alerts indicators.
-#' @param station Name or index of the station to consider. Default: the first one
-#' @param noNA TRUE to show only errors associated with full lines (old behavior)
-#'
-#' @export
-getIndicators = function(r, thresh, station=1, noNA=TRUE)
-{
- if (is.character(station))
- station = match(station, r$stations)
-
- #TODO: duplicated block (same in plotCloud())
- XY = subset(r$data, subset = (Station == station), select = c(r$experts,"Measure","Prediction"))
- Y = XY[,"Measure"]
- hatY = XY[,"Prediction"]
- indices = !is.na(Y) & !is.na(hatY)
- if (noNA)
- {
- X = XY[,names(XY) %in% r$experts]
- indices = indices & getNoNAindices(X)
- }
- Y = Y[indices]
- hatY = hatY[indices]
-
- RMSE = round(sqrt(sum((Y - hatY)^2) / length(Y)),2)
- EV = round(1 - var(Y-hatY) / var(Y), 2)
- A = sum(hatY >= thresh & Y >= thresh, na.rm=TRUE) #right alarm
- B = sum(hatY >= thresh & Y < thresh, na.rm=TRUE) #false alarm
- C = sum(hatY < thresh & Y >= thresh, na.rm=TRUE) #missed alert
- TS = round(A/(A+B+C),2)
- FA = B/(A+B)
- MA = C/(A+C)
- return (list("TS"=TS, "FA"=FA, "MA"=MA, "RMSE"=RMSE, "EV"=EV))
-}